Signal recognition and parameter estimation of BPSK-LFM combined modulation

Science.gov (United States)

Long, Chao; Zhang, Lin; Liu, Yu

2015-07-01

Intra-pulse analysis plays an important role in electronic warfare. Intra-pulse feature abstraction focuses on primary parameters such as instantaneous frequency, modulation, and symbol rate. In this paper, automatic modulation recognition and feature extraction for combined BPSK-LFM modulation signals based on decision theoretic approach is studied. The simulation results show good recognition effect and high estimation precision, and the system is easy to be realized.

Functional characterization of recombinant chloroplast signal recognition particle

NARCIS (Netherlands)

Groves, M R; Mant, A; Kuhn, A; Koch, J; Dübel, S; Robinson, C; Sinning, I

2001-01-01

The signal recognition particle (SRP) is a ubiquitous system for the targeting of membrane and secreted proteins. The chloroplast SRP (cpSRP) is unique among SRPs in that it possesses no RNA and is functional in post-translational as well as co-translational targeting. We have expressed and purified

An Online Full-Body Motion Recognition Method Using Sparse and Deficient Signal Sequences

Directory of Open Access Journals (Sweden)

Chengyu Guo

2014-01-01

Full Text Available This paper presents a method to recognize continuous full-body human motion online by using sparse, low-cost sensors. The only input signals needed are linear accelerations without any rotation information, which are provided by four Wiimote sensors attached to the four human limbs. Based on the fused hidden Markov model (FHMM and autoregressive process, a predictive fusion model (PFM is put forward, which considers the different influences of the upper and lower limbs, establishes HMM for each part, and fuses them using a probabilistic fusion model. Then an autoregressive process is introduced in HMM to predict the gesture, which enables the model to deal with incomplete signal data. In order to reduce the number of alternatives in the online recognition process, a graph model is built that rejects parts of motion types based on the graph structure and previous recognition results. Finally, an online signal segmentation method based on semantics information and PFM is presented to finish the efficient recognition task. The results indicate that the method is robust with a high recognition rate of sparse and deficient signals and can be used in various interactive applications.

Physical signals for protein–DNA recognition

International Nuclear Information System (INIS)

Cao, Xiao-Qin; Zeng, Jia; Yan, Hong

2009-01-01

This paper discovers consensus physical signals around eukaryotic splice sites, transcription start sites, and replication origin start and end sites on a genome-wide scale based on their DNA flexibility profiles calculated by three different flexibility models. These salient physical signals are localized highly rigid and flexible DNAs, which may play important roles in protein–DNA recognition by the sliding search mechanism. The found physical signals lead us to a detailed hypothetical view of the search process in which a DNA-binding protein first finds a genomic region close to the target site from an arbitrary starting location by three-dimensional (3D) hopping and intersegment transfer mechanisms for long distances, and subsequently uses the one-dimensional (1D) sliding mechanism facilitated by the localized highly rigid DNAs to accurately locate the target flexible binding site within 30 bp (base pair) short distances. Guided by these physical signals, DNA-binding proteins rapidly search the entire genome to recognize a specific target site from the 3D to 1D pathway. Our findings also show that current promoter prediction programs (PPPs) based on DNA physical properties may suffer from lots of false positives because other functional sites such as splice sites and replication origins have similar physical signals as promoters do

Assessment of Homomorphic Analysis for Human Activity Recognition from Acceleration Signals.

Science.gov (United States)

Vanrell, Sebastian Rodrigo; Milone, Diego Humberto; Rufiner, Hugo Leonardo

2017-07-03

Unobtrusive activity monitoring can provide valuable information for medical and sports applications. In recent years, human activity recognition has moved to wearable sensors to deal with unconstrained scenarios. Accelerometers are the preferred sensors due to their simplicity and availability. Previous studies have examined several \\azul{classic} techniques for extracting features from acceleration signals, including time-domain, time-frequency, frequency-domain, and other heuristic features. Spectral and temporal features are the preferred ones and they are generally computed from acceleration components, leaving the acceleration magnitude potential unexplored. In this study, based on homomorphic analysis, a new type of feature extraction stage is proposed in order to exploit discriminative activity information present in acceleration signals. Homomorphic analysis can isolate the information about whole body dynamics and translate it into a compact representation, called cepstral coefficients. Experiments have explored several configurations of the proposed features, including size of representation, signals to be used, and fusion with other features. Cepstral features computed from acceleration magnitude obtained one of the highest recognition rates. In addition, a beneficial contribution was found when time-domain and moving pace information was included in the feature vector. Overall, the proposed system achieved a recognition rate of 91.21% on the publicly available SCUT-NAA dataset. To the best of our knowledge, this is the highest recognition rate on this dataset.

A two-step recognition of signal sequences determines the translocation efficiency of proteins.

Science.gov (United States)

Belin, D; Bost, S; Vassalli, J D; Strub, K

1996-02-01

The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated derivatives thereof, ovalbumin and preprolactin) were found to have the differential activities in the two events. For example, the mPAI-2 signal sequence first binds SRP with moderate efficiency and secondly promotes the vectorial transport of only a fraction of the SRP-bound nascent chains. Our results provide evidence that the translocation efficiency of proteins can be controlled by the recognition of their signal sequences at two steps: during SRP-mediated targeting and during formation of a committed translocation complex. This second recognition may occur at several time points during the insertion/translocation step. In conclusion, signal sequences have a more complex structure than previously anticipated, allowing for multiple and independent interactions with the translocation machinery.

CNNs for sinusoidal signal recognition in hearing rehabilitation

Science.gov (United States)

Carnimeo, Leonarda; Giaquinto, Antonio

2003-04-01

In this paper, a contribution is given to provide a tool to the recognition of sinusoidal signals with a particular reference to the field of pediatric hearing rehabilitation. To this purpose, a synthesis technique previously developed by the authors' is used to design a Cellular Neural Network for an Associative Memory able to compare submitted discrete-time sinusoidal signals with memorized ones. A robustness analysis of the synthesized associative memory is also developed both for noisy inputs and for parameter variations. Simulation results are then reported to illustrate the performances of the designed network.

S1PR3 Signaling Drives Bacterial Killing and Is Required for Survival in Bacterial Sepsis.

Science.gov (United States)

Hou, JinChao; Chen, QiXing; Wu, XiaoLiang; Zhao, DongYan; Reuveni, Hadas; Licht, Tamar; Xu, MengLong; Hu, Hu; Hoeft, Andreas; Ben-Sasson, Shmuel A; Shu, Qiang; Fang, XiangMing

2017-12-15

Efficient elimination of pathogenic bacteria is a critical determinant in the outcome of sepsis. Sphingosine-1-phosphate receptor 3 (S1PR3) mediates multiple aspects of the inflammatory response during sepsis, but whether S1PR3 signaling is necessary for eliminating the invading pathogens remains unknown. To investigate the role of S1PR3 in antibacterial immunity during sepsis. Loss- and gain-of-function experiments were performed using cell and murine models. S1PR3 levels were determined in patients with sepsis and healthy volunteers. S1PR3 protein levels were up-regulated in macrophages upon bacterial stimulation. S1pr3 -/- mice showed increased mortality and increased bacterial burden in multiple models of sepsis. The transfer of wild-type bone marrow-derived macrophages rescued S1pr3 -/- mice from lethal sepsis. S1PR3-overexpressing macrophages further ameliorated the mortality rate of sepsis. Loss of S1PR3 led to markedly decreased bacterial killing in macrophages. Enhancing endogenous S1PR3 activity using a peptide agonist potentiated the macrophage bactericidal function and improved survival rates in multiple models of sepsis. Mechanically, the reactive oxygen species levels were decreased and phagosome maturation was delayed in S1pr3 -/- macrophages due to impaired recruitment of vacuolar protein-sorting 34 to the phagosomes. In addition, S1RP3 expression levels were elevated in monocytes from patients with sepsis. Higher levels of monocytic S1PR3 were associated with efficient intracellular bactericidal activity, better immune status, and preferable outcomes. S1PR3 signaling drives bacterial killing and is essential for survival in bacterial sepsis. Interventions targeting S1PR3 signaling could have translational implications for manipulating the innate immune response to combat pathogens.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

Science.gov (United States)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Development of precursors recognition methods in vector signals

Science.gov (United States)

Kapralov, V. G.; Elagin, V. V.; Kaveeva, E. G.; Stankevich, L. A.; Dremin, M. M.; Krylov, S. V.; Borovov, A. E.; Harfush, H. A.; Sedov, K. S.

2017-10-01

Precursor recognition methods in vector signals of plasma diagnostics are presented. Their requirements and possible options for their development are considered. In particular, the variants of using symbolic regression for building a plasma disruption prediction system are discussed. The initial data preparation using correlation analysis and symbolic regression is discussed. Special attention is paid to the possibility of using algorithms in real time.

Pseudomonas Evades Immune Recognition of Flagellin in Both Mammals and Plants

Science.gov (United States)

Bardoel, Bart W.; van der Ent, Sjoerd; Pel, Michiel J. C.; Tommassen, Jan; Pieterse, Corné M. J.; van Kessel, Kok P. M.; van Strijp, Jos A. G.

2011-01-01

The building blocks of bacterial flagella, flagellin monomers, are potent stimulators of host innate immune systems. Recognition of flagellin monomers occurs by flagellin-specific pattern-recognition receptors, such as Toll-like receptor 5 (TLR5) in mammals and flagellin-sensitive 2 (FLS2) in plants. Activation of these immune systems via flagellin leads eventually to elimination of the bacterium from the host. In order to prevent immune activation and thus favor survival in the host, bacteria secrete many proteins that hamper such recognition. In our search for Toll like receptor (TLR) antagonists, we screened bacterial supernatants and identified alkaline protease (AprA) of Pseudomonas aeruginosa as a TLR5 signaling inhibitor as evidenced by a marked reduction in IL-8 production and NF-κB activation. AprA effectively degrades the TLR5 ligand monomeric flagellin, while polymeric flagellin (involved in bacterial motility) and TLR5 itself resist degradation. The natural occurring alkaline protease inhibitor AprI of P. aeruginosa blocked flagellin degradation by AprA. P. aeruginosa aprA mutants induced an over 100-fold enhanced activation of TLR5 signaling, because they fail to degrade excess monomeric flagellin in their environment. Interestingly, AprA also prevents flagellin-mediated immune responses (such as growth inhibition and callose deposition) in Arabidopsis thaliana plants. This was due to decreased activation of the receptor FLS2 and clearly demonstrated by delayed stomatal closure with live bacteria in plants. Thus, by degrading the ligand for TLR5 and FLS2, P. aeruginosa escapes recognition by the innate immune systems of both mammals and plants. PMID:21901099

Neural Network Based Recognition of Signal Patterns in Application to Automatic Testing of Rails

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Tomasz Ciszewski

2006-01-01

Full Text Available The paper describes the application of neural network for recognition of signal patterns in measuring data gathered by the railroad ultrasound testing car. Digital conversion of the measuring signal allows to store and process large quantities of data. The elaboration of smart, effective and automatic procedures recognizing the obtained patterns on the basisof measured signal amplitude has been presented. The test shows only two classes of pattern recognition. In authors’ opinion if we deliver big enough quantity of training data, presented method is applicable to a system that recognizes many classes.

Pseudomonas evades immune recognition of flagellin in both mammals and plants.

Directory of Open Access Journals (Sweden)

Bart W Bardoel

2011-08-01

Full Text Available The building blocks of bacterial flagella, flagellin monomers, are potent stimulators of host innate immune systems. Recognition of flagellin monomers occurs by flagellin-specific pattern-recognition receptors, such as Toll-like receptor 5 (TLR5 in mammals and flagellin-sensitive 2 (FLS2 in plants. Activation of these immune systems via flagellin leads eventually to elimination of the bacterium from the host. In order to prevent immune activation and thus favor survival in the host, bacteria secrete many proteins that hamper such recognition. In our search for Toll like receptor (TLR antagonists, we screened bacterial supernatants and identified alkaline protease (AprA of Pseudomonas aeruginosa as a TLR5 signaling inhibitor as evidenced by a marked reduction in IL-8 production and NF-κB activation. AprA effectively degrades the TLR5 ligand monomeric flagellin, while polymeric flagellin (involved in bacterial motility and TLR5 itself resist degradation. The natural occurring alkaline protease inhibitor AprI of P. aeruginosa blocked flagellin degradation by AprA. P. aeruginosa aprA mutants induced an over 100-fold enhanced activation of TLR5 signaling, because they fail to degrade excess monomeric flagellin in their environment. Interestingly, AprA also prevents flagellin-mediated immune responses (such as growth inhibition and callose deposition in Arabidopsis thaliana plants. This was due to decreased activation of the receptor FLS2 and clearly demonstrated by delayed stomatal closure with live bacteria in plants. Thus, by degrading the ligand for TLR5 and FLS2, P. aeruginosa escapes recognition by the innate immune systems of both mammals and plants.

Communicative Signals Promote Object Recognition Memory and Modulate the Right Posterior STS.

Science.gov (United States)

Redcay, Elizabeth; Ludlum, Ruth S; Velnoskey, Kayla R; Kanwal, Simren

2016-01-01

Detection of communicative signals is thought to facilitate knowledge acquisition early in life, but less is known about the role these signals play in adult learning or about the brain systems supporting sensitivity to communicative intent. The current study examined how ostensive gaze cues and communicative actions affect adult recognition memory and modulate neural activity as measured by fMRI. For both the behavioral and fMRI experiments, participants viewed a series of videos of an actress acting on one of two objects in front of her. Communicative context in the videos was manipulated in a 2 × 2 design in which the actress either had direct gaze (Gaze) or wore a visor (NoGaze) and either pointed at (Point) or reached for (Reach) one of the objects (target) in front of her. Participants then completed a recognition memory task with old (target and nontarget) objects and novel objects. Recognition memory for target objects in the Gaze conditions was greater than NoGaze, but no effects of gesture type were seen. Similarly, the fMRI video-viewing task revealed a significant effect of Gaze within right posterior STS (pSTS), but no significant effects of Gesture. Furthermore, pSTS sensitivity to Gaze conditions was related to greater memory for objects viewed in Gaze, as compared with NoGaze, conditions. Taken together, these results demonstrate that the ostensive, communicative signal of direct gaze preceding an object-directed action enhances recognition memory for attended items and modulates the pSTS response to object-directed actions. Thus, establishment of a communicative context through ostensive signals remains an important component of learning and memory into adulthood, and the pSTS may play a role in facilitating this type of social learning.

Bacterial Biofilm Control by Perturbation of Bacterial Signaling Processes

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Tim Holm Jakobsen

2017-09-01

Full Text Available The development of effective strategies to combat biofilm infections by means of either mechanical or chemical approaches could dramatically change today’s treatment procedures for the benefit of thousands of patients. Remarkably, considering the increased focus on biofilms in general, there has still not been invented and/or developed any simple, efficient and reliable methods with which to “chemically” eradicate biofilm infections. This underlines the resilience of infective agents present as biofilms and it further emphasizes the insufficiency of today’s approaches used to combat chronic infections. A potential method for biofilm dismantling is chemical interception of regulatory processes that are specifically involved in the biofilm mode of life. In particular, bacterial cell to cell signaling called “Quorum Sensing” together with intracellular signaling by bis-(3′-5′-cyclic-dimeric guanosine monophosphate (cyclic-di-GMP have gained a lot of attention over the last two decades. More recently, regulatory processes governed by two component regulatory systems and small non-coding RNAs have been increasingly investigated. Here, we review novel findings and potentials of using small molecules to target and modulate these regulatory processes in the bacterium Pseudomonas aeruginosa to decrease its pathogenic potential.

Contribution to automatic speech recognition. Analysis of the direct acoustical signal. Recognition of isolated words and phoneme identification

International Nuclear Information System (INIS)

Dupeyrat, Benoit

1981-01-01

This report deals with the acoustical-phonetic step of the automatic recognition of the speech. The parameters used are the extrema of the acoustical signal (coded in amplitude and duration). This coding method, the properties of which are described, is simple and well adapted to a digital processing. The quality and the intelligibility of the coded signal after reconstruction are particularly satisfactory. An experiment for the automatic recognition of isolated words has been carried using this coding system. We have designed a filtering algorithm operating on the parameters of the coding. Thus the characteristics of the formants can be derived under certain conditions which are discussed. Using these characteristics the identification of a large part of the phonemes for a given speaker was achieved. Carrying on the studies has required the development of a particular methodology of real time processing which allowed immediate evaluation of the improvement of the programs. Such processing on temporal coding of the acoustical signal is extremely powerful and could represent, used in connection with other methods an efficient tool for the automatic processing of the speech.(author) [fr

Intracellular Zn(2+) signaling in the dentate gyrus is required for object recognition memory.

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Takeda, Atsushi; Tamano, Haruna; Ogawa, Taisuke; Takada, Shunsuke; Nakamura, Masatoshi; Fujii, Hiroaki; Ando, Masaki

2014-11-01

The role of perforant pathway-dentate granule cell synapses in cognitive behavior was examined focusing on synaptic Zn(2+) signaling in the dentate gyrus. Object recognition memory was transiently impaired when extracellular Zn(2+) levels were decreased by injection of clioquinol and N,N,N',N'-tetrakis-(2-pyridylmethyl) ethylendediamine. To pursue the effect of the loss and/or blockade of Zn(2+) signaling in dentate granule cells, ZnAF-2DA (100 pmol, 0.1 mM/1 µl), an intracellular Zn(2+) chelator, was locally injected into the dentate molecular layer of rats. ZnAF-2DA injection, which was estimated to chelate intracellular Zn(2+) signaling only in the dentate gyrus, affected object recognition memory 1 h after training without affecting intracellular Ca(2+) signaling in the dentate molecular layer. In vivo dentate gyrus long-term potentiation (LTP) was affected under the local perfusion of the recording region (the dentate granule cell layer) with 0.1 mM ZnAF-2DA, but not with 1-10 mM CaEDTA, an extracellular Zn(2+) chelator, suggesting that the blockade of intracellular Zn(2+) signaling in dentate granule cells affects dentate gyrus LTP. The present study demonstrates that intracellular Zn(2+) signaling in the dentate gyrus is required for object recognition memory, probably via dentate gyrus LTP expression. Copyright © 2014 Wiley Periodicals, Inc.

Dual-Process Theory and Signal-Detection Theory of Recognition Memory

Science.gov (United States)

Wixted, John T.

2007-01-01

Two influential models of recognition memory, the unequal-variance signal-detection model and a dual-process threshold/detection model, accurately describe the receiver operating characteristic, but only the latter model can provide estimates of recollection and familiarity. Such estimates often accord with those provided by the remember-know…

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.

Nasal chemosensory cells use bitter taste signaling to detect irritants and bacterial signals.

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Tizzano, Marco; Gulbransen, Brian D; Vandenbeuch, Aurelie; Clapp, Tod R; Herman, Jake P; Sibhatu, Hiruy M; Churchill, Mair E A; Silver, Wayne L; Kinnamon, Sue C; Finger, Thomas E

2010-02-16

The upper respiratory tract is continually assaulted with harmful dusts and xenobiotics carried on the incoming airstream. Detection of such irritants by the trigeminal nerve evokes protective reflexes, including sneezing, apnea, and local neurogenic inflammation of the mucosa. Although free intra-epithelial nerve endings can detect certain lipophilic irritants (e.g., mints, ammonia), the epithelium also houses a population of trigeminally innervated solitary chemosensory cells (SCCs) that express T2R bitter taste receptors along with their downstream signaling components. These SCCs have been postulated to enhance the chemoresponsive capabilities of the trigeminal irritant-detection system. Here we show that transduction by the intranasal solitary chemosensory cells is necessary to evoke trigeminally mediated reflex reactions to some irritants including acyl-homoserine lactone bacterial quorum-sensing molecules, which activate the downstream signaling effectors associated with bitter taste transduction. Isolated nasal chemosensory cells respond to the classic bitter ligand denatonium as well as to the bacterial signals by increasing intracellular Ca(2+). Furthermore, these same substances evoke changes in respiration indicative of trigeminal activation. Genetic ablation of either G alpha-gustducin or TrpM5, essential elements of the T2R transduction cascade, eliminates the trigeminal response. Because acyl-homoserine lactones serve as quorum-sensing molecules for gram-negative pathogenic bacteria, detection of these substances by airway chemoreceptors offers a means by which the airway epithelium may trigger an epithelial inflammatory response before the bacteria reach population densities capable of forming destructive biofilms.

The time course of individual face recognition: A pattern analysis of ERP signals.

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Nemrodov, Dan; Niemeier, Matthias; Mok, Jenkin Ngo Yin; Nestor, Adrian

2016-05-15

An extensive body of work documents the time course of neural face processing in the human visual cortex. However, the majority of this work has focused on specific temporal landmarks, such as N170 and N250 components, derived through univariate analyses of EEG data. Here, we take on a broader evaluation of ERP signals related to individual face recognition as we attempt to move beyond the leading theoretical and methodological framework through the application of pattern analysis to ERP data. Specifically, we investigate the spatiotemporal profile of identity recognition across variation in emotional expression. To this end, we apply pattern classification to ERP signals both in time, for any single electrode, and in space, across multiple electrodes. Our results confirm the significance of traditional ERP components in face processing. At the same time though, they support the idea that the temporal profile of face recognition is incompletely described by such components. First, we show that signals associated with different facial identities can be discriminated from each other outside the scope of these components, as early as 70ms following stimulus presentation. Next, electrodes associated with traditional ERP components as well as, critically, those not associated with such components are shown to contribute information to stimulus discriminability. And last, the levels of ERP-based pattern discrimination are found to correlate with recognition accuracy across subjects confirming the relevance of these methods for bridging brain and behavior data. Altogether, the current results shed new light on the fine-grained time course of neural face processing and showcase the value of novel methods for pattern analysis to investigating fundamental aspects of visual recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Blockade of intracellular Zn2+ signaling in the dentate gyrus erases recognition memory via impairment of maintained LTP.

Science.gov (United States)

Tamano, Haruna; Minamino, Tatsuya; Fujii, Hiroaki; Takada, Shunsuke; Nakamura, Masatoshi; Ando, Masaki; Takeda, Atsushi

2015-08-01

There is no evidence on the precise role of synaptic Zn2+ signaling on the retention and recall of recognition memory. On the basis of the findings that intracellular Zn2+ signaling in the dentate gyrus is required for object recognition, short-term memory, the present study deals with the effect of spatiotemporally blocking Zn2+ signaling in the dentate gyrus after LTP induction and learning. Three-day-maintained LTP was impaired 1 day after injection of clioquinol into the dentate gyrus, which transiently reduced intracellular Zn2+ signaling in the dentate gyrus. The irreversible impairment was rescued not only by co-injection of ZnCl2 , which ameliorated the loss of Zn2+ signaling, but also by pre-injection of Jasplakinolide, a stabilizer of F-actin, prior to clioquinol injection. Simultaneously, 3-day-old space recognition memory was impaired 1 day after injection of clioquinol into the dentate gyrus, but not by pre-injection of Jasplakinolide. Jasplakinolide also rescued both impairments of 3-day-maintained LTP and 3-day-old memory after injection of ZnAF-2DA into the dentate gyrus, which blocked intracellular Zn2+ signaling in the dentate gyrus. The present paper indicates that the blockade and/or loss of intracellular Zn2+ signaling in the dentate gyrus coincidently impair maintained LTP and recognition memory. The mechanism maintaining LTP via intracellular Zn2+ signaling in dentate granule cells, which may be involved in the formation of F-actin, may retain space recognition memory. © 2015 Wiley Periodicals, Inc.

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

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals

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Jiaduo Zhao

2016-01-01

Full Text Available In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector’s false alarms.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

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Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

JAK kinases are required for the bacterial RNA and poly I:C induced tyrosine phosphorylation of PKR

Science.gov (United States)

Bleiblo, Farag; Michael, Paul; Brabant, Danielle; Ramana, Chilakamarti V; Tai, TC; Saleh, Mazen; Parrillo, Joseph E; Kumar, Anand; Kumar, Aseem

2013-01-01

Discriminating the molecular patterns associated with RNA is central to innate immunity. The protein kinase PKR is a cytosolic sensor involved in the recognition of viral dsRNA and triggering interferon-induced signaling. Here, we identified bacterial RNA as a novel distinct pattern recognized by PKR. We show that the tyrosine phosphorylation of PKR induced by either bacterial RNA or poly I:C is impaired in mutant cells lacking TYK2, JAK1, or JAK2 kinases. PKR was found to be a direct substrate for the activated JAKs. Our results indicated that the double-stranded structures of bacterial RNA are required to fully activate PKR. These results suggest that bacterial RNA signaling is analogous in some respects to that of viral RNA and interferons and may have implications in bacterial immunity. PMID:23236554

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

Science.gov (United States)

Zhang, Y; Liu, A; Yu, K

1999-06-01

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

Cross-talk and information transfer in mammalian and bacterial signaling.

Directory of Open Access Journals (Sweden)

Samanthe M Lyons

Full Text Available In mammalian and bacterial cells simple phosphorylation circuits play an important role in signaling. Bacteria have hundreds of two-component signaling systems that involve phosphotransfer between a receptor and a response regulator. In mammalian cells a similar pathway is the TGF-beta pathway, where extracellular TGF-beta ligands activate cell surface receptors that phosphorylate Smad proteins, which in turn activate many genes. In TGF-beta signaling the multiplicity of ligands begs the question as to whether cells can distinguish signals coming from different ligands, but transduced through a small set of Smads. Here we use information theory with stochastic simulations of networks to address this question. We find that when signals are transduced through only one Smad, the cell cannot distinguish between different levels of the external ligands. Increasing the number of Smads from one to two significantly improves information transmission as well as the ability to discriminate between ligands. Surprisingly, both total information transmitted and the capacity to discriminate between ligands are quite insensitive to high levels of cross-talk between the two Smads. Robustness against cross-talk requires that the average amplitude of the signals are large. We find that smaller systems, as exemplified by some two-component systems in bacteria, are significantly much less robust against cross-talk. For such system sizes phosphotransfer is also less robust against cross-talk than phosphorylation. This suggests that mammalian signal transduction can tolerate a high amount of cross-talk without degrading information content. This may have played a role in the evolution of new functionalities from small mutations in signaling pathways, allowed for the development of cross-regulation and led to increased overall robustness due to redundancy in signaling pathways. On the other hand the lack of cross-regulation observed in many bacterial two

Bacterial signaling ecology and potential applications during aquatic biofilm construction.

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Vega, Leticia M; Alvarez, Pedro J; McLean, Robert J C

2014-07-01

In their natural environment, bacteria and other microorganisms typically grow as surface-adherent biofilm communities. Cell signal processes, including quorum signaling, are now recognized as being intimately involved in the development and function of biofilms. In contrast to their planktonic (unattached) counterparts, bacteria within biofilms are notoriously resistant to many traditional antimicrobial agents and so represent a major challenge in industry and medicine. Although biofilms impact many human activities, they actually represent an ancient mode of bacterial growth as shown in the fossil record. Consequently, many aquatic organisms have evolved strategies involving signal manipulation to control or co-exist with biofilms. Here, we review the chemical ecology of biofilms and propose mechanisms whereby signal manipulation can be used to promote or control biofilms.

Analysis of physiological signals for recognition of boredom, pain, and surprise emotions.

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Jang, Eun-Hye; Park, Byoung-Jun; Park, Mi-Sook; Kim, Sang-Hyeob; Sohn, Jin-Hun

2015-06-18

The aim of the study was to examine the differences of boredom, pain, and surprise. In addition to that, it was conducted to propose approaches for emotion recognition based on physiological signals. Three emotions, boredom, pain, and surprise, are induced through the presentation of emotional stimuli and electrocardiography (ECG), electrodermal activity (EDA), skin temperature (SKT), and photoplethysmography (PPG) as physiological signals are measured to collect a dataset from 217 participants when experiencing the emotions. Twenty-seven physiological features are extracted from the signals to classify the three emotions. The discriminant function analysis (DFA) as a statistical method, and five machine learning algorithms (linear discriminant analysis (LDA), classification and regression trees (CART), self-organizing map (SOM), Naïve Bayes algorithm, and support vector machine (SVM)) are used for classifying the emotions. The result shows that the difference of physiological responses among emotions is significant in heart rate (HR), skin conductance level (SCL), skin conductance response (SCR), mean skin temperature (meanSKT), blood volume pulse (BVP), and pulse transit time (PTT), and the highest recognition accuracy of 84.7% is obtained by using DFA. This study demonstrates the differences of boredom, pain, and surprise and the best emotion recognizer for the classification of the three emotions by using physiological signals.

A two-step recognition of signal sequences determines the translocation efficiency of proteins.

OpenAIRE

Belin, D; Bost, S; Vassalli, J D; Strub, K

1996-01-01

The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated...

Application of an automatic pattern recognition for aleatory signals for the surveillance of nuclear reactor and rotating machinery

International Nuclear Information System (INIS)

Nascimento, J.A. do.

1982-02-01

An automatic pattern recognition program PSDREC, developed for the surveillance of nuclear reactor and rotating machinery is described and the relevant theory is outlined. Pattern recognition analysis of noise signals is a powerful technique for assessing 'system normality' in dynamic systems. This program, with applies 8 statistical tests to calculated power spectral density (PSD) distribution, was earlier installed in a PDP-11/45 computer at IPEN. To analyse recorded signals from three systems, namely an operational BWR power reactor (neutron signals), a water pump and a diesel engine (vibration signals) this technique was used. Results of the tests are considered satisfactory. (Author) [pt

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain.

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Zhuang, Ning; Zeng, Ying; Tong, Li; Zhang, Chi; Zhang, Hanming; Yan, Bin

2017-01-01

This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy. The performance of the proposed method is verified on a publicly available emotional database. The results show that the three features are effective for emotion recognition. The role of each IMF is inquired and we find that high frequency component IMF1 has significant effect on different emotional states detection. The informative electrodes based on EMD strategy are analyzed. In addition, the classification accuracy of the proposed method is compared with several classical techniques, including fractal dimension (FD), sample entropy, differential entropy, and discrete wavelet transform (DWT). Experiment results on DEAP datasets demonstrate that our method can improve emotion recognition performance.

Linearmycins Activate a Two-Component Signaling System Involved in Bacterial Competition and Biofilm Morphology

Science.gov (United States)

2017-01-01

ABSTRACT Bacteria use two-component signaling systems to adapt and respond to their competitors and changing environments. For instance, competitor bacteria may produce antibiotics and other bioactive metabolites and sequester nutrients. To survive, some species of bacteria escape competition through antibiotic production, biofilm formation, or motility. Specialized metabolite production and biofilm formation are relatively well understood for bacterial species in isolation. How bacteria control these functions when competitors are present is not well studied. To address fundamental questions relating to the competitive mechanisms of different species, we have developed a model system using two species of soil bacteria, Bacillus subtilis and Streptomyces sp. strain Mg1. Using this model, we previously found that linearmycins produced by Streptomyces sp. strain Mg1 cause lysis of B. subtilis cells and degradation of colony matrix. We identified strains of B. subtilis with mutations in the two-component signaling system yfiJK operon that confer dual phenotypes of specific linearmycin resistance and biofilm morphology. We determined that expression of the ATP-binding cassette (ABC) transporter yfiLMN operon, particularly yfiM and yfiN, is necessary for biofilm morphology. Using transposon mutagenesis, we identified genes that are required for YfiLMN-mediated biofilm morphology, including several chaperones. Using transcriptional fusions, we found that YfiJ signaling is activated by linearmycins and other polyene metabolites. Finally, using a truncated YfiJ, we show that YfiJ requires its transmembrane domain to activate downstream signaling. Taken together, these results suggest coordinated dual antibiotic resistance and biofilm morphology by a single multifunctional ABC transporter promotes competitive fitness of B. subtilis. IMPORTANCE DNA sequencing approaches have revealed hitherto unexplored diversity of bacterial species in a wide variety of environments that

Molecular Pathways for Immune Recognition of Preproinsulin Signal Peptide in Type 1 Diabetes.

Science.gov (United States)

Kronenberg-Versteeg, Deborah; Eichmann, Martin; Russell, Mark A; de Ru, Arnoud; Hehn, Beate; Yusuf, Norkhairin; van Veelen, Peter A; Richardson, Sarah J; Morgan, Noel G; Lemberg, Marius K; Peakman, Mark

2018-04-01

The signal peptide region of preproinsulin (PPI) contains epitopes targeted by HLA-A-restricted (HLA-A0201, A2402) cytotoxic T cells as part of the pathogenesis of β-cell destruction in type 1 diabetes. We extended the discovery of the PPI epitope to disease-associated HLA-B*1801 and HLA-B*3906 (risk) and HLA-A*1101 and HLA-B*3801 (protective) alleles, revealing that four of six alleles present epitopes derived from the signal peptide region. During cotranslational translocation of PPI, its signal peptide is cleaved and retained within the endoplasmic reticulum (ER) membrane, implying it is processed for immune recognition outside of the canonical proteasome-directed pathway. Using in vitro translocation assays with specific inhibitors and gene knockout in PPI-expressing target cells, we show that PPI signal peptide antigen processing requires signal peptide peptidase (SPP). The intramembrane protease SPP generates cytoplasm-proximal epitopes, which are transporter associated with antigen processing (TAP), ER-luminal epitopes, which are TAP independent, each presented by different HLA class I molecules and N-terminal trimmed by ER aminopeptidase 1 for optimal presentation. In vivo, TAP expression is significantly upregulated and correlated with HLA class I hyperexpression in insulin-containing islets of patients with type 1 diabetes. Thus, PPI signal peptide epitopes are processed by SPP and loaded for HLA-guided immune recognition via pathways that are enhanced during disease pathogenesis. © 2018 by the American Diabetes Association.

THE ROLE OF PROCALCITONIN IN BACTERIAL INFECTION RECOGNITION

Directory of Open Access Journals (Sweden)

Lucija Gabršek

2001-12-01

Full Text Available Background. Early recognition of bacterial infection and antibiotic treatment are very important in critically ill patients. Procalcitonin (PCT is a marker of bacterial infections accompanied by systemic inflammatory response. Higher values were also noticed with parasitical and fungal infections, but PCT is normal in viral and systemic diseases. The aim of this study was to assess whether PCT is better marker for bacterial infections than C-reactive protein (CRP and if they have a prognostic value.Methods. 34 patients were included into our retrospective study. All of them had clinical or laboratory signs of infection at the first PCT determination. We measured PCT, CRP, erythrocyte sedimentation rate (SR and leukocyte count. On the base of microbiological results we divided patients into three groups. Group A had patients with sterile cultures, group B included the ones with negative blood cultures, but from other cultures causative agents were identified. The patients in group C had positive blood cultures. Retrospectively we studied PCT and CRP values among groups and among survivors and non survivors.Results. An average median value of PCT in group A was 8.9 ± 13.3 ng/ml, in group B 5.3 ± 9.3 ng/ml and in group C 21.0 ± 25.0 ng/ml. In group B, the average median value of PCT was significantly higher than in group C (p = 0.019, but that was not the case in group A (p = 0.23. The average median values of CRP were 129.9 ± 67.4 mg/l in group A, 104.3 ± 60.1 mg/l in group B and 117.4 ± 46.1 mg/l in group C. Between groups, differences of CRP values were not statistically significant. The average initial value of PCT in group of non survivors (8.9 ± 49 was not significantly higher then in group of survivors (3.14 ± 55.4 (p = 0.48. The average final value was significantly higher (p = 0.0013 in group of non survivors (13.1 ± 23.9 ng/l than in group of survivors (0.55 ± 7.3 ng/ml. In both groups the average initial values of CRP did not

Molecular cloning and characterization of a short peptidoglycan recognition protein from silkworm Bombyx mori.

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Yang, P-J; Zhan, M-Y; Ye, C; Yu, X-Q; Rao, X-J

2017-12-01

Peptidoglycan is the major bacterial component recognized by the insect immune system. Peptidoglycan recognition proteins (PGRPs) are a family of pattern-recognition receptors that recognize peptidoglycans and modulate innate immune responses. Some PGRPs retain N-acetylmuramoyl-L-alanine amidase (Enzyme Commission number: 3.5.1.28) activity to hydrolyse bacterial peptidoglycans. Others have lost the enzymatic activity and work only as immune receptors. They are all important modulators for innate immunity. Here, we report the cloning and functional analysis of PGRP-S4, a short-form PGRP from the domesticated silkworm, Bombyx mori. The PGRP-S4 gene encodes a protein of 199 amino acids with a signal peptide and a PGRP domain. PGRP-S4 was expressed in the fat body, haemocytes and midgut. Its expression level was significantly induced by bacterial challenges in the midgut. The recombinant PGRP-S4 bound bacteria and different peptidoglycans. In addition, it inhibited bacterial growth and hydrolysed an Escherichia coli peptidoglycan in the presence of Zn 2+ . Scanning electron microscopy showed that PGRP-S4 disrupted the bacterial cell surface. PGRP-S4 further increased prophenoloxidase activation caused by peptidoglycans. Taken together, our data suggest that B. mori PGRP-S4 has multiple functions in immunity. © 2017 The Royal Entomological Society.

Entamoeba Clone-Recognition Experiments: Morphometrics, Aggregative Behavior, and Cell-Signaling Characterization.

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Espinosa, Avelina; Paz-Y-Miño-C, Guillermo; Hackey, Meagan; Rutherford, Scott

2016-05-01

Studies on clone- and kin-discrimination in protists have proliferated during the past decade. We report clone-recognition experiments in seven Entamoeba lineages (E. invadens IP-1, E. invadens VK-1:NS, E. terrapinae, E. moshkovskii Laredo, E. moshkovskii Snake, E. histolytica HM-1:IMSS and E. dispar). First, we characterized morphometrically each clone (length, width, and cell-surface area) and documented how they differed statistically from one another (as per single-variable or canonical-discriminant analyses). Second, we demonstrated that amebas themselves could discriminate self (clone) from different (themselves vs. other clones). In mix-cell-line cultures between closely-related (E. invadens IP-1 vs. E. invadens VK-1:NS) or distant-phylogenetic clones (E. terrapinae vs. E. moshkovskii Laredo), amebas consistently aggregated with same-clone members. Third, we identified six putative cell-signals secreted by the amebas (RasGap/Ankyrin, coronin-WD40, actin, protein kinases, heat shock 70, and ubiquitin) and which known functions in Entamoeba spp. included: cell proliferation, cell adhesion, cell movement, and stress-induced encystation. To our knowledge, this is the first multi-clone characterization of Entamoeba spp. morphometrics, aggregative behavior, and cell-signaling secretion in the context of clone-recognition. Protists allow us to study cell-cell recognition from ecological and evolutionary perspectives. Modern protistan lineages can be central to studies about the origins and evolution of multicellularity. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

The Prc and RseP proteases control bacterial cell-surface signalling activity.

NARCIS (Netherlands)

Bastiaansen, K.C.J.T.; Ibañez, A.; Ramos, JL; Bitter, W.; Llamas, M.A.

2014-01-01

Summary: Extracytoplasmic function (ECF) sigma factors play a key role in the regulation of vital functions in the bacterial response to the environment. In Gram-negative bacteria, activity of these sigma factors is often controlled by cell-surface signalling (CSS), a regulatory system that also

Real-time intelligent pattern recognition algorithm for surface EMG signals

Directory of Open Access Journals (Sweden)

Jahed Mehran

2007-12-01

Full Text Available Abstract Background Electromyography (EMG is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided a user assessment routine to evaluate the correctness of executed movements. Methods We propose to use an intelligent approach based on adaptive neuro-fuzzy inference system (ANFIS integrated with a real-time learning scheme to identify hand motion commands. For this purpose and to consider the effect of user evaluation on recognizing hand movements, vision feedback is applied to increase the capability of our system. By using this scheme the user may assess the correctness of the performed hand movement. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP and least mean square (LMS is utilized. Also in order to optimize the number of fuzzy rules, a subtractive clustering algorithm has been developed. To design an effective system, we consider a conventional scheme of EMG pattern recognition system. To design this system we propose to use two different sets of EMG features, namely time domain (TD and time-frequency representation (TFR. Also in order to decrease the undesirable effects of the dimension of these feature sets, principle component analysis (PCA is utilized. Results In this study, the myoelectric signals considered for classification consists of six unique hand movements. Features chosen for EMG signal

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

Science.gov (United States)

Su, Zhongqing; Ye, Lin

2004-08-01

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

Blockade of intracellular Zn2+ signaling in the basolateral amygdala affects object recognition memory via attenuation of dentate gyrus LTP.

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Fujise, Yuki; Kubota, Mitsuyasu; Suzuki, Miki; Tamano, Haruna; Takeda, Atsushi

2017-09-01

Hippocampus-dependent memory is modulated by the amygdala. However, it is unknown whether intracellular Zn 2+ signaling in the amygdala is involved in hippocampus-dependent memory. On the basis of the evidence that intracellular Zn 2+ signaling in dentate granule cells (DGC) is necessary for object recognition memory via LTP at medial perforant pathway (PP)-DGC synapses, the present study examined whether intracellular Zn 2+ signaling in the amygdala influences object recognition memory via modulation of LTP at medial PP-DGC synapses. When ZnAF-2DA (100 μM, 2 μl) was injected into the basolateral amygdala (BLA), intracellular ZnAF-2 locally chelated intracellular Zn 2+ in the amygdala. Recognition memory was affected when training of object recognition test was performed 20 min after ZnAF-2DA injection into the BLA. Twenty minutes after injection of ZnAF-2DA into the BLA, LTP induction at medial PP-DGC synapses was attenuated, while LTP induction at PP-BLA synapses was potentiated and LTP induction at BLA-DGC synapses was attenuated. These results suggest that intracellular Zn 2+ signaling in the BLA is involved in BLA-associated LTP and modulates LTP at medial PP-DGC synapses, followed by modulation of object recognition memory. Copyright © 2017 Elsevier Ltd. All rights reserved.

Arabidopsis EF-Tu receptor enhances bacterial disease resistance in transgenic wheat.

Science.gov (United States)

Schoonbeek, Henk-Jan; Wang, Hsi-Hua; Stefanato, Francesca L; Craze, Melanie; Bowden, Sarah; Wallington, Emma; Zipfel, Cyril; Ridout, Christopher J

2015-04-01

Perception of pathogen (or microbe)-associated molecular patterns (PAMPs/MAMPs) by pattern recognition receptors (PRRs) is a key component of plant innate immunity. The Arabidopsis PRR EF-Tu receptor (EFR) recognizes the bacterial PAMP elongation factor Tu (EF-Tu) and its derived peptide elf18. Previous work revealed that transgenic expression of AtEFR in Solanaceae confers elf18 responsiveness and broad-spectrum bacterial disease resistance. In this study, we developed a set of bioassays to study the activation of PAMP-triggered immunity (PTI) in wheat. We generated transgenic wheat (Triticum aestivum) plants expressing AtEFR driven by the constitutive rice actin promoter and tested their response to elf18. We show that transgenic expression of AtEFR in wheat confers recognition of elf18, as measured by the induction of immune marker genes and callose deposition. When challenged with the cereal bacterial pathogen Pseudomonas syringae pv. oryzae, transgenic EFR wheat lines had reduced lesion size and bacterial multiplication. These results demonstrate that AtEFR can be transferred successfully from dicot to monocot species, further revealing that immune signalling pathways are conserved across these distant phyla. As novel PRRs are identified, their transfer between plant families represents a useful strategy for enhancing resistance to pathogens in crops. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Emotion recognition techniques using physiological signals and video games -Systematic review-

OpenAIRE

Callejas-Cuervo, Mauro; Martínez-Tejada, Laura Alejandra; Alarcón-Aldana, Andrea Catherine

2017-01-01

Abstract Emotion recognition systems from physiological signals are innovative techniques that allow studying the behavior and reaction of an individual when exposed to information that may evoke emotional reactions through multimedia tools, for example, video games. This type of approach is used to identify the behavior of an individual in different fields, such as medicine, education, psychology, etc., in order to assess the effect that the content has on the individual that is interacting ...

The role of multimodal signals in species recognition between tree-killing bark beetles in a narrow sympatric zone.

Science.gov (United States)

Deepa S. Pureswaran; Richard W. Hofstetter; Brian Sullivan; Kristen A. Potter

2016-01-01

When related species coexist, selection pressure should favor evolution of species recognition mechanisms to prevent interspecific pairing and wasteful reproductive encounters. We investigated the potential role of pheromone and acoustic signals in species recognition between two species of tree-killing bark beetles, the southern pine beetle, Dendroctonus frontalis...

JAK kinases are required for the bacterial RNA and poly I:C induced tyrosine phosphorylation of PKR

OpenAIRE

Bleiblo, Farag; Michael, Paul; Brabant, Danielle; Ramana, Chilakamarti V; Tai, TC; Saleh, Mazen; Parrillo, Joseph E; Kumar, Anand; Kumar, Aseem

2012-01-01

Discriminating the molecular patterns associated with RNA is central to innate immunity. The protein kinase PKR is a cytosolic sensor involved in the recognition of viral dsRNA and triggering interferon-induced signaling. Here, we identified bacterial RNA as a novel distinct pattern recognized by PKR. We show that the tyrosine phosphorylation of PKR induced by either bacterial RNA or poly I:C is impaired in mutant cells lacking TYK2, JAK1, or JAK2 kinases. PKR was found to be a direct substra...

Influence of different envelope maskers on signal recognition and neuronal representation in the auditory system of a grasshopper.

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Daniela Neuhofer

Full Text Available BACKGROUND: Animals that communicate by sound face the problem that the signals arriving at the receiver often are degraded and masked by noise. Frequency filters in the receiver's auditory system may improve the signal-to-noise ratio (SNR by excluding parts of the spectrum which are not occupied by the species-specific signals. This solution, however, is hardly amenable to species that produce broad band signals or have ears with broad frequency tuning. In mammals auditory filters exist that work in the temporal domain of amplitude modulations (AM. Do insects also use this type of filtering? PRINCIPAL FINDINGS: Combining behavioural and neurophysiological experiments we investigated whether AM filters may improve the recognition of masked communication signals in grasshoppers. The AM pattern of the sound, its envelope, is crucial for signal recognition in these animals. We degraded the species-specific song by adding random fluctuations to its envelope. Six noise bands were used that differed in their overlap with the spectral content of the song envelope. If AM filters contribute to reduced masking, signal recognition should depend on the degree of overlap between the song envelope spectrum and the noise spectra. Contrary to this prediction, the resistance against signal degradation was the same for five of six masker bands. Most remarkably, the band with the strongest frequency overlap to the natural song envelope (0-100 Hz impaired acceptance of degraded signals the least. To assess the noise filter capacities of single auditory neurons, the changes of spike trains as a function of the masking level were assessed. Increasing levels of signal degradation in different frequency bands led to similar changes in the spike trains in most neurones. CONCLUSIONS: There is no indication that auditory neurones of grasshoppers are specialized to improve the SNR with respect to the pattern of amplitude modulations.

Emotion Recognition of Speech Signals Based on Filter Methods

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Narjes Yazdanian

2016-10-01

Full Text Available Speech is the basic mean of communication among human beings.With the increase of transaction between human and machine, necessity of automatic dialogue and removing human factor has been considered. The aim of this study was to determine a set of affective features the speech signal is based on emotions. In this study system was designs that include three mains sections, features extraction, features selection and classification. After extraction of useful features such as, mel frequency cepstral coefficient (MFCC, linear prediction cepstral coefficients (LPC, perceptive linear prediction coefficients (PLP, ferment frequency, zero crossing rate, cepstral coefficients and pitch frequency, Mean, Jitter, Shimmer, Energy, Minimum, Maximum, Amplitude, Standard Deviation, at a later stage with filter methods such as Pearson Correlation Coefficient, t-test, relief and information gain, we came up with a method to rank and select effective features in emotion recognition. Then Result, are given to the classification system as a subset of input. In this classification stage, multi support vector machine are used to classify seven type of emotion. According to the results, that method of relief, together with multi support vector machine, has the most classification accuracy with emotion recognition rate of 93.94%.

Angle-of-arrival-based gesture recognition using ultrasonic multi-frequency signals

KAUST Repository

Chen, Hui

2017-11-02

Hand gestures are tools for conveying information, expressing emotion, interacting with electronic devices or even serving disabled people as a second language. A gesture can be recognized by capturing the movement of the hand, in real time, and classifying the collected data. Several commercial products such as Microsoft Kinect, Leap Motion Sensor, Synertial Gloves and HTC Vive have been released and new solutions have been proposed by researchers to handle this task. These systems are mainly based on optical measurements, inertial measurements, ultrasound signals and radio signals. This paper proposes an ultrasonic-based gesture recognition system using AOA (Angle of Arrival) information of ultrasonic signals emitted from a wearable ultrasound transducer. The 2-D angles of the moving hand are estimated using multi-frequency signals captured by a fixed receiver array. A simple redundant dictionary matching classifier is designed to recognize gestures representing the numbers from `0\\' to `9\\' and compared with a neural network classifier. Average classification accuracies of 95.5% and 94.4% are obtained, respectively, using the two classification methods.

A census of membrane-bound and intracellular signal transduction proteins in bacteria: bacterial IQ, extroverts and introverts.

Science.gov (United States)

Galperin, Michael Y

2005-06-14

Analysis of complete microbial genomes showed that intracellular parasites and other microorganisms that inhabit stable ecological niches encode relatively primitive signaling systems, whereas environmental microorganisms typically have sophisticated systems of environmental sensing and signal transduction. This paper presents results of a comprehensive census of signal transduction proteins--histidine kinases, methyl-accepting chemotaxis receptors, Ser/Thr/Tyr protein kinases, adenylate and diguanylate cyclases and c-di-GMP phosphodiesterases--encoded in 167 bacterial and archaeal genomes, sequenced by the end of 2004. The data have been manually checked to avoid false-negative and false-positive hits that commonly arise during large-scale automated analyses and compared against other available resources. The census data show uneven distribution of most signaling proteins among bacterial and archaeal phyla. The total number of signal transduction proteins grows approximately as a square of genome size. While histidine kinases are found in representatives of all phyla and are distributed according to the power law, other signal transducers are abundant in certain phylogenetic groups but virtually absent in others. The complexity of signaling systems differs even among closely related organisms. Still, it usually can be correlated with the phylogenetic position of the organism, its lifestyle, and typical environmental challenges it encounters. The number of encoded signal transducers (or their fraction in the total protein set) can be used as a measure of the organism's ability to adapt to diverse conditions, the 'bacterial IQ', while the ratio of transmembrane receptors to intracellular sensors can be used to define whether the organism is an 'extrovert', actively sensing the environmental parameters, or an 'introvert', more concerned about its internal homeostasis. Some of the microorganisms with the highest IQ, including the current leader Wolinella succinogenes

A census of membrane-bound and intracellular signal transduction proteins in bacteria: Bacterial IQ, extroverts and introverts

Directory of Open Access Journals (Sweden)

Galperin Michael Y

2005-06-01

Full Text Available Abstract Background Analysis of complete microbial genomes showed that intracellular parasites and other microorganisms that inhabit stable ecological niches encode relatively primitive signaling systems, whereas environmental microorganisms typically have sophisticated systems of environmental sensing and signal transduction. Results This paper presents results of a comprehensive census of signal transduction proteins – histidine kinases, methyl-accepting chemotaxis receptors, Ser/Thr/Tyr protein kinases, adenylate and diguanylate cyclases and c-di-GMP phosphodiesterases – encoded in 167 bacterial and archaeal genomes, sequenced by the end of 2004. The data have been manually checked to avoid false-negative and false-positive hits that commonly arise during large-scale automated analyses and compared against other available resources. The census data show uneven distribution of most signaling proteins among bacterial and archaeal phyla. The total number of signal transduction proteins grows approximately as a square of genome size. While histidine kinases are found in representatives of all phyla and are distributed according to the power law, other signal transducers are abundant in certain phylogenetic groups but virtually absent in others. Conclusion The complexity of signaling systems differs even among closely related organisms. Still, it usually can be correlated with the phylogenetic position of the organism, its lifestyle, and typical environmental challenges it encounters. The number of encoded signal transducers (or their fraction in the total protein set can be used as a measure of the organism's ability to adapt to diverse conditions, the 'bacterial IQ', while the ratio of transmembrane receptors to intracellular sensors can be used to define whether the organism is an 'extrovert', actively sensing the environmental parameters, or an 'introvert', more concerned about its internal homeostasis. Some of the microorganisms with the

Involvement of bacterial quorum-sensing signals in spoilage of bean sprouts

DEFF Research Database (Denmark)

Rasch, Maria; Andersen, Jens Bo; Nielsen, Kristian Fog

2005-01-01

Bacterial communication signals, acylated homoserine lactones (AHLs), were extracted from samples of commercial bean sprouts undergoing soft-rot spoilage. Bean sprouts produced in the laboratory did not undergo soft-rot spoilage and did not contain AHLs or AHL-producing bacteria, although...... the bacterial population reached levels similar to those in the commercial sprouts, 10(8) to 10(9) CFU/g. AHL-producing bacteria (Enterobacteriaceae and pseudomonads) were isolated from commercial sprouts, and strains that were both proteolytic and pectinolytic were capable of causing soft-rot spoilage in bean...... sprouts. Thin-layer chromatography and liquid chromatography-high-resolution mass spectrometry revealed the presence of N-3-oxo-hexanoyl-l-homoserine lactone in spoiled bean sprouts and in extracts from pure cultures of bacteria. During normal spoilage, the pH of the sprouts increased due to proteolytic...

Selecting Informative Features of the Helicopter and Aircraft Acoustic Signals in the Adaptive Autonomous Information Systems for Recognition

Directory of Open Access Journals (Sweden)

V. K. Hohlov

2017-01-01

Full Text Available The article forms the rationale for selecting the informative features of the helicopter and aircraft acoustic signals to solve a problem of their recognition and shows that the most informative ones are the counts of extrema in the energy spectra of the input signals, which represent non-centered random variables. An apparatus of the multiple initial regression coefficients was selected as a mathematical tool of research. The application of digital re-circulators with positive and negative feedbacks, which have the comb-like frequency characteristics, solves the problem of selecting informative features. A distinguishing feature of such an approach is easy agility of the comb frequency characteristics just through the agility of a delay value of digital signal in the feedback circuit. Adding an adaptation block to the selection block of the informative features enables us to ensure the invariance of used informative feature and counts of local extrema of the spectral power density to the airspeed of a helicopter. The paper gives reasons for the principle of adaptation and the structure of the adaptation block. To form the discriminator characteristics are used the cross-correlation statistical characteristics of the quadrature components of acoustic signal realizations, obtained by Hilbert transform. The paper proposes to provide signal recognition using a regression algorithm that allows handling the non-centered informative features and using a priori information about coefficients of initial regression of signal and noise.The simulation in Matlab Simulink has shown that selected informative features of signals in regressive processing of signal realizations of 0.5 s duration have good separability, and based on a set of 100 acoustic signal realizations in each class in full-scale conditions, has proved ensuring a correct recognition probability of 0.975, at least. The considered principles of informative features selection and adaptation can

Investigating Strength and Frequency Effects in Recognition Memory Using Type-2 Signal Detection Theory

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Higham, Philip A.; Perfect, Timothy J.; Bruno, Davide

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower…

Mining Data of Noisy Signal Patterns in Recognition of Gasoline Bio-Based Additives using Electronic Nose

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Osowski Stanisław

2017-03-01

Full Text Available The paper analyses the distorted data of an electronic nose in recognizing the gasoline bio-based additives. Different tools of data mining, such as the methods of data clustering, principal component analysis, wavelet transformation, support vector machine and random forest of decision trees are applied. A special stress is put on the robustness of signal processing systems to the noise distorting the registered sensor signals. A special denoising procedure based on application of discrete wavelet transformation has been proposed. This procedure enables to reduce the error rate of recognition in a significant way. The numerical results of experiments devoted to the recognition of different blends of gasoline have shown the superiority of support vector machine in a noisy environment of measurement.

Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

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Arozi, Moh; Putri, Farika T.; Ariyanto, Mochammad; Khusnul Ari, M.; Munadi, Setiawan, Joga D.

2017-01-01

People with disabilities are increasing from year to year either due to congenital factors, sickness, accident factors and war. One form of disability is the case of interruptions of hand function. The condition requires and encourages the search for solutions in the form of creating an artificial hand with the ability as a human hand. The development of science in the field of neuroscience currently allows the use of electromyography (EMG) to control the motion of artificial prosthetic hand into the necessary use of EMG as an input signal to control artificial prosthetic hand. This study is the beginning of a significant research planned in the development of artificial prosthetic hand with EMG signal input. This initial research focused on the study of EMG signal recognition. Preliminary results show that the EMG signal recognition using combined discrete wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) produces accuracy 98.3 % for training and 98.51% for testing. Thus the results can be used as an input signal for Simulink block diagram of a prosthetic hand that will be developed on next study. The research will proceed with the construction of artificial prosthetic hand along with Simulink program controlling and integrating everything into one system.

A proteomic analysis of Arabidopsis thaliana seedling responses to 3-oxo-octanoyl-homoserine lactone, a bacterial quorum-sensing signal

International Nuclear Information System (INIS)

Miao, Chunjuan; Liu, Fang; Zhao, Qian; Jia, Zhenhua; Song, Shuishan

2012-01-01

Highlights: ► 3OC8-HSL can change the expression of diverse proteins in Arabidopsis. ► 3OC8-HSL responsive proteins were identified using MALDI-TOF-MS. ► Plant could have an extensive range of functional responses to bacterial AHL. -- Abstract: N-acyl-homoserine lactones (AHLs) are a class of bacterial quorum-sensing (QS) signals that are commonly used by Gram-negative bacteria for cell-to-cell communication. Recently, it has become evident that AHLs can regulate plant root growth and trigger plant defense responses; however, little is known about the plant response mechanisms to bacterial QS signals. In this study, we used a proteomic approach to investigate the responses of Arabidopsis thaliana seedlings to N-3-oxo-octanoyl-homoserine lactone (3OC8-HSL), a bacterial QS signal. The results revealed that the abundance of 53 protein spots was significantly altered; two thirds of these proteins were found to be up-regulated after 3OC8-HSL treatment. Thirty-four proteins were identified using MALDI-TOF-MS. These 3OC8-HSL-responsive proteins, in addition to one protein of unknown function, are implicated in a variety of physiological processes, including metabolism of carbohydrate and energy, protein biosynthesis and quality control systems, defense response and signal transduction and cytoskeleton remodeling. Our bioinformatic analysis indicated that the chloroplasts are the intracellular organelles most influenced by the exposure to 3OC8-HSL. Our data indicate that plants have an extensive range of functional responses to bacterial AHLs that may play important roles in the interaction between plants and bacteria.

A sensor-based wrist pulse signal processing and lung cancer recognition.

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Zhang, Zhichao; Zhang, Yuan; Yao, Lina; Song, Houbing; Kos, Anton

2018-03-01

Pulse diagnosis is an efficient method in traditional Chinese medicine for detecting the health status of a person in a non-invasive and convenient way. Jin's pulse diagnosis (JPD) is a very efficient recent development that is gradually recognized and well validated by the medical community in recent years. However, no acceptable results have been achieved for lung cancer recognition in the field of biomedical signal processing using JPD. More so, there is no standard JPD pulse feature defined with respect to pulse signals. Our work is designed mainly for care giving service conveniently at home to the people having lung cancer by proposing a novel wrist pulse signal processing method, having an insight from JPD. We developed an iterative slide window (ISW) algorithm to segment the de-noised signal into single periods. We analyzed the characteristics of the segmented pulse waveform and for the first time summarized 26 features to classify the pulse waveforms of healthy individuals and lung cancer patients using a cubic support vector machine (CSVM). The result achieved by the proposed method is found to be 78.13% accurate. Copyright © 2018 Elsevier Inc. All rights reserved.

Effects of jasmonic acid, ethylene, and salicylic acid signaling on the rhizosphere bacterial community of Arabidopsis thaliana.

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Doornbos, Rogier F; Geraats, Bart P J; Kuramae, Eiko E; Van Loon, L C; Bakker, Peter A H M

2011-04-01

Systemically induced resistance is a promising strategy to control plant diseases, as it affects numerous pathogens. However, since induced resistance reduces one or both growth and activity of plant pathogens, the indigenous microflora may also be affected by an enhanced defensive state of the plant. The aim of this study was to elucidate how much the bacterial rhizosphere microflora of Arabidopsis is affected by induced systemic resistance (ISR) or systemic acquired resistance (SAR). Therefore, the bacterial microflora of wild-type plants and plants affected in their defense signaling was compared. Additionally, ISR was induced by application of methyl jasmonate and SAR by treatment with salicylic acid or benzothiadiazole. As a comparative model, we also used wild type and ethylene-insensitive tobacco. Some of the Arabidopsis genotypes affected in defense signaling showed altered numbers of culturable bacteria in their rhizospheres; however, effects were dependent on soil type. Effects of plant genotype on rhizosphere bacterial community structure could not be related to plant defense because chemical activation of ISR or SAR had no significant effects on density and structure of the rhizosphere bacterial community. These findings support the notion that control of plant diseases by elicitation of systemic resistance will not significantly affect the resident soil bacterial microflora.

Human Walking Pattern Recognition Based on KPCA and SVM with Ground Reflex Pressure Signal

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Zhaoqin Peng

2013-01-01

Full Text Available Algorithms based on the ground reflex pressure (GRF signal obtained from a pair of sensing shoes for human walking pattern recognition were investigated. The dimensionality reduction algorithms based on principal component analysis (PCA and kernel principal component analysis (KPCA for walking pattern data compression were studied in order to obtain higher recognition speed. Classifiers based on support vector machine (SVM, SVM-PCA, and SVM-KPCA were designed, and the classification performances of these three kinds of algorithms were compared using data collected from a person who was wearing the sensing shoes. Experimental results showed that the algorithm fusing SVM and KPCA had better recognition performance than the other two methods. Experimental outcomes also confirmed that the sensing shoes developed in this paper can be employed for automatically recognizing human walking pattern in unlimited environments which demonstrated the potential application in the control of exoskeleton robots.

Urtica dioica modulates hippocampal insulin signaling and recognition memory deficit in streptozotocin induced diabetic mice.

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Patel, Sita Sharan; Gupta, Sahil; Udayabanu, Malairaman

2016-06-01

Diabetes mellitus has been associated with functional abnormalities in the hippocampus and performance of cognitive function. Urtica dioica (UD) has been used in the treatment of diabetes. In our previous report we observed that UD extract attenuate diabetes mediated associative and spatial memory dysfunction. The present study aimed to evaluate the effect of UD extract on mouse model of diabetes-induced recognition memory deficit and explore the possible mechanism behind it. Streptozotocin (STZ) (50 mg/kg, i.p. consecutively for 5 days) was used to induce diabetes followed by UD extract (50 mg/kg, oral) or rosiglitazone (ROSI) (5 mg/kg, oral) administration for 8 weeks. STZ induced diabetic mice showed significant decrease in hippocampal insulin signaling and translocation of glucose transporter type 4 (GLUT4) to neuronal membrane resulting in cognitive dysfunction and hypolocomotion. UD treatment effectively improved hippocampal insulin signaling, glucose tolerance and recognition memory performance in diabetic mice, which was comparable to ROSI. Further, diabetes mediated oxidative stress and inflammation was reversed by chronic UD or ROSI administration. UD leaves extract acts via insulin signaling pathway and might prove to be effective for the diabetes mediated central nervous system complications.

A proteomic analysis of Arabidopsis thaliana seedling responses to 3-oxo-octanoyl-homoserine lactone, a bacterial quorum-sensing signal

Energy Technology Data Exchange (ETDEWEB)

Miao, Chunjuan, E-mail: chunjuanjay@163.com [Biology Institute, Hebei Academy of Sciences, Shijiazhuang 050051 (China); Hebei Engineering and Technology Center of Microbiological Control on Main Crop Disease, Shijiazhuang 050051 (China); Liu, Fang, E-mail: liufang830818@126.com [Biology Institute, Hebei Academy of Sciences, Shijiazhuang 050051 (China); Hebei Engineering and Technology Center of Microbiological Control on Main Crop Disease, Shijiazhuang 050051 (China); Zhao, Qian, E-mail: zhqbluesea@163.com [Biology Institute, Hebei Academy of Sciences, Shijiazhuang 050051 (China); Hebei Engineering and Technology Center of Microbiological Control on Main Crop Disease, Shijiazhuang 050051 (China); Jia, Zhenhua, E-mail: zhenhuaj@hotmail.com [Biology Institute, Hebei Academy of Sciences, Shijiazhuang 050051 (China); Hebei Engineering and Technology Center of Microbiological Control on Main Crop Disease, Shijiazhuang 050051 (China); Song, Shuishan, E-mail: shuishans@hotmail.com [Biology Institute, Hebei Academy of Sciences, Shijiazhuang 050051 (China); Hebei Engineering and Technology Center of Microbiological Control on Main Crop Disease, Shijiazhuang 050051 (China)

2012-10-19

Highlights: Black-Right-Pointing-Pointer 3OC8-HSL can change the expression of diverse proteins in Arabidopsis. Black-Right-Pointing-Pointer 3OC8-HSL responsive proteins were identified using MALDI-TOF-MS. Black-Right-Pointing-Pointer Plant could have an extensive range of functional responses to bacterial AHL. -- Abstract: N-acyl-homoserine lactones (AHLs) are a class of bacterial quorum-sensing (QS) signals that are commonly used by Gram-negative bacteria for cell-to-cell communication. Recently, it has become evident that AHLs can regulate plant root growth and trigger plant defense responses; however, little is known about the plant response mechanisms to bacterial QS signals. In this study, we used a proteomic approach to investigate the responses of Arabidopsis thaliana seedlings to N-3-oxo-octanoyl-homoserine lactone (3OC8-HSL), a bacterial QS signal. The results revealed that the abundance of 53 protein spots was significantly altered; two thirds of these proteins were found to be up-regulated after 3OC8-HSL treatment. Thirty-four proteins were identified using MALDI-TOF-MS. These 3OC8-HSL-responsive proteins, in addition to one protein of unknown function, are implicated in a variety of physiological processes, including metabolism of carbohydrate and energy, protein biosynthesis and quality control systems, defense response and signal transduction and cytoskeleton remodeling. Our bioinformatic analysis indicated that the chloroplasts are the intracellular organelles most influenced by the exposure to 3OC8-HSL. Our data indicate that plants have an extensive range of functional responses to bacterial AHLs that may play important roles in the interaction between plants and bacteria.

On the Measurement of Criterion Noise in Signal Detection Theory: The Case of Recognition Memory

Science.gov (United States)

Kellen, David; Klauer, Karl Christoph; Singmann, Henrik

2012-01-01

Traditional approaches within the framework of signal detection theory (SDT; Green & Swets, 1966), especially in the field of recognition memory, assume that the positioning of response criteria is not a noisy process. Recent work (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008) has challenged this assumption, arguing not only…

Pattern-recognition receptors: signaling pathways and dysregulation in canine chronic enteropathies-brief review.

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Heilmann, Romy M; Allenspach, Karin

2017-11-01

Pattern-recognition receptors (PRRs) are expressed by innate immune cells and recognize pathogen-associated molecular patterns (PAMPs) as well as endogenous damage-associated molecular pattern (DAMP) molecules. With a large potential for synergism or convergence between their signaling pathways, PRRs orchestrate a complex interplay of cellular mediators and transcription factors, and thus play a central role in homeostasis and host defense. Aberrant activation of PRR signaling, mutations of the receptors and/or their downstream signaling molecules, and/or DAMP/PAMP complex-mediated receptor signaling can potentially lead to chronic auto-inflammatory diseases or development of cancer. PRR signaling pathways appear to also present an interesting new avenue for the modulation of inflammatory responses and to serve as potential novel therapeutic targets. Evidence for a dysregulation of the PRR toll-like receptor (TLR)2, TLR4, TLR5, and TLR9, nucleotide-binding oligomerization domain-containing protein (NOD)2, and the receptor of advanced glycation end products (RAGE) exists in dogs with chronic enteropathies. We describe the TLR, NOD2, and RAGE signaling pathways and evaluate the current veterinary literature-in comparison to human medicine-to determine the role of TLRs, NOD2, and RAGE in canine chronic enteropathies.

The tradeoff between signal detection and recognition rules auditory sensitivity under variable background noise conditions.

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Lugli, Marco

2015-12-07

Animal acoustic communication commonly takes place under masked conditions. For instance, sound signals relevant for mating and survival are very often masked by background noise, which makes their detection and recognition by organisms difficult. Ambient noise (AN) varies in level and shape among different habitats, but also remarkable variations in time and space occurs within the same habitat. Variable AN conditions mask hearing thresholds of the receiver in complex and unpredictable ways, thereby causing distortions in sound perception. When communication takes place in a noisy environment, a highly sensitive system might confer no advantage to the receiver compared to a less sensitive one. The effects of noise masking on auditory thresholds and hearing-related functions are well known, and the potential role of AN in the evolution of the species' auditory sensitivity has been recognized by few authors. The mechanism of the underlying selection process has never been explored, however. Here I present a simple fitness model that seeks for the best sensitivity of a hearing system performing the detection and recognition of the sound under variable AN conditions. The model predicts higher sensitivity (i.e. lower hearing thresholds) as best strategy for species living in quiet habitats and lower sensitivity (i.e. higher hearing thresholds) as best strategy for those living in noisy habitats provided the cost of incorrect recognition is not low. The tradeoff between detection and recognition of acoustic signals appears to be a key factor determining the best level of hearing sensitivity of a species when acoustic communication is corrupted by noise. Copyright © 2015 Elsevier Ltd. All rights reserved.

Is the C-terminal insertional signal in Gram-negative bacterial outer membrane proteins species-specific or not?

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Paramasivam Nagarajan

2012-09-01

Full Text Available Abstract Background In Gram-negative bacteria, the outer membrane is composed of an asymmetric lipid bilayer of phopspholipids and lipopolysaccharides, and the transmembrane proteins that reside in this membrane are almost exclusively β-barrel proteins. These proteins are inserted into the membrane by a highly conserved and essential machinery, the BAM complex. It recognizes its substrates, unfolded outer membrane proteins (OMPs, through a C-terminal motif that has been speculated to be species-specific, based on theoretical and experimental results from only two species, Escherichia coli and Neisseria meningitidis, where it was shown on the basis of individual sequences and motifs that OMPs from the one cannot easily be over expressed in the other, unless the C-terminal motif was adapted. In order to determine whether this species specificity is a general phenomenon, we undertook a large-scale bioinformatics study on all predicted OMPs from 437 fully sequenced proteobacterial strains. Results We were able to verify the incompatibility reported between Escherichia coli and Neisseria meningitidis, using clustering techniques based on the pairwise Hellinger distance between sequence spaces for the C-terminal motifs of individual organisms. We noticed that the amino acid position reported to be responsible for this incompatibility between Escherichia coli and Neisseria meningitidis does not play a major role for determining species specificity of OMP recognition by the BAM complex. Instead, we found that the signal is more diffuse, and that for most organism pairs, the difference between the signals is hard to detect. Notable exceptions are the Neisseriales, and Helicobacter spp. For both of these organism groups, we describe the specific sequence requirements that are at the basis of the observed difference. Conclusions Based on the finding that the differences between the recognition motifs of almost all organisms are small, we assume that

A Bacterial Receptor PcrK Senses the Plant Hormone Cytokinin to Promote Adaptation to Oxidative Stress

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Fang-Fang Wang

2017-12-01

Full Text Available Summary: Recognition of the host plant is a prerequisite for infection by pathogenic bacteria. However, how bacterial cells sense plant-derived stimuli, especially chemicals that function in regulating plant development, remains completely unknown. Here, we have identified a membrane-bound histidine kinase of the phytopathogenic bacterium Xanthomonas campestris, PcrK, as a bacterial receptor that specifically detects the plant cytokinin 2-isopentenyladenine (2iP. 2iP binds to the extracytoplasmic region of PcrK to decrease its autokinase activity. Through a four-step phosphorelay, 2iP stimulation decreased the phosphorylation level of PcrR, the cognate response regulator of PcrK, to activate the phosphodiesterase activity of PcrR in degrading the second messenger 3′,5′-cyclic diguanylic acid. 2iP perception by the PcrK-PcrR remarkably improves bacterial tolerance to oxidative stress by regulating the transcription of 56 genes, including the virulence-associated TonB-dependent receptor gene ctrA. Our results reveal an evolutionarily conserved, inter-kingdom signaling by which phytopathogenic bacteria intercept a plant hormone signal to promote adaptation to oxidative stress. : How pathogenic bacteria use receptors to recognize the signals of the host plant is unknown. Wang et al. have identified a bacterial receptor histidine kinase that specifically senses the plant hormone cytokinin. Through a four-step phosphorelay, cytokinin perception triggers degradation of a second messenger, c-di-GMP, to activate the bacterial response to oxidative stress. Keywords: histidine kinase, ligand, cytokinin, autokinase activity, phosphorelay, response regulator, two-component signal transduction system, Xanthomonas campestris pv. campestris, virulence, oxidative stress

Health monitoring of 90° bolted joints using fuzzy pattern recognition of ultrasonic signals

International Nuclear Information System (INIS)

Jalalpour, M; El-Osery, A I; Austin, E M; Reda Taha, M M

2014-01-01

Bolted joints are important parts for aerospace structures. However, there is a significant risk associated with assembling bolted joints due to potential human error during the assembly process. Such errors are expensive to find and correct if exposed during environmental testing, yet checking the integrity of individual fasteners after assembly would be a time consuming task. Recent advances in structural health monitoring (SHM) can provide techniques to not only automate this process but also make it reliable. This integrity monitoring requires damage features to be related to physical conditions representing the structural integrity of bolted joints. In this paper an SHM technique using ultrasonic signals and fuzzy pattern recognition to monitor the integrity of 90° bolted joints in aerospace structures is described. The proposed technique is based on normalized fast Fourier transform (NFFT) of transmitted signals and fuzzy pattern recognition. Moreover, experimental observations of a case study on an aluminum 90° bolted joint are presented. We demonstrate the ability of the proposed method to efficiently monitor and indicate bolted joint integrity. (paper)

Are there differential deficits in facial emotion recognition between paranoid and non-paranoid schizophrenia? A signal detection analysis.

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Huang, Charles Lung-Cheng; Hsiao, Sigmund; Hwu, Hai-Gwo; Howng, Shen-Long

2013-10-30

This study assessed facial emotion recognition abilities in subjects with paranoid and non-paranoid schizophrenia (NPS) using signal detection theory. We explore the differential deficits in facial emotion recognition in 44 paranoid patients with schizophrenia (PS) and 30 non-paranoid patients with schizophrenia (NPS), compared to 80 healthy controls. We used morphed faces with different intensities of emotion and computed the sensitivity index (d') of each emotion. The results showed that performance differed between the schizophrenia and healthy controls groups in the recognition of both negative and positive affects. The PS group performed worse than the healthy controls group but better than the NPS group in overall performance. Performance differed between the NPS and healthy controls groups in the recognition of all basic emotions and neutral faces; between the PS and healthy controls groups in the recognition of angry faces; and between the PS and NPS groups in the recognition of happiness, anger, sadness, disgust, and neutral affects. The facial emotion recognition impairment in schizophrenia may reflect a generalized deficit rather than a negative-emotion specific deficit. The PS group performed worse than the control group, but better than the NPS group in facial expression recognition, with differential deficits between PS and NPS patients. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Subject-independent emotion recognition based on physiological signals: a three-stage decision method.

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Chen, Jing; Hu, Bin; Wang, Yue; Moore, Philip; Dai, Yongqiang; Feng, Lei; Ding, Zhijie

2017-12-20

Collaboration between humans and computers has become pervasive and ubiquitous, however current computer systems are limited in that they fail to address the emotional component. An accurate understanding of human emotions is necessary for these computers to trigger proper feedback. Among multiple emotional channels, physiological signals are synchronous with emotional responses; therefore, analyzing physiological changes is a recognized way to estimate human emotions. In this paper, a three-stage decision method is proposed to recognize four emotions based on physiological signals in the multi-subject context. Emotion detection is achieved by using a stage-divided strategy in which each stage deals with a fine-grained goal. The decision method consists of three stages. During the training process, the initial stage transforms mixed training subjects to separate groups, thus eliminating the effect of individual differences. The second stage categorizes four emotions into two emotion pools in order to reduce recognition complexity. The third stage trains a classifier based on emotions in each emotion pool. During the testing process, a test case or test trial will be initially classified to a group followed by classification into an emotion pool in the second stage. An emotion will be assigned to the test trial in the final stage. In this paper we consider two different ways of allocating four emotions into two emotion pools. A comparative analysis is also carried out between the proposal and other methods. An average recognition accuracy of 77.57% was achieved on the recognition of four emotions with the best accuracy of 86.67% to recognize the positive and excited emotion. Using differing ways of allocating four emotions into two emotion pools, we found there is a difference in the effectiveness of a classifier on learning each emotion. When compared to other methods, the proposed method demonstrates a significant improvement in recognizing four emotions in the

A novel screen-printed mast cell-based electrochemical sensor for detecting spoilage bacterial quorum signaling molecules (N-acyl-homoserine-lactones) in freshwater fish.

Science.gov (United States)

Jiang, Donglei; Liu, Yan; Jiang, Hui; Rao, Shengqi; Fang, Wu; Wu, Mangang; Yuan, Limin; Fang, Weiming

2018-04-15

A novel screen-printed cell-based electrochemical sensor was developed to assess bacterial quorum signaling molecules, N-acylhomoserine lactones (AHLs). Screen-printed carbon electrode (SPCE), which possesses excellent properties such as low-cost, disposable and energy-efficient, was modified with multi-walled carbon nanotubes (MWNTs) to improve electrochemical signals and enhance the sensitivity. Rat basophilic leukemia (RBL-2H3) mast cells encapsulated in alginate/graphene oxide (NaAgl/GO) hydrogel were immobilized on the MWNTs/SPCE to serve as recognition element. Electrochemical impedance spectroscopy (EIS) was employed to record the cell impedance signal as-influenced by Pseudomonas aeruginosa quorum-sensing molecule, N-3-oxododecanoyl homoserine lactone (3OC 12 -HSL). Experimental results show that 3OC 12 -HSL caused a significant decrease in cell viability in a dose dependent manner. The EIS value decreased with concentrations of 3OC 12 -HSL in the range of 0.1-1μM, and the detection limit for 3OC 12 -HSL was calculated to be 0.094μM. These results were confirmed via cell viability, SEM, TEM analysis. Next, the sensor was successfully applied to monitoring the production of AHLs by spoilage bacteria in three different freshwater fish juice samples which efficiently proved the practicability of this cell based method. Therefore, the proposed cell sensor may serve as an innovative and effective approach to the measurement of quorum signaling molecule and thus provides a new avenue for real-time monitoring the spoilage bacteria in freshwater fish production. Copyright © 2017 Elsevier B.V. All rights reserved.

Speech Recognition

Directory of Open Access Journals (Sweden)

Adrian Morariu

2009-01-01

Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.

Time-frequency feature analysis and recognition of fission neutrons signal based on support vector machine

International Nuclear Information System (INIS)

Jin Jing; Wei Biao; Feng Peng; Tang Yuelin; Zhou Mi

2010-01-01

Based on the interdependent relationship between fission neutrons ( 252 Cf) and fission chain ( 235 U system), the paper presents the time-frequency feature analysis and recognition in fission neutron signal based on support vector machine (SVM) through the analysis on signal characteristics and the measuring principle of the 252 Cf fission neutron signal. The time-frequency characteristics and energy features of the fission neutron signal are extracted by using wavelet decomposition and de-noising wavelet packet decomposition, and then applied to training and classification by means of support vector machine based on statistical learning theory. The results show that, it is effective to obtain features of nuclear signal via wavelet decomposition and de-noising wavelet packet decomposition, and the latter can reflect the internal characteristics of the fission neutron system better. With the training accomplished, the SVM classifier achieves an accuracy rate above 70%, overcoming the lack of training samples, and verifying the effectiveness of the algorithm. (authors)

Automatic speech recognition (zero crossing method). Automatic recognition of isolated vowels

International Nuclear Information System (INIS)

Dupeyrat, Benoit

1975-01-01

This note describes a recognition method of isolated vowels, using a preprocessing of the vocal signal. The processing extracts the extrema of the vocal signal and the interval time separating them (Zero crossing distances of the first derivative of the signal). The recognition of vowels uses normalized histograms of the values of these intervals. The program determines a distance between the histogram of the sound to be recognized and histograms models built during a learning phase. The results processed on real time by a minicomputer, are relatively independent of the speaker, the fundamental frequency being not allowed to vary too much (i.e. speakers of the same sex). (author) [fr

Pattern recognition and modelling of earthquake registrations with interactive computer support

International Nuclear Information System (INIS)

Manova, Katarina S.

2004-01-01

The object of the thesis is Pattern Recognition. Pattern recognition i.e. classification, is applied in many fields: speech recognition, hand printed character recognition, medical analysis, satellite and aerial-photo interpretations, biology, computer vision, information retrieval and so on. In this thesis is studied its applicability in seismology. Signal classification is an area of great importance in a wide variety of applications. This thesis deals with the problem of (automatic) classification of earthquake signals, which are non-stationary signals. Non-stationary signal classification is an area of active research in the signal and image processing community. The goal of the thesis is recognition of earthquake signals according to their epicentral zone. Source classification i.e. recognition is based on transformation of seismograms (earthquake registrations) to images, via time-frequency transformations, and applying image processing and pattern recognition techniques for feature extraction, classification and recognition. The tested data include local earthquakes from seismic regions in Macedonia. By using actual seismic data it is shown that proposed methods provide satisfactory results for classification and recognition.(Author)

Investigating strength and frequency effects in recognition memory using type-2 signal detection theory.

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Higham, Philip A; Perfect, Timothy J; Bruno, Davide

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower false alarm rate, for low frequency words compared with high frequency words. In Experiment 2, the authors manipulated item strength with repetition, which showed an increased hit rate but no effect on the false alarm rate. Whereas Type-1 indices were ambiguous as to whether these effects were based on a criterion- or distribution-shift model, the two models predict opposite effects on Type-2 distractor monitoring under some assumptions. Hence, Type-2 ROC analysis discriminated between potential models of recognition that could not be discriminated using Type-1 indices alone. In Experiment 3, the authors manipulated Type-1 response bias by varying the number of old versus new response categories to confirm the assumptions made in Experiments 1 and 2. The authors conclude that Type-2 analyses are a useful tool for investigating recognition memory when used in conjunction with more traditional Type-1 analyses.

A novel feature ranking algorithm for biometric recognition with PPG signals.

Science.gov (United States)

Reşit Kavsaoğlu, A; Polat, Kemal; Recep Bozkurt, M

2014-06-01

This study is intended for describing the application of the Photoplethysmography (PPG) signal and the time domain features acquired from its first and second derivatives for biometric identification. For this purpose, a sum of 40 features has been extracted and a feature-ranking algorithm is proposed. This proposed algorithm calculates the contribution of each feature to biometric recognition and collocates the features, the contribution of which is from great to small. While identifying the contribution of the features, the Euclidean distance and absolute distance formulas are used. The efficiency of the proposed algorithms is demonstrated by the results of the k-NN (k-nearest neighbor) classifier applications of the features. During application, each 15-period-PPG signal belonging to two different durations from each of the thirty healthy subjects were used with a PPG data acquisition card. The first PPG signals recorded from the subjects were evaluated as the 1st configuration; the PPG signals recorded later at a different time as the 2nd configuration and the combination of both were evaluated as the 3rd configuration. When the results were evaluated for the k-NN classifier model created along with the proposed algorithm, an identification of 90.44% for the 1st configuration, 94.44% for the 2nd configuration, and 87.22% for the 3rd configuration has successfully been attained. The obtained results showed that both the proposed algorithm and the biometric identification model based on this developed PPG signal are very promising for contactless recognizing the people with the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Signal processing, sensor fusion, and target recognition; Proceedings of the Meeting, Orlando, FL, Apr. 20-22, 1992

Science.gov (United States)

Libby, Vibeke; Kadar, Ivan

Consideration is given to a multiordered mapping technique for target prioritization, a neural network approach to multiple-target-tracking problems, a multisensor fusion algorithm for multitarget multibackground classification, deconvolutiom of multiple images of the same object, neural networks and genetic algorithms for combinatorial optimization of sensor data fusion, classification of atmospheric acoustic signals from fixed-wing aircraft, and an optics approach to sensor fusion for target recognition. Also treated are a zoom lens for automatic target recognition, a hybrid model for the analysis of radar sensors, an innovative test bed for developing and assessing air-to-air noncooperative target identification algorithms, SAR imagery scene segmentation using fractal processing, sonar feature-based bandwidth compression, laboratory experiments for a new sonar system, computational algorithms for discrete transform using fixed-size filter matrices, and pattern recognition for power systems.

ST2 negatively regulates TLR2 signaling, but is not required for bacterial lipoprotein-induced tolerance.

LENUS (Irish Health Repository)

Liu, Jinghua

2010-05-15

Activation of TLR signaling is critical for host innate immunity against bacterial infection. Previous studies reported that the ST2 receptor, a member of the Toll\\/IL-1 receptor superfamily, functions as a negative regulator of TLR4 signaling and maintains LPS tolerance. However, it is undetermined whether ST2 negatively regulates TLR2 signaling and furthermore, whether a TLR2 agonist, bacterial lipoprotein (BLP)-induced tolerance is dependent on ST2. In this study, we show that BLP stimulation-induced production of proinflammatory cytokines and immunocomplex formation of TLR2-MyD88 and MyD88-IL-1R-associated kinase (IRAK) were significantly enhanced in ST2-deficient macrophages compared with those in wild-type controls. Furthermore, overexpression of ST2 dose-dependently attenuated BLP-induced NF-kappaB activation, suggesting a negative regulatory role of ST2 in TLR2 signaling. A moderate but significantly attenuated production of TNF-alpha and IL-6 on a second BLP stimulation was observed in BLP-pretreated, ST2-deficient macrophages, which is associated with substantially reduced IRAK-1 protein expression and downregulated TLR2-MyD88 and MyD88-IRAK immunocomplex formation. ST2-deficient mice, when pretreated with a nonlethal dose of BLP, benefitted from an improved survival against a subsequent lethal BLP challenge, indicating BLP tolerance develops in the absence of the ST2 receptor. Taken together, our results demonstrate that ST2 acts as a negative regulator of TLR2 signaling, but is not required for BLP-induced tolerance.

UHF Signal Processing and Pattern Recognition of Partial Discharge in Gas-Insulated Switchgear Using Chromatic Methodology.

Science.gov (United States)

Wang, Xiaohua; Li, Xi; Rong, Mingzhe; Xie, Dingli; Ding, Dan; Wang, Zhixiang

2017-01-18

The ultra-high frequency (UHF) method is widely used in insulation condition assessment. However, UHF signal processing algorithms are complicated and the size of the result is large, which hinders extracting features and recognizing partial discharge (PD) patterns. This article investigated the chromatic methodology that is novel in PD detection. The principle of chromatic methodologies in color science are introduced. The chromatic processing represents UHF signals sparsely. The UHF signals obtained from PD experiments were processed using chromatic methodology and characterized by three parameters in chromatic space ( H , L , and S representing dominant wavelength, signal strength, and saturation, respectively). The features of the UHF signals were studied hierarchically. The results showed that the chromatic parameters were consistent with conventional frequency domain parameters. The global chromatic parameters can be used to distinguish UHF signals acquired by different sensors, and they reveal the propagation properties of the UHF signal in the L-shaped gas-insulated switchgear (GIS). Finally, typical PD defect patterns had been recognized by using novel chromatic parameters in an actual GIS tank and good performance of recognition was achieved.

Bacterial Signaling Nucleotides Inhibit Yeast Cell Growth by Impacting Mitochondrial and Other Specifically Eukaryotic Functions.

Science.gov (United States)

Hesketh, Andy; Vergnano, Marta; Wan, Chris; Oliver, Stephen G

2017-07-25

We have engineered Saccharomyces cerevisiae to inducibly synthesize the prokaryotic signaling nucleotides cyclic di-GMP (cdiGMP), cdiAMP, and ppGpp in order to characterize the range of effects these nucleotides exert on eukaryotic cell function during bacterial pathogenesis. Synthetic genetic array (SGA) and transcriptome analyses indicated that, while these compounds elicit some common reactions in yeast, there are also complex and distinctive responses to each of the three nucleotides. All three are capable of inhibiting eukaryotic cell growth, with the guanine nucleotides exhibiting stronger effects than cdiAMP. Mutations compromising mitochondrial function and chromatin remodeling show negative epistatic interactions with all three nucleotides. In contrast, certain mutations that cause defects in chromatin modification and ribosomal protein function show positive epistasis, alleviating growth inhibition by at least two of the three nucleotides. Uniquely, cdiGMP is lethal both to cells growing by respiration on acetate and to obligately fermentative petite mutants. cdiGMP is also synthetically lethal with the ribonucleotide reductase (RNR) inhibitor hydroxyurea. Heterologous expression of the human ppGpp hydrolase Mesh1p prevented the accumulation of ppGpp in the engineered yeast and restored cell growth. Extensive in vivo interactions between bacterial signaling molecules and eukaryotic gene function occur, resulting in outcomes ranging from growth inhibition to death. cdiGMP functions through a mechanism that must be compensated by unhindered RNR activity or by functionally competent mitochondria. Mesh1p may be required for abrogating the damaging effects of ppGpp in human cells subjected to bacterial infection. IMPORTANCE During infections, pathogenic bacteria can release nucleotides into the cells of their eukaryotic hosts. These nucleotides are recognized as signals that contribute to the initiation of defensive immune responses that help the infected

Bacterial Effectors and Their Functions in the Ubiquitin-Proteasome System: Insight from the Modes of Substrate Recognition

Directory of Open Access Journals (Sweden)

Minsoo Kim

2014-08-01

Full Text Available Protein ubiquitination plays indispensable roles in the regulation of cell homeostasis and pathogenesis of neoplastic, infectious, and neurodegenerative diseases. Given the importance of this modification, it is to be expected that several pathogenic bacteria have developed the ability to utilize the host ubiquitin system for their own benefit. Modulation of the host ubiquitin system by bacterial effector proteins inhibits innate immune responses and hijacks central signaling pathways. Bacterial effectors mimic enzymes of the host ubiquitin system, but may or may not be structurally similar to the mammalian enzymes. Other effectors bind and modify components of the host ubiquitin system, and some are themselves subject to ubiquitination. This review will describe recent findings, based on structural analyses, regarding how pathogens use post-translational modifications of proteins to establish an infection.

Bacterial effectors and their functions in the ubiquitin-proteasome system: insight from the modes of substrate recognition.

Science.gov (United States)

Kim, Minsoo; Otsubo, Ryota; Morikawa, Hanako; Nishide, Akira; Takagi, Kenji; Sasakawa, Chihiro; Mizushima, Tsunehiro

2014-08-18

Protein ubiquitination plays indispensable roles in the regulation of cell homeostasis and pathogenesis of neoplastic, infectious, and neurodegenerative diseases. Given the importance of this modification, it is to be expected that several pathogenic bacteria have developed the ability to utilize the host ubiquitin system for their own benefit. Modulation of the host ubiquitin system by bacterial effector proteins inhibits innate immune responses and hijacks central signaling pathways. Bacterial effectors mimic enzymes of the host ubiquitin system, but may or may not be structurally similar to the mammalian enzymes. Other effectors bind and modify components of the host ubiquitin system, and some are themselves subject to ubiquitination. This review will describe recent findings, based on structural analyses, regarding how pathogens use post-translational modifications of proteins to establish an infection.

Recognition Memory zROC Slopes for Items with Correct versus Incorrect Source Decisions Discriminate the Dual Process and Unequal Variance Signal Detection Models

Science.gov (United States)

Starns, Jeffrey J.; Rotello, Caren M.; Hautus, Michael J.

2014-01-01

We tested the dual process and unequal variance signal detection models by jointly modeling recognition and source confidence ratings. The 2 approaches make unique predictions for the slope of the recognition memory zROC function for items with correct versus incorrect source decisions. The standard bivariate Gaussian version of the unequal…

Towards rationally redesigning bacterial signaling systems using information encoded in abundant sequence data

Science.gov (United States)

Cheng, Ryan; Morcos, Faruck; Levine, Herbert; Onuchic, Jose

2014-03-01

An important challenge in biology is to distinguish the subset of residues that allow bacterial two-component signaling (TCS) proteins to preferentially interact with their correct TCS partner such that they can bind and transfer signal. Detailed knowledge of this information would allow one to search sequence-space for mutations that can systematically tune the signal transmission between TCS partners as well as re-encode a TCS protein to preferentially transfer signals to a non-partner. Motivated by the notion that this detailed information is found in sequence data, we explore the mutual sequence co-evolution between signaling partners to infer how mutations can positively or negatively alter their interaction. Using Direct Coupling Analysis (DCA) for determining evolutionarily conserved interprotein interactions, we apply a DCA-based metric to quantify mutational changes in the interaction between TCS proteins and demonstrate that it accurately correlates with experimental mutagenesis studies probing the mutational change in the in vitro phosphotransfer. Our methodology serves as a potential framework for the rational design of TCS systems as well as a framework for the system-level study of protein-protein interactions in sequence-rich systems. This research has been supported by the NSF INSPIRE award MCB-1241332 and by the CTBP sponsored by the NSF (Grant PHY-1308264).

Differential effects of interleukin-17 receptor signaling on innate and adaptive immunity during central nervous system bacterial infection

Directory of Open Access Journals (Sweden)

Vidlak Debbie

2012-06-01

Full Text Available Abstract Although IL-17A (commonly referred to as IL-17 has been implicated in the pathogenesis of central nervous system (CNS autoimmune disease, its role during CNS bacterial infections remains unclear. To evaluate the broader impact of IL-17 family members in the context of CNS infection, we utilized IL-17 receptor (IL-17R knockout (KO mice that lack the ability to respond to IL-17, IL-17F and IL-17E (IL-25. In this article, we demonstrate that IL-17R signaling regulates bacterial clearance as well as natural killer T (NKT cell and gamma-delta (γδ T cell infiltrates during Staphylococcus aureus-induced brain abscess formation. Specifically, when compared with wild-type (WT animals, IL-17R KO mice exhibited elevated bacterial burdens at days 7 and 14 following S. aureus infection. Additionally, IL-17R KO animals displayed elevated neutrophil chemokine production, revealing the ability to compensate for the lack of IL-17R activity. Despite these differences, innate immune cell recruitment into brain abscesses was similar in IL-17R KO and WT mice, whereas IL-17R signaling exerted a greater influence on adaptive immune cell recruitment. In particular, γδ T cell influx was increased in IL-17R KO mice at day 7 post-infection. In addition, NK1.1high infiltrates were absent in brain abscesses of IL-17R KO animals and, surprisingly, were rarely detected in the livers of uninfected IL-17R KO mice. Although IL-17 is a key regulator of neutrophils in other infection models, our data implicate an important role for IL-17R signaling in regulating adaptive immunity during CNS bacterial infection.

Reptile Toll-like receptor 5 unveils adaptive evolution of bacterial flagellin recognition.

Science.gov (United States)

Voogdt, Carlos G P; Bouwman, Lieneke I; Kik, Marja J L; Wagenaar, Jaap A; van Putten, Jos P M

2016-01-07

Toll-like receptors (TLR) are ancient innate immune receptors crucial for immune homeostasis and protection against infection. TLRs are present in mammals, birds, amphibians and fish but have not been functionally characterized in reptiles despite the central position of this animal class in vertebrate evolution. Here we report the cloning, characterization, and function of TLR5 of the reptile Anolis carolinensis (Green Anole lizard). The receptor (acTLR5) displays the typical TLR protein architecture with 22 extracellular leucine rich repeats flanked by a N- and C-terminal leucine rich repeat domain, a membrane-spanning region, and an intracellular TIR domain. The receptor is phylogenetically most similar to TLR5 of birds and most distant to fish TLR5. Transcript analysis revealed acTLR5 expression in multiple lizard tissues. Stimulation of acTLR5 with TLR ligands demonstrated unique responsiveness towards bacterial flagellin in both reptile and human cells. Comparison of acTLR5 and human TLR5 using purified flagellins revealed differential sensitivity to Pseudomonas but not Salmonella flagellin, indicating development of species-specific flagellin recognition during the divergent evolution of mammals and reptiles. Our discovery of reptile TLR5 fills the evolutionary gap regarding TLR conservation across vertebrates and provides novel insights in functional evolution of host-microbe interactions.

Application of pattern recognition technique on randon signals for automatic monitoring of dynamic systems with emphasis on nuclear reactors

International Nuclear Information System (INIS)

Nascimento, J.A. do.

1981-01-01

The time varying or noise component of dynamic system parameters contains information on the system state. Pattern recognition analysis of noise signals for such systems is a powerful technique for assessing 'system normality' or 'correct operation'. Data analysis with modern small computers enables the otherwise unmanageable volumes of data to be processed on line and the results presented in a meaningful form. These informations provide necessary data for maintaining the system at optimum operating conditions. An automatic pattern recognition program, PSDREC, developmed for the surveillance of nuclear reactor and rotating machinery is described, and the relevant theory is outlined. This program, which applies 8 statistical tests to calculated power spectral density (PSD) distributions, was earlier installed in a PDP-11/45 computer at IPEN. In this work it has been used to separately analyse recorded signals from three systems, namely an operational BWR power reactor (neutron signals), a water pump and a diesel motor (vibration signals). The latter two were, respectively, operated over a wide-range of flow and load conditions. The statistical tests were applied to frequency bands of (0,1-40) Hz, (0-1000) Hz and (0,20000) Hz. for the BWR, pump and diesel signal data, respectively. Operation and analysis conditions are given together with representative graphs of the analysed PSD distributions. Results of the tests - discussed in some detail - are considered to be satisfactory. (Author) [pt

Signal Recognition Particle 54 kD Protein (SRP54 from the Marine Sponge Geodia cydonium

Directory of Open Access Journals (Sweden)

Sonja Durajlija-Žinić

2002-01-01

Full Text Available In the systematic search for phylogenetically conserved proteins in the simplest and most ancient extant metazoan phylum – Porifera, we have identified and analyzed a cDNA encoding the signal recognition particle 54 kD protein (SRP54 from the marine sponge Geodia cydonium (Demospongiae. The signal recognition particle (SRP is a universally conserved ribonucleoprotein complex of a very ancient origin, comprising SRP RNA and several proteins (six in mammals. The nucleotide sequence of the sponge cDNA predicts a protein of 499 amino acid residues with a calculated Mr of 55175. G. cydonium SRP54 displays unusually high overall similarity (90 % with human/mammalian SRP54 proteins, higher than with Drosophila melanogaster (88 %, or Caenorhabditis elegans (82 %. The same was found for the majority of known and phylogenetically conserved proteins from sponges, indicating that the molecular evolutionary rates in protein coding genes in Porifera as well as in highly developed mammals (vertebrates are slower, when compared with the rates in homologous genes from invertebrates (insects, nematodes. Therefore, genes/proteins from sponges might be the best candidates for the reconstruction of ancient structures of proteins and genome/proteome complexity in the ancestral organism, common to all multicellular animals.

Risperidone reverses the spatial object recognition impairment and hippocampal BDNF-TrkB signalling system alterations induced by acute MK-801 treatment

Science.gov (United States)

Chen, Guangdong; Lin, Xiaodong; Li, Gongying; Jiang, Diego; Lib, Zhiruo; Jiang, Ronghuan; Zhuo, Chuanjun

2017-01-01

The aim of the present study was to investigate the effects of a commonly-used atypical antipsychotic, risperidone, on alterations in spatial learning and in the hippocampal brain-derived neurotrophic factor (BDNF)-tyrosine receptor kinase B (TrkB) signalling system caused by acute dizocilpine maleate (MK-801) treatment. In experiment 1, adult male Sprague-Dawley rats subjected to acute treatment of either low-dose MK801 (0.1 mg/kg) or normal saline (vehicle) were tested for spatial object recognition and hippocampal expression levels of BDNF, TrkB and the phophorylation of TrkB (p-TrkB). We found that compared to the vehicle, MK-801 treatment impaired spatial object recognition of animals and downregulated the expression levels of p-TrkB. In experiment 2, MK-801- or vehicle-treated animals were further injected with risperidone (0.1 mg/kg) or vehicle before behavioural testing and sacrifice. Of note, we found that risperidone successfully reversed the deleterious effects of MK-801 on spatial object recognition and upregulated the hippocampal BDNF-TrkB signalling system. Collectively, the findings suggest that cognitive deficits from acute N-methyl-D-aspartate receptor blockade may be associated with the hypofunction of hippocampal BDNF-TrkB signalling system and that risperidone was able to reverse these alterations. PMID:28451387

Bacterial nucleotide-based second messengers.

Science.gov (United States)

Pesavento, Christina; Hengge, Regine

2009-04-01

In all domains of life nucleotide-based second messengers transduce signals originating from changes in the environment or in intracellular conditions into appropriate cellular responses. In prokaryotes cyclic di-GMP has emerged as an important and ubiquitous second messenger regulating bacterial life-style transitions relevant for biofilm formation, virulence, and many other bacterial functions. This review describes similarities and differences in the architecture of the cAMP, (p)ppGpp, and c-di-GMP signaling systems and their underlying signaling principles. Moreover, recent advances in c-di-GMP-mediated signaling will be presented and the integration of c-di-GMP signaling with other nucleotide-based signaling systems will be discussed.

Development of Adaptive AE Signal Pattern Recognition Program and Application to Classification of Defects in Metal Contact Regions of Rotating Component

International Nuclear Information System (INIS)

Lee, K. Y.; Lee, C. M.; Kim, J. S.

1996-01-01

In this study, the artificial defects in rotary compressor are classified using pattern recognition of acoustic emission signal. For this purpose the computer program is developed. The neural network classifier is compared with the statistical classifier such as the linear discriminant function classifier and empirical Bayesian classifier. It is concluded that the former is better. It is possible to acquire the recognition rate of above 99% by neural network classifier

Bacterial Signaling Nucleotides Inhibit Yeast Cell Growth by Impacting Mitochondrial and Other Specifically Eukaryotic Functions

Directory of Open Access Journals (Sweden)

Andy Hesketh

2017-07-01

Full Text Available We have engineered Saccharomyces cerevisiae to inducibly synthesize the prokaryotic signaling nucleotides cyclic di-GMP (cdiGMP, cdiAMP, and ppGpp in order to characterize the range of effects these nucleotides exert on eukaryotic cell function during bacterial pathogenesis. Synthetic genetic array (SGA and transcriptome analyses indicated that, while these compounds elicit some common reactions in yeast, there are also complex and distinctive responses to each of the three nucleotides. All three are capable of inhibiting eukaryotic cell growth, with the guanine nucleotides exhibiting stronger effects than cdiAMP. Mutations compromising mitochondrial function and chromatin remodeling show negative epistatic interactions with all three nucleotides. In contrast, certain mutations that cause defects in chromatin modification and ribosomal protein function show positive epistasis, alleviating growth inhibition by at least two of the three nucleotides. Uniquely, cdiGMP is lethal both to cells growing by respiration on acetate and to obligately fermentative petite mutants. cdiGMP is also synthetically lethal with the ribonucleotide reductase (RNR inhibitor hydroxyurea. Heterologous expression of the human ppGpp hydrolase Mesh1p prevented the accumulation of ppGpp in the engineered yeast and restored cell growth. Extensive in vivo interactions between bacterial signaling molecules and eukaryotic gene function occur, resulting in outcomes ranging from growth inhibition to death. cdiGMP functions through a mechanism that must be compensated by unhindered RNR activity or by functionally competent mitochondria. Mesh1p may be required for abrogating the damaging effects of ppGpp in human cells subjected to bacterial infection.

Quorum signaling mycotoxins: A new risk strategy for bacterial biocontrol of Fusarium verticillioides and other endophytic fungal species?

Science.gov (United States)

Bacterial endophytes are used as biocontrol organisms for plant pathogens such as the maize endophyte Fusarium verticillioides and its production of fumonisin mycotoxins. However, such applications are not always predictable and efficient. All bacteria communicate via cell-dependent signals, which...

Automated pattern recognition system for noise analysis

International Nuclear Information System (INIS)

Sides, W.H. Jr.; Piety, K.R.

1980-01-01

A pattern recognition system was developed at ORNL for on-line monitoring of noise signals from sensors in a nuclear power plant. The system continuousy measures the power spectral density (PSD) values of the signals and the statistical characteristics of the PSDs in unattended operation. Through statistical comparison of current with past PSDs (pattern recognition), the system detects changes in the noise signals. Because the noise signals contain information about the current operational condition of the plant, a change in these signals could indicate a change, either normal or abnormal, in the operational condition

Estradiol-Induced Object Recognition Memory Consolidation Is Dependent on Activation of mTOR Signaling in the Dorsal Hippocampus

Science.gov (United States)

Fortress, Ashley M.; Fan, Lu; Orr, Patrick T.; Zhao, Zaorui; Frick, Karyn M.

2013-01-01

The mammalian target of rapamycin (mTOR) signaling pathway is an important regulator of protein synthesis and is essential for various forms of hippocampal memory. Here, we asked whether the enhancement of object recognition memory consolidation produced by dorsal hippocampal infusion of 17[Beta]-estradiol (E[subscript 2]) is dependent on mTOR…

Study of the vocal signal in the amplitude-time representation. Speech segmentation and recognition algorithms

International Nuclear Information System (INIS)

Baudry, Marc

1978-01-01

This dissertation exposes an acoustical and phonetical study of vocal signal. The complex pattern of the signal is segmented into simple sub-patterns and each one of these sub-patterns may be segmented again into another more simplest patterns with lower level. Application of pattern recognition techniques facilitates on one hand this segmentation and on the other hand the definition of the structural relations between the sub-patterns. Particularly, we have developed syntactic techniques in which the rewriting rules, context-sensitive, are controlled by predicates using parameters evaluated on the sub-patterns themselves. This allow to generalize a pure syntactic analysis by adding a semantic information. The system we expose, realizes pre-classification and a partial identification of the phonemes as also the accurate detection of each pitch period. The voice signal is analysed directly using the amplitude-time representation. This system has been implemented on a mini-computer and it works in the real time. (author) [fr

Evaluating music emotion recognition:Lessons from music genre recognition?

OpenAIRE

Sturm, Bob L.

2013-01-01

A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER syste...

Pseudomonas evades immune recognition of flagellin in both mammals and plants

NARCIS (Netherlands)

Bardoel, B.W.; Ent, S. van der; Pel, M.J.C.; Tommassen, J.; Pieterse, C.M.J.; Kessel, K.P.M. van; Strijp, J.A.G. van

2011-01-01

The building blocks of bacterial flagella, flagellin monomers, are potent stimulators of host innate immune systems. Recognition of flagellin monomers occurs by flagellin-specific pattern-recognition receptors, such as Toll-like receptor 5 (TLR5) in mammals and flagellin-sensitive 2 (FLS2) in

Cross-kingdom signalling: exploitation of bacterial quorum sensing molecules by the green seaweed Ulva.

Science.gov (United States)

Joint, Ian; Tait, Karen; Wheeler, Glen

2007-07-29

The green seaweed Ulva has been shown to detect signal molecules produced by bacteria. Biofilms that release N-acylhomoserine lactones (AHLs) attract zoospores--the motile reproductive stages of Ulva. The evidence for AHL involvement is based on several independent lines of evidence, including the observation that zoospores are attracted to wild-type bacteria that produce AHLs but are not attracted to mutants that do not produce signal molecules. Synthetic AHL also attracts zoospores and the attraction is lost in the presence of autoinducer inactivation (AiiA) protein. The mechanism of attraction is not chemotactic but involves chemokinesis. When zoospores detect AHLs, the swimming rate is reduced and this results in accumulation of cells at the source of the AHL. It has been demonstrated that the detection of AHLs results in calcium influx into the zoospore. This is the first example of a calcium signalling event in a eukaryote in response to bacterial quorum sensing molecules. The role of AHLs in the ecology of Ulva is discussed. It is probable that AHLs act as cues for the settlement of zoospores, rather than being directly involved as a signalling mechanism.

Individual recognition based on communication behaviour of male fowl.

Science.gov (United States)

Smith, Carolynn L; Taubert, Jessica; Weldon, Kimberly; Evans, Christopher S

2016-04-01

Correctly directing social behaviour towards a specific individual requires an ability to discriminate between conspecifics. The mechanisms of individual recognition include phenotype matching and familiarity-based recognition. Communication-based recognition is a subset of familiarity-based recognition wherein the classification is based on behavioural or distinctive signalling properties. Male fowl (Gallus gallus) produce a visual display (tidbitting) upon finding food in the presence of a female. Females typically approach displaying males. However, males may tidbit without food. We used the distinctiveness of the visual display and the unreliability of some males to test for communication-based recognition in female fowl. We manipulated the prior experience of the hens with the males to create two classes of males: S(+) wherein the tidbitting signal was paired with a food reward to the female, and S (-) wherein the tidbitting signal occurred without food reward. We then conducted a sequential discrimination test with hens using a live video feed of a familiar male. The results of the discrimination tests revealed that hens discriminated between categories of males based on their signalling behaviour. These results suggest that fowl possess a communication-based recognition system. This is the first demonstration of live-to-video transfer of recognition in any species of bird. Copyright © 2016 Elsevier B.V. All rights reserved.

Omni-PolyA: a method and tool for accurate recognition of Poly(A) signals in human genomic DNA

KAUST Repository

Magana-Mora, Arturo

2017-08-15

BackgroundPolyadenylation is a critical stage of RNA processing during the formation of mature mRNA, and is present in most of the known eukaryote protein-coding transcripts and many long non-coding RNAs. The correct identification of poly(A) signals (PAS) not only helps to elucidate the 3′-end genomic boundaries of a transcribed DNA region and gene regulatory mechanisms but also gives insight into the multiple transcript isoforms resulting from alternative PAS. Although progress has been made in the in-silico prediction of genomic signals, the recognition of PAS in DNA genomic sequences remains a challenge.ResultsIn this study, we analyzed human genomic DNA sequences for the 12 most common PAS variants. Our analysis has identified a set of features that helps in the recognition of true PAS, which may be involved in the regulation of the polyadenylation process. The proposed features, in combination with a recognition model, resulted in a novel method and tool, Omni-PolyA. Omni-PolyA combines several machine learning techniques such as different classifiers in a tree-like decision structure and genetic algorithms for deriving a robust classification model. We performed a comparison between results obtained by state-of-the-art methods, deep neural networks, and Omni-PolyA. Results show that Omni-PolyA significantly reduced the average classification error rate by 35.37% in the prediction of the 12 considered PAS variants relative to the state-of-the-art results.ConclusionsThe results of our study demonstrate that Omni-PolyA is currently the most accurate model for the prediction of PAS in human and can serve as a useful complement to other PAS recognition methods. Omni-PolyA is publicly available as an online tool accessible at www.cbrc.kaust.edu.sa/omnipolya/.

Flexible Piezoelectric Sensor-Based Gait Recognition

Directory of Open Access Journals (Sweden)

Youngsu Cha

2018-02-01

Full Text Available Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.

Fatigue Crack Growth Behavior of and Recognition of AE Signals from Composite Patch-Repaired Aluminum Panel

International Nuclear Information System (INIS)

Kim, Sung Jin; Kwon, Oh Yang; Jang, Yong Joon

2007-01-01

The fatigue crack growth behavior of a cracked and patch-repaired Ah2024-T3 panel has been monitored by acoustic emission(AE). The overall crack growth rate was reduced The crack propagation into the adjacent hole was also retarded by introducing the patch repair. AE signals due to crack growth after the patch repair and those due to debonding of the plate-patch interface were discriminated by using the principal component analysis. The former showed high center frequency and low amplitude, whereas the latter showed long rise tine, low frequency and high amplitude. This type of AE signal recognition method could be effective for the prediction of fatigue crack growth behavior in the patch-repaired structures with the aid of AE source location

Recognition of secretory proteins in Escherichia coli requires signals in addition to the signal sequence and slow folding

Directory of Open Access Journals (Sweden)

Flower Ann M

2002-11-01

Full Text Available Abstract Background The Sec-dependent protein export apparatus of Escherichia coli is very efficient at correctly identifying proteins to be exported from the cytoplasm. Even bacterial strains that carry prl mutations, which allow export of signal sequence-defective precursors, accurately differentiate between cytoplasmic and mutant secretory proteins. It was proposed previously that the basis for this precise discrimination is the slow folding rate of secretory proteins, resulting in binding by the secretory chaperone, SecB, and subsequent targeting to translocase. Based on this proposal, we hypothesized that a cytoplasmic protein containing a mutation that slows its rate of folding would be recognized by SecB and therefore targeted to the Sec pathway. In a Prl suppressor strain the mutant protein would be exported to the periplasm due to loss of ability to reject non-secretory proteins from the pathway. Results In the current work, we tested this hypothesis using a mutant form of λ repressor that folds slowly. No export of the mutant protein was observed, even in a prl strain. We then examined binding of the mutant λ repressor to SecB. We did not observe interaction by either of two assays, indicating that slow folding is not sufficient for SecB binding and targeting to translocase. Conclusions These results strongly suggest that to be targeted to the export pathway, secretory proteins contain signals in addition to the canonical signal sequence and the rate of folding.

Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

Science.gov (United States)

Lhamon, Michael Earl

A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase

Effects of cue modality and emotional category on recognition of nonverbal emotional signals in schizophrenia.

Science.gov (United States)

Vogel, Bastian D; Brück, Carolin; Jacob, Heike; Eberle, Mark; Wildgruber, Dirk

2016-07-07

Impaired interpretation of nonverbal emotional cues in patients with schizophrenia has been reported in several studies and a clinical relevance of these deficits for social functioning has been assumed. However, it is unclear to what extent the impairments depend on specific emotions or specific channels of nonverbal communication. Here, the effect of cue modality and emotional categories on accuracy of emotion recognition was evaluated in 21 patients with schizophrenia and compared to a healthy control group (n = 21). To this end, dynamic stimuli comprising speakers of both genders in three different sensory modalities (auditory, visual and audiovisual) and five emotional categories (happy, alluring, neutral, angry and disgusted) were used. Patients with schizophrenia were found to be impaired in emotion recognition in comparison to the control group across all stimuli. Considering specific emotions more severe deficits were revealed in the recognition of alluring stimuli and less severe deficits in the recognition of disgusted stimuli as compared to all other emotions. Regarding cue modality the extent of the impairment in emotional recognition did not significantly differ between auditory and visual cues across all emotional categories. However, patients with schizophrenia showed significantly more severe disturbances for vocal as compared to facial cues when sexual interest is expressed (alluring stimuli), whereas more severe disturbances for facial as compared to vocal cues were observed when happiness or anger is expressed. Our results confirmed that perceptual impairments can be observed for vocal as well as facial cues conveying various social and emotional connotations. The observed differences in severity of impairments with most severe deficits for alluring expressions might be related to specific difficulties in recognizing the complex social emotional information of interpersonal intentions as compared to "basic" emotional states. Therefore

Orexin signaling during social defeat stress influences subsequent social interaction behaviour and recognition memory.

Science.gov (United States)

Eacret, Darrell; Grafe, Laura A; Dobkin, Jane; Gotter, Anthony L; Rengerb, John J; Winrow, Christopher J; Bhatnagar, Seema

2018-06-11

Orexins are neuropeptides synthesized in the lateral hypothalamus that influence arousal, feeding, reward pathways, and the response to stress. However, the role of orexins in repeated stress is not fully characterized. Here, we examined how orexins and their receptors contribute to the coping response during repeated social defeat and subsequent anxiety-like and memory-related behaviors. Specifically, we used Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) to stimulate orexins prior to each of five consecutive days of social defeat stress in adult male rats. Additionally, we determined the role of the orexin 2 receptor in these behaviors by using a selective orexin 2 receptor antagonist (MK-1064) administered prior to each social defeat. Following the 5 day social defeat conditioning period, rats were evaluated in social interaction and novel object recognition paradigms to assess anxiety-like behavior and recognition memory, respectively. Activation of orexin neurons by DREADDs prior to each social defeat decreased the average latency to become defeated across 5 days, indicative of a passive coping strategy that we have previously linked to a stress vulnerable phenotype. Moreover, stimulation of orexin signaling during defeat conditioning decreased subsequent social interaction and performance in the novel object recognition test indicating increased subsequent anxiety-like behavior and reduced working memory. Blocking the orexin 2 receptor during repeated defeat did not alter these effects. Together, our results suggest that orexin neuron activation produces a passive coping phenotype during social defeat leading to subsequent anxiety-like behaviors and memory deficits. Copyright © 2018. Published by Elsevier B.V.

Perceptual Plasticity for Auditory Object Recognition

Science.gov (United States)

Heald, Shannon L. M.; Van Hedger, Stephen C.; Nusbaum, Howard C.

2017-01-01

In our auditory environment, we rarely experience the exact acoustic waveform twice. This is especially true for communicative signals that have meaning for listeners. In speech and music, the acoustic signal changes as a function of the talker (or instrument), speaking (or playing) rate, and room acoustics, to name a few factors. Yet, despite this acoustic variability, we are able to recognize a sentence or melody as the same across various kinds of acoustic inputs and determine meaning based on listening goals, expectations, context, and experience. The recognition process relates acoustic signals to prior experience despite variability in signal-relevant and signal-irrelevant acoustic properties, some of which could be considered as “noise” in service of a recognition goal. However, some acoustic variability, if systematic, is lawful and can be exploited by listeners to aid in recognition. Perceivable changes in systematic variability can herald a need for listeners to reorganize perception and reorient their attention to more immediately signal-relevant cues. This view is not incorporated currently in many extant theories of auditory perception, which traditionally reduce psychological or neural representations of perceptual objects and the processes that act on them to static entities. While this reduction is likely done for the sake of empirical tractability, such a reduction may seriously distort the perceptual process to be modeled. We argue that perceptual representations, as well as the processes underlying perception, are dynamically determined by an interaction between the uncertainty of the auditory signal and constraints of context. This suggests that the process of auditory recognition is highly context-dependent in that the identity of a given auditory object may be intrinsically tied to its preceding context. To argue for the flexible neural and psychological updating of sound-to-meaning mappings across speech and music, we draw upon examples

What Makes a Bacterial Species Pathogenic?:Comparative Genomic Analysis of the Genus Leptospira.

Science.gov (United States)

Fouts, Derrick E; Matthias, Michael A; Adhikarla, Haritha; Adler, Ben; Amorim-Santos, Luciane; Berg, Douglas E; Bulach, Dieter; Buschiazzo, Alejandro; Chang, Yung-Fu; Galloway, Renee L; Haake, David A; Haft, Daniel H; Hartskeerl, Rudy; Ko, Albert I; Levett, Paul N; Matsunaga, James; Mechaly, Ariel E; Monk, Jonathan M; Nascimento, Ana L T; Nelson, Karen E; Palsson, Bernhard; Peacock, Sharon J; Picardeau, Mathieu; Ricaldi, Jessica N; Thaipandungpanit, Janjira; Wunder, Elsio A; Yang, X Frank; Zhang, Jun-Jie; Vinetz, Joseph M

2016-02-01

Leptospirosis, caused by spirochetes of the genus Leptospira, is a globally widespread, neglected and emerging zoonotic disease. While whole genome analysis of individual pathogenic, intermediately pathogenic and saprophytic Leptospira species has been reported, comprehensive cross-species genomic comparison of all known species of infectious and non-infectious Leptospira, with the goal of identifying genes related to pathogenesis and mammalian host adaptation, remains a key gap in the field. Infectious Leptospira, comprised of pathogenic and intermediately pathogenic Leptospira, evolutionarily diverged from non-infectious, saprophytic Leptospira, as demonstrated by the following computational biology analyses: 1) the definitive taxonomy and evolutionary relatedness among all known Leptospira species; 2) genomically-predicted metabolic reconstructions that indicate novel adaptation of infectious Leptospira to mammals, including sialic acid biosynthesis, pathogen-specific porphyrin metabolism and the first-time demonstration of cobalamin (B12) autotrophy as a bacterial virulence factor; 3) CRISPR/Cas systems demonstrated only to be present in pathogenic Leptospira, suggesting a potential mechanism for this clade's refractoriness to gene targeting; 4) finding Leptospira pathogen-specific specialized protein secretion systems; 5) novel virulence-related genes/gene families such as the Virulence Modifying (VM) (PF07598 paralogs) proteins and pathogen-specific adhesins; 6) discovery of novel, pathogen-specific protein modification and secretion mechanisms including unique lipoprotein signal peptide motifs, Sec-independent twin arginine protein secretion motifs, and the absence of certain canonical signal recognition particle proteins from all Leptospira; and 7) and demonstration of infectious Leptospira-specific signal-responsive gene expression, motility and chemotaxis systems. By identifying large scale changes in infectious (pathogenic and intermediately pathogenic

What Makes a Bacterial Species Pathogenic?:Comparative Genomic Analysis of the Genus Leptospira.

Directory of Open Access Journals (Sweden)

Derrick E Fouts

2016-02-01

Full Text Available Leptospirosis, caused by spirochetes of the genus Leptospira, is a globally widespread, neglected and emerging zoonotic disease. While whole genome analysis of individual pathogenic, intermediately pathogenic and saprophytic Leptospira species has been reported, comprehensive cross-species genomic comparison of all known species of infectious and non-infectious Leptospira, with the goal of identifying genes related to pathogenesis and mammalian host adaptation, remains a key gap in the field. Infectious Leptospira, comprised of pathogenic and intermediately pathogenic Leptospira, evolutionarily diverged from non-infectious, saprophytic Leptospira, as demonstrated by the following computational biology analyses: 1 the definitive taxonomy and evolutionary relatedness among all known Leptospira species; 2 genomically-predicted metabolic reconstructions that indicate novel adaptation of infectious Leptospira to mammals, including sialic acid biosynthesis, pathogen-specific porphyrin metabolism and the first-time demonstration of cobalamin (B12 autotrophy as a bacterial virulence factor; 3 CRISPR/Cas systems demonstrated only to be present in pathogenic Leptospira, suggesting a potential mechanism for this clade's refractoriness to gene targeting; 4 finding Leptospira pathogen-specific specialized protein secretion systems; 5 novel virulence-related genes/gene families such as the Virulence Modifying (VM (PF07598 paralogs proteins and pathogen-specific adhesins; 6 discovery of novel, pathogen-specific protein modification and secretion mechanisms including unique lipoprotein signal peptide motifs, Sec-independent twin arginine protein secretion motifs, and the absence of certain canonical signal recognition particle proteins from all Leptospira; and 7 and demonstration of infectious Leptospira-specific signal-responsive gene expression, motility and chemotaxis systems. By identifying large scale changes in infectious (pathogenic and intermediately

Recognition of extracellular bacteria by NLRs and its role in the development of adaptive immunity

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Jonathan eFerrand

2013-10-01

Full Text Available Innate immune recognition of bacteria is the first requirement for mounting an effective immune response able to control infection. Over the previous decade, the general paradigm was that extracellular bacteria were only sensed by cell surface-expressed Toll-like receptors (TLRs, whereas cytoplasmic sensors, including members of the Nod-like receptor (NLR family, were specific to pathogens capable of breaching the host cell membrane. It has become apparent, however, that intracellular innate immune molecules, such as the NLRs, play key roles in the sensing of not only intracellular, but also extracellular bacterial pathogens or their components. In this review, we will discuss the various mechanisms used by bacteria to activate NLR signaling in host cells. These mechanisms include bacterial secretion systems, pore-forming toxins and outer membrane vesicles. We will then focus on the influence of NLR activation on the development of adaptive immune responses in different cell types.

Dynamic chemical communication between plants and bacteria through airborne signals: induced resistance by bacterial volatiles.

Science.gov (United States)

Farag, Mohamed A; Zhang, Huiming; Ryu, Choong-Min

2013-07-01

Certain plant growth-promoting rhizobacteria (PGPR) elicit induced systemic resistance (ISR) and plant growth promotion in the absence of physical contact with plants via volatile organic compound (VOC) emissions. In this article, we review the recent progess made by research into the interactions between PGPR VOCs and plants, focusing on VOC emission by PGPR strains in plants. Particular attention is given to the mechanisms by which these bacterial VOCs elicit ISR. We provide an overview of recent progress in the elucidation of PGPR VOC interactions from studies utilizing transcriptome, metabolome, and proteome analyses. By monitoring defense gene expression patterns, performing 2-dimensional electrophoresis, and studying defense signaling null mutants, salicylic acid and ethylene have been found to be key players in plant signaling pathways involved in the ISR response. Bacterial VOCs also confer induced systemic tolerance to abiotic stresses, such as drought and heavy metals. A review of current analytical approaches for PGPR volatile profiling is also provided with needed future developments emphasized. To assess potential utilization of PGPR VOCs for crop plants, volatile suspensions have been applied to pepper and cucumber roots and found to be effective at protecting plants against plant pathogens and insect pests in the field. Taken together, these studies provide further insight into the biological and ecological potential of PGPR VOCs for enhancing plant self-immunity and/or adaptation to biotic and abiotic stresses in modern agriculture.

Accuracy of MFCC-Based Speaker Recognition in Series 60 Device

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Pasi Fränti

2005-10-01

Full Text Available A fixed point implementation of speaker recognition based on MFCC signal processing is considered. We analyze the numerical error of the MFCC and its effect on the recognition accuracy. Techniques to reduce the information loss in a converted fixed point implementation are introduced. We increase the signal processing accuracy by adjusting the ratio of presentation accuracy of the operators and the signal. The signal processing error is found out to be more important to the speaker recognition accuracy than the error in the classification algorithm. The results are verified by applying the alternative technique to speech data. We also discuss the specific programming requirements set up by the Symbian and Series 60.

Autophagic clearance of bacterial pathogens: molecular recognition of intracellular microorganisms.

Science.gov (United States)

Pareja, Maria Eugenia Mansilla; Colombo, Maria I

2013-01-01

Autophagy is involved in several physiological and pathological processes. One of the key roles of the autophagic pathway is to participate in the first line of defense against the invasion of pathogens, as part of the innate immune response. Targeting of intracellular bacteria by the autophagic machinery, either in the cytoplasm or within vacuolar compartments, helps to control bacterial proliferation in the host cell, controlling also the spreading of the infection. In this review we will describe the means used by diverse bacterial pathogens to survive intracellularly and how they are recognized by the autophagic molecular machinery, as well as the mechanisms used to avoid autophagic clearance.

Fractal and twin SVM-based handgrip recognition for healthy subjects and trans-radial amputees using myoelectric signal.

Science.gov (United States)

Arjunan, Sridhar Poosapadi; Kumar, Dinesh Kant; Jayadeva J

2016-02-01

Identifying functional handgrip patterns using surface electromygram (sEMG) signal recorded from amputee residual muscle is required for controlling the myoelectric prosthetic hand. In this study, we have computed the signal fractal dimension (FD) and maximum fractal length (MFL) during different grip patterns performed by healthy and transradial amputee subjects. The FD and MFL of the sEMG, referred to as the fractal features, were classified using twin support vector machines (TSVM) to recognize the handgrips. TSVM requires fewer support vectors, is suitable for data sets with unbalanced distributions, and can simultaneously be trained for improving both sensitivity and specificity. When compared with other methods, this technique resulted in improved grip recognition accuracy, sensitivity, and specificity, and this improvement was significant (κ=0.91).

Pedestrian recognition using automotive radar sensors

OpenAIRE

A. Bartsch; F. Fitzek; R. H. Rasshofer

2012-01-01

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insight...

Neural Mechanisms and Information Processing in Recognition Systems

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Mamiko Ozaki

2014-10-01

Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.

Pattern Recognition of Signals for the Fault-Slip Type of Rock Burst in Coal Mines

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X. S. Liu

2015-01-01

Full Text Available The fault-slip type of rock burst is a major threat to the safety of coal mining, and effectively recognizing its signals patterns is the foundation for the early warning and prevention. At first, a mechanical model of the fault-slip was established and the mechanism of the rock burst induced by the fault-slip was revealed. Then, the patterns of the electromagnetic radiation, acoustic emission (AE, and microseismic signals in the fault-slip type of rock burst were proposed, in that before the rock burst occurs, the electromagnetic radiation intensity near the sliding surface increases rapidly, the AE energy rises exponentially, and the energy released by microseismic events experiences at least one peak and is close to the next peak. At last, in situ investigations were performed at number 1412 coal face in the Huafeng Mine, China. Results showed that the signals patterns proposed are in good agreement with the process of the fault-slip type of rock burst. The pattern recognition can provide a basis for the early warning and the implementation of relief measures of the fault-slip type of rock burst.

Opposing roles for interferon regulatory factor-3 (IRF-3 and type I interferon signaling during plague.

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Ami A Patel

Full Text Available Type I interferons (IFN-I broadly control innate immunity and are typically transcriptionally induced by Interferon Regulatory Factors (IRFs following stimulation of pattern recognition receptors within the cytosol of host cells. For bacterial infection, IFN-I signaling can result in widely variant responses, in some cases contributing to the pathogenesis of disease while in others contributing to host defense. In this work, we addressed the role of type I IFN during Yersinia pestis infection in a murine model of septicemic plague. Transcription of IFN-β was induced in vitro and in vivo and contributed to pathogenesis. Mice lacking the IFN-I receptor, Ifnar, were less sensitive to disease and harbored more neutrophils in the later stage of infection which correlated with protection from lethality. In contrast, IRF-3, a transcription factor commonly involved in inducing IFN-β following bacterial infection, was not necessary for IFN production but instead contributed to host defense. In vitro, phagocytosis of Y. pestis by macrophages and neutrophils was more effective in the presence of IRF-3 and was not affected by IFN-β signaling. This activity correlated with limited bacterial growth in vivo in the presence of IRF-3. Together the data demonstrate that IRF-3 is able to activate pathways of innate immunity against bacterial infection that extend beyond regulation of IFN-β production.

Modulation of pathogen recognition by autophagy

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Ji Eun eOh

2012-03-01

Full Text Available Autophagy is an ancient biological process for maintaining cellular homeostasis by degradation of long-lived cytosolic proteins and organelles. Recent studies demonstrated that autophagy is availed by immune cells to regulate innate immunity. On the one hand, cells exert direct effector function by degrading intracellular pathogens; on the other hand, autophagy modulates pathogen recognition and downstream signaling for innate immune responses. Pathogen recognition via pattern recognition receptors induces autophagy. The function of phagocytic cells is enhanced by recruitment of autophagy-related proteins. Moreover, autophagy acts as a delivery system for viral replication complexes to migrate to the endosomal compartments where virus sensing occurs. In another case, key molecules of the autophagic pathway have been found to negatively regulate immune signaling, thus preventing aberrant activation of cytokine production and consequent immune responses. In this review, we focus on the recent advances in the role of autophagy in pathogen recognition and modulation of innate immune responses.

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...

Bacterial surface adaptation

Science.gov (United States)

Utada, Andrew

2014-03-01

Biofilms are structured multi-cellular communities that are fundamental to the biology and ecology of bacteria. Parasitic bacterial biofilms can cause lethal infections and biofouling, but commensal bacterial biofilms, such as those found in the gut, can break down otherwise indigestible plant polysaccharides and allow us to enjoy vegetables. The first step in biofilm formation, adaptation to life on a surface, requires a working knowledge of low Reynolds number fluid physics, and the coordination of biochemical signaling, polysaccharide production, and molecular motility motors. These crucial early stages of biofilm formation are at present poorly understood. By adapting methods from soft matter physics, we dissect bacterial social behavior at the single cell level for several prototypical bacterial species, including Pseudomonas aeruginosa and Vibrio cholerae.

A DESIGN FRAMEWORK FOR HUMAN EMOTION RECOGNITION USING ELECTROCARDIOGRAM AND SKIN CONDUCTANCE RESPONSE SIGNALS

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KHAIRUN NISA’ MINHAD

2017-11-01

Full Text Available Identification of human emotional state while driving a vehicle can help in understanding the human behaviour. Based on this identification, a response system can be developed in order to mitigate the impact that may be resulted from the behavioural changes. However, the adaptation of emotions to the environment at most scenarios is subjective to an individual’s perspective. Many factors, mainly cultural and geography, gender, age, life style and history, level of education and professional status, can affect the detection of human emotional affective states. This work investigated sympathetic responses toward human emotions defined by using electrocardiography (ECG and skin conductance response (SCR signals recorded simultaneously. This work aimed to recognize ECG and SCR patterns of the investigated emotions measured using selected sensor. A pilot study was conducted to evaluate the proposed framework. Initial results demonstrated the importance of suitability of the stimuli used to evoke the emotions and high opportunity for the ECG and SCR signals to be used in the automotive real-time emotion recognition systems.

Forensic speaker recognition

NARCIS (Netherlands)

Meuwly, Didier

2013-01-01

The aim of forensic speaker recognition is to establish links between individuals and criminal activities, through audio speech recordings. This field is multidisciplinary, combining predominantly phonetics, linguistics, speech signal processing, and forensic statistics. On these bases, expert-based

Systemic cytokine signaling via IL-17 in smokers with obstructive pulmonary disease: a link to bacterial colonization?

Science.gov (United States)

Andelid, Kristina; Tengvall, Sara; Andersson, Anders; Levänen, Bettina; Christenson, Karin; Jirholt, Pernilla; Åhrén, Christina; Qvarfordt, Ingemar; Ekberg-Jansson, Ann; Lindén, Anders

2015-01-01

We examined whether systemic cytokine signaling via interleukin (IL)-17 and growth-related oncogene-α (GRO-α) is impaired in smokers with obstructive pulmonary disease including chronic bronchitis (OPD-CB). We also examined how this systemic cytokine signaling relates to bacterial colonization in the airways of the smokers with OPD-CB. Currently smoking OPD-CB patients (n=60, corresponding to Global initiative for chronic Obstructive Lung Disease [GOLD] stage I–IV) underwent recurrent blood and sputum sampling over 60 weeks, during stable conditions and at exacerbations. We characterized cytokine protein concentrations in blood and bacterial growth in sputum. Asymptomatic smokers (n=10) and never-smokers (n=10) were included as control groups. During stable clinical conditions, the protein concentrations of IL-17 and GRO-α were markedly lower among OPD-CB patients compared with never-smoker controls, whereas the asymptomatic smoker controls displayed intermediate concentrations. Notably, among OPD-CB patients, colonization by opportunistic pathogens was associated with markedly lower IL-17 and GRO-α, compared with colonization by common respiratory pathogens or oropharyngeal flora. During exacerbations in the OPD-CB patients, GRO-α and neutrophil concentrations were increased, whereas protein concentrations and messenger RNA for IL-17 were not detectable in a reproducible manner. In smokers with OPD-CB, systemic cytokine signaling via IL-17 and GRO-α is impaired and this alteration may be linked to colonization by opportunistic pathogens in the airways. Given the potential pathogenic and therapeutic implications, these findings deserve to be validated in new and larger patient cohorts. PMID:25848245

Quorum sensing communication between bacteria and human cells: signals, targets and functions

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Angelika eHolm

2014-06-01

Full Text Available Both direct and long-range interactions between pathogenic Pseudomonas aeruginosa bacteria and their eukaryotic hosts are important in the outcome of infections. For cell-to-cell communication, these bacteria employ the quorum sensing (QS system to pass on information of the density of the bacterial population and collectively switch on virulence factor production, biofilm formation and resistance development. Thus, QS allows bacteria to behave as a community to perform tasks which would be impossible for individual cells, e.g. to overcome defense and immune systems and establish infections in higher organisms. This review highlights these aspects of QS and our own recent research on how P.aeruginosa communicates with human cells using the small QS signal molecules N-acyl homoserine lactones (AHL. We focus on how this conversation changes the behavior and function of neutrophils, macrophages and epithelial cells and on how the signaling machinery in human cells responsible for the recognition of AHL. Understanding the bacteria-host relationships at both cellular and molecular levels is essential for the identification of new targets and for the development of novel strategies to fight bacterial infections in the future.

Detection and recognition of mechanical, digging and vehicle signals in the optical fiber pre-warning system

Science.gov (United States)

Tian, Qing; Yang, Dan; Zhang, Yuan; Qu, Hongquan

2018-04-01

This paper presents detection and recognition method to locate and identify harmful intrusions in the optical fiber pre-warning system (OFPS). Inspired by visual attention architecture (VAA), the process flow is divided into two parts, i.e., data-driven process and task-driven process. At first, data-driven process takes all the measurements collected by the system as input signals, which is handled by detection method to locate the harmful intrusion in both spatial domain and time domain. Then, these detected intrusion signals are taken over by task-driven process. Specifically, we get pitch period (PP) and duty cycle (DC) of the intrusion signals to identify the mechanical and manual digging (MD) intrusions respectively. For the passing vehicle (PV) intrusions, their strong low frequency component can be used as good feature. In generally, since the harmful intrusion signals only account for a small part of whole measurements, the data-driven process reduces the amount of input data for subsequent task-driven process considerably. Furthermore, the task-driven process determines the harmful intrusions orderly according to their severity, which makes a priority mechanism for the system as well as targeted processing for different harmful intrusion. At last, real experiments are performed to validate the effectiveness of this method.

Dynamic Programming Algorithms in Speech Recognition

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Titus Felix FURTUNA

2008-01-01

Full Text Available In a system of speech recognition containing words, the recognition requires the comparison between the entry signal of the word and the various words of the dictionary. The problem can be solved efficiently by a dynamic comparison algorithm whose goal is to put in optimal correspondence the temporal scales of the two words. An algorithm of this type is Dynamic Time Warping. This paper presents two alternatives for implementation of the algorithm designed for recognition of the isolated words.

[Recognition of walking stance phase and swing phase based on moving window].

Science.gov (United States)

Geng, Xiaobo; Yang, Peng; Wang, Xinran; Geng, Yanli; Han, Yu

2014-04-01

Wearing transfemoral prosthesis is the only way to complete daily physical activity for amputees. Motion pattern recognition is important for the control of prosthesis, especially in the recognizing swing phase and stance phase. In this paper, it is reported that surface electromyography (sEMG) signal is used in swing and stance phase recognition. sEMG signal of related muscles was sampled by Infiniti of a Canadian company. The sEMG signal was then filtered by weighted filtering window and analyzed by height permitted window. The starting time of stance phase and swing phase is determined through analyzing special muscles. The sEMG signal of rectus femoris was used in stance phase recognition and sEMG signal of tibialis anterior is used in swing phase recognition. In a certain tolerating range, the double windows theory, including weighted filtering window and height permitted window, can reach a high accuracy rate. Through experiments, the real walking consciousness of the people was reflected by sEMG signal of related muscles. Using related muscles to recognize swing and stance phase is reachable. The theory used in this paper is useful for analyzing sEMG signal and actual prosthesis control.

Hybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine

Science.gov (United States)

Yang, Zhutian; Wu, Zhilu; Yin, Zhendong; Quan, Taifan; Sun, Hongjian

2013-01-01

Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for recognizing radar emitter signals. In this paper, a hybrid recognition approach is presented that classifies radar emitter signals by exploiting the different separability of samples. The proposed approach comprises two steps, namely the primary signal recognition and the advanced signal recognition. In the former step, a novel rough k-means classifier, which comprises three regions, i.e., certain area, rough area and uncertain area, is proposed to cluster the samples of radar emitter signals. In the latter step, the samples within the rough boundary are used to train the relevance vector machine (RVM). Then RVM is used to recognize the samples in the uncertain area; therefore, the classification accuracy is improved. Simulation results show that, for recognizing radar emitter signals, the proposed hybrid recognition approach is more accurate, and presents lower computational complexity than traditional approaches. PMID:23344380

Interference in Bacterial Quorum Sensing: A Biopharmaceutical Perspective

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Benjamin Rémy

2018-03-01

Full Text Available Numerous bacteria utilize molecular communication systems referred to as quorum sensing (QS to synchronize the expression of certain genes regulating, among other aspects, the expression of virulence factors and the synthesis of biofilm. To achieve this process, bacteria use signaling molecules, known as autoinducers (AIs, as chemical messengers to share information. Naturally occurring strategies that interfere with bacterial signaling have been extensively studied in recent years, examining their potential to control bacteria. To interfere with QS, bacteria use quorum sensing inhibitors (QSIs to block the action of AIs and quorum quenching (QQ enzymes to degrade signaling molecules. Recent studies have shown that these strategies are promising routes to decrease bacterial pathogenicity and decrease biofilms, potentially enhancing bacterial susceptibility to antimicrobial agents including antibiotics and bacteriophages. The efficacy of QSIs and QQ enzymes has been demonstrated in various animal models and are now considered in the development of new medical devices against bacterial infections, including dressings, and catheters for enlarging the therapeutic arsenal against bacteria.

Type I interferon and pattern recognition receptor signaling following particulate matter inhalation

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Erdely Aaron

2012-07-01

Full Text Available Abstract Background Welding, a process that generates an aerosol containing gases and metal-rich particulates, induces adverse physiological effects including inflammation, immunosuppression and cardiovascular dysfunction. This study utilized microarray technology and subsequent pathway analysis as an exploratory search for markers/mechanisms of in vivo systemic effects following inhalation. Mice were exposed by inhalation to gas metal arc – stainless steel (GMA-SS welding fume at 40 mg/m3 for 3 hr/d for 10 d and sacrificed 4 hr, 14 d and 28 d post-exposure. Whole blood cells, aorta and lung were harvested for global gene expression analysis with subsequent Ingenuity Pathway Analysis and confirmatory qRT-PCR. Serum was collected for protein profiling. Results The novel finding was a dominant type I interferon signaling network with the transcription factor Irf7 as a central component maintained through 28 d. Remarkably, these effects showed consistency across all tissues indicating a systemic type I interferon response that was complemented by changes in serum proteins (decreased MMP-9, CRP and increased VCAM1, oncostatin M, IP-10. In addition, pulmonary expression of interferon α and β and Irf7 specific pattern recognition receptors (PRR and signaling molecules (Ddx58, Ifih1, Dhx58, ISGF3 were induced, an effect that showed specificity when compared to other inflammatory exposures. Also, a canonical pathway indicated a coordinated response of multiple PRR and associated signaling molecules (Tlr7, Tlr2, Clec7a, Nlrp3, Myd88 to inhalation of GMA-SS. Conclusion This methodological approach has the potential to identify consistent, prominent and/or novel pathways and provides insight into mechanisms that contribute to pulmonary and systemic effects following toxicant exposure.

Evaluating music emotion recognition

DEFF Research Database (Denmark)

Sturm, Bob L.

2013-01-01

A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do...... not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER system, and conclude with recommendations....

Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

Energy Technology Data Exchange (ETDEWEB)

Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P [College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha (China)

2006-10-15

Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method.

Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

International Nuclear Information System (INIS)

Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P

2006-01-01

Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method

Acoustic Pattern Recognition on Android Devices

DEFF Research Database (Denmark)

Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild

2013-01-01

an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the Open......CV library is used for signal processing. We conclude that the approach presented here is a viable solution to pattern recognition problems. Since it requires no network connection, it shows promise in fields such as wildlife research....

Two-step membrane binding by the bacterial SRP receptor enable efficient and accurate Co-translational protein targeting.

Science.gov (United States)

Hwang Fu, Yu-Hsien; Huang, William Y C; Shen, Kuang; Groves, Jay T; Miller, Thomas; Shan, Shu-Ou

2017-07-28

The signal recognition particle (SRP) delivers ~30% of the proteome to the eukaryotic endoplasmic reticulum, or the bacterial plasma membrane. The precise mechanism by which the bacterial SRP receptor, FtsY, interacts with and is regulated at the target membrane remain unclear. Here, quantitative analysis of FtsY-lipid interactions at single-molecule resolution revealed a two-step mechanism in which FtsY initially contacts membrane via a Dynamic mode, followed by an SRP-induced conformational transition to a Stable mode that activates FtsY for downstream steps. Importantly, mutational analyses revealed extensive auto-inhibitory mechanisms that prevent free FtsY from engaging membrane in the Stable mode; an engineered FtsY pre-organized into the Stable mode led to indiscriminate targeting in vitro and disrupted FtsY function in vivo. Our results show that the two-step lipid-binding mechanism uncouples the membrane association of FtsY from its conformational activation, thus optimizing the balance between the efficiency and fidelity of co-translational protein targeting.

Autonomic nervous system dynamics for mood and emotional-state recognition significant advances in data acquisition, signal processing and classification

CERN Document Server

Valenza, Gaetano

2014-01-01

This monograph reports on advances in the measurement and study of autonomic nervous system (ANS) dynamics as a source of reliable and effective markers for mood state recognition and assessment of emotional responses. Its primary impact will be in affective computing and the application of emotion-recognition systems. Applicative studies of biosignals such as: electrocardiograms; electrodermal responses; respiration activity; gaze points; and pupil-size variation are covered in detail, and experimental results explain how to characterize the elicited affective levels and mood states pragmatically and accurately using the information thus extracted from the ANS. Nonlinear signal processing techniques play a crucial role in understanding the ANS physiology underlying superficially noticeable changes and provide important quantifiers of cardiovascular control dynamics. These have prognostic value in both healthy subjects and patients with mood disorders. Moreover, Autonomic Nervous System Dynamics for Mood and ...

Bacterial and parasitic diseases of parrots.

Science.gov (United States)

Doneley, Robert J T

2009-09-01

As wild-caught birds become increasingly rare in aviculture, there is a corresponding decline in the incidence of bacterial and parasitic problems and an increase in the recognition of the importance of maintaining health through better nutrition and husbandry. Nevertheless, the relatively close confines of captivity mean an increased pathogen load in the environment in which companion and aviary parrots live. This increased pathogen load leads to greater exposure of these birds to bacteria and parasites, and consequently a greater risk of infection and disease. This article discusses bacterial and parasitic infections in companion and aviary parrots. It includes the origins, pathogens, diagnosis, treatment, and some of the associated risk factors.

Lipopolysaccharide recognition, internalisation, signalling and other cellular effects

NARCIS (Netherlands)

Diks, S. H.; van Deventer, S. J.; Peppelenbosch, M. P.

2001-01-01

Despite the importance of bacterial lipopolysaccharide (LPS) in infection and inflammation, many aspects of LPS action remain poorly understood. Especially, the mechanisms by which cells recognise and react to endotoxins or endotoxin-containing particles and how cellular responses are translated

Exposure to bacterial signals does not alter pea aphids' survival upon a second challenge or investment in production of winged offspring.

Directory of Open Access Journals (Sweden)

Bas ter Braak

Full Text Available Pea aphids have an obligate nutritional symbiosis with the bacteria Buchneraaphidicola and frequently also harbor one or more facultative symbionts. Aphids are also susceptible to bacterial pathogen infections, and it has been suggested that aphids have a limited immune response towards such pathogen infections compared to other, more well-studied insects. However, aphids do possess at least some of the genes known to be involved in bacterial immune responses in other insects, and immune-competent hemocytes. One possibility is that immune priming with microbial elicitors could stimulate immune protection against subsequent bacterial infections, as has been observed in several other insect systems. To address this hypothesis we challenged aphids with bacterial immune elicitors twenty-four hours prior to live bacterial pathogen infections and then compared their survival rates to aphids that were not pre-exposed to bacterial signals. Using two aphid genotypes, we found no evidence for immune protection conferred by immune priming during infections with either Serratia marcescens or with Escherichia coli. Immune priming was not altered by the presence of facultative, beneficial symbionts in the aphids. In the absence of inducible immune protection, aphids may allocate energy towards other defense traits, including production of offspring with wings that could escape deteriorating conditions. To test this, we monitored the ratio of winged to unwinged offspring produced by adult mothers of a single clone that had been exposed to bacterial immune elicitors, to live E. coli infections or to no challenge. We found no correlation between immune challenge and winged offspring production, suggesting that this mechanism of defense, which functions upon exposure to fungal pathogens, is not central to aphid responses to bacterial infections.

Autophagy and bacterial clearance: a not so clear picture

OpenAIRE

Mostowy, Serge

2012-01-01

Autophagy, an intracellular degradation process highly conserved from yeast to humans, is viewed as an important defence mechanism to clear intracellular bacteria. However, recent work has shown that autophagy may have different roles during different bacterial infections that restrict bacterial replication (antibacterial autophagy), act in cell autonomous signalling (non-bacterial autophagy) or support bacterial replication (pro-bacterial autophagy). This review will focus on newfound intera...

Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

Science.gov (United States)

Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

2015-01-01

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

Forensic Speaker Recognition Law Enforcement and Counter-Terrorism

CERN Document Server

Patil, Hemant

2012-01-01

Forensic Speaker Recognition: Law Enforcement and Counter-Terrorism is an anthology of the research findings of 35 speaker recognition experts from around the world. The volume provides a multidimensional view of the complex science involved in determining whether a suspect’s voice truly matches forensic speech samples, collected by law enforcement and counter-terrorism agencies, that are associated with the commission of a terrorist act or other crimes. While addressing such topics as the challenges of forensic case work, handling speech signal degradation, analyzing features of speaker recognition to optimize voice verification system performance, and designing voice applications that meet the practical needs of law enforcement and counter-terrorism agencies, this material all sounds a common theme: how the rigors of forensic utility are demanding new levels of excellence in all aspects of speaker recognition. The contributors are among the most eminent scientists in speech engineering and signal process...

Pattern recognition and classification an introduction

CERN Document Server

Dougherty, Geoff

2012-01-01

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer visi

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.

Dissecting Bacterial Cell Wall Entry and Signaling in Eukaryotic Cells: an Actin-Dependent Pathway Parallels Platelet-Activating Factor Receptor-Mediated Endocytosis.

Science.gov (United States)

Loh, Lip Nam; Gao, Geli; Tuomanen, Elaine I

2017-01-03

The Gram-positive bacterial cell wall (CW) peptidoglycan-teichoic acid complex is released into the host environment during bacterial metabolism or death. It is a highly inflammatory Toll-like receptor 2 (TLR2) ligand, and previous in vivo studies have demonstrated its ability to recapitulate pathological features of pneumonia and meningitis. We report that an actin-dependent pathway is involved in the internalization of the CW by epithelial and endothelial cells, in addition to the previously described platelet-activating factor receptor (PAFr)-dependent uptake pathway. Unlike the PAFr-dependent pathway, which is mediated by clathrin and dynamin and does not lead to signaling, the alternative pathway is sensitive to 5-(N-ethyl-N-isopropyl) amiloride (EIPA) and engenders Rac1, Cdc42, and phosphatidylinositol 3-kinase (PI3K) signaling. Upon internalization by this macropinocytosis-like pathway, CW is trafficked to lysosomes. Intracellular CW trafficking is more complex than previously recognized and suggests multiple points of interaction with and without innate immune signaling. Streptococcus pneumoniae is a major human pathogen infecting the respiratory tract and brain. It is an established model organism for understanding how infection injures the host. During infection or bacterial growth, bacteria shed their cell wall (CW) into the host environment and trigger inflammation. A previous study has shown that CW enters and crosses cell barriers by interacting with a receptor on the surfaces of host cells, termed platelet-activating factor receptor (PAFr). In the present study, by using cells that are depleted of PAFr, we identified a second pathway with features of macropinocytosis, which is a receptor-independent fluid uptake mechanism by cells. Each pathway contributes approximately the same amount of cell wall trafficking, but the PAFr pathway is silent, while the new pathway appears to contribute to the host inflammatory response to CW insult. Copyright © 2017

HuAc: Human Activity Recognition Using Crowdsourced WiFi Signals and Skeleton Data

Directory of Open Access Journals (Sweden)

Linlin Guo

2018-01-01

Full Text Available The joint of WiFi-based and vision-based human activity recognition has attracted increasing attention in the human-computer interaction, smart home, and security monitoring fields. We propose HuAc, the combination of WiFi-based and Kinect-based activity recognition system, to sense human activity in an indoor environment with occlusion, weak light, and different perspectives. We first construct a WiFi-based activity recognition dataset named WiAR to provide a benchmark for WiFi-based activity recognition. Then, we design a mechanism of subcarrier selection according to the sensitivity of subcarriers to human activities. Moreover, we optimize the spatial relationship of adjacent skeleton joints and draw out a corresponding relationship between CSI and skeleton-based activity recognition. Finally, we explore the fusion information of CSI and crowdsourced skeleton joints to achieve the robustness of human activity recognition. We implemented HuAc using commercial WiFi devices and evaluated it in three kinds of scenarios. Our results show that HuAc achieves an average accuracy of greater than 93% using WiAR dataset.

Models of Recognition, Repetition Priming, and Fluency : Exploring a New Framework

Science.gov (United States)

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

2012-01-01

We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely…

The ARTT motif and a unified structural understanding of substraterecognition in ADP ribosylating bacterial toxins and eukaryotic ADPribosyltransferases

Energy Technology Data Exchange (ETDEWEB)

Han, S.; Tainer, J.A.

2001-08-01

ADP-ribosylation is a widely occurring and biologically critical covalent chemical modification process in pathogenic mechanisms, intracellular signaling systems, DNA repair, and cell division. The reaction is catalyzed by ADP-ribosyltransferases, which transfer the ADP-ribose moiety of NAD to a target protein with nicotinamide release. A family of bacterial toxins and eukaryotic enzymes has been termed the mono-ADP-ribosyltransferases, in distinction to the poly-ADP-ribosyltransferases, which catalyze the addition of multiple ADP-ribose groups to the carboxyl terminus of eukaryotic nucleoproteins. Despite the limited primary sequence homology among the different ADP-ribosyltransferases, a central cleft bearing NAD-binding pocket formed by the two perpendicular b-sheet core has been remarkably conserved between bacterial toxins and eukaryotic mono- and poly-ADP-ribosyltransferases. The majority of bacterial toxins and eukaryotic mono-ADP-ribosyltransferases are characterized by conserved His and catalytic Glu residues. In contrast, Diphtheria toxin, Pseudomonas exotoxin A, and eukaryotic poly-ADP-ribosyltransferases are characterized by conserved Arg and catalytic Glu residues. The NAD-binding core of a binary toxin and a C3-like toxin family identified an ARTT motif (ADP-ribosylating turn-turn motif) that is implicated in substrate specificity and recognition by structural and mutagenic studies. Here we apply structure-based sequence alignment and comparative structural analyses of all known structures of ADP-ribosyltransfeases to suggest that this ARTT motif is functionally important in many ADP-ribosylating enzymes that bear a NAD binding cleft as characterized by conserved Arg and catalytic Glu residues. Overall, structure-based sequence analysis reveals common core structures and conserved active sites of ADP-ribosyltransferases to support similar NAD binding mechanisms but differing mechanisms of target protein binding via sequence variations within the ARTT

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

Science.gov (United States)

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

2013-09-27

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

Effects of Pre-Experimental Knowledge on Recognition Memory

Science.gov (United States)

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

2011-01-01

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

From Off-line to On-line Handwriting Recognition

NARCIS (Netherlands)

Lallican, P.; Viard-Gaudin, C.; Knerr, S.

2004-01-01

On-line handwriting includes more information on time order of the writing signal and on the dynamics of the writing process than off-line handwriting. Therefore, on-line recognition systems achieve higher recognition rates. This can be concluded from results reported in the literature, and has been

Are Haar-like Rectangular Features for Biometric Recognition Reducible?

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2013-01-01

Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features...... which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal...... and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features...

Source Separation via Spectral Masking for Speech Recognition Systems

Directory of Open Access Journals (Sweden)

Gustavo Fernandes Rodrigues

2012-12-01

Full Text Available In this paper we present an insight into the use of spectral masking techniques in time-frequency domain, as a preprocessing step for the speech signal recognition. Speech recognition systems have their performance negatively affected in noisy environments or in the presence of other speech signals. The limits of these masking techniques for different levels of the signal-to-noise ratio are discussed. We show the robustness of the spectral masking techniques against four types of noise: white, pink, brown and human speech noise (bubble noise. The main contribution of this work is to analyze the performance limits of recognition systems  using spectral masking. We obtain an increase of 18% on the speech hit rate, when the speech signals were corrupted by other speech signals or bubble noise, with different signal-to-noise ratio of approximately 1, 10 and 20 dB. On the other hand, applying the ideal binary masks to mixtures corrupted by white, pink and brown noise, results an average growth of 9% on the speech hit rate, with the same different signal-to-noise ratio. The experimental results suggest that the masking spectral techniques are more suitable for the case when it is applied a bubble noise, which is produced by human speech, than for the case of applying white, pink and brown noise.

Electromyographic Grasp Recognition for a Five Fingered Robotic Hand

Directory of Open Access Journals (Sweden)

Nayan M. Kakoty

2012-09-01

Full Text Available This paper presents classification of grasp types based on surface electromyographic signals. Classification is through radial basis function kernel support vector machine using sum of wavelet decomposition coefficients of the EMG signals. In a study involving six subjects, we achieved an average recognition rate of 86%. The electromyographic grasp recognition together with a 8-bit microcontroller has been employed to control a fivefingered robotic hand to emulate six grasp types used during 70% daily living activities.

Physics of Automatic Target Recognition

CERN Document Server

Sadjadi, Firooz

2007-01-01

Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filt...

Get rich quick: the signal to respond procedure reveals the time course of semantic richness effects during visual word recognition.

Science.gov (United States)

Hargreaves, Ian S; Pexman, Penny M

2014-05-01

According to several current frameworks, semantic processing involves an early influence of language-based information followed by later influences of object-based information (e.g., situated simulations; Santos, Chaigneau, Simmons, & Barsalou, 2011). In the present study we examined whether these predictions extend to the influence of semantic variables in visual word recognition. We investigated the time course of semantic richness effects in visual word recognition using a signal-to-respond (STR) paradigm fitted to a lexical decision (LDT) and a semantic categorization (SCT) task. We used linear mixed effects to examine the relative contributions of language-based (number of senses, ARC) and object-based (imageability, number of features, body-object interaction ratings) descriptions of semantic richness at four STR durations (75, 100, 200, and 400ms). Results showed an early influence of number of senses and ARC in the SCT. In both LDT and SCT, object-based effects were the last to influence participants' decision latencies. We interpret our results within a framework in which semantic processes are available to influence word recognition as a function of their availability over time, and of their relevance to task-specific demands. Copyright © 2014 Elsevier B.V. All rights reserved.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

Science.gov (United States)

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Bacterial Exposures and Associations with Atopy and Asthma in Children.

Directory of Open Access Journals (Sweden)

Maria Valkonen

Full Text Available The increase in prevalence of asthma and atopic diseases in Western countries has been linked to aspects of microbial exposure patterns of people. It remains unclear which microbial aspects contribute to the protective farm effect.The objective of this study was to identify bacterial groups associated with prevalence of asthma and atopy, and to quantify indoor exposure to some of these bacterial groups.A DNA fingerprinting technique, denaturing gradient gel electrophoresis (DGGE, was applied to mattress dust samples of farm children and control children in the context of the GABRIEL Advanced study. Associations between signals in DGGE and atopy, asthma and other allergic health outcomes were analyzed. Quantitative DNA based assays (qPCR for four bacterial groups were applied on the dust samples to seek quantitative confirmation of associations indicated in DNA fingerprinting.Several statistically significant associations between individual bacterial signals and also bacterial diversity in DGGE and health outcomes in children were observed. The majority of these associations showed inverse relationships with atopy, less so with asthma. Also, in a subsequent confirmation study using a quantitative method (qPCR, higher mattress levels of specifically targeted bacterial groups - Mycobacterium spp., Bifidobacteriaceae spp. and two different clusters of Clostridium spp. - were associated with a lower prevalence of atopy.DNA fingerprinting proved useful in identifying bacterial signals that were associated with atopy in particular. These findings were quantitatively confirmed for selected bacterial groups with a second method. High correlations between the different bacterial exposures impede a clear attribution of protective effects to one specific bacterial group. More diverse bacterial flora in mattress dust may link to microbial exposure patterns that protect against development of atopic diseases.

Automatic shape recognition of a fast transient signal

International Nuclear Information System (INIS)

Charles, Gilbert.

1976-01-01

A system was developed to recognize if the shape of a signal x(t) is similar (or identical) to the one of an element yi(t) of an ensemble S composed by N known signals, that are memorised. x(t) is a time limited T 2 ) give the similarity measure of two signals. To solve the problem of the digital recording of the signals x(t) two devices were realized: a digital-to-analog converter which permits the recording of fast transient signals (band pass>1GHz, sampling-frequency approximately 100GHz, resolution: 9 bits, 576 samples); an automatic attenuator which scales the signal x(t) before the digitalization (the band pass is 70MHz at -1dB). A theoretical analysis permits to determine what must be the resolution of the digital-to-analog converter as a fonction of the signal-caracteristics and of the wanted precision for the calculus of rho 2 [fr

Man machine interface based on speech recognition

International Nuclear Information System (INIS)

Jorge, Carlos A.F.; Aghina, Mauricio A.C.; Mol, Antonio C.A.; Pereira, Claudio M.N.A.

2007-01-01

This work reports the development of a Man Machine Interface based on speech recognition. The system must recognize spoken commands, and execute the desired tasks, without manual interventions of operators. The range of applications goes from the execution of commands in an industrial plant's control room, to navigation and interaction in virtual environments. Results are reported for isolated word recognition, the isolated words corresponding to the spoken commands. For the pre-processing stage, relevant parameters are extracted from the speech signals, using the cepstral analysis technique, that are used for isolated word recognition, and corresponds to the inputs of an artificial neural network, that performs recognition tasks. (author)

Orientation Encoding and Viewpoint Invariance in Face Recognition: Inferring Neural Properties from Large-Scale Signals.

Science.gov (United States)

Ramírez, Fernando M

2018-05-01

Viewpoint-invariant face recognition is thought to be subserved by a distributed network of occipitotemporal face-selective areas that, except for the human anterior temporal lobe, have been shown to also contain face-orientation information. This review begins by highlighting the importance of bilateral symmetry for viewpoint-invariant recognition and face-orientation perception. Then, monkey electrophysiological evidence is surveyed describing key tuning properties of face-selective neurons-including neurons bimodally tuned to mirror-symmetric face-views-followed by studies combining functional magnetic resonance imaging (fMRI) and multivariate pattern analyses to probe the representation of face-orientation and identity information in humans. Altogether, neuroimaging studies suggest that face-identity is gradually disentangled from face-orientation information along the ventral visual processing stream. The evidence seems to diverge, however, regarding the prevalent form of tuning of neural populations in human face-selective areas. In this context, caveats possibly leading to erroneous inferences regarding mirror-symmetric coding are exposed, including the need to distinguish angular from Euclidean distances when interpreting multivariate pattern analyses. On this basis, this review argues that evidence from the fusiform face area is best explained by a view-sensitive code reflecting head angular disparity, consistent with a role of this area in face-orientation perception. Finally, the importance is stressed of explicit models relating neural properties to large-scale signals.

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.

Prompt recognition of brain states by their EEG signals

DEFF Research Database (Denmark)

Peters, B.O.; Pfurtscheller, G.; Flyvbjerg, H.

1997-01-01

Brain states corresponding to intention of movement of left and right index finger and right foot are classified by a ''committee'' of artificial neural networks processing individual channels of 56-electrode electroencephalograms (EEGs). Correct recognition is achieved in 83% of cases...

Automatic recognition of the unconscious reactions from physiological signals

NARCIS (Netherlands)

Ivonin, L.; Chang, H.M.; Chen, W.; Rauterberg, G.W.M.; Holzinger, A.; Ziefle, M.; Hitz, M.; Debevc, M.

2013-01-01

While the research in affective computing has been exclusively dealing with the recognition of explicit affective and cognitive states, carefully designed psychological and neuroimaging studies indicated that a considerable part of human experiences is tied to a deeper level of a psyche and not

Exploratory Data Analysis of Acceleration Signals to Select Light-Weight and Accurate Features for Real-Time Activity Recognition on Smartphones

Directory of Open Access Journals (Sweden)

Seok-Won Lee

2013-09-01

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

Pyoverdine, the Major Siderophore in Pseudomonas aeruginosa, Evades NGAL Recognition

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Mary E. Peek

2012-01-01

Full Text Available Pseudomonas aeruginosa is the most common pathogen that persists in the cystic fibrosis lungs. Bacteria such as P. aeruginosa secrete siderophores (iron-chelating molecules and the host limits bacterial growth by producing neutrophil-gelatinase-associated lipocalin (NGAL that specifically scavenges bacterial siderophores, therefore preventing bacteria from establishing infection. P. aeruginosa produces a major siderophore known as pyoverdine, found to be important for bacterial virulence and biofilm development. We report that pyoverdine did not bind to NGAL, as measured by tryptophan fluorescence quenching, while enterobactin bound to NGAL effectively causing a strong response. The experimental data indicate that pyoverdine evades NGAL recognition. We then employed a molecular modeling approach to simulate the binding of pyoverdine to human NGAL using NGAL’s published crystal structures. The docking of pyoverdine to NGAL predicted nine different docking positions; however, neither apo- nor ferric forms of pyoverdine docked into the ligand-binding site in the calyx of NGAL where siderophores are known to bind. The molecular modeling results offer structural support that pyoverdine does not bind to NGAL, confirming the results obtained in the tryptophan quenching assay. The data suggest that pyoverdine is a stealth siderophore that evades NGAL recognition allowing P. aeruginosa to establish chronic infections in CF lungs.

One process is not enough! A speed-accuracy tradeoff study of recognition memory.

Science.gov (United States)

Boldini, Angela; Russo, Riccardo; Avons, S E

2004-04-01

Speed-accuracy tradeoff (SAT) methods have been used to contrast single- and dual-process accounts of recognition memory. In these procedures, subjects are presented with individual test items and are required to make recognition decisions under various time constraints. In this experiment, we presented word lists under incidental learning conditions, varying the modality of presentation and level of processing. At test, we manipulated the interval between each visually presented test item and a response signal, thus controlling the amount of time available to retrieve target information. Study-test modality match had a beneficial effect on recognition accuracy at short response-signal delays (deep than from shallow processing at study only at relatively long response-signal delays (> or =300 msec). The results are congruent with views suggesting that both fast familiarity and slower recollection processes contribute to recognition memory.

sEMG-Based Gesture Recognition with Convolution Neural Networks

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Zhen Ding

2018-06-01

Full Text Available The traditional classification methods for limb motion recognition based on sEMG have been deeply researched and shown promising results. However, information loss during feature extraction reduces the recognition accuracy. To obtain higher accuracy, the deep learning method was introduced. In this paper, we propose a parallel multiple-scale convolution architecture. Compared with the state-of-art methods, the proposed architecture fully considers the characteristics of the sEMG signal. Larger sizes of kernel filter than commonly used in other CNN-based hand recognition methods are adopted. Meanwhile, the characteristics of the sEMG signal, that is, muscle independence, is considered when designing the architecture. All the classification methods were evaluated on the NinaPro database. The results show that the proposed architecture has the highest recognition accuracy. Furthermore, the results indicate that parallel multiple-scale convolution architecture with larger size of kernel filter and considering muscle independence can significantly increase the classification accuracy.

Binding of Signal Recognition Particle Gives Ribosome/Nascent Chain Complexes a Competitive Advantage in Endoplasmic Reticulum Membrane Interaction

Science.gov (United States)

Neuhof, Andrea; Rolls, Melissa M.; Jungnickel, Berit; Kalies, Kai-Uwe; Rapoport, Tom A.

1998-01-01

Most secretory and membrane proteins are sorted by signal sequences to the endoplasmic reticulum (ER) membrane early during their synthesis. Targeting of the ribosome-nascent chain complex (RNC) involves the binding of the signal sequence to the signal recognition particle (SRP), followed by an interaction of ribosome-bound SRP with the SRP receptor. However, ribosomes can also independently bind to the ER translocation channel formed by the Sec61p complex. To explain the specificity of membrane targeting, it has therefore been proposed that nascent polypeptide-associated complex functions as a cytosolic inhibitor of signal sequence- and SRP-independent ribosome binding to the ER membrane. We report here that SRP-independent binding of RNCs to the ER membrane can occur in the presence of all cytosolic factors, including nascent polypeptide-associated complex. Nontranslating ribosomes competitively inhibit SRP-independent membrane binding of RNCs but have no effect when SRP is bound to the RNCs. The protective effect of SRP against ribosome competition depends on a functional signal sequence in the nascent chain and is also observed with reconstituted proteoliposomes containing only the Sec61p complex and the SRP receptor. We conclude that cytosolic factors do not prevent the membrane binding of ribosomes. Instead, specific ribosome targeting to the Sec61p complex is provided by the binding of SRP to RNCs, followed by an interaction with the SRP receptor, which gives RNC–SRP complexes a selective advantage in membrane targeting over nontranslating ribosomes. PMID:9436994

Hepatitis B virus polymerase blocks pattern recognition receptor signaling via interaction with DDX3: implications for immune evasion.

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Haifeng Wang

Full Text Available Viral infection leads to induction of pattern-recognition receptor signaling, which leads to interferon regulatory factor (IRF activation and ultimately interferon (IFN production. To establish infection, many viruses have strategies to evade the innate immunity. For the hepatitis B virus (HBV, which causes chronic infection in the liver, the evasion strategy remains uncertain. We now show that HBV polymerase (Pol blocks IRF signaling, indicating that HBV Pol is the viral molecule that effectively counteracts host innate immune response. In particular, HBV Pol inhibits TANK-binding kinase 1 (TBK1/IkappaB kinase-epsilon (IKKepsilon, the effector kinases of IRF signaling. Intriguingly, HBV Pol inhibits TBK1/IKKepsilon activity by disrupting the interaction between IKKepsilon and DDX3 DEAD box RNA helicase, which was recently shown to augment TBK1/IKKepsilon activity. This unexpected role of HBV Pol may explain how HBV evades innate immune response in the early phase of the infection. A therapeutic implication of this work is that a strategy to interfere with the HBV Pol-DDX3 interaction might lead to the resolution of life-long persistent infection.

Mapping the signal peptide binding and oligomer contact sites of the core subunit of the pea twin arginine protein translocase.

Science.gov (United States)

Ma, Xianyue; Cline, Kenneth

2013-03-01

Twin arginine translocation (Tat) systems of thylakoid and bacterial membranes transport folded proteins using the proton gradient as the sole energy source. Tat substrates have hydrophobic signal peptides with an essential twin arginine (RR) recognition motif. The multispanning cpTatC plays a central role in Tat operation: It binds the signal peptide, directs translocase assembly, and may facilitate translocation. An in vitro assay with pea (Pisum sativum) chloroplasts was developed to conduct mutagenesis and analysis of cpTatC functions. Ala scanning mutagenesis identified mutants defective in substrate binding and receptor complex assembly. Mutations in the N terminus (S1) and first stromal loop (S2) caused specific defects in signal peptide recognition. Cys matching between substrate and imported cpTatC confirmed that S1 and S2 directly and specifically bind the RR proximal region of the signal peptide. Mutations in four lumen-proximal regions of cpTatC were defective in receptor complex assembly. Copurification and Cys matching analyses suggest that several of the lumen proximal regions may be important for cpTatC-cpTatC interactions. Surprisingly, RR binding domains of adjacent cpTatCs directed strong cpTatC-cpTatC cross-linking. This suggests clustering of binding sites on the multivalent receptor complex and explains the ability of Tat to transport cross-linked multimers. Transport of substrate proteins cross-linked to the signal peptide binding site tentatively identified mutants impaired in the translocation step.

Physiological arousal in processing recognition information

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Guy Hochman

2010-07-01

Full Text Available The recognition heuristic (RH; Goldstein and Gigerenzer, 2002 suggests that, when applicable, probabilistic inferences are based on a noncompensatory examination of whether an object is recognized or not. The overall findings on the processes that underlie this fast and frugal heuristic are somewhat mixed, and many studies have expressed the need for considering a more compensatory integration of recognition information. Regardless of the mechanism involved, it is clear that recognition has a strong influence on choices, and this finding might be explained by the fact that recognition cues arouse affect and thus receive more attention than cognitive cues. To test this assumption, we investigated whether recognition results in a direct affective signal by measuring physiological arousal (i.e., peripheral arterial tone in the established city-size task. We found that recognition of cities does not directly result in increased physiological arousal. Moreover, the results show that physiological arousal increased with increasing inconsistency between recognition information and additional cue information. These findings support predictions derived by a compensatory Parallel Constraint Satisfaction model rather than predictions of noncompensatory models. Additional results concerning confidence ratings, response times, and choice proportions further demonstrated that recognition information and other cognitive cues are integrated in a compensatory manner.

Cyclic GMP-AMP as an Endogenous Second Messenger in Innate Immune Signaling by Cytosolic DNA.

Science.gov (United States)

Kato, Kazuki; Omura, Hiroki; Ishitani, Ryuichiro; Nureki, Osamu

2017-06-20

The innate immune system functions as the first line of defense against invading bacteria and viruses. In this context, the cGAS/STING [cyclic guanosine monophosphate (GMP)-adenosine monophosphate (AMP) synthase/STING] signaling axis perceives the nonself DNA associated with bacterial and viral infections, as well as the leakage of self DNA by cellular dysfunction and stresses, to elicit the host's immune responses. In this pathway, the noncanonical cyclic dinucleotide 2',3'-cyclic GMP-AMP (2',3'-cGAMP) functions as a second messenger for signal transduction: 2',3'-cGAMP is produced by the enzyme cGAS upon its recognition of double-stranded DNA, and then the 2',3'-cGAMP is recognized by the receptor STING to induce the phosphorylation of downstream factors, including TBK1 (TANK binding kinase 1) and IRF3 (interferon regulatory factor 3). Numerous crystal structures of the components of this cGAS/STING signaling axis have been reported and these clarify the structural basis for their signal transduction mechanisms. In this review, we summarize recent progress made in the structural dissection of this signaling pathway and indicate possible directions of forthcoming research.

Sonic Hedgehog Signaling Regulates Hematopoietic Stem/Progenitor Cell Activation during the Granulopoietic Response to Systemic Bacterial Infection.

Science.gov (United States)

Shi, Xin; Wei, Shengcai; Simms, Kevin J; Cumpston, Devan N; Ewing, Thomas J; Zhang, Ping

2018-01-01

Activation and reprogramming of hematopoietic stem/progenitor cells play a critical role in the granulopoietic response to bacterial infection. Our current study determined the significance of Sonic hedgehog (SHH) signaling in the regulation of hematopoietic precursor cell activity during the host defense response to systemic bacterial infection. Bacteremia was induced in male Balb/c mice via intravenous injection (i.v.) of Escherichia coli (5 × 10 7 CFUs/mouse). Control mice received i.v. saline. SHH protein level in bone marrow cell (BMC) lysates was markedly increased at both 24 and 48 h of bacteremia. By contrast, the amount of soluble SHH ligand in marrow elutes was significantly reduced. These contrasting alterations suggested that SHH ligand release from BMCs was reduced and/or binding of soluble SHH ligand to BMCs was enhanced. At both 12 and 24 h of bacteremia, SHH mRNA expression by BMCs was significantly upregulated. This upregulation of SHH mRNA expression was followed by a marked increase in SHH protein expression in BMCs. Activation of the ERK1/2-SP1 pathway was involved in mediating the upregulation of SHH gene expression. The major cell type showing the enhancement of SHH expression in the bone marrow was lineage positive cells. Gli1 positioned downstream of the SHH receptor activation serves as a key component of the hedgehog (HH) pathway. Primitive hematopoietic precursor cells exhibited the highest level of baseline Gli1 expression, suggesting that they were active cells responding to SHH ligand stimulation. Along with the increased expression of SHH in the bone marrow, expression of Gli1 by marrow cells was significantly upregulated at both mRNA and protein levels following bacteremia. This enhancement of Gli1 expression was correlated with activation of hematopoietic stem/progenitor cell proliferation. Mice with Gli1 gene deletion showed attenuation in activation of marrow hematopoietic stem/progenitor cell proliferation and inhibition

FPGA-Based Implementation of Lithuanian Isolated Word Recognition Algorithm

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Tomyslav Sledevič

2013-05-01

Full Text Available The paper describes the FPGA-based implementation of Lithuanian isolated word recognition algorithm. FPGA is selected for parallel process implementation using VHDL to ensure fast signal processing at low rate clock signal. Cepstrum analysis was applied to features extraction in voice. The dynamic time warping algorithm was used to compare the vectors of cepstrum coefficients. A library of 100 words features was created and stored in the internal FPGA BRAM memory. Experimental testing with speaker dependent records demonstrated the recognition rate of 94%. The recognition rate of 58% was achieved for speaker-independent records. Calculation of cepstrum coefficients lasted for 8.52 ms at 50 MHz clock, while 100 DTWs took 66.56 ms at 25 MHz clock.Article in Lithuanian

From bacterial to human dihydrouridine synthase: automated structure determination

Energy Technology Data Exchange (ETDEWEB)

Whelan, Fiona, E-mail: fiona.whelan@york.ac.uk; Jenkins, Huw T., E-mail: fiona.whelan@york.ac.uk [The University of York, Heslington, York YO10 5DD (United Kingdom); Griffiths, Samuel C. [University of Oxford, Headington, Oxford OX3 7BN (United Kingdom); Byrne, Robert T. [Ludwig-Maximilians-University Munich, Feodor-Lynen-Strasse 25, 81377 Munich (Germany); Dodson, Eleanor J.; Antson, Alfred A., E-mail: fiona.whelan@york.ac.uk [The University of York, Heslington, York YO10 5DD (United Kingdom)

2015-06-30

The crystal structure of a human dihydrouridine synthase, an enzyme associated with lung cancer, with 18% sequence identity to a T. maritima enzyme, has been determined at 1.9 Å resolution by molecular replacement after extensive molecular remodelling of the template. The reduction of uridine to dihydrouridine at specific positions in tRNA is catalysed by dihydrouridine synthase (Dus) enzymes. Increased expression of human dihydrouridine synthase 2 (hDus2) has been linked to pulmonary carcinogenesis, while its knockdown decreased cancer cell line viability, suggesting that it may serve as a valuable target for therapeutic intervention. Here, the X-ray crystal structure of a construct of hDus2 encompassing the catalytic and tRNA-recognition domains (residues 1–340) determined at 1.9 Å resolution is presented. It is shown that the structure can be determined automatically by phenix.mr-rosetta starting from a bacterial Dus enzyme with only 18% sequence identity and a significantly divergent structure. The overall fold of the human Dus2 is similar to that of bacterial enzymes, but has a larger recognition domain and a unique three-stranded antiparallel β-sheet insertion into the catalytic domain that packs next to the recognition domain, contributing to domain–domain interactions. The structure may inform the development of novel therapeutic approaches in the fight against lung cancer.

From bacterial to human dihydrouridine synthase: automated structure determination

International Nuclear Information System (INIS)

Whelan, Fiona; Jenkins, Huw T.; Griffiths, Samuel C.; Byrne, Robert T.; Dodson, Eleanor J.; Antson, Alfred A.

2015-01-01

The crystal structure of a human dihydrouridine synthase, an enzyme associated with lung cancer, with 18% sequence identity to a T. maritima enzyme, has been determined at 1.9 Å resolution by molecular replacement after extensive molecular remodelling of the template. The reduction of uridine to dihydrouridine at specific positions in tRNA is catalysed by dihydrouridine synthase (Dus) enzymes. Increased expression of human dihydrouridine synthase 2 (hDus2) has been linked to pulmonary carcinogenesis, while its knockdown decreased cancer cell line viability, suggesting that it may serve as a valuable target for therapeutic intervention. Here, the X-ray crystal structure of a construct of hDus2 encompassing the catalytic and tRNA-recognition domains (residues 1–340) determined at 1.9 Å resolution is presented. It is shown that the structure can be determined automatically by phenix.mr-rosetta starting from a bacterial Dus enzyme with only 18% sequence identity and a significantly divergent structure. The overall fold of the human Dus2 is similar to that of bacterial enzymes, but has a larger recognition domain and a unique three-stranded antiparallel β-sheet insertion into the catalytic domain that packs next to the recognition domain, contributing to domain–domain interactions. The structure may inform the development of novel therapeutic approaches in the fight against lung cancer

Signal-to-Signal Ratio Independent Speaker Identification for Co-channel Speech Signals

DEFF Research Database (Denmark)

Saeidi, Rahim; Mowlaee, Pejman; Kinnunen, Tomi

2010-01-01

In this paper, we consider speaker identification for the co-channel scenario in which speech mixture from speakers is recorded by one microphone only. The goal is to identify both of the speakers from their mixed signal. High recognition accuracies have already been reported when an accurately...

Exploration into the spatial and temporal mechanisms of bacterial polarity

DEFF Research Database (Denmark)

Ebersbach, Gitte; Jacobs-Wagner, Christine; Charbon, Gitte Ebersbach

2007-01-01

The recognition of bacterial asymmetry is not new: the first high-resolution microscopy studies revealed that bacteria come in a multitude of shapes and sometimes carry asymmetrically localized external structures such as flagella on the cell surface. Even so, the idea that bacteria could have...... polarity in bacteria....

Detecting Release of Bacterial dsDNA into the Host Cytosol Using Fluorescence Microscopy.

Science.gov (United States)

Dreier, Roland Felix; Santos, José Carlos; Broz, Petr

2018-01-01

Recognition of pathogens by the innate immune system relies on germline-encoded pattern recognition receptors (PRRs) that recognize unique microbial molecules, so-called pathogen-associated molecular patterns (PAMPs). Nucleic acids and their derivatives are one of the most important groups of PAMPs, and are recognized by a number of surface-associated as well as cytosolic PRRs. Cyclic GMP-AMP synthase (cGAS) recognizes the presence of pathogen- or host-derived dsDNA in the cytosol and initiates type-I-IFN production. Here, we describe a methodology that allows for evaluating the association of cGAS with released bacterial dsDNA during Francisella novicida infection of macrophages, by fluorescence confocal microscopy. This method can be adapted to the study of cGAS-dependent responses elicited by other intracellular bacterial pathogens and in other cell types.

Development of a System for Automatic Recognition of Speech

Directory of Open Access Journals (Sweden)

Roman Jarina

2003-01-01

Full Text Available The article gives a review of a research on processing and automatic recognition of speech signals (ARR at the Department of Telecommunications of the Faculty of Electrical Engineering, University of iilina. On-going research is oriented to speech parametrization using 2-dimensional cepstral analysis, and to an application of HMMs and neural networks for speech recognition in Slovak language. The article summarizes achieved results and outlines future orientation of our research in automatic speech recognition.

Waveguide-type optical circuits for recognition of optical 8QAM-coded label

Science.gov (United States)

Surenkhorol, Tumendemberel; Kishikawa, Hiroki; Goto, Nobuo; Gonchigsumlaa, Khishigjargal

2017-10-01

Optical signal processing is expected to be applied in network nodes. In photonic routers, label recognition is one of the important functions. We have studied different kinds of label recognition methods so far for on-off keying, binary phase-shift keying, quadrature phase-shift keying, and 16 quadrature amplitude modulation-coded labels. We propose a method based on waveguide circuits to recognize an optical eight quadrature amplitude modulation (8QAM)-coded label by simple passive optical signal processing. The recognition of the proposed method is theoretically analyzed and numerically simulated by the finite difference beam propagation method. The noise tolerance is discussed, and bit-error rate against optical signal-to-noise ratio is evaluated. The scalability of the proposed method is also discussed theoretically for two-symbol length 8QAM-coded labels.

A Host-Produced Autoinducer-2 Mimic Activates Bacterial Quorum Sensing.

Science.gov (United States)

Ismail, Anisa S; Valastyan, Julie S; Bassler, Bonnie L

2016-04-13

Host-microbial symbioses are vital to health; nonetheless, little is known about the role crosskingdom signaling plays in these relationships. In a process called quorum sensing, bacteria communicate with one another using extracellular signal molecules called autoinducers. One autoinducer, AI-2, is proposed to promote interspecies bacterial communication, including in the mammalian gut. We show that mammalian epithelia produce an AI-2 mimic activity in response to bacteria or tight-junction disruption. This AI-2 mimic is detected by the bacterial AI-2 receptor, LuxP/LsrB, and can activate quorum-sensing-controlled gene expression, including in the enteric pathogen Salmonella typhimurium. AI-2 mimic activity is induced when epithelia are directly or indirectly exposed to bacteria, suggesting that a secreted bacterial component(s) stimulates its production. Mutagenesis revealed genes required for bacteria to both detect and stimulate production of the AI-2 mimic. These findings uncover a potential role for the mammalian AI-2 mimic in fostering crosskingdom signaling and host-bacterial symbioses. Copyright © 2016 Elsevier Inc. All rights reserved.

Wavelet analysis and it's applications to recognition of nuclear explosion and lightning

International Nuclear Information System (INIS)

Zhang Zhongshan; Zhang Enshan; Gao Chunxia

1999-01-01

An approach to feature extraction and recognition of the characteristic signal is studied. And the method is applied to recognition of nuclear explosions and lightning. The results show the method is valid

Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

Science.gov (United States)

Kim, Jonghwa; André, Elisabeth

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user's emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.

Dielectric and ferroelectric sensing based on molecular recognition in Cu(1,10-phenlothroline)2SeO4.(diol) systems

Science.gov (United States)

Ye, Heng-Yun; Liao, Wei-Qiang; Zhou, Qionghua; Zhang, Yi; Wang, Jinlan; You, Yu-Meng; Wang, Jin-Yun; Chen, Zhong-Ning; Li, Peng-Fei; Fu, Da-Wei; Huang, Songping D.; Xiong, Ren-Gen

2017-02-01

The process of molecular recognition is the assembly of two or more molecules through weak interactions. Information in the process of molecular recognition can be transmitted to us via physical signals, which may find applications in sensing and switching. The conventional signals are mainly limited to light signal. Here, we describe the recognition of diols with Cu(1,10-phenlothroline)2SeO4 and the transduction of discrete recognition events into dielectric and/or ferroelectric signals. We observe that systems of Cu(1,10-phenlothroline)2SeO4.(diol) exhibit significant dielectric and/or ferroelectric dependence on different diol molecules. The compounds including ethane-1,2-diol or propane-1,2-diol just show small temperature-dependent dielectric anomalies and no reversible polarization, while the compound including ethane-1,3-diol shows giant temperature-dependent dielectric anomalies as well as ferroelectric reversible spontaneous polarization. This finding shows that dielectricity and/or ferroelectricity has the potential to be used for signalling molecular recognition.

Automatic Emotion Recognition in Speech: Possibilities and Significance

Directory of Open Access Journals (Sweden)

Milana Bojanić

2009-12-01

Full Text Available Automatic speech recognition and spoken language understanding are crucial steps towards a natural humanmachine interaction. The main task of the speech communication process is the recognition of the word sequence, but the recognition of prosody, emotion and stress tags may be of particular importance as well. This paper discusses thepossibilities of recognition emotion from speech signal in order to improve ASR, and also provides the analysis of acoustic features that can be used for the detection of speaker’s emotion and stress. The paper also provides a short overview of emotion and stress classification techniques. The importance and place of emotional speech recognition is shown in the domain of human-computer interactive systems and transaction communication model. The directions for future work are given at the end of this work.

Evaluation of blind signal separation methods

NARCIS (Netherlands)

Schobben, D.W.E.; Torkkola, K.; Smaragdis, P.

1999-01-01

Recently many new Blind Signal Separation BSS algorithms have been introduced Authors evaluate the performance of their algorithms in various ways Among these are speech recognition rates plots of separated signals plots of cascaded mixingunmixing impulse responses and signal to noise ratios Clearly

Interfering with bacterial gossip

DEFF Research Database (Denmark)

Bjarnsholt, Thomas; Tolker-Nielsen, Tim; Givskov, Michael

2011-01-01

that appropriately target bacteria in their relevant habitat with the aim of mitigating their destructive impact on patients. In this review we describe molecular mechanisms involved in “bacterial gossip” (more scientifically referred to as quorum sensing (QS) and c-di-GMP signaling), virulence, biofilm formation...

Using probability density function in the procedure for recognition of the type of physical exercise

Directory of Open Access Journals (Sweden)

Cakić Nikola

2017-01-01

Full Text Available This paper presents a method for recognition of physical exercises, using only a triaxial accelerometer of a smartphone. The smartphone itself is free to move inside subject's pocket. Exercises for leg muscle strengthening from subject's standing position squat, right knee rise and lunge with right leg were analyzed. All exercises were performed with the accelerometric sensor of a smartphone placed in the pocket next to the leg used for exercises. In order to test the proposed recognition method, the knee rise exercise of the opposite leg with the same position of the sensor was randomly selected. Filtering of the raw accelerometric signals was carried out using Butterworth tenth-order low-pass filter. The filtered signals from each of the three axes were described using three signal descriptors. After the descriptors were calculated, a probability density function was constructed for each of the descriptors. The program that implemented the proposed recognition method was executed online within an Android application of the smartphone. Signals from two male and two female subjects were considered as a reference for exercise recognition. The exercise recognition accuracy was 94.22% for three performed exercises, and 85.33% for all four considered exercises.

Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model

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Lokesh Selvaraj

2014-01-01

Full Text Available Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO is suggested. The suggested methodology contains four stages, namely, (i denoising, (ii feature mining (iii, vector quantization, and (iv IPSO based hidden Markov model (HMM technique (IP-HMM. At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC, mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

Function and Dynamics of Tetraspanins during Antigen Recognition and Immunological Synapse Formation

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Vera eRocha-Perugini

2016-01-01

Full Text Available Tetraspanin-enriched microdomains (TEMs are specialized membrane platforms driven by protein-protein interactions that integrate membrane receptors and adhesion molecules. Tetraspanins participate in antigen recognition and presentation by antigen presenting cells (APCs through the organization of pattern recognition receptors (PRRs and their downstream induced-signaling, as well as the regulation of MHC-II-peptide trafficking. T lymphocyte activation is triggered upon specific recognition of antigens present on the APC surface during immunological synapse (IS formation. This dynamic process is characterized by a defined spatial organization involving the compartmentalization of receptors and adhesion molecules in specialized membrane domains that are connected to the underlying cytoskeleton and signaling molecules. Tetraspanins contribute to the spatial organization and maturation of the IS by controlling receptor clustering and local accumulation of adhesion receptors and integrins, their downstream signaling and linkage to the actin cytoskeleton. This review offers a perspective on the important role of TEMs in the regulation of antigen recognition and presentation, and in the dynamics of IS architectural organization.

Function and Dynamics of Tetraspanins during Antigen Recognition and Immunological Synapse Formation

Science.gov (United States)

Rocha-Perugini, Vera; Sánchez-Madrid, Francisco; Martínez del Hoyo, Gloria

2016-01-01

Tetraspanin-enriched microdomains (TEMs) are specialized membrane platforms driven by protein–protein interactions that integrate membrane receptors and adhesion molecules. Tetraspanins participate in antigen recognition and presentation by antigen-­presenting cells (APCs) through the organization of pattern-recognition receptors (PRRs) and their downstream-induced signaling, as well as the regulation of MHC-II–peptide trafficking. T lymphocyte activation is triggered upon specific recognition of antigens present on the APC surface during immunological synapse (IS) formation. This dynamic process is characterized by a defined spatial organization involving the compartmentalization of receptors and adhesion molecules in specialized membrane domains that are connected to the underlying cytoskeleton and signaling molecules. Tetraspanins contribute to the spatial organization and maturation of the IS by controlling receptor clustering and local accumulation of adhesion receptors and integrins, their downstream signaling, and linkage to the actin cytoskeleton. This review offers a perspective on the important role of TEMs in the regulation of antigen recognition and presentation and in the dynamics of IS architectural organization. PMID:26793193

Hybrid Speaker Recognition Using Universal Acoustic Model

Science.gov (United States)

Nishimura, Jun; Kuroda, Tadahiro

We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.

Enzymatic recognition of DNA replication origins

International Nuclear Information System (INIS)

Stayton, M.M.; Bertsch, L.; Biswas, S.

1983-01-01

In this paper we discuss the process of recognition of the complementary-strand origin with emphasis on RNA polymerase action in priming M13 DNA replication, the role of primase in G4 DNA replication, and the function of protein n, a priming protein, during primosome assembly. These phage systems do not require several of the bacterial DNA replication enzymes, particularly those involved in the regulation of chromosome copy number of the initiatiion of replication of duplex DNA. 51 references, 13 figures, 1 table

Testing Theories of Recognition Memory by Predicting Performance Across Paradigms

Science.gov (United States)

Smith, David G.; Duncan, Matthew J. J.

2004-01-01

Signal-detection theory (SDT) accounts of recognition judgments depend on the assumption that recognition decisions result from a single familiarity-based process. However, fits of a hybrid SDT model, called dual-process theory (DPT), have provided evidence for the existence of a second, recollection-based process. In 2 experiments, the authors…

EBR-II [Experimental Breeder Reactor-II] system surveillance using pattern recognition software

International Nuclear Information System (INIS)

Mott, J.E.; Radtke, W.H.; King, R.W.

1986-02-01

The problem of most accurately determining the Experimental Breeder Reactor-II (EBR-II) reactor outlet temperature from currently available plant signals is investigated. Historically, the reactor outlet pipe was originally instrumented with 8 temperature sensors but, during 22 years of operation, all these instruments have failed except for one remaining thermocouple, and its output had recently become suspect. Using pattern recognition methods to compare values of 129 plant signals for similarities over a 7 month period spanning reconfiguration of the core and recalibration of many plant signals, it was determined that the remaining reactor outlet pipe thermocouple is still useful as an indicator of true mixed mean reactor outlet temperature. Application of this methodology to investigate one specific signal has automatically validated the vast majority of the 129 signals used for pattern recognition and also highlighted a few inconsistent signals for further investigation

Hand Gesture Recognition Using Ultrasonic Waves

KAUST Repository

AlSharif, Mohammed Hussain

2016-04-01

Gesturing is a natural way of communication between people and is used in our everyday conversations. Hand gesture recognition systems are used in many applications in a wide variety of fields, such as mobile phone applications, smart TVs, video gaming, etc. With the advances in human-computer interaction technology, gesture recognition is becoming an active research area. There are two types of devices to detect gestures; contact based devices and contactless devices. Using ultrasonic waves for determining gestures is one of the ways that is employed in contactless devices. Hand gesture recognition utilizing ultrasonic waves will be the focus of this thesis work. This thesis presents a new method for detecting and classifying a predefined set of hand gestures using a single ultrasonic transmitter and a single ultrasonic receiver. This method uses a linear frequency modulated ultrasonic signal. The ultrasonic signal is designed to meet the project requirements such as the update rate, the range of detection, etc. Also, it needs to overcome hardware limitations such as the limited output power, transmitter, and receiver bandwidth, etc. The method can be adapted to other hardware setups. Gestures are identified based on two main features; range estimation of the moving hand and received signal strength (RSS). These two factors are estimated using two simple methods; channel impulse response (CIR) and cross correlation (CC) of the reflected ultrasonic signal from the gesturing hand. A customized simple hardware setup was used to classify a set of hand gestures with high accuracy. The detection and classification were done using methods of low computational cost. This makes the proposed method to have a great potential for the implementation in many devices including laptops and mobile phones. The predefined set of gestures can be used for many control applications.

Single-Walled Carbon Nanotubes as Fluorescence Biosensors for Pathogen Recognition in Water Systems

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Venkata K. K. Upadhyayula

2008-01-01

Full Text Available The possibility of using single-walled carbon nanotubes (SWCNTs aggregates as fluorescence sensors for pathogen recognition in drinking water treatment applications has been studied. Batch adsorption study is conducted to adsorb large concentrations of Staphylococcus aureus aureus SH 1000 and Escherichia coli pKV-11 on single-walled carbon nanotubes. Subsequently the immobilized bacteria are detected with confocal microscopy by coating the nanotubes with fluorescence emitting antibodies. The Freundlich adsorption equilibrium constant (k for S.aureus and E.coli determined from batch adsorption study was found to be 9×108 and 2×108 ml/g, respectively. The visualization of bacterial cells adsorbed on fluorescently modified carbon nanotubes is also clearly seen. The results indicate that hydrophobic single-walled carbon nanotubes have excellent bacterial adsorption capacity and fluorescent detection capability. This is an important advancement in designing fluorescence biosensors for pathogen recognition in water systems.

Bacterial Multidrug Efflux Pumps: Much More Than Antibiotic Resistance Determinants.

Science.gov (United States)

Blanco, Paula; Hernando-Amado, Sara; Reales-Calderon, Jose Antonio; Corona, Fernando; Lira, Felipe; Alcalde-Rico, Manuel; Bernardini, Alejandra; Sanchez, Maria Blanca; Martinez, Jose Luis

2016-02-16

Bacterial multidrug efflux pumps are antibiotic resistance determinants present in all microorganisms. With few exceptions, they are chromosomally encoded and present a conserved organization both at the genetic and at the protein levels. In addition, most, if not all, strains of a given bacterial species present the same chromosomally-encoded efflux pumps. Altogether this indicates that multidrug efflux pumps are ancient elements encoded in bacterial genomes long before the recent use of antibiotics for human and animal therapy. In this regard, it is worth mentioning that efflux pumps can extrude a wide range of substrates that include, besides antibiotics, heavy metals, organic pollutants, plant-produced compounds, quorum sensing signals or bacterial metabolites, among others. In the current review, we present information on the different functions that multidrug efflux pumps may have for the bacterial behaviour in different habitats as well as on their regulation by specific signals. Since, in addition to their function in non-clinical ecosystems, multidrug efflux pumps contribute to intrinsic, acquired, and phenotypic resistance of bacterial pathogens, the review also presents information on the search for inhibitors of multidrug efflux pumps, which are currently under development, in the aim of increasing the susceptibility of bacterial pathogens to antibiotics.

Are bacterial volatile compounds poisonous odors to a fungal pathogen Botrytis cinerea, alarm signals to Arabidopsis seedlings for eliciting induced resistance, or both?

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Choong-Min eRyu

2016-02-01

Full Text Available Biological control (biocontrol agents act on plants via numerous mechanisms, and can be used to protect plants from pathogens. Biocontrol agents can act directly as pathogen antagonists or competitors or indirectly to promote plant induced systemic resistance (ISR. Whether a biocontrol agent acts directly or indirectly depends on the specific strain and the pathosystem type. We reported previously that bacterial volatile organic compounds (VOCs are determinants for eliciting plant ISR. Emerging data suggest that bacterial VOCs also can directly inhibit fungal and plant growth. The aim of the current study was to differentiate direct and indirect mechanisms of bacterial VOC effects against Botrytis cinerea infection of Arabidopsis. Volatile emissions from Bacillus subtilis GB03 successfully protected Arabidopsis seedlings against B. cinerea. First, we investigated the direct effects of bacterial VOCs on symptom development and different phenological stages of B. cinerea including spore germination, mycelial attachment to the leaf surface, mycelial growth, and sporulation in vitro and in planta. Volatile emissions inhibited hyphal growth in a dose-dependent manner in vitro, and interfered with fungal attachment on the hydrophobic leaf surface. Second, the optimized bacterial concentration that did not directly inhibit fungal growth successfully protected Arabidopsis from fungal infection, which indicates that bacterial VOC-elicited plant ISR has a more important role in biocontrol than direct inhibition of fungal growth on Arabidopsis. We performed qRT-PCR to investigate the priming of the defense-related genes PR1, PDF1.2, and ChiB at 0, 12, 24, and 36 hours post-infection and 14 days after the start of plant exposure to bacterial VOCs. The results indicate that bacterial VOCs potentiate expression of PR1 and PDF1.2 but not ChiB, which stimulates SA- and JA-dependent signaling pathways in plant ISR and protects plants against pathogen

Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition.

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Wirsich, Jonathan; Bénar, Christian; Ranjeva, Jean-Philippe; Descoins, Médéric; Soulier, Elisabeth; Le Troter, Arnaud; Confort-Gouny, Sylviane; Liégeois-Chauvel, Catherine; Guye, Maxime

2014-10-15

Simultaneous EEG-fMRI has opened up new avenues for improving the spatio-temporal resolution of functional brain studies. However, this method usually suffers from poor EEG quality, especially for evoked potentials (ERPs), due to specific artifacts. As such, the use of EEG-informed fMRI analysis in the context of cognitive studies has particularly focused on optimizing narrow ERP time windows of interest, which ignores the rich diverse temporal information of the EEG signal. Here, we propose to use simultaneous EEG-fMRI to investigate the neural cascade occurring during face recognition in 14 healthy volunteers by using the successive ERP peaks recorded during the cognitive part of this process. N170, N400 and P600 peaks, commonly associated with face recognition, were successfully and reproducibly identified for each trial and each subject by using a group independent component analysis (ICA). For the first time we use this group ICA to extract several independent components (IC) corresponding to the sequence of activation and used single-trial peaks as modulation parameters in a general linear model (GLM) of fMRI data. We obtained an occipital-temporal-frontal stream of BOLD signal modulation, in accordance with the three successive IC-ERPs providing an unprecedented spatio-temporal characterization of the whole cognitive process as defined by BOLD signal modulation. By using this approach, the pattern of EEG-informed BOLD modulation provided improved characterization of the network involved than the fMRI-only analysis or the source reconstruction of the three ERPs; the latter techniques showing only two regions in common localized in the occipital lobe. Copyright © 2014 Elsevier Inc. All rights reserved.

Looking for myself: current multisensory input alters self-face recognition.

Science.gov (United States)

Tsakiris, Manos

2008-01-01

How do I know the person I see in the mirror is really me? Is it because I know the person simply looks like me, or is it because the mirror reflection moves when I move, and I see it being touched when I feel touch myself? Studies of face-recognition suggest that visual recognition of stored visual features inform self-face recognition. In contrast, body-recognition studies conclude that multisensory integration is the main cue to selfhood. The present study investigates for the first time the specific contribution of current multisensory input for self-face recognition. Participants were stroked on their face while they were looking at a morphed face being touched in synchrony or asynchrony. Before and after the visuo-tactile stimulation participants performed a self-recognition task. The results show that multisensory signals have a significant effect on self-face recognition. Synchronous tactile stimulation while watching another person's face being similarly touched produced a bias in recognizing one's own face, in the direction of the other person included in the representation of one's own face. Multisensory integration can update cognitive representations of one's body, such as the sense of ownership. The present study extends this converging evidence by showing that the correlation of synchronous multisensory signals also updates the representation of one's face. The face is a key feature of our identity, but at the same time is a source of rich multisensory experiences used to maintain or update self-representations.

LPI Radar Waveform Recognition Based on Time-Frequency Distribution

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Ming Zhang

2016-10-01

Full Text Available In this paper, an automatic radar waveform recognition system in a high noise environment is proposed. Signal waveform recognition techniques are widely applied in the field of cognitive radio, spectrum management and radar applications, etc. We devise a system to classify the modulating signals widely used in low probability of intercept (LPI radar detection systems. The radar signals are divided into eight types of classifications, including linear frequency modulation (LFM, BPSK (Barker code modulation, Costas codes and polyphase codes (comprising Frank, P1, P2, P3 and P4. The classifier is Elman neural network (ENN, and it is a supervised classification based on features extracted from the system. Through the techniques of image filtering, image opening operation, skeleton extraction, principal component analysis (PCA, image binarization algorithm and Pseudo–Zernike moments, etc., the features are extracted from the Choi–Williams time-frequency distribution (CWD image of the received data. In order to reduce the redundant features and simplify calculation, the features selection algorithm based on mutual information between classes and features vectors are applied. The superiority of the proposed classification system is demonstrated by the simulations and analysis. Simulation results show that the overall ratio of successful recognition (RSR is 94.7% at signal-to-noise ratio (SNR of −2 dB.

Towards Contactless Silent Speech Recognition Based on Detection of Active and Visible Articulators Using IR-UWB Radar.

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Shin, Young Hoon; Seo, Jiwon

2016-10-29

People with hearing or speaking disabilities are deprived of the benefits of conventional speech recognition technology because it is based on acoustic signals. Recent research has focused on silent speech recognition systems that are based on the motions of a speaker's vocal tract and articulators. Because most silent speech recognition systems use contact sensors that are very inconvenient to users or optical systems that are susceptible to environmental interference, a contactless and robust solution is hence required. Toward this objective, this paper presents a series of signal processing algorithms for a contactless silent speech recognition system using an impulse radio ultra-wide band (IR-UWB) radar. The IR-UWB radar is used to remotely and wirelessly detect motions of the lips and jaw. In order to extract the necessary features of lip and jaw motions from the received radar signals, we propose a feature extraction algorithm. The proposed algorithm noticeably improved speech recognition performance compared to the existing algorithm during our word recognition test with five speakers. We also propose a speech activity detection algorithm to automatically select speech segments from continuous input signals. Thus, speech recognition processing is performed only when speech segments are detected. Our testbed consists of commercial off-the-shelf radar products, and the proposed algorithms are readily applicable without designing specialized radar hardware for silent speech processing.

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Science.gov (United States)

Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

2015-01-01

A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

Speech emotion recognition methods: A literature review

Science.gov (United States)

Basharirad, Babak; Moradhaseli, Mohammadreza

2017-10-01

Recently, attention of the emotional speech signals research has been boosted in human machine interfaces due to availability of high computation capability. There are many systems proposed in the literature to identify the emotional state through speech. Selection of suitable feature sets, design of a proper classifications methods and prepare an appropriate dataset are the main key issues of speech emotion recognition systems. This paper critically analyzed the current available approaches of speech emotion recognition methods based on the three evaluating parameters (feature set, classification of features, accurately usage). In addition, this paper also evaluates the performance and limitations of available methods. Furthermore, it highlights the current promising direction for improvement of speech emotion recognition systems.

Ubiquitous Structural Signaling in Bacterial Phytochromes

NARCIS (Netherlands)

Björling, Alexander; Berntsson, Oskar; Takala, Heikki; Gallagher, Kevin D.; Patel, Hardik; Gustavsson, Emil; St. Peter, Rachael; Duong, Phu; Nugent, Angela; Zhang, Fan; Berntsen, Peter; Appio, Roberto; Rajkovic, Ivan; Lehtivuori, Heli; Panman, Matthijs R.; Hoernke, Maria; Niebling, Stephan; Harimoorthy, Rajiv; Lamparter, Tilman; Stojković, Emina A.; Ihalainen, Janne A.; Westenhoff, Sebastian

2015-01-01

The phytochrome family of light-switchable proteins has long been studied by biochemical, spectroscopic and crystallographic means, while a direct probe for global conformational signal propagation has been lacking. Using solution X-ray scattering, we find that the photosensory cores of several

Structures of SRP54 and SRP19, the two proteins that organize the ribonucleic core of the signal recognition particle from Pyrococcus furiosus.

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Pascal F Egea

Full Text Available In all organisms the Signal Recognition Particle (SRP, binds to signal sequences of proteins destined for secretion or membrane insertion as they emerge from translating ribosomes. In Archaea and Eucarya, the conserved ribonucleoproteic core is composed of two proteins, the accessory protein SRP19, the essential GTPase SRP54, and an evolutionarily conserved and essential SRP RNA. Through the GTP-dependent interaction between the SRP and its cognate receptor SR, ribosomes harboring nascent polypeptidic chains destined for secretion are dynamically transferred to the protein translocation apparatus at the membrane. We present here high-resolution X-ray structures of SRP54 and SRP19, the two RNA binding components forming the core of the signal recognition particle from the hyper-thermophilic archaeon Pyrococcus furiosus (Pfu. The 2.5 A resolution structure of free Pfu-SRP54 is the first showing the complete domain organization of a GDP bound full-length SRP54 subunit. In its ras-like GTPase domain, GDP is found tightly associated with the protein. The flexible linker that separates the GTPase core from the hydrophobic signal sequence binding M domain, adopts a purely alpha-helical structure and acts as an articulated arm allowing the M domain to explore multiple regions as it scans for signal peptides as they emerge from the ribosomal tunnel. This linker is structurally coupled to the GTPase catalytic site and likely to propagate conformational changes occurring in the M domain through the SRP RNA upon signal sequence binding. Two different 1.8 A resolution crystal structures of free Pfu-SRP19 reveal a compact, rigid and well-folded protein even in absence of its obligate SRP RNA partner. Comparison with other SRP19*SRP RNA structures suggests the rearrangement of a disordered loop upon binding with the RNA through a reciprocal induced-fit mechanism and supports the idea that SRP19 acts as a molecular scaffold and a chaperone, assisting the SRP

SSVEP recognition using common feature analysis in brain-computer interface.

Science.gov (United States)

Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2015-04-15

Canonical correlation analysis (CCA) has been successfully applied to steady-state visual evoked potential (SSVEP) recognition for brain-computer interface (BCI) application. Although the CCA method outperforms the traditional power spectral density analysis through multi-channel detection, it requires additionally pre-constructed reference signals of sine-cosine waves. It is likely to encounter overfitting in using a short time window since the reference signals include no features from training data. We consider that a group of electroencephalogram (EEG) data trials recorded at a certain stimulus frequency on a same subject should share some common features that may bear the real SSVEP characteristics. This study therefore proposes a common feature analysis (CFA)-based method to exploit the latent common features as natural reference signals in using correlation analysis for SSVEP recognition. Good performance of the CFA method for SSVEP recognition is validated with EEG data recorded from ten healthy subjects, in contrast to CCA and a multiway extension of CCA (MCCA). Experimental results indicate that the CFA method significantly outperformed the CCA and the MCCA methods for SSVEP recognition in using a short time window (i.e., less than 1s). The superiority of the proposed CFA method suggests it is promising for the development of a real-time SSVEP-based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.

Control of Target Molecular Recognition in a Small Pore Space with Biomolecule-Recognition Gating Membrane.

Science.gov (United States)

Okuyama, Hiroto; Oshiba, Yuhei; Ohashi, Hidenori; Yamaguchi, Takeo

2018-05-01

A biomolecule-recognition gating membrane, which introduces thermosensitive graft polymer including molecular recognition receptor into porous membrane substrate, can close its pores by recognizing target biomolecule. The present study reports strategies for improving both versatility and sensitivity of the gating membrane. First, the membrane is fabricated by introducing the receptor via a selectively reactive click reaction improving the versatility. Second, the sensitivity of the membrane is enhanced via an active delivering method of the target molecules into the pores. In the method, the tiny signal of the target biomolecule is amplified as obvious pressure change. Furthermore, this offers 15 times higher sensitivity compared to the previously reported passive delivering method (membrane immersion to sample solution) with significantly shorter recognition time. The improvement will aid in applying the gating membrane to membrane sensors in medical fields. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Window Size Impact in Human Activity Recognition

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Oresti Banos

2014-04-01

Full Text Available Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1–2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities.

New signal processing methods for the evaluation of eddy current NDT data

International Nuclear Information System (INIS)

Anon.

1987-01-01

Signal processing and pattern recognition methods play a crucial role in a number of areas associated with nondestructive evaluation. Defect characterization schemes often involve mapping the signal onto an appropriate feature domain and using pattern recognition techniques for classification. In addition, signal processing methods are also used to acquire, enhance, restore, and compress data. EPRI Project RP 2673-4 is concerned with developing new signal processing and pattern recognition techniques for evaluating eddy current signals. Efforts under this project have focused on three closely related areas. The thrust has been to: (1) develop a scheme to compress eddy current signals for the purposes of storing them in a compact form, (2) develop a robust clustering algorithm capable of discarding feature vectors that fall in the gray areas between clusters, and (3) investigate the feasibility of designing and developing a digital eddyscope

Bacterial Serine/Threonine Protein Kinases in Host-Pathogen Interactions*

Science.gov (United States)

Canova, Marc J.; Molle, Virginie

2014-01-01

In bacterial pathogenesis, monitoring and adapting to the dynamically changing environment in the host and an ability to disrupt host immune responses are critical. The virulence determinants of pathogenic bacteria include the sensor/signaling proteins of the serine/threonine protein kinase (STPK) family that have a dual role of sensing the environment and subverting specific host defense processes. STPKs can sense a wide range of signals and coordinate multiple cellular processes to mount an appropriate response. Here, we review some of the well studied bacterial STPKs that are essential virulence factors and that modify global host responses during infection. PMID:24554701

Bacterial serine/threonine protein kinases in host-pathogen interactions.

Science.gov (United States)

Canova, Marc J; Molle, Virginie

2014-04-04

In bacterial pathogenesis, monitoring and adapting to the dynamically changing environment in the host and an ability to disrupt host immune responses are critical. The virulence determinants of pathogenic bacteria include the sensor/signaling proteins of the serine/threonine protein kinase (STPK) family that have a dual role of sensing the environment and subverting specific host defense processes. STPKs can sense a wide range of signals and coordinate multiple cellular processes to mount an appropriate response. Here, we review some of the well studied bacterial STPKs that are essential virulence factors and that modify global host responses during infection.

Paracrine signaling in a bacterium.

Science.gov (United States)

López, Daniel; Vlamakis, Hera; Losick, Richard; Kolter, Roberto

2009-07-15

Cellular differentiation is triggered by extracellular signals that cause target cells to adopt a particular fate. Differentiation in bacteria typically involves autocrine signaling in which all cells in the population produce and respond to the same signal. Here we present evidence for paracrine signaling in bacterial populations-some cells produce a signal to which only certain target cells respond. Biofilm formation in Bacillus involves two centrally important signaling molecules, ComX and surfactin. ComX triggers the production of surfactin. In turn, surfactin causes a subpopulation of cells to produce an extracellular matrix. Cells that produced surfactin were themselves unable to respond to it. Likewise, once surfactin-responsive cells commenced matrix production, they no longer responded to ComX and could not become surfactin producers. Insensitivity to ComX was the consequence of the extracellular matrix as mutant cells unable to make matrix responded to both ComX and surfactin. Our results demonstrate that extracellular signaling was unidirectional, with one subpopulation producing a signal and a different subpopulation responding to it. Paracrine signaling in a bacterial population ensures the maintenance, over generations, of particular cell types even in the presence of molecules that would otherwise cause those cells to differentiate into other cell types.

Functional characterizations of RIG-I to GCRV and viral/bacterial PAMPs in grass carp Ctenopharyngodon idella.

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Lijun Chen

Full Text Available BACKGROUND: RIG-I (retinoic acid inducible gene-I is one of the key cytosolic pattern recognition receptors (PRRs for detecting nucleotide pathogen associated molecular patterns (PAMPs and mediating the induction of type I interferon and inflammatory cytokines in innate immune response. Though the mechanism is well characterized in mammals, the study of the accurate function of RIG-I in teleosts is still in its infancy. METHODOLOGY/PRINCIPAL FINDINGS: To clarify the functional characterizations of RIG-I in grass carp Ctenopharyngodon idella (CiRIG-I, six representative overexpression plasmids were constructed and transfected into C. idella kidney (CIK cell lines to obtain stably expressing recombinant proteins, respectively. A virus titer test and 96-well plate staining assay showed that all constructs exhibited the antiviral activity somewhat. The quantitative real-time RT-PCR (qRT-PCR demonstrated that mRNA expressions of CiIPS-1, CiIFN-I and CiMx2 were regulated by not only virus (GCRV or viral PAMP (poly(IC challenge but also bacterial PAMPs (LPS and PGN stimulation in the steadily transfected cells. The results showed that the full-length CiRIG-I played a key role in RLR pathway. The repressor domain (RD exerted an inhibitory function of the signaling channel under all utilized challenges. Caspase activation and recruitment domains (CARDs showed a positive role in GCRV and poly(I:C challenge. Helicase motifs were crucial for the signaling pathway upon LPS and PGN stimulation. Interestingly, ΔCARDs (CARDs deleted showed positive modulation in RIG-I signal transduction. CONCLUSIONS/SIGNIFICANCE: The results provided some novel insights into RIG-I sensing with a strikingly broad regulation in teleosts, responding not only to the dsRNA virus or synthetic dsRNA but also bacterial PAMPs.

Single-Walled Carbon Nano tubes as Fluorescence Biosensors for Pathogen Recognition in Water Systems

International Nuclear Information System (INIS)

Upadhyayula, V.K.K

2008-01-01

The possibility of using single-walled carbon nanotubes (SWCNTs) aggregates as fluorescence sensors for pathogen recognition in drinking water treatment applications has been studied. Batch adsorption study is conducted to adsorb large concentrations of Staphylococcus aureus aureus SH 1000 and Escherichia coli pKV-11 on single-walled carbon nanotubes. Subsequently the immobilized bacteria are detected with confocal microscopy by coating the nanotubes with fluorescence emitting antibodies. The Freundlich adsorption equilibrium constant (k) for S.aureus and E.coli determined from batch adsorption study was found to be 9 x108 and 2 x108 ml/g, respectively. The visualization of bacterial cells adsorbed on fluorescently modified carbon nanotubes is also clearly seen. The results indicate that hydrophobic single-walled carbon nanotubes have excellent bacterial adsorption capacity and fluorescent detection capability. This is an important advancement in designing fluorescence biosensors for pathogen recognition in water systems.

The Bacterial Microflora of Fish, Revised

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B. Austin

2006-01-01

Full Text Available The results of numerous studies indicate that fish possess bacterial populations on or in their skin, gills, digestive tract, and light-emitting organs. In addition, the internal organs (kidney, liver, and spleen of healthy fish may contain bacteria, but there is debate about whether or not muscle is actually sterile. Using traditional culture-dependent techniques, the numbers and taxonomic composition of the bacterial populations generally reflect those of the surrounding water. More modern culture-independent approaches have permitted the recognition of previously uncultured bacteria. The role of the organisms includes the ability to degrade complex molecules (therefore exercising a potential benefit in nutrition, to produce vitamins and polymers, and to be responsible for the emission of light by the light-emitting organs of deep-sea fish. Taxa, including Pseudomonas, may contribute to spoilage by the production of histamines in fish tissue.

Recall and recognition hypermnesia for Socratic stimuli.

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Kazén, Miguel; Solís-Macías, Víctor M

2016-01-01

In two experiments, we investigate hypermnesia, net memory improvements with repeated testing of the same material after a single study trial. In the first experiment, we found hypermnesia across three trials for the recall of word solutions to Socratic stimuli (dictionary-like definitions of concepts) replicating Erdelyi, Buschke, and Finkelstein and, for the first time using these materials, for their recognition. In the second experiment, we had two "yes/no" recognition groups, a Socratic stimuli group presented with concrete and abstract verbal materials and a word-only control group. Using signal detection measures, we found hypermnesia for concrete Socratic stimuli-and stable performance for abstract stimuli across three recognition tests. The control group showed memory decrements across tests. We interpret these findings with the alternative retrieval pathways (ARP) hypothesis, contrasting it with alternative theories of hypermnesia, such as depth of processing, generation and retrieve-recognise. We conclude that recognition hypermnesia for concrete Socratic stimuli is a reliable phenomenon, which we found in two experiments involving both forced-choice and yes/no recognition procedures.

Interfamily transfer of a plant pattern-recognition receptor confers broad-spectrum bacterial resistance

NARCIS (Netherlands)

Lacombe, S.; Rougon-Cardoso, A.; Sherwood, E.; Peeters, N.; Dahlbeck, D.; Esse, van H.P.; Smoker, M.; Rallapalli, G.; Thomma, B.P.H.J.; Staskawicz, B.; Jones, J.D.G.; Zipfel, C.

2010-01-01

Plant diseases cause massive losses in agriculture. Increasing the natural defenses of plants may reduce the impact of phytopathogens on agricultural productivity. Pattern-recognition receptors (PRRs) detect microbes by recognizing conserved pathogen-associated molecular patterns (PAMPs)1, 2, 3.

Carbon nanotubes as in vivo bacterial probes.

Science.gov (United States)

Bardhan, Neelkanth M; Ghosh, Debadyuti; Belcher, Angela M

2014-09-17

With the rise in antibiotic-resistant infections, non-invasive sensing of infectious diseases is increasingly important. Optical imaging, although safer and simpler, is less developed than other modalities such as radioimaging, due to low availability of target-specific molecular probes. Here we report carbon nanotubes (SWNTs) as bacterial probes for fluorescence imaging of pathogenic infections. We demonstrate that SWNTs functionalized using M13 bacteriophage (M13-SWNT) can distinguish between F'-positive and F'-negative bacterial strains. Moreover, through one-step modification, we attach an anti-bacterial antibody on M13-SWNT, making it easily tunable for sensing specific F'-negative bacteria. We illustrate detection of Staphylococcus aureus intramuscular infections, with ~3.4 × enhancement in fluorescence intensity over background. SWNT imaging presents lower signal spread ~0.08 × and higher signal amplification ~1.4 × , compared with conventional dyes. We show the probe offers greater ~5.7 × enhancement in imaging of S. aureus infective endocarditis. These biologically functionalized, aqueous-dispersed, actively targeted, modularly tunable SWNT probes offer new avenues for exploration of deeply buried infections.

Carbon nanotubes as in vivo bacterial probes

Science.gov (United States)

Bardhan, Neelkanth M.; Ghosh, Debadyuti; Belcher, Angela M.

2014-09-01

With the rise in antibiotic-resistant infections, non-invasive sensing of infectious diseases is increasingly important. Optical imaging, although safer and simpler, is less developed than other modalities such as radioimaging, due to low availability of target-specific molecular probes. Here we report carbon nanotubes (SWNTs) as bacterial probes for fluorescence imaging of pathogenic infections. We demonstrate that SWNTs functionalized using M13 bacteriophage (M13-SWNT) can distinguish between F‧-positive and F‧-negative bacterial strains. Moreover, through one-step modification, we attach an anti-bacterial antibody on M13-SWNT, making it easily tunable for sensing specific F‧-negative bacteria. We illustrate detection of Staphylococcus aureus intramuscular infections, with ~3.4 × enhancement in fluorescence intensity over background. SWNT imaging presents lower signal spread ~0.08 × and higher signal amplification ~1.4 × , compared with conventional dyes. We show the probe offers greater ~5.7 × enhancement in imaging of S. aureus infective endocarditis. These biologically functionalized, aqueous-dispersed, actively targeted, modularly tunable SWNT probes offer new avenues for exploration of deeply buried infections.

Feature selection in classification of eye movements using electrooculography for activity recognition.

Science.gov (United States)

Mala, S; Latha, K

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition.

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Directory of Open Access Journals (Sweden)

Jiangyi Qin

Full Text Available A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

Anti-signal recognition particle autoantibody ELISA validation and clinical associations.

Science.gov (United States)

Aggarwal, Rohit; Oddis, Chester V; Goudeau, Danielle; Fertig, Noreen; Metes, Ilinca; Stephens, Chad; Qi, Zengbiao; Koontz, Diane; Levesque, Marc C

2015-07-01

The aim of this study was to develop and validate a quantitative anti-signal recognition particle (SRP) autoantibody serum ELISA in patients with myositis and longitudinal association with myositis disease activity. We developed a serum ELISA using recombinant purified full-length human SRP coated on ELISA plates and a secondary antibody that bound human IgG to detect anti-SRP binding. Protein immunoprecipitation was used as the gold standard for the presence of anti-SRP. Serum samples from three groups were analysed: SRP(+) myositis subjects by immunoprecipitation, SRP(-) myositis subjects by immunoprecipitation and non-myositis controls. The ELISA's sensitivity, specificity, positive predictive value and negative predictive value were evaluated. Percentage agreement and test-retest reliability were assessed. Serial samples from seven SRP immunoprecipitation-positive subjects were also tested, along with serum muscle enzymes and manual muscle testing. Using immunoprecipitation, we identified 26 SRP(+) myositis patients and 77 SRP(-) controls (including 38 patients with necrotizing myopathy). Non-myositis control patients included SLE (n = 4) and SSc (n = 7) patients. Anti-SRP positivity by ELISA showed strong agreement (97.1%) with immunoprecipitation (κ = 0.94). The sensitivity, specificity, positive predictive value, and negative predictive value of the anti-SRP ELISA were 88, 100, 100 and 96, respectively. The area under the curve was 0.94, and test-retest reliability was strong (r = 0.91, P < 0.001). Serial samples showed that anti-SRP levels paralleled changes in muscle enzymes and manual muscle testing. We developed a quantitative ELISA for detecting serum anti-SRP autoantibodies and validated the assay in myositis. Longitudinal assessment of SRP levels by ELISA may be a useful biomarker for disease activity. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions

Engineering nanoparticles to silence bacterial communication

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Kristen Publicover Miller

2015-03-01

Full Text Available The alarming spread of bacterial resistance to traditional antibiotics has warranted the study of alternative antimicrobial agents. Quorum sensing is a chemical cell-to-cell communication mechanism utilized by bacteria to coordinate group behaviors and establish infections. Quorum sensing is integral to bacterial survival, and therefore provides a unique target for antimicrobial therapy. In this study, silicon dioxide nanoparticles (Si-NP were engineered to target the signaling molecules (i.e. acylhomoserine lactones (HSL used for quorum sensing in order to halt bacterial communication. Specifically, when Si-NP were surface functionalized with beta-cyclodextrin (beta-CD, then added to cultures of bacteria (Vibrio fischeri, whose luminous output depends upon HSL-mediated quorum sensing, the cell-to-cell communication was dramatically reduced. Reductions in luminescence were further verified by quantitative polymerase chain reaction (qPCR analyses of luminescence genes. Binding of AHLs to Si-NPs was examined using nuclear magnetic resonance (NMR spectroscopy. The results indicated that by delivering high concentrations of engineered NPs with associated quenching compounds, the chemical signals were removed from the immediate bacterial environment. In actively-metabolizing cultures, this treatment blocked the ability of bacteria to communicate and regulate quorum sensing, effectively silencing and isolating the cells. Si-NPs provide a scaffold and critical stepping-stone for more pointed developments in antimicrobial therapy, especially with regard to quorum sensing – a target that will reduce resistance pressures imposed by traditional antibiotics.

Molecular basis for convergent evolution of glutamate recognition by pentameric ligand-gated ion channels

DEFF Research Database (Denmark)

Lynagh, Timothy; Beech, Robin N.; Lalande, Maryline J.

2015-01-01

that glutamate recognition requires an arginine residue in the base of the binding site, which originated at least three distinct times according to phylogenetic analysis. Most remarkably, the arginine emerged on the principal face of the binding site in the Lophotrochozoan lineage, but 65 amino acids upstream......Glutamate is an indispensable neurotransmitter, triggering postsynaptic signals upon recognition by postsynaptic receptors. We questioned the phylogenetic position and the molecular details of when and where glutamate recognition arose in the glutamate-gated chloride channels. Experiments revealed......, on the complementary face, in the Ecdysozoan lineage. This combined experimental and computational approach throws new light on the evolution of synaptic signalling....

Recognition of power quality events by using multiwavelet-based neural networks

Energy Technology Data Exchange (ETDEWEB)

Kaewarsa, Suriya; Attakitmongcol, Kitti; Kulworawanichpong, Thanatchai [School of Electrical Engineering, Suranaree University of Technology, 111 University Avenue, Muang District, Nakhon Ratchasima 30000 (Thailand)

2008-05-15

Recognition of power quality events by analyzing the voltage and current waveform disturbances is a very important task for the power system monitoring. This paper presents a novel approach for the recognition of power quality disturbances using multiwavelet transform and neural networks. The proposed method employs the multiwavelet transform using multiresolution signal decomposition techniques working together with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, such as voltage sag, swell, interruption, notching, impulsive transient, and harmonic distortion show that the classifier can detect and classify different power quality signal types efficiency. (author)

The chemical structure of DNA sequence signals for RNA transcription

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George, D. G.; Dayhoff, M. O.

1982-01-01

The proposed recognition sites for RNA transcription for E. coli NRA polymerase, bacteriophage T7 RNA polymerase, and eukaryotic RNA polymerase Pol II are evaluated in the light of the requirements for efficient recognition. It is shown that although there is good experimental evidence that specific nucleic acid sequence patterns are involved in transcriptional regulation in bacteria and bacterial viruses, among the sequences now available, only in the case of the promoters recognized by bacteriophage T7 polymerase does it seem likely that the pattern is sufficient. It is concluded that the eukaryotic pattern that is investigated is not restrictive enough to serve as a recognition site.

Structural pattern recognition methods based on string comparison for fusion databases

International Nuclear Information System (INIS)

Dormido-Canto, S.; Farias, G.; Dormido, R.; Vega, J.; Sanchez, J.; Duro, N.; Vargas, H.; Ratta, G.; Pereira, A.; Portas, A.

2008-01-01

Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed

Structural pattern recognition methods based on string comparison for fusion databases

Energy Technology Data Exchange (ETDEWEB)

Dormido-Canto, S. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain)], E-mail: sebas@dia.uned.es; Farias, G.; Dormido, R. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain); Sanchez, J.; Duro, N.; Vargas, H. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Ratta, G.; Pereira, A.; Portas, A. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain)

2008-04-15

Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed.

Quorum sensing is a language of chemical signals and plays an ecological role in algal-bacterial interactions.

Science.gov (United States)

Zhou, Jin; Lyu, Yihua; Richlen, Mindy; Anderson, Donald M; Cai, Zhonghua

2016-01-01

Algae are ubiquitous in the marine environment, and the ways in which they interact with bacteria are of particular interest in marine ecology field. The interactions between primary producers and bacteria impact the physiology of both partners, alter the chemistry of their environment, and shape microbial diversity. Although algal-bacterial interactions are well known and studied, information regarding the chemical-ecological role of this relationship remains limited, particularly with respect to quorum sensing (QS), which is a system of stimuli and response correlated to population density. In the microbial biosphere, QS is pivotal in driving community structure and regulating behavioral ecology, including biofilm formation, virulence, antibiotic resistance, swarming motility, and secondary metabolite production. Many marine habitats, such as the phycosphere, harbour diverse populations of microorganisms and various signal languages (such as QS-based autoinducers). QS-mediated interactions widely influence algal-bacterial symbiotic relationships, which in turn determine community organization, population structure, and ecosystem functioning. Understanding infochemicals-mediated ecological processes may shed light on the symbiotic interactions between algae host and associated microbes. In this review, we summarize current achievements about how QS modulates microbial behavior, affects symbiotic relationships, and regulates phytoplankton chemical ecological processes. Additionally, we present an overview of QS-modulated co-evolutionary relationships between algae and bacterioplankton, and consider the potential applications and future perspectives of QS.

Chemical basis of prey recognition in thamnophiine snakes: the unexpected new roles of parvalbumins.

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Maïté Smargiassi

Full Text Available Detecting and locating prey are key to predatory success within trophic chains. Predators use various signals through specialized visual, olfactory, auditory or tactile sensory systems to pinpoint their prey. Snakes chemically sense their prey through a highly developed auxiliary olfactory sense organ, the vomeronasal organ (VNO. In natricine snakes that are able to feed on land and water, the VNO plays a critical role in predatory behavior by detecting cues, known as vomodors, which are produced by their potential prey. However, the chemical nature of these cues remains unclear. Recently, we demonstrated that specific proteins-parvalbumins-present in the cutaneous mucus of the common frog (Rana temporaria may be natural chemoattractive proteins for these snakes. Here, we show that parvalbumins and parvalbumin-like proteins, which are mainly intracellular, are physiologically present in the epidermal mucous cells and mucus of several frog and fish genera from both fresh and salt water. These proteins are located in many tissues and function as Ca(2+ buffers. In addition, we clarified the intrinsic role of parvalbumins present in the cutaneous mucus of amphibians and fishes. We demonstrate that these Ca(2+-binding proteins participate in innate bacterial defense mechanisms by means of calcium chelation. We show that these parvalbumins are chemoattractive for three different thamnophiine snakes, suggesting that these chemicals play a key role in their prey-recognition mechanism. Therefore, we suggest that recognition of parvalbumin-like proteins or other calcium-binding proteins by the VNO could be a generalized prey-recognition process in snakes. Detecting innate prey defense mechanism compounds may have driven the evolution of this predator-prey interaction.

Effects of training on recognition of musical instruments presented through cochlear implant simulations.

Science.gov (United States)

Driscoll, Virginia D; Oleson, Jacob; Jiang, Dingfeng; Gfeller, Kate

2009-01-01

The simulation of the CI (cochlear implant) signal presents a degraded representation of each musical instrument, which makes recognition difficult. To examine the efficiency and effectiveness of three types of training on recognition of musical instruments as presented through simulations of the sounds transmitted through a CI. Participants were randomly assigned to one of three training conditions: repeated exposure, feedback, and direct instruction. Sixty-six adults with normal hearing. Each participant completed three training sessions per week, over a five-week time period, in which they listened to the CI simulations of eight different musical instruments. Analyses on percent of instruments identified correctly showed statistically significant differences between recognition accuracy of the three training conditions (p different types of training are differentially effective with regard to improving recognition of musical instruments presented through a degraded signal, which has practical implications for the auditory rehabilitation of persons who use cochlear implants.

Bacterial tower of Babel --How cheating and lying diversify bacterial communication

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Eldar, Avigdor

2012-02-01

In microbial ``quorum sensing'' (QS) communication systems, microbes produce and respond to a signaling molecule, enabling a cooperative response at high cell densities. Many species of bacteria show fast, intraspecific, evolutionary divergence of their QS pathway specificity---signaling molecules activate cognate receptors in the same strain but fail to activate, and sometimes inhibit, those of other strains. Despite many molecular studies, it has remained unclear how a signaling molecule and receptor can coevolve, what maintains diversity, and what drives the evolution of cross-inhibition. Here I use mathematical analysis to show that when QS controls the production of extracellular enzymes ---``public goods''---diversification can readily evolve. Coevolution is positively selected by cycles of alternating ``cheating'' receptor mutations and ``cheating immunity'' signaling mutations. The maintenance of diversity and the evolution of cross-inhibition between strains are facilitated by facultative cheating between the competing strains. My results suggest a role for complex social strategies in the long-term evolution of QS systems. More generally, my model of QS divergence suggests a form of kin recognition where different kin types coexist in unstructured populations.

Opposing roles of Toll-like receptor and cytosolic DNA-STING signaling pathways for Staphylococcus aureus cutaneous host defense.

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Philip O Scumpia

2017-07-01

Full Text Available Successful host defense against pathogens requires innate immune recognition of the correct pathogen associated molecular patterns (PAMPs by pathogen recognition receptors (PRRs to trigger the appropriate gene program tailored to the pathogen. While many PRR pathways contribute to the innate immune response to specific pathogens, the relative importance of each pathway for the complete transcriptional program elicited has not been examined in detail. Herein, we used RNA-sequencing with wildtype and mutant macrophages to delineate the innate immune pathways contributing to the early transcriptional response to Staphylococcus aureus, a ubiquitous microorganism that can activate a wide variety of PRRs. Unexpectedly, two PRR pathways-the Toll-like receptor (TLR and Stimulator of Interferon Gene (STING pathways-were identified as dominant regulators of approximately 95% of the genes that were potently induced within the first four hours of macrophage infection with live S. aureus. TLR signaling predominantly activated a pro-inflammatory program while STING signaling activated an antiviral/type I interferon response with live but not killed S. aureus. This STING response was largely dependent on the cytosolic DNA sensor cyclic guanosine-adenosine synthase (cGAS. Using a cutaneous infection model, we found that the TLR and STING pathways played opposite roles in host defense to S. aureus. TLR signaling was required for host defense, with its absence reducing interleukin (IL-1β production and neutrophil recruitment, resulting in increased bacterial growth. In contrast, absence of STING signaling had the opposite effect, enhancing the ability to restrict the infection. These results provide novel insights into the complex interplay of innate immune signaling pathways triggered by S. aureus and uncover opposing roles of TLR and STING in cutaneous host defense to S. aureus.

Accessing Specific Peptide Recognition by Combinatorial Chemistry

DEFF Research Database (Denmark)

Li, Ming

Molecular recognition is at the basis of all processes for life, and plays a central role in many biological processes, such as protein folding, the structural organization of cells and organelles, signal transduction, and the immune response. Hence, my PhD project is entitled “Accessing Specific...... Peptide Recognition by Combinatorial Chemistry”. Molecular recognition is a specific interaction between two or more molecules through noncovalent bonding, such as hydrogen bonding, metal coordination, van der Waals forces, π−π, hydrophobic, or electrostatic interactions. The association involves kinetic....... Combinatorial chemistry was invented in 1980s based on observation of functional aspects of the adaptive immune system. It was employed for drug development and optimization in conjunction with high-throughput synthesis and screening. (chapter 2) Combinatorial chemistry is able to rapidly produce many thousands...

DMBT1 functions as pattern-recognition molecule for poly-sulfated and poly-phosphorylated ligands

DEFF Research Database (Denmark)

End, Caroline; Bikker, Floris; Renner, Marcus

2009-01-01

at unraveling the molecular basis of its function in mucosal protection and of its broad pathogen-binding specificity. We report that DMBT1 directly interacts with dextran sulfate sodium (DSS) and carrageenan, a structurally similar sulfated polysaccharide, which is used as a texturizer and thickener in human...... dietary products. However, binding of DMBT1 does not reduce the cytotoxic effects of these agents to intestinal epithelial cells in vitro. DSS and carrageenan compete for DMBT1-mediated bacterial aggregation via interaction with its bacterial-recognition motif. Competition and ELISA studies identify poly...

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

Science.gov (United States)

Zhang, Jianhai; Chen, Ming; Zhao, Shaokai; Hu, Sanqing; Shi, Zhiguo; Cao, Yu

2016-09-22

Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP). Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation). Furthermore, support vector machine (SVM) was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels' weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels). In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a contribution to the

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition

Directory of Open Access Journals (Sweden)

Jianhai Zhang

2016-09-01

Full Text Available Electroencephalogram (EEG signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP. Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation. Furthermore, support vector machine (SVM was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels’ weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels. In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a

Manipulation of host membranes by bacterial effectors.

Science.gov (United States)

Ham, Hyeilin; Sreelatha, Anju; Orth, Kim

2011-07-18

Bacterial pathogens interact with host membranes to trigger a wide range of cellular processes during the course of infection. These processes include alterations to the dynamics between the plasma membrane and the actin cytoskeleton, and subversion of the membrane-associated pathways involved in vesicle trafficking. Such changes facilitate the entry and replication of the pathogen, and prevent its phagocytosis and degradation. In this Review, we describe the manipulation of host membranes by numerous bacterial effectors that target phosphoinositide metabolism, GTPase signalling and autophagy.

Crystal structure and novel recognition motif of rho ADP-ribosylating C3 exoenzyme from Clostridium botulinum: structural insights for recognition specificity and catalysis.

Science.gov (United States)

Han, S; Arvai, A S; Clancy, S B; Tainer, J A

2001-01-05

Clostridium botulinum C3 exoenzyme inactivates the small GTP-binding protein family Rho by ADP-ribosylating asparagine 41, which depolymerizes the actin cytoskeleton. C3 thus represents a major family of the bacterial toxins that transfer the ADP-ribose moiety of NAD to specific amino acids in acceptor proteins to modify key biological activities in eukaryotic cells, including protein synthesis, differentiation, transformation, and intracellular signaling. The 1.7 A resolution C3 exoenzyme structure establishes the conserved features of the core NAD-binding beta-sandwich fold with other ADP-ribosylating toxins despite little sequence conservation. Importantly, the central core of the C3 exoenzyme structure is distinguished by the absence of an active site loop observed in many other ADP-ribosylating toxins. Unlike the ADP-ribosylating toxins that possess the active site loop near the central core, the C3 exoenzyme replaces the active site loop with an alpha-helix, alpha3. Moreover, structural and sequence similarities with the catalytic domain of vegetative insecticidal protein 2 (VIP2), an actin ADP-ribosyltransferase, unexpectedly implicates two adjacent, protruding turns, which join beta5 and beta6 of the toxin core fold, as a novel recognition specificity motif for this newly defined toxin family. Turn 1 evidently positions the solvent-exposed, aromatic side-chain of Phe209 to interact with the hydrophobic region of Rho adjacent to its GTP-binding site. Turn 2 evidently both places the Gln212 side-chain for hydrogen bonding to recognize Rho Asn41 for nucleophilic attack on the anomeric carbon of NAD ribose and holds the key Glu214 catalytic side-chain in the adjacent catalytic pocket. This proposed bipartite ADP-ribosylating toxin turn-turn (ARTT) motif places the VIP2 and C3 toxin classes into a single ARTT family characterized by analogous target protein recognition via turn 1 aromatic and turn 2 hydrogen-bonding side-chain moieties. Turn 2 centrally anchors

Bacterial RNA induces myocyte cellular dysfunction through the activation of PKR

Science.gov (United States)

Bleiblo, Farag; Michael, Paul; Brabant, Danielle; Ramana, Chilakamarti V.; Tai, TC; Saleh, Mazen; Parrillo, Joseph E.; Kumar, Anand

2012-01-01

Severe sepsis and the ensuing septic shock are serious life threatening conditions. These diseases are triggered by the host's over exuberant systemic response to the infecting pathogen. Several surveillance mechanisms have evolved to discriminate self from foreign RNA and accordingly trigger effective cellular responses to target the pathogenic threats. The RNA-dependent protein kinase (PKR) is a key component of the cytoplasmic RNA sensors involved in the recognition of viral double-stranded RNA (dsRNA). Here, we identify bacterial RNA as a distinct pathogenic pattern recognized by PKR. Our results indicate that natural RNA derived from bacteria directly binds to and activates PKR. We further show that bacterial RNA induces human cardiac myocyte apoptosis and identify the requirement for PKR in mediating this response. In addition to bacterial immunity, the results presented here may also have implications in cardiac pathophysiology. PMID:22833816

Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

Science.gov (United States)

Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

2017-01-01

Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

Random Deep Belief Networks for Recognizing Emotions from Speech Signals

Directory of Open Access Journals (Sweden)

Guihua Wen

2017-01-01

Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

Facial Emotion Recognition Using Context Based Multimodal Approach

Directory of Open Access Journals (Sweden)

Priya Metri

2011-12-01

Full Text Available Emotions play a crucial role in person to person interaction. In recent years, there has been a growing interest in improving all aspects of interaction between humans and computers. The ability to understand human emotions is desirable for the computer in several applications especially by observing facial expressions. This paper explores a ways of human-computer interaction that enable the computer to be more aware of the user’s emotional expressions we present a approach for the emotion recognition from a facial expression, hand and body posture. Our model uses multimodal emotion recognition system in which we use two different models for facial expression recognition and for hand and body posture recognition and then combining the result of both classifiers using a third classifier which give the resulting emotion . Multimodal system gives more accurate result than a signal or bimodal system

Bacterial proteases and virulence

DEFF Research Database (Denmark)

Frees, Dorte; Brøndsted, Lone; Ingmer, Hanne

2013-01-01

signalling to short-circuit host cell processes. Common to both intra- and extracellular proteases is the tight control of their proteolytic activities. In general, substrate recognition by the intracellular proteases is highly selective which is, in part, attributed to the chaperone activity associated...... tolerance to adverse conditions such as those experienced in the host. In the membrane, HtrA performs similar functions whereas the extracellular proteases, in close contact with host components, pave the way for spreading infections by degrading host matrix components or interfering with host cell...... with the proteases either encoded within the same polypeptide or on separate subunits. In contrast, substrate recognition by extracellular proteases is less selective and therefore these enzymes are generally expressed as zymogens to prevent premature proteolytic activity that would be detrimental to the cell...

A real time mobile-based face recognition with fisherface methods

Science.gov (United States)

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

2018-03-01

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

Metagenome-based diversity analyses suggest a strong locality signal for bacterial communities associated with oyster aquaculture farms in Ofunato Bay

KAUST Repository

Kobiyama, Atsushi

2018-04-30

Ofunato Bay, in Japan, is the home of buoy-and-rope-type oyster aquaculture activities. Since the oysters filter suspended materials and excrete organic matter into the seawater, bacterial communities residing in its vicinity may show dynamic changes depending on the oyster culture activities. We employed a shotgun metagenomic technique to study bacterial communities near oyster aquaculture facilities at the center of the bay (KSt. 2) and compared the results with those of two other localities far from the station, one to the northeast (innermost bay, KSt. 1) and the other to the southwest (bay entrance, KSt. 3). Seawater samples were collected every month from January to December 2015 from the surface (1 m) and deeper (8 or 10 m) layers of the three locations, and the sequentially filtered fraction on 0.2-μm membranes was sequenced on an Illumina MiSeq system. The acquired reads were uploaded to MG-RAST for KEGG functional abundance analysis, while taxonomic analyses at the phylum and genus levels were performed using MEGAN after parsing the BLAST output. Discrimination analyses were then performed using the ROC-AUC value of the cross validation, targeting the depth (shallow or deep), locality [(KSt. 1 + KSt. 2) vs. KSt 3; (KSt. 1 + KSt. 3) vs. KSt. 2 or the (KSt. 2 + KSt. 3) vs. KSt. 1] and seasonality (12 months). The matrix discrimination analysis on the adjacent 2 continuous seasons by ROC-AUC, which was based on the datasets that originated from different depths, localities and months, showed the strongest discrimination signal on the taxonomy matrix at the phylum level for the datasets from July to August compared with those from September to June, while the KEGG matrix showed the strongest signal for the datasets from March to June compared with those from July to February. Then, the locality combination was subjected to the same ROC-AUC discrimination analysis, resulting in significant differences between KSt. 2 and KSt. 1 + KSt. 3

Metagenome-based diversity analyses suggest a strong locality signal for bacterial communities associated with oyster aquaculture farms in Ofunato Bay

KAUST Repository

Kobiyama, Atsushi; Ikeo, Kazuho; Reza, Md. Shaheed; Rashid, Jonaira; Yamada, Yuichiro; Ikeda, Yuri; Ikeda, Daisuke; Mizusawa, Nanami; Sato, Shigeru; Ogata, Takehiko; Jimbo, Mitsuru; Kudo, Toshiaki; Kaga, Shinnosuke; Watanabe, Shiho; Naiki, Kimiaki; Kaga, Yoshimasa; Mineta, Katsuhiko; Bajic, Vladimir B.; Gojobori, Takashi; Watabe, Shugo

2018-01-01

Ofunato Bay, in Japan, is the home of buoy-and-rope-type oyster aquaculture activities. Since the oysters filter suspended materials and excrete organic matter into the seawater, bacterial communities residing in its vicinity may show dynamic changes depending on the oyster culture activities. We employed a shotgun metagenomic technique to study bacterial communities near oyster aquaculture facilities at the center of the bay (KSt. 2) and compared the results with those of two other localities far from the station, one to the northeast (innermost bay, KSt. 1) and the other to the southwest (bay entrance, KSt. 3). Seawater samples were collected every month from January to December 2015 from the surface (1 m) and deeper (8 or 10 m) layers of the three locations, and the sequentially filtered fraction on 0.2-μm membranes was sequenced on an Illumina MiSeq system. The acquired reads were uploaded to MG-RAST for KEGG functional abundance analysis, while taxonomic analyses at the phylum and genus levels were performed using MEGAN after parsing the BLAST output. Discrimination analyses were then performed using the ROC-AUC value of the cross validation, targeting the depth (shallow or deep), locality [(KSt. 1 + KSt. 2) vs. KSt 3; (KSt. 1 + KSt. 3) vs. KSt. 2 or the (KSt. 2 + KSt. 3) vs. KSt. 1] and seasonality (12 months). The matrix discrimination analysis on the adjacent 2 continuous seasons by ROC-AUC, which was based on the datasets that originated from different depths, localities and months, showed the strongest discrimination signal on the taxonomy matrix at the phylum level for the datasets from July to August compared with those from September to June, while the KEGG matrix showed the strongest signal for the datasets from March to June compared with those from July to February. Then, the locality combination was subjected to the same ROC-AUC discrimination analysis, resulting in significant differences between KSt. 2 and KSt. 1 + KSt. 3

Modeling Fan Effects on the Time Course of Associative Recognition

Science.gov (United States)

Schneider, Darryl W.; Anderson, John R.

2012-01-01

We investigated the time course of associative recognition using the response signal procedure, whereby a stimulus is presented and followed after a variable lag by a signal indicating that an immediate response is required. More specifically, we examined the effects of associative fan (the number of associations that an item has with other items…

Visual detection and microplate assay for Staphylococcus aureus based on aptamer recognition coupled to tyramine signal amplification

International Nuclear Information System (INIS)

Yuan, Jinglei; Li, Can; Ma, Xiaoyuan; Xia, Yu; Chen, Jie; Wang, Zhouping; Yu, Ye

2014-01-01

We have developed a specific method for the visual detection of Staphylococcus aureus based on aptamer recognition coupled to tyramine signal amplification technology. A biotinylated aptamer specific for S. aureus was immobilized on the surface of the wells of a microplate via biotin-avidin binding. Then, the target bacteria (S. aureus), the biotinylated-aptamer-streptavidin-HRP conjugates, biotinylated tyramine, hydrogen peroxide and streptavidin-HRP were successively placed in the wells of the microplate. After adding TMB reagent and stop solution, the intensity of the yellow reaction product can be visually inspected or measured with a plate reader. Under optimized conditions, there is a linear relationship between absorbance at 450 nm and the concentration of S. aureus in the 10 to 107 cfu mL −1 concentration range (with an R 2 of 0.9976). The limit of detection is 8 cfu mL −1 . (author)

Signal Detection with Criterion Noise: Applications to Recognition Memory

Science.gov (United States)

Benjamin, Aaron S.; Diaz, Michael; Wee, Serena

2009-01-01

A tacit but fundamental assumption of the theory of signal detection is that criterion placement is a noise-free process. This article challenges that assumption on theoretical and empirical grounds and presents the noisy decision theory of signal detection (ND-TSD). Generalized equations for the isosensitivity function and for measures of…

Anti-synthetase syndrome associated with anti PL-12 and anti-Signal recognition particle antibodies and a necrotizing auto-immune myositis.

Science.gov (United States)

Malkan, Ashish; Cappelen-Smith, Cecilia; Beran, Roy; Griffith, Neil; Toong, Catherine; Wang, Min-Xia; Cordato, Dennis

2015-02-01

We report a 37-year-old woman with a 2 month history of proximal muscle weakness and extremely high creatine kinase (21,808 U/L) due to necrotizing auto-immune myositis (NAM) in association with anti-synthetase syndrome. Myositis-specific auto-immune antibody panel was positive for anti-Signal recognition particle and anti-PL-12. CT scan of the chest confirmed interstitial lung disease. Prednisolone, intravenous immunoglobulin and cyclophosphamide therapy was given with gradual improvement. This patient is notable for the unusual combination of NAM and anti-synthetase syndrome with the rare finding of two myositis-specific autoantibodies, which directed testing for associated extramuscular features and management with more aggressive immunotherapy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Solid-State NMR on bacterial cells: selective cell wall signal enhancement and resolution improvement using dynamic nuclear polarization

International Nuclear Information System (INIS)

Takahashi, Hiroki; Bardet, Michel; De Paepe, Gael; Hediger, Sabine; Ayala, Isabel; Simorre, Jean-Pierre

2013-01-01

Dynamic nuclear polarization (DNP) enhanced solid-state nuclear magnetic resonance (NMR) has recently emerged as a powerful technique for the study of material surfaces. In this study, we demonstrate its potential to investigate cell surface in intact cells. Using Bacillus subtilis bacterial cells as an example, it is shown that the polarizing agent 1-(TEMPO-4-oxy)-3-(TEMPO-4-amino)propan-2-ol (TOTAPOL) has a strong binding affinity to cell wall polymers (peptidoglycan). This particular interaction is thoroughly investigated with a systematic study on extracted cell wall materials, disrupted cells, and entire cells, which proved that TOTAPOL is mainly accumulating in the cell wall. This property is used on one hand to selectively enhance or suppress cell wall signals by controlling radical concentrations and on the other hand to improve spectral resolution by means of a difference spectrum. Comparing DNP-enhanced and conventional solid-state NMR, an absolute sensitivity ratio of 24 was obtained on the entire cell sample. This important increase in sensitivity together with the possibility of enhancing specifically cell wall signals and improving resolution really opens new avenues for the use of DNP-enhanced solid-state NMR as an on-cell investigation tool. (authors)

Solid-state NMR on bacterial cells: selective cell wall signal enhancement and resolution improvement using dynamic nuclear polarization.

Science.gov (United States)

Takahashi, Hiroki; Ayala, Isabel; Bardet, Michel; De Paëpe, Gaël; Simorre, Jean-Pierre; Hediger, Sabine

2013-04-03

Dynamic nuclear polarization (DNP) enhanced solid-state nuclear magnetic resonance (NMR) has recently emerged as a powerful technique for the study of material surfaces. In this study, we demonstrate its potential to investigate cell surface in intact cells. Using Bacillus subtilis bacterial cells as an example, it is shown that the polarizing agent 1-(TEMPO-4-oxy)-3-(TEMPO-4-amino)propan-2-ol (TOTAPOL) has a strong binding affinity to cell wall polymers (peptidoglycan). This particular interaction is thoroughly investigated with a systematic study on extracted cell wall materials, disrupted cells, and entire cells, which proved that TOTAPOL is mainly accumulating in the cell wall. This property is used on one hand to selectively enhance or suppress cell wall signals by controlling radical concentrations and on the other hand to improve spectral resolution by means of a difference spectrum. Comparing DNP-enhanced and conventional solid-state NMR, an absolute sensitivity ratio of 24 was obtained on the entire cell sample. This important increase in sensitivity together with the possibility of enhancing specifically cell wall signals and improving resolution really opens new avenues for the use of DNP-enhanced solid-state NMR as an on-cell investigation tool.

Speech recognition in natural background noise.

Directory of Open Access Journals (Sweden)

Julien Meyer

Full Text Available In the real world, human speech recognition nearly always involves listening in background noise. The impact of such noise on speech signals and on intelligibility performance increases with the separation of the listener from the speaker. The present behavioral experiment provides an overview of the effects of such acoustic disturbances on speech perception in conditions approaching ecologically valid contexts. We analysed the intelligibility loss in spoken word lists with increasing listener-to-speaker distance in a typical low-level natural background noise. The noise was combined with the simple spherical amplitude attenuation due to distance, basically changing the signal-to-noise ratio (SNR. Therefore, our study draws attention to some of the most basic environmental constraints that have pervaded spoken communication throughout human history. We evaluated the ability of native French participants to recognize French monosyllabic words (spoken at 65.3 dB(A, reference at 1 meter at distances between 11 to 33 meters, which corresponded to the SNRs most revealing of the progressive effect of the selected natural noise (-8.8 dB to -18.4 dB. Our results showed that in such conditions, identity of vowels is mostly preserved, with the striking peculiarity of the absence of confusion in vowels. The results also confirmed the functional role of consonants during lexical identification. The extensive analysis of recognition scores, confusion patterns and associated acoustic cues revealed that sonorant, sibilant and burst properties were the most important parameters influencing phoneme recognition. . Altogether these analyses allowed us to extract a resistance scale from consonant recognition scores. We also identified specific perceptual consonant confusion groups depending of the place in the words (onset vs. coda. Finally our data suggested that listeners may access some acoustic cues of the CV transition, opening interesting perspectives for

Speech recognition in natural background noise.

Science.gov (United States)

Meyer, Julien; Dentel, Laure; Meunier, Fanny

2013-01-01

In the real world, human speech recognition nearly always involves listening in background noise. The impact of such noise on speech signals and on intelligibility performance increases with the separation of the listener from the speaker. The present behavioral experiment provides an overview of the effects of such acoustic disturbances on speech perception in conditions approaching ecologically valid contexts. We analysed the intelligibility loss in spoken word lists with increasing listener-to-speaker distance in a typical low-level natural background noise. The noise was combined with the simple spherical amplitude attenuation due to distance, basically changing the signal-to-noise ratio (SNR). Therefore, our study draws attention to some of the most basic environmental constraints that have pervaded spoken communication throughout human history. We evaluated the ability of native French participants to recognize French monosyllabic words (spoken at 65.3 dB(A), reference at 1 meter) at distances between 11 to 33 meters, which corresponded to the SNRs most revealing of the progressive effect of the selected natural noise (-8.8 dB to -18.4 dB). Our results showed that in such conditions, identity of vowels is mostly preserved, with the striking peculiarity of the absence of confusion in vowels. The results also confirmed the functional role of consonants during lexical identification. The extensive analysis of recognition scores, confusion patterns and associated acoustic cues revealed that sonorant, sibilant and burst properties were the most important parameters influencing phoneme recognition. . Altogether these analyses allowed us to extract a resistance scale from consonant recognition scores. We also identified specific perceptual consonant confusion groups depending of the place in the words (onset vs. coda). Finally our data suggested that listeners may access some acoustic cues of the CV transition, opening interesting perspectives for future studies.

Innate recognition of bacteria in human milk is mediated by a milk-derived highly expressed pattern recognition receptor, soluble CD14.

OpenAIRE

Lab?ta, MO; Vidal, K; Nores, JE; Arias, M; Vita, N; Morgan, BP; Guillemot, JC; Loyaux, D; Ferrara, P; Schmid, D; Affolter, M; Borysiewicz, LK; Donnet-Hughes, A; Schiffrin, EJ

2000-01-01

Little is known about innate immunity to bacteria after birth in the hitherto sterile fetal intestine. Breast-feeding has long been associated with a lower incidence of gastrointestinal infections and inflammatory and allergic diseases. We found in human breast milk a 48-kD polypeptide, which we confirmed by mass spectrometry and sequencing to be a soluble form of the bacterial pattern recognition receptor CD14 (sCD14). Milk sCD14 (m-sCD14) concentrations were up to 20-fold higher than serum ...

Innate Recognition of Bacteria in Human Milk Is Mediated by a Milk-Derived Highly Expressed Pattern Recognition Receptor, Soluble Cd14

OpenAIRE

Labéta, Mario O.; Vidal, Karine; Nores, Julia E. Rey; Arias, Mauricio; Vita, Natalio; Morgan, B. Paul; Guillemot, Jean Claude; Loyaux, Denis; Ferrara, Pascual; Schmid, Daniel; Affolter, Michael; Borysiewicz, Leszek K.; Donnet-Hughes, Anne; Schiffrin, Eduardo J.

2000-01-01

Little is known about innate immunity to bacteria after birth in the hitherto sterile fetal intestine. Breast-feeding has long been associated with a lower incidence of gastrointestinal infections and inflammatory and allergic diseases. We found in human breast milk a 48-kD polypeptide, which we confirmed by mass spectrometry and sequencing to be a soluble form of the bacterial pattern recognition receptor CD14 (sCD14). Milk sCD14 (m-sCD14) concentrations were up to 20-fold higher than serum ...

Development of bacterial display peptides for use in biosensing applications

Science.gov (United States)

Stratis-Cullum, Dimitra N.; Kogot, Joshua M.; Sellers, Michael S.; Hurley, Margaret M.; Sarkes, Deborah A.; Pennington, Joseph M.; Val-Addo, Irene; Adams, Bryn L.; Warner, Candice R.; Carney, James P.; Brown, Rebecca L.; Pellegrino, Paul M.

2012-06-01

Recent advances in synthetic library engineering continue to show promise for the rapid production of reagent technology in response to biological threats. A synthetic library of peptide mutants built off a bacterial host offers a convenient means to link the peptide sequence, (i.e., identity of individual library members) with the desired molecular recognition traits, but also allows for a relatively simple protocol, amenable to automation. An improved understanding of the mechanisms of recognition and control of synthetic reagent isolation and evolution remain critical to success. In this paper, we describe our approach to development of peptide affinity reagents based on peptide bacterial display technology with improved control of binding interactions for stringent evolution of reagent candidates, and tailored performance capabilities. There are four key elements to the peptide affinity reagent program including: (1) the diverse bacterial library technology, (2) advanced reagent screening amenable to laboratory automation and control, (3) iterative characterization and feedback on both affinity and specificity of the molecular interactions, and (3) integrated multiscale computational prescreening of candidate peptide ligands including in silico prediction of improved binding performance. Specific results on peptides binders to Protective Antigen (PA) protein of Bacillus anthracis and Staphylococcal Enterotoxin B (SEB) will be presented. Recent highlights of on cell vs. off-cell affinity behavior and correlation of the results with advanced docking simulations on the protein-peptide system(s) are included. The potential of this technology and approach to enable rapid development of a new affinity reagent with unprecedented speed (less than one week) would allow for rapid response to new and constantly emerging threats.

Chemical signaling between plants and plant-pathogenic bacteria.

Science.gov (United States)

Venturi, Vittorio; Fuqua, Clay

2013-01-01

Studies of chemical signaling between plants and bacteria in the past have been largely confined to two models: the rhizobial-legume symbiotic association and pathogenesis between agrobacteria and their host plants. Recent studies are beginning to provide evidence that many plant-associated bacteria undergo chemical signaling with the plant host via low-molecular-weight compounds. Plant-produced compounds interact with bacterial regulatory proteins that then affect gene expression. Similarly, bacterial quorum-sensing signals result in a range of functional responses in plants. This review attempts to highlight current knowledge in chemical signaling that takes place between pathogenic bacteria and plants. This chemical communication between plant and bacteria, also referred to as interkingdom signaling, will likely become a major research field in the future, as it allows the design of specific strategies to create plants that are resistant to plant pathogens.

Exponential signaling gain at the receptor level enhances signal-to-noise ratio in bacterial chemotaxis.

Directory of Open Access Journals (Sweden)

Silke Neumann

Full Text Available Cellular signaling systems show astonishing precision in their response to external stimuli despite strong fluctuations in the molecular components that determine pathway activity. To control the effects of noise on signaling most efficiently, living cells employ compensatory mechanisms that reach from simple negative feedback loops to robustly designed signaling architectures. Here, we report on a novel control mechanism that allows living cells to keep precision in their signaling characteristics - stationary pathway output, response amplitude, and relaxation time - in the presence of strong intracellular perturbations. The concept relies on the surprising fact that for systems showing perfect adaptation an exponential signal amplification at the receptor level suffices to eliminate slowly varying multiplicative noise. To show this mechanism at work in living systems, we quantified the response dynamics of the E. coli chemotaxis network after genetically perturbing the information flux between upstream and downstream signaling components. We give strong evidence that this signaling system results in dynamic invariance of the activated response regulator against multiplicative intracellular noise. We further demonstrate that for environmental conditions, for which precision in chemosensing is crucial, the invariant response behavior results in highest chemotactic efficiency. Our results resolve several puzzling features of the chemotaxis pathway that are widely conserved across prokaryotes but so far could not be attributed any functional role.

Direct bacterial killing in vitro by recombinant Nod2 is compromised by Crohn's disease-associated mutations.

Directory of Open Access Journals (Sweden)

Laurent-Herve Perez

2010-06-01

Full Text Available A homeostatic relationship with the intestinal microflora is increasingly appreciated as essential for human health and wellbeing. Mutations in the leucine-rich repeat (LRR domain of Nod2, a bacterial recognition protein, are associated with development of the inflammatory bowel disorder, Crohn's disease. We investigated the molecular mechanisms underlying disruption of intestinal symbiosis in patients carrying Nod2 mutations.In this study, using purified recombinant LRR domains, we demonstrate that Nod2 is a direct antimicrobial agent and this activity is generally deficient in proteins carrying Crohn's-associated mutations. Wild-type, but not Crohn's-associated, Nod2 LRR domains directly interacted with bacteria in vitro, altered their metabolism and disrupted the integrity of the plasma membrane. Antibiotic activity was also expressed by the LRR domains of Nod1 and other pattern recognition receptors suggesting that the LRR domain is a conserved anti-microbial motif supporting innate cellular immunity.The lack of anti-bacterial activity demonstrated with Crohn's-associated Nod2 mutations in vitro, supports the hypothesis that a deficiency in direct bacterial killing contributes to the association of Nod2 polymorphisms with the disease.

Cellular reprogramming by gram-positive bacterial components: a review.

LENUS (Irish Health Repository)

Buckley, Julliette M

2012-02-03

LPS tolerance has been the focus of extensive scientific and clinical research over the last several decades in an attempt to elucidate the sequence of changes that occur at a molecular level in tolerized cells. Tolerance to components of gram-positive bacterial cell walls such as bacterial lipoprotein and lipoteichoic acid is a much lesser studied, although equally important, phenomenon. This review will focus on cellular reprogramming by gram-positive bacterial components and examines the alterations in cell surface receptor expression, changes in intracellular signaling, gene expression and cytokine production, and the phenomenon of cross-tolerance.

Predicting automatic speech recognition performance over communication channels from instrumental speech quality and intelligibility scores

NARCIS (Netherlands)

Gallardo, L.F.; Möller, S.; Beerends, J.

2017-01-01

The performance of automatic speech recognition based on coded-decoded speech heavily depends on the quality of the transmitted signals, determined by channel impairments. This paper examines relationships between speech recognition performance and measurements of speech quality and intelligibility

The cingulo-opercular network provides word-recognition benefit.

Science.gov (United States)

Vaden, Kenneth I; Kuchinsky, Stefanie E; Cute, Stephanie L; Ahlstrom, Jayne B; Dubno, Judy R; Eckert, Mark A

2013-11-27

Recognizing speech in difficult listening conditions requires considerable focus of attention that is often demonstrated by elevated activity in putative attention systems, including the cingulo-opercular network. We tested the prediction that elevated cingulo-opercular activity provides word-recognition benefit on a subsequent trial. Eighteen healthy, normal-hearing adults (10 females; aged 20-38 years) performed word recognition (120 trials) in multi-talker babble at +3 and +10 dB signal-to-noise ratios during a sparse sampling functional magnetic resonance imaging (fMRI) experiment. Blood oxygen level-dependent (BOLD) contrast was elevated in the anterior cingulate cortex, anterior insula, and frontal operculum in response to poorer speech intelligibility and response errors. These brain regions exhibited significantly greater correlated activity during word recognition compared with rest, supporting the premise that word-recognition demands increased the coherence of cingulo-opercular network activity. Consistent with an adaptive control network explanation, general linear mixed model analyses demonstrated that increased magnitude and extent of cingulo-opercular network activity was significantly associated with correct word recognition on subsequent trials. These results indicate that elevated cingulo-opercular network activity is not simply a reflection of poor performance or error but also supports word recognition in difficult listening conditions.

Theoretical Study of Molecular Determinants Involved in Signal Binding to the TraR Protein of Agrobacterium tumefaciens

Directory of Open Access Journals (Sweden)

N. Kumar

2005-10-01

Full Text Available N-acylated homoserine lactone (AHL mediated cell-cell communication in bacteria is dependent on the recognition of the cognate signal by its receptor. This interaction allows the receptor-ligand complex to act as a transcriptional activator, controlling the expression of a range of bacterial phenotypes, including virulence factor expression and biofilm formation. One approach to determine the key features of signal- binding is to model the intermolecular interactions between the receptor and ligand using computational-based modeling software (LigandFit. In this communication, we have modeled the crystal structure of the AHL receptor protein TraR and its AHL signal N-(3- oxooctanoyl-homoserine lactone from Agrobacterium tumefaciens and compared it to the previously reported antagonist behaviour of a number of AHL analogues, in an attempt to determine structural constraints for ligand binding. We conclude that (i a common conformation of the AHL in the hydrophobic and hydrophilic region exists for ligand-binding, (ii a tail chain length threshold of 8 carbons is most favourable for ligand-binding affinity, (iii the positive correlation in the docking studies could be used a virtual screening tool.

VanT, a central regulator of quorum sensing signalling in Vibrio anguillarum

OpenAIRE

Croxatto, Antony

2006-01-01

Many bacteria produce signal molecules that serve in a cell-to-cell communication system termed quorum sensing. This signalling system allows a bacterial population to co-ordinately regulate functions according to their cell number in a defined environment. As bacterial growth progresses towards the stationary phase, signalling molecules accumulate in the growth medium and, above a certain threshold level, regulate the expression of genes involved in diverse functions. Most of the functions m...

Bacterial communications in implant infections: a target for an intelligence war.

Science.gov (United States)

Costerton, J W; Montanaro, L; Arciola, C R

2007-09-01

The status of population density is communicated among bacteria by specific secreted molecules, called pheromones or autoinducers, and the control mechanism is called "quorum-sensing". Quorum-sensing systems regulate the expression of a panel of genes, allowing bacteria to adapt to modified environmental conditions at a high density of population. The two known different quorum systems are described as the LuxR-LuxI system in gram-negative bacteria, which uses an N-acyl-homoserine lactone (AHL) as signal, and the agr system in gram-positive bacteria, which uses a peptide-tiolactone as signal and the RNAIII as effector molecules. Both in gram-negative and in gram-positive bacteria, quorum-sensing systems regulate the expression of adhesion mechanisms (biofilm and adhesins) and virulence factors (toxins and exoenzymes) depending on population cell density. In gram-negative Pseudomonas aeruginosa, analogs of signaling molecules such as furanone analogs, are effective in attenuating bacterial virulence and controlling bacterial infections. In grampositive Staphylococcus aureus, the quorum-sensing RNAIII-inhibiting peptide (RIP), tested in vitro and in animal infection models, has been proved to inhibit virulence and prevent infections. Attenuation of bacterial virulence by quorum-sensing inhibitors, rather than by bactericidal or bacteriostatic drugs, is a highly attractive concept because these antibacterial agents are less likely to induce the development of bacterial resistance.

Double-Windows-Based Motion Recognition in Multi-Floor Buildings Assisted by a Built-In Barometer.

Science.gov (United States)

Liu, Maolin; Li, Huaiyu; Wang, Yuan; Li, Fei; Chen, Xiuwan

2018-04-01

Accelerometers, gyroscopes and magnetometers in smartphones are often used to recognize human motions. Since it is difficult to distinguish between vertical motions and horizontal motions in the data provided by these built-in sensors, the vertical motion recognition accuracy is relatively low. The emergence of a built-in barometer in smartphones improves the accuracy of motion recognition in the vertical direction. However, there is a lack of quantitative analysis and modelling of the barometer signals, which is the basis of barometer's application to motion recognition, and a problem of imbalanced data also exists. This work focuses on using the barometers inside smartphones for vertical motion recognition in multi-floor buildings through modelling and feature extraction of pressure signals. A novel double-windows pressure feature extraction method, which adopts two sliding time windows of different length, is proposed to balance recognition accuracy and response time. Then, a random forest classifier correlation rule is further designed to weaken the impact of imbalanced data on recognition accuracy. The results demonstrate that the recognition accuracy can reach 95.05% when pressure features and the improved random forest classifier are adopted. Specifically, the recognition accuracy of the stair and elevator motions is significantly improved with enhanced response time. The proposed approach proves effective and accurate, providing a robust strategy for increasing accuracy of vertical motions.

Pattern Recognition

Directory of Open Access Journals (Sweden)

Aleš Procházka

2018-05-01

Full Text Available Multimodal signal analysis based on sophisticated sensors, efficient communicationsystems and fast parallel processing methods has a rapidly increasing range of multidisciplinaryapplications. The present paper is devoted to pattern recognition, machine learning, and the analysisof sleep stages in the detection of sleep disorders using polysomnography (PSG data, includingelectroencephalography (EEG, breathing (Flow, and electro-oculogram (EOG signals. The proposedmethod is based on the classification of selected features by a neural network system with sigmoidaland softmax transfer functions using Bayesian methods for the evaluation of the probabilities of theseparate classes. The application is devoted to the analysis of the sleep stages of 184 individualswith different diagnoses, using EEG and further PSG signals. Data analysis points to an averageincrease of the length of the Wake stage by 2.7% per 10 years and a decrease of the length of theRapid Eye Movement (REM stages by 0.8% per 10 years. The mean classification accuracy for givensets of records and single EEG and multimodal features is 88.7% ( standard deviation, STD: 2.1 and89.6% (STD:1.9, respectively. The proposed methods enable the use of adaptive learning processesfor the detection and classification of health disorders based on prior specialist experience andman–machine interaction.

Distributed Recognition of Natural Songs by European Starlings

Science.gov (United States)

Knudsen, Daniel; Thompson, Jason V.; Gentner, Timothy Q.

2010-01-01

Individual vocal recognition behaviors in songbirds provide an excellent framework for the investigation of comparative psychological and neurobiological mechanisms that support the perception and cognition of complex acoustic communication signals. To this end, the complex songs of European starlings have been studied extensively. Yet, several…

Variable Frame Rate and Length Analysis for Data Compression in Distributed Speech Recognition

DEFF Research Database (Denmark)

Kraljevski, Ivan; Tan, Zheng-Hua

2014-01-01

This paper addresses the issue of data compression in distributed speech recognition on the basis of a variable frame rate and length analysis method. The method first conducts frame selection by using a posteriori signal-to-noise ratio weighted energy distance to find the right time resolution...... length for steady regions. The method is applied to scalable source coding in distributed speech recognition where the target bitrate is met by adjusting the frame rate. Speech recognition results show that the proposed approach outperforms other compression methods in terms of recognition accuracy...... for noisy speech while achieving higher compression rates....

IL-1RI (Interleukin-1 Receptor Type I Signalling is Essential for Host Defence and Hemichannel Activity During Acute Central Nervous System Bacterial Infection

Directory of Open Access Journals (Sweden)

Juan Xiong

2012-03-01

Full Text Available Staphylococcus aureus is a common aetiological agent of bacterial brain abscesses. We have previously established that a considerable IL-1 (interleukin-1 response is elicited immediately following S. aureus infection, where the cytokine can exert pleiotropic effects on glial activation and blood–brain barrier permeability. To assess the combined actions of IL-1α and IL-1β during CNS (central nervous system infection, host defence responses were evaluated in IL-1RI (IL-1 receptor type I KO (knockout animals. IL-1RI KO mice were exquisitely sensitive to intracerebral S. aureus infection, as demonstrated by enhanced mortality rates and bacterial burdens within the first 24 h following pathogen exposure compared with WT (wild-type animals. Loss of IL-1RI signalling also dampened the expression of select cytokines and chemokines, concomitant with significant reductions in neutrophil and macrophage infiltrates into the brain. In addition, the opening of astrocyte hemichannels during acute infection was shown to be dependent on IL-1RI activity. Collectively, these results demonstrate that IL-1RI signalling plays a pivotal role in the genesis of immune responses during the acute stage of brain abscess development through S. aureus containment, inflammatory mediator production, peripheral immune cell recruitment, and regulation of astrocyte hemichannel activity. Taken in the context of previous studies with MyD88 (myeloid differentiation primary response gene 88 and TLR2 (Toll-like receptor 2 KO animals, the current report advances our understanding of MyD88-dependent cascades and implicates IL-1RI signalling as a major antimicrobial effector pathway during acute brain-abscess formation.

Optical character recognition of camera-captured images based on phase features

Science.gov (United States)

Diaz-Escobar, Julia; Kober, Vitaly

2015-09-01

Nowadays most of digital information is obtained using mobile devices specially smartphones. In particular, it brings the opportunity for optical character recognition in camera-captured images. For this reason many recognition applications have been recently developed such as recognition of license plates, business cards, receipts and street signal; document classification, augmented reality, language translator and so on. Camera-captured images are usually affected by geometric distortions, nonuniform illumination, shadow, noise, which make difficult the recognition task with existing systems. It is well known that the Fourier phase contains a lot of important information regardless of the Fourier magnitude. So, in this work we propose a phase-based recognition system exploiting phase-congruency features for illumination/scale invariance. The performance of the proposed system is tested in terms of miss classifications and false alarms with the help of computer simulation.

Preliminary Analysis of Automatic Speech Recognition and Synthesis Technology.

Science.gov (United States)

1983-05-01

ANDELES CA 0 SHDAP ET AL MAY 93 UNCISSIFED UCG -020-8 MDA04-8’-C-415F/ 17/2 N mE = h IEEE 11111 10’ ~ 2.0 11-41 & 11111I25IID MICROCOPY RESOLUTION TEST...speech. Private industry, which sees a major market for improved speech recognition systems, is attempting to solve the problems involved in...manufacturer is able to market such a recognition system. A second requirement for the spotting of keywords in distress signals concerns the need for a

Discrete-State and Continuous Models of Recognition Memory: Testing Core Properties under Minimal Assumptions

Science.gov (United States)

Kellen, David; Klauer, Karl Christoph

2014-01-01

A classic discussion in the recognition-memory literature concerns the question of whether recognition judgments are better described by continuous or discrete processes. These two hypotheses are instantiated by the signal detection theory model (SDT) and the 2-high-threshold model, respectively. Their comparison has almost invariably relied on…

Joint variable frame rate and length analysis for speech recognition under adverse conditions

DEFF Research Database (Denmark)

Tan, Zheng-Hua; Kraljevski, Ivan

2014-01-01

This paper presents a method that combines variable frame length and rate analysis for speech recognition in noisy environments, together with an investigation of the effect of different frame lengths on speech recognition performance. The method adopts frame selection using an a posteriori signal......-to-noise (SNR) ratio weighted energy distance and increases the length of the selected frames, according to the number of non-selected preceding frames. It assigns a higher frame rate and a normal frame length to a rapidly changing and high SNR region of a speech signal, and a lower frame rate and an increased...... frame length to a steady or low SNR region. The speech recognition results show that the proposed variable frame rate and length method outperforms fixed frame rate and length analysis, as well as standalone variable frame rate analysis in terms of noise-robustness....

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.

[Surface electromyography signal classification using gray system theory].

Science.gov (United States)

Xie, Hongbo; Ma, Congbin; Wang, Zhizhong; Huang, Hai

2004-12-01

A new method based on gray correlation was introduced to improve the identification rate in artificial limb. The electromyography (EMG) signal was first transformed into time-frequency domain by wavelet transform. Singular value decomposition (SVD) was then used to extract feature vector from the wavelet coefficient for pattern recognition. The decision was made according to the maximum gray correlation coefficient. Compared with neural network recognition, this robust method has an almost equivalent recognition rate but much lower computation costs and less training samples.

The hydrophobic core of twin-arginine signal sequences orchestrates specific binding to Tat-pathway related chaperones.

Directory of Open Access Journals (Sweden)

Anitha Shanmugham

Full Text Available Redox enzyme maturation proteins (REMPs bind pre-proteins destined for translocation across the bacterial cytoplasmic membrane via the twin-arginine translocation system and enable the enzymatic incorporation of complex cofactors. Most REMPs recognize one specific pre-protein. The recognition site usually resides in the N-terminal signal sequence. REMP binding protects signal peptides against degradation by proteases. REMPs are also believed to prevent binding of immature pre-proteins to the translocon. The main aim of this work was to better understand the interaction between REMPs and substrate signal sequences. Two REMPs were investigated: DmsD (specific for dimethylsulfoxide reductase, DmsA and TorD (specific for trimethylamine N-oxide reductase, TorA. Green fluorescent protein (GFP was genetically fused behind the signal sequences of TorA and DmsA. This ensures native behavior of the respective signal sequence and excludes any effects mediated by the mature domain of the pre-protein. Surface plasmon resonance analysis revealed that these chimeric pre-proteins specifically bind to the cognate REMP. Furthermore, the region of the signal sequence that is responsible for specific binding to the corresponding REMP was identified by creating region-swapped chimeric signal sequences, containing parts of both the TorA and DmsA signal sequences. Surprisingly, specificity is not encoded in the highly variable positively charged N-terminal region of the signal sequence, but in the more similar hydrophobic C-terminal parts. Interestingly, binding of DmsD to its model substrate reduced membrane binding of the pre-protein. This property could link REMP-signal peptide binding to its reported proofreading function.

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

Degradation of Bacterial Quorum Sensing Signaling Molecules by the Microscopic Yeast Trichosporon loubieri Isolated from Tropical Wetland Waters

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Cheng-Siang Wong

2013-09-01

Full Text Available Proteobacteria produce N-acylhomoserine lactones as signaling molecules, which will bind to their cognate receptor and activate quorum sensing-mediated phenotypes in a population-dependent manner. Although quorum sensing signaling molecules can be degraded by bacteria or fungi, there is no reported work on the degradation of such molecules by basidiomycetous yeast. By using a minimal growth medium containing N-3-oxohexanoylhomoserine lactone as the sole source of carbon, a wetland water sample from Malaysia was enriched for microbial strains that can degrade N-acylhomoserine lactones, and consequently, a basidiomycetous yeast strain WW1C was isolated. Morphological phenotype and molecular analyses confirmed that WW1C was a strain of Trichosporon loubieri. We showed that WW1C degraded AHLs with N-acyl side chains ranging from 4 to 10 carbons in length, with or without oxo group substitutions at the C3 position. Re-lactonisation bioassays revealed that WW1C degraded AHLs via a lactonase activity. To the best of our knowledge, this is the first report of degradation of N-acyl-homoserine lactones and utilization of N-3-oxohexanoylhomoserine as carbon and nitrogen source for growth by basidiomycetous yeast from tropical wetland water; and the degradation of bacterial quorum sensing molecules by an eukaryotic yeast.

A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition.

Science.gov (United States)

Benatti, Simone; Casamassima, Filippo; Milosevic, Bojan; Farella, Elisabetta; Schönle, Philipp; Fateh, Schekeb; Burger, Thomas; Huang, Qiuting; Benini, Luca

2015-10-01

Wearable devices offer interesting features, such as low cost and user friendliness, but their use for medical applications is an open research topic, given the limited hardware resources they provide. In this paper, we present an embedded solution for real-time EMG-based hand gesture recognition. The work focuses on the multi-level design of the system, integrating the hardware and software components to develop a wearable device capable of acquiring and processing EMG signals for real-time gesture recognition. The system combines the accuracy of a custom analog front end with the flexibility of a low power and high performance microcontroller for on-board processing. Our system achieves the same accuracy of high-end and more expensive active EMG sensors used in applications with strict requirements on signal quality. At the same time, due to its flexible configuration, it can be compared to the few wearable platforms designed for EMG gesture recognition available on market. We demonstrate that we reach similar or better performance while embedding the gesture recognition on board, with the benefit of cost reduction. To validate this approach, we collected a dataset of 7 gestures from 4 users, which were used to evaluate the impact of the number of EMG channels, the number of recognized gestures and the data rate on the recognition accuracy and on the computational demand of the classifier. As a result, we implemented a SVM recognition algorithm capable of real-time performance on the proposed wearable platform, achieving a classification rate of 90%, which is aligned with the state-of-the-art off-line results and a 29.7 mW power consumption, guaranteeing 44 hours of continuous operation with a 400 mAh battery.

The progesterone-induced enhancement of object recognition memory consolidation involves activation of the extracellular signal-regulated kinase (ERK) and mammalian target of rapamycin (mTOR) pathways in the dorsal hippocampus

Science.gov (United States)

Orr, Patrick T.; Rubin, Amanda J.; Fan, Lu; Kent, Brianne A.; Frick, Karyn M.

2012-01-01

Although much recent work has elucidated the biochemical mechanisms underlying the modulation of memory by 17β-estradiol, little is known about the signaling events through which progesterone (P) regulates memory. We recently demonstrated that immediate post-training infusion of P into the dorsal hippocampus enhances object recognition memory consolidation in young ovariectomized female mice (Orr et al., 2009). The goal of the present study was to identify the biochemical alterations that might underlie this mnemonic enhancement. We hypothesized that the P-induced enhancement of object recognition would be dependent on activation of the ERK and mTOR pathways. In young ovariectomized mice, we found that bilateral dorsal hippocampal infusion of P significantly increased levels of phospho-p42 ERK and the mTOR substrate S6K in the dorsal hippocampus 5 minutes after infusion. Phospho-p42 ERK levels were downregulated 15 minutes after infusion and returned to baseline 30 minutes after infusion, suggesting a biphasic effect of P on ERK activation. Dorsal hippocampal ERK and mTOR activation were necessary for P to facilitate memory consolidation, as suggested by the fact that inhibitors of both pathways infused into the dorsal hippocampus immediately after training blocked the P-induced enhancement of object recognition. Collectively, these data provide the first demonstration that the ability of P to enhance memory consolidation depends on the rapid activation of cell signaling and protein synthesis pathways in the dorsal hippocampus. PMID:22265866

Recognition of Handwriting from Electromyography

Science.gov (United States)

Linderman, Michael; Lebedev, Mikhail A.; Erlichman, Joseph S.

2009-01-01

Handwriting – one of the most important developments in human culture – is also a methodological tool in several scientific disciplines, most importantly handwriting recognition methods, graphology and medical diagnostics. Previous studies have relied largely on the analyses of handwritten traces or kinematic analysis of handwriting; whereas electromyographic (EMG) signals associated with handwriting have received little attention. Here we show for the first time, a method in which EMG signals generated by hand and forearm muscles during handwriting activity are reliably translated into both algorithm-generated handwriting traces and font characters using decoding algorithms. Our results demonstrate the feasibility of recreating handwriting solely from EMG signals – the finding that can be utilized in computer peripherals and myoelectric prosthetic devices. Moreover, this approach may provide a rapid and sensitive method for diagnosing a variety of neurogenerative diseases before other symptoms become clear. PMID:19707562

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

Science.gov (United States)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

Facial Expression Recognition via Non-Negative Least-Squares Sparse Coding

Directory of Open Access Journals (Sweden)

Ying Chen

2014-05-01

Full Text Available Sparse coding is an active research subject in signal processing, computer vision, and pattern recognition. A novel method of facial expression recognition via non-negative least squares (NNLS sparse coding is presented in this paper. The NNLS sparse coding is used to form a facial expression classifier. To testify the performance of the presented method, local binary patterns (LBP and the raw pixels are extracted for facial feature representation. Facial expression recognition experiments are conducted on the Japanese Female Facial Expression (JAFFE database. Compared with other widely used methods such as linear support vector machines (SVM, sparse representation-based classifier (SRC, nearest subspace classifier (NSC, K-nearest neighbor (KNN and radial basis function neural networks (RBFNN, the experiment results indicate that the presented NNLS method performs better than other used methods on facial expression recognition tasks.

New pattern recognition system in the e-nose for Chinese spirit identification

International Nuclear Information System (INIS)

Zeng Hui; Li Qiang; Gu Yu

2016-01-01

This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (S f ), crest factor value (C f ), impulse factor value (I f ), clearance factor value (CL f ), kurtosis factor value (K v ) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively. (paper)

Overview of radar intra-pulse modulation recognition

Science.gov (United States)

Zang, Hanlin; Li, Yanling

2018-05-01

This paper introduces the current radar intra-pulse modulation method, describes the status quo and development direction of the intentional modulation and unintentional modulation in the pulse, and summarizes the existing problems and prospects for the future. Looking forward to the future, and providing a reference direction for the research on radar signal recognition in the next step.

Functional microdomains in bacterial membranes.

Science.gov (United States)

López, Daniel; Kolter, Roberto

2010-09-01

The membranes of eukaryotic cells harbor microdomains known as lipid rafts that contain a variety of signaling and transport proteins. Here we show that bacterial membranes contain microdomains functionally similar to those of eukaryotic cells. These membrane microdomains from diverse bacteria harbor homologs of Flotillin-1, a eukaryotic protein found exclusively in lipid rafts, along with proteins involved in signaling and transport. Inhibition of lipid raft formation through the action of zaragozic acid--a known inhibitor of squalene synthases--impaired biofilm formation and protein secretion but not cell viability. The orchestration of physiological processes in microdomains may be a more widespread feature of membranes than previously appreciated.

A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM

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Chenchen Huang

2014-01-01

Full Text Available Feature extraction is a very important part in speech emotion recognition, and in allusion to feature extraction in speech emotion recognition problems, this paper proposed a new method of feature extraction, using DBNs in DNN to extract emotional features in speech signal automatically. By training a 5 layers depth DBNs, to extract speech emotion feature and incorporate multiple consecutive frames to form a high dimensional feature. The features after training in DBNs were the input of nonlinear SVM classifier, and finally speech emotion recognition multiple classifier system was achieved. The speech emotion recognition rate of the system reached 86.5%, which was 7% higher than the original method.

A study on the extraction of feature variables for the pattern recognition for welding flaws

International Nuclear Information System (INIS)

Kim, J. Y.; Kim, C. H.; Kim, B. H.

1996-01-01

In this study, the researches classifying the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing, feature extraction, feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function classifier, the empirical Bayesian classifier. Also, the pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack, lack of penetration, lack of fusion, porosity, and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately teamed the neural network classifier is better than stastical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

A Multimodal Database for Affect Recognition and Implicit Tagging

NARCIS (Netherlands)

Soleymani, Mohammad; Lichtenauer, Jeroen; Pun, Thierry; Pantic, Maja

MAHNOB-HCI is a multimodal database recorded in response to affective stimuli with the goal of emotion recognition and implicit tagging research. A multimodal setup was arranged for synchronized recording of face videos, audio signals, eye gaze data, and peripheral/central nervous system

Transcriptome of American oysters, Crassostrea virginica, in response to bacterial challenge: insights into potential mechanisms of disease resistance.

Science.gov (United States)

McDowell, Ian C; Nikapitiya, Chamilani; Aguiar, Derek; Lane, Christopher E; Istrail, Sorin; Gomez-Chiarri, Marta

2014-01-01

The American oyster Crassostrea virginica, an ecologically and economically important estuarine organism, can suffer high mortalities in areas in the Northeast United States due to Roseovarius Oyster Disease (ROD), caused by the gram-negative bacterial pathogen Roseovarius crassostreae. The goals of this research were to provide insights into: 1) the responses of American oysters to R. crassostreae, and 2) potential mechanisms of resistance or susceptibility to ROD. The responses of oysters to bacterial challenge were characterized by exposing oysters from ROD-resistant and susceptible families to R. crassostreae, followed by high-throughput sequencing of cDNA samples from various timepoints after disease challenge. Sequence data was assembled into a reference transcriptome and analyzed through differential gene expression and functional enrichment to uncover genes and processes potentially involved in responses to ROD in the American oyster. While susceptible oysters experienced constant levels of mortality when challenged with R. crassostreae, resistant oysters showed levels of mortality similar to non-challenged oysters. Oysters exposed to R. crassostreae showed differential expression of transcripts involved in immune recognition, signaling, protease inhibition, detoxification, and apoptosis. Transcripts involved in metabolism were enriched in susceptible oysters, suggesting that bacterial infection places a large metabolic demand on these oysters. Transcripts differentially expressed in resistant oysters in response to infection included the immune modulators IL-17 and arginase, as well as several genes involved in extracellular matrix remodeling. The identification of potential genes and processes responsible for defense against R. crassostreae in the American oyster provides insights into potential mechanisms of disease resistance.

Speech and audio processing for coding, enhancement and recognition

CERN Document Server

Togneri, Roberto; Narasimha, Madihally

2015-01-01

This book describes the basic principles underlying the generation, coding, transmission and enhancement of speech and audio signals, including advanced statistical and machine learning techniques for speech and speaker recognition with an overview of the key innovations in these areas. Key research undertaken in speech coding, speech enhancement, speech recognition, emotion recognition and speaker diarization are also presented, along with recent advances and new paradigms in these areas. ·         Offers readers a single-source reference on the significant applications of speech and audio processing to speech coding, speech enhancement and speech/speaker recognition. Enables readers involved in algorithm development and implementation issues for speech coding to understand the historical development and future challenges in speech coding research; ·         Discusses speech coding methods yielding bit-streams that are multi-rate and scalable for Voice-over-IP (VoIP) Networks; ·     �...

The interplay of sequence conservation and T cell immune recognition

DEFF Research Database (Denmark)

Bresciani, Anne Gøther; Sette, Alessandro; Greenbaum, Jason

2014-01-01

examined the hypothesis that conservation of a peptide in bacteria that are part of the healthy human microbiome leads to a reduced level of immunogenicity due to tolerization of T cells to the commensal bacteria. This was done by comparing experimentally characterized T cell epitope recognition data from...... the Immune Epitope Database with their conservation in the human microbiome. Indeed, we did see a lower immunogenicity for conserved peptides conserved. While many aspects how this conservation comparison is done require further optimization, this is a first step towards a better understanding T cell...... recognition of peptides in bacterial pathogens is influenced by their conservation in commensal bacteria. If the further work proves that this approach is successful, the degree of overlap of a peptide with the human proteome or microbiome could be added to the arsenal of tools available to assess peptide...

Automatic speech recognition (zero crossing method). Automatic recognition of isolated vowels; Reconnaissance automatique de la parole (methode des passages par zero). Reconnaissance automatique de voyelles isolees

Energy Technology Data Exchange (ETDEWEB)

Dupeyrat, Benoit

1975-06-10

This note describes a recognition method of isolated vowels, using a preprocessing of the vocal signal. The processing extracts the extrema of the vocal signal and the interval time separating them (Zero crossing distances of the first derivative of the signal). The recognition of vowels uses normalized histograms of the values of these intervals. The program determines a distance between the histogram of the sound to be recognized and histograms models built during a learning phase. The results processed on real time by a minicomputer, are relatively independent of the speaker, the fundamental frequency being not allowed to vary too much (i.e. speakers of the same sex). (author) [French] Cette note decrit une methode de reconnaissance automatique de voyelles isolees basee sur un pretraitement particulier du signal vocal. Ce pretraitement consiste a extraire les extrema du signal vocal et les intervalles de temps les separant (distances entre passages par zero de la derivee du signal). La reconnaissance des voyelles est faite en utilisant des histogrammes normalises des valeurs de ces interval les. Le programme de reconnaissance utilise une distance entre l'histogramme du son a reconnaitre et des histogrammes modeles provenant d'un apprentissage. Les resultats obtenus en temps reels sur un minicalculateur, sont assez independants du locuteur, pourvu que la frequence fondamentale de la voix ne varie pas trop (locuteurs de meme sexe). (auteur)

Bacterial Signaling to the Nervous System through Toxins and Metabolites.

Science.gov (United States)

Yang, Nicole J; Chiu, Isaac M

2017-03-10

Mammalian hosts interface intimately with commensal and pathogenic bacteria. It is increasingly clear that molecular interactions between the nervous system and microbes contribute to health and disease. Both commensal and pathogenic bacteria are capable of producing molecules that act on neurons and affect essential aspects of host physiology. Here we highlight several classes of physiologically important molecular interactions that occur between bacteria and the nervous system. First, clostridial neurotoxins block neurotransmission to or from neurons by targeting the SNARE complex, causing the characteristic paralyses of botulism and tetanus during bacterial infection. Second, peripheral sensory neurons-olfactory chemosensory neurons and nociceptor sensory neurons-detect bacterial toxins, formyl peptides, and lipopolysaccharides through distinct molecular mechanisms to elicit smell and pain. Bacteria also damage the central nervous system through toxins that target the brain during infection. Finally, the gut microbiota produces molecules that act on enteric neurons to influence gastrointestinal motility, and metabolites that stimulate the "gut-brain axis" to alter neural circuits, autonomic function, and higher-order brain function and behavior. Furthering the mechanistic and molecular understanding of how bacteria affect the nervous system may uncover potential strategies for modulating neural function and treating neurological diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...

Non-native Listeners’ Recognition of High-Variability Speech Using PRESTO

Science.gov (United States)

Tamati, Terrin N.; Pisoni, David B.

2015-01-01

Background Natural variability in speech is a significant challenge to robust successful spoken word recognition. In everyday listening environments, listeners must quickly adapt and adjust to multiple sources of variability in both the signal and listening environments. High-variability speech may be particularly difficult to understand for non-native listeners, who have less experience with the second language (L2) phonological system and less detailed knowledge of sociolinguistic variation of the L2. Purpose The purpose of this study was to investigate the effects of high-variability sentences on non-native speech recognition and to explore the underlying sources of individual differences in speech recognition abilities of non-native listeners. Research Design Participants completed two sentence recognition tasks involving high-variability and low-variability sentences. They also completed a battery of behavioral tasks and self-report questionnaires designed to assess their indexical processing skills, vocabulary knowledge, and several core neurocognitive abilities. Study Sample Native speakers of Mandarin (n = 25) living in the United States recruited from the Indiana University community participated in the current study. A native comparison group consisted of scores obtained from native speakers of English (n = 21) in the Indiana University community taken from an earlier study. Data Collection and Analysis Speech recognition in high-variability listening conditions was assessed with a sentence recognition task using sentences from PRESTO (Perceptually Robust English Sentence Test Open-Set) mixed in 6-talker multitalker babble. Speech recognition in low-variability listening conditions was assessed using sentences from HINT (Hearing In Noise Test) mixed in 6-talker multitalker babble. Indexical processing skills were measured using a talker discrimination task, a gender discrimination task, and a forced-choice regional dialect categorization task. Vocabulary

Structure of the complex between teicoplanin and a bacterial cell-wall peptide: use of a carrier-protein approach

International Nuclear Information System (INIS)

Economou, Nicoleta J.; Zentner, Isaac J.; Lazo, Edwin; Jakoncic, Jean; Stojanoff, Vivian; Weeks, Stephen D.; Grasty, Kimberly C.; Cocklin, Simon; Loll, Patrick J.

2013-01-01

Using a carrier-protein strategy, the structure of teicoplanin bound to its bacterial cell-wall target has been determined. The structure reveals the molecular determinants of target recognition, flexibility in the antibiotic backbone and intrinsic radiation sensitivity of teicoplanin. Multidrug-resistant bacterial infections are commonly treated with glycopeptide antibiotics such as teicoplanin. This drug inhibits bacterial cell-wall biosynthesis by binding and sequestering a cell-wall precursor: a d-alanine-containing peptide. A carrier-protein strategy was used to crystallize the complex of teicoplanin and its target peptide by fusing the cell-wall peptide to either MBP or ubiquitin via native chemical ligation and subsequently crystallizing the protein–peptide–antibiotic complex. The 2.05 Å resolution MBP–peptide–teicoplanin structure shows that teicoplanin recognizes its ligand through a combination of five hydrogen bonds and multiple van der Waals interactions. Comparison of this teicoplanin structure with that of unliganded teicoplanin reveals a flexibility in the antibiotic peptide backbone that has significant implications for ligand recognition. Diffraction experiments revealed an X-ray-induced dechlorination of the sixth amino acid of the antibiotic; it is shown that teicoplanin is significantly more radiation-sensitive than other similar antibiotics and that ligand binding increases radiosensitivity. Insights derived from this new teicoplanin structure may contribute to the development of next-generation antibacterials designed to overcome bacterial resistance

Threshold models of recognition and the recognition heuristic

Directory of Open Access Journals (Sweden)

Edgar Erdfelder

2011-02-01

Full Text Available According to the recognition heuristic (RH theory, decisions follow the recognition principle: Given a high validity of the recognition cue, people should prefer recognized choice options compared to unrecognized ones. Assuming that the memory strength of choice options is strongly correlated with both the choice criterion and recognition judgments, the RH is a reasonable strategy that approximates optimal decisions with a minimum of cognitive effort (Davis-Stober, Dana, and Budescu, 2010. However, theories of recognition memory are not generally compatible with this assumption. For example, some threshold models of recognition presume that recognition judgments can arise from two types of cognitive states: (1 certainty states in which judgments are almost perfectly correlated with memory strength and (2 uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. We report an experiment designed to test the prediction that the RH applies to certainty states only. Our results show that memory states rather than recognition judgments affect use of recognition information in binary decisions.

The enzymes of bacterial census and censorship.

Science.gov (United States)

Fast, Walter; Tipton, Peter A

2012-01-01

N-Acyl-L-homoserine lactones (AHLs) are a major class of quorum-sensing signals used by Gram-negative bacteria to regulate gene expression in a population-dependent manner, thereby enabling group behavior. Enzymes capable of generating and catabolizing AHL signals are of significant interest for the study of microbial ecology and quorum-sensing pathways, for understanding the systems that bacteria have evolved to interact with small-molecule signals, and for their possible use in therapeutic and industrial applications. The recent structural and functional studies reviewed here provide a detailed insight into the chemistry and enzymology of bacterial communication. Copyright © 2011 Elsevier Ltd. All rights reserved.

Hidden Markov models in automatic speech recognition

Science.gov (United States)

Wrzoskowicz, Adam

1993-11-01

This article describes a method for constructing an automatic speech recognition system based on hidden Markov models (HMMs). The author discusses the basic concepts of HMM theory and the application of these models to the analysis and recognition of speech signals. The author provides algorithms which make it possible to train the ASR system and recognize signals on the basis of distinct stochastic models of selected speech sound classes. The author describes the specific components of the system and the procedures used to model and recognize speech. The author discusses problems associated with the choice of optimal signal detection and parameterization characteristics and their effect on the performance of the system. The author presents different options for the choice of speech signal segments and their consequences for the ASR process. The author gives special attention to the use of lexical, syntactic, and semantic information for the purpose of improving the quality and efficiency of the system. The author also describes an ASR system developed by the Speech Acoustics Laboratory of the IBPT PAS. The author discusses the results of experiments on the effect of noise on the performance of the ASR system and describes methods of constructing HMM's designed to operate in a noisy environment. The author also describes a language for human-robot communications which was defined as a complex multilevel network from an HMM model of speech sounds geared towards Polish inflections. The author also added mandatory lexical and syntactic rules to the system for its communications vocabulary.

Technical Reviews on Pattern Recognition in Process Analytical Technology

International Nuclear Information System (INIS)

Kim, Jong Yun; Choi, Yong Suk; Ji, Sun Kyung; Park, Yong Joon; Song, Kyu Seok; Jung, Sung Hee

2008-12-01

Pattern recognition is one of the first and the most widely adopted chemometric tools among many active research area in chemometrics such as design of experiment(DoE), pattern recognition, multivariate calibration, signal processing. Pattern recognition has been used to identify the origin of a wine and the time of year that the vine was grown by using chromatography, cause of fire by using GC/MS chromatography, detection of explosives and land mines, cargo and luggage inspection in seaports and airports by using a prompt gamma-ray activation analysis, and source apportionment of environmental pollutant by using a stable isotope ratio mass spectrometry. Recently, pattern recognition has been taken into account as a major chemometric tool in the so-called 'process analytical technology (PAT)', which is a newly-developed concept in the area of process analytics proposed by US Food and Drug Administration (US FDA). For instance, identification of raw material by using a pattern recognition analysis plays an important role for the effective quality control of the production process. Recently, pattern recognition technique has been used to identify the spatial distribution and uniformity of the active ingredients present in the product such as tablet by transforming the chemical data into the visual information

A Novel AT-Rich DNA Recognition Mechanism for Bacterial Xenogeneic Silencer MvaT.

Directory of Open Access Journals (Sweden)

Pengfei Ding

2015-06-01

Full Text Available Bacterial xenogeneic silencing proteins selectively bind to and silence expression from many AT rich regions of the chromosome. They serve as master regulators of horizontally acquired DNA, including a large number of virulence genes. To date, three distinct families of xenogeneic silencers have been identified: H-NS of Proteobacteria, Lsr2 of the Actinomycetes, and MvaT of Pseudomonas sp. Although H-NS and Lsr2 family proteins are structurally different, they all recognize the AT-rich DNA minor groove through a common AT-hook-like motif, which is absent in the MvaT family. Thus, the DNA binding mechanism of MvaT has not been determined. Here, we report the characteristics of DNA sequences targeted by MvaT with protein binding microarrays, which indicates that MvaT prefers binding flexible DNA sequences with multiple TpA steps. We demonstrate that there are clear differences in sequence preferences between MvaT and the other two xenogeneic silencer families. We also determined the structure of the DNA-binding domain of MvaT in complex with a high affinity DNA dodecamer using solution NMR. This is the first experimental structure of a xenogeneic silencer in complex with DNA, which reveals that MvaT recognizes the AT-rich DNA both through base readout by an "AT-pincer" motif inserted into the minor groove and through shape readout by multiple lysine side chains interacting with the DNA sugar-phosphate backbone. Mutations of key MvaT residues for DNA binding confirm their importance with both in vitro and in vivo assays. This novel DNA binding mode enables MvaT to better tolerate GC-base pair interruptions in the binding site and less prefer A tract DNA when compared to H-NS and Lsr2. Comparison of MvaT with other bacterial xenogeneic silencers provides a clear picture that nature has evolved unique solutions for different bacterial genera to distinguish foreign from self DNA.

Dual-Recognition Förster Resonance Energy Transfer Based Platform for One-Step Sensitive Detection of Pathogenic Bacteria Using Fluorescent Vancomycin-Gold Nanoclusters and Aptamer-Gold Nanoparticles.

Science.gov (United States)

Yu, Mengqun; Wang, Hong; Fu, Fei; Li, Linyao; Li, Jing; Li, Gan; Song, Yang; Swihart, Mark T; Song, Erqun

2017-04-04

The effective monitoring, identification, and quantification of pathogenic bacteria is essential for addressing serious public health issues. In this study, we present a universal and facile one-step strategy for sensitive and selective detection of pathogenic bacteria using a dual-molecular affinity-based Förster (fluorescence) resonance energy transfer (FRET) platform based on the recognition of bacterial cell walls by antibiotic and aptamer molecules, respectively. As a proof of concept, Vancomycin (Van) and a nucleic acid aptamer were employed in a model dual-recognition scheme for detecting Staphylococcus aureus (Staph. aureus). Within 30 min, by using Van-functionalized gold nanoclusters and aptamer-modified gold nanoparticles as the energy donor and acceptor, respectively, the FRET signal shows a linear variation with the concentration of Staph. aureus in the range from 20 to 10 8 cfu/mL with a detection limit of 10 cfu/mL. Other nontarget bacteria showed negative results, demonstrating the good specificity of the approach. When employed to assay Staph. aureus in real samples, the dual-recognition FRET strategy showed recoveries from 99.00% to the 109.75% with relative standard derivations (RSDs) less than 4%. This establishes a universal detection platform for sensitive, specific, and simple pathogenic bacteria detection, which could have great impact in the fields of food/public safety monitoring and infectious disease diagnosis.

An adaptive deep Q-learning strategy for handwritten digit recognition.

Science.gov (United States)

Qiao, Junfei; Wang, Gongming; Li, Wenjing; Chen, Min

2018-02-22

Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further improved. In this paper, an adaptive deep Q-learning strategy is proposed to improve accuracy and shorten running time for handwritten digit recognition. The adaptive deep Q-learning strategy combines the feature-extracting capability of deep learning and the decision-making of reinforcement learning to form an adaptive Q-learning deep belief network (Q-ADBN). First, Q-ADBN extracts the features of original images using an adaptive deep auto-encoder (ADAE), and the extracted features are considered as the current states of Q-learning algorithm. Second, Q-ADBN receives Q-function (reward signal) during recognition of the current states, and the final handwritten digits recognition is implemented by maximizing the Q-function using Q-learning algorithm. Finally, experimental results from the well-known MNIST dataset show that the proposed Q-ADBN has a superiority to other similar methods in terms of accuracy and running time. Copyright © 2018 Elsevier Ltd. All rights reserved.

Robust Automatic Speech Recognition Features using Complex Wavelet Packet Transform Coefficients

Directory of Open Access Journals (Sweden)

TjongWan Sen

2009-11-01

Full Text Available To improve the performance of phoneme based Automatic Speech Recognition (ASR in noisy environment; we developed a new technique that could add robustness to clean phonemes features. These robust features are obtained from Complex Wavelet Packet Transform (CWPT coefficients. Since the CWPT coefficients represent all different frequency bands of the input signal, decomposing the input signal into complete CWPT tree would also cover all frequencies involved in recognition process. For time overlapping signals with different frequency contents, e. g. phoneme signal with noises, its CWPT coefficients are the combination of CWPT coefficients of phoneme signal and CWPT coefficients of noises. The CWPT coefficients of phonemes signal would be changed according to frequency components contained in noises. Since the numbers of phonemes in every language are relatively small (limited and already well known, one could easily derive principal component vectors from clean training dataset using Principal Component Analysis (PCA. These principal component vectors could be used then to add robustness and minimize noises effects in testing phase. Simulation results, using Alpha Numeric 4 (AN4 from Carnegie Mellon University and NOISEX-92 examples from Rice University, showed that this new technique could be used as features extractor that improves the robustness of phoneme based ASR systems in various adverse noisy conditions and still preserves the performance in clean environments.

Recognition of Lipopolysaccharide and Activation of NF-κB by Cytosolic Sensor NOD1 in Teleost Fish

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Dekun Bi

2018-06-01

Full Text Available Lipopolysaccharide (LPS is the major component of the outer membrane of Gram-negative bacteria. This molecule can induce strong immune response and various biological effects. In mammals, TLR4 can recognize LPS and induce inflammatory response. However, the innate receptor in fish for recognizing LPS remains ambiguous. LPS can invade the cytoplasm via outer membrane vesicles produced by Gram-negative bacteria and could be detected by intracellular receptor caspase-11 in mammals, so, there may also exist the intracellular receptors that can recognize LPS in fish. NOD1 is a member of NOD-like receptors family and can recognize the iE-DAP in the cytoplasm in mammals. In fish, NOD1 can also respond to infection of Gram-negative bacteria and may play an important role in the identification of bacterial components. In this study, to study whether NOD1 is a recognition receptor for LPS, we detected the expression of NOD1 and several cytokines at transcript levels to determine whether LPS can induce inflammatory response in teleost fish and NOD1 can respond to LPS. Then, we perform the binding analysis between NOD1 and ultrapure LPS by using Streptavidin pulldown assay and enzyme-linked immunosorbent assay to prove that NOD1 can be combined with LPS, and using dual luciferase reporter gene assay to verify the signal pathways activated by NOD1. Next, through cell viability analysis, we proved that LPS-induced cytotoxicity can be mediated by NOD1 in fish. The results showed that NOD1 can identify LPS and activate the NF-κB signal pathway by recruiting RIPK2 and then promoting the expression of inflammatory cytokines to induce the resistance of organism against bacterial infection.

New technique for real-time distortion-invariant multiobject recognition and classification

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Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

Damaged-self recognition in common bean (Phaseolus vulgaris shows taxonomic specificity and triggers signalling via reactive oxygen species (ROS

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Dalia eDuran

2014-10-01

Full Text Available Plants require reliable mechanisms to detect injury. Danger signals or 'damage-associated molecular patterns' (DAMPs are released from stressed host cells and allow injury detection independently of enemy-derived molecules. We studied the response of common bean (Phaseolus vulgaris to the application of leaf homogenate as a source of DAMPs and measured the production of reactive oxygen species (ROS as an early response and the secretion of extrafloral nectar (EFN as a jasmonic acid (JA–dependent late response. We observed a strong taxonomic signal in the response to different leaf homogenates. ROS formation and EFN secretion were highly correlated and responded most strongly to leaf homogenates produced using the same cultivar or closely related accessions, less to a distantly related cultivar of common bean or each of the two congeneric species, P. lunatus and P. coccineus, and not at all to homogenates prepared from species in different genera, not even when using other Fabaceae. Interestingly, leaf homogenates also reduced the infection by the bacterial pathogen, Pseudomonas syringae, when they were applied directly before challenging, although the same homogenates exhibited no direct in vitro inhibitory effect in the bacterium. We conclude that ROS signaling is associated to the induction of EFN secretion and that the specific blend of DAMPs that are released from damaged cells allows the plant to distinguish the 'damaged self' from the damaged 'non-self'. The very early responses of plants to DAMPs can trigger resistance to both, herbivores and pathogens, which should be adaptive because injury facilitates infection, independently of its causal reason.

Memory evaluation in mild cognitive impairment using recall and recognition tests.

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Bennett, Ilana J; Golob, Edward J; Parker, Elizabeth S; Starr, Arnold

2006-11-01

Amnestic mild cognitive impairment (MCI) is a selective episodic memory deficit that often indicates early Alzheimer's disease. Episodic memory function in MCI is typically defined by deficits in free recall, but can also be tested using recognition procedures. To assess both recall and recognition in MCI, MCI (n = 21) and older comparison (n = 30) groups completed the USC-Repeatable Episodic Memory Test. Subjects memorized two verbally presented 15-item lists. One list was used for three free recall trials, immediately followed by yes/no recognition. The second list was used for three-alternative forced-choice recognition. Relative to the comparison group, MCI had significantly fewer hits and more false alarms in yes/no recognition, and were less accurate in forced-choice recognition. Signal detection analysis showed that group differences were not due to response bias. Discriminant function analysis showed that yes/no recognition was a better predictor of group membership than free recall or forced-choice measures. MCI subjects recalled fewer items than comparison subjects, with no group differences in repetitions, intrusions, serial position effects, or measures of recall strategy (subjective organization, recall consistency). Performance deficits on free recall and recognition in MCI suggest a combination of both tests may be useful for defining episodic memory impairment associated with MCI and early Alzheimer's disease.

Bacterial bioluminescence onset and quenching: a dynamical model for a quorum sensing-mediated property

OpenAIRE

Side, Domenico Delle; Nassisi, Vincenzo; Pennetta, Cecilia; Alifano, Pietro; Di Salvo, Marco; Talà, Adelfia; Chechkin, Aleksei; Seno, Flavio; Trovato, Antonio

2017-01-01

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distri...

Acute exposure to crystalline silica reduces macrophage activation in response to bacterial lipoproteins

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Gillian Lee Beamer

2016-02-01

Full Text Available Numerous studies have examined the relationship between alveolar macrophages (AM and crystalline silica (SiO2 using in vitro and in vivo immunotoxicity models; however, exactly how exposure to SiO2 alters the functionality of AM and the potential consequences for immunity to respiratory pathogens remains largely unknown. Because recognition and clearance of inhaled particulates and microbes is largely mediated by pattern recognition receptors (PRR on the surface of AM, we hypothesized that exposure to SiO2 limits the ability of AM to respond to bacterial challenge by altering PRR expression. Alveolar and bone marrow-derived macrophages downregulate TLR2 expression following acute SiO2 exposure (e.g. 4 hours. Interestingly, these responses were dependent upon interactions between SiO2 and the class A scavenger receptor CD204, but not MARCO. Furthermore, SiO2 exposure decreased uptake of fluorescently labeled Pam2CSK4 and Pam3CSK4, resulting in reduced secretion of IL-1β, but not IL-6. Collectively, our data suggest that SiO2 exposure alters AM phenotype, which in turn affects their ability to uptake and respond to bacterial lipoproteins.

Contrasting ability to take up leucine and thymidine among freshwater bacterial groups: implications for bacterial production measurements

Science.gov (United States)

Pérez, María Teresa; Hörtnagl, Paul; Sommaruga, Ruben

2010-01-01

We examined the ability of different freshwater bacterial groups to take up leucine and thymidine in two lakes. Utilization of both substrates by freshwater bacteria was examined at the community level by looking at bulk incorporation rates and at the single-cell level by combining fluorescent in situ hybridization and signal amplification by catalysed reporter deposition with microautoradiography. Our results showed that leucine was taken up by 70–80% of Bacteria-positive cells, whereas only 15–43% of Bacteria-positive cells were able to take up thymidine. When a saturating substrate concentration in combination with a short incubation was used, 80–90% of Betaproteobacteria and 67–79% of Actinobacteria were positive for leucine uptake, whereas thymidine was taken up by bacterial group. Bacterial abundance was a good predictor of the relative contribution of bacterial groups to leucine uptake, whereas when thymidine was used Actinobacteria represented the large majority (> 80%) of the cells taking up this substrate. Increasing the substrate concentration to 100 nM did not affect the percentage of R-BT cells taking up leucine (> 90% even at low concentrations), but moderately increased the fraction of thymidine-positive R-BT cells to a maximum of 35% of the hybridized cells. Our results show that even at very high concentrations, thymidine is not taken up by all, otherwise active, bacterial cells. PMID:19725866

A Robust and Device-Free System for the Recognition and Classification of Elderly Activities.

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Li, Fangmin; Al-Qaness, Mohammed Abdulaziz Aide; Zhang, Yong; Zhao, Bihai; Luan, Xidao

2016-12-01

Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention, namely device-free human activity recognition that neither requires the target object to wear or carry a device nor install cameras in a perceived area. The device-free technique for activity recognition uses only the signals of common wireless local area network (WLAN) devices available everywhere. In this paper, we present a novel elderly activities recognition system by leveraging the fluctuation of the wireless signals caused by human motion. We present an efficient method to select the correct data from the Channel State Information (CSI) streams that were neglected in previous approaches. We apply a Principle Component Analysis method that exposes the useful information from raw CSI. Thereafter, Forest Decision (FD) is adopted to classify the proposed activities and has gained a high accuracy rate. Extensive experiments have been conducted in an indoor environment to test the feasibility of the proposed system with a total of five volunteer users. The evaluation shows that the proposed system is applicable and robust to electromagnetic noise.

When the face fits: recognition of celebrities from matching and mismatching faces and voices.

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Stevenage, Sarah V; Neil, Greg J; Hamlin, Iain

2014-01-01

The results of two experiments are presented in which participants engaged in a face-recognition or a voice-recognition task. The stimuli were face-voice pairs in which the face and voice were co-presented and were either "matched" (same person), "related" (two highly associated people), or "mismatched" (two unrelated people). Analysis in both experiments confirmed that accuracy and confidence in face recognition was consistently high regardless of the identity of the accompanying voice. However accuracy of voice recognition was increasingly affected as the relationship between voice and accompanying face declined. Moreover, when considering self-reported confidence in voice recognition, confidence remained high for correct responses despite the proportion of these responses declining across conditions. These results converged with existing evidence indicating the vulnerability of voice recognition as a relatively weak signaller of identity, and results are discussed in the context of a person-recognition framework.

Face recognition increases during saccade preparation.

Science.gov (United States)

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

2014-01-01

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

Pedestrian recognition using automotive radar sensors

Science.gov (United States)

Bartsch, A.; Fitzek, F.; Rasshofer, R. H.

2012-09-01

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

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%.

Expression of Toll-like receptor 9 and response to bacterial CpG oligodeoxynucleotides in human intestinal epithelium

DEFF Research Database (Denmark)

Pedersen, G; Andresen, Lars; Matthiessen, M W

2005-01-01

Recognition of repeat CpG motifs, which are common in bacterial, but not in mammalian, DNA, through Toll-like receptor (TLR)9 is an integral part of the innate immune system. As the role of TLR9 in the human gut is unknown, we determined the spectrum of TLR9 expression in normal and inflamed colo...... in vitro despite spontaneous TLR9 gene expression. This suggests that the human epithelium is able to avoid inappropriate immune responses to luminal bacterial products through modulation of the TLR9 pathway....

Innate immune signalling at the intestinal epithelium in homeostasis and disease

Science.gov (United States)

Pott, Johanna; Hornef, Mathias

2012-01-01

The intestinal epithelium—which constitutes the interface between the enteric microbiota and host tissues—actively contributes to the maintenance of mucosal homeostasis and defends against pathogenic microbes. The recognition of conserved microbial products by cytosolic or transmembrane pattern recognition receptors in epithelial cells initiates signal transduction and influences effector cell function. However, the signalling pathways, effector molecules and regulatory mechanisms involved are not yet fully understood, and the functional outcome is poorly defined. This review analyses the complex and dynamic role of intestinal epithelial innate immune recognition and signalling, on the basis of results in intestinal epithelial cell-specific transgene or gene-deficient animals. This approach identifies specific epithelial cell functions within the diverse cellular composition of the mucosal tissue, in the presence of the complex and dynamic gut microbiota. These insights have thus provided a more comprehensive understanding of the role of the intestinal epithelium in innate immunity during homeostasis and disease. PMID:22801555

Pathogen recognition in the innate immune response.

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Kumar, Himanshu; Kawai, Taro; Akira, Shizuo

2009-04-28

Immunity against microbial pathogens primarily depends on the recognition of pathogen components by innate receptors expressed on immune and non-immune cells. Innate receptors are evolutionarily conserved germ-line-encoded proteins and include TLRs (Toll-like receptors), RLRs [RIG-I (retinoic acid-inducible gene-I)-like receptors] and NLRs (Nod-like receptors). These receptors recognize pathogens or pathogen-derived products in different cellular compartments, such as the plasma membrane, the endosomes or the cytoplasm, and induce the expression of cytokines, chemokines and co-stimulatory molecules to eliminate pathogens and instruct pathogen-specific adaptive immune responses. In the present review, we will discuss the recent progress in the study of pathogen recognition by TLRs, RLRs and NLRs and their signalling pathways.

Molecular cloning and functional characterization of peptidoglycan recognition protein OmPGRP-L2 from the rainbow trout, Oncorhynchus mykiss.

Science.gov (United States)

Jang, Ju Hye; Kim, Hyun; Cho, Ju Hyun

2017-10-01

Peptidoglycan recognition proteins (PGRPs), a group of pattern recognition receptors (PRRs), are innate immune molecules that are structurally conserved through evolution in both invertebrate and vertebrate animals. In teleost fish, several PGRPs have been characterized recently. They have both amidase activity and bactericidal activity and are involved in indirectly killing bacteria and regulating multiple signaling pathways. However, the knowledge of functional similarity and divergence between PGRP paralogs for their role as an immune modulator in teleost fish is still limited. In this study, we identified a novel PGRP paralog, termed OmPGRP-L2 from the rainbow trout (Oncorhynchus mykiss). OmPGRP-L2 contains the conserved PGRP domain and the four Zn 2+ -binding amino acid residues required for amidase activity. Quantitative RT-PCR analysis indicated that OmPGRP-L2 is highly expressed in liver. Overexpression of OmPGRP-L2 in a rainbow trout hepatocyte cell line RTH-149 challenged with Edwardsiella tarda resulted in down-regulation of IL-1β and TNF-α expression. When overexpressed in RTH-149 cells, OmPGRP-L2 inhibited NF-κB activity with or without bacterial stimulation. Collectively, these findings suggest that OmPGRP-L2 has an immunomodulatory function, via NF-κB inhibition in liver. Copyright © 2017 Elsevier B.V. All rights reserved.

Reversing the picture superiority effect: a speed-accuracy trade-off study of recognition memory.

Science.gov (United States)

Boldini, Angela; Russo, Riccardo; Punia, Sahiba; Avons, S E

2007-01-01

Speed-accuracy trade-off methods have been used to contrast single- and dual-process accounts of recognition memory. With these procedures, subjects are presented with individual test items and required to make recognition decisions under various time constraints. In three experiments, we presented words and pictures to be intentionally learned; test stimuli were always visually presented words. At test, we manipulated the interval between the presentation of each test stimulus and that of a response signal, thus controlling the amount of time available to retrieve target information. The standard picture superiority effect was significant in long response deadline conditions (i.e., > or = 2,000 msec). Conversely, a significant reverse picture superiority effect emerged at short response-signal deadlines (< 200 msec). The results are congruent with views suggesting that both fast familiarity and slower recollection processes contribute to recognition memory. Alternative accounts are also discussed.

Wavelet-based moment invariants for pattern recognition

Science.gov (United States)

Chen, Guangyi; Xie, Wenfang

2011-07-01

Moment invariants have received a lot of attention as features for identification and inspection of two-dimensional shapes. In this paper, two sets of novel moments are proposed by using the auto-correlation of wavelet functions and the dual-tree complex wavelet functions. It is well known that the wavelet transform lacks the property of shift invariance. A little shift in the input signal will cause very different output wavelet coefficients. The autocorrelation of wavelet functions and the dual-tree complex wavelet functions, on the other hand, are shift-invariant, which is very important in pattern recognition. Rotation invariance is the major concern in this paper, while translation invariance and scale invariance can be achieved by standard normalization techniques. The Gaussian white noise is added to the noise-free images and the noise levels vary with different signal-to-noise ratios. Experimental results conducted in this paper show that the proposed wavelet-based moments outperform Zernike's moments and the Fourier-wavelet descriptor for pattern recognition under different rotation angles and different noise levels. It can be seen that the proposed wavelet-based moments can do an excellent job even when the noise levels are very high.

Event recognition using signal spectrograms in long pulse experiments

International Nuclear Information System (INIS)

Gonzalez, J.; Ruiz, M.; Barrera, E.; Arcas, G.; Lopez, J. M.; Vega, J.

2010-01-01

As discharge duration increases, real-time complex analysis of the signal becomes more important. In this context, data acquisition and processing systems must provide models for designing experiments which use event oriented plasma control. One example of advanced data analysis is signal classification. The off-line statistical analysis of a large number of discharges provides information to develop algorithms for the determination of the plasma parameters from measurements of magnetohydrodinamic waves, for example, to detect density fluctuations induced by the Alfven cascades using morphological patterns. The need to apply different algorithms to the signals and to address different processing algorithms using the previous results necessitates the use of an event-based experiment. The Intelligent Test and Measurement System platform is an example of architecture designed to implement distributed data acquisition and real-time processing systems. The processing algorithm sequence is modeled using an event-based paradigm. The adaptive capacity of this model is based on the logic defined by the use of state machines in SCXML. The Intelligent Test and Measurement System platform mixes a local multiprocessing model with a distributed deployment of services based on Jini.

Pattern recognition

CERN Document Server

Theodoridis, Sergios

2003-01-01

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

Feature Selection for Nonstationary Data: Application to Human Recognition Using Medical Biometrics.

Science.gov (United States)

Komeili, Majid; Louis, Wael; Armanfard, Narges; Hatzinakos, Dimitrios

2018-05-01

Electrocardiogram (ECG) and transient evoked otoacoustic emission (TEOAE) are among the physiological signals that have attracted significant interest in biometric community due to their inherent robustness to replay and falsification attacks. However, they are time-dependent signals and this makes them hard to deal with in across-session human recognition scenario where only one session is available for enrollment. This paper presents a novel feature selection method to address this issue. It is based on an auxiliary dataset with multiple sessions where it selects a subset of features that are more persistent across different sessions. It uses local information in terms of sample margins while enforcing an across-session measure. This makes it a perfect fit for aforementioned biometric recognition problem. Comprehensive experiments on ECG and TEOAE variability due to time lapse and body posture are done. Performance of the proposed method is compared against seven state-of-the-art feature selection algorithms as well as another six approaches in the area of ECG and TEOAE biometric recognition. Experimental results demonstrate that the proposed method performs noticeably better than other algorithms.

RF-Care: Device-Free Posture Recognition for Elderly People Using A Passive RFID Tag Array

Directory of Open Access Journals (Sweden)

Lina Yao

2015-09-01

Full Text Available Activity recognition is a fundamental research topic for a wide range of important applications such as fall detection for elderly people. Existing techniques mainly rely on wearable sensors, which may not be reliable and practical in real-world situations since people often forget to wear these sensors. For this reason, device-free activity recognition has gained the popularity in recent years. In this paper, we propose an RFID (radio frequency identification based, device-free posture recognition system. More specifically, we analyze Received Signal Strength Indicator (RSSI signal patterns from an RFID tag array, and systematically examine the impact of tag configuration on system performance. On top of selected optimal subset of tags, we study the challenges on posture recognition. Apart from exploring posture classification, we specially propose to infer posture transitions via Dirichlet Process Gaussian Mixture Model (DPGMM based Hidden Markov Model (HMM, which effectively captures the nature of uncertainty caused by signal strength varieties during posture transitions. We run a pilot study to evaluate our system with 12 orientation-sensitive postures and a series of posture change sequences. We conduct extensive experiments in both lab and real-life home environments. The results demonstrate that our system achieves high accuracy in both environments, which holds the potential to support assisted living of elderly people.

Quantitative SERS Detection of Dopamine in Cerebrospinal Fluid by Dual-Recognition-Induced Hot Spot Generation.

Science.gov (United States)

Zhang, Kun; Liu, Yu; Wang, Yuning; Zhang, Ren; Liu, Jiangang; Wei, Jia; Qian, Hufei; Qian, Kun; Chen, Ruoping; Liu, Baohong

2018-05-09

Reliable profiling of the extracellular dopamine (DA) concentration in the central nervous system is essential for a deep understanding of its biological and pathological functions. However, quantitative determination of this neurotransmitter remains a challenge because of the extremely low concentration of DA in the cerebrospinal fluid (CSF) of patients. Herein, on the basis of the specific recognition of boronate toward diol and N-hydroxysuccinimide ester toward the amine group, a simple and highly sensitive strategy was presented for DA detection by using surface-enhanced Raman scattering (SERS) spectroscopy as a signal readout. This was realized by first immobilizing 3,3'-dithiodipropionic acid di( N-hydroxysuccinimide ester) on gold thin film surfaces to capture DA, followed by introducing 3-mercaptophenylboronic acid (3-MPBA)-functionalized silver nanoparticles to generate numerous plasmonic "hot spots" with the nanoparticle-on-mirror geometry. Such a dual-recognition mechanism not only avoids complicated bioelement-based manipulations but also efficiently decreases the background signal. With the direct use of the recognition probe 3-MPBA as a Raman reporter, the "signal-on" SERS method was employed to quantify the concentration of DA from 1 pM to 1 μM with a detection limit of 0.3 pM. Moreover, our dual-recognition-directed SERS assay exhibited a high resistance to cerebral interference and was successfully applied to monitoring of DA in CSF samples of patients.

Does humor in radio advertising affect recognition of novel product brand names?

Science.gov (United States)

Berg, E M; Lippman, L G

2001-04-01

The authors proposed that item selection during shopping is based on brand name recognition rather than recall. College students rated advertisements and news stories of a simulated radio program for level of amusement (orienting activity) before participating in a surprise recognition test. Humor level of the advertisements was varied systematically, and content was controlled. According to signal detection analysis, humor did not affect the strength of recognition memory for brand names (nonsense units). However, brand names and product types were significantly more likely to be associated when appearing in humorous advertisements than in nonhumorous advertisements. The results are compared with prior findings concerning humor and recall.

Infliximab ameliorates AD-associated object recognition memory impairment.

Science.gov (United States)

Kim, Dong Hyun; Choi, Seong-Min; Jho, Jihoon; Park, Man-Seok; Kang, Jisu; Park, Se Jin; Ryu, Jong Hoon; Jo, Jihoon; Kim, Hyun Hee; Kim, Byeong C

2016-09-15

Dysfunctions in the perirhinal cortex (PRh) are associated with visual recognition memory deficit, which is frequently detected in the early stage of Alzheimer's disease. Muscarinic acetylcholine receptor-dependent long-term depression (mAChR-LTD) of synaptic transmission is known as a key pathway in eliciting this type of memory, and Tg2576 mice expressing enhanced levels of Aβ oligomers are found to have impaired mAChR-LTD in this brain area at as early as 3 months of age. We found that the administration of Aβ oligomers in young normal mice also induced visual recognition memory impairment and perturbed mAChR-LTD in mouse PRh slices. In addition, when mice were treated with infliximab, a monoclonal antibody against TNF-α, visual recognition memory impaired by pre-administered Aβ oligomers dramatically improved and the detrimental Aβ effect on mAChR-LTD was annulled. Taken together, these findings suggest that Aβ-induced inflammation is mediated through TNF-α signaling cascades, disturbing synaptic transmission in the PRh, and leading to visual recognition memory deficits. Copyright © 2016 Elsevier B.V. All rights reserved.

Surveillance of a nuclear reactor core by use of a pattern recognition method

International Nuclear Information System (INIS)

Invernizzi, Michel.

1982-07-01

A pattern recognition system is described for the surveillance of a PWR reactor. This report contains four chapters. The first one succinctly deals with statistical pattern recognition principles. In the second chapter we show how a surveillance problem may be treated by pattern recognition and we present methods for surveillances (detection of abnormalities), controls (kind of running recognition) and diagnotics (kind of abnormality recognition). The third chapter shows a surveillance method of a nuclear plant. The signals used are the neutron noise observations made by the ionization chambers inserted in the reactor. Abnormality is defined in opposition with the training set witch is supposed to be an exhaustive summary of normality. In the fourth chapter we propose a scheme for an adaptative recognition and a method based on classes modelisations by hyper-spheres. This method has been tested on simulated training sets in two-dimensional feature spaces. It gives solutions to problems of non-linear separability [fr

Infrared and visible fusion face recognition based on NSCT domain

Science.gov (United States)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-01-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In this paper, a novel fusion algorithm in non-subsampled contourlet transform (NSCT) domain is proposed for Infrared and visible face fusion recognition. Firstly, NSCT is used respectively to process the infrared and visible face images, which exploits the image information at multiple scales, orientations, and frequency bands. Then, to exploit the effective discriminant feature and balance the power of high-low frequency band of NSCT coefficients, the local Gabor binary pattern (LGBP) and Local Binary Pattern (LBP) are applied respectively in different frequency parts to obtain the robust representation of infrared and visible face images. Finally, the score-level fusion is used to fuse the all the features for final classification. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. Experiments results show that the proposed method extracts the complementary features of near-infrared and visible-light images and improves the robustness of unconstrained face recognition.

Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers

DEFF Research Database (Denmark)

Borkowski, Robert; Zibar, Darko; Caballero Jambrina, Antonio

2013-01-01

We present a technique for modulation format recognition for heterogeneous reconfigurable optical networks. The method is based on Stokes space signal representation and uses a variational Bayesian expectation maximization machine learning algorithm. Differentiation between diverse common coheren...

Rice bacterial blight pathogen Xanthomonas oryzae pv. oryzae produces multiple DSF-family signals in regulation of virulence factor production

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Cha Jae-Soon

2010-07-01

Full Text Available Abstract Background Xanthomonas oryzae pv. oryzae (Xoo is the causal agent of rice bacterial blight disease. Xoo produces a range of virulence factors, including EPS, extracellular enzyme, iron-chelating siderophores, and type III-secretion dependent effectors, which are collectively essential for virulence. Genetic and genomics evidence suggest that Xoo might use the diffusible signal factor (DSF type quorum sensing (QS system to regulate the virulence factor production. However, little is known about the chemical structure of the DSF-like signal(s produced by Xoo and the factors influencing the signal production. Results Xoo genome harbours an rpf cluster comprising rpfB, rpfF, rpfC and rpfG. The proteins encoded by these genes are highly homologous to their counterparts in X. campestris pv. campestris (Xcc, suggesting that Xcc and Xoo might use similar mechanisms for DSF biosynthesis and autoregulation. Consistent with in silico analysis, the rpfF mutant was DSF-deficient and the rpfC mutant produced about 25 times higher DSF-like activity than the wild type Xoo strain KACC10331. From the supernatants of rpfC mutant, we purified three compounds showing strong DSF-like activity. Mass spectrometry and NMR analysis revealed that two of them were the previously characterized DSF and BDSF; the third one was a novel unsaturated fatty acid with 2 double bonds and was designated as CDSF in this study. Further analysis showed that all the three DSF-family signals were synthesized via the enzyme RpfF encoded by Xoo2868. DSF and BDSF at a final concentration of 3 μM to the rpfF mutant could fully restore its extracellular xylanase activity and EPS production to the wild type level, but CDSF was less active than DSF and BDSF in induction of EPS and xylanase. DSF and CDSF shared a similar cell density-dependent production time course with the maximum production being detected at 42 h after inoculation, whereas the maximum production of BDSF was observed

An automatic system for Turkish word recognition using Discrete Wavelet Neural Network based on adaptive entropy

International Nuclear Information System (INIS)

Avci, E.

2007-01-01

In this paper, an automatic system is presented for word recognition using real Turkish word signals. This paper especially deals with combination of the feature extraction and classification from real Turkish word signals. A Discrete Wavelet Neural Network (DWNN) model is used, which consists of two layers: discrete wavelet layer and multi-layer perceptron. The discrete wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of Discrete Wavelet Transform (DWT) and wavelet entropy. The multi-layer perceptron used for classification is a feed-forward neural network. The performance of the used system is evaluated by using noisy Turkish word signals. Test results showing the effectiveness of the proposed automatic system are presented in this paper. The rate of correct recognition is about 92.5% for the sample speech signals. (author)

Collective Functionality through Bacterial Individuality

Science.gov (United States)

Ackermann, Martin

According to the conventional view, the properties of an organism are a product of nature and nurture - of its genes and the environment it lives in. Recent experiments with unicellular organisms have challenged this view: several molecular mechanisms generate phenotypic variation independently of environmental signals, leading to variation in clonal groups. My presentation will focus on the causes and consequences of this microbial individuality. Using examples from bacterial genetic model systems, I will first discuss different molecular and cellular mechanisms that give rise to bacterial individuality. Then, I will discuss the consequences of individuality, and focus on how phenotypic variation in clonal populations of bacteria can promote interactions between individuals, lead to the division of labor, and allow clonal groups of bacteria to cope with environmental uncertainty. Variation between individuals thus provides clonal groups with collective functionality.

Immune receptors involved in Streptococcus suis recognition by dendritic cells.

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Marie-Pier Lecours

Full Text Available Streptococcus suis is an important swine pathogen and an emerging zoonotic agent of septicemia and meningitis. Knowledge on host immune responses towards S. suis, and strategies used by this pathogen for subversion of these responses is scarce. The objective of this study was to identify the immune receptors involved in S. suis recognition by dendritic cells (DCs. Production of cytokines and expression of co-stimulatory molecules by DCs were shown to strongly rely on MyD88-dependent signaling pathways, suggesting that DCs recognize S. suis and become activated mostly through Toll-like receptor (TLR signaling. Supporting this fact, TLR2(-/- DCs were severely impaired in the release of several cytokines and the surface expression of CD86 and MHC-II. The release of IL-12p70 and CXC10, and the expression of CD40 were found to depend on signaling by both TLR2 and TLR9. The release of IL-23 and CXCL1 were partially dependent on NOD2. Finally, despite the fact that MyD88 signaling was crucial for DC activation and maturation, MyD88-dependent pathways were not implicated in S. suis internalization by DCs. This first study on receptors involved in DC activation by S. suis suggests a major involvement of MyD88 signaling pathways, mainly (but not exclusively through TLR2. A multimodal recognition involving a combination of different receptors seems essential for DC effective response to S. suis.

An Uncommon Cause of Stroke: Non-bacterial Thrombotic Endocarditis.

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Gundersen, Hilde; Moynihan, Barry

2016-10-01

Our objective is to present the case of an uncommon but probably under-recognized cause of stroke: Non-bacterial thrombotic endocarditis (NBTE). A 59-year-old man presented to our hospital with multiple bihemispheric infarcts despite taking rivaroxaban for pulmonary emboli diagnosed 2 weeks earlier. The patient's symptoms progressed quickly and he died within a week of his initial presentation despite attempts at neuroradiologically guided clot retrieval and early recognition and treatment of disseminated intravascular coagulation. On postmortem examination it was discovered that he had an undiagnosed squamous cell adenocarcinoma of the lung and NBTE. NBTE is difficult to diagnose and difficult to treat. It is associated with a mortality rate and is often not diagnosed until autopsy. However there are case reports in the literature where NBTE has been successfully treated. Early recognition and prompt treatment of the underlying disease process is the essential first step. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Death and Survival in Streptococcus mutans: Differing Outcomes of a Quorum-Sensing Signalling Peptide

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Vincent eLeung

2015-10-01

Full Text Available Bacteria are considered ‘social’ organisms able to communicate with one another using small hormone-like molecules (pheromones in a process called quorum-sensing. These signalling molecules increase in concentration as a function of bacterial cell density. For most human pathogens, quorum-sensing is critical for virulence and biofilm formation, and the opportunity to interfere with bacterial quorum-sensing could provide a sophisticated means for manipulating the composition of pathogenic biofilms, and possibly eradicating the infection. Streptococcus mutans is a well-characterized resident of the dental plaque biofilm, and is the major pathogen of dental caries (tooth decay. In S. mutans, its CSP quorum-sensing signalling peptide does not act as a classical quorum-sensing signal by accumulating passively in proportion to cell density. In fact, particular stresses such as those encountered in the oral cavity, induces the production of the CSP pheromone, suggesting that the pheromone most probably functions as a stress-inducible alarmone by triggering the signalling to the bacterial population to initiate an adaptive response that results in different phenotypic outcomes. This mini-review discusses two different CSP-induced phenotypes, bacterial ‘suicide’ and dormancy, and the underlying mechanisms by which S. mutans utilizes the same quorum-sensing signalling peptide to regulate two opposite phenotypes.

Andrographolide suppresses TRIF-dependent signaling of toll-like receptors by targeting TBK1.

Science.gov (United States)

Kim, Ah-Yeon; Shim, Hyun-Jin; Shin, Hyeon-Myeong; Lee, Yoo Jung; Nam, Hyeonjeong; Kim, Su Yeon; Youn, Hyung-Sun

2018-04-01

Toll-like receptors (TLRs) play a crucial role in danger recognition and induction of innate immune response against bacterial and viral infections. The TLR adaptor molecule, toll-interleukin-1 receptor domain-containing adapter inducing interferon-β (TRIF), facilitates TLR3 and TLR4 signaling, leading to the activation of the transcription factor, NF-κB and interferon regulatory factor 3 (IRF3). Andrographolide, the active component of Andrographis paniculata, exerts anti-inflammatory effects; however, the principal molecular mechanisms remain unclear. The objective of this study was to investigate the role of andrographolide in TLR signaling pathways. Andrographolide suppressed NF-κB activation as well as COX-2 expression induced by TLR3 or TLR4 agonists. Andrographolide also suppressed the activation of IRF3 and the expression of interferon inducible protein-10 (IP-10) induced by TLR3 or TLR4 agonists. Andrographolide attenuated ligand-independent activation of IRF3 following overexpression of TRIF, TBK1, or IRF3. Furthermore, andrographolide inhibited TBK1 kinase activity in vitro. These results indicate that andrographolide modulates the TRIF-dependent pathway of TLRs by targeting TBK1 and represents a potential new anti-inflammatory candidate. Copyright © 2018 Elsevier B.V. All rights reserved.

Association of impaired facial affect recognition with basic facial and visual processing deficits in schizophrenia.

Science.gov (United States)

Norton, Daniel; McBain, Ryan; Holt, Daphne J; Ongur, Dost; Chen, Yue

2009-06-15

Impaired emotion recognition has been reported in schizophrenia, yet the nature of this impairment is not completely understood. Recognition of facial emotion depends on processing affective and nonaffective facial signals, as well as basic visual attributes. We examined whether and how poor facial emotion recognition in schizophrenia is related to basic visual processing and nonaffective face recognition. Schizophrenia patients (n = 32) and healthy control subjects (n = 29) performed emotion discrimination, identity discrimination, and visual contrast detection tasks, where the emotionality, distinctiveness of identity, or visual contrast was systematically manipulated. Subjects determined which of two presentations in a trial contained the target: the emotional face for emotion discrimination, a specific individual for identity discrimination, and a sinusoidal grating for contrast detection. Patients had significantly higher thresholds (worse performance) than control subjects for discriminating both fearful and happy faces. Furthermore, patients' poor performance in fear discrimination was predicted by performance in visual detection and face identity discrimination. Schizophrenia patients require greater emotional signal strength to discriminate fearful or happy face images from neutral ones. Deficient emotion recognition in schizophrenia does not appear to be determined solely by affective processing but is also linked to the processing of basic visual and facial information.

Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition.

Science.gov (United States)

Tao, Dapeng; Jin, Lianwen; Yuan, Yuan; Xue, Yang

2016-06-01

With the rapid development of mobile devices and pervasive computing technologies, acceleration-based human activity recognition, a difficult yet essential problem in mobile apps, has received intensive attention recently. Different acceleration signals for representing different activities or even a same activity have different attributes, which causes troubles in normalizing the signals. We thus cannot directly compare these signals with each other, because they are embedded in a nonmetric space. Therefore, we present a nonmetric scheme that retains discriminative and robust frequency domain information by developing a novel ensemble manifold rank preserving (EMRP) algorithm. EMRP simultaneously considers three aspects: 1) it encodes the local geometry using the ranking order information of intraclass samples distributed on local patches; 2) it keeps the discriminative information by maximizing the margin between samples of different classes; and 3) it finds the optimal linear combination of the alignment matrices to approximate the intrinsic manifold lied in the data. Experiments are conducted on the South China University of Technology naturalistic 3-D acceleration-based activity dataset and the naturalistic mobile-devices based human activity dataset to demonstrate the robustness and effectiveness of the new nonmetric scheme for acceleration-based human activity recognition.

Pattern-recognition software detecting the onset of failures in complex systems

International Nuclear Information System (INIS)

Mott, J.; King, R.

1987-01-01

A very general mathematical framework for embodying learned data from a complex system and combining it with a current observation to estimate the true current state of the system has been implemented using nearly universal pattern-recognition algorithms and applied to surveillance of the EBR-II power plant. In this application the methodology can provide signal validation and replacement of faulty signals on a near-real-time basis for hundreds of plant parameters. The mathematical framework, the pattern-recognition algorithms, examples of the learning and estimating process, and plant operating decisions made using this methodology are discussed. The entire methodology has been reduced to a set of FORTRAN subroutines which are small, fast, robust and executable on a personal computer with a serial link to the system's data acquisition computer, or on the data acquisition computer itself

Speech recognition in normal hearing and sensorineural hearing loss as a function of the number of spectral channels

NARCIS (Netherlands)

Baskent, Deniz

Speech recognition by normal-hearing listeners improves as a function of the number of spectral channels when tested with a noiseband vocoder simulating cochlear implant signal processing. Speech recognition by the best cochlear implant users, however, saturates around eight channels and does not

The T cell STAT signaling network is reprogrammed within hours of bacteremia via secondary signals1

Science.gov (United States)

Hotson, Andrew N.; Hardy, Jonathan W.; Hale, Matthew B.; Contag, Christopher H.; Nolan, Garry P.

2014-01-01

The delicate balance between protective immunity and inflammatory disease is challenged during sepsis, a pathologic state characterized by aspects of both a hyper-active immune response and immunosuppression. The events driven by systemic infection by bacterial pathogens on the T cell signaling network that likely control these responses have not been illustrated in great detail. We characterized how intracellular signaling within the immune compartment is reprogrammed at the single cell level when the host is challenged with a high levels of pathogen. To accomplish this, we applied flow cytometry to measure the phosphorylation potential of key signal transduction proteins during acute bacterial challenge. We modeled the onset of sepsis by intravenous administration of avirulent strains of Listeria and E. coli to mice. Within six hours of bacterial challenge, T cells were globally restricted in their ability to respond to specific cytokine stimulations as determined by assessing the extent of STAT protein phosphorylation. Mechanisms by which this negative feedback response occurred included SOCS1 and SOCS3 gene up regulation and IL-6 induced endocystosis of the IL-6 receptor. In addition, macrophages were partially tolerized in their ability to respond to TLR agonists. Thus, in contrast to the view that there is a wholesale immune activation during sepsis, one immediate host response to blood borne bacteria was induction of a refractory period during which leukocyte activation by specific stimulations was attenuated. PMID:19494279

Subversion of the Endocytic and Secretory Pathways by Bacterial Effector Proteins

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Mary M. Weber

2018-01-01

Full Text Available Intracellular bacteria have developed numerous strategies to hijack host vesicular trafficking pathways to form their unique replicative niches. To promote intracellular replication, the bacteria must interact with host organelles and modulate host signaling pathways to acquire nutrients and membrane for the growing parasitophorous vacuole all while suppressing activation of the immune response. To facilitate host cell subversion, bacterial pathogens use specialized secretion systems to deliver bacterial virulence factors, termed effectors, into the host cell that mimic, agonize, and/or antagonize the function of host proteins. In this review we will discuss how bacterial effector proteins from Coxiella burnetii, Brucella abortus, Salmonella enterica serovar Typhimurium, Legionella pneumophila, Chlamydia trachomatis, and Orientia tsutsugamushi manipulate the endocytic and secretory pathways. Understanding how bacterial effector proteins manipulate host processes not only gives us keen insight into bacterial pathogenesis, but also enhances our understanding of how eukaryotic membrane trafficking is regulated.

8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...

Oxytocin increases bias, but not accuracy, in face recognition line-ups.

Science.gov (United States)

Bate, Sarah; Bennetts, Rachel; Parris, Benjamin A; Bindemann, Markus; Udale, Robert; Bussunt, Amanda

2015-07-01

Previous work indicates that intranasal inhalation of oxytocin improves face recognition skills, raising the possibility that it may be used in security settings. However, it is unclear whether oxytocin directly acts upon the core face-processing system itself or indirectly improves face recognition via affective or social salience mechanisms. In a double-blind procedure, 60 participants received either an oxytocin or placebo nasal spray before completing the One-in-Ten task-a standardized test of unfamiliar face recognition containing target-present and target-absent line-ups. Participants in the oxytocin condition outperformed those in the placebo condition on target-present trials, yet were more likely to make false-positive errors on target-absent trials. Signal detection analyses indicated that oxytocin induced a more liberal response bias, rather than increasing accuracy per se. These findings support a social salience account of the effects of oxytocin on face recognition and indicate that oxytocin may impede face recognition in certain scenarios. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Bacterial toxins as pathogen weapons against phagocytes

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Ana edo Vale

2016-02-01

Full Text Available Bacterial toxins are virulence factors that manipulate host cell functions and take over the control of vital processes of living organisms to favour microbial infection. Some toxins directly target innate immune cells, thereby annihilating a major branch of the host immune response. In this review we will focus on bacterial toxins that act from the extracellular milieu and hinder the function of macrophages and neutrophils. In particular, we will concentrate on toxins from Gram-positive and Gram-negative bacteria that manipulate cell signalling or induce cell death by either imposing direct damage to the host cells cytoplasmic membrane or enzymatically modifying key eukaryotic targets. Outcomes regarding pathogen dissemination, host damage and disease progression will be discussed.

Object Recognition System-on-Chip Using the Support Vector Machines

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Houzet Dominique

2005-01-01

Full Text Available The first aim of this work is to propose the design of a system-on-chip (SoC platform dedicated to digital image and signal processing, which is tuned to implement efficiently multiply-and-accumulate (MAC vector/matrix operations. The second aim of this work is to implement a recent promising neural network method, namely, the support vector machine (SVM used for real-time object recognition, in order to build a vision machine. With such a reconfigurable and programmable SoC platform, it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform, based on the results of the learning phase on an objects' database, which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is a general-purpose automatic classifier. Many applications can be considered as a classification problem, but are usually treated specifically in order to optimize the cost of the implemented solution. The cost of our approach is more important than a dedicated one, but in a near future, hundreds of millions of gates will be common and affordable compared to the design cost. What we are proposing here is a general-purpose classification neural network implemented on a reconfigurable SoC platform. The first version presented here is limited in size and thus in object recognition performances, but can be easily upgraded according to technology improvements.

Heme as a danger molecule in pathogen recognition.

Science.gov (United States)

Wegiel, Barbara; Hauser, Carl J; Otterbein, Leo E

2015-12-01

Appropriate control of redox mechanisms are critical for and effective innate immune response, which employs multiple cell types, receptors and molecules that recognize danger signals when they reach the host. Recognition of pathogen-associated pattern molecules (PAMPs) is a fundamental host survival mechanism for efficient elimination of invading pathogens and resolution of the infection and inflammation. In addition to PAMPs, eukaryotic cells contain a plethora of intracellular molecules that are normally secured within the confines of the plasma membrane, but if liberated and encountered in the extracellular milieu can provoke rapid cell activation. These are known as Alarmins or Danger-Associated Molecular Patterns (DAMPs) and can be released actively by cells or passively as a result of sterile cellular injury after trauma, ischemia, or toxin-induced cell rupture. Both PAMPs and DAMPs are recognized by a series of cognate receptors that increase the generation of free radicals and activate specific signaling pathways that result in regulation of a variety of stress response, redox sensitive genes. Multiple mediators released, as cells die include, but are not limited to ATP, hydrogen peroxide, heme, formyl peptides, DNA or mitochondria provide the second signal to amplify immune responses. In this review, we will focus on how sterile and infective stimuli activate the stress response gene heme oxygenase-1 (Hmox1, HO-1), a master gene critical to an appropriate host response that is now recognized as one with enormous therapeutic potential. HO-1 gene expression is regulated in large part by redox-sensitive proteins including but not limited to nrf2. Both PAMPs and DAMPs increase the activation of nrf2 and HO-1. Heme is a powerful pro-oxidant and as such should be qualified as a DAMP. With its degradation by HO-1a molecule of carbon monoxide (CO) is generated that in turn serves as a bioactive signaling molecule. PAMPs such as bacterial endotoxin activate HO-1

Signal recognition particle assembly in relation to the function of amplified nucleoli of Xenopus oocytes.

Science.gov (United States)

Sommerville, John; Brumwell, Craig L; Politz, Joan C Ritland; Pederson, Thoru

2005-03-15

The signal recognition particle (SRP) is a ribonucleoprotein machine that controls the translation and intracellular sorting of membrane and secreted proteins. The SRP contains a core RNA subunit with which six proteins are assembled. Recent work in both yeast and mammalian cells has identified the nucleolus as a possible initial site of SRP assembly. In the present study, SRP RNA and protein components were identified in the extrachromosomal, amplified nucleoli of Xenopus laevis oocytes. Fluorescent SRP RNA microinjected into the oocyte nucleus became specifically localized in the nucleoli, and endogenous SRP RNA was also detected in oocyte nucleoli by RNA in situ hybridization. An initial step in the assembly of SRP involves the binding of the SRP19 protein to SRP RNA. When green fluorescent protein (GFP)-tagged SRP19 protein was injected into the oocyte cytoplasm it was imported into the nucleus and became concentrated in the amplified nucleoli. After visiting the amplified nucleoli, GFP-tagged SRP19 protein was detected in the cytoplasm in a ribonucleoprotein complex, having a sedimentation coefficient characteristic of the SRP. These results suggest that the amplified nucleoli of Xenopus oocytes produce maternal stores not only of ribosomes, the classical product of nucleoli, but also of SRP, presumably as a global developmental strategy for stockpiling translational machinery for early embryogenesis.

Evolution of novel signal traits in the absence of female preferences in Neoconocephalus katydids (Orthoptera, Tettigoniidae.

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Sarah L Bush

2010-08-01

Full Text Available BACKGROUND SIGNIFICANCE: Communication signals that function to bring together the sexes are important for maintaining reproductive isolation in many taxa. Changes in male calls are often attributed to sexual selection, in which female preferences initiate signal divergence. Natural selection can also influence signal traits if calls attract predators or parasitoids, or if calling is energetically costly. Neutral evolution is often neglected in the context of acoustic communication.We describe a signal trait that appears to have evolved in the absence of either sexual or natural selection. In the katydid genus Neoconocephalus, calls with a derived pattern in which pulses are grouped into pairs have evolved five times independently. We have previously shown that in three of these species, females require the double pulse pattern for call recognition, and hence the recognition system of the females is also in a derived state. Here we describe the remaining two species and find that although males produce the derived call pattern, females use the ancestral recognition mechanism in which no pulse pattern is required. Females respond equally well to the single and double pulse calls, indicating that the derived trait is selectively neutral in the context of mate recognition.These results suggest that 1 neutral changes in signal traits could be important in the diversification of communication systems, and 2 males rather than females may be responsible for initiating signal divergence.

A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors.

Science.gov (United States)

Cheng, Juan; Chen, Xun; Liu, Aiping; Peng, Hu

2015-09-15

Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (i.e., palm orientation represented by the mean and variance of ACC signals, hand movement represented by the fixed-point ACC sequence, and hand shape represented by both the mean absolute value (MAV) and autoregressive model coefficients (ARs)). Afterwards, palm orientation is first classified, distinguishing "Palm Downward" sign gestures from "Palm Inward" ones. Only the "Palm Inward" gestures are sent for further hand movement and hand shape recognition by dynamic time warping (DTW) algorithm and hidden Markov models (HMM) respectively. Finally, component recognition results are integrated to identify one certain coded gesture. Experimental results demonstrate that the proposed SLR framework with a vocabulary scale of 223 characters can achieve an averaged recognition accuracy of 96.01% ± 0.83% for coded gesture recognition tasks and 92.73% ± 1.47% for character recognition tasks. Besides, it demonstrats that sEMG signals are rather consistent for a given hand shape independent of hand movements. Hence, the number of training samples will not be significantly increased when the vocabulary scale increases, since not only the number of the completely new proposed coded gestures is constant and limited, but also the transition movement which connects successive signs needs no

De Novo Transcriptome Analysis Shows That SAV-3 Infection Upregulates Pattern Recognition Receptors of the Endosomal Toll-Like and RIG-I-Like Receptor Signaling Pathways in Macrophage/Dendritic Like TO-Cells

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Cheng Xu

2016-04-01

Full Text Available A fundamental step in cellular defense mechanisms is the recognition of “danger signals” made of conserved pathogen associated molecular patterns (PAMPs expressed by invading pathogens, by host cell germ line coded pattern recognition receptors (PRRs. In this study, we used RNA-seq and the Kyoto encyclopedia of genes and genomes (KEGG to identify PRRs together with the network pathway of differentially expressed genes (DEGs that recognize salmonid alphavirus subtype 3 (SAV-3 infection in macrophage/dendritic like TO-cells derived from Atlantic salmon (Salmo salar L headkidney leukocytes. Our findings show that recognition of SAV-3 in TO-cells was restricted to endosomal Toll-like receptors (TLRs 3 and 8 together with RIG-I-like receptors (RLRs and not the nucleotide-binding oligomerization domain-like receptors NOD-like receptor (NLRs genes. Among the RLRs, upregulated genes included the retinoic acid inducible gene I (RIG-I, melanoma differentiation association 5 (MDA5 and laboratory of genetics and physiology 2 (LGP2. The study points to possible involvement of the tripartite motif containing 25 (TRIM25 and mitochondrial antiviral signaling protein (MAVS in modulating RIG-I signaling being the first report that links these genes to the RLR pathway in SAV-3 infection in TO-cells. Downstream signaling suggests that both the TLR and RLR pathways use interferon (IFN regulatory factors (IRFs 3 and 7 to produce IFN-a2. The validity of RNA-seq data generated in this study was confirmed by quantitative real time qRT-PCR showing that genes up- or downregulated by RNA-seq were also up- or downregulated by RT-PCR. Overall, this study shows that de novo transcriptome assembly identify key receptors of the TLR and RLR sensors engaged in host pathogen interaction at cellular level. We envisage that data presented here can open a road map for future intervention strategies in SAV infection of salmon.

Bacterial quorum sensing and nitrogen cycling in rhizosphere soil

Energy Technology Data Exchange (ETDEWEB)

DeAngelis, K.M.; Lindow, S.E.; Firestone, M.K.

2008-10-01

Plant photosynthate fuels carbon-limited microbial growth and activity, resulting in increased rhizosphere nitrogen (N)-mineralization. Most soil organic N is macromolecular (chitin, protein, nucleotides); enzymatic depolymerization is likely rate-limiting for plant N accumulation. Analyzing Avena (wild oat) planted in microcosms containing sieved field soil, we observed increased rhizosphere chitinase and protease specific activities, bacterial cell densities, and dissolved organic nitrogen (DON) compared to bulk soil. Low-molecular weight DON (<3000 Da) was undetectable in bulk soil but comprised 15% of rhizosphere DON. Extracellular enzyme production in many bacteria requires quorum sensing (QS), cell-density dependent group behavior. Because proteobacteria are considered major rhizosphere colonizers, we assayed the proteobacterial QS signals acyl-homoserine lactones (AHLs), which were significantly increased in the rhizosphere. To investigate the linkage between soil signaling and N cycling, we characterized 533 bacterial isolates from Avena rhizosphere: 24% had chitinase or protease activity and AHL production; disruption of QS in 7 of 8 eight isolates disrupted enzyme activity. Many {alpha}-Proteobacteria were newly found with QS-controlled extracellular enzyme activity. Enhanced specific activities of N-cycling enzymes accompanied by bacterial density-dependent behaviors in rhizosphere soil gives rise to the hypothesis that QS could be a control point in the complex process of rhizosphere N-mineralization.

Fringe patterns generated by micro-optical sensors for pattern recognition.

Science.gov (United States)

Tamee, Kreangsak; Chaiwong, Khomyuth; Yothapakdee, Kriengsak; Yupapin, Preecha P

2015-01-01

We present a new result of pattern recognition generation scheme using a small-scale optical muscle sensing system, which consisted of an optical add-drop filter incorporating two nonlinear optical side ring resonators. When light from laser source enters into the system, the device is stimulated by an external physical parameter that introduces a change in the phase of light propagation within the sensing device, which can be formed by the interference fringe patterns. Results obtained have shown that the fringe patterns can be used to form the relationship between signal patterns and fringe pattern recognitions.

Improved Hip-Based Individual Recognition Using Wearable Motion Recording Sensor

Science.gov (United States)

Gafurov, Davrondzhon; Bours, Patrick

In todays society the demand for reliable verification of a user identity is increasing. Although biometric technologies based on fingerprint or iris can provide accurate and reliable recognition performance, they are inconvenient for periodic or frequent re-verification. In this paper we propose a hip-based user recognition method which can be suitable for implicit and periodic re-verification of the identity. In our approach we use a wearable accelerometer sensor attached to the hip of the person, and then the measured hip motion signal is analysed for identity verification purposes. The main analyses steps consists of detecting gait cycles in the signal and matching two sets of detected gait cycles. Evaluating the approach on a hip data set consisting of 400 gait sequences (samples) from 100 subjects, we obtained equal error rate (EER) of 7.5% and identification rate at rank 1 was 81.4%. These numbers are improvements by 37.5% and 11.2% respectively of the previous study using the same data set.

Embedded Face Detection and Recognition

Directory of Open Access Journals (Sweden)

Göksel Günlü

2012-10-01

Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on-site and on-time. At this point, the use of smart cameras – of which the popularity has been increasing – is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image-processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high-bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general-purpose processors. In smart cameras – which are real-life applications of such methods – the widest use is on DSPs. In the present study, the Viola-Jones face detection method – which was reported to run faster on PCs – was optimized for DSPs; the face recognition method was combined with the developed sub-region and mask-based DCT (Discrete Cosine Transform. As the employed DSP is a fixed-point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub-regions and from each sub-region the robust coefficients against disruptive elements – like face expression, illumination, etc. – were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for recognition. Thanks to its

The integration of familiarity and recollection information in short-term recognition: modeling speed-accuracy trade-off functions.

Science.gov (United States)

Göthe, Katrin; Oberauer, Klaus

2008-05-01

Dual process models postulate familiarity and recollection as the basis of the recognition process. We investigated the time-course of integration of the two information sources to one recognition judgment in a working memory task. We tested 24 subjects with a response signal variant of the modified Sternberg recognition task (Oberauer, 2001) to isolate the time course of three different probe types indicating different combinations of familiarity and source information. We compared two mathematical models implementing different ways of integrating familiarity and recollection. Within each model, we tested three assumptions about the nature of the familiarity signal, with familiarity having (a) only positive values, indicating similarity of the probe with the memory list, (b) only negative values, indicating novelty, or (c) both positive and negative values. Both models provided good fits to the data. A model combining the outputs of both processes additively (Integration Model) gave an overall better fit to the data than a model based on a continuous familiarity signal and a probabilistic all-or-none recollection process (Dominance Model).

Gesture recognition for smart home applications using portable radar sensors.

Science.gov (United States)

Wan, Qian; Li, Yiran; Li, Changzhi; Pal, Ranadip

2014-01-01

In this article, we consider the design of a human gesture recognition system based on pattern recognition of signatures from a portable smart radar sensor. Powered by AAA batteries, the smart radar sensor operates in the 2.4 GHz industrial, scientific and medical (ISM) band. We analyzed the feature space using principle components and application-specific time and frequency domain features extracted from radar signals for two different sets of gestures. We illustrate that a nearest neighbor based classifier can achieve greater than 95% accuracy for multi class classification using 10 fold cross validation when features are extracted based on magnitude differences and Doppler shifts as compared to features extracted through orthogonal transformations. The reported results illustrate the potential of intelligent radars integrated with a pattern recognition system for high accuracy smart home and health monitoring purposes.

Screening mycotoxins for quorum inhibition in a biocontrol bacterial endophyte

Science.gov (United States)

Bacterial endophytes are used as biocontrol organisms for plant pathogens such as the maize endophyte Fusarium verticillioides and its production of fumonisin mycotoxins. However, such applications are not always predictable and efficient. Bacteria communicate via cell-dependent signals, which are r...

Research on Interaction-oriented Gesture Recognition

Directory of Open Access Journals (Sweden)

Lu Huang

2014-01-01

Full Text Available This thesis designs a series of gesture interaction with the features of the natural human-machine interaction; besides, it utilizes the 3D acceleration sensors as interactive input. Afterwards, it builds the Discrete Hidden Markov Model to make gesture recognition by introducing the collection proposal of gesture interaction based on the acceleration sensors and pre-handling the gesture acceleration signal obtained in the collection. In the end, the thesis proofs the design proposal workable and effective according to the experiments.

Efficient iris recognition by characterizing key local variations.

Science.gov (United States)

Ma, Li; Tan, Tieniu; Wang, Yunhong; Zhang, Dexin

2004-06-01

Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image structure, are utilized to represent the characteristics of the iris. The whole procedure of feature extraction includes two steps: 1) a set of one-dimensional intensity signals is constructed to effectively characterize the most important information of the original two-dimensional image; 2) using a particular class of wavelets, a position sequence of local sharp variation points in such signals is recorded as features. We also present a fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences. Experimental results on 2255 iris images show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.

Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

Science.gov (United States)

Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

2018-01-01

Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

Bacterial subversion of host actin dynamics at the plasma membrane.

Science.gov (United States)

Carabeo, Rey

2011-10-01

Invasion of non-phagocytic cells by a number of bacterial pathogens involves the subversion of the actin cytoskeletal remodelling machinery to produce actin-rich cell surface projections designed to engulf the bacteria. The signalling that occurs to induce these actin-rich structures has considerable overlap among a diverse group of bacteria. The molecular organization within these structures act in concert to internalize the invading pathogen. This dynamic process could be subdivided into three acts - actin recruitment, engulfment, and finally, actin disassembly/internalization. This review will present the current state of knowledge of the molecular processes involved in each stage of bacterial invasion, and provide a perspective that highlights the temporal and spatial control of actin remodelling that occurs during bacterial invasion. © 2011 Blackwell Publishing Ltd.

Gait Recognition Based on Outermost Contour

Directory of Open Access Journals (Sweden)

Lili Liu

2011-10-01

Full Text Available Gait recognition aims to identify people by the way they walk. In this paper, a simple but e ective gait recognition method based on Outermost Contour is proposed. For each gait image sequence, an adaptive silhouette extraction algorithm is firstly used to segment the frames of the sequence and a series of postprocessing is applied to obtain the normalized silhouette images with less noise. Then a novel feature extraction method based on Outermost Contour is performed. Principal Component Analysis (PCA is adopted to reduce the dimensionality of the distance signals derived from the Outermost Contours of silhouette images. Then Multiple Discriminant Analysis (MDA is used to optimize the separability of gait features belonging to di erent classes. Nearest Neighbor (NN classifier and Nearest Neighbor classifier with respect to class Exemplars (ENN are used to classify the final feature vectors produced by MDA. In order to verify the e ectiveness and robustness of our feature extraction algorithm, we also use two other classifiers: Backpropagation Neural Network (BPNN and Support Vector Machine (SVM for recognition. Experimental results on a gait database of 100 people show that the accuracy of using MDA, BPNN and SVM can achieve 97.67%, 94.33% and 94.67%, respectively.

Age differences in right-wing authoritarianism and their relation to emotion recognition.

Science.gov (United States)

Ruffman, Ted; Wilson, Marc; Henry, Julie D; Dawson, Abigail; Chen, Yan; Kladnitski, Natalie; Myftari, Ella; Murray, Janice; Halberstadt, Jamin; Hunter, John A

2016-03-01

This study examined the correlates of right-wing authoritarianism (RWA) in older adults. Participants were given tasks measuring emotion recognition, executive functions and fluid IQ and questionnaires measuring RWA, perceived threat and social dominance orientation. Study 1 established higher age-related RWA across the age span in more than 2,600 New Zealanders. Studies 2 to 4 found that threat, education, social dominance and age all predicted unique variance in older adults' RWA, but the most consistent predictor was emotion recognition, predicting unique variance in older adults' RWA independent of all other variables. We argue that older adults' worse emotion recognition is associated with a more general change in social judgment. Expression of extreme attitudes (right- or left-wing) has the potential to antagonize others, but worse emotion recognition means that subtle signals will not be perceived, making the expression of extreme attitudes more likely. Our findings are consistent with other studies showing that worsening emotion recognition underlies age-related declines in verbosity, understanding of social gaffes, and ability to detect lies. Such results indicate that emotion recognition is a core social insight linked to many aspects of social cognition. (c) 2016 APA, all rights reserved).

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.

Application of the new pattern recognition system in the new e-nose to detecting Chinese spirits

International Nuclear Information System (INIS)

Gu Yu; Li Qiang

2014-01-01

We present a new pattern recognition system based on moving average and linear discriminant analysis (LDA), which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensitive sensor system we designed, called the new e-nose. Using the new e-nose, we obtain the template datum of Chinese spirits via a new pattern recognition system. To verify the effectiveness of the new pattern recognition system, we select three kinds of Chinese spirits to test, our results confirm that the new pattern recognition system can perfectly identify and distinguish between the Chinese spirits. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

Two-Component Signaling System VgrRS Directly Senses Extracytoplasmic and Intracellular Iron to Control Bacterial Adaptation under Iron Depleted Stress.

Directory of Open Access Journals (Sweden)

Li Wang

2016-12-01

Full Text Available Both iron starvation and excess are detrimental to cellular life, especially for animal and plant pathogens since they always live in iron-limited environments produced by host immune responses. However, how organisms sense and respond to iron is incompletely understood. Herein, we reveal that in the phytopathogenic bacterium Xanthomonas campestris pv. campestris, VgrS (also named ColS is a membrane-bound receptor histidine kinase that senses extracytoplasmic iron limitation in the periplasm, while its cognate response regulator, VgrR (ColR, detects intracellular iron excess. Under iron-depleted conditions, dissociation of Fe3+ from the periplasmic sensor region of VgrS activates the VgrS autophosphorylation and subsequent phosphotransfer to VgrR, an OmpR-family transcription factor that regulates bacterial responses to take up iron. VgrR-VgrS regulon and the consensus DNA binding motif of the transcription factor VgrR were dissected by comparative proteomic and ChIP-seq analyses, which revealed that in reacting to iron-depleted environments, VgrR directly or indirectly controls the expressions of hundreds of genes that are involved in various physiological cascades, especially those associated with iron-uptake. Among them, we demonstrated that the phosphorylated VgrR tightly represses the transcription of a special TonB-dependent receptor gene, tdvA. This regulation is a critical prerequisite for efficient iron uptake and bacterial virulence since activation of tdvA transcription is detrimental to these processes. When the intracellular iron accumulates, the VgrR-Fe2+ interaction dissociates not only the binding between VgrR and the tdvA promoter, but also the interaction between VgrR and VgrS. This relieves the repression in tdvA transcription to impede continuous iron uptake and avoids possible toxic effects of excessive iron accumulation. Our results revealed a signaling system that directly senses both extracytoplasmic and intracellular

Speech pattern recognition for forensic acoustic purposes

OpenAIRE

Herrera Martínez, Marcelo; Aldana Blanco, Andrea Lorena; Guzmán Palacios, Ana María

2014-01-01

The present paper describes the development of a software for analysis of acoustic voice parameters (APAVOIX), which can be used for forensic acoustic purposes, based on the speaker recognition and identification. This software enables to observe in a clear manner, the parameters which are sufficient and necessary when performing a comparison between two voice signals, the suspicious and the original one. These parameters are used according to the classic method, generally used by state entit...

Emotion of Physiological Signals Classification Based on TS Feature Selection

Institute of Scientific and Technical Information of China (English)

Wang Yujing; Mo Jianlin

2015-01-01

This paper propose a method of TS-MLP about emotion recognition of physiological signal.It can recognize emotion successfully by Tabu search which selects features of emotion’s physiological signals and multilayer perceptron that is used to classify emotion.Simulation shows that it has achieved good emotion classification performance.

Pattern recognition methods for acoustic emission analysis

International Nuclear Information System (INIS)

Doctor, P.G.; Harrington, T.P.; Hutton, P.H.

1979-07-01

Models have been developed that relate the rate of acoustic emissions to structural integrity. The implementation of these techniques in the field has been hindered by the noisy environment in which the data must be taken. Acoustic emissions from noncritical sources are recorded in addition to those produced by critical sources, such as flaws. A technique is discussed for prescreening acoustic events and filtering out those that are produced by noncritical sources. The methodology that was investigated is pattern recognition. Three different pattern recognition techniques were applied to a data set that consisted of acoustic emissions caused by crack growth and acoustic signals caused by extraneous noise sources. Examination of the acoustic emission data presented has uncovered several features of the data that can provide a reasonable filter. Two of the most valuable features are the frequency of maximum response and the autocorrelation coefficient at Lag 13. When these two features and several others were combined with a least squares decision algorithm, 90% of the acoustic emissions in the data set were correctly classified. It appears possible to design filters that eliminate extraneous noise sources from flaw-growth acoustic emissions using pattern recognition techniques

Multimodal approaches for emotion recognition: a survey

Science.gov (United States)

Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

2005-01-01

Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

Automated recognition system for ELM classification in JET

International Nuclear Information System (INIS)

Duro, N.; Dormido, R.; Vega, J.; Dormido-Canto, S.; Farias, G.; Sanchez, J.; Vargas, H.; Murari, A.

2009-01-01

Edge localized modes (ELMs) are instabilities occurring in the edge of H-mode plasmas. Considerable efforts are being devoted to understanding the physics behind this non-linear phenomenon. A first characterization of ELMs is usually their identification as type I or type III. An automated pattern recognition system has been developed in JET for off-line ELM recognition and classification. The empirical method presented in this paper analyzes each individual ELM instead of starting from a temporal segment containing many ELM bursts. The ELM recognition and isolation is carried out using three signals: Dα, line integrated electron density and stored diamagnetic energy. A reduced set of characteristics (such as diamagnetic energy drop, ELM period or Dα shape) has been extracted to build supervised and unsupervised learning systems for classification purposes. The former are based on support vector machines (SVM). The latter have been developed with hierarchical and K-means clustering methods. The success rate of the classification systems is about 98% for a database of almost 300 ELMs.

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

Directory of Open Access Journals (Sweden)

Masanao Sato

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

Aesthetic preference recognition of 3D shapes using EEG.

Science.gov (United States)

Chew, Lin Hou; Teo, Jason; Mountstephens, James

2016-04-01

Recognition and identification of aesthetic preference is indispensable in industrial design. Humans tend to pursue products with aesthetic values and make buying decisions based on their aesthetic preferences. The existence of neuromarketing is to understand consumer responses toward marketing stimuli by using imaging techniques and recognition of physiological parameters. Numerous studies have been done to understand the relationship between human, art and aesthetics. In this paper, we present a novel preference-based measurement of user aesthetics using electroencephalogram (EEG) signals for virtual 3D shapes with motion. The 3D shapes are designed to appear like bracelets, which is generated by using the Gielis superformula. EEG signals were collected by using a medical grade device, the B-Alert X10 from advance brain monitoring, with a sampling frequency of 256 Hz and resolution of 16 bits. The signals obtained when viewing 3D bracelet shapes were decomposed into alpha, beta, theta, gamma and delta rhythm by using time-frequency analysis, then classified into two classes, namely like and dislike by using support vector machines and K-nearest neighbors (KNN) classifiers respectively. Classification accuracy of up to 80 % was obtained by using KNN with the alpha, theta and delta rhythms as the features extracted from frontal channels, Fz, F3 and F4 to classify two classes, like and dislike.

Three regularities of recognition memory: the role of bias.

Science.gov (United States)

Hilford, Andrew; Maloney, Laurence T; Glanzer, Murray; Kim, Kisok

2015-12-01

A basic assumption of Signal Detection Theory is that decisions are made on the basis of likelihood ratios. In a preceding paper, Glanzer, Hilford, and Maloney (Psychonomic Bulletin & Review, 16, 431-455, 2009) showed that the likelihood ratio assumption implies that three regularities will occur in recognition memory: (1) the Mirror Effect, (2) the Variance Effect, (3) the normalized Receiver Operating Characteristic (z-ROC) Length Effect. The paper offered formal proofs and computational demonstrations that decisions based on likelihood ratios produce the three regularities. A survey of data based on group ROCs from 36 studies validated the likelihood ratio assumption by showing that its three implied regularities are ubiquitous. The study noted, however, that bias, another basic factor in Signal Detection Theory, can obscure the Mirror Effect. In this paper we examine how bias affects the regularities at the theoretical level. The theoretical analysis shows: (1) how bias obscures the Mirror Effect, not the other two regularities, and (2) four ways to counter that obscuring. We then report the results of five experiments that support the theoretical analysis. The analyses and the experimental results also demonstrate: (1) that the three regularities govern individual, as well as group, performance, (2) alternative explanations of the regularities are ruled out, and (3) that Signal Detection Theory, correctly applied, gives a simple and unified explanation of recognition memory data.

Human Age Recognition by Electrocardiogram Signal Based on Artificial Neural Network

Science.gov (United States)

Dasgupta, Hirak

2016-12-01

The objective of this work is to make a neural network function approximation model to detect human age from the electrocardiogram (ECG) signal. The input vectors of the neural network are the Katz fractal dimension of the ECG signal, frequencies in the QRS complex, male or female (represented by numeric constant) and the average of successive R-R peak distance of a particular ECG signal. The QRS complex has been detected by short time Fourier transform algorithm. The successive R peak has been detected by, first cutting the signal into periods by auto-correlation method and then finding the absolute of the highest point in each period. The neural network used in this problem consists of two layers, with Sigmoid neuron in the input and linear neuron in the output layer. The result shows the mean of errors as -0.49, 1.03, 0.79 years and the standard deviation of errors as 1.81, 1.77, 2.70 years during training, cross validation and testing with unknown data sets, respectively.

Bacterial computing: a form of natural computing and its applications.

Science.gov (United States)

Lahoz-Beltra, Rafael; Navarro, Jorge; Marijuán, Pedro C

2014-01-01

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular "learning" along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems.

Laser capture microdissection of bacterial cells targeted by fluorescence in situ hybridization

DEFF Research Database (Denmark)

Schou, Kirstine Klitgaard; Mølbak, Lars; Jensen, Tim Kåre

2005-01-01

RNA gene PCR was performed from the dissected microcolonies, and the subsequent DNA sequence analysis identified the dissected bacterial cells as belonging to the Brachyspira aalborgi cluster 1. The advantage of this technique is the ability to combine the histological recognition of the specific bacteria......Direct cultivation-independent sequence retrieval of unidentified bacteria from histological tissue sections has been limited by the difficulty of selectively isolating specific bacteria from a complex environment. Here, a new DNA isolation approach is presented for prokaryotic cells...

Bacterial intoxication evokes cellular senescence with persistent DNA damage and cytokine signalling

Czech Academy of Sciences Publication Activity Database

Blažková, Hana; Krejčíková, Kateřina; Moudrý, Pavel; Frisan, T.; Hodný, Zdeněk; Bartek, Jiří

2009-01-01

Roč. 14, 1-2 (2009), s. 357-367 ISSN 1582-1838 R&D Projects: GA AV ČR IAA500390501; GA ČR GA204/08/1418; GA ČR GA301/08/0353 Institutional research plan: CEZ:AV0Z50520514 Keywords : cellular senescence * DNA damage response * bacterial toxins Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 5.228, year: 2009

Genetic determinants of mate recognition in Brachionus manjavacas (Rotifera).

Science.gov (United States)

Snell, Terry W; Shearer, Tonya L; Smith, Hilary A; Kubanek, Julia; Gribble, Kristin E; Welch, David B Mark

2009-09-09

Mate choice is of central importance to most animals, influencing population structure, speciation, and ultimately the survival of a species. Mating behavior of male brachionid rotifers is triggered by the product of a chemosensory gene, a glycoprotein on the body surface of females called the mate recognition pheromone. The mate recognition pheromone has been biochemically characterized, but little was known about the gene(s). We describe the isolation and characterization of the mate recognition pheromone gene through protein purification, N-terminal amino acid sequence determination, identification of the mate recognition pheromone gene from a cDNA library, sequencing, and RNAi knockdown to confirm the functional role of the mate recognition pheromone gene in rotifer mating. A 29 kD protein capable of eliciting rotifer male circling was isolated by high-performance liquid chromatography. Two transcript types containing the N-terminal sequence were identified in a cDNA library; further characterization by screening a genomic library and by polymerase chain reaction revealed two genes belonging to each type. Each gene begins with a signal peptide region followed by nearly perfect repeats of an 87 to 92 codon motif with no codons between repeats and the final motif prematurely terminated by the stop codon. The two Type A genes contain four and seven repeats and the two Type B genes contain three and five repeats, respectively. Only the Type B gene with three repeats encodes a peptide with a molecular weight of 29 kD. Each repeat of the Type B gene products contains three asparagines as potential sites for N-glycosylation; there are no asparagines in the Type A genes. RNAi with Type A double-stranded RNA did not result in less circling than in the phosphate-buffered saline control, but transfection with Type B double-stranded RNA significantly reduced male circling by 17%. The very low divergence between repeat units, even at synonymous positions, suggests that the

Neutrophils to the ROScue: Mechanisms of NADPH Oxidase Activation and Bacterial Resistance

Directory of Open Access Journals (Sweden)

Giang T. Nguyen

2017-08-01

Full Text Available Reactive oxygen species (ROS generated by NADPH oxidase play an important role in antimicrobial host defense and inflammation. Their deficiency in humans results in recurrent and severe bacterial infections, while their unregulated release leads to pathology from excessive inflammation. The release of high concentrations of ROS aids in clearance of invading bacteria. Localization of ROS release to phagosomes containing pathogens limits tissue damage. Host immune cells, like neutrophils, also known as PMNs, will release large amounts of ROS at the site of infection following the activation of surface receptors. The binding of ligands to G-protein-coupled receptors (GPCRs, toll-like receptors, and cytokine receptors can prime PMNs for a more robust response if additional signals are encountered. Meanwhile, activation of Fc and integrin directly induces high levels of ROS production. Additionally, GPCRs that bind to the bacterial-peptide analog fMLP, a neutrophil chemoattractant, can both prime cells and trigger low levels of ROS production. Engagement of these receptors initiates intracellular signaling pathways, resulting in activation of downstream effector proteins, assembly of the NADPH oxidase complex, and ultimately, the production of ROS by this complex. Within PMNs, ROS released by the NADPH oxidase complex can activate granular proteases and induce the formation of neutrophil extracellular traps (NETs. Additionally, ROS can cross the membranes of bacterial pathogens and damage their nucleic acids, proteins, and cell membranes. Consequently, in order to establish infections, bacterial pathogens employ various strategies to prevent restriction by PMN-derived ROS or downstream consequences of ROS production. Some pathogens are able to directly prevent the oxidative burst of phagocytes using secreted effector proteins or toxins that interfere with translocation of the NADPH oxidase complex or signaling pathways needed for its activation

Methods for analysis of bacterial autoinducer-2 production.

Science.gov (United States)

Taga, Michiko E

2005-07-01

The quorum-sensing signal molecule autoinducer-2 (AI-2) is produced by over 50 diverse bacterial species and controls many different processes, including antibiotic production, biofilm formation, and virulence. AI-2 production often varies according to growth phase, media conditions, and the presence of specific factors. This unit describes a biological assay for AI-2 activity produced by a bacterial strain of interest. The assay employs an AI-2 reporter strain, Vibrio harveyi BB170, which produces light in response to AI-2. In the first stage of the assay, culture fluids of the bacterial strain of interest are collected over a time course of growth and filtered to remove cells. In the next stage, these culture fluids are mixed with BB170, and the light produced in response to AI-2 in the culture fluids is measured using a luminometer. BB170 is exquisitely sensitive to AI-2, and therefore, even low amounts of AI-2 can be detected using this bioassay.

Peptidoglycan recognition proteins kill bacteria by inducing oxidative, thiol, and metal stress.

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Des Raj Kashyap

2014-07-01

Full Text Available Mammalian Peptidoglycan Recognition Proteins (PGRPs are a family of evolutionary conserved bactericidal innate immunity proteins, but the mechanism through which they kill bacteria is unclear. We previously proposed that PGRPs are bactericidal due to induction of reactive oxygen species (ROS, a mechanism of killing that was also postulated, and later refuted, for several bactericidal antibiotics. Here, using whole genome expression arrays, qRT-PCR, and biochemical tests we show that in both Escherichia coli and Bacillus subtilis PGRPs induce a transcriptomic signature characteristic of oxidative stress, as well as correlated biochemical changes. However, induction of ROS was required, but not sufficient for PGRP killing. PGRPs also induced depletion of intracellular thiols and increased cytosolic concentrations of zinc and copper, as evidenced by transcriptome changes and supported by direct measurements. Depletion of thiols and elevated concentrations of metals were also required, but by themselves not sufficient, for bacterial killing. Chemical treatment studies demonstrated that efficient bacterial killing can be recapitulated only by the simultaneous addition of agents leading to production of ROS, depletion of thiols, and elevation of intracellular metal concentrations. These results identify a novel mechanism of bacterial killing by innate immunity proteins, which depends on synergistic effect of oxidative, thiol, and metal stress and differs from bacterial killing by antibiotics. These results offer potential targets for developing new antibacterial agents that would kill antibiotic-resistant bacteria.

Time and nature of the signal for maternal recognition of pregnancy in the pig

NARCIS (Netherlands)

Meulen, van der J.

1989-01-01

A vital link in a complex of physiological processes occurring during early pregnancy is the so-called maternal recognition of pregnancy: the prolongation of ovarian luteal function for continuation of progesterone secretion by an anti-luteolytic action of the developing embryos.

Man-system interface based on automatic speech recognition: integration to a virtual control desk

Energy Technology Data Exchange (ETDEWEB)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C., E-mail: calexandre@ien.gov.b, E-mail: mol@ien.gov.b, E-mail: cmnap@ien.gov.b, E-mail: mag@ien.gov.b [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Nomiya, Diogo V., E-mail: diogonomiya@gmail.co [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

2009-07-01

This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

Man-system interface based on automatic speech recognition: integration to a virtual control desk

International Nuclear Information System (INIS)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C.; Nomiya, Diogo V.

2009-01-01

This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

Optical Pattern Recognition

Science.gov (United States)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Application of image recognition-based automatic hyphae detection in fungal keratitis.

Science.gov (United States)

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal

A new selective developmental deficit: Impaired object recognition with normal face recognition.

Science.gov (United States)

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

Bacterial Molecular Signals in the Sinorhizobium fredii-Soybean Symbiosis

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Francisco J. López-Baena

2016-05-01

Full Text Available Sinorhizobium (Ensifer fredii (S. fredii is a rhizobial species exhibiting a remarkably broad nodulation host-range. Thus, S. fredii is able to effectively nodulate dozens of different legumes, including plants forming determinate nodules, such as the important crops soybean and cowpea, and plants forming indeterminate nodules, such as Glycyrrhiza uralensis and pigeon-pea. This capacity of adaptation to different symbioses makes the study of the molecular signals produced by S. fredii strains of increasing interest since it allows the analysis of their symbiotic role in different types of nodule. In this review, we analyze in depth different S. fredii molecules that act as signals in symbiosis, including nodulation factors, different surface polysaccharides (exopolysaccharides, lipopolysaccharides, cyclic glucans, and K-antigen capsular polysaccharides, and effectors delivered to the interior of the host cells through a symbiotic type 3 secretion system.

Proactive Interference Slows Recognition by Eliminating Fast Assessments of Familiarity

Science.gov (United States)

Oztekin, Ilke; McElree, Brian

2007-01-01

The response-signal speed-accuracy tradeoff (SAT) procedure was used to investigate how proactive interference (PI) affects retrieval from working memory. Participants were presented with 6-item study lists, followed immediately by a recognition probe. A variant of a release from PI design was used: All items in a list were from the same semantic…

Pattern-Recognition Receptor Signaling Regulator mRNA Expression in Humans and Mice, and in Transient Inflammation or Progressive Fibrosis

Science.gov (United States)

Günthner, Roman; Kumar, Vankayala Ramaiah Santhosh; Lorenz, Georg; Anders, Hans-Joachim; Lech, Maciej

2013-01-01

The cell type-, organ-, and species-specific expression of the pattern-recognition receptors (PRRs) are well described but little is known about the respective expression profiles of their negative regulators. We therefore determined the mRNA expression levels of A20, CYLD, DUBA, ST2, CD180, SIGIRR, TANK, SOCS1, SOCS3, SHIP, IRAK-M, DOK1, DOK2, SHP1, SHP2, TOLLIP, IRF4, SIKE, NLRX1, ERBIN, CENTB1, and Clec4a2 in human and mouse solid organs. Humans and mice displayed significant differences between their respective mRNA expression patterns of these factors. Additionally, we characterized their expression profiles in mononuclear blood cells upon bacterial endotoxin, which showed a consistent induction of A20, SOCS3, IRAK-M, and Clec4a2 in human and murine cells. Furthermore, we studied the expression pattern in transient kidney ischemia-reperfusion injury versus post-ischemic atrophy and fibrosis in mice. A20, CD180, ST2, SOCS1, SOCS3, SHIP, IRAK-M, DOK1, DOK2, IRF4, CENTB1, and Clec4a2 were all induced, albeit at different times of injury and repair. Progressive fibrosis was associated with a persistent induction of these factors. Thus, the organ- and species-specific expression patterns need to be considered in the design and interpretation of studies related to PRR-mediated innate immunity, which seems to be involved in tissue injury, tissue regeneration and in progressive tissue scarring. PMID:24009023

Role of innate T cells in anti-bacterial immunity

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Yifang eGao

2015-06-01

Full Text Available Innate T cells are a heterogeneous group of αβ and γδ T cells that respond rapidly (<2 hours upon activation. These innate T cells also share a non MHC class I or II restriction requirement for antigen recognition. Three major populations within the innate T cell group are recognized, namely Invariant NKT cells (iNKT; Mucosal associated invariant T cells (MAIT and gamma delta T cells. These cells recognize foreign/self-lipid presented by non-classical MHC molecules, such as CD1d, MR1 and CD1a.They are activated during the early stages of bacterial infection and act as a bridge between the innate and adaptive immune systems. In this review we focus on the functional properties of these 3 innate T cell populations and how they are purposed for antimicrobial defense. Furthermore we address the mechanisms through which their effector functions are targeted for bacterial control and compare this in human and murine systems. Lastly we speculate on future roles of these cell types in therapeutic settings such as vaccination.

Recognition of neural brain activity patterns correlated with complex motor activity

Science.gov (United States)

Kurkin, Semen; Musatov, Vyacheslav Yu.; Runnova, Anastasia E.; Grubov, Vadim V.; Efremova, Tatyana Yu.; Zhuravlev, Maxim O.

2018-04-01

In this paper, based on the apparatus of artificial neural networks, a technique for recognizing and classifying patterns corresponding to imaginary movements on electroencephalograms (EEGs) obtained from a group of untrained subjects was developed. The works on the selection of the optimal type, topology, training algorithms and neural network parameters were carried out from the point of view of the most accurate and fast recognition and classification of patterns on multi-channel EEGs associated with the imagination of movements. The influence of the number and choice of the analyzed channels of a multichannel EEG on the quality of recognition of imaginary movements was also studied, and optimal configurations of electrode arrangements were obtained. The effect of pre-processing of EEG signals is analyzed from the point of view of improving the accuracy of recognition of imaginary movements.

An effective approach for iris recognition using phase-based image matching.

Science.gov (United States)

Miyazawa, Kazuyuki; Ito, Koichi; Aoki, Takafumi; Kobayashi, Koji; Nakajima, Hiroshi

2008-10-01

This paper presents an efficient algorithm for iris recognition using phase-based image matching--an image matching technique using phase components in 2D Discrete Fourier Transforms (DFTs) of given images. Experimental evaluation using CASIA iris image databases (versions 1.0 and 2.0) and Iris Challenge Evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of iris images makes possible to achieve highly accurate iris recognition with a simple matching algorithm. This paper also discusses major implementation issues of our algorithm. In order to reduce the size of iris data and to prevent the visibility of iris images, we introduce the idea of 2D Fourier Phase Code (FPC) for representing iris information. The 2D FPC is particularly useful for implementing compact iris recognition devices using state-of-the-art Digital Signal Processing (DSP) technology.

Development of Infrared Lip Movement Sensor for Spoken Word Recognition

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Takahiro Yoshida

2007-12-01

Full Text Available Lip movement of speaker is very informative for many application of speech signal processing such as multi-modal speech recognition and password authentication without speech signal. However, in collecting multi-modal speech information, we need a video camera, large amount of memory, video interface, and high speed processor to extract lip movement in real time. Such a system tends to be expensive and large. This is one reasons of preventing the use of multi-modal speech processing. In this study, we have developed a simple infrared lip movement sensor mounted on a headset, and made it possible to acquire lip movement by PDA, mobile phone, and notebook PC. The sensor consists of an infrared LED and an infrared photo transistor, and measures the lip movement by the reflected light from the mouth region. From experiment, we achieved 66% successfully word recognition rate only by lip movement features. This experimental result shows that our developed sensor can be utilized as a tool for multi-modal speech processing by combining a microphone mounted on the headset.

The physical basis of bacterial quorum communication

CERN Document Server

2015-01-01

This book aims to educate physical scientists and quantitatively-oriented biologists on the application of physical experimentation and analysis, together with appropriate modeling, to understanding and interpreting microbial chemical communication and especially quorum sensing (QS). Quorum sensing describes a chemical communication behavior that is nearly universal among bacteria. Individual cells release a diffusible small molecule (an autoinducer) into their environment. A high concentration of this autoinducer serves as a signal of high population density, triggering new patterns of gene expression throughout the population. However QS is often much more complex than simple census-taking. Many QS bacteria produce and detect multiple autoinducers, which generate quorum signal cross talk with each other and with other bacterial species. QS gene regulatory networks operate in physically complex environments and respond to a range of inputs in addition to autoinducer signals. While many individual QS systems ...

Evolution and Design Governing Signal Precision and Amplification in a Bacterial Chemosensory Pathway.

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Mathilde Guzzo

2015-08-01

Full Text Available Understanding the principles underlying the plasticity of signal transduction networks is fundamental to decipher the functioning of living cells. In Myxococcus xanthus, a particular chemosensory system (Frz coordinates the activity of two separate motility systems (the A- and S-motility systems, promoting multicellular development. This unusual structure asks how signal is transduced in a branched signal transduction pathway. Using combined evolution-guided and single cell approaches, we successfully uncoupled the regulations and showed that the A-motility regulation system branched-off an existing signaling system that initially only controlled S-motility. Pathway branching emerged in part following a gene duplication event and changes in the circuit structure increasing the signaling efficiency. In the evolved pathway, the Frz histidine kinase generates a steep biphasic response to increasing external stimulations, which is essential for signal partitioning to the motility systems. We further show that this behavior results from the action of two accessory response regulator proteins that act independently to filter and amplify signals from the upstream kinase. Thus, signal amplification loops may underlie the emergence of new connectivity in signal transduction pathways.

Gesture recognition based on computer vision and glove sensor for remote working environments

Energy Technology Data Exchange (ETDEWEB)

Chien, Sung Il; Kim, In Chul; Baek, Yung Mok; Kim, Dong Su; Jeong, Jee Won; Shin, Kug [Kyungpook National University, Taegu (Korea)

1998-04-01

In this research, we defined a gesture set needed for remote monitoring and control of a manless system in atomic power station environments. Here, we define a command as the loci of a gesture. We aim at the development of an algorithm using a vision sensor and glove sensors in order to implement the gesture recognition system. The gesture recognition system based on computer vision tracks a hand by using cross correlation of PDOE image. To recognize the gesture word, the 8 direction code is employed as the input symbol for discrete HMM. Another gesture recognition based on sensor has introduced Pinch glove and Polhemus sensor as an input device. The extracted feature through preprocessing now acts as an input signal of the recognizer. For recognition 3D loci of Polhemus sensor, discrete HMM is also adopted. The alternative approach of two foregoing recognition systems uses the vision and and glove sensors together. The extracted mesh feature and 8 direction code from the locus tracking are introduced for further enhancing recognition performance. MLP trained by backpropagation is introduced here and its performance is compared to that of discrete HMM. (author). 32 refs., 44 figs., 21 tabs.

Double network bacterial cellulose hydrogel to build a biology-device interface

Science.gov (United States)

Shi, Zhijun; Li, Ying; Chen, Xiuli; Han, Hongwei; Yang, Guang

2013-12-01

Establishing a biology-device interface might enable the interaction between microelectronics and biotechnology. In this study, electroactive hydrogels have been produced using bacterial cellulose (BC) and conducting polymer (CP) deposited on the BC hydrogel surface to cover the BC fibers. The structures of these composites thus have double networks, one of which is a layer of electroactive hydrogels combined with BC and CP. The electroconductivity provides the composites with capabilities for voltage and current response, and the BC hydrogel layer provides good biocompatibility, biodegradability, bioadhesion and mass transport properties. Such a system might allow selective biological functions such as molecular recognition and specific catalysis and also for probing the detailed genetic and molecular mechanisms of life. A BC-CP composite hydrogel could then lead to a biology-device interface. Cyclic voltammetry and electrochemical impedance spectroscopy (EIS) are used here to study the composite hydrogels' electroactive property. BC-PAni and BC-PPy respond to voltage changes. This provides a mechanism to amplify electrochemical signals for analysis or detection. BC hydrogels were found to be able to support the growth, spreading and migration of human normal skin fibroblasts without causing any cytotoxic effect on the cells in the cell culture. These double network BC-CP hydrogels are biphasic Janus hydrogels which integrate electroactivity with biocompatibility, and might provide a biology-device interface to produce implantable devices for personalized and regenerative medicine.

Detection of Bacterial Endospores in Soil by Terbium Fluorescence

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Andrea Brandes Ammann

2011-01-01

Full Text Available Spore formation is a survival mechanism of microorganisms when facing unfavorable environmental conditions resulting in “dormant” states. We investigated the occurrence of bacterial endospores in soils from various locations including grasslands (pasture, meadow, allotment gardens, and forests, as well as fluvial sediments. Bacterial spores are characterized by their high content of dipicolinic acid (DPA. In the presence of terbium, DPA forms a complex showing a distinctive photoluminescence spectrum. DPA was released from soil by microwaving or autoclaving. The addition of aluminium chloride reduced signal quenching by interfering compounds such as phosphate. The highest spore content (up to 109 spores per gram of dry soil was found in grassland soils. Spore content is related to soil type, to soil depth, and to soil carbon-to-nitrogen ratio. Our study might provide a basis for the detection of “hot spots” of bacterial spores in soil.

Predicting the effect of spectral subtraction on the speech recognition threshold based on the signal-to-noise ratio in the envelope domain

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2011-01-01

rarely been evaluated perceptually in terms of speech intelligibility. This study analyzed the effects of the spectral subtraction strategy proposed by Berouti at al. [ICASSP 4 (1979), 208-211] on the speech recognition threshold (SRT) obtained with sentences presented in stationary speech-shaped noise....... The SRT was measured in five normal-hearing listeners in six conditions of spectral subtraction. The results showed an increase of the SRT after processing, i.e. a decreased speech intelligibility, in contrast to what is predicted by the Speech Transmission Index (STI). Here, another approach is proposed......, denoted the speech-based envelope power spectrum model (sEPSM) which predicts the intelligibility based on the signal-to-noise ratio in the envelope domain. In contrast to the STI, the sEPSM is sensitive to the increased amount of the noise envelope power as a consequence of the spectral subtraction...

Vitamin D signaling in intestinal innate immunity and homeostasis.

Science.gov (United States)

Dimitrov, Vassil; White, John H

2017-09-15

The lumen of the gut hosts a plethora of microorganisms that participate in food assimilation, inactivation of harmful particles and in vitamin synthesis. On the other hand, enteric flora, a number of food antigens, and toxins are capable of triggering immune responses causing inflammation, which, when unresolved, may lead to chronic conditions such as inflammatory bowel disease (IBD). It is important, therefore, to contain the gut bacteria within the lumen, control microbial load and composition, as well as ensure adequate innate and adaptive immune responses to pathogenic threats. There is growing evidence that vitamin D signaling has impacts on all these aspects of intestinal physiology, contributing to healthy enteric homeostasis. VD was first discovered as the curative agent for nutritional rickets, and its classical actions are associated with calcium absorption and bone health. However, vitamin D exhibits a number of extra-skeletal effects, particularly in innate immunity. Notably, it stimulates production of pattern recognition receptors, anti-microbial peptides, and cytokines, which are at the forefront of innate immune responses. They play a role in sensing the microbiota, in preventing excessive bacterial overgrowth, and complement the actions of vitamin D signaling in enhancing intestinal barrier function. Vitamin D also favours tolerogenic rather than inflammogenic T cell differentiation and function. Compromised innate immune function and overactive adaptive immunity, as well as defective intestinal barrier function, have been associated with IBD. Importantly, observational and intervention studies support a beneficial role of vitamin D supplementation in patients with Crohn's disease, a form of IBD. This review summarizes the effects of vitamin D signaling on barrier integrity and innate and adaptive immunity in the gut, as well as on microbial load and composition. Collectively, studies to date reveal that vitamin D signaling has widespread effects

Research on recognition of ramp angle based on transducer

Directory of Open Access Journals (Sweden)

Wenhao GU

2015-12-01

Full Text Available Focusing on the recognition of ramp angle, the relationship between the signal of vehicle transducer and real ramp angle is studied. The force change of vehicle on the ramp, and the relationship between the body tilt angle and front and rear suspension scale is discussed. According to the suspension and tire deformation, error angle of the ramp angle is deduced. A mathematical model is established with Matlab/Simulink and used for simulation to generate error curve of ramp angle. The results show that the error angle increases with the increasing of the ramp angle, and the limit value can reach 6.5%, while the identification method can effectively eliminate this error, and enhance the accuracy of ramp angle recognition.

Blind Recognition of Binary BCH Codes for Cognitive Radios

Directory of Open Access Journals (Sweden)

Jing Zhou

2016-01-01

Full Text Available A novel algorithm of blind recognition of Bose-Chaudhuri-Hocquenghem (BCH codes is proposed to solve the problem of Adaptive Coding and Modulation (ACM in cognitive radio systems. The recognition algorithm is based on soft decision situations. The code length is firstly estimated by comparing the Log-Likelihood Ratios (LLRs of the syndromes, which are obtained according to the minimum binary parity check matrixes of different primitive polynomials. After that, by comparing the LLRs of different minimum polynomials, the code roots and generator polynomial are reconstructed. When comparing with some previous approaches, our algorithm yields better performance even on very low Signal-Noise-Ratios (SNRs with lower calculation complexity. Simulation results show the efficiency of the proposed algorithm.

Histogram Equalization to Model Adaptation for Robust Speech Recognition

Directory of Open Access Journals (Sweden)

Suh Youngjoo

2010-01-01

Full Text Available We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained acoustic covariance models are efficiently adapted by the signal-to-noise ratio-dependent linear interpolation between trained covariance models and utterance-level sample covariance models. Speech recognition experiments on both the digit-based Aurora2 task and the large vocabulary-based task showed that the proposed model adaptation approach provides significant performance improvements compared to the baseline speech recognizer trained on the clean speech data.

Recognition of familiar food activates feeding via an endocrine serotonin signal in Caenorhabditis elegans

Science.gov (United States)

Song, Bo-mi; Faumont, Serge; Lockery, Shawn; Avery, Leon

2013-01-01

Familiarity discrimination has a significant impact on the pattern of food intake across species. However, the mechanism by which the recognition memory controls feeding is unclear. Here, we show that the nematode Caenorhabditis elegans forms a memory of particular foods after experience and displays behavioral plasticity, increasing the feeding response when they subsequently recognize the familiar food. We found that recognition of familiar food activates the pair of ADF chemosensory neurons, which subsequently increase serotonin release. The released serotonin activates the feeding response mainly by acting humorally and directly activates SER-7, a type 7 serotonin receptor, in MC motor neurons in the feeding organ. Our data suggest that worms sense the taste and/or smell of novel bacteria, which overrides the stimulatory effect of familiar bacteria on feeding by suppressing the activity of ADF or its upstream neurons. Our study provides insight into the mechanism by which familiarity discrimination alters behavior. DOI: http://dx.doi.org/10.7554/eLife.00329.001 PMID:23390589

Bacterial pathogenesis of plants: future challenges from a microbial perspective: Challenges in Bacterial Molecular Plant Pathology.

Science.gov (United States)

Pfeilmeier, Sebastian; Caly, Delphine L; Malone, Jacob G

2016-10-01

Plant infection is a complicated process. On encountering a plant, pathogenic microorganisms must first adapt to life on the epiphytic surface, and survive long enough to initiate an infection. Responsiveness to the environment is critical throughout infection, with intracellular and community-level signal transduction pathways integrating environmental signals and triggering appropriate responses in the bacterial population. Ultimately, phytopathogens must migrate from the epiphytic surface into the plant tissue using motility and chemotaxis pathways. This migration is coupled with overcoming the physical and chemical barriers to entry into the plant apoplast. Once inside the plant, bacteria use an array of secretion systems to release phytotoxins and protein effectors that fulfil diverse pathogenic functions (Fig. ) (Melotto and Kunkel, ; Phan Tran et al., ). As our understanding of the pathways and mechanisms underpinning plant pathogenicity increases, a number of central research challenges are emerging that will profoundly shape the direction of research in the future. We need to understand the bacterial phenotypes that promote epiphytic survival and surface adaptation in pathogenic bacteria. How do these pathways function in the context of the plant-associated microbiome, and what impact does this complex microbial community have on the onset and severity of plant infections? The huge importance of bacterial signal transduction to every stage of plant infection is becoming increasingly clear. However, there is a great deal to learn about how these signalling pathways function in phytopathogenic bacteria, and the contribution they make to various aspects of plant pathogenicity. We are increasingly able to explore the structural and functional diversity of small-molecule natural products from plant pathogens. We need to acquire a much better understanding of the production, deployment, functional redundancy and physiological roles of these molecules. Type III

Knee joint vibroarthrographic signal processing and analysis

CERN Document Server

Wu, Yunfeng

2015-01-01

This book presents the cutting-edge technologies of knee joint vibroarthrographic signal analysis for the screening and detection of knee joint injuries. It describes a number of effective computer-aided methods for analysis of the nonlinear and nonstationary biomedical signals generated by complex physiological mechanics. This book also introduces several popular machine learning and pattern recognition algorithms for biomedical signal classifications. The book is well-suited for all researchers looking to better understand knee joint biomechanics and the advanced technology for vibration arthrometry. Dr. Yunfeng Wu is an Associate Professor at the School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China.

Sparse coding of the modulation spectrum for noise-robust automatic speech recognition

NARCIS (Netherlands)

Ahmadi, S.; Ahadi, S.M.; Cranen, B.; Boves, L.W.J.

2014-01-01

The full modulation spectrum is a high-dimensional representation of one-dimensional audio signals. Most previous research in automatic speech recognition converted this very rich representation into the equivalent of a sequence of short-time power spectra, mainly to simplify the computation of the

A Recombinant Secondary Antibody Mimic as a Target-specific Signal Amplifier and an Antibody Immobilizer in Immunoassays.

Science.gov (United States)

Min, Junseon; Song, Eun Kyung; Kim, Hansol; Kim, Kyoung Taek; Park, Tae Joo; Kang, Sebyung

2016-04-11

We construct a novel recombinant secondary antibody mimic, GST-ABD, which can bind to the Fc regions of target-bound primary antibodies and acquire multiple HRPs simultaneously. We produce it in tenth of mg quantities with a bacterial overexpression system and simple purification procedures, significantly reducing the manufacturing cost and time without the use of animals. GST-ABD is effectively conjugated with 3 HRPs per molecule on an average and selectively bind to the Fc region of primary antibodies derived from three different species (mouse, rabbit, and rat). HRP-conjugated GST-ABD (HRP-GST-ABD) is successfully used as an alternative to secondary antibodies to amplify target-specific signals in both ELISA and immunohistochemistry regardless of the target molecules and origin of primary antibodies used. GST-ABD also successfully serves as an anchoring adaptor on the surface of GSH-coated plates for immobilizing antigen-capturing antibodies in an orientation-controlled manner for sandwich-type indirect ELISA through simple molecular recognition without any complicated chemical modification.

Unrealistic optimism and 'nosognosia': illness recognition in the healthy brain.

Science.gov (United States)

McKay, Ryan; Buchmann, Andreas; Germann, Nicole; Yu, Shancong; Brugger, Peter

2014-12-01

At the centenary of research on anosognosia, the time seems ripe to supplement work in anosognosic patients with empirical studies on nosognosia in healthy participants. To this end, we adopted a signal detection framework to investigate the lateralized recognition of illness words--an operational measure of nosognosia--in healthy participants. As positively biased reports about one's current health status (anosognosia) and future health status (unrealistic optimism) have both been associated with deficient right hemispheric functioning, and conversely with undisturbed left hemispheric functioning, we hypothesised that more optimistic participants would adopt a more conservative response criterion, and/or display less sensitivity, when identifying illnesses in our nosognosia task; especially harmful illnesses presented to the left hemisphere via the right visual field. Thirty-two healthy right-handed men estimated their own relative risk of contracting a series of illnesses in the future, and then completed a novel computer task assessing their recognition of illness names presented to the left or right visual field. To check that effects were specific to the recognition of illness (rather than reflecting recognition of lexical items per se), we also administered a standard lateralized lexical decision task. Highly optimistic participants tended to be more conservative in detecting illnesses, especially harmful illnesses presented to the right visual field. Contrary to expectation, they were also more sensitive to illness names in this half-field. We suggest that, in evolutionary terms, unrealistic optimism may be an adaptive trait that combines a high perceptual sensitivity to threat with a high threshold for acknowledging its presence. The signal detection approach to nosognosia developed here may open up new avenues for the understanding of anosognosia in neurological patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

A universal entropy-driven mechanism for thioredoxin–target recognition

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Palde, Prakash B.; Carroll, Kate S.

2015-01-01

Cysteine residues in cytosolic proteins are maintained in their reduced state, but can undergo oxidation owing to posttranslational modification during redox signaling or under conditions of oxidative stress. In large part, the reduction of oxidized protein cysteines is mediated by a small 12-kDa thiol oxidoreductase, thioredoxin (Trx). Trx provides reducing equivalents for central metabolic enzymes and is implicated in redox regulation of a wide number of target proteins, including transcription factors. Despite its importance in cellular redox homeostasis, the precise mechanism by which Trx recognizes target proteins, especially in the absence of any apparent signature binding sequence or motif, remains unknown. Knowledge of the forces associated with the molecular recognition that governs Trx–protein interactions is fundamental to our understanding of target specificity. To gain insight into Trx–target recognition, we have thermodynamically characterized the noncovalent interactions between Trx and target proteins before S-S reduction using isothermal titration calorimetry (ITC). Our findings indicate that Trx recognizes the oxidized form of its target proteins with exquisite selectivity, compared with their reduced counterparts. Furthermore, we show that recognition is dependent on the conformational restriction inherent to oxidized targets. Significantly, the thermodynamic signatures for multiple Trx targets reveal favorable entropic contributions as the major recognition force dictating these protein–protein interactions. Taken together, our data afford significant new insight into the molecular forces responsible for Trx–target recognition and should aid the design of new strategies for thiol oxidoreductase inhibition. PMID:26080424

[Enzymes for disrupting bacterial communication, an alternative to antibiotics?

Science.gov (United States)

Rémy, B; Plener, L; Elias, M; Daudé, D; Chabrière, E

2016-11-01

Quorum sensing (QS) is used by bacteria to communicate and synchronize their actions according to the cell density. In this way, they produce and secrete in the surrounding environment small molecules dubbed autoinducers (AIs) that regulate the expression of certain genes. The phenotypic traits regulated by QS are diverse and include pathogenicity, biofilm formation or resistance to anti-microbial treatments. The strategy, aiming at disrupting QS, known as quorum quenching (QQ), has emerged to counteract bacterial virulence and involves QS-inhibitors (QSI) or QQ-enzymes degrading AIs. Differently from antibiotics, QQ aims at blocking cell signaling and does not alter bacterial survival. This considerably decreases the selection pressure as compared to bactericide treatments and may reduce the occurrence of resistance mechanisms. QQ-enzymes are particularly appealing as they may disrupt molecular QS-signal without entering the cell and in a catalytic way. This review covers several aspects of QQ-based medical applications and the potential subsequent emergence of resistance is discussed. Copyright © 2016 Académie Nationale de Pharmacie. All rights reserved.

Modulation of immune response by bacterial lipopolysaccharides

Directory of Open Access Journals (Sweden)

Gustavo Aldapa-Vega

2016-08-01

Full Text Available Lipopolysaccharide (LPS is a molecule that is profusely found on the outer membrane of Gram-negative bacteria and is also a potent stimulator of the immune response. As the main molecule on the bacterial surface, is also the most biologically active. The immune response of the host is activated by the recognition of LPS through Toll-like receptor 4 (TLR4 and this receptor-ligand interaction is closely linked to LPS structure. Microorganisms have evolved systems to control the expression and structure of LPS, producing structural variants that are used for modulating the host immune responses during infection. Examples of this include Helicobacter pylori, Francisella tularensis, Chlamydia trachomatis and Salmonella spp. High concentrations of LPS can cause fever, increased heart rate and lead to septic shock and death. However, at relatively low concentrations some LPS are highly active immunomodulators, which can induce non-specific resistance to invading microorganisms. The elucidation of the molecular and cellular mechanisms involved in the recognition of LPS and its structural variants has been fundamental to understand inflammation and is currently a pivotal field of research to understand the innate immune response, inflammation, the complex host-pathogen relationship and has important implications for the rational development of new immunomodulators and adjuvants.

Signalling components of the house mouse mate recognition system