Hemispheric asymmetries of a motor memory in a recognition test after learning a movement sequence.

PubMed

Leinen, Peter; Panzer, Stefan; Shea, Charles H

2016-11-01

Two experiments utilizing a spatial-temporal movement sequence were designed to determine if the memory of the sequence is lateralized in the left or right hemisphere. In Experiment 1, dominant right-handers were randomly assigned to one of two acquisition groups: a left-hand starter and a right-hand starter group. After an acquisition phase, reaction time (RT) was measured in a recognition test by providing the learned sequential pattern in the left or right visual half-field for 150ms. In a retention test and two transfer tests the dominant coordinate system for sequence production was evaluated. In Experiment 2 dominant left-handers and dominant right-handers had to acquire the sequence with their dominant limb. The results of Experiment 1 indicated that RT was significantly shorter when the acquired sequence was provided in the right visual field during the recognition test. The same results occurred in Experiment 2 for dominant right-handers and left-handers. These results indicated a right visual field left hemisphere advantage in the recognition test for the practiced stimulus for dominant left and right-handers, when the task was practiced with the dominant limb. Copyright © 2016 Elsevier B.V. All rights reserved.

[GNU Pattern: open source pattern hunter for biological sequences based on SPLASH algorithm].

PubMed

Xu, Ying; Li, Yi-xue; Kong, Xiang-yin

2005-06-01

To construct a high performance open source software engine based on IBM SPLASH algorithm for later research on pattern discovery. Gpat, which is based on SPLASH algorithm, was developed by using open source software. GNU Pattern (Gpat) software was developped, which efficiently implemented the core part of SPLASH algorithm. Full source code of Gpat was also available for other researchers to modify the program under the GNU license. Gpat is a successful implementation of SPLASH algorithm and can be used as a basic framework for later research on pattern recognition in biological sequences.

The evolution of vertebrate Toll-like receptors

USGS Publications Warehouse

Roach, J.C.; Glusman, G.; Rowen, L.; Kaur, A.; Purcell, M.K.; Smith, K.D.; Hood, L.E.; Aderem, A.

2005-01-01

The complete sequences of Takifugu Toll-like receptor (TLR) loci and gene predictions from many draft genomes enable comprehensive molecular phylogenetic analysis. Strong selective pressure for recognition of and response to pathogen-associated molecular patterns has maintained a largely unchanging TLR recognition in all vertebrates. There are six major families of vertebrate TLRs. This repertoire is distinct from that of invertebrates. TLRs within a family recognize a general class of pathogen-associated molecular patterns. Most vertebrates have exactly one gene ortholog for each TLR family. The family including TLR1 has more species-specific adaptations than other families. A major family including TLR11 is represented in humans only by a pseudogene. Coincidental evolution plays a minor role in TLR evolution. The sequencing phase of this study produced finished genomic sequences for the 12 Takifugu rubripes TLRs. In addition, we have produced > 70 gene models, including sequences from the opossum, chicken, frog, dog, sea urchin, and sea squirt. ?? 2005 by The National Academy of Sciences of the USA.

Protein classification using sequential pattern mining.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2006-01-01

Protein classification in terms of fold recognition can be employed to determine the structural and functional properties of a newly discovered protein. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. One of the most efficient SPM algorithms, cSPADE, is employed for protein primary structure analysis. Then a classifier uses the extracted sequential patterns for classifying proteins of unknown structure in the appropriate fold category. The proposed methodology exhibited an overall accuracy of 36% in a multi-class problem of 17 candidate categories. The classification performance reaches up to 65% when the three most probable protein folds are considered.

The Coding of Biological Information: From Nucleotide Sequence to Protein Recognition

NASA Astrophysics Data System (ADS)

Štambuk, Nikola

The paper reviews the classic results of Swanson, Dayhoff, Grantham, Blalock and Root-Bernstein, which link genetic code nucleotide patterns to the protein structure, evolution and molecular recognition. Symbolic representation of the binary addresses defining particular nucleotide and amino acid properties is discussed, with consideration of: structure and metric of the code, direct correspondence between amino acid and nucleotide information, and molecular recognition of the interacting protein motifs coded by the complementary DNA and RNA strands.

Event-related potential correlates of declarative and non-declarative sequence knowledge.

PubMed

Ferdinand, Nicola K; Rünger, Dennis; Frensch, Peter A; Mecklinger, Axel

2010-07-01

The goal of the present study was to demonstrate that declarative and non-declarative knowledge acquired in an incidental sequence learning task contributes differentially to memory retrieval and leads to dissociable ERP signatures in a recognition memory task. For this purpose, participants performed a sequence learning task and were classified as verbalizers, partial verbalizers, or nonverbalizers according to their ability to verbally report the systematic response sequence. Thereafter, ERPs were recorded in a recognition memory task time-locked to sequence triplets that were either part of the previously learned sequence or not. Although all three groups executed old sequence triplets faster than new triplets in the recognition memory task, qualitatively distinct ERP patterns were found for participants with and without reportable knowledge. Verbalizers and, to a lesser extent, partial verbalizers showed an ERP correlate of recollection for parts of the incidentally learned sequence. In contrast, nonverbalizers showed a different ERP effect with a reverse polarity that might reflect priming. This indicates that an ensemble of qualitatively different processes is at work when declarative and non-declarative sequence knowledge is retrieved. By this, our findings favor a multiple-systems view postulating that explicit and implicit learning are supported by different and functionally independent systems. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Charge pattern matching as a ‘fuzzy’ mode of molecular recognition for the functional phase separations of intrinsically disordered proteins

NASA Astrophysics Data System (ADS)

Lin, Yi-Hsuan; Brady, Jacob P.; Forman-Kay, Julie D.; Chan, Hue Sun

2017-11-01

Biologically functional liquid-liquid phase separation of intrinsically disordered proteins (IDPs) is driven by interactions encoded by their amino acid sequences. Little is currently known about the molecular recognition mechanisms for distributing different IDP sequences into various cellular membraneless compartments. Pertinent physics was addressed recently by applying random-phase-approximation (RPA) polymer theory to electrostatics, which is a major energetic component governing IDP phase properties. RPA accounts for charge patterns and thus has advantages over Flory-Huggins (FH) and Overbeek-Voorn mean-field theories. To make progress toward deciphering the phase behaviors of multiple IDP sequences, the RPA formulation for one IDP species plus solvent is hereby extended to treat polyampholyte solutions containing two IDP species plus solvent. The new formulation generally allows for binary coexistence of two phases, each containing a different set of volume fractions ({φ }1,{φ }2) for the two different IDP sequences. The asymmetry between the two predicted coexisting phases with regard to their {φ }1/{φ }2 ratios for the two sequences increases with increasing mismatch between their charge patterns. This finding points to a multivalent, stochastic, ‘fuzzy’ mode of molecular recognition that helps populate various IDP sequences differentially into separate phase compartments. An intuitive illustration of this trend is provided by FH models, whereby a hypothetical case of ternary coexistence is also explored. Augmentations of the present RPA theory with a relative permittivity {ɛ }{{r}}(φ ) that depends on IDP volume fraction φ ={φ }1+{φ }2 lead to higher propensities to phase separate, in line with the case with one IDP species we studied previously. Notably, the cooperative, phase-separation-enhancing effects predicted by the prescriptions for {ɛ }{{r}}(φ ) we deem physically plausible are much more prominent than that entailed by common effective medium approximations based on Maxwell Garnett and Bruggeman mixing formulas. Ramifications of our findings on further theoretical development for IDP phase separation are discussed.

Applications of statistical physics and information theory to the analysis of DNA sequences

NASA Astrophysics Data System (ADS)

Grosse, Ivo

2000-10-01

DNA carries the genetic information of most living organisms, and the of genome projects is to uncover that genetic information. One basic task in the analysis of DNA sequences is the recognition of protein coding genes. Powerful computer programs for gene recognition have been developed, but most of them are based on statistical patterns that vary from species to species. In this thesis I address the question if there exist universal statistical patterns that are different in coding and noncoding DNA of all living species, regardless of their phylogenetic origin. In search for such species-independent patterns I study the mutual information function of genomic DNA sequences, and find that it shows persistent period-three oscillations. To understand the biological origin of the observed period-three oscillations, I compare the mutual information function of genomic DNA sequences to the mutual information function of stochastic model sequences. I find that the pseudo-exon model is able to reproduce the mutual information function of genomic DNA sequences. Moreover, I find that a generalization of the pseudo-exon model can connect the existence and the functional form of long-range correlations to the presence and the length distributions of coding and noncoding regions. Based on these theoretical studies I am able to find an information-theoretical quantity, the average mutual information (AMI), whose probability distributions are significantly different in coding and noncoding DNA, while they are almost identical in all studied species. These findings show that there exist universal statistical patterns that are different in coding and noncoding DNA of all studied species, and they suggest that the AMI may be used to identify genes in different living species, irrespective of their taxonomic origin.

Static hand gesture recognition from a video

NASA Astrophysics Data System (ADS)

Rokade, Rajeshree S.; Doye, Dharmpal

2011-10-01

A sign language (also signed language) is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns to convey meaning- "simultaneously combining hand shapes, orientation and movement of the hands". Sign languages commonly develop in deaf communities, which can include interpreters, friends and families of deaf people as well as people who are deaf or hard of hearing themselves. In this paper, we proposed a novel system for recognition of static hand gestures from a video, based on Kohonen neural network. We proposed algorithm to separate out key frames, which include correct gestures from a video sequence. We segment, hand images from complex and non uniform background. Features are extracted by applying Kohonen on key frames and recognition is done.

Schizophrenia patients demonstrate a dissociation on declarative and non-declarative memory tests.

PubMed

Perry, W; Light, G A; Davis, H; Braff, D L

2000-12-15

Declarative memory refers to the recall and recognition of factual information. In contrast, non-declarative memory entails a facilitation of memory based on prior exposure and is typically assessed with priming and perceptual-motor sequencing tasks. In this study, schizophrenia patients were compared to normal comparison subjects on two computerized memory tasks: the Word-stem Priming Test (n=30) and the Pattern Sequence Learning Test (n=20). Word-stem Priming includes recall, recognition (declarative) and priming (non-declarative) components of memory. The schizophrenia patients demonstrated an impaired performance on recall of words with relative improvement during the recognition portion of the test. Furthermore, they performed normally on the priming portion of the test. Thus, on tests of declarative memory, the patients had retrieval deficits with intact performance on the non-declarative memory component. The Pattern Sequence Learning Test utilizes a serial reaction time paradigm to assess non-declarative memory. The schizophrenia patients' serial reaction time was significantly slower than that of comparison subjects. However, the patients' rate of acquisition was not different from the normal comparison group. The data suggest that patients with schizophrenia process more slowly than normal, but have an intact non-declarative memory. The schizophrenia patients' dissociation on declarative vs. non-declarative memory tests is discussed in terms of possible underlying structural impairment.

Human activities recognition by head movement using partial recurrent neural network

NASA Astrophysics Data System (ADS)

Tan, Henry C. C.; Jia, Kui; De Silva, Liyanage C.

2003-06-01

Traditionally, human activities recognition has been achieved mainly by the statistical pattern recognition methods or the Hidden Markov Model (HMM). In this paper, we propose a novel use of the connectionist approach for the recognition of ten simple human activities: walking, sitting down, getting up, squatting down and standing up, in both lateral and frontal views, in an office environment. By means of tracking the head movement of the subjects over consecutive frames from a database of different color image sequences, and incorporating the Elman model of the partial recurrent neural network (RNN) that learns the sequential patterns of relative change of the head location in the images, the proposed system is able to robustly classify all the ten activities performed by unseen subjects from both sexes, of different race and physique, with a recognition rate as high as 92.5%. This demonstrates the potential of employing partial RNN to recognize complex activities in the increasingly popular human-activities-based applications.

The recognition and modification sites for the bacterial type I restriction systems KpnAI, StySEAI, StySENI and StySGI

PubMed Central

Kasarjian, Julie K. A.; Hidaka, Masumi; Horiuchi, Takashi; Iida, Masatake; Ryu, Junichi

2004-01-01

Using an in vivo plasmid transformation method, we have determined the DNA sequences recognized by the KpnAI, StySEAI, StySENI and StySGI R-M systems from Klebsiella oxytoca strain M5a1, Salmonella eastbourne, Salmonella enteritidis and Salmonella gelsenkirchen, respectively. These type I restriction-modification systems were originally identified using traditional phage assay, and described here is the plasmid transformation test and computer program used to determine their DNA recognition sequences. For this test, we constructed two sets of plasmids, pL and pE, that contain phage lambda and Escherichia coli K-12 chromosomal DNA fragments, respectively. Further, using the methylation sensitivities of various known type II restriction enzymes, we identified the target adenines for methylation (listed in bold italics below as A or T in case of the complementary strand). The recognition sequence and methylation sites are GAA(6N)TGCC (KpnAI), ACA(6N)TYCA (StySEAI), CGA(6N)TACC (StySENI) and TAAC(7N)RTCG (StySGI). These DNA recognition sequences all have a typical type I bipartite pattern and represent three novel specificities and one isoschizomer (StySENI). For confirmation, oligonucleotides containing each of the predicted sequences were synthesized, cloned into plasmid pMECA and transformed into each strain, resulting in a large reduction in efficiency of transformation (EOT). PMID:15199175

Bacteria evade immune recognition via TLR13 and binding of their 23S rRNA by MLS antibiotics by the same mechanisms

PubMed Central

Hochrein, Hubertus; Kirschning, Carsten J.

2013-01-01

The immune system recognizes pathogens and other danger by means of pattern recognition receptors. Recently, we have demonstrated that the orphan Toll-like receptor 13 (TLR13) senses a defined sequence of the bacterial rRNA and that bacteria use specific mechanisms to evade macrolide lincosamide streptogramin (MLS) antibiotics detection via TLR13. PMID:23802068

Algorithm, applications and evaluation for protein comparison by Ramanujan Fourier transform.

PubMed

Zhao, Jian; Wang, Jiasong; Hua, Wei; Ouyang, Pingkai

2015-12-01

The amino acid sequence of a protein determines its chemical properties, chain conformation and biological functions. Protein sequence comparison is of great importance to identify similarities of protein structures and infer their functions. Many properties of a protein correspond to the low-frequency signals within the sequence. Low frequency modes in protein sequences are linked to the secondary structures, membrane protein types, and sub-cellular localizations of the proteins. In this paper, we present Ramanujan Fourier transform (RFT) with a fast algorithm to analyze the low-frequency signals of protein sequences. The RFT method is applied to similarity analysis of protein sequences with the Resonant Recognition Model (RRM). The results show that the proposed fast RFT method on protein comparison is more efficient than commonly used discrete Fourier transform (DFT). RFT can detect common frequencies as significant feature for specific protein families, and the RFT spectrum heat-map of protein sequences demonstrates the information conservation in the sequence comparison. The proposed method offers a new tool for pattern recognition, feature extraction and structural analysis on protein sequences. Copyright © 2015 Elsevier Ltd. All rights reserved.

Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network.

PubMed

Zhao, Yongjia; Zhou, Suiping

2017-02-28

The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However, it is still a challenging task to reliably extract discriminative features for gait recognition with noisy and complex data sequences collected from casually worn wearable devices like smartphones. To cope with this problem, we propose a novel image-based gait recognition approach using the Convolutional Neural Network (CNN) without the need to manually extract discriminative features. The CNN's input image, which is encoded straightforwardly from the inertial sensor data sequences, is called Angle Embedded Gait Dynamic Image (AE-GDI). AE-GDI is a new two-dimensional representation of gait dynamics, which is invariant to rotation and translation. The performance of the proposed approach in gait authentication and gait labeling is evaluated using two datasets: (1) the McGill University dataset, which is collected under realistic conditions; and (2) the Osaka University dataset with the largest number of subjects. Experimental results show that the proposed approach achieves competitive recognition accuracy over existing approaches and provides an effective parametric solution for identification among a large number of subjects by gait patterns.

Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network

PubMed Central

Zhao, Yongjia; Zhou, Suiping

2017-01-01

The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However, it is still a challenging task to reliably extract discriminative features for gait recognition with noisy and complex data sequences collected from casually worn wearable devices like smartphones. To cope with this problem, we propose a novel image-based gait recognition approach using the Convolutional Neural Network (CNN) without the need to manually extract discriminative features. The CNN’s input image, which is encoded straightforwardly from the inertial sensor data sequences, is called Angle Embedded Gait Dynamic Image (AE-GDI). AE-GDI is a new two-dimensional representation of gait dynamics, which is invariant to rotation and translation. The performance of the proposed approach in gait authentication and gait labeling is evaluated using two datasets: (1) the McGill University dataset, which is collected under realistic conditions; and (2) the Osaka University dataset with the largest number of subjects. Experimental results show that the proposed approach achieves competitive recognition accuracy over existing approaches and provides an effective parametric solution for identification among a large number of subjects by gait patterns. PMID:28264503

Tracking down the path of memory: eye scanpaths facilitate retrieval of visuospatial information.

PubMed

Bochynska, Agata; Laeng, Bruno

2015-09-01

Recent research points to a crucial role of eye fixations on the same spatial locations where an item appeared when learned, for the successful retrieval of stored information (e.g., Laeng et al. in Cognition 131:263-283, 2014. doi: 10.1016/j.cognition.2014.01.003 ). However, evidence about whether the specific temporal sequence (i.e., scanpath) of these eye fixations is also relevant for the accuracy of memory remains unclear. In the current study, eye fixations were recorded while looking at a checkerboard-like pattern. In a recognition session (48 h later), animations were shown where each square that formed the pattern was presented one by one, either according to the same, idiosyncratic, temporal sequence in which they were originally viewed by each participant or in a shuffled sequence although the squares were, in both conditions, always in their correct positions. Afterward, participants judged whether they had seen the same pattern before or not. Showing the elements serially according to the original scanpath's sequence yielded a significantly better recognition performance than the shuffled condition. In a forced fixation condition, where the gaze was maintained on the center of the screen, the advantage of memory accuracy for same versus shuffled scanpaths disappeared. Concluding, gaze scanpaths (i.e., the order of fixations and not simply their positions) are functional to visual memory and physical reenacting of the original, embodied, perception can facilitate retrieval.

Serial position effects in recognition memory for odors: a reexamination.

PubMed

Miles, Christopher; Hodder, Kathryn

2005-10-01

Seven experiments examined recognition memory for sequentially presented odors. Following Reed (2000), participants were presented with a sequence of odors and then required to identify an odor from the sequence in a test probe comprising 2 odors. The pattern of results obtained by Reed (2000, although statistically marginal) demonstrated enhanced recognition for odors presented at the start (primacy) and end (recency) of the sequence: a result that we failed to replicate in any of the experiments reported here. Experiments 1 and 3 were designed to replicate Reed (2000), employing five-item and seven-item sequences, respectively, and each demonstrated significant recency, with evidence of primacy in Experiment 3 only. Experiment 2 replicated Experiment 1, with reduced interstimulus intervals, and produced a null effect of serial position. The ease with which the odors could be verbally labeled was manipulated in Experiments 4 and 5. Nameable odors produced a null effect of serial position (Experiment 4), and hard-to-name odors produced a pronounced recency effect (Experiment 5); nevertheless, overall rates of recognition were remarkably similar for the two experiments at around 70%. Articulatory suppression reduced recognition accuracy (Experiment 6), but recency was again present in the absence of primacy. Odor recognition performance was immune to the effects of an interleaved odor (Experiment 7), and, again, both primacy and recency effects were absent. There was no evidence of olfactory fatigue: Recognition accuracy improved across trials (Experiment 1). It is argued that the results of the experiments reported here are generally consistent with that body of work employing hard-to-name visual stimuli, where recency is obtained in the absence of primacy when the retention interval is short.

Continuous Chinese sign language recognition with CNN-LSTM

NASA Astrophysics Data System (ADS)

Yang, Su; Zhu, Qing

2017-07-01

The goal of sign language recognition (SLR) is to translate the sign language into text, and provide a convenient tool for the communication between the deaf-mute and the ordinary. In this paper, we formulate an appropriate model based on convolutional neural network (CNN) combined with Long Short-Term Memory (LSTM) network, in order to accomplish the continuous recognition work. With the strong ability of CNN, the information of pictures captured from Chinese sign language (CSL) videos can be learned and transformed into vector. Since the video can be regarded as an ordered sequence of frames, LSTM model is employed to connect with the fully-connected layer of CNN. As a recurrent neural network (RNN), it is suitable for sequence learning tasks with the capability of recognizing patterns defined by temporal distance. Compared with traditional RNN, LSTM has performed better on storing and accessing information. We evaluate this method on our self-built dataset including 40 daily vocabularies. The experimental results show that the recognition method with CNN-LSTM can achieve a high recognition rate with small training sets, which will meet the needs of real-time SLR system.

Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

PubMed Central

Alam, Mohammad S.; Bhuiyan, Sharif M. A.

2014-01-01

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

Codon-Anticodon Recognition in the Bacillus subtilis glyQS T Box Riboswitch

PubMed Central

Caserta, Enrico; Liu, Liang-Chun; Grundy, Frank J.; Henkin, Tina M.

2015-01-01

Many amino acid-related genes in Gram-positive bacteria are regulated by the T box riboswitch. The leader RNA of genes in the T box family controls the expression of downstream genes by monitoring the aminoacylation status of the cognate tRNA. Previous studies identified a three-nucleotide codon, termed the “Specifier Sequence,” in the riboswitch that corresponds to the amino acid identity of the downstream genes. Pairing of the Specifier Sequence with the anticodon of the cognate tRNA is the primary determinant of specific tRNA recognition. This interaction mimics codon-anticodon pairing in translation but occurs in the absence of the ribosome. The goal of the current study was to determine the effect of a full range of mismatches for comparison with codon recognition in translation. Mutations were individually introduced into the Specifier Sequence of the glyQS leader RNA and tRNAGly anticodon to test the effect of all possible pairing combinations on tRNA binding affinity and antitermination efficiency. The functional role of the conserved purine 3′ of the Specifier Sequence was also verifiedin this study. We found that substitutions at the Specifier Sequence resulted in reduced binding, the magnitude of which correlates well with the predicted stability of the RNA-RNA pairing. However, the tolerance for specific mismatches in antitermination was generally different from that during decoding, which reveals a unique tRNA recognition pattern in the T box antitermination system. PMID:26229106

An SRY mutation causing human sex reversal resolves a general mechanism of structure-specific DNA recognition: application to the four-way DNA junction.

PubMed

Peters, R; King, C Y; Ukiyama, E; Falsafi, S; Donahoe, P K; Weiss, M A

1995-04-11

SRY, a genetic "master switch" for male development in mammals, exhibits two biochemical activities: sequence-specific recognition of duplex DNA and sequence-independent binding to the sharp angles of four-way DNA junctions. Here, we distinguish between these activities by analysis of a mutant SRY associated with human sex reversal (46, XY female with pure gonadal dysgenesis). The substitution (168T in human SRY) alters a nonpolar side chain in the minor-groove DNA recognition alpha-helix of the HMG box [Haqq, C.M., King, C.-Y., Ukiyama, E., Haqq, T.N., Falsalfi, S., Donahoe, P.K., & Weiss, M.A. (1994) Science 266, 1494-1500]. The native (but not mutant) side chain inserts between specific base pairs in duplex DNA, interrupting base stacking at a site of induced DNA bending. Isotope-aided 1H-NMR spectroscopy demonstrates that analogous side-chain insertion occurs on binding of SRY to a four-way junction, establishing a shared mechanism of sequence- and structure-specific DNA binding. Although the mutant DNA-binding domain exhibits > 50-fold reduction in sequence-specific DNA recognition, near wild-type affinity for four-way junctions is retained. Our results (i) identify a shared SRY-DNA contact at a site of either induced or intrinsic DNA bending, (ii) demonstrate that this contact is not required to bind an intrinsically bent DNA target, and (iii) rationalize patterns of sequence conservation or diversity among HMG boxes. Clinical association of the I68T mutation with human sex reversal supports the hypothesis that specific DNA recognition by SRY is required for male sex determination.

Comprehensive Development Program of Hunter-Killer Peptides for Prostate Cancer

DTIC Science & Technology

2004-05-01

sequence-pattern recognition approach identifies substance P as a potential apoptotic peptide Gabriel del Rio, Susana Castro-Obregon, Rammohan Rao, H... Daniel Rajotte*.**, Stanislaw Krajewski*, H. Michael Ellerby*St , Dale E. Bredesen*st , Renata Pasqualini*", and Erkki Ruoslahti*** *Cancer Research

A shared representation of order between encoding and recognition in visual short-term memory.

PubMed

Kalm, Kristjan; Norris, Dennis

2017-07-15

Many complex tasks require people to bind individual events into a sequence that can be held in short term memory (STM). For this purpose information about the order of the individual events in the sequence needs to be maintained in an active and accessible form in STM over a period of few seconds. Here we investigated how the temporal order information is shared between the presentation and response phases of an STM task. We trained a classification algorithm on the fMRI activity patterns from the presentation phase of the STM task to predict the order of the items during the subsequent recognition phase. While voxels in a number of brain regions represented positional information during either presentation and recognition phases, only voxels in the lateral prefrontal cortex (PFC) and the anterior temporal lobe (ATL) represented position consistently across task phases. A shared positional code in the ATL might reflect verbal recoding of visual sequences to facilitate the maintenance of order information over several seconds. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Pattern recognition and feature extraction with an optical Hough transform

NASA Astrophysics Data System (ADS)

Fernández, Ariel

2016-09-01

Pattern recognition and localization along with feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for the recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital- only methods. Starting from the integral representation of the GHT, it is possible to device an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a rotating pupil mask for orientation variation, implemented on a high-contrast spatial light modulator (SLM). Real-time (as limited by the frame rate of the device used to capture the GHT) can also be achieved, allowing for the processing of video sequences. Besides, by thresholding of the GHT (with the aid of another SLM) and inverse transforming (which is optically achieved in the incoherent system under appropriate focusing setting), the previously detected features of interest can be extracted.

Robust Radio Broadcast Monitoring Using a Multi-Band Spectral Entropy Signature

NASA Astrophysics Data System (ADS)

Camarena-Ibarrola, Antonio; Chávez, Edgar; Tellez, Eric Sadit

Monitoring media broadcast content has deserved a lot of attention lately from both academy and industry due to the technical challenge involved and its economic importance (e.g. in advertising). The problem pose a unique challenge from the pattern recognition point of view because a very high recognition rate is needed under non ideal conditions. The problem consist in comparing a small audio sequence (the commercial ad) with a large audio stream (the broadcast) searching for matches.

Human action recognition based on spatial-temporal descriptors using key poses

NASA Astrophysics Data System (ADS)

Hu, Shuo; Chen, Yuxin; Wang, Huaibao; Zuo, Yaqing

2014-11-01

Human action recognition is an important area of pattern recognition today due to its direct application and need in various occasions like surveillance and virtual reality. In this paper, a simple and effective human action recognition method is presented based on the key poses of human silhouette and the spatio-temporal feature. Firstly, the contour points of human silhouette have been gotten, and the key poses are learned by means of K-means clustering based on the Euclidean distance between each contour point and the centre point of the human silhouette, and then the type of each action is labeled for further match. Secondly, we obtain the trajectories of centre point of each frame, and create a spatio-temporal feature value represented by W to describe the motion direction and speed of each action. The value W contains the information of location and temporal order of each point on the trajectories. Finally, the matching stage is performed by comparing the key poses and W between training sequences and test sequences, the nearest neighbor sequences is found and its label supplied the final result. Experiments on the public available Weizmann datasets show the proposed method can improve accuracy by distinguishing amphibious poses and increase suitability for real-time applications by reducing the computational cost.

Morphological self-organizing feature map neural network with applications to automatic target recognition

NASA Astrophysics Data System (ADS)

Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

2005-01-01

The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

Techniques for generation of control and guidance signals derived from optical fields, part 2

NASA Technical Reports Server (NTRS)

Hemami, H.; Mcghee, R. B.; Gardner, S. R.

1971-01-01

The development is reported of a high resolution technique for the detection and identification of landmarks from spacecraft optical fields. By making use of nonlinear regression analysis, a method is presented whereby a sequence of synthetic images produced by a digital computer can be automatically adjusted to provide a least squares approximation to a real image. The convergence of the method is demonstrated by means of a computer simulation for both elliptical and rectangular patterns. Statistical simulation studies with elliptical and rectangular patterns show that the computational techniques developed are able to at least match human pattern recognition capabilities, even in the presence of large amounts of noise. Unlike most pattern recognition techniques, this ability is unaffected by arbitrary pattern rotation, translation, and scale change. Further development of the basic approach may eventually allow a spacecraft or robot vehicle to be provided with an ability to very accurately determine its spatial relationship to arbitrary known objects within its optical field of view.

A novel paired domain DNA recognition motif can mediate Pax2 repression of gene transcription.

PubMed

Håvik, B; Ragnhildstveit, E; Lorens, J B; Saelemyr, K; Fauske, O; Knudsen, L K; Fjose, A

1999-12-20

The paired domain (PD) is an evolutionarily conserved DNA-binding domain encoded by the Pax gene family of developmental regulators. The Pax proteins are transcription factors and are involved in a variety of processes such as brain development, patterning of the central nervous system (CNS), and B-cell development. In this report we demonstrate that the zebrafish Pax2 PD can interact with a novel type of DNA sequences in vitro, the triple-A motif, consisting of a heptameric nucleotide sequence G/CAAACA/TC with an invariant core of three adjacent adenosines. This recognition sequence was found to be conserved in known natural Pax5 repressor elements involved in controlling the expression of the p53 and J-chain genes. By identifying similar high affinity binding sites in potential target genes of the Pax2 protein, including the pax2 gene itself, we obtained further evidence that the triple-A sites are biologically significant. The putative natural target sites also provide a basis for defining an extended consensus recognition sequence. In addition, we observed in transformation assays a direct correlation between Pax2 repressor activity and the presence of triple-A sites. The results suggest that a transcriptional regulatory function of Pax proteins can be modulated by PD binding to different categories of target sequences. Copyright 1999 Academic Press.

Structural requirements for recognition of the HLA-Dw14 class II epitope: A key HLA determinant associated with rheumatoid arthritis

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

Hiraiwa, Akikazu; Yamanaka, Katsuo; Kwok, W.W.

Although HLA genes have been shown to be associated with certain diseases, the basis for this association is unknown. Recent studies, however, have documented patterns of nucleotide sequence variation among some HLA genes associated with a particular disease. For rheumatoid arthritis, HLA genes in most patients have a shared nucleotide sequence encoding a key structural element of an HLA class II polypeptide; this sequence element is critical for the interaction of the HLA molecule with antigenic peptides and with responding T cells, suggestive of a direct role for this sequence element in disease susceptibility. The authors describe the serological andmore » cellular immunologic characteristics encoded by this rheumatoid arthritis-associated sequence element. Site-directed mutagenesis of the DRB1 gene was used to define amino acids critical for antibody and T-cell recognition of this structural element, focusing on residues that distinguish the rheumatoid arthritis-associated alleles Dw4 and Dw14 from a closely related allele, Dw10, not associated with disease. Both the gain and loss of rheumatoid arthritis-associated epitopes were highly dependent on three residues within a discrete domain of the HLA-DR molecule. Recognition was most strongly influenced by the following amino acids (in order): 70 > 71 > 67. Some alloreactive T-cell clones were also influenced by amino acid variation in portions of the DR molecule lying outside the shared sequence element.« less

Pen-chant: Acoustic emissions of handwriting and drawing

NASA Astrophysics Data System (ADS)

Seniuk, Andrew G.

The sounds generated by a writing instrument ('pen-chant') provide a rich and underutilized source of information for pattern recognition. We examine the feasibility of recognition of handwritten cursive text, exclusively through an analysis of acoustic emissions. We design and implement a family of recognizers using a template matching approach, with templates and similarity measures derived variously from: smoothed amplitude signal with fixed resolution, discrete sequence of magnitudes obtained from peaks in the smoothed amplitude signal, and ordered tree obtained from a scale space signal representation. Test results are presented for recognition of isolated lowercase cursive characters and for whole words. We also present qualitative results for recognizing gestures such as circling, scratch-out, check-marks, and hatching. Our first set of results, using samples provided by the author, yield recognition rates of over 70% (alphabet) and 90% (26 words), with a confidence of +/-8%, based solely on acoustic emissions. Our second set of results uses data gathered from nine writers. These results demonstrate that acoustic emissions are a rich source of information, usable---on their own or in conjunction with image-based features---to solve pattern recognition problems. In future work, this approach can be applied to writer identification, handwriting and gesture-based computer input technology, emotion recognition, and temporal analysis of sketches.

An early illness recognition framework using a temporal Smith Waterman algorithm and NLP.

PubMed

Hajihashemi, Zahra; Popescu, Mihail

2013-01-01

In this paper we propose a framework for detecting health patterns based on non-wearable sensor sequence similarity and natural language processing (NLP). In TigerPlace, an aging in place facility from Columbia, MO, we deployed 47 sensor networks together with a nursing electronic health record (EHR) system to provide early illness recognition. The proposed framework utilizes sensor sequence similarity and NLP on EHR nursing comments to automatically notify the physician when health problems are detected. The reported methodology is inspired by genomic sequence annotation using similarity algorithms such as Smith Waterman (SW). Similarly, for each sensor sequence, we associate health concepts extracted from the nursing notes using Metamap, a NLP tool provided by Unified Medical Language System (UMLS). Since sensor sequences, unlike genomics ones, have an associated time dimension we propose a temporal variant of SW (TSW) to account for time. The main challenges presented by our framework are finding the most suitable time sequence similarity and aggregation of the retrieved UMLS concepts. On a pilot dataset from three Tiger Place residents, with a total of 1685 sensor days and 626 nursing records, we obtained an average precision of 0.64 and a recall of 0.37.

Activity and function recognition for moving and static objects in urban environments from wide-area persistent surveillance inputs

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Bobick, Aaron; Jones, Eric

2010-04-01

In this paper, we describe results from experimental analysis of a model designed to recognize activities and functions of moving and static objects from low-resolution wide-area video inputs. Our model is based on representing the activities and functions using three variables: (i) time; (ii) space; and (iii) structures. The activity and function recognition is achieved by imposing lexical, syntactic, and semantic constraints on the lower-level event sequences. In the reported research, we have evaluated the utility and sensitivity of several algorithms derived from natural language processing and pattern recognition domains. We achieved high recognition accuracy for a wide range of activity and function types in the experiments using Electro-Optical (EO) imagery collected by Wide Area Airborne Surveillance (WAAS) platform.

Short memory fuzzy fusion image recognition schema employing spatial and Fourier descriptors

NASA Astrophysics Data System (ADS)

Raptis, Sotiris N.; Tzafestas, Spyros G.

2001-03-01

Single images quite often do not bear enough information for precise interpretation due to a variety of reasons. Multiple image fusion and adequate integration recently became the state of the art in the pattern recognition field. In this paper presented here and enhanced multiple observation schema is discussed investigating improvements to the baseline fuzzy- probabilistic image fusion methodology. The first innovation introduced consists in considering only a limited but seemingly ore effective part of the uncertainty information obtained by a certain time restricting older uncertainty dependencies and alleviating computational burden that is now needed for short sequence (stored into memory) of samples. The second innovation essentially grouping them into feature-blind object hypotheses. Experiment settings include a sequence of independent views obtained by camera being moved around the investigated object.

Transcription Factors Bind Thousands of Active and InactiveRegions in the Drosophila Blastoderm

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

Li, Xiao-Yong; MacArthur, Stewart; Bourgon, Richard

2008-01-10

Identifying the genomic regions bound by sequence-specific regulatory factors is central both to deciphering the complex DNA cis-regulatory code that controls transcription in metazoans and to determining the range of genes that shape animal morphogenesis. Here, we use whole-genome tiling arrays to map sequences bound in Drosophila melanogaster embryos by the six maternal and gap transcription factors that initiate anterior-posterior patterning. We find that these sequence-specific DNA binding proteins bind with quantitatively different specificities to highly overlapping sets of several thousand genomic regions in blastoderm embryos. Specific high- and moderate-affinity in vitro recognition sequences for each factor are enriched inmore » bound regions. This enrichment, however, is not sufficient to explain the pattern of binding in vivo and varies in a context-dependent manner, demonstrating that higher-order rules must govern targeting of transcription factors. The more highly bound regions include all of the over forty well-characterized enhancers known to respond to these factors as well as several hundred putative new cis-regulatory modules clustered near developmental regulators and other genes with patterned expression at this stage of embryogenesis. The new targets include most of the microRNAs (miRNAs) transcribed in the blastoderm, as well as all major zygotically transcribed dorsal-ventral patterning genes, whose expression we show to be quantitatively modulated by anterior-posterior factors. In addition to these highly bound regions, there are several thousand regions that are reproducibly bound at lower levels. However, these poorly bound regions are, collectively, far more distant from genes transcribed in the blastoderm than highly bound regions; are preferentially found in protein-coding sequences; and are less conserved than highly bound regions. Together these observations suggest that many of these poorly-bound regions are not involved in early-embryonic transcriptional regulation, and a significant proportion may be nonfunctional. Surprisingly, for five of the six factors, their recognition sites are not unambiguously more constrained evolutionarily than the immediate flanking DNA, even in more highly bound and presumably functional regions, indicating that comparative DNA sequence analysis is limited in its ability to identify functional transcription factor targets.« less

Patterns and plasticity in RNA-protein interactions enable recruitment of multiple proteins through a single site

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

Valley, Cary T.; Porter, Douglas F.; Qiu, Chen

2012-06-28

mRNA control hinges on the specificity and affinity of proteins for their RNA binding sites. Regulatory proteins must bind their own sites and reject even closely related noncognate sites. In the PUF [Pumilio and fem-3 binding factor (FBF)] family of RNA binding proteins, individual proteins discriminate differences in the length and sequence of binding sites, allowing each PUF to bind a distinct battery of mRNAs. Here, we show that despite these differences, the pattern of RNA interactions is conserved among PUF proteins: the two ends of the PUF protein make critical contacts with the two ends of the RNA sites.more » Despite this conserved 'two-handed' pattern of recognition, the RNA sequence is flexible. Among the binding sites of yeast Puf4p, RNA sequence dictates the pattern in which RNA bases are flipped away from the binding surface of the protein. Small differences in RNA sequence allow new modes of control, recruiting Puf5p in addition to Puf4p to a single site. This embedded information adds a new layer of biological meaning to the connections between RNA targets and PUF proteins.« less

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2008-12-01

Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences. In this paper, a novel building block of proteins called Top-n-grams is presented, which contains the evolutionary information extracted from the protein sequence frequency profiles. The protein sequence frequency profiles are calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into Top-n-grams. The protein sequences are transformed into fixed-dimension feature vectors by the occurrence times of each Top-n-gram. The training vectors are evaluated by SVM to train classifiers which are then used to classify the test protein sequences. We demonstrate that the prediction performance of remote homology detection and fold recognition can be improved by combining Top-n-grams and latent semantic analysis (LSA), which is an efficient feature extraction technique from natural language processing. When tested on superfamily and fold benchmarks, the method combining Top-n-grams and LSA gives significantly better results compared to related methods. The method based on Top-n-grams significantly outperforms the methods based on many other building blocks including N-grams, patterns, motifs and binary profiles. Therefore, Top-n-gram is a good building block of the protein sequences and can be widely used in many tasks of the computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the prediction of protein binding sites.

Research of Daily Conversation Transmitting System Based on Mouth Part Pattern Recognition

NASA Astrophysics Data System (ADS)

Watanabe, Mutsumi; Nishi, Natsuko

The authors are developing a vision-based intension transfer technique by recognizing user’s face expressions and movements, to help free and convenient communications with aged or disabled persons who find difficulties in talking, discriminating small character prints and operating keyboards by hands and fingers. In this paper we report a prototype system, where layered daily conversations are successively selected by recognizing the transition in shape of user’s mouth parts using camera image sequences settled in front of the user. Four mouth part patterns are used in the system. A method that automatically recognizes these patterns by analyzing the intensity histogram data around the mouth region is newly developed. The confirmation of a selection on the way is executed by detecting the open and shut movements of mouth through the temporal change in intensity histogram data. The method has been installed in a desktop PC by VC++ programs. Experimental results of mouth shape pattern recognition by twenty-five persons have shown the effectiveness of the method.

Learning piano melodies in visuo-motor or audio-motor training conditions and the neural correlates of their cross-modal transfer.

PubMed

Engel, Annerose; Bangert, Marc; Horbank, David; Hijmans, Brenda S; Wilkens, Katharina; Keller, Peter E; Keysers, Christian

2012-11-01

To investigate the cross-modal transfer of movement patterns necessary to perform melodies on the piano, 22 non-musicians learned to play short sequences on a piano keyboard by (1) merely listening and replaying (vision of own fingers occluded) or (2) merely observing silent finger movements and replaying (on a silent keyboard). After training, participants recognized with above chance accuracy (1) audio-motor learned sequences upon visual presentation (89±17%), and (2) visuo-motor learned sequences upon auditory presentation (77±22%). The recognition rates for visual presentation significantly exceeded those for auditory presentation (p<.05). fMRI revealed that observing finger movements corresponding to audio-motor trained melodies is associated with stronger activation in the left rolandic operculum than observing untrained sequences. This region was also involved in silent execution of sequences, suggesting that a link to motor representations may play a role in cross-modal transfer from audio-motor training condition to visual recognition. No significant differences in brain activity were found during listening to visuo-motor trained compared to untrained melodies. Cross-modal transfer was stronger from the audio-motor training condition to visual recognition and this is discussed in relation to the fact that non-musicians are familiar with how their finger movements look (motor-to-vision transformation), but not with how they sound on a piano (motor-to-sound transformation). Copyright © 2012 Elsevier Inc. All rights reserved.

Sequence Dependencies of DNA Deformability and Hydration in the Minor Groove

PubMed Central

Yonetani, Yoshiteru; Kono, Hidetoshi

2009-01-01

Abstract DNA deformability and hydration are both sequence-dependent and are essential in specific DNA sequence recognition by proteins. However, the relationship between the two is not well understood. Here, systematic molecular dynamics simulations of 136 DNA sequences that differ from each other in their central tetramer revealed that sequence dependence of hydration is clearly correlated with that of deformability. We show that this correlation can be illustrated by four typical cases. Most rigid basepair steps are highly likely to form an ordered hydration pattern composed of one water molecule forming a bridge between the bases of distinct strands, but a few exceptions favor another ordered hydration composed of two water molecules forming such a bridge. Steps with medium deformability can display both of these hydration patterns with frequent transition. Highly flexible steps do not have any stable hydration pattern. A detailed picture of this correlation demonstrates that motions of hydration water molecules and DNA bases are tightly coupled with each other at the atomic level. These results contribute to our understanding of the entropic contribution from water molecules in protein or drug binding and could be applied for the purpose of predicting binding sites. PMID:19686662

A novel probabilistic framework for event-based speech recognition

NASA Astrophysics Data System (ADS)

Juneja, Amit; Espy-Wilson, Carol

2003-10-01

One of the reasons for unsatisfactory performance of the state-of-the-art automatic speech recognition (ASR) systems is the inferior acoustic modeling of low-level acoustic-phonetic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal, but such a system for continuous speech recognition (CSR) is not known to exist. A probabilistic and statistical framework for CSR based on the idea of the representation of speech sounds by bundles of binary valued articulatory phonetic features is proposed. Multiple probabilistic sequences of linguistically motivated landmarks are obtained using binary classifiers of manner phonetic features-syllabic, sonorant and continuant-and the knowledge-based acoustic parameters (APs) that are acoustic correlates of those features. The landmarks are then used for the extraction of knowledge-based APs for source and place phonetic features and their binary classification. Probabilistic landmark sequences are constrained using manner class language models for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge-based systems that led the ASR community to switch to systems highly dependent on statistical pattern analysis methods and probabilistic language or grammar models.

Time manages interference in visual short-term memory.

PubMed

Smith, Amy V; McKeown, Denis; Bunce, David

2017-09-01

Emerging evidence suggests that age-related declines in memory may reflect a failure in pattern separation, a process that is believed to reduce the encoding overlap between similar stimulus representations during memory encoding. Indeed, behavioural pattern separation may be indexed by a visual continuous recognition task in which items are presented in sequence and observers report for each whether it is novel, previously viewed (old), or whether it shares features with a previously viewed item (similar). In comparison to young adults, older adults show a decreased pattern separation when the number of items between "old" and "similar" items is increased. Yet the mechanisms of forgetting underpinning this type of recognition task are yet to be explored in a cognitively homogenous group, with careful control over the parameters of the task, including elapsing time (a critical variable in models of forgetting). By extending the inter-item intervals, number of intervening items and overall decay interval, we observed in a young adult sample (N = 35, M age  = 19.56 years) that the critical factor governing performance was inter-item interval. We argue that tasks using behavioural continuous recognition to index pattern separation in immediate memory will benefit from generous inter-item spacing, offering protection from inter-item interference.

Identification of a β-glucosidase from the Mucor circinelloides genome by peptide pattern recognition.

PubMed

Huang, Yuhong; Busk, Peter Kamp; Grell, Morten Nedergaard; Zhao, Hai; Lange, Lene

2014-12-01

Mucor circinelloides produces plant cell wall degrading enzymes that allow it to grow on complex polysaccharides. Although the genome of M. circinelloides has been sequenced, only few plant cell wall degrading enzymes are annotated in this species. We applied peptide pattern recognition, which is a non-alignment based method for sequence analysis to map conserved sequences in glycoside hydrolase families. The conserved sequences were used to identify similar genes in the M. circinelloides genome. We found 12 different novel genes encoding members of the GH3, GH5, GH9, GH16, GH38, GH47 and GH125 families in M. circinelloides. One of the two GH3-encoding genes was predicted to encode a β-glucosidase (EC 3.2.1.21). We expressed this gene in Pichia pastoris KM71H and found that the purified recombinant protein had relative high β-glucosidase activity (1.73U/mg) at pH5 and 50°C. The Km and Vmax with p-nitrophenyl-β-d-glucopyranoside as substrate was 0.20mM and 2.41U/mg, respectively. The enzyme was not inhibited by glucose and retained 84% activity at glucose concentrations up to 140mM. Although zygomycetes are not considered to be important degraders of lignocellulosic biomass in nature, the present finding of an active β-glucosidase in M. circinelloides demonstrates that enzymes from this group of fungi have a potential for cellulose degradation. Copyright © 2014 Elsevier Inc. All rights reserved.

Deaf-And-Mute Sign Language Generation System

NASA Astrophysics Data System (ADS)

Kawai, Hideo; Tamura, Shinichi

1984-08-01

We have developed a system which can recognize speech and generate the corresponding animation-like sign language sequence. The system is implemented in a popular personal computer. This has three video-RAM's and a voice recognition board which can recognize only registered voice of a specific speaker. Presently, fourty sign language patterns and fifty finger spellings are stored in two floppy disks. Each sign pattern is composed of one to four sub-patterns. That is, if the pattern is composed of one sub-pattern, it is displayed as a still pattern. If not, it is displayed as a motion pattern. This system will help communications between deaf-and-mute persons and healthy persons. In order to display in high speed, almost programs are written in a machine language.

Functional and computational analysis of amino acid patterns predictive of type III secretion system substrates in Pseudomonas syringae

USDA-ARS?s Scientific Manuscript database

Bacterial type III secretion systems (T3SSs) deliver proteins called effectors into eukaryotic cells. Although N-terminal amino acid sequences are required for translocation, the mechanism of substrate recognition by the T3SS is unknown. Almost all actively deployed T3SS substrates in the plant path...

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Driving style recognition method using braking characteristics based on hidden Markov model

PubMed Central

Wu, Chaozhong; Lyu, Nengchao; Huang, Zhen

2017-01-01

Since the advantage of hidden Markov model in dealing with time series data and for the sake of identifying driving style, three driving style (aggressive, moderate and mild) are modeled reasonably through hidden Markov model based on driver braking characteristics to achieve efficient driving style. Firstly, braking impulse and the maximum braking unit area of vacuum booster within a certain time are collected from braking operation, and then general braking and emergency braking characteristics are extracted to code the braking characteristics. Secondly, the braking behavior observation sequence is used to describe the initial parameters of hidden Markov model, and the generation of the hidden Markov model for differentiating and an observation sequence which is trained and judged by the driving style is introduced. Thirdly, the maximum likelihood logarithm could be implied from the observable parameters. The recognition accuracy of algorithm is verified through experiments and two common pattern recognition algorithms. The results showed that the driving style discrimination based on hidden Markov model algorithm could realize effective discriminant of driving style. PMID:28837580

Double-Barrier Memristive Devices for Unsupervised Learning and Pattern Recognition.

PubMed

Hansen, Mirko; Zahari, Finn; Ziegler, Martin; Kohlstedt, Hermann

2017-01-01

The use of interface-based resistive switching devices for neuromorphic computing is investigated. In a combined experimental and numerical study, the important device parameters and their impact on a neuromorphic pattern recognition system are studied. The memristive cells consist of a layer sequence Al/Al 2 O 3 /Nb x O y /Au and are fabricated on a 4-inch wafer. The key functional ingredients of the devices are a 1.3 nm thick Al 2 O 3 tunnel barrier and a 2.5 mm thick Nb x O y memristive layer. Voltage pulse measurements are used to study the electrical conditions for the emulation of synaptic functionality of single cells for later use in a recognition system. The results are evaluated and modeled in the framework of the plasticity model of Ziegler et al. Based on this model, which is matched to experimental data from 84 individual devices, the network performance with regard to yield, reliability, and variability is investigated numerically. As the network model, a computing scheme for pattern recognition and unsupervised learning based on the work of Querlioz et al. (2011), Sheridan et al. (2014), Zahari et al. (2015) is employed. This is a two-layer feedforward network with a crossbar array of memristive devices, leaky integrate-and-fire output neurons including a winner-takes-all strategy, and a stochastic coding scheme for the input pattern. As input pattern, the full data set of digits from the MNIST database is used. The numerical investigation indicates that the experimentally obtained yield, reliability, and variability of the memristive cells are suitable for such a network. Furthermore, evidence is presented that their strong I - V non-linearity might avoid the need for selector devices in crossbar array structures.

A galectin from Eriocheir sinensis functions as pattern recognition receptor enhancing microbe agglutination and haemocytes encapsulation.

PubMed

Wang, Mengqiang; Wang, Lingling; Huang, Mengmeng; Yi, Qilin; Guo, Ying; Gai, Yunchao; Wang, Hao; Zhang, Huan; Song, Linsheng

2016-08-01

Galectins are a family of β-galactoside binding lectins that function as pattern recognition receptors (PRRs) in innate immune system of both vertebrates and invertebrates. The cDNA of Chinese mitten crab Eriocheir sinensis galectin (designated as EsGal) was cloned via rapid amplification of cDNA ends (RACE) technique based on expressed sequence tags (ESTs) analysis. The full-length cDNA of EsGal was 999 bp. Its open reading frame encoded a polypeptide of 218 amino acids containing a GLECT/Gal-bind_lectin domain and a proline/glycine rich low complexity region. The deduced amino acid sequence and domain organization of EsGal were highly similar to those of crustacean galectins. The mRNA transcripts of EsGal were found to be constitutively expressed in a wide range of tissues and mainly in hepatopancreas, gill and haemocytes. The mRNA expression level of EsGal increased rapidly and significantly after crabs were stimulated by different microbes. The recombinant EsGal (rEsGal) could bind various pathogen-associated molecular patterns (PAMPs), including lipopolysaccharide (LPS), peptidoglycan (PGN) and glucan (GLU), and exhibited strong activity to agglutinate Escherichia coli, Vibrio anguillarum, Bacillus subtilis, Micrococcus luteus, Staphylococcus aureus and Pichia pastoris, and such agglutinating activity could be inhibited by both d-galactose and α-lactose. The in vitro encapsulation assay revealed that rEsGal could enhance the encapsulation of haemocytes towards agarose beads. These results collectively suggested that EsGal played crucial roles in the immune recognition and elimination of pathogens and contributed to the innate immune response against various microbes in crabs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pattern of eyelid motion predictive of decision errors during drowsiness: oculomotor indices of altered states.

PubMed

Lobb, M L; Stern, J A

1986-08-01

Sequential patterns of eye and eyelid motion were identified in seven subjects performing a modified serial probe recognition task under drowsy conditions. Using simultaneous EOG and video recordings, eyelid motion was divided into components above, within, and below the pupil and the durations in sequence were recorded. A serial probe recognition task was modified to allow for distinguishing decision errors from attention errors. Decision errors were found to be more frequent following a downward shift in the gaze angle which the eyelid closing sequence was reduced from a five element to a three element sequence. The velocity of the eyelid moving over the pupil during decision errors was slow in the closing and fast in the reopening phase, while on decision correct trials it was fast in closing and slower in reopening. Due to the high variability of eyelid motion under drowsy conditions these findings were only marginally significant. When a five element blink occurred, the velocity of the lid over pupil motion component of these endogenous eye blinks was significantly faster on decision correct than on decision error trials. Furthermore, the highly variable, long duration closings associated with the decision response produced slow eye movements in the horizontal plane (SEM) which were more frequent and significantly longer in duration on decision error versus decision correct responses.

Acquisition of Malay word recognition skills: lessons from low-progress early readers.

PubMed

Lee, Lay Wah; Wheldall, Kevin

2011-02-01

Malay is a consistent alphabetic orthography with complex syllable structures. The focus of this research was to investigate word recognition performance in order to inform reading interventions for low-progress early readers. Forty-six Grade 1 students were sampled and 11 were identified as low-progress readers. The results indicated that both syllable awareness and phoneme blending were significant predictors of word recognition, suggesting that both syllable and phonemic grain-sizes are important in Malay word recognition. Item analysis revealed a hierarchical pattern of difficulty based on the syllable and the phonic structure of the words. Error analysis identified the sources of errors to be errors due to inefficient syllable segmentation, oversimplification of syllables, insufficient grapheme-phoneme knowledge and inefficient phonemic code assembly. Evidence also suggests that direct instruction in syllable segmentation, phonemic awareness and grapheme-phoneme correspondence is necessary for low-progress readers to acquire word recognition skills. Finally, a logical sequence to teach grapheme-phoneme decoding in Malay is suggested. Copyright © 2010 John Wiley & Sons, Ltd.

Pattern Recognition of Adsorbing HP Lattice Proteins

NASA Astrophysics Data System (ADS)

Wilson, Matthew S.; Shi, Guangjie; Wüst, Thomas; Landau, David P.; Schmid, Friederike

2015-03-01

Protein adsorption is relevant in fields ranging from medicine to industry, and the qualitative behavior exhibited by course-grained models could shed insight for further research in such fields. Our study on the selective adsorption of lattice proteins utilizes the Wang-Landau algorithm to simulate the Hydrophobic-Polar (H-P) model with an efficient set of Monte Carlo moves. Each substrate is modeled as a square pattern of 9 lattice sites which attract either H or P monomers, and are located on an otherwise neutral surface. The fully enumerated set of 102 unique surfaces is simulated with each protein sequence. A collection of 27-monomer sequences is used- each of which is non-degenerate and protein-like. Thermodynamic quantities such as the specific heat and free energy are calculated from the density of states, and are used to investigate the adsorption of lattice proteins on patterned substrates. Research supported by NSF.

Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

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.

An ultra-sparse code underliesthe generation of neural sequences in a songbird

NASA Astrophysics Data System (ADS)

Hahnloser, Richard H. R.; Kozhevnikov, Alexay A.; Fee, Michale S.

2002-09-01

Sequences of motor activity are encoded in many vertebrate brains by complex spatio-temporal patterns of neural activity; however, the neural circuit mechanisms underlying the generation of these pre-motor patterns are poorly understood. In songbirds, one prominent site of pre-motor activity is the forebrain robust nucleus of the archistriatum (RA), which generates stereotyped sequences of spike bursts during song and recapitulates these sequences during sleep. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA. Recordings of identified HVC neurons in sleeping and singing birds show that individual HVC neurons projecting onto RA neurons produce bursts sparsely, at a single, precise time during the RA sequence. These HVC neurons burst sequentially with respect to one another. We suggest that at each time in the RA sequence, the ensemble of active RA neurons is driven by a subpopulation of RA-projecting HVC neurons that is active only at that time. As a population, these HVC neurons may form an explicit representation of time in the sequence. Such a sparse representation, a temporal analogue of the `grandmother cell' concept for object recognition, eliminates the problem of temporal interference during sequence generation and learning attributed to more distributed representations.

On Utilizing Optimal and Information Theoretic Syntactic Modeling for Peptide Classification

NASA Astrophysics Data System (ADS)

Aygün, Eser; Oommen, B. John; Cataltepe, Zehra

Syntactic methods in pattern recognition have been used extensively in bioinformatics, and in particular, in the analysis of gene and protein expressions, and in the recognition and classification of bio-sequences. These methods are almost universally distance-based. This paper concerns the use of an Optimal and Information Theoretic (OIT) probabilistic model [11] to achieve peptide classification using the information residing in their syntactic representations. The latter has traditionally been achieved using the edit distances required in the respective peptide comparisons. We advocate that one can model the differences between compared strings as a mutation model consisting of random Substitutions, Insertions and Deletions (SID) obeying the OIT model. Thus, in this paper, we show that the probability measure obtained from the OIT model can be perceived as a sequence similarity metric, using which a Support Vector Machine (SVM)-based peptide classifier, referred to as OIT_SVM, can be devised.

A Review of Subsequence Time Series Clustering

PubMed Central

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

A review of subsequence time series clustering.

PubMed

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

Distorted Character Recognition Via An Associative Neural Network

NASA Astrophysics Data System (ADS)

Messner, Richard A.; Szu, Harold H.

1987-03-01

The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

A standardization model based on image recognition for performance evaluation of an oral scanner.

PubMed

Seo, Sang-Wan; Lee, Wan-Sun; Byun, Jae-Young; Lee, Kyu-Bok

2017-12-01

Accurate information is essential in dentistry. The image information of missing teeth is used in optically based medical equipment in prosthodontic treatment. To evaluate oral scanners, the standardized model was examined from cases of image recognition errors of linear discriminant analysis (LDA), and a model that combines the variables with reference to ISO 12836:2015 was designed. The basic model was fabricated by applying 4 factors to the tooth profile (chamfer, groove, curve, and square) and the bottom surface. Photo-type and video-type scanners were used to analyze 3D images after image capture. The scans were performed several times according to the prescribed sequence to distinguish the model from the one that did not form, and the results confirmed it to be the best. In the case of the initial basic model, a 3D shape could not be obtained by scanning even if several shots were taken. Subsequently, the recognition rate of the image was improved with every variable factor, and the difference depends on the tooth profile and the pattern of the floor surface. Based on the recognition error of the LDA, the recognition rate decreases when the model has a similar pattern. Therefore, to obtain the accurate 3D data, the difference of each class needs to be provided when developing a standardized model.

Analysis of DNA methylation in Arabidopsis thaliana based on methylation-sensitive AFLP markers.

PubMed

Cervera, M T; Ruiz-García, L; Martínez-Zapater, J M

2002-12-01

AFLP analysis using restriction enzyme isoschizomers that differ in their sensitivity to methylation of their recognition sites has been used to analyse the methylation state of anonymous CCGG sequences in Arabidopsis thaliana. The technique was modified to improve the quality of fingerprints and to visualise larger numbers of scorable fragments. Sequencing of amplified fragments indicated that detection was generally associated with non-methylation of the cytosine to which the isoschizomer is sensitive. Comparison of EcoRI/ HpaII and EcoRI/ MspI patterns in different ecotypes revealed that 35-43% of CCGG sites were differentially digested by the isoschizomers. Interestingly, the pattern of digestion among different plants belonging to the same ecotype is highly conserved, with the rate of intra-ecotype methylation-sensitive polymorphisms being less than 1%. However, pairwise comparisons of methylation patterns between samples belonging to different ecotypes revealed differences in up to 34% of the methylation-sensitive polymorphisms. The lack of correlation between inter-ecotype similarity matrices based on methylation-insensitive or methylation-sensitive polymorphisms suggests that whatever the mechanisms regulating methylation may be, they are not related to nucleotide sequence variation.

Promoter mapping of the mouse Tcp-10bt gene in transgenic mice identifies essential male germ cell regulatory sequences.

PubMed

Ewulonu, U K; Snyder, L; Silver, L M; Schimenti, J C

1996-03-01

Transgenic mice were generated to localize essential promoter elements in the mouse testis-expressed Tcp-10 genes. These genes are expressed exclusively in male germ cells, and exhibit a diffuse range of transcriptional start sites, possibly due to the absence of a TATA box. A series of transgene constructs containing different amounts of 5' flanking DNA revealed that all sequences necessary for appropriate temporal and tissue-specific transcription of Tcp-10 reside between positions -1 to -973. All transgenic animals containing these sequences expressed a chimeric transgene at high levels, in a pattern that paralleled the endogenous genes. These experiments further defined a 227 bp fragment from -746 to -973 that was absolutely essential for expression. In a gel-shift assay, this 227-bp fragment bound nuclear protein from testis, but not other tissues, to yield two retarded bands. Sequence analysis of this fragment revealed a half-site for the AP-2 transcription factor recognition sequence. Gel shift assays using native or mutant oligonucleotides demonstrated that the putative AP-2 recognition sequence was essential for generating the retarded bands. Since the binding activity is testis-specific, but AP-2 expression is not exclusive to male germ cells, it is possible that transcription of Tcp-10 requires interaction between AP-2 and a germ cell-specific transcription factor.

Modularity of music: evidence from a case of pure amusia.

PubMed

Piccirilli, M; Sciarma, T; Luzzi, S

2000-10-01

A case of pure amusia in a 20 year old left handed non-professional musician is reported. The patient showed an impairment of music abilities in the presence of normal processing of speech and environmental sounds. Furthermore, whereas recognition and production of melodic sequences were grossly disturbed, both the recognition and production of rhythm patterns were preserved. This selective breakdown pattern was produced by a focal lesion in the left superior temporal gyrus. This case thus suggests that not only linguistic and musical skills, but also melodic and rhythmic processing are independent of each other. This functional dissociation in the musical domain supports the hypothesis that music components have a modular organisation. Furthermore, there is the suggestion that amusia may be produced by a lesion located strictly in one hemisphere and that the superior temporal gyrus plays a crucial part in melodic processing.

Characterizing the spatio-temporal dynamics of the neural events occurring prior to and up to overt recognition of famous faces.

PubMed

Jemel, Boutheina; Schuller, Anne-Marie; Goffaux, Valérie

2010-10-01

Although it is generally acknowledged that familiar face recognition is fast, mandatory, and proceeds outside conscious control, it is still unclear whether processes leading to familiar face recognition occur in a linear (i.e., gradual) or a nonlinear (i.e., all-or-none) manner. To test these two alternative accounts, we recorded scalp ERPs while participants indicated whether they recognize as familiar the faces of famous and unfamiliar persons gradually revealed in a descending sequence of frames, from the noisier to the least noisy. This presentation procedure allowed us to characterize the changes in scalp ERP responses occurring prior to and up to overt recognition. Our main finding is that gradual and all-or-none processes are possibly involved during overt recognition of familiar faces. Although the N170 and the N250 face-sensitive responses displayed an abrupt activity change at the moment of overt recognition of famous faces, later ERPs encompassing the N400 and late positive component exhibited an incremental increase in amplitude as the point of recognition approached. In addition, famous faces that were not overtly recognized at one trial before recognition elicited larger ERP potentials than unfamiliar faces, probably reflecting a covert recognition process. Overall, these findings present evidence that recognition of familiar faces implicates spatio-temporally complex neural processes exhibiting differential pattern activity changes as a function of recognition state.

Use of Biometrics within Sub-Saharan Refugee Communities

DTIC Science & Technology

2013-12-01

fingerprint patterns, iris pattern recognition, and facial recognition as a means of establishing an individual’s identity. Biometrics creates and...Biometrics typically comprises fingerprint patterns, iris pattern recognition, and facial recognition as a means of establishing an individual’s identity...authentication because it identifies an individual based on mathematical analysis of the random pattern visible within the iris. Facial recognition is

Rotation-invariant neural pattern recognition system with application to coin recognition.

PubMed

Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

1992-01-01

In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

Leucine-rich Repeats of Bacterial Surface Proteins Serve as Common Pattern Recognition Motifs of Human Scavenger Receptor gp340*

PubMed Central

Loimaranta, Vuokko; Hytönen, Jukka; Pulliainen, Arto T.; Sharma, Ashu; Tenovuo, Jorma; Strömberg, Nicklas; Finne, Jukka

2009-01-01

Scavenger receptors are innate immune molecules recognizing and inducing the clearance of non-host as well as modified host molecules. To recognize a wide pattern of invading microbes, many scavenger receptors bind to common pathogen-associated molecular patterns, such as lipopolysaccharides and lipoteichoic acids. Similarly, the gp340/DMBT1 protein, a member of the human scavenger receptor cysteine-rich protein family, displays a wide ligand repertoire. The peptide motif VEVLXXXXW derived from its scavenger receptor cysteine-rich domains is involved in some of these interactions, but most of the recognition mechanisms are unknown. In this study, we used mass spectrometry sequencing, gene inactivation, and recombinant proteins to identify Streptococcus pyogenes protein Spy0843 as a recognition receptor of gp340. Antibodies against Spy0843 are shown to protect against S. pyogenes infection, but no function or host receptor have been identified for the protein. Spy0843 belongs to the leucine-rich repeat (Lrr) family of eukaryotic and prokaryotic proteins. Experiments with truncated forms of the recombinant proteins confirmed that the Lrr region is needed in the binding of Spy0843 to gp340. The same motif of two other Lrr proteins, LrrG from the Gram-positive S. agalactiae and BspA from the Gram-negative Tannerella forsythia, also mediated binding to gp340. Moreover, inhibition of Spy0843 binding occurred with peptides containing the VEVLXXXXW motif, but also peptides devoid of the XXXXW motif inhibited binding of Lrr proteins. These results thus suggest that the conserved Lrr motif in bacterial proteins serves as a novel pattern recognition motif for unique core peptides of human scavenger receptor gp340. PMID:19465482

Phylogenetic analysis and expression profiling of the pattern recognition receptors: Insights into molecular recognition of invading pathogens in Manduca sexta.

PubMed

Zhang, Xiufeng; He, Yan; Cao, Xiaolong; Gunaratna, Ramesh T; Chen, Yun-ru; Blissard, Gary; Kanost, Michael R; Jiang, Haobo

2015-07-01

Pattern recognition receptors (PRRs) detect microbial pathogens and trigger innate immune responses. Previous biochemical studies have elucidated the physiological functions of eleven PRRs in Manduca sexta but our understanding of the recognition process is still limited, lacking genomic perspectives. While 34 C-type lectin-domain proteins and 16 Toll-like receptors are reported in the companion papers, we present here 120 other putative PRRs identified through the genome annotation. These include 76 leucine-rich repeat (LRR) proteins, 14 peptidoglycan recognition proteins, 6 EGF/Nim-domain proteins, 5 β-1,3-glucanase-related proteins, 4 galectins, 4 fibrinogen-related proteins, 3 thioester proteins, 5 immunoglobulin-domain proteins, 2 hemocytins, and 1 Reeler. Sequence alignment and phylogenetic analysis reveal the evolution history of a diverse repertoire of proteins for pathogen recognition. While functions of insect LRR proteins are mostly unknown, their structure diversification is phenomenal: In addition to the Toll homologs, 22 LRR proteins with a signal peptide are expected to be secreted; 18 LRR proteins lacking signal peptides may be cytoplasmic; 36 LRRs with a signal peptide and a transmembrane segment may be non-Toll receptors on the surface of cells. Expression profiles of the 120 genes in 52 tissue samples reflect complex regulation in various developmental stages and physiological states, including some likely by Rel family transcription factors via κB motifs in the promoter regions. This collection of information is expected to facilitate future biochemical studies detailing their respective roles in this model insect. Copyright © 2015 Elsevier Ltd. All rights reserved.

Phylogenetic analysis and expression profiling of the pattern recognition receptors: insights into molecular recognition of invading pathogens in Manduca sexta

PubMed Central

Zhang, Xiufeng; He, Yan; Cao, Xiaolong; Gunaratna, Ramesh T.; Chen, Yun-ru; Blissard, Gary; Kanost, Michael R.; Jiang, Haobo

2015-01-01

Pattern recognition receptors (PRRs) detect microbial pathogens and trigger innate immune responses. Previous biochemical studies have elucidated the physiological functions of eleven PRRs in Manduca sexta but our understanding of the recognition process is still limited, lacking genomic perspectives. While 34 C-type lectin-domain proteins and 16 Toll-like receptors are reported in the companion papers, we present here 120 other putative PRRs identified through the genome annotation. These include 76 leucine-rich repeat (LRR) proteins, 14 peptidoglycan recognition proteins, 6 EGF/Nim-domain proteins, 5 β-1,3-glucanase-related proteins, 4 galectins, 4 fibrinogen-related proteins, 3 thioester proteins, 5 immunoglobulin-domain proteins, 2 hemocytins, and 1 Reeler. Sequence alignment and phylogenetic analysis reveal the evolution history of a diverse repertoire of proteins for pathogen recognition. While functions of insect LRR proteins are mostly unknown, their structure diversification is phenomenal: In addition to the Toll homologs, 22 LRR proteins with a signal peptide are expected to be secreted; 18 LRR proteins lacking signal peptides may be cytoplasmic; 36 LRRs with a signal peptide and a transmembrane segment may be non-Toll receptors on the surface of cells. Expression profiles of the 120 genes in 52 tissue samples reflect complex regulation in various developmental stages and physiological states, including some likely by Rel family transcription factors via κB motifs in the promoter regions. This collection of information is expected to facilitate future biochemical studies detailing their respective roles in this model insect. PMID:25701384

Applying Suffix Rules to Organization Name Recognition

NASA Astrophysics Data System (ADS)

Inui, Takashi; Murakami, Koji; Hashimoto, Taiichi; Utsumi, Kazuo; Ishikawa, Masamichi

This paper presents a method for boosting the performance of the organization name recognition, which is a part of named entity recognition (NER). Although gazetteers (lists of the NEs) have been known as one of the effective features for supervised machine learning approaches on the NER task, the previous methods which have applied the gazetteers to the NER were very simple. The gazetteers have been used just for searching the exact matches between input text and NEs included in them. The proposed method generates regular expression rules from gazetteers, and, with these rules, it can realize a high-coverage searches based on looser matches between input text and NEs. To generate these rules, we focus on the two well-known characteristics of NE expressions; 1) most of NE expressions can be divided into two parts, class-reference part and instance-reference part, 2) for most of NE expressions the class-reference parts are located at the suffix position of them. A pattern mining algorithm runs on the set of NEs in the gazetteers, and some frequent word sequences from which NEs are constructed are found. Then, we employ only word sequences which have the class-reference part at the suffix position as suffix rules. Experimental results showed that our proposed method improved the performance of the organization name recognition, and achieved the 84.58 F-value for evaluation data.

A conserved mechanism for replication origin recognition and binding in archaea.

PubMed

Majerník, Alan I; Chong, James P J

2008-01-15

To date, methanogens are the only group within the archaea where firing DNA replication origins have not been demonstrated in vivo. In the present study we show that a previously identified cluster of ORB (origin recognition box) sequences do indeed function as an origin of replication in vivo in the archaeon Methanothermobacter thermautotrophicus. Although the consensus sequence of ORBs in M. thermautotrophicus is somewhat conserved when compared with ORB sequences in other archaea, the Cdc6-1 protein from M. thermautotrophicus (termed MthCdc6-1) displays sequence-specific binding that is selective for the MthORB sequence and does not recognize ORBs from other archaeal species. Stabilization of in vitro MthORB DNA binding by MthCdc6-1 requires additional conserved sequences 3' to those originally described for M. thermautotrophicus. By testing synthetic sequences bearing mutations in the MthORB consensus sequence, we show that Cdc6/ORB binding is critically dependent on the presence of an invariant guanine found in all archaeal ORB sequences. Mutation of a universally conserved arginine residue in the recognition helix of the winged helix domain of archaeal Cdc6-1 shows that specific origin sequence recognition is dependent on the interaction of this arginine residue with the invariant guanine. Recognition of a mutated origin sequence can be achieved by mutation of the conserved arginine residue to a lysine or glutamine residue. Thus despite a number of differences in protein and DNA sequences between species, the mechanism of origin recognition and binding appears to be conserved throughout the archaea.

Function-based classification of carbohydrate-active enzymes by recognition of short, conserved peptide motifs.

PubMed

Busk, Peter Kamp; Lange, Lene

2013-06-01

Functional prediction of carbohydrate-active enzymes is difficult due to low sequence identity. However, similar enzymes often share a few short motifs, e.g., around the active site, even when the overall sequences are very different. To exploit this notion for functional prediction of carbohydrate-active enzymes, we developed a simple algorithm, peptide pattern recognition (PPR), that can divide proteins into groups of sequences that share a set of short conserved sequences. When this method was used on 118 glycoside hydrolase 5 proteins with 9% average pairwise identity and representing four characterized enzymatic functions, 97% of the proteins were sorted into groups correlating with their enzymatic activity. Furthermore, we analyzed 8,138 glycoside hydrolase 13 proteins including 204 experimentally characterized enzymes with 28 different functions. There was a 91% correlation between group and enzyme activity. These results indicate that the function of carbohydrate-active enzymes can be predicted with high precision by finding short, conserved motifs in their sequences. The glycoside hydrolase 61 family is important for fungal biomass conversion, but only a few proteins of this family have been functionally characterized. Interestingly, PPR divided 743 glycoside hydrolase 61 proteins into 16 subfamilies useful for targeted investigation of the function of these proteins and pinpointed three conserved motifs with putative importance for enzyme activity. Furthermore, the conserved sequences were useful for cloning of new, subfamily-specific glycoside hydrolase 61 proteins from 14 fungi. In conclusion, identification of conserved sequence motifs is a new approach to sequence analysis that can predict carbohydrate-active enzyme functions with high precision.

Creation of a type IIS restriction endonuclease with a long recognition sequence

PubMed Central

Lippow, Shaun M.; Aha, Patti M.; Parker, Matthew H.; Blake, William J.; Baynes, Brian M.; Lipovšek, Daša

2009-01-01

Type IIS restriction endonucleases cleave DNA outside their recognition sequences, and are therefore particularly useful in the assembly of DNA from smaller fragments. A limitation of type IIS restriction endonucleases in assembly of long DNA sequences is the relative abundance of their target sites. To facilitate ligation-based assembly of extremely long pieces of DNA, we have engineered a new type IIS restriction endonuclease that combines the specificity of the homing endonuclease I-SceI with the type IIS cleavage pattern of FokI. We linked a non-cleaving mutant of I-SceI, which conveys to the chimeric enzyme its specificity for an 18-bp DNA sequence, to the catalytic domain of FokI, which cuts DNA at a defined site outside the target site. Whereas previously described chimeric endonucleases do not produce type IIS-like precise DNA overhangs suitable for ligation, our chimeric endonuclease cleaves double-stranded DNA exactly 2 and 6 nt from the target site to generate homogeneous, 5′, four-base overhangs, which can be ligated with 90% fidelity. We anticipate that these enzymes will be particularly useful in manipulation of DNA fragments larger than a thousand bases, which are very likely to contain target sites for all natural type IIS restriction endonucleases. PMID:19304757

Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition

PubMed Central

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-01-01

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates (F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware. PMID:28208736

Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition.

PubMed

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-02-08

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates ( F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware.

Influence of motion on face recognition.

PubMed

Bonfiglio, Natale S; Manfredi, Valentina; Pessa, Eliano

2012-02-01

The influence of motion information and temporal associations on recognition of non-familiar faces was investigated using two groups which performed a face recognition task. One group was presented with regular temporal sequences of face views designed to produce the impression of motion of the face rotating in depth, the other group with random sequences of the same views. In one condition, participants viewed the sequences of the views in rapid succession with a negligible interstimulus interval (ISI). This condition was characterized by three different presentation times. In another condition, participants were presented a sequence with a 1-sec. ISI among the views. That regular sequences of views with a negligible ISI and a shorter presentation time were hypothesized to give rise to better recognition, related to a stronger impression of face rotation. Analysis of data from 45 participants showed a shorter presentation time was associated with significantly better accuracy on the recognition task; however, differences between performances associated with regular and random sequences were not significant.

HIV-1 gp140 epitope recognition is influenced by immunoglobulin DH gene segment sequence

PubMed Central

Wang, Yuge; Kapoor, Pratibha; Parks, Robert; Silva-Sanchez, Aaron; Alam, S. Munir; Verkoczy, Laurent; Liao, Hua-Xin; Zhuang, Yingxin; Burrows, Peter; Levinson, Michael; Elgavish, Ada; Cui, Xiangqin; Haynes, Barton F.; Schroeder, Harry

2015-01-01

Complementarity determining region 3 of the immunoglobulin (Ig) H chain (CDR-H3) lies at the center of the antigen binding site where it often plays a decisive role in antigen recognition and binding. Amino acids encoded by the diversity (DH) gene segment are the main component of CDR-H3. Each DH has the potential to rearrange into one of six DH reading frames (RFs), each of which exhibits a characteristic amino acid hydrophobicity signature that has been conserved among jawed vertebrates by natural selection. A preference for use of RF1 promotes the incorporation of tyrosine into CDR-H3 while suppressing the inclusion of hydrophobic or charged amino acids. To test the hypothesis that these evolutionary constraints on DH sequence influence epitope recognition, we used mice with a single DH that has been altered to preferentially use RF2 or inverted RF1. B cells in these mice produce a CDR-H3 repertoire that is enriched for valine or arginine in place of tyrosine. We serially immunized this panel of mice with gp140 from HIV-1 JR-FL isolate and then used ELISA or peptide microarray to assess antibody binding to key or overlapping HIV-1 envelope epitopes. By ELISA, serum reactivity to key epitopes varied by DH sequence. By microarray, sera with Ig CDR-H3s enriched for arginine bound to linear peptides with a greater range of hydrophobicity, but had a lower intensity of binding than sera containing Ig CDR-H3s enriched for tyrosine or valine. We conclude that patterns of epitope recognition and binding can be heavily influenced by DH germline sequence. This may help explain why antibodies in HIV infected patients must undergo extensive somatic mutation in order to bind to specific viral epitopes and achieve neutralization. PMID:26687685

Proliferating cell nuclear antigen (Pcna) as a direct downstream target gene of Hoxc8

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

Min, Hyehyun; Lee, Ji-Yeon; Bok, Jinwoong

2010-02-19

Hoxc8 is a member of Hox family transcription factors that play crucial roles in spatiotemporal body patterning during embryogenesis. Hox proteins contain a conserved 61 amino acid homeodomain, which is responsible for recognition and binding of the proteins onto Hox-specific DNA binding motifs and regulates expression of their target genes. Previously, using proteome analysis, we identified Proliferating cell nuclear antigen (Pcna) as one of the putative target genes of Hoxc8. Here, we asked whether Hoxc8 regulates Pcna expression by directly binding to the regulatory sequence of Pcna. In mouse embryos at embryonic day 11.5, the expression pattern of Pcna wasmore » similar to that of Hoxc8 along the anteroposterior body axis. Moreover, Pcna transcript levels as well as cell proliferation rate were increased by overexpression of Hoxc8 in C3H10T1/2 mouse embryonic fibroblast cells. Characterization of 2.3 kb genomic sequence upstream of Pcna coding region revealed that the upstream sequence contains several Hox core binding sequences and one Hox-Pbx binding sequence. Direct binding of Hoxc8 proteins to the Pcna regulatory sequence was verified by chromatin immunoprecipitation assay. Taken together, our data suggest that Pcna is a direct downstream target of Hoxc8.« less

The diversity of H3 loops determines the antigen-binding tendencies of antibody CDR loops.

PubMed

Tsuchiya, Yuko; Mizuguchi, Kenji

2016-04-01

Of the complementarity-determining regions (CDRs) of antibodies, H3 loops, with varying amino acid sequences and loop lengths, adopt particularly diverse loop conformations. The diversity of H3 conformations produces an array of antigen recognition patterns involving all the CDRs, in which the residue positions actually in contact with the antigen vary considerably. Therefore, for a deeper understanding of antigen recognition, it is necessary to relate the sequence and structural properties of each residue position in each CDR loop to its ability to bind antigens. In this study, we proposed a new method for characterizing the structural features of the CDR loops and obtained the antigen-binding ability of each residue position in each CDR loop. This analysis led to a simple set of rules for identifying probable antigen-binding residues. We also found that the diversity of H3 loop lengths and conformations affects the antigen-binding tendencies of all the CDR loops. © 2016 The Protein Society.

Nucleic acid constructs containing orthogonal site selective recombinases (OSSRs)

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

Gilmore, Joshua M.; Anderson, J. Christopher; Dueber, John E.

The present invention provides for a recombinant nucleic acid comprising a nucleotide sequence comprising a plurality of constructs, wherein each construct independently comprises a nucleotide sequence of interest flanked by a pair of recombinase recognition sequences. Each pair of recombinase recognition sequences is recognized by a distinct recombinase. Optionally, each construct can, independently, further comprise one or more genes encoding a recombinase capable of recognizing the pair of recombinase recognition sequences of the construct. The recombinase can be an orthogonal (non-cross reacting), site-selective recombinase (OSSR).

Molecular phylogeny of the neotropical genus Christensonella (Orchidaceae, Maxillariinae): species delimitation and insights into chromosome evolution.

PubMed

Koehler, Samantha; Cabral, Juliano S; Whitten, W Mark; Williams, Norris H; Singer, Rodrigo B; Neubig, Kurt M; Guerra, Marcelo; Souza, Anete P; Amaral, Maria do Carmo E

2008-10-01

Species' boundaries applied within Christensonella have varied due to the continuous pattern of variation and mosaic distribution of diagnostic characters. The main goals of this study were to revise the species' delimitation and propose a more stable classification for this genus. In order to achieve these aims phylogenetic relationships were inferred using DNA sequence data and cytological diversity within Christensonella was examined based on chromosome counts and heterochromatin patterns. The results presented describe sets of diagnostic morphological characters that can be used for species' identification. Phylogenetic studies were based on sequence data of nuclear and plastid regions, analysed using maximum parsimony and maximum likelihood criteria. Cytogenetic observations of mitotic cells were conducted using CMA and DAPI fluorochromes. Six of 21 currently accepted species were recovered. The results also support recognition of the 'C. pumila' clade as a single species. Molecular phylogenetic relationships within the 'C. acicularis-C. madida' and 'C. ferdinandiana-C. neowiedii' species' complexes were not resolved and require further study. Deeper relationships were incongruent between plastid and nuclear trees, but with no strong bootstrap support for either, except for the position of C. vernicosa. Cytogenetic data indicated chromosome numbers of 2n = 36, 38 and 76, and with substantial variation in the presence and location of CMA/DAPI heterochromatin bands. The recognition of ten species of Christensonella is proposed according to the molecular and cytogenetic patterns observed. In addition, diagnostic morphological characters are presented for each recognized species. Banding patterns and chromosome counts suggest the occurrence of centric fusion/fission events, especially for C. ferdinandiana. The results suggest that 2n = 36 karyotypes evolved from 2n = 38 through descendent dysploidy. Patterns of heterochromatin distribution and other karyotypic data proved to be a valuable source of information to understand evolutionary patterns within Maxillariinae orchids.

Molecular Phylogeny of the Neotropical Genus Christensonella (Orchidaceae, Maxillariinae): Species Delimitation and Insights into Chromosome Evolution

PubMed Central

Koehler, Samantha; Cabral, Juliano S.; Whitten, W. Mark; Williams, Norris H.; Singer, Rodrigo B.; Neubig, Kurt M.; Guerra, Marcelo; Souza, Anete P.; Amaral, Maria do Carmo E.

2008-01-01

Background and Aims Species' boundaries applied within Christensonella have varied due to the continuous pattern of variation and mosaic distribution of diagnostic characters. The main goals of this study were to revise the species' delimitation and propose a more stable classification for this genus. In order to achieve these aims phylogenetic relationships were inferred using DNA sequence data and cytological diversity within Christensonella was examined based on chromosome counts and heterochromatin patterns. The results presented describe sets of diagnostic morphological characters that can be used for species' identification. Methods Phylogenetic studies were based on sequence data of nuclear and plastid regions, analysed using maximum parsimony and maximum likelihood criteria. Cytogenetic observations of mitotic cells were conducted using CMA and DAPI fluorochromes. Key Results Six of 21 currently accepted species were recovered. The results also support recognition of the ‘C. pumila’ clade as a single species. Molecular phylogenetic relationships within the ‘C. acicularis–C. madida’ and ‘C. ferdinandiana–C. neowiedii’ species' complexes were not resolved and require further study. Deeper relationships were incongruent between plastid and nuclear trees, but with no strong bootstrap support for either, except for the position of C. vernicosa. Cytogenetic data indicated chromosome numbers of 2n = 36, 38 and 76, and with substantial variation in the presence and location of CMA/DAPI heterochromatin bands. Conclusions The recognition of ten species of Christensonella is proposed according to the molecular and cytogenetic patterns observed. In addition, diagnostic morphological characters are presented for each recognized species. Banding patterns and chromosome counts suggest the occurrence of centric fusion/fission events, especially for C. ferdinandiana. The results suggest that 2n = 36 karyotypes evolved from 2n = 38 through descendent dysploidy. Patterns of heterochromatin distribution and other karyotypic data proved to be a valuable source of information to understand evolutionary patterns within Maxillariinae orchids. PMID:18687799

Possibility expectation and its decision making algorithm

NASA Technical Reports Server (NTRS)

Keller, James M.; Yan, Bolin

1992-01-01

The fuzzy integral has been shown to be an effective tool for the aggregation of evidence in decision making. Of primary importance in the development of a fuzzy integral pattern recognition algorithm is the choice (construction) of the measure which embodies the importance of subsets of sources of evidence. Sugeno fuzzy measures have received the most attention due to the recursive nature of the fabrication of the measure on nested sequences of subsets. Possibility measures exhibit an even simpler generation capability, but usually require that one of the sources of information possess complete credibility. In real applications, such normalization may not be possible, or even desirable. In this report, both the theory and a decision making algorithm for a variation of the fuzzy integral are presented. This integral is based on a possibility measure where it is not required that the measure of the universe be unity. A training algorithm for the possibility densities in a pattern recognition application is also presented with the results demonstrated on the shuttle-earth-space training and testing images.

FPGA design of correlation-based pattern recognition

NASA Astrophysics Data System (ADS)

Jridi, Maher; Alfalou, Ayman

2017-05-01

Optical/Digital pattern recognition and tracking based on optical/digital correlation are a well-known techniques to detect, identify and localize a target object in a scene. Despite the limited number of treatments required by the correlation scheme, computational time and resources are relatively high. The most computational intensive treatment required by the correlation is the transformation from spatial to spectral domain and then from spectral to spatial domain. Furthermore, these transformations are used on optical/digital encryption schemes like the double random phase encryption (DRPE). In this paper, we present a VLSI architecture for the correlation scheme based on the fast Fourier transform (FFT). One interesting feature of the proposed scheme is its ability to stream image processing in order to perform correlation for video sequences. A trade-off between the hardware consumption and the robustness of the correlation can be made in order to understand the limitations of the correlation implementation in reconfigurable and portable platforms. Experimental results obtained from HDL simulations and FPGA prototype have demonstrated the advantages of the proposed scheme.

A discriminative method for family-based protein remote homology detection that combines inductive logic programming and propositional models

PubMed Central

2011-01-01

Background Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). Results We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. Conclusions The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions. PMID:21429187

A discriminative method for family-based protein remote homology detection that combines inductive logic programming and propositional models.

PubMed

Bernardes, Juliana S; Carbone, Alessandra; Zaverucha, Gerson

2011-03-23

Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions.

Human action recognition based on kinematic similarity in real time

PubMed Central

Chen, Longting; Luo, Ailing; Zhang, Sicong

2017-01-01

Human action recognition using 3D pose data has gained a growing interest in the field of computer robotic interfaces and pattern recognition since the availability of hardware to capture human pose. In this paper, we propose a fast, simple, and powerful method of human action recognition based on human kinematic similarity. The key to this method is that the action descriptor consists of joints position, angular velocity and angular acceleration, which can meet the different individual sizes and eliminate the complex normalization. The angular parameters of joints within a short sliding time window (approximately 5 frames) around the current frame are used to express each pose frame of human action sequence. Moreover, three modified KNN (k-nearest-neighbors algorithm) classifiers are employed in our method: one for achieving the confidence of every frame in the training step, one for estimating the frame label of each descriptor, and one for classifying actions. Additional estimating of the frame’s time label makes it possible to address single input frames. This approach can be used on difficult, unsegmented sequences. The proposed method is efficient and can be run in real time. The research shows that many public datasets are irregularly segmented, and a simple method is provided to regularize the datasets. The approach is tested on some challenging datasets such as MSR-Action3D, MSRDailyActivity3D, and UTD-MHAD. The results indicate our method achieves a higher accuracy. PMID:29073131

Face recognition based on matching of local features on 3D dynamic range sequences

NASA Astrophysics Data System (ADS)

Echeagaray-Patrón, B. A.; Kober, Vitaly

2016-09-01

3D face recognition has attracted attention in the last decade due to improvement of technology of 3D image acquisition and its wide range of applications such as access control, surveillance, human-computer interaction and biometric identification systems. Most research on 3D face recognition has focused on analysis of 3D still data. In this work, a new method for face recognition using dynamic 3D range sequences is proposed. Experimental results are presented and discussed using 3D sequences in the presence of pose variation. The performance of the proposed method is compared with that of conventional face recognition algorithms based on descriptors.

Application of artificial neural networks to identify equilibration in computer simulations

NASA Astrophysics Data System (ADS)

Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

2017-11-01

Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

Does the cost function matter in Bayes decision rule?

PubMed

Schlü ter, Ralf; Nussbaum-Thom, Markus; Ney, Hermann

2012-02-01

In many tasks in pattern recognition, such as automatic speech recognition (ASR), optical character recognition (OCR), part-of-speech (POS) tagging, and other string recognition tasks, we are faced with a well-known inconsistency: The Bayes decision rule is usually used to minimize string (symbol sequence) error, whereas, in practice, we want to minimize symbol (word, character, tag, etc.) error. When comparing different recognition systems, we do indeed use symbol error rate as an evaluation measure. The topic of this work is to analyze the relation between string (i.e., 0-1) and symbol error (i.e., metric, integer valued) cost functions in the Bayes decision rule, for which fundamental analytic results are derived. Simple conditions are derived for which the Bayes decision rule with integer-valued metric cost function and with 0-1 cost gives the same decisions or leads to classes with limited cost. The corresponding conditions can be tested with complexity linear in the number of classes. The results obtained do not make any assumption w.r.t. the structure of the underlying distributions or the classification problem. Nevertheless, the general analytic results are analyzed via simulations of string recognition problems with Levenshtein (edit) distance cost function. The results support earlier findings that considerable improvements are to be expected when initial error rates are high.

Face recognition system and method using face pattern words and face pattern bytes

DOEpatents

Zheng, Yufeng

2014-12-23

The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

Structural Analysis of Single-Point Mutations Given an RNA Sequence: A Case Study with RNAMute

NASA Astrophysics Data System (ADS)

Churkin, Alexander; Barash, Danny

2006-12-01

We introduce here for the first time the RNAMute package, a pattern-recognition-based utility to perform mutational analysis and detect vulnerable spots within an RNA sequence that affect structure. Mutations in these spots may lead to a structural change that directly relates to a change in functionality. Previously, the concept was tried on RNA genetic control elements called "riboswitches" and other known RNA switches, without an organized utility that analyzes all single-point mutations and can be further expanded. The RNAMute package allows a comprehensive categorization, given an RNA sequence that has functional relevance, by exploring the patterns of all single-point mutants. For illustration, we apply the RNAMute package on an RNA transcript for which individual point mutations were shown experimentally to inactivate spectinomycin resistance in Escherichia coli. Functional analysis of mutations on this case study was performed experimentally by creating a library of point mutations using PCR and screening to locate those mutations. With the availability of RNAMute, preanalysis can be performed computationally before conducting an experiment.

Computational identification of epitopes in the glycoproteins of novel bunyavirus (SFTS virus) recognized by a human monoclonal antibody (MAb 4-5)

NASA Astrophysics Data System (ADS)

Zhang, Wenshuai; Zeng, Xiaoyan; Zhang, Li; Peng, Haiyan; Jiao, Yongjun; Zeng, Jun; Treutlein, Herbert R.

2013-06-01

In this work, we have developed a new approach to predict the epitopes of antigens that are recognized by a specific antibody. Our method is based on the "multiple copy simultaneous search" (MCSS) approach which identifies optimal locations of small chemical functional groups on the surfaces of the antibody, and identifying sequence patterns of peptides that can bind to the surface of the antibody. The identified sequence patterns are then used to search the amino-acid sequence of the antigen protein. The approach was validated by reproducing the binding epitope of HIV gp120 envelop glycoprotein for the human neutralizing antibody as revealed in the available crystal structure. Our method was then applied to predict the epitopes of two glycoproteins of a newly discovered bunyavirus recognized by an antibody named MAb 4-5. These predicted epitopes can be verified by experimental methods. We also discuss the involvement of different amino acids in the antigen-antibody recognition based on the distributions of MCSS minima of different functional groups.

Multimodal neuroelectric interface development

NASA Technical Reports Server (NTRS)

Trejo, Leonard J.; Wheeler, Kevin R.; Jorgensen, Charles C.; Rosipal, Roman; Clanton, Sam T.; Matthews, Bryan; Hibbs, Andrew D.; Matthews, Robert; Krupka, Michael

2003-01-01

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.

Identification and transcriptional analysis of two types of lectins (SgCTL-1 and SgGal-1) from mollusk Solen grandis.

PubMed

Wei, Xiumei; Yang, Jianmin; Liu, Xiangquan; Yang, Dinglong; Xu, Jie; Fang, Jinghui; Wang, Weijun; Yang, Jialong

2012-08-01

C-type lectin and galectin are two types of animal carbohydrate-binding proteins which serve as pathogen recognition molecules and play crucial roles in the innate immunity of invertebrates. In the present study, a C-type lectin (designated as SgCTL-1) and galectin (designated as SgGal-1) were identified from mollusk Solen grandis, and their expression patterns, both in tissues and toward three pathogen-associated molecular patterns (PAMPs) stimulation were characterized. The full-length cDNA of SgCTL-1 and SgGal-1 was 1280 and 1466 bp, containing an open reading frame (ORF) of 519 and 1218 bp, respectively. Their deduced amino acid sequences showed high similarity to other members of C-type lectin and galectin superfamily, respectively. SgCTL-1 encoded a single carbohydrate-recognition domain (CRD), and the motif of Ca(2+)-binding site 2 was EPN (Glu(135)-Pro(136)-Asn(137)). While SgGal-1 encoded two CRDs, and the amino acid residues constituted the carbohydrate-binding motifs were well conserved in CRD1 but partially conserved in CRD2. Although SgCTL-1 and SgGal-1 exhibited different tissue expression pattern, they were both constitutively expressed in all tested tissues, including hemocytes, gonad, mantle, muscle, gill and hepatopancreas, and they were both highly expressed in hepatopancreas and gill. Furthermore, the mRNA expression of two lectins in hemocytes was significantly (P < 0.01) up-regulated with different levels after S. grandis were stimulated by lipopolysaccharide (LPS), peptidoglycan (PGN) or β-1,3-glucan. Our results suggested that SgCTL-1 and SgGal-1 from razor clam were two novel members of animal lectins, and they might function as pattern recognition receptors (PRRs) taking part in the process of pathogen recognition. Copyright © 2012 Elsevier Ltd. All rights reserved.

Fluidity of HIV-1-Specific T-Cell Responses during Acute and Early Subtype C HIV-1 Infection and Associations with Early Disease Progression ▿

PubMed Central

Mlotshwa, Mandla; Riou, Catherine; Chopera, Denis; de Assis Rosa, Debra; Ntale, Roman; Treunicht, Florette; Woodman, Zenda; Werner, Lise; van Loggerenberg, Francois; Mlisana, Koleka; Abdool Karim, Salim; Williamson, Carolyn; Gray, Clive M.

2010-01-01

Deciphering immune events during early stages of human immunodeficiency virus type 1 (HIV-1) infection is critical for understanding the course of disease. We characterized the hierarchy of HIV-1-specific T-cell gamma interferon (IFN-γ) enzyme-linked immunospot (ELISPOT) assay responses during acute subtype C infection in 53 individuals and associated temporal patterns of responses with disease progression in the first 12 months. There was a diverse pattern of T-cell recognition across the proteome, with the recognition of Nef being immunodominant as early as 3 weeks postinfection. Over the first 6 months, we found that there was a 23% chance of an increased response to Nef for every week postinfection (P = 0.0024), followed by a nonsignificant increase to Pol (4.6%) and Gag (3.2%). Responses to Env and regulatory proteins appeared to remain stable. Three temporal patterns of HIV-specific T-cell responses could be distinguished: persistent, lost, or new. The proportion of persistent T-cell responses was significantly lower (P = 0.0037) in individuals defined as rapid progressors than in those progressing slowly and who controlled viremia. Almost 90% of lost T-cell responses were coincidental with autologous viral epitope escape. Regression analysis between the time to fixed viral escape and lost T-cell responses (r = 0.61; P = 0.019) showed a mean delay of 14 weeks after viral escape. Collectively, T-cell epitope recognition is not a static event, and temporal patterns of IFN-γ-based responses exist. This is due partly to viral sequence variation but also to the recognition of invariant viral epitopes that leads to waves of persistent T-cell immunity, which appears to associate with slower disease progression in the first year of infection. PMID:20826686

Specific and Modular Binding Code for Cytosine Recognition in Pumilio/FBF (PUF) RNA-binding Domains

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

Dong, Shuyun; Wang, Yang; Cassidy-Amstutz, Caleb

2011-10-28

Pumilio/fem-3 mRNA-binding factor (PUF) proteins possess a recognition code for bases A, U, and G, allowing designed RNA sequence specificity of their modular Pumilio (PUM) repeats. However, recognition side chains in a PUM repeat for cytosine are unknown. Here we report identification of a cytosine-recognition code by screening random amino acid combinations at conserved RNA recognition positions using a yeast three-hybrid system. This C-recognition code is specific and modular as specificity can be transferred to different positions in the RNA recognition sequence. A crystal structure of a modified PUF domain reveals specific contacts between an arginine side chain and themore » cytosine base. We applied the C-recognition code to design PUF domains that recognize targets with multiple cytosines and to generate engineered splicing factors that modulate alternative splicing. Finally, we identified a divergent yeast PUF protein, Nop9p, that may recognize natural target RNAs with cytosine. This work deepens our understanding of natural PUF protein target recognition and expands the ability to engineer PUF domains to recognize any RNA sequence.« less

Learned Non-Rigid Object Motion is a View-Invariant Cue to Recognizing Novel Objects

PubMed Central

Chuang, Lewis L.; Vuong, Quoc C.; Bülthoff, Heinrich H.

2012-01-01

There is evidence that observers use learned object motion to recognize objects. For instance, studies have shown that reversing the learned direction in which a rigid object rotated in depth impaired recognition accuracy. This motion reversal can be achieved by playing animation sequences of moving objects in reverse frame order. In the current study, we used this sequence-reversal manipulation to investigate whether observers encode the motion of dynamic objects in visual memory, and whether such dynamic representations are encoded in a way that is dependent on the viewing conditions. Participants first learned dynamic novel objects, presented as animation sequences. Following learning, they were then tested on their ability to recognize these learned objects when their animation sequence was shown in the same sequence order as during learning or in the reverse sequence order. In Experiment 1, we found that non-rigid motion contributed to recognition performance; that is, sequence-reversal decreased sensitivity across different tasks. In subsequent experiments, we tested the recognition of non-rigidly deforming (Experiment 2) and rigidly rotating (Experiment 3) objects across novel viewpoints. Recognition performance was affected by viewpoint changes for both experiments. Learned non-rigid motion continued to contribute to recognition performance and this benefit was the same across all viewpoint changes. By comparison, learned rigid motion did not contribute to recognition performance. These results suggest that non-rigid motion provides a source of information for recognizing dynamic objects, which is not affected by changes to viewpoint. PMID:22661939

Pattern Recognition Using Artificial Neural Network: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, artificial neural network techniques theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system using ANN and identify research topics and applications which are at the forefront of this exciting and challenging field.

Recognition of Yeast Species from Gene Sequence Comparisons

USDA-ARS?s Scientific Manuscript database

This review discusses recognition of yeast species from gene sequence comparisons, which have been responsible for doubling the number of known yeasts over the past decade. The resolution provided by various single gene sequences is examined for both ascomycetous and basidiomycetous species, and th...

Wavelet-Based Signal and Image Processing for Target Recognition

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.

2002-11-01

The PI visited NSWC Dahlgren, VA, for six weeks in May-June 2002 and collaborated with scientists in the G33 TEAMS facility, and with Marilyn Rudzinsky of T44 Technology and Photonic Systems Branch. During this visit the PI also presented six educational seminars to NSWC scientists on various aspects of signal processing. Several items from the grant proposal were completed, including (1) wavelet-based algorithms for interpolation of 1-d signals and 2-d images; (2) Discrete Wavelet Transform domain based algorithms for filtering of image data; (3) wavelet-based smoothing of image sequence data originally obtained for the CRITTIR (Clutter Rejection Involving Temporal Techniques in the Infra-Red) project. The PI visited the University of Stellenbosch, South Africa to collaborate with colleagues Prof. B.M. Herbst and Prof. J. du Preez on the use of wavelet image processing in conjunction with pattern recognition techniques. The University of Stellenbosch has offered the PI partial funding to support a sabbatical visit in Fall 2003, the primary purpose of which is to enable the PI to develop and enhance his expertise in Pattern Recognition. During the first year, the grant supported publication of 3 referred papers, presentation of 9 seminars and an intensive two-day course on wavelet theory. The grant supported the work of two students who functioned as research assistants.

Auditory Pattern Recognition and Brief Tone Discrimination of Children with Reading Disorders

ERIC Educational Resources Information Center

Walker, Marianna M.; Givens, Gregg D.; Cranford, Jerry L.; Holbert, Don; Walker, Letitia

2006-01-01

Auditory pattern recognition skills in children with reading disorders were investigated using perceptual tests involving discrimination of frequency and duration tonal patterns. A behavioral test battery involving recognition of the pattern of presentation of tone triads was used in which individual components differed in either frequency or…

Image pattern recognition supporting interactive analysis and graphical visualization

NASA Technical Reports Server (NTRS)

Coggins, James M.

1992-01-01

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Understanding eye movements in face recognition using hidden Markov models.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2014-09-16

We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data. We conducted a face recognition task with Asian participants, and model each participant's eye movement pattern with an HMM, which summarized the participant's scan paths in face recognition with both regions of interest and the transition probabilities among them. By clustering these HMMs, we showed that participants' eye movements could be categorized into holistic or analytic patterns, demonstrating significant individual differences even within the same culture. Participants with the analytic pattern had longer response times, but did not differ significantly in recognition accuracy from those with the holistic pattern. We also found that correct and wrong recognitions were associated with distinctive eye movement patterns; the difference between the two patterns lies in the transitions rather than locations of the fixations alone. © 2014 ARVO.

Absolute Position Encoders With Vertical Image Binning

NASA Technical Reports Server (NTRS)

Leviton, Douglas B.

2005-01-01

Improved optoelectronic patternrecognition encoders that measure rotary and linear 1-dimensional positions at conversion rates (numbers of readings per unit time) exceeding 20 kHz have been invented. Heretofore, optoelectronic pattern-recognition absoluteposition encoders have been limited to conversion rates <15 Hz -- too low for emerging industrial applications in which conversion rates ranging from 1 kHz to as much as 100 kHz are required. The high conversion rates of the improved encoders are made possible, in part, by use of vertically compressible or binnable (as described below) scale patterns in combination with modified readout sequences of the image sensors [charge-coupled devices (CCDs)] used to read the scale patterns. The modified readout sequences and the processing of the images thus read out are amenable to implementation by use of modern, high-speed, ultra-compact microprocessors and digital signal processors or field-programmable gate arrays. This combination of improvements makes it possible to greatly increase conversion rates through substantial reductions in all three components of conversion time: exposure time, image-readout time, and image-processing time.

Layers: A molecular surface peeling algorithm and its applications to analyze protein structures

PubMed Central

Karampudi, Naga Bhushana Rao; Bahadur, Ranjit Prasad

2015-01-01

We present an algorithm ‘Layers’ to peel the atoms of proteins as layers. Using Layers we show an efficient way to transform protein structures into 2D pattern, named residue transition pattern (RTP), which is independent of molecular orientations. RTP explains the folding patterns of proteins and hence identification of similarity between proteins is simple and reliable using RTP than with the standard sequence or structure based methods. Moreover, Layers generates a fine-tunable coarse model for the molecular surface by using non-random sampling. The coarse model can be used for shape comparison, protein recognition and ligand design. Additionally, Layers can be used to develop biased initial configuration of molecules for protein folding simulations. We have developed a random forest classifier to predict the RTP of a given polypeptide sequence. Layers is a standalone application; however, it can be merged with other applications to reduce the computational load when working with large datasets of protein structures. Layers is available freely at http://www.csb.iitkgp.ernet.in/applications/mol_layers/main. PMID:26553411

Influence of time and length size feature selections for human activity sequences recognition.

PubMed

Fang, Hongqing; Chen, Long; Srinivasan, Raghavendiran

2014-01-01

In this paper, Viterbi algorithm based on a hidden Markov model is applied to recognize activity sequences from observed sensors events. Alternative features selections of time feature values of sensors events and activity length size feature values are tested, respectively, and then the results of activity sequences recognition performances of Viterbi algorithm are evaluated. The results show that the selection of larger time feature values of sensor events and/or smaller activity length size feature values will generate relatively better results on the activity sequences recognition performances. © 2013 ISA Published by ISA All rights reserved.

Exploring 3D Human Action Recognition: from Offline to Online.

PubMed

Liu, Zhenyu; Li, Rui; Tan, Jianrong

2018-02-20

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems-including real-time performance and sequence segmentation-are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset.

Exploring 3D Human Action Recognition: from Offline to Online

PubMed Central

Li, Rui; Liu, Zhenyu; Tan, Jianrong

2018-01-01

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems—including real-time performance and sequence segmentation—are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset. PMID:29461502

Foreshock Patterns Preceding Great Earthquakes in the Subduction Zone of Chile

NASA Astrophysics Data System (ADS)

Papadopoulos, G. A.; Minadakis, G.

2016-10-01

Foreshock activity is considered as one of the most promising precursory changes for the main shock prediction in the short term. Averaging over several foreshock sequences has shown that foreshocks are characterized by distinct 3D patterns: their epicenters move towards the main shock epicenter, event count accelerates, and b-value drops. However, these space-time-size patterns were verified so far only in a very few individual cases mainly due to inadequate seismicity catalogue data. We have investigated 3D foreshock patterns before the M w 8.8 Maule in 27 February 2010, M w 8.1 Iquique in 1 April 2014, and M w 8.4 Illapel in 16 September 2015 great earthquakes in the Chile subduction zone. To avoid biased results, no a priori spatiotemporal definitions of foreshocks were inserted. The procedure was based on pattern recognition from statistically significant seismicity changes in the three domains. The pattern recognition in one domain was independent of the pattern recognition in another domain. We found and verified with two independent catalogue data sets (CSN, IPOC) that within a critical area of ca. 65 km from the main shock epicenter, the 2014 event was preceded by distinct foreshock 3D patterns. A nearly weak foreshock stage (20 January-14 March 2014) was followed by a main-strong stage (15 March-1 April 2014) highly significant in all domains, although foreshock activity slightly decreased in about the last 5 days. Seismic moment release also accelerated in the last stage due to the occurrence of a cluster of very strong foreshock events. Foreshock activity very likely occurred in the hanging-wall fault domain on the South American Plate overriding Nazca Plate. The 2014 foreshock activity was quite similar to the one preceding the 6 Apr. 2009 L' Aquila (Italy) M w 6.3 earthquake associated with normal faulting. Using the 2014 earthquake as a reference event, we observed that similar foreshock 3D patterns preceded the 2010 and 2015 earthquakes within critical distances of about 170 and 50 km, respectively. However, the foreshock activities were only weak in both the cases likely because of poor catalogue completeness.

Structural insight into the specificity of the B3 DNA-binding domains provided by the co-crystal structure of the C-terminal fragment of BfiI restriction enzyme

PubMed Central

Golovenko, Dmitrij; Manakova, Elena; Zakrys, Linas; Zaremba, Mindaugas; Sasnauskas, Giedrius; Gražulis, Saulius; Siksnys, Virginijus

2014-01-01

The B3 DNA-binding domains (DBDs) of plant transcription factors (TF) and DBDs of EcoRII and BfiI restriction endonucleases (EcoRII-N and BfiI-C) share a common structural fold, classified as the DNA-binding pseudobarrel. The B3 DBDs in the plant TFs recognize a diverse set of target sequences. The only available co-crystal structure of the B3-like DBD is that of EcoRII-N (recognition sequence 5′-CCTGG-3′). In order to understand the structural and molecular mechanisms of specificity of B3 DBDs, we have solved the crystal structure of BfiI-C (recognition sequence 5′-ACTGGG-3′) complexed with 12-bp cognate oligoduplex. Structural comparison of BfiI-C–DNA and EcoRII-N–DNA complexes reveals a conserved DNA-binding mode and a conserved pattern of interactions with the phosphodiester backbone. The determinants of the target specificity are located in the loops that emanate from the conserved structural core. The BfiI-C–DNA structure presented here expands a range of templates for modeling of the DNA-bound complexes of the B3 family of plant TFs. PMID:24423868

Biosensors for DNA sequence detection

NASA Technical Reports Server (NTRS)

Vercoutere, Wenonah; Akeson, Mark

2002-01-01

DNA biosensors are being developed as alternatives to conventional DNA microarrays. These devices couple signal transduction directly to sequence recognition. Some of the most sensitive and functional technologies use fibre optics or electrochemical sensors in combination with DNA hybridization. In a shift from sequence recognition by hybridization, two emerging single-molecule techniques read sequence composition using zero-mode waveguides or electrical impedance in nanoscale pores.

Sequencing and de novo analysis of the hemocytes transcriptome in Litopenaeus vannamei response to white spot syndrome virus infection.

PubMed

Xue, Shuxia; Liu, Yichen; Zhang, Yichen; Sun, Yan; Geng, Xuyun; Sun, Jinsheng

2013-01-01

White spot syndrome virus (WSSV) is a causative pathogen found in most shrimp farming areas of the world and causes large economic losses to the shrimp aquaculture. The mechanism underlying the molecular pathogenesis of the highly virulent WSSV remains unknown. To better understand the virus-host interactions at the molecular level, the transcriptome profiles in hemocytes of unchallenged and WSSV-challenged shrimp (Litopenaeus vannamei) were compared using a short-read deep sequencing method (Illumina). RNA-seq analysis generated more than 25.81 million clean pair end (PE) reads, which were assembled into 52,073 unigenes (mean size = 520 bp). Based on sequence similarity searches, 23,568 (45.3%) genes were identified, among which 6,562 and 7,822 unigenes were assigned to gene ontology (GO) categories and clusters of orthologous groups (COG), respectively. Searches in the Kyoto Encyclopedia of Genes and Genomes Pathway database (KEGG) mapped 14,941 (63.4%) unigenes to 240 KEGG pathways. Among all the annotated unigenes, 1,179 were associated with immune-related genes. Digital gene expression (DGE) analysis revealed that the host transcriptome profile was slightly changed in the early infection (5 hours post injection) of the virus, while large transcriptional differences were identified in the late infection (48 hpi) of WSSV. The differentially expressed genes mainly involved in pattern recognition genes and some immune response factors. The results indicated that antiviral immune mechanisms were probably involved in the recognition of pathogen-associated molecular patterns. This study provided a global survey of host gene activities against virus infection in a non-model organism, pacific white shrimp. Results can contribute to the in-depth study of candidate genes in white shrimp, and help to improve the current understanding of host-pathogen interactions.

Transcriptomic analysis reveals tomato genes whose expression is induced specifically during effector-triggered immunity and identifies the Epk1 protein kinase which is required for the host response to three bacterial effector proteins.

PubMed

Pombo, Marina A; Zheng, Yi; Fernandez-Pozo, Noe; Dunham, Diane M; Fei, Zhangjun; Martin, Gregory B

2014-01-01

Plants have two related immune systems to defend themselves against pathogen attack. Initially,pattern-triggered immunity is activated upon recognition of microbe-associated molecular patterns by pattern recognition receptors. Pathogenic bacteria deliver effector proteins into the plant cell that interfere with this immune response and promote disease. However, some plants express resistance proteins that detect the presence of specific effectors leading to a robust defense response referred to as effector-triggered immunity. The interaction of tomato with Pseudomonas syringae pv. tomato is an established model system for understanding the molecular basis of these plant immune responses. We apply high-throughput RNA sequencing to this pathosystem to identify genes whose expression changes specifically during pattern-triggered or effector-triggered immunity. We then develop reporter genes for each of these responses that will enable characterization of the host response to the large collection of P. s. pv. tomato strains that express different combinations of effectors. Virus-induced gene silencing of 30 of the effector-triggered immunity-specific genes identifies Epk1 which encodes a predicted protein kinase from a family previously unknown to be involved in immunity. Knocked-down expression of Epk1 compromises effector-triggered immunity triggered by three bacterial effectors but not by effectors from non-bacterial pathogens. Epistasis experiments indicate that Epk1 acts upstream of effector-triggered immunity-associated MAP kinase signaling. Using RNA-seq technology we identify genes involved in specific immune responses. A functional genomics screen led to the discovery of Epk1, a novel predicted protein kinase required for plant defense activation upon recognition of three different bacterial effectors.

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

Unravelling Glucan Recognition Systems by Glycome Microarrays Using the Designer Approach and Mass Spectrometry*

PubMed Central

Palma, Angelina S.; Liu, Yan; Zhang, Hongtao; Zhang, Yibing; McCleary, Barry V.; Yu, Guangli; Huang, Qilin; Guidolin, Leticia S.; Ciocchini, Andres E.; Torosantucci, Antonella; Wang, Denong; Carvalho, Ana Luísa; Fontes, Carlos M. G. A.; Mulloy, Barbara; Childs, Robert A.; Feizi, Ten; Chai, Wengang

2015-01-01

Glucans are polymers of d-glucose with differing linkages in linear or branched sequences. They are constituents of microbial and plant cell-walls and involved in important bio-recognition processes, including immunomodulation, anticancer activities, pathogen virulence, and plant cell-wall biodegradation. Translational possibilities for these activities in medicine and biotechnology are considerable. High-throughput micro-methods are needed to screen proteins for recognition of specific glucan sequences as a lead to structure–function studies and their exploitation. We describe construction of a “glucome” microarray, the first sequence-defined glycome-scale microarray, using a “designer” approach from targeted ligand-bearing glucans in conjunction with a novel high-sensitivity mass spectrometric sequencing method, as a screening tool to assign glucan recognition motifs. The glucome microarray comprises 153 oligosaccharide probes with high purity, representing major sequences in glucans. Negative-ion electrospray tandem mass spectrometry with collision-induced dissociation was used for complete linkage analysis of gluco-oligosaccharides in linear “homo” and “hetero” and branched sequences. The system is validated using antibodies and carbohydrate-binding modules known to target α- or β-glucans in different biological contexts, extending knowledge on their specificities, and applied to reveal new information on glucan recognition by two signaling molecules of the immune system against pathogens: Dectin-1 and DC-SIGN. The sequencing of the glucan oligosaccharides by the MS method and their interrogation on the microarrays provides detailed information on linkage, sequence and chain length requirements of glucan-recognizing proteins, and are a sensitive means of revealing unsuspected sequences in the polysaccharides. PMID:25670804

Synthesis of compact patterns for NMR relaxation decay in intelligent "electronic tongue" for analyzing heavy oil composition

NASA Astrophysics Data System (ADS)

Lapshenkov, E. M.; Volkov, V. Y.; Kulagin, V. P.

2018-05-01

The article is devoted to the problem of pattern creation of the NMR sensor signal for subsequent recognition by the artificial neural network in the intelligent device "the electronic tongue". The specific problem of removing redundant data from the spin-spin relaxation signal pattern that is used as a source of information in analyzing the composition of oil and petroleum products is considered. The method is proposed that makes it possible to remove redundant data of the relaxation decay pattern but without introducing additional distortion. This method is based on combining some relaxation decay curve intervals that increment below the noise level such that the increment of the combined intervals is above the noise level. In this case, the relaxation decay curve samples that are located inside the combined intervals are removed from the pattern. This method was tested on the heavy-oil NMR signal patterns that were created by using the Carr-Purcell-Meibum-Gill (CPMG) sequence for recording the relaxation process. Parameters of CPMG sequence are: 100 μs - time interval between 180° pulses, 0.4s - duration of measurement. As a result, it was revealed that the proposed method allowed one to reduce the number of samples 15 times (from 4000 to 270), and the maximum detected root mean square error (RMS error) equals 0.00239 (equivalent to signal-to-noise ratio 418).

Molecular cloning and functional characterization of a short peptidoglycan recognition protein (HcPGRPS1) from the freshwater mussel, Hyriopsis cumingi.

PubMed

Yang, Ziyan; Li, Junhua; Li, Ying; Wu, Hongjuan; Wang, Xiaoyan

2013-12-01

Peptidoglycan recognition proteins (PGRPs), which are evolutionarily conserved from invertebrates to vertebrates, function as pattern-recognition and effector molecules in innate immunity. In the present study, a short-form PGRP, designated as HcPGRPS1 was identified from freshwater mussel Hyriopsis cumingi. The deduced amino acid sequence of HcPGRPS1 is composed of 235 residues which contains a conserved PGRP domain at the C-terminus. Sequence analysis showed that HcPGRPS1 shared high identities with other known PGRPs. The mRNA of HcPGRPS1 is constitutively expressed in a wide range of all tested tissues, with highest expression level in hepatopancreas, and its expression in tissues (gonad, nephridium, gill and foot) was up-regulated significantly after LPS or PGN stimulation (P<0.05). The recombinant protein of HcPGRPS1 exhibited binding activity and peptidoglycan-lytic amidase activity toward Lys-PGN from Staphylococcus aureus and DAP-PGN from Bacillus subtilis. Furthermore, recombinant HcPGRPS1 displayed strong antibacterial activity to both Gram-negative bacteria Escherichia coli, Aeromonas hydrophila, Aeromonas sobria and Gram-positive bacteria S. aureus in the presence of Zn(2+). These results suggested that HcPGRPS1 plays a multifunctional role in the defense and protection mechanisms of mussel innate immunity against infections. Copyright © 2013 Elsevier Ltd. All rights reserved.

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Specific minor groove solvation is a crucial determinant of DNA binding site recognition

PubMed Central

Harris, Lydia-Ann; Williams, Loren Dean; Koudelka, Gerald B.

2014-01-01

The DNA sequence preferences of nearly all sequence specific DNA binding proteins are influenced by the identities of bases that are not directly contacted by protein. Discrimination between non-contacted base sequences is commonly based on the differential abilities of DNA sequences to allow narrowing of the DNA minor groove. However, the factors that govern the propensity of minor groove narrowing are not completely understood. Here we show that the differential abilities of various DNA sequences to support formation of a highly ordered and stable minor groove solvation network are a key determinant of non-contacted base recognition by a sequence-specific binding protein. In addition, disrupting the solvent network in the non-contacted region of the binding site alters the protein's ability to recognize contacted base sequences at positions 5–6 bases away. This observation suggests that DNA solvent interactions link contacted and non-contacted base recognition by the protein. PMID:25429976

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

PubMed Central

Swartz, R. Andrew

2013-01-01

This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

MUSI: an integrated system for identifying multiple specificity from very large peptide or nucleic acid data sets.

PubMed

Kim, Taehyung; Tyndel, Marc S; Huang, Haiming; Sidhu, Sachdev S; Bader, Gary D; Gfeller, David; Kim, Philip M

2012-03-01

Peptide recognition domains and transcription factors play crucial roles in cellular signaling. They bind linear stretches of amino acids or nucleotides, respectively, with high specificity. Experimental techniques that assess the binding specificity of these domains, such as microarrays or phage display, can retrieve thousands of distinct ligands, providing detailed insight into binding specificity. In particular, the advent of next-generation sequencing has recently increased the throughput of such methods by several orders of magnitude. These advances have helped reveal the presence of distinct binding specificity classes that co-exist within a set of ligands interacting with the same target. Here, we introduce a software system called MUSI that can rapidly analyze very large data sets of binding sequences to determine the relevant binding specificity patterns. Our pipeline provides two major advances. First, it can detect previously unrecognized multiple specificity patterns in any data set. Second, it offers integrated processing of very large data sets from next-generation sequencing machines. The results are visualized as multiple sequence logos describing the different binding preferences of the protein under investigation. We demonstrate the performance of MUSI by analyzing recent phage display data for human SH3 domains as well as microarray data for mouse transcription factors.

Screening strategies for a highly polymorphic gene: DHPLC analysis of the Fanconi anemia group A gene.

PubMed

Rischewski, J; Schneppenheim, R

2001-01-30

Patients with Fanconi anemia (Fanc) are at risk of developing leukemia. Mutations of the group A gene (FancA) are most common. A multitude of polymorphisms and mutations within the 43 exons of the gene are described. To examine the role of heterozygosity as a risk factor for malignancies, a partially automatized screening method to identify aberrations was needed. We report on our experience with DHPLC (WAVE (Transgenomic)). PCR amplification of all 43 exons from one individual was performed on one microtiter plate on a gradient thermocycler. DHPLC analysis conditions were established via melting curves, prediction software, and test runs with aberrant samples. PCR products were analyzed twice: native, and after adding a WT-PCR product. Retention patterns were compared with previously identified polymorphic PCR products or mutants. We have defined the mutation screening conditions for all 43 exons of FancA using DHPLC. So far, 40 different sequence variations have been detected in more than 100 individuals. The native analysis identifies heterozygous individuals, and the second run detects homozygous aberrations. Retention patterns are specific for the underlying sequence aberration, thus reducing sequencing demand and costs. DHPLC is a valuable tool for reproducible recognition of known sequence aberrations and screening for unknown mutations in the highly polymorphic FancA gene.

An evolution based biosensor receptor DNA sequence generation algorithm.

PubMed

Kim, Eungyeong; Lee, Malrey; Gatton, Thomas M; Lee, Jaewan; Zang, Yupeng

2010-01-01

A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.

Hand gesture recognition by analysis of codons

NASA Astrophysics Data System (ADS)

Ramachandra, Poornima; Shrikhande, Neelima

2007-09-01

The problem of recognizing gestures from images using computers can be approached by closely understanding how the human brain tackles it. A full fledged gesture recognition system will substitute mouse and keyboards completely. Humans can recognize most gestures by looking at the characteristic external shape or the silhouette of the fingers. Many previous techniques to recognize gestures dealt with motion and geometric features of hands. In this thesis gestures are recognized by the Codon-list pattern extracted from the object contour. All edges of an image are described in terms of sequence of Codons. The Codons are defined in terms of the relationship between maxima, minima and zeros of curvature encountered as one traverses the boundary of the object. We have concentrated on a catalog of 24 gesture images from the American Sign Language alphabet (Letter J and Z are ignored as they are represented using motion) [2]. The query image given as an input to the system is analyzed and tested against the Codon-lists, which are shape descriptors for external parts of a hand gesture. We have used the Weighted Frequency Indexing Transform (WFIT) approach which is used in DNA sequence matching for matching the Codon-lists. The matching algorithm consists of two steps: 1) the query sequences are converted to short sequences and are assigned weights and, 2) all the sequences of query gestures are pruned into match and mismatch subsequences by the frequency indexing tree based on the weights of the subsequences. The Codon sequences with the most weight are used to determine the most precise match. Once a match is found, the identified gesture and corresponding interpretation are shown as output.

Advanced optical correlation and digital methods for pattern matching—50th anniversary of Vander Lugt matched filter

NASA Astrophysics Data System (ADS)

Millán, María S.

2012-10-01

On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical-digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption-decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical-digital solutions.

Recent speciation in the Indo-West Pacific: rapid evolution of gamete recognition and sperm morphology in cryptic species of sea urchin.

PubMed Central

Landry, C; Geyer, L B; Arakaki, Y; Uehara, T; Palumbi, Stephen R

2003-01-01

The rich species diversity of the marine Indo-West Pacific (IWP) has been explained largely on the basis of historical observation of large-scale diversity gradients. Careful study of divergence among closely related species can reveal important new information about the pace and mechanisms of their formation, and can illuminate the genesis of biogeographic patterns. Young species inhabiting the IWP include urchins of the genus Echinometra, which diverged over the past 1-5 Myr. Here, we report the most recent divergence of two cryptic species of Echinometra inhabiting this region. Mitochondrial cytochrome oxidase 1 (CO1) sequence data show that in Echinometra oblonga, species-level divergence in sperm morphology, gamete recognition proteins and gamete compatibility arose between central and western Pacific populations in the past 250 000 years. Divergence in sperm attachment proteins suggests rapid evolution of the fertilization system. Divergence of sperm morphology may be a common feature of free-spawning animals, and offers opportunities to simultaneously understand genetic divergence, changes in protein expression patterns and morphological evolution in traits directly related to reproductive isolation. PMID:12964987

Sequencing batch-reactor control using Gaussian-process models.

PubMed

Kocijan, Juš; Hvala, Nadja

2013-06-01

This paper presents a Gaussian-process (GP) model for the design of sequencing batch-reactor (SBR) control for wastewater treatment. The GP model is a probabilistic, nonparametric model with uncertainty predictions. In the case of SBR control, it is used for the on-line optimisation of the batch-phases duration. The control algorithm follows the course of the indirect process variables (pH, redox potential and dissolved oxygen concentration) and recognises the characteristic patterns in their time profile. The control algorithm uses GP-based regression to smooth the signals and GP-based classification for the pattern recognition. When tested on the signals from an SBR laboratory pilot plant, the control algorithm provided a satisfactory agreement between the proposed completion times and the actual termination times of the biodegradation processes. In a set of tested batches the final ammonia and nitrate concentrations were below 1 and 0.5 mg L(-1), respectively, while the aeration time was shortened considerably. Copyright © 2013 Elsevier Ltd. All rights reserved.

Conserved patterns hidden within group A Streptococcus M protein hypervariability recognize human C4b-binding protein

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

Buffalo, Cosmo Z.; Bahn-Suh, Adrian J.; Hirakis, Sophia P.

No vaccine exists against group A Streptococcus (GAS), a leading cause of worldwide morbidity and mortality. A severe hurdle is the hypervariability of its major antigen, the M protein, with >200 different M types known. Neutralizing antibodies typically recognize M protein hypervariable regions (HVRs) and confer narrow protection. In stark contrast, human C4b-binding protein (C4BP), which is recruited to the GAS surface to block phagocytic killing, interacts with a remarkably large number of M protein HVRs (apparently ~90%). Such broad recognition is rare, and we discovered a unique mechanism for this through the structure determination of four sequence-diverse M proteinsmore » in complexes with C4BP. The structures revealed a uniform and tolerant ‘reading head’ in C4BP, which detected conserved sequence patterns hidden within hypervariability. Our results open up possibilities for rational therapies that target the M–C4BP interaction, and also inform a path towards vaccine design.« less

The effect of letter string length and report condition on letter recognition accuracy.

PubMed

Raghunandan, Avesh; Karmazinaite, Berta; Rossow, Andrea S

Letter sequence recognition accuracy has been postulated to be limited primarily by low-level visual factors. The influence of high level factors such as visual memory (load and decay) has been largely overlooked. This study provides insight into the role of these factors by investigating the interaction between letter sequence recognition accuracy, letter string length and report condition. Letter sequence recognition accuracy for trigrams and pentagrams were measured in 10 adult subjects for two report conditions. In the complete report condition subjects reported all 3 or all 5 letters comprising trigrams and pentagrams, respectively. In the partial report condition, subjects reported only a single letter in the trigram or pentagram. Letters were presented for 100ms and rendered in high contrast, using black lowercase Courier font that subtended 0.4° at the fixation distance of 0.57m. Letter sequence recognition accuracy was consistently higher for trigrams compared to pentagrams especially for letter positions away from fixation. While partial report increased recognition accuracy in both string length conditions, the effect was larger for pentagrams, and most evident for the final letter positions within trigrams and pentagrams. The effect of partial report on recognition accuracy for the final letter positions increased as eccentricity increased away from fixation, and was independent of the inner/outer position of a letter. Higher-level visual memory functions (memory load and decay) play a role in letter sequence recognition accuracy. There is also suggestion of additional delays imposed on memory encoding by crowded letter elements. Copyright © 2016 Spanish General Council of Optometry. Published by Elsevier España, S.L.U. All rights reserved.

Segmentation and Recognition of Continuous Human Activity

DTIC Science & Technology

2001-01-01

This paper presents a methodology for automatic segmentation and recognition of continuous human activity . We segment a continuous human activity into...commencement or termination. We use single action sequences for the training data set. The test sequences, on the other hand, are continuous sequences of human ... activity that consist of three or more actions in succession. The system has been tested on continuous activity sequences containing actions such as

Structural analysis of DNA binding by C.Csp231I, a member of a novel class of R-M controller proteins regulating gene expression

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

Shevtsov, M. B.; Streeter, S. D.; Thresh, S.-J.

2015-02-01

The structure of the new class of controller proteins (exemplified by C.Csp231I) in complex with its 21 bp DNA-recognition sequence is presented, and the molecular basis of sequence recognition in this class of proteins is discussed. An unusual extended spacer between the dimer binding sites suggests a novel interaction between the two C-protein dimers. In a wide variety of bacterial restriction–modification systems, a regulatory ‘controller’ protein (or C-protein) is required for effective transcription of its own gene and for transcription of the endonuclease gene found on the same operon. We have recently turned our attention to a new class ofmore » controller proteins (exemplified by C.Csp231I) that have quite novel features, including a much larger DNA-binding site with an 18 bp (∼60 Å) spacer between the two palindromic DNA-binding sequences and a very different recognition sequence from the canonical GACT/AGTC. Using X-ray crystallography, the structure of the protein in complex with its 21 bp DNA-recognition sequence was solved to 1.8 Å resolution, and the molecular basis of sequence recognition in this class of proteins was elucidated. An unusual aspect of the promoter sequence is the extended spacer between the dimer binding sites, suggesting a novel interaction between the two C-protein dimers when bound to both recognition sites correctly spaced on the DNA. A U-bend model is proposed for this tetrameric complex, based on the results of gel-mobility assays, hydrodynamic analysis and the observation of key contacts at the interface between dimers in the crystal.« less

Robust autoassociative memory with coupled networks of Kuramoto-type oscillators

NASA Astrophysics Data System (ADS)

Heger, Daniel; Krischer, Katharina

2016-08-01

Uncertain recognition success, unfavorable scaling of connection complexity, or dependence on complex external input impair the usefulness of current oscillatory neural networks for pattern recognition or restrict technical realizations to small networks. We propose a network architecture of coupled oscillators for pattern recognition which shows none of the mentioned flaws. Furthermore we illustrate the recognition process with simulation results and analyze the dynamics analytically: Possible output patterns are isolated attractors of the system. Additionally, simple criteria for recognition success are derived from a lower bound on the basins of attraction.

Digital video steganalysis exploiting collusion sensitivity

NASA Astrophysics Data System (ADS)

Budhia, Udit; Kundur, Deepa

2004-09-01

In this paper we present an effective steganalyis technique for digital video sequences based on the collusion attack. Steganalysis is the process of detecting with a high probability and low complexity the presence of covert data in multimedia. Existing algorithms for steganalysis target detecting covert information in still images. When applied directly to video sequences these approaches are suboptimal. In this paper, we present a method that overcomes this limitation by using redundant information present in the temporal domain to detect covert messages in the form of Gaussian watermarks. Our gains are achieved by exploiting the collusion attack that has recently been studied in the field of digital video watermarking, and more sophisticated pattern recognition tools. Applications of our scheme include cybersecurity and cyberforensics.

Widespread Site-Dependent Buffering of Human Regulatory Polymorphism

PubMed Central

Kutyavin, Tanya; Stamatoyannopoulos, John A.

2012-01-01

The average individual is expected to harbor thousands of variants within non-coding genomic regions involved in gene regulation. However, it is currently not possible to interpret reliably the functional consequences of genetic variation within any given transcription factor recognition sequence. To address this, we comprehensively analyzed heritable genome-wide binding patterns of a major sequence-specific regulator (CTCF) in relation to genetic variability in binding site sequences across a multi-generational pedigree. We localized and quantified CTCF occupancy by ChIP-seq in 12 related and unrelated individuals spanning three generations, followed by comprehensive targeted resequencing of the entire CTCF–binding landscape across all individuals. We identified hundreds of variants with reproducible quantitative effects on CTCF occupancy (both positive and negative). While these effects paralleled protein–DNA recognition energetics when averaged, they were extensively buffered by striking local context dependencies. In the significant majority of cases buffering was complete, resulting in silent variants spanning every position within the DNA recognition interface irrespective of level of binding energy or evolutionary constraint. The prevalence of complex partial or complete buffering effects severely constrained the ability to predict reliably the impact of variation within any given binding site instance. Surprisingly, 40% of variants that increased CTCF occupancy occurred at positions of human–chimp divergence, challenging the expectation that the vast majority of functional regulatory variants should be deleterious. Our results suggest that, even in the presence of “perfect” genetic information afforded by resequencing and parallel studies in multiple related individuals, genomic site-specific prediction of the consequences of individual variation in regulatory DNA will require systematic coupling with empirical functional genomic measurements. PMID:22457641

The evolution and phylogeography of the African elephant inferred from mitochondrial DNA sequence and nuclear microsatellite markers.

PubMed

Eggert, Lori S; Rasner, Caylor A; Woodruff, David S

2002-10-07

Recent genetic results support the recognition of two African elephant species: Loxodonta africana, the savannah elephant, and Loxodonta cyclotis, the forest elephant. The study, however, did not include the populations of West Africa, where the taxonomic affinities of elephants have been much debated. We examined mitochondrial cytochrome b control region sequences and four microsatellite loci to investigate the genetic differences between the forest and savannah elephants of West and Central Africa. We then combined our data with published control region sequences from across Africa to examine patterns at the continental level. Our analysis reveals several deeply divergent lineages that do not correspond with the currently recognized taxonomy: (i) the forest elephants of Central Africa; the forest and savannah elephants of West Africa; and (iii) the savannah elephants of eastern, southern and Central Africa. We propose that the complex phylogeographic patterns we detect in African elephants result from repeated continental-scale climatic changes over their five-to-six million year evolutionary history. Until there is consensus on the taxonomy, we suggest that the genetic and ecological distinctness of these lineages should be an important factor in conservation management planning.

Structural determinants of nuclear export signal orientation in binding to exportin CRM1

DOE PAGES

Fung, Ho Yee Joyce; Fu, Szu -Chin; Brautigam, Chad A.; ...

2015-09-08

The Chromosome Region of Maintenance 1 (CRM1) protein mediates nuclear export of hundreds of proteins through recognition of their nuclear export signals (NESs), which are highly variable in sequence and structure. The plasticity of the CRM1-NES interaction is not well understood, as there are many NES sequences that seem incompatible with structures of the NES-bound CRM1 groove. Crystal structures of CRM1 bound to two different NESs with unusual sequences showed the NES peptides binding the CRM1 groove in the opposite orientation (minus) to that of previously studied NESs (plus). A comparison of minus and plus NESs identified structural and sequencemore » determinants for NES orientation. The binding of NESs to CRM1 in both orientations results in a large expansion in NES consensus patterns and therefore a corresponding expansion of potential NESs in the proteome.« less

RM-SORN: a reward-modulated self-organizing recurrent neural network.

PubMed

Aswolinskiy, Witali; Pipa, Gordon

2015-01-01

Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

Cerebellar contribution to feedforward control of locomotion.

PubMed

Pisotta, Iolanda; Molinari, Marco

2014-01-01

The cerebellum is an important contributor to feedforward control mechanisms of the central nervous system, and sequencing-the process that allows spatial and temporal relationships between events to be recognized-has been implicated as the fundamental cerebellar mode of operation. By adopting such a mode and because cerebellar activity patterns are sensitive to a variety of sensorimotor-related tasks, the cerebellum is believed to support motor and cognitive functions that are encoded in the frontal and parietal lobes of the cerebral cortex. In this model, the cerebellum is hypothesized to make predictions about the consequences of a motor or cognitive command that originates from the cortex to prepare the entire system to cope with ongoing changes. In this framework, cerebellar predictive mechanisms for locomotion are addressed, focusing on sensorial and motoric sequencing. The hypothesis that sequence recognition is the mechanism by which the cerebellum functions in gait control is presented and discussed.

Evidence for two attentional components in visual working memory.

PubMed

Allen, Richard J; Baddeley, Alan D; Hitch, Graham J

2014-11-01

How does executive attentional control contribute to memory for sequences of visual objects, and what does this reveal about storage and processing in working memory? Three experiments examined the impact of a concurrent executive load (backward counting) on memory for sequences of individually presented visual objects. Experiments 1 and 2 found disruptive concurrent load effects of equivalent magnitude on memory for shapes, colors, and colored shape conjunctions (as measured by single-probe recognition). These effects were present only for Items 1 and 2 in a 3-item sequence; the final item was always impervious to this disruption. This pattern of findings was precisely replicated in Experiment 3 when using a cued verbal recall measure of shape-color binding, with error analysis providing additional insights concerning attention-related loss of early-sequence items. These findings indicate an important role for executive processes in maintaining representations of earlier encountered stimuli in an active form alongside privileged storage of the most recent stimulus. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Evolutionary mechanisms involved in the virulence of infectious salmon anaemia virus (ISAV), a piscine orthomyxovirus

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

Markussen, Turhan; Jonassen, Christine Monceyron; Numanovic, Sanela

2008-05-10

Infectious salmon anaemia virus (ISAV) is an orthomyxovirus causing a multisystemic, emerging disease in Atlantic salmon. Here we present, for the first time, detailed sequence analyses of the full-genome sequence of a presumed avirulent isolate displaying a full-length hemagglutinin-esterase (HE) gene (HPR0), and compare this with full-genome sequences of 11 Norwegian ISAV isolates from clinically diseased fish. These analyses revealed the presence of a virulence marker right upstream of the putative cleavage site R{sub 267} in the fusion (F) protein, suggesting a Q{sub 266} {yields} L{sub 266} substitution to be a prerequisite for virulence. To gain virulence in isolates lackingmore » this substitution, a sequence insertion near the cleavage site seems to be required. This strongly suggests the involvement of a protease recognition pattern at the cleavage site of the fusion protein as a determinant of virulence, as seen in highly pathogenic influenza A virus H5 or H7 and the paramyxovirus Newcastle disease virus.« less

Management of familial cancer: sequencing, surveillance and society.

PubMed

Samuel, Nardin; Villani, Anita; Fernandez, Conrad V; Malkin, David

2014-12-01

The clinical management of familial cancer begins with recognition of patterns of cancer occurrence suggestive of genetic susceptibility in a proband or pedigree, to enable subsequent investigation of the underlying DNA mutations. In this regard, next-generation sequencing of DNA continues to transform cancer diagnostics, by enabling screening for cancer-susceptibility genes in the context of known and emerging familial cancer syndromes. Increasingly, not only are candidate cancer genes sequenced, but also entire 'healthy' genomes are mapped in children with cancer and their family members. Although large-scale genomic analysis is considered intrinsic to the success of cancer research and discovery, a number of accompanying ethical and technical issues must be addressed before this approach can be adopted widely in personalized therapy. In this Perspectives article, we describe our views on how the emergence of new sequencing technologies and cancer surveillance strategies is altering the framework for the clinical management of hereditary cancer. Genetic counselling and disclosure issues are discussed, and strategies for approaching ethical dilemmas are proposed.

Immune-Related Transcriptome of Coptotermes formosanus Shiraki Workers: The Defense Mechanism

PubMed Central

Hussain, Abid; Li, Yi-Feng; Cheng, Yu; Liu, Yang; Chen, Chuan-Cheng; Wen, Shuo-Yang

2013-01-01

Formosan subterranean termites, Coptotermes formosanus Shiraki, live socially in microbial-rich habitats. To understand the molecular mechanism by which termites combat pathogenic microbes, a full-length normalized cDNA library and four Suppression Subtractive Hybridization (SSH) libraries were constructed from termite workers infected with entomopathogenic fungi (Metarhizium anisopliae and Beauveria bassiana), Gram-positive Bacillus thuringiensis and Gram-negative Escherichia coli, and the libraries were analyzed. From the high quality normalized cDNA library, 439 immune-related sequences were identified. These sequences were categorized as pattern recognition receptors (47 sequences), signal modulators (52 sequences), signal transducers (137 sequences), effectors (39 sequences) and others (164 sequences). From the SSH libraries, 27, 17, 22 and 15 immune-related genes were identified from each SSH library treated with M. anisopliae, B. bassiana, B. thuringiensis and E. coli, respectively. When the normalized cDNA library was compared with the SSH libraries, 37 immune-related clusters were found in common; 56 clusters were identified in the SSH libraries, and 259 were identified in the normalized cDNA library. The immune-related gene expression pattern was further investigated using quantitative real time PCR (qPCR). Important immune-related genes were characterized, and their potential functions were discussed based on the integrated analysis of the results. We suggest that normalized cDNA and SSH libraries enable us to discover functional genes transcriptome. The results remarkably expand our knowledge about immune-inducible genes in C. formosanus Shiraki and enable the future development of novel control strategies for the management of Formosan subterranean termites. PMID:23874972

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

NASA Astrophysics Data System (ADS)

Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

2018-01-01

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.

Exploring the sequence-structure protein landscape in the glycosyltransferase family

PubMed Central

Zhang, Ziding; Kochhar, Sunil; Grigorov, Martin

2003-01-01

To understand the molecular basis of glycosyltransferases’ (GTFs) catalytic mechanism, extensive structural information is required. Here, fold recognition methods were employed to assign 3D protein shapes (folds) to the currently known GTF sequences, available in public databases such as GenBank and Swissprot. First, GTF sequences were retrieved and classified into clusters, based on sequence similarity only. Intracluster sequence similarity was chosen sufficiently high to ensure that the same fold is found within a given cluster. Then, a representative sequence from each cluster was selected to compose a subset of GTF sequences. The members of this reduced set were processed by three different fold recognition methods: 3D-PSSM, FUGUE, and GeneFold. Finally, the results from different fold recognition methods were analyzed and compared to sequence-similarity search methods (i.e., BLAST and PSI-BLAST). It was established that the folds of about 70% of all currently known GTF sequences can be confidently assigned by fold recognition methods, a value which is higher than the fold identification rate based on sequence comparison alone (48% for BLAST and 64% for PSI-BLAST). The identified folds were submitted to 3D clustering, and we found that most of the GTF sequences adopt the typical GTF A or GTF B folds. Our results indicate a lack of evidence that new GTF folds (i.e., folds other than GTF A and B) exist. Based on cases where fold identification was not possible, we suggest several sequences as the most promising targets for a structural genomics initiative focused on the GTF protein family. PMID:14500887

The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors

NASA Astrophysics Data System (ADS)

Marshall, J. S.; Blake, A. S. T.; Thomson, M. A.; Escudero, L.; de Vries, J.; Weston, J.; MicroBooNE Collaboration

2017-09-01

The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. The Pandora Software Development Kit provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each address a specific task in a particular topology; a series of many tens of algorithms then carefully builds-up a picture of the event. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction.

Real Time Large Memory Optical Pattern Recognition.

DTIC Science & Technology

1984-06-01

AD-Ri58 023 REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION(U) - h ARMY MISSILE COMMAND REDSTONE ARSENAL AL RESEARCH DIRECTORATE D A GREGORY JUN...TECHNICAL REPORT RR-84-9 Ln REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION Don A. Gregory Research Directorate US Army Missile Laboratory JUNE 1984 L...RR-84-9 , ___/_ _ __ _ __ _ __ _ __"__ _ 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED Real Time Large Memory Optical Pattern Technical

Classification and machine recognition of severe weather patterns

NASA Technical Reports Server (NTRS)

Wang, P. P.; Burns, R. C.

1976-01-01

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

Fuzzy Logic-Based Audio Pattern Recognition

NASA Astrophysics Data System (ADS)

Malcangi, M.

2008-11-01

Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

New Optical Transforms For Statistical Image Recognition

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1983-12-01

In optical implementation of statistical image recognition, new optical transforms on large images for real-time recognition are of special interest. Several important linear transformations frequently used in statistical pattern recognition have now been optically implemented, including the Karhunen-Loeve transform (KLT), the Fukunaga-Koontz transform (FKT) and the least-squares linear mapping technique (LSLMT).1-3 The KLT performs principle components analysis on one class of patterns for feature extraction. The FKT performs feature extraction for separating two classes of patterns. The LSLMT separates multiple classes of patterns by maximizing the interclass differences and minimizing the intraclass variations.

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

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

PubMed Central

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 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. Images PMID:8599930

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

PubMed

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.

Relative role of transfer zones in controlling sequence stacking patterns and facies distribution: insights from the Fushan Depression, South China Sea

NASA Astrophysics Data System (ADS)

Liu, Entao; Wang, Hua; Li, Yuan; Huang, Chuanyan

2015-04-01

In sedimentary basins, a transfer zone can be defined as a coordinated system of deformational features which has good prospects for hydrocarbon exploration. Although the term 'transfer zone' has been widely applied to the study of extensional basins, little attention has been paid to its controlling effect on sequence tracking pattern and depositional facies distribution. Fushan Depression is a half-graben rift sub-basin, located in the southeast of the Beibuwan Basin, South China Sea. In this study, comparative analysis of seismic reflection, palaeogeomorphology, fault activity and depositional facies distribution in the southern slope indicates that three different types of sequence stacking patterns (i.e. multi-level step-fault belt in the western area, flexure slope belt in the central area, gentle slope belt in the eastern area) were developed along the southern slope, together with a large-scale transfer zone in the central area, at the intersection of the western and eastern fault systems. Further analysis shows that the transfer zone played an important role in the diversity of sequence stacking patterns in the southern slope by dividing the Fushan Depression into two non-interfering tectonic systems forming different sequence patterns, and leading to the formation of the flexure slope belt in the central area. The transfer zone had an important controlling effect on not only the diversity of sequence tracking patterns, but also the facies distribution on the relay ramp. During the high-stand stage, under the controlling effect of the transfer zone, the sediments contain a significant proportion of coarser material accumulated and distributed along the ramp axis. By contrast, during the low-stand stage, the transfer zone did not seem to contribute significantly to the low-stand fan distribution which was mainly controlled by the slope gradient (palaeogeomorphology). Therefore, analysis of the transfer zone can provide a new perspective for basin analysis. In addition, the transfer zone area demonstrated unique hydrocarbon accumulation models different from the western and eastern areas. It was not only a structural high combined with sufficient coarse-grained reservoir quality sands, but was also associated with large-scale sublacustrine fan deposits with high quality reservoirs, indicating that the recognition of transfer zones can improve the prediction of hydrocarbon occurrences in similar settings.

The Need for Careful Data Collection for Pattern Recognition in Digital Pathology.

PubMed

Marée, Raphaël

2017-01-01

Effective pattern recognition requires carefully designed ground-truth datasets. In this technical note, we first summarize potential data collection issues in digital pathology and then propose guidelines to build more realistic ground-truth datasets and to control their quality. We hope our comments will foster the effective application of pattern recognition approaches in digital pathology.

Pattern recognition: A basis for remote sensing data analysis

NASA Technical Reports Server (NTRS)

Swain, P. H.

1973-01-01

The theoretical basis for the pattern-recognition-oriented algorithms used in the multispectral data analysis software system is discussed. A model of a general pattern recognition system is presented. The receptor or sensor is usually a multispectral scanner. For each ground resolution element the receptor produces n numbers or measurements corresponding to the n channels of the scanner.

Optical Pattern Recognition With Self-Amplification

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1994-01-01

In optical pattern recognition system with self-amplification, no reference beam used in addressing mode. Polarization of laser beam and orientation of photorefractive crystal chosen to maximize photorefractive effect. Intensity of recognition signal is orders of magnitude greater than other optical correlators. Apparatus regarded as real-time or quasi-real-time optical pattern recognizer with memory and reprogrammability.

Identification of immunity-related genes in the larvae of Protaetia brevitarsis seulensis (Coleoptera: Cetoniidae) by a next-generation sequencing-based transcriptome analysis.

PubMed

Bang, Kyeongrin; Hwang, Sejung; Lee, Jiae; Cho, Saeyoull

2015-01-01

To identify immune-related genes in the larvae of white-spotted flower chafers, next-generation sequencing was conducted with an Illumina HiSeq2000, resulting in 100 million cDNA reads with sequence information from over 10 billion base pairs (bp) and >50× transcriptome coverage. A subset of 77,336 contigs was created, and ∼35,532 sequences matched entries against the NCBI nonredundant database (cutoff, e < 10(-5)). Statistical analysis was performed on the 35,532 contigs. For profiling of the immune response, samples were analyzed by aligning 42 base sequence tags to the de novo reference assembly, comparing levels in immunized larvae to control levels of expression. Of the differentially expressed genes, 3,440 transcripts were upregulated and 3,590 transcripts were downregulated. Many of these genes were confirmed as immune-related genes such as pattern recognition proteins, immune-related signal transduction proteins, antimicrobial peptides, and cellular response proteins, by comparison to published data. © The Author 2015. Published by Oxford University Press on behalf of the Entomological Society of America.

Human behavior recognition using a context-free grammar

NASA Astrophysics Data System (ADS)

Rosani, Andrea; Conci, Nicola; De Natale, Francesco G. B.

2014-05-01

Automatic recognition of human activities and behaviors is still a challenging problem for many reasons, including limited accuracy of the data acquired by sensing devices, high variability of human behaviors, and gap between visual appearance and scene semantics. Symbolic approaches can significantly simplify the analysis and turn raw data into chains of meaningful patterns. This allows getting rid of most of the clutter produced by low-level processing operations, embedding significant contextual information into the data, as well as using simple syntactic approaches to perform the matching between incoming sequences and models. We propose a symbolic approach to learn and detect complex activities through the sequences of atomic actions. Compared to previous methods based on context-free grammars, we introduce several important novelties, such as the capability to learn actions based on both positive and negative samples, the possibility of efficiently retraining the system in the presence of misclassified or unrecognized events, and the use of a parsing procedure that allows correct detection of the activities also when they are concatenated and/or nested one with each other. An experimental validation on three datasets with different characteristics demonstrates the robustness of the approach in classifying complex human behaviors.

Sonar Recognition Training: An Investigation of Whole VS. Part and Analytic VS. Synthetic Procedures.

ERIC Educational Resources Information Center

Annett, John

An experienced person, in such tasks as sonar detection and recognition, has a considerable superiority over a machine recognition system in auditory pattern recognition. However, people require extensive exposure to auditory patterns before achieving a high level of performance. In an attempt to discover a method of training people to recognize…

Degraded character recognition based on gradient pattern

NASA Astrophysics Data System (ADS)

Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

2010-02-01

Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

Automatic Target Recognition Based on Cross-Plot

PubMed Central

Wong, Kelvin Kian Loong; Abbott, Derek

2011-01-01

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository. PMID:21980508

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

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

Acciarri, R.; Adams, C.; An, R.

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

DOE PAGES

Acciarri, R.; Adams, C.; An, R.; ...

2018-01-29

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

Mechanisms and neural basis of object and pattern recognition: a study with chess experts.

PubMed

Bilalić, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-11-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.

Finger Vein Recognition Based on Local Directional Code

PubMed Central

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger vein recognition based on local directional code.

PubMed

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-11-05

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

Structural basis for microRNA targeting

DOE PAGES

Schirle, Nicole T.; Sheu-Gruttadauria, Jessica; MacRae, Ian J.

2014-10-31

MicroRNAs (miRNAs) control expression of thousands of genes in plants and animals. miRNAs function by guiding Argonaute proteins to complementary sites in messenger RNAs (mRNAs) targeted for repression. In this paper, we determined crystal structures of human Argonaute-2 (Ago2) bound to a defined guide RNA with and without target RNAs representing miRNA recognition sites. These structures suggest a stepwise mechanism, in which Ago2 primarily exposes guide nucleotides (nt) 2 to 5 for initial target pairing. Pairing to nt 2 to 5 promotes conformational changes that expose nt 2 to 8 and 13 to 16 for further target recognition. Interactions withmore » the guide-target minor groove allow Ago2 to interrogate target RNAs in a sequence-independent manner, whereas an adenosine binding-pocket opposite guide nt 1 further facilitates target recognition. Spurious slicing of miRNA targets is avoided through an inhibitory coordination of one catalytic magnesium ion. Finally, these results explain the conserved nucleotide-pairing patterns in animal miRNA target sites first observed over two decades ago.« less

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Influence of Blurred Ways on Pattern Recognition of a Scale-Free Hopfield Neural Network

NASA Astrophysics Data System (ADS)

Chang, Wen-Li

2010-01-01

We investigate the influence of blurred ways on pattern recognition of a Barabási-Albert scale-free Hopfield neural network (SFHN) with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio (the number of patterns to average degree P/langlekrangle) is, the smaller the overlap of SFHN is. The influence of directed (large) way is largest and the directed (small) way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network P/N is less than 0. 1 conditions, there are three families curves of the overlap corresponding to directed (small), random and directed (large) blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.

The recognition of graphical patterns invariant to geometrical transformation of the models

NASA Astrophysics Data System (ADS)

Ileană, Ioan; Rotar, Corina; Muntean, Maria; Ceuca, Emilian

2010-11-01

In case that a pattern recognition system is used for images recognition (in robot vision, handwritten recognition etc.), the system must have the capacity to identify an object indifferently of its size or position in the image. The problem of the invariance of recognition can be approached in some fundamental modes. One may apply the similarity criterion used in associative recall. The original pattern is replaced by a mathematical transform that assures some invariance (e.g. the value of two-dimensional Fourier transformation is translation invariant, the value of Mellin transformation is scale invariant). In a different approach the original pattern is represented through a set of features, each of them being coded indifferently of the position, orientation or position of the pattern. Generally speaking, it is easy to obtain invariance in relation with one transformation group, but is difficult to obtain simultaneous invariance at rotation, translation and scale. In this paper we analyze some methods to achieve invariant recognition of images, particularly for digit images. A great number of experiments are due and the conclusions are underplayed in the paper.

REBASE--a database for DNA restriction and modification: enzymes, genes and genomes.

PubMed

Roberts, Richard J; Vincze, Tamas; Posfai, Janos; Macelis, Dana

2015-01-01

REBASE is a comprehensive and fully curated database of information about the components of restriction-modification (RM) systems. It contains fully referenced information about recognition and cleavage sites for both restriction enzymes and methyltransferases as well as commercial availability, methylation sensitivity, crystal and sequence data. All genomes that are completely sequenced are analyzed for RM system components, and with the advent of PacBio sequencing, the recognition sequences of DNA methyltransferases (MTases) are appearing rapidly. Thus, Type I and Type III systems can now be characterized in terms of recognition specificity merely by DNA sequencing. The contents of REBASE may be browsed from the web http://rebase.neb.com and selected compilations can be downloaded by FTP (ftp.neb.com). Monthly updates are also available via email. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Pattern recognition technique

NASA Technical Reports Server (NTRS)

Hong, J. P.

1971-01-01

Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

Galectins as self/non-self recognition receptors in innate and adaptive immunity: an unresolved paradox

PubMed Central

Vasta, Gerardo R.; Ahmed, Hafiz; Nita-Lazar, Mihai; Banerjee, Aditi; Pasek, Marta; Shridhar, Surekha; Guha, Prasun; Fernández-Robledo, José A.

2012-01-01

Galectins are characterized by their binding affinity for β-galactosides, a unique binding site sequence motif, and wide taxonomic distribution and structural conservation in vertebrates, invertebrates, protista, and fungi. Since their initial description, galectins were considered to bind endogenous (“self”) glycans and mediate developmental processes and cancer. In the past few years, however, numerous studies have described the diverse effects of galectins on cells involved in both innate and adaptive immune responses, and the mechanistic aspects of their regulatory roles in immune homeostasis. More recently, however, evidence has accumulated to suggest that galectins also bind exogenous (“non-self”) glycans on the surface of potentially pathogenic microbes, parasites, and fungi, suggesting that galectins can function as pattern recognition receptors (PRRs) in innate immunity. Thus, a perplexing paradox arises by the fact that galectins also recognize lactosamine-containing glycans on the host cell surface during developmental processes and regulation of immune responses. According to the currently accepted model for non-self recognition, PRRs recognize pathogens via highly conserved microbial surface molecules of wide distribution such as LPS or peptidoglycan (pathogen-associated molecular patterns; PAMPs), which are absent in the host. Hence, this would not apply to galectins, which apparently bind similar self/non-self molecular patterns on host and microbial cells. This paradox underscores first, an oversimplification in the use of the PRR/PAMP terminology. Second, and most importantly, it reveals significant gaps in our knowledge about the diversity of the host galectin repertoire, and the subcellular targeting, localization, and secretion. Furthermore, our knowledge about the structural and biophysical aspects of their interactions with the host and microbial carbohydrate moieties is fragmentary, and warrants further investigation. PMID:22811679

Systematic analysis of phosphotyrosine antibodies recognizing single phosphorylated EPIYA-motifs in CagA of East Asian-type Helicobacter pylori strains.

PubMed

Lind, Judith; Backert, Steffen; Hoffmann, Rebecca; Eichler, Jutta; Yamaoka, Yoshio; Perez-Perez, Guillermo I; Torres, Javier; Sticht, Heinrich; Tegtmeyer, Nicole

2016-09-02

Highly virulent strains of the gastric pathogen Helicobacter pylori encode a type IV secretion system (T4SS) that delivers the effector protein CagA into gastric epithelial cells. Translocated CagA undergoes tyrosine phosphorylation by members of the oncogenic c-Src and c-Abl host kinases at EPIYA-sequence motifs A, B and D in East Asian-type strains. These phosphorylated EPIYA-motifs serve as recognition sites for various SH2-domains containing human proteins, mediating interactions of CagA with host signaling factors to manipulate signal transduction pathways. Recognition of phospho-CagA is mainly based on the use of commercial pan-phosphotyrosine antibodies that were originally designed to detect phosphotyrosines in mammalian proteins. Specific anti-phospho-EPIYA antibodies for each of the three sites in CagA are not forthcoming. This study was designed to systematically analyze the detection preferences of each phosphorylated East Asian CagA EPIYA-motif by pan-phosphotyrosine antibodies and to determine a minimal recognition sequence. We synthesized phospho- and non-phosphopeptides derived from each predominant EPIYA-site, and determined the recognition patterns by seven different pan-phosphotyrosine antibodies using Western blotting, and also investigated representative East Asian H. pylori isolates during infection. The results indicate that a total of only 9-11 amino acids containing the phosphorylated East Asian EPIYA-types are required and sufficient to detect the phosphopeptides with high specificity. However, the sequence recognition by the different antibodies was found to bear high variability. From the seven antibodies used, only four recognized all three phosphorylated EPIYA-motifs A, B and D similarly well. Two of the phosphotyrosine antibodies preferentially bound primarily to the phosphorylated motif A and D, while the seventh antibody failed to react with any of the phosphorylated EPIYA-motifs. Control experiments confirmed that none of the antibodies reacted with non-phospho-CagA peptides and in accordance were able to recognize phosphotyrosine proteins in human cells. The results of this study disclose the various binding preferences of commercial anti-phosphotyrosine antibodies for phospho-EPIYA-motifs, and are valuable in the application for further characterization of CagA phosphorylation events during infection with H. pylori and risk prediction for gastric disease development.

DNA-imprinted polymer nanoparticles with monodispersity and prescribed DNA-strand patterns

NASA Astrophysics Data System (ADS)

Trinh, Tuan; Liao, Chenyi; Toader, Violeta; Barłóg, Maciej; Bazzi, Hassan S.; Li, Jianing; Sleiman, Hanadi F.

2018-02-01

As colloidal self-assembly increasingly approaches the complexity of natural systems, an ongoing challenge is to generate non-centrosymmetric structures. For example, patchy, Janus or living crystallization particles have significantly advanced the area of polymer assembly. It has remained difficult, however, to devise polymer particles that associate in a directional manner, with controlled valency and recognition motifs. Here, we present a method to transfer DNA patterns from a DNA cage to a polymeric nanoparticle encapsulated inside the cage in three dimensions. The resulting DNA-imprinted particles (DIPs), which are 'moulded' on the inside of the DNA cage, consist of a monodisperse crosslinked polymer core with a predetermined pattern of different DNA strands covalently 'printed' on their exterior, and further assemble with programmability and directionality. The number, orientation and sequence of DNA strands grafted onto the polymeric core can be controlled during the process, and the strands are addressable independently of each other.

A comparison of the real-time controllability of pattern recognition to conventional myoelectric control for discrete and simultaneous movements

PubMed Central

2014-01-01

Myoelectric control has been used for decades to control powered upper limb prostheses. Conventional, amplitude-based control has been employed to control a single prosthesis degree of freedom (DOF) such as closing and opening of the hand. Within the last decade, new and advanced arm and hand prostheses have been constructed that are capable of actuating numerous DOFs. Pattern recognition control has been proposed to control a greater number of DOFs than conventional control, but has traditionally been limited to sequentially controlling DOFs one at a time. However, able-bodied individuals use multiple DOFs simultaneously, and it may be beneficial to provide amputees the ability to perform simultaneous movements. In this study, four amputees who had undergone targeted motor reinnervation (TMR) surgery with previous training using myoelectric prostheses were configured to use three control strategies: 1) conventional amplitude-based myoelectric control, 2) sequential (one-DOF) pattern recognition control, 3) simultaneous pattern recognition control. Simultaneous pattern recognition was enabled by having amputees train each simultaneous movement as a separate motion class. For tasks that required control over just one DOF, sequential pattern recognition based control performed the best with the lowest average completion times, completion rates and length error. For tasks that required control over 2 DOFs, the simultaneous pattern recognition controller performed the best with the lowest average completion times, completion rates and length error compared to the other control strategies. In the two strategies in which users could employ simultaneous movements (conventional and simultaneous pattern recognition), amputees chose to use simultaneous movements 78% of the time with simultaneous pattern recognition and 64% of the time with conventional control for tasks that required two DOF motions to reach the target. These results suggest that when amputees are given the ability to control multiple DOFs simultaneously, they choose to perform tasks that utilize multiple DOFs with simultaneous movements. Additionally, they were able to perform these tasks with higher performance (faster speed, lower length error and higher completion rates) without losing substantial performance in 1 DOF tasks. PMID:24410948

Recognition of Double Stranded RNA by Guanidine-Modified Peptide Nucleic Acids (GPNA)

PubMed Central

Gupta, Pankaj; Muse, Oluwatoyosi; Rozners, Eriks

2011-01-01

Double helical RNA has become an attractive target for molecular recognition because many non-coding RNAs play important roles in control of gene expression. Recently, we discovered that short peptide nucleic acids (PNA) bind strongly and sequence selectively to a homopurine tract of double helical RNA via triple helix formation. Herein we tested if the molecular recognition of RNA can be enhanced by α-guanidine modification of PNA. Our study was motivated by the discovery of Ly and co-workers that the guanidine modification greatly enhances the cellular delivery of PNA. Isothermal titration calorimetry showed that the guanidine-modified PNA (GPNA) had reduced affinity and sequence selectivity for triple helical recognition of RNA. The data suggested that in contrast to unmodified PNA, which formed a 1:1 PNA-RNA triple helix, GPNA preferred a 2:1 GPNA-RNA triplex-invasion complex. Nevertheless, promising results were obtained for recognition of biologically relevant double helical RNA. Consistent with enhanced strand invasion ability, GPNA derived from D-arginine recognized the transactivation response element (TAR) of HIV-1 with high affinity and sequence selectivity, presumably via Watson-Crick duplex formation. On the other hand, strong and sequence selective triple helices were formed by unmodified and nucelobase-modified PNAs and the purine rich strand of bacterial A-site. These results suggest that appropriate chemical modifications of PNA may enhance molecular recognition of complex non-coding RNAs. PMID:22146072

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

Behavioral and Single-Neuron Sensitivity to Millisecond Variations in Temporally Patterned Communication Signals

PubMed Central

Baker, Christa A.; Ma, Lisa; Casareale, Chelsea R.

2016-01-01

In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8–12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. SIGNIFICANCE STATEMENT The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. PMID:27559179

Behavioral and Single-Neuron Sensitivity to Millisecond Variations in Temporally Patterned Communication Signals.

PubMed

Baker, Christa A; Ma, Lisa; Casareale, Chelsea R; Carlson, Bruce A

2016-08-24

In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8-12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. Copyright © 2016 the authors 0270-6474/16/368985-16$15.00/0.

Discovery of multi-ring basins - Gestalt perception in planetary science

NASA Technical Reports Server (NTRS)

Hartmann, W. K.

1981-01-01

Early selenographers resolved individual structural components of multi-ring basin systems but missed the underlying large-scale multi-ring basin patterns. The recognition of multi-ring basins as a general class of planetary features can be divided into five steps. Gilbert (1893) took a first step in recognizing radial 'sculpture' around the Imbrium basin system. Several writers through the 1940's rediscovered the radial sculpture and extended this concept by describing concentric rings around several circular maria. Some reminiscences are given about the fourth step - discovery of the Orientale basin and other basin systems by rectified lunar photography at the University of Arizona in 1961-62. Multi-ring basins remained a lunar phenomenon until the fifth step - discovery of similar systems of features on other planets, such as Mars (1972), Mercury (1974), and possibly Callisto and Ganymede (1979). This sequence is an example of gestalt recognition whose implications for scientific research are discussed.

Recent high-energy marine events in the sediments of Lagoa de Óbidos and Martinhal (Portugal): recognition, age and likely causes

NASA Astrophysics Data System (ADS)

Costa, P. J. M.; Leroy, S. A. G.; Dinis, J. L.; Dawson, A. G.; Kortekaas, S.

2012-05-01

A key issue in coastal hazards research is the need to distinguish sediments deposited by past extreme storms from those of past tsunamis. This study contributes to this aim by investigating patterns of sedimentation associated with extreme coastal flood events, in particular, within the Lagoa de Óbidos (Portugal). The recent stratigraphy of this coastal lagoon was studied using a wide range of techniques including visual description, grain-size analysis, digital and x-ray photography, magnetic susceptibility and geochemical analysis. The sequence was dated by 14C, 210Pb and Optically Stimulated Luminescence. Results disclose a distinctive coarser sedimentary unit, within the top of the sequence studied, and shown in quartz sand by the enrichment of elements with marine affinity (e.g., Ca and Na) and carbonates. The unit fines upwards and inland, thins inland and presents a sharp erosive basal contact. A noticeable post-event change in the sedimentary pattern was observed. The likely agent of sedimentation is discussed here and the conceivable association with the Great Lisbon tsunami of AD 1755 is debated, while a comparison is attempted with a possibly synchronous deposit from a tsunami in Martinhal (Algarve, Portugal). The possibility of a storm origin is also discussed in the context of the storminess of the western Portuguese coast and the North Atlantic Oscillation. This study highlights certain characteristics of the sedimentology of the deposits that may have a value in the recognition of extreme marine inundation signatures elsewhere in the world.

Correlation Time of Ocean Ambient Noise Intensity in San Diego Bay and Target Recognition in Acoustic Daylight Images

NASA Astrophysics Data System (ADS)

Wadsworth, Adam J.

A method for passively detecting and imaging underwater targets using ambient noise as the sole source of illumination (named acoustic daylight) was successfully implemented in the form of the Acoustic Daylight Ocean Noise Imaging System (ADONIS). In a series of imaging experiments conducted in San Diego Bay, where the dominant source of high-frequency ambient noise is snapping shrimp, a large quantity of ambient noise intensity data was collected with the ADONIS (Epifanio, 1997). In a subset of the experimental data sets, fluctuations of time-averaged ambient noise intensity exhibited a diurnal pattern consistent with the increase in frequency of shrimp snapping near dawn and dusk. The same subset of experimental data is revisited here and the correlation time is estimated and analysed for sequences of ambient noise data several minutes in length, with the aim of detecting possible periodicities or other trends in the fluctuation of the shrimp-dominated ambient noise field. Using videos formed from sequences of acoustic daylight images along with other experimental information, candidate segments of static-configuration ADONIS raw ambient noise data were isolated. For each segment, the normalized intensity auto-correlation closely resembled the delta function, the auto-correlation of white noise. No intensity fluctuation patterns at timescales smaller than a few minutes were discernible, suggesting that the shrimp do not communicate, synchronise, or exhibit any periodicities in their snapping. Also presented here is a ADONIS-specific target recognition algorithm based on principal component analysis, along with basic experimental results using a database of acoustic daylight images.

Profiles of cognitive dysfunction in chronic amphetamine and heroin abusers.

PubMed

Ornstein, T J; Iddon, J L; Baldacchino, A M; Sahakian, B J; London, M; Everitt, B J; Robbins, T W

2000-08-01

Groups of subjects whose primary drug of abuse was amphetamine or heroin were compared, together with age- and IQ-matched control subjects. The study consisted of a neuropsychological test battery which included both conventional tests and also computerised tests of recognition memory, spatial working memory, planning, sequence generation, visual discrimination learning, and attentional set-shifting. Many of these tests have previously been shown to be sensitive to cortical damage (including selective lesions of the temporal or frontal lobes) and to cognitive deficits in dementia, basal ganglia disease, and neuropsychiatric disorder. Qualitative differences, as well as some commonalities, were found in the profile of cognitive impairment between the two groups. The chronic amphetamine abusers were significantly impaired in performance on the extra-dimensional shift task (a core component of the Wisconsin Card Sort Test) whereas in contrast, the heroin abusers were impaired in learning the normally easier intra-dimensional shift component. Both groups were impaired in some of tests of spatial working memory. However, the amphetamine group, unlike the heroin group, were not deficient in an index of strategic performance on this test. The heroin group failed to show significant improvement between two blocks of a sequence generation task after training and additionally exhibited more perseverative behavior on this task. The two groups were profoundly, but equivalently impaired on a test of pattern recognition memory sensitive to temporal lobe dysfunction. These results indicate that chronic drug use may lead to distinct patterns of cognitive impairment that may be associated with dysfunction of different components of cortico-striatal circuitry.

Test Sequence Priming in Recognition Memory

ERIC Educational Resources Information Center

Johns, Elizabeth E.; Mewhort, D. J. K.

2009-01-01

The authors examined priming within the test sequence in 3 recognition memory experiments. A probe primed its successor whenever both probes shared a feature with the same studied item ("interjacent priming"), indicating that the study item like the probe is central to the decision. Interjacent priming occurred even when the 2 probes did…

On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

NASA Astrophysics Data System (ADS)

Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Insight into Buffalo (Bubalus bubalis) RIG1 and MDA5 Receptors: A Comparative Study on dsRNA Recognition and In-Vitro Antiviral Response

PubMed Central

Singh, Manvender; Brahma, Biswajit; Maharana, Jitendra; Patra, Mahesh Chandra; Kumar, Sushil; Mishra, Purusottam; Saini, Megha; De, Bidhan Chandra; Mahanty, Sourav; Datta, Tirtha Kumar; De, Sachinandan

2014-01-01

RIG1 and MDA5 have emerged as important intracellular innate pattern recognition receptors that recognize viral RNA and mediate cellular signals controlling Type I interferon (IFN-I) response. Buffalo RIG1 and MDA5 genes were investigated to understand the mechanism of receptor induced antiviral response. Sequence analysis revealed that RIG1 and MDA5 maintain a domain arrangement that is common in mammals. Critical binding site residues of the receptors are evolutionary conserved among mammals. Molecular dynamics simulations suggested that RIG1 and MDA5 follow a similar, if not identical, dsRNA binding pattern that has been previously reported in human. Moreover, binding free energy calculation revealed that MDA5 had a greater affinity towards dsRNA compared to RIG1. Constitutive expressions of RLR genes were ubiquitous in different tissues without being specific to immune organs. Poly I:C stimulation induced elevated expressions of IFN-β and IFN-stimulated genes (ISGs) through interferon regulatory factors (IRFs) mediated pathway in buffalo foetal fibroblast cells. The present study provides crucial insights into the structure and function of RIG1 and MDA5 receptors in buffalo. PMID:24587036

Bioinformatics analysis identifies several intrinsically disordered human E3 ubiquitin-protein ligases.

PubMed

Boomsma, Wouter; Nielsen, Sofie V; Lindorff-Larsen, Kresten; Hartmann-Petersen, Rasmus; Ellgaard, Lars

2016-01-01

The ubiquitin-proteasome system targets misfolded proteins for degradation. Since the accumulation of such proteins is potentially harmful for the cell, their prompt removal is important. E3 ubiquitin-protein ligases mediate substrate ubiquitination by bringing together the substrate with an E2 ubiquitin-conjugating enzyme, which transfers ubiquitin to the substrate. For misfolded proteins, substrate recognition is generally delegated to molecular chaperones that subsequently interact with specific E3 ligases. An important exception is San1, a yeast E3 ligase. San1 harbors extensive regions of intrinsic disorder, which provide both conformational flexibility and sites for direct recognition of misfolded targets of vastly different conformations. So far, no mammalian ortholog of San1 is known, nor is it clear whether other E3 ligases utilize disordered regions for substrate recognition. Here, we conduct a bioinformatics analysis to examine >600 human and S. cerevisiae E3 ligases to identify enzymes that are similar to San1 in terms of function and/or mechanism of substrate recognition. An initial sequence-based database search was found to detect candidates primarily based on the homology of their ordered regions, and did not capture the unique disorder patterns that encode the functional mechanism of San1. However, by searching specifically for key features of the San1 sequence, such as long regions of intrinsic disorder embedded with short stretches predicted to be suitable for substrate interaction, we identified several E3 ligases with these characteristics. Our initial analysis revealed that another remarkable trait of San1 is shared with several candidate E3 ligases: long stretches of complete lysine suppression, which in San1 limits auto-ubiquitination. We encode these characteristic features into a San1 similarity-score, and present a set of proteins that are plausible candidates as San1 counterparts in humans. In conclusion, our work indicates that San1 is not a unique case, and that several other yeast and human E3 ligases have sequence properties that may allow them to recognize substrates by a similar mechanism as San1.

Pattern-Recognition System for Approaching a Known Target

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Cheng, Yang

2008-01-01

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the lander.

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

33 CFR 106.215 - Company or OCS facility personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... appropriate: (a) Knowledge of current and anticipated security threats and patterns. (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Recognition of techniques used to circumvent security...

33 CFR 106.215 - Company or OCS facility personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... appropriate: (a) Knowledge of current and anticipated security threats and patterns. (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Recognition of techniques used to circumvent security...

Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

NASA Astrophysics Data System (ADS)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

PubMed

Gruel, Jérémy; LeBorgne, Michel; LeMeur, Nolwenn; Théret, Nathalie

2011-09-12

Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns

PubMed Central

2011-01-01

Background Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Results Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Conclusions Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks. PMID:21910886

Shallowing-upward cyclic patterns within larger-scale transgressive-regressive (T-R) sedimentary sequences, St. Peter through Decorah Formations, Ordovician, Iowa area

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

Witzke, B.J.

1993-03-01

Four large-scale (2--8 Ma) T-R sedimentary sequences of M. Ord. age (late Chaz.-Sherm.) were delimited by Witzke Kolata (1980) in the Iowa area, each bounded by local to regional unconformity/disconformity surfaces. These encompass both siliciclastic and carbonate intervals, in ascending order: (1) St. Peter-Glenwood fms., (2) Platteville Fm., (3) Decorah Fm., (4) Dunleith/upper Decorah fms. Finer-scale resolution of depth-related depositional features has led to regional recognition of smaller-scale shallowing-upward cyclicity contained within each large-scale sequence. Such smaller-scale cyclicity encompasses stratigraphic intervals of 1--10 m thickness, with estimated durations of 0.5--1.5 Ma. The St. Peter Sandst. has long been regarded asmore » a classic transgressive sheet sand. However, four discrete shallowing-upward packages characterize the St. Peter-Glenwood interval regionally (IA, MN, NB, KS), including western facies displaying coarsening-upward sandstone packages with condensed conodont-rich brown shale and phosphatic sediments in their lower part (local oolitic ironstone), commonly above pyritic hardgrounds. Regional continuity of small-scale cyclic patterns in M. Ord. strata of the Iowa area may suggest eustatic controls; this can be tested through inter-regional comparisons.« less

Quantification of DNA cleavage specificity in Hi-C experiments.

PubMed

Meluzzi, Dario; Arya, Gaurav

2016-01-08

Hi-C experiments produce large numbers of DNA sequence read pairs that are typically analyzed to deduce genomewide interactions between arbitrary loci. A key step in these experiments is the cleavage of cross-linked chromatin with a restriction endonuclease. Although this cleavage should happen specifically at the enzyme's recognition sequence, an unknown proportion of cleavage events may involve other sequences, owing to the enzyme's star activity or to random DNA breakage. A quantitative estimation of these non-specific cleavages may enable simulating realistic Hi-C read pairs for validation of downstream analyses, monitoring the reproducibility of experimental conditions and investigating biophysical properties that correlate with DNA cleavage patterns. Here we describe a computational method for analyzing Hi-C read pairs to estimate the fractions of cleavages at different possible targets. The method relies on expressing an observed local target distribution downstream of aligned reads as a linear combination of known conditional local target distributions. We validated this method using Hi-C read pairs obtained by computer simulation. Application of the method to experimental Hi-C datasets from murine cells revealed interesting similarities and differences in patterns of cleavage across the various experiments considered. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Molecular cloning and characterization of a C-type lectin in roughskin sculpin (Trachidermus fasciatus).

PubMed

Yu, Shanshan; Yang, Hui; Chai, Yingmei; Liu, Yingying; Zhang, Qiuxia; Ding, Xinbiao; Zhu, Qian

2013-02-01

C-type lectins, as the members of pattern-recognition receptors (PRRs), play significant roles in innate immunity responses through binding to the pathogen-associated molecular patterns (PAMPs) presented on surfaces of microorganisms. In our study, a C-type lectin gene (TfCTL1) was cloned from the roughskin sculpin using expression sequence tag (EST) and rapid amplification of cDNA ends (RACE) techniques. The full-length of TfCTL1 was 696 bp, consisting of a 95 bp 5' untranslated region (UTR), a 498 bp open reading frame (ORF) encoding a 165 amino acid protein, and a 103 bp 3' UTR with a polyadenylation signal sequence AATAAA and a poly(A) tail. The deduced amino acid sequence of TfCTL1 contained a signal peptide and a single carbohydrate recognition domain (CRD) which had four conserved disulfide-bonded cysteine residues (Cys(61)-Cys(158), Cys(134)-Cys(150)) and a Ca(2+)/carbohydrate-binding site (QPD motif). Results from the qRT-PCR indicated that TfCTL1 mRNA was predominately expressed in the liver. The temporal expression of TfCTL1 was obviously up-regulated in the skin, blood, spleen and heart in time dependent manners by lipopolysaccharide (LPS) challenge, whereas in the liver, TfCTL1 was initially down-regulated from 2 h to 48 h followed by an abrupt up-regulation at 72 h. Recombinant TfCTL1 CRD purified from Escherichia coli BL21 was able to agglutinate some Gram-positive bacteria, Gram-negative bacteria and a yeast in a Ca(2+)-dependent manner. Further analysis showed that TfCTL1 can bind to several kinds of microorganisms selectively in a Ca(2+)-independent manner. These results suggested that TfCTL1 might be involved in the innate response as a PRR. Copyright © 2012 Elsevier Ltd. All rights reserved.

Preservation Obscures Pelagic Deep-Sea Fish Diversity: Doubling the Number of Sole-Bearing Opisthoproctids and Resurrection of the Genus Monacoa (Opisthoproctidae, Argentiniformes)

PubMed Central

Sado, Tetsuya; Hahn, Christoph; Byrkjedal, Ingvar; Miya, Masaki

2016-01-01

The family Opisthoproctidae (barreleyes) constitutes one of the most peculiar looking and unknown deep-sea fish groups in terms of taxonomy and specialized adaptations. All the species in the family are united by the possession of tubular eyes, with one distinct lineage exhibiting also drastic shortening of the body. Two new species of the mesopelagic opisthoproctid mirrorbelly genus Monacoa are described based on pigmentation patterns of the “sole”—a unique vertebrate structure used in the reflection and control of bioluminescence in most short-bodied forms. Different pigmentation patterns of the soles, previously noted as intraspecific variations based on preserved specimens, are here shown species-specific and likely used for communication in addition to counter-illumination of down-welling sunlight. The genus Monacoa is resurrected from Opisthoproctus based on extensive morphological synaphomorphies pertaining to the anal fin and snout. Doubling the species diversity within sole-bearing opisthoproctids, including recognition of two genera, is unambiguously supported by mitogenomic DNA sequence data. Regular fixation with formalin and alcohol preservation is shown problematic concerning the retention of species-specific pigmentation patterns. Examination or photos of fresh material before formalin fixation is shown paramount for correct species recognition of sole-bearing opisthoproctids—a relatively unknown issue concerning species diversity in the deep-sea pelagic realm. PMID:27508419

Research on gait-based human identification

NASA Astrophysics Data System (ADS)

Li, Youguo

Gait recognition refers to automatic identification of individual based on his/her style of walking. This paper proposes a gait recognition method based on Continuous Hidden Markov Model with Mixture of Gaussians(G-CHMM). First, we initialize a Gaussian mix model for training image sequence with K-means algorithm, then train the HMM parameters using a Baum-Welch algorithm. These gait feature sequences can be trained and obtain a Continuous HMM for every person, therefore, the 7 key frames and the obtained HMM can represent each person's gait sequence. Finally, the recognition is achieved by Front algorithm. The experiments made on CASIA gait databases obtain comparatively high correction identification ratio and comparatively strong robustness for variety of bodily angle.

Research and Implementation of Tibetan Word Segmentation Based on Syllable Methods

NASA Astrophysics Data System (ADS)

Jiang, Jing; Li, Yachao; Jiang, Tao; Yu, Hongzhi

2018-03-01

Tibetan word segmentation (TWS) is an important problem in Tibetan information processing, while abbreviated word recognition is one of the key and most difficult problems in TWS. Most of the existing methods of Tibetan abbreviated word recognition are rule-based approaches, which need vocabulary support. In this paper, we propose a method based on sequence tagging model for abbreviated word recognition, and then implement in TWS systems with sequence labeling models. The experimental results show that our abbreviated word recognition method is fast and effective and can be combined easily with the segmentation model. This significantly increases the effect of the Tibetan word segmentation.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

NASA Astrophysics Data System (ADS)

Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

2017-01-01

In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

Deep Recurrent Neural Networks for Human Activity Recognition

PubMed Central

Murad, Abdulmajid

2017-01-01

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs. PMID:29113103

Deep Recurrent Neural Networks for Human Activity Recognition.

PubMed

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

ICPR-2016 - International Conference on Pattern Recognition

Science.gov Websites

Learning for Scene Understanding" Speakers ICPR2016 PAPER AWARDS Best Piero Zamperoni Student Paper -Paced Dictionary Learning for Cross-Domain Retrieval and Recognition Xu, Dan; Song, Jingkuan; Alameda discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and

The Spatial Vision Tree: A Generic Pattern Recognition Engine- Scientific Foundations, Design Principles, and Preliminary Tree Design

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2010-01-01

New foundational ideas are used to define a novel approach to generic visual pattern recognition. These ideas proceed from the starting point of the intrinsic equivalence of noise reduction and pattern recognition when noise reduction is taken to its theoretical limit of explicit matched filtering. This led us to think of the logical extension of sparse coding using basis function transforms for both de-noising and pattern recognition to the full pattern specificity of a lexicon of matched filter pattern templates. A key hypothesis is that such a lexicon can be constructed and is, in fact, a generic visual alphabet of spatial vision. Hence it provides a tractable solution for the design of a generic pattern recognition engine. Here we present the key scientific ideas, the basic design principles which emerge from these ideas, and a preliminary design of the Spatial Vision Tree (SVT). The latter is based upon a cryptographic approach whereby we measure a large aggregate estimate of the frequency of occurrence (FOO) for each pattern. These distributions are employed together with Hamming distance criteria to design a two-tier tree. Then using information theory, these same FOO distributions are used to define a precise method for pattern representation. Finally the experimental performance of the preliminary SVT on computer generated test images and complex natural images is assessed.

Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

NASA Astrophysics Data System (ADS)

Yevin, Igor; Koblyakov, Alexander

The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

Computer discrimination procedures applicable to aerial and ERTS multispectral data

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Torline, R. J.; Allen, W. A.

1970-01-01

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

2014-09-01

In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

Detection of possible restriction sites for type II restriction enzymes in DNA sequences.

PubMed

Gagniuc, P; Cimponeriu, D; Ionescu-Tîrgovişte, C; Mihai, Andrada; Stavarachi, Monica; Mihai, T; Gavrilă, L

2011-01-01

In order to make a step forward in the knowledge of the mechanism operating in complex polygenic disorders such as diabetes and obesity, this paper proposes a new algorithm (PRSD -possible restriction site detection) and its implementation in Applied Genetics software. This software can be used for in silico detection of potential (hidden) recognition sites for endonucleases and for nucleotide repeats identification. The recognition sites for endonucleases may result from hidden sequences through deletion or insertion of a specific number of nucleotides. Tests were conducted on DNA sequences downloaded from NCBI servers using specific recognition sites for common type II restriction enzymes introduced in the software database (n = 126). Each possible recognition site indicated by the PRSD algorithm implemented in Applied Genetics was checked and confirmed by NEBcutter V2.0 and Webcutter 2.0 software. In the sequence NG_008724.1 (which includes 63632 nucleotides) we found a high number of potential restriction sites for ECO R1 that may be produced by deletion (n = 43 sites) or insertion (n = 591 sites) of one nucleotide. The second module of Applied Genetics has been designed to find simple repeats sizes with a real future in understanding the role of SNPs (Single Nucleotide Polymorphisms) in the pathogenesis of the complex metabolic disorders. We have tested the presence of simple repetitive sequences in five DNA sequence. The software indicated exact position of each repeats detected in the tested sequences. Future development of Applied Genetics can provide an alternative for powerful tools used to search for restriction sites or repetitive sequences or to improve genotyping methods.

A 21.7 kb DNA segment on the left arm of yeast chromosome XIV carries WHI3, GCR2, SPX18, SPX19, an homologue to the heat shock gene SSB1 and 8 new open reading frames of unknown function.

PubMed

Jonniaux, J L; Coster, F; Purnelle, B; Goffeau, A

1994-12-01

We report the amino acid sequence of 13 open reading frames (ORF > 299 bp) located on a 21.7 kb DNA segment from the left arm of chromosome XIV of Saccharomyces cerevisiae. Five open reading frames had been entirely or partially sequenced previously: WHI3, GCR2, SPX19, SPX18 and a heat shock gene similar to SSB1. The products of 8 other ORFs are new putative proteins among which N1394 is probably a membrane protein. N1346 contains a leucine zipper pattern and the corresponding ORF presents an HAP (global regulator of respiratory genes) upstream activating sequence in the promoting region. N1386 shares homologies with the DNA structure-specific recognition protein family SSRPs and the corresponding ORF is preceded by an MCB (MluI cell cycle box) upstream activating factor.

Crosslinking transcription factors to their recognition sequences with PtII complexes

NASA Technical Reports Server (NTRS)

Chu, B. C.; Orgel, L. E.

1992-01-01

We have prepared phosphorothioate-containing cyclic oligodeoxynucleotides that fold into 'dumbbells' containing CRE and TRE sequences, the binding sequences for the CREB and JUN proteins, respectively. Six phosphorothioate residues were introduced into each of the recognition sequences. K2PtCl4 crosslinks CRE to CREB and TRE to JUN. The extent of crosslinking is about eight times greater than that observed with standard oligodeoxynucleotides and amounts to 30-50% of the efficiency of non-covalent association as estimated by gel-shift assays. Crosslinking is reversed by incubation with NaCN. The crosslinking reaction is specific--a dumbbell oligonucleotide with six phosphorothioate groups introduced into the Sp1 recognition sequence could not be crosslinked efficiently to CREB or JUN proteins with K2PtCl4. The binding of TRE to CREB is not strong enough for effective detection by gel-shift assays, but the TRE-CREB complex is crosslinked efficiently by K2PtCl4 and can then readily be detected.

Extrinsic finger and thumb muscles command a virtual hand to allow individual finger and grasp control.

PubMed

Birdwell, J Alexander; Hargrove, Levi J; Weir, Richard F ff; Kuiken, Todd A

2015-01-01

Fine-wire intramuscular electrodes were used to obtain electromyogram (EMG) signals from six extrinsic hand muscles associated with the thumb, index, and middle fingers. Subjects' EMG activity was used to control a virtual three-degree-of-freedom (DOF) hand as they conformed the hand to a sequence of hand postures testing two controllers: direct EMG control and pattern recognition control. Subjects tested two conditions using each controller: starting the hand from a predefined neutral posture before each new posture and starting the hand from the previous posture in the sequence. Subjects demonstrated their abilities to simultaneously, yet individually, move all three DOFs during the direct EMG control trials; however, results showed subjects did not often utilize this feature. Performance metrics such as failure rate and completion time showed no significant difference between the two controllers.

Toxins of Prokaryotic Toxin-Antitoxin Systems with Sequence-Specific Endoribonuclease Activity

PubMed Central

Masuda, Hisako; Inouye, Masayori

2017-01-01

Protein translation is the most common target of toxin-antitoxin system (TA) toxins. Sequence-specific endoribonucleases digest RNA in a sequence-specific manner, thereby blocking translation. While past studies mainly focused on the digestion of mRNA, recent analysis revealed that toxins can also digest tRNA, rRNA and tmRNA. Purified toxins can digest single-stranded portions of RNA containing recognition sequences in the absence of ribosome in vitro. However, increasing evidence suggests that in vivo digestion may occur in association with ribosomes. Despite the prevalence of recognition sequences in many mRNA, preferential digestion seems to occur at specific positions within mRNA and also in certain reading frames. In this review, a variety of tools utilized to study the nuclease activities of toxins over the past 15 years will be reviewed. A recent adaptation of an RNA-seq-based technique to analyze entire sets of cellular RNA will be introduced with an emphasis on its strength in identifying novel targets and redefining recognition sequences. The differences in biochemical properties and postulated physiological roles will also be discussed. PMID:28420090

Pattern association--a key to recognition of shark attacks.

PubMed

Cirillo, G; James, H

2004-12-01

Investigation of a number of shark attacks in South Australian waters has lead to recognition of pattern similarities on equipment recovered from the scene of such attacks. Six cases are presented in which a common pattern of striations has been noted.

Recognition vs Reverse Engineering in Boolean Concepts Learning

ERIC Educational Resources Information Center

Shafat, Gabriel; Levin, Ilya

2012-01-01

This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Finger vein recognition based on personalized weight maps.

PubMed

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-09-10

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Finger Vein Recognition Based on Personalized Weight Maps

PubMed Central

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-01-01

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition. PMID:24025556

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.

PubMed

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-22

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

PubMed Central

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-01-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

NASA Astrophysics Data System (ADS)

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

A bottom-up model of spatial attention predicts human error patterns in rapid scene recognition.

PubMed

Einhäuser, Wolfgang; Mundhenk, T Nathan; Baldi, Pierre; Koch, Christof; Itti, Laurent

2007-07-20

Humans demonstrate a peculiar ability to detect complex targets in rapidly presented natural scenes. Recent studies suggest that (nearly) no focal attention is required for overall performance in such tasks. Little is known, however, of how detection performance varies from trial to trial and which stages in the processing hierarchy limit performance: bottom-up visual processing (attentional selection and/or recognition) or top-down factors (e.g., decision-making, memory, or alertness fluctuations)? To investigate the relative contribution of these factors, eight human observers performed an animal detection task in natural scenes presented at 20 Hz. Trial-by-trial performance was highly consistent across observers, far exceeding the prediction of independent errors. This consistency demonstrates that performance is not primarily limited by idiosyncratic factors but by visual processing. Two statistical stimulus properties, contrast variation in the target image and the information-theoretical measure of "surprise" in adjacent images, predict performance on a trial-by-trial basis. These measures are tightly related to spatial attention, demonstrating that spatial attention and rapid target detection share common mechanisms. To isolate the causal contribution of the surprise measure, eight additional observers performed the animal detection task in sequences that were reordered versions of those all subjects had correctly recognized in the first experiment. Reordering increased surprise before and/or after the target while keeping the target and distractors themselves unchanged. Surprise enhancement impaired target detection in all observers. Consequently, and contrary to several previously published findings, our results demonstrate that attentional limitations, rather than target recognition alone, affect the detection of targets in rapidly presented visual sequences.

Homing endonucleases: from basics to therapeutic applications.

PubMed

Marcaida, Maria J; Muñoz, Inés G; Blanco, Francisco J; Prieto, Jesús; Montoya, Guillermo

2010-03-01

Homing endonucleases (HE) are double-stranded DNAses that target large recognition sites (12-40 bp). HE-encoding sequences are usually embedded in either introns or inteins. Their recognition sites are extremely rare, with none or only a few of these sites present in a mammalian-sized genome. However, these enzymes, unlike standard restriction endonucleases, tolerate some sequence degeneracy within their recognition sequence. Several members of this enzyme family have been used as templates to engineer tools to cleave DNA sequences that differ from their original wild-type targets. These custom HEs can be used to stimulate double-strand break homologous recombination in cells, to induce the repair of defective genes with very low toxicity levels. The use of tailored HEs opens up new possibilities for gene therapy in patients with monogenic diseases that can be treated ex vivo. This review provides an overview of recent advances in this field.

Implementation and Sequencing of Practice Transformation in Urban Practices with Underserved Patients.

PubMed

Quigley, Denise D; Predmore, Zachary S; Chen, Alex Y; Hays, Ron D

Patient-centered medical home (PCMH) has gained momentum as a model for primary-care health services reform. We conducted interviews at 14 primary care practices undergoing PCMH transformation in a large urban federally qualified health center in California and used grounded theory to identify common themes and patterns. We found clinics pursued a common sequence of changes in PCMH transformation: Clinics began with National Committee for Quality Assurance (NCQA) level 3 recognition, adding care coordination staff, reorganizing data flow among teams, and integrating with a centralized quality improvement and accountability infrastructure. Next, they realigned to support continuity of care. Then, clinics improved access by adding urgent care, patient portals, or extending hours. Most then improved planning and management of patient visits. Only a handful worked explicitly on improving access with same day slots, scheduling processes, and test result communication. The clinics' changes align with specific NCQA PCMH standards but also include adding physicians and services, culture changes, and improved communication with patients. NCQA PCMH level 3 recognition is only the beginning of a continuous improvement process to become patient centered. Full PCMH transformation took time and effort and relied on a sequential approach, with an early focus on foundational changes that included use of a robust quality improvement strategy before changes to delivery of and access to care.

A bacterial tyrosine phosphatase inhibits plant pattern recognition receptor activation

USDA-ARS?s Scientific Manuscript database

Perception of pathogen-associated molecular patterns (PAMPs) by surface-localised pattern-recognition receptors (PRRs) is a key component of plant innate immunity. Most known plant PRRs are receptor kinases and initiation of PAMP-triggered immunity (PTI) signalling requires phosphorylation of the PR...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (xi...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (xi...

Infrared face recognition based on LBP histogram and KW feature selection

NASA Astrophysics Data System (ADS)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.

Optical Pattern Recognition for Missile Guidance.

DTIC Science & Technology

1982-11-15

directed to novel pattern recognition algo- rithms (that allow pattern recognition and object classification in the face of various geometrical and...I wats EF5 = 50) p.j/t’ni 2 (for btith image pat tern recognitio itas a preproicessing oiperatiton. Ini devices). TIhe rt’ad light intensity (0.33t mW...electrodes on its large faces . This Priz light modulator and the motivation for its devel- SLM is known as the Prom (Pockels real-time optical opment. In Sec

Individual differences in language and working memory affect children's speech recognition in noise.

PubMed

McCreery, Ryan W; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc

2017-05-01

We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Ninety-six children with normal hearing, who were between 5 and 12 years of age. Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Working memory and language both influence children's speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child's auditory skills, consistent with the Ease of Language Understanding model.

Recognition as Support for Reasoning about Horizontal Motion: A Further Resource for School Science?

ERIC Educational Resources Information Center

Howe, Christine; Taylor Tavares, Joana; Devine, Amy

2016-01-01

Background: Even infants can recognize whether patterns of motion are or are not natural, yet an acknowledged challenge for science education is to promote adequate reasoning about such patterns. Since research indicates linkage between the conceptual bases of recognition and reasoning, it seems possible that recognition can be engaged to support…

Enantiospecific recognition of DNA sequences by a proflavine Tröger base.

PubMed

Bailly, C; Laine, W; Demeunynck, M; Lhomme, J

2000-07-05

The DNA interaction of a chiral Tröger base derived from proflavine was investigated by DNA melting temperature measurements and complementary biochemical assays. DNase I footprinting experiments demonstrate that the binding of the proflavine-based Tröger base is both enantio- and sequence-specific. The (+)-isomer poorly interacts with DNA in a non-sequence-selective fashion. In sharp contrast, the corresponding (-)-isomer recognizes preferentially certain DNA sequences containing both A. T and G. C base pairs, such as the motifs 5'-GTT. AAC and 5'-ATGA. TCAT. This is the first experimental demonstration that acridine-type Tröger bases can be used for enantiospecific recognition of DNA sequences. Copyright 2000 Academic Press.

33 CFR 105.210 - Facility personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

...: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely...

33 CFR 105.210 - Facility personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

...: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely...

A promoter recognition mechanism common to yeast mitochondrial and phage t7 RNA polymerases.

PubMed

Nayak, Dhananjaya; Guo, Qing; Sousa, Rui

2009-05-15

Yeast mitochondrial (YMt) and phage T7 RNA polymerases (RNAPs) are two divergent representatives of a large family of single subunit RNAPs that are also found in the mitochondria and chloroplasts of higher eukaryotes, mammalian nuclei, and many other bacteriophage. YMt and phage T7 promoters differ greatly in sequence and length, and the YMt RNAP uses an accessory factor for initiation, whereas T7 RNAP does not. We obtain evidence here that, despite these apparent differences, both the YMt and T7 RNAPs utilize a similar promoter recognition loop to bind their respective promoters. Mutations in this element in YMt RNAP specifically disrupt mitochondrial promoter utilization, and experiments with site-specifically tethered chemical nucleases indicate that this element binds the mitochondrial promoter almost identically to how the promoter recognition loop from the phage RNAP binds its promoter. Sequence comparisons reveal that the other members of the single subunit RNAP family display loops of variable sequence and size at a position corresponding to the YMt and T7 RNAP promoter recognition loops. We speculate that these elements may be involved in promoter recognition in most or all of these enzymes and that this element's structure allows it to accommodate significant sequence and length variation to provide a mechanism for rapid evolution of new promoter specificities in this RNAP family.

An iris recognition algorithm based on DCT and GLCM

NASA Astrophysics Data System (ADS)

Feng, G.; Wu, Ye-qing

2008-04-01

With the enlargement of mankind's activity range, the significance for person's status identity is becoming more and more important. So many different techniques for person's status identity were proposed for this practical usage. Conventional person's status identity methods like password and identification card are not always reliable. A wide variety of biometrics has been developed for this challenge. Among those biologic characteristics, iris pattern gains increasing attention for its stability, reliability, uniqueness, noninvasiveness and difficult to counterfeit. The distinct merits of the iris lead to its high reliability for personal identification. So the iris identification technique had become hot research point in the past several years. This paper presents an efficient algorithm for iris recognition using gray-level co-occurrence matrix(GLCM) and Discrete Cosine transform(DCT). To obtain more representative iris features, features from space and DCT transformation domain are extracted. Both GLCM and DCT are applied on the iris image to form the feature sequence in this paper. The combination of GLCM and DCT makes the iris feature more distinct. Upon GLCM and DCT the eigenvector of iris extracted, which reflects features of spatial transformation and frequency transformation. Experimental results show that the algorithm is effective and feasible with iris recognition.

DNA recognition by an RNA-guided bacterial Argonaute

PubMed Central

Doudna, Jennifer A.

2017-01-01

Argonaute (Ago) proteins are widespread in prokaryotes and eukaryotes and share a four-domain architecture capable of RNA- or DNA-guided nucleic acid recognition. Previous studies identified a prokaryotic Argonaute protein from the eubacterium Marinitoga piezophila (MpAgo), which binds preferentially to 5′-hydroxylated guide RNAs and cleaves single-stranded RNA (ssRNA) and DNA (ssDNA) targets. Here we present a 3.2 Å resolution crystal structure of MpAgo bound to a 21-nucleotide RNA guide and a complementary 21-nucleotide ssDNA substrate. Comparison of this ternary complex to other target-bound Argonaute structures reveals a unique orientation of the N-terminal domain, resulting in a straight helical axis of the entire RNA-DNA heteroduplex through the central cleft of the protein. Additionally, mismatches introduced into the heteroduplex reduce MpAgo cleavage efficiency with a symmetric profile centered around the middle of the helix. This pattern differs from the canonical mismatch tolerance of other Argonautes, which display decreased cleavage efficiency for substrates bearing sequence mismatches to the 5′ region of the guide strand. This structural analysis of MpAgo bound to a hybrid helix advances our understanding of the diversity of target recognition mechanisms by Argonaute proteins. PMID:28520746

A proposed technique for vehicle tracking, direction, and speed determination

NASA Astrophysics Data System (ADS)

Fisher, Paul S.; Angaye, Cleopas O.; Fisher, Howard P.

2004-12-01

A technique for recognition of vehicles in terms of direction, distance, and rate of change is presented. This represents very early work on this problem with significant hurdles still to be addressed. These are discussed in the paper. However, preliminary results also show promise for this technique for use in security and defense environments where the penetration of a perimeter is of concern. The material described herein indicates a process whereby the protection of a barrier could be augmented by computers and installed cameras assisting the individuals charged with this responsibility. The technique we employ is called Finite Inductive Sequences (FI) and is proposed as a means for eliminating data requiring storage and recognition where conventional mathematical models don"t eliminate enough and statistical models eliminate too much. FI is a simple idea and is based upon a symbol push-out technique that allows the order (inductive base) of the model to be set to an a priori value for all derived rules. The rules are obtained from exemplar data sets, and are derived by a technique called Factoring, yielding a table of rules called a Ruling. These rules can then be used in pattern recognition applications such as described in this paper.

New generation of human machine interfaces for controlling UAV through depth-based gesture recognition

NASA Astrophysics Data System (ADS)

Mantecón, Tomás.; del Blanco, Carlos Roberto; Jaureguizar, Fernando; García, Narciso

2014-06-01

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

Identification and molecular profiling of DC-SIGN-like from big belly seahorse (Hippocampus abdominalis) inferring its potential relevancy in host immunity.

PubMed

Jo, Eunyoung; Elvitigala, Don Anushka Sandaruwan; Wan, Qiang; Oh, Minyoung; Oh, Chulhong; Lee, Jehee

2017-12-01

Dendritic-cell-specific ICAM-3-grabbing non-integrin (DC-SIGN) is a C-type lectin that functions as a pattern recognition receptor by recognizing pathogen-associated molecular patterns (PAMPs). It is also involved in various events of the dendritic cell (DC) life cycle, such as DC migration, antigen capture and presentation, and T cell priming. In this study, a DC-SIGN-like gene from the big belly seahorse Hippocampus abdominalis (designated as ShDCS-like) was identified and molecularly characterized. The putative, complete ORF was found to be 1368 bp in length, encoding a protein of 462 amino acids with a molecular mass of 52.6 kDa and a theoretical isoelectric point of 8.26. The deduced amino acid sequence contains a single carbohydrate recognition domain (CRD), in which six conserved cysteine residues and two Ca 2+ -binding site motifs (QPN, WND) were identified. Based on pairwise sequence analysis, ShDCS-like exhibits the highest amino acid identity (94.6%) and similarity (97.4%) with DC-SIGN-like counterpart from tiger tail seahorse Hippocampus comes. Quantitative real-time PCR revealed that ShDCS-like mRNA is transcribed universally in all tissues examined, but with abundance in kidney and gill tissues. The basal mRNA expression of ShDCS-like was modulated in blood cell, kidney, gill and liver tissues in response to the stimulation of healthy fish with lipopolysaccharides (LPS), Edwardsiella tarda, or Streptococcus iniae. Moreover, recombinant ShDCS-like-CRD domain exhibited detectable agglutination activity against different bacteria. Collectively, these results suggest that ShDCS-like may potentially involve in immune function in big belly seahorses. Copyright © 2017 Elsevier Ltd. All rights reserved.

From The Cover: Induction of antiviral immunity requires Toll-like receptor signaling in both stromal and dendritic cell compartments

NASA Astrophysics Data System (ADS)

Sato, Ayuko; Iwasaki, Akiko

2004-11-01

Pattern recognition by Toll-like receptors (TLRs) is known to be important for the induction of dendritic cell (DC) maturation. DCs, in turn, are critically important in the initiation of T cell responses. However, most viruses do not infect DCs. This recognition system poses a biological problem in ensuring that most viral infections be detected by pattern recognition receptors. Furthermore, it is unknown what, if any, is the contribution of TLRs expressed by cells that are infected by a virus, versus TLRs expressed by DCs, in the initiation of antiviral adaptive immunity. Here we address these issues using a physiologically relevant model of mucosal infection with herpes simplex virus type 2. We demonstrate that innate immune recognition of viral infection occurs in two distinct stages, one at the level of the infected epithelial cells and the other at the level of the noninfected DCs. Importantly, both TLR-mediated recognition events are required for the induction of effector T cells. Our results demonstrate that virally infected tissues instruct DCs to initiate the appropriate class of effector T cell responses and reveal the critical importance of the stromal cells in detecting infectious agents through their own pattern recognition receptors. mucosal immunity | pattern recognition | viral infection

A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views.

PubMed

Chaaraoui, Alexandros Andre; Flórez-Revuelta, Francisco

2014-01-01

This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a learning algorithm that by means of model fusion of multiple camera streams builds a bag of key poses, which serves as a dictionary of known poses and allows converting the training sequences into sequences of key poses. These are used in order to perform action recognition by means of a sequence matching algorithm. Experimentation on three different datasets returns high and stable recognition rates. To the best of our knowledge, this paper presents the highest results so far on the MuHAVi-MAS dataset. Real-time suitability is given, since the method easily performs above video frequency. Therefore, the related requirements that applications as ambient-assisted living services impose are successfully fulfilled.

Repetition and lag effects in movement recognition.

PubMed

Hall, C R; Buckolz, E

1982-03-01

Whether repetition and lag improve the recognition of movement patterns was investigated. Recognition memory was tested for one repetition, two-repetitions massed, and two-repetitions distributed with movement patterns at lags of 3, 5, 7, and 13. Recognition performance was examined both immediately afterwards and following a 48 hour delay. Both repetition and lag effects failed to be demonstrated, providing some support for the claim that memory is unaffected by repetition at a constant level of processing (Craik & Lockhart, 1972). There was, as expected, a significant decrease in recognition memory following the retention interval, but this appeared unrelated to repetition or lag.

Dentate gyrus supports slope recognition memory, shades of grey-context pattern separation and recognition memory, and CA3 supports pattern completion for object memory.

PubMed

Kesner, Raymond P; Kirk, Ryan A; Yu, Zhenghui; Polansky, Caitlin; Musso, Nick D

2016-03-01

In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats displayed a significant interaction between the two groups and the number of available objects suggesting impairment in a pattern completion function for object cues. Copyright © 2015 Elsevier Inc. All rights reserved.

Misconceptions on Missing Data in RAD-seq Phylogenetics with a Deep-scale Example from Flowering Plants.

PubMed

Eaton, Deren A R; Spriggs, Elizabeth L; Park, Brian; Donoghue, Michael J

2017-05-01

Restriction-site associated DNA (RAD) sequencing and related methods rely on the conservation of enzyme recognition sites to isolate homologous DNA fragments for sequencing, with the consequence that mutations disrupting these sites lead to missing information. There is thus a clear expectation for how missing data should be distributed, with fewer loci recovered between more distantly related samples. This observation has led to a related expectation: that RAD-seq data are insufficiently informative for resolving deeper scale phylogenetic relationships. Here we investigate the relationship between missing information among samples at the tips of a tree and information at edges within it. We re-analyze and review the distribution of missing data across ten RAD-seq data sets and carry out simulations to determine expected patterns of missing information. We also present new empirical results for the angiosperm clade Viburnum (Adoxaceae, with a crown age >50 Ma) for which we examine phylogenetic information at different depths in the tree and with varied sequencing effort. The total number of loci, the proportion that are shared, and phylogenetic informativeness varied dramatically across the examined RAD-seq data sets. Insufficient or uneven sequencing coverage accounted for similar proportions of missing data as dropout from mutation-disruption. Simulations reveal that mutation-disruption, which results in phylogenetically distributed missing data, can be distinguished from the more stochastic patterns of missing data caused by low sequencing coverage. In Viburnum, doubling sequencing coverage nearly doubled the number of parsimony informative sites, and increased by >10X the number of loci with data shared across >40 taxa. Our analysis leads to a set of practical recommendations for maximizing phylogenetic information in RAD-seq studies. [hierarchical redundancy; phylogenetic informativeness; quartet informativeness; Restriction-site associated DNA (RAD) sequencing; sequencing coverage; Viburnum.]. © The authors 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Sparse distributed memory

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1989-01-01

Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs. This memory exhibits behaviors, both in theory and in experiment, that resemble those previously unapproached by machines - e.g., rapid recognition of faces or odors, discovery of new connections between seemingly unrelated ideas, continuation of a sequence of events when given a cue from the middle, knowing that one doesn't know, or getting stuck with an answer on the tip of one's tongue. These behaviors are now within reach of machines that can be incorporated into the computing systems of robots capable of seeing, talking, and manipulating. Kanerva's theory is a break with the Western rationalistic tradition, allowing a new interpretation of learning and cognition that respects biology and the mysteries of individual human beings.

Method of determining the necessary number of observations for video stream documents recognition

NASA Astrophysics Data System (ADS)

Arlazarov, Vladimir V.; Bulatov, Konstantin; Manzhikov, Temudzhin; Slavin, Oleg; Janiszewski, Igor

2018-04-01

This paper discusses a task of document recognition on a sequence of video frames. In order to optimize the processing speed an estimation is performed of stability of recognition results obtained from several video frames. Considering identity document (Russian internal passport) recognition on a mobile device it is shown that significant decrease is possible of the number of observations necessary for obtaining precise recognition result.

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed Central

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-01-01

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. PMID:29172273

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-11-26

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License

Dictionary-driven prokaryotic gene finding.

PubMed

Shibuya, Tetsuo; Rigoutsos, Isidore

2002-06-15

Gene identification, also known as gene finding or gene recognition, is among the important problems of molecular biology that have been receiving increasing attention with the advent of large scale sequencing projects. Previous strategies for solving this problem can be categorized into essentially two schools of thought: one school employs sequence composition statistics, whereas the other relies on database similarity searches. In this paper, we propose a new gene identification scheme that combines the best characteristics from each of these two schools. In particular, our method determines gene candidates among the ORFs that can be identified in a given DNA strand through the use of the Bio-Dictionary, a database of patterns that covers essentially all of the currently available sample of the natural protein sequence space. Our approach relies entirely on the use of redundant patterns as the agents on which the presence or absence of genes is predicated and does not employ any additional evidence, e.g. ribosome-binding site signals. The Bio-Dictionary Gene Finder (BDGF), the algorithm's implementation, is a single computational engine able to handle the gene identification task across distinct archaeal and bacterial genomes. The engine exhibits performance that is characterized by simultaneous very high values of sensitivity and specificity, and a high percentage of correctly predicted start sites. Using a collection of patterns derived from an old (June 2000) release of the Swiss-Prot/TrEMBL database that contained 451 602 proteins and fragments, we demonstrate our method's generality and capabilities through an extensive analysis of 17 complete archaeal and bacterial genomes. Examples of previously unreported genes are also shown and discussed in detail.

Solution NMR studies provide structural basis for endotoxin pattern recognition by the innate immune receptor CD14

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

Albright, Seth; Chen Bin; Holbrook, Kristen

CD14 functions as a key pattern recognition receptor for a diverse array of Gram-negative and Gram-positive cell-wall components in the host innate immune response by binding to pathogen-associated molecular patterns (PAMPs) at partially overlapping binding site(s). To determine the potential contribution of CD14 residues in this pattern recognition, we have examined using solution NMR spectroscopy, the binding of three different endotoxin ligands, lipopolysaccharide, lipoteichoic acid, and a PGN-derived compound, muramyl dipeptide to a {sup 15}N isotopically labeled 152-residue N-terminal fragment of sCD14 expressed in Pichia pastoris. Mapping of NMR spectral changes upon addition of ligands revealed that the pattern ofmore » residues affected by binding of each ligand is partially similar and partially different. This first direct structural observation of the ability of specific residue combinations of CD14 to differentially affect endotoxin binding may help explain the broad specificity of CD14 in ligand recognition and provide a structural basis for pattern recognition. Another interesting finding from the observed spectral changes is that the mode of binding may be dynamically modulated and could provide a mechanism for binding endotoxins with structural diversity through a common binding site.« less

Forecasting of hourly load by pattern recognition in a small area power system

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

Dehdashti-Shahrokh, A.

1982-01-01

An intuitive, logical, simple and efficient method of forecasting hourly load in a small area power system is presented. A pattern recognition approach is used in developing the forecasting model. Pattern recognition techniques are powerful tools in the field of artificial intelligence (cybernetics) and simulate the way the human brain operates to make decisions. Pattern recognition is generally used in analysis of processes where the total physical nature behind the process variation is unkown but specific kinds of measurements explain their behavior. In this research basic multivariate analyses, in conjunction with pattern recognition techniques, are used to develop a linearmore » deterministic model to forecast hourly load. This method assumes that load patterns in the same geographical area are direct results of climatological changes (weather sensitive load), and have occurred in the past as a result of similar climatic conditions. The algorithm described in here searches for the best possible pattern from a seasonal library of load and weather data in forecasting hourly load. To accommodate the unpredictability of weather and the resulting load, the basic twenty-four load pattern was divided into eight three-hour intervals. This division was made to make the model adaptive to sudden climatic changes. The proposed method offers flexible lead times of one to twenty-four hours. The results of actual data testing had indicated that this proposed method is computationally efficient, highly adaptive, with acceptable data storage size and accuracy that is comparable to many other existing methods.« less

Classification of Anticipatory Signals for Grasp and Release from Surface Electromyography.

PubMed

Siu, Ho Chit; Shah, Julie A; Stirling, Leia A

2016-10-25

Surface electromyography (sEMG) is a technique for recording natural muscle activation signals, which can serve as control inputs for exoskeletons and prosthetic devices. Previous experiments have incorporated these signals using both classical and pattern-recognition control methods in order to actuate such devices. We used the results of an experiment incorporating grasp and release actions with object contact to develop an intent-recognition system based on Gaussian mixture models (GMM) and continuous-emission hidden Markov models (HMM) of sEMG data. We tested this system with data collected from 16 individuals using a forearm band with distributed sEMG sensors. The data contain trials with shifted band alignments to assess robustness to sensor placement. This study evaluated and found that pattern-recognition-based methods could classify transient anticipatory sEMG signals in the presence of shifted sensor placement and object contact. With the best-performing classifier, the effect of label lengths in the training data was also examined. A mean classification accuracy of 75.96% was achieved through a unigram HMM method with five mixture components. Classification accuracy on different sub-movements was found to be limited by the length of the shortest sub-movement, which means that shorter sub-movements within dynamic sequences require larger training sets to be classified correctly. This classification of user intent is a potential control mechanism for a dynamic grasping task involving user contact with external objects and noise. Further work is required to test its performance as part of an exoskeleton controller, which involves contact with actuated external surfaces.

Classification of Anticipatory Signals for Grasp and Release from Surface Electromyography

PubMed Central

Siu, Ho Chit; Shah, Julie A.; Stirling, Leia A.

2016-01-01

Surface electromyography (sEMG) is a technique for recording natural muscle activation signals, which can serve as control inputs for exoskeletons and prosthetic devices. Previous experiments have incorporated these signals using both classical and pattern-recognition control methods in order to actuate such devices. We used the results of an experiment incorporating grasp and release actions with object contact to develop an intent-recognition system based on Gaussian mixture models (GMM) and continuous-emission hidden Markov models (HMM) of sEMG data. We tested this system with data collected from 16 individuals using a forearm band with distributed sEMG sensors. The data contain trials with shifted band alignments to assess robustness to sensor placement. This study evaluated and found that pattern-recognition-based methods could classify transient anticipatory sEMG signals in the presence of shifted sensor placement and object contact. With the best-performing classifier, the effect of label lengths in the training data was also examined. A mean classification accuracy of 75.96% was achieved through a unigram HMM method with five mixture components. Classification accuracy on different sub-movements was found to be limited by the length of the shortest sub-movement, which means that shorter sub-movements within dynamic sequences require larger training sets to be classified correctly. This classification of user intent is a potential control mechanism for a dynamic grasping task involving user contact with external objects and noise. Further work is required to test its performance as part of an exoskeleton controller, which involves contact with actuated external surfaces. PMID:27792155

Optical character recognition based on nonredundant correlation measurements.

PubMed

Braunecker, B; Hauck, R; Lohmann, A W

1979-08-15

The essence of character recognition is a comparison between the unknown character and a set of reference patterns. Usually, these reference patterns are all possible characters themselves, the whole alphabet in the case of letter characters. Obviously, N analog measurements are highly redundant, since only K = log(2)N binary decisions are enough to identify one out of N characters. Therefore, we devised K reference patterns accordingly. These patterns, called principal components, are found by digital image processing, but used in an optical analog computer. We will explain the concept of principal components, and we will describe experiments with several optical character recognition systems, based on this concept.

Self-organizing neural network models for visual pattern recognition.

PubMed

Fukushima, K

1987-01-01

Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

PubMed

Bahlmann, Claus; Burkhardt, Hans

2004-03-01

In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.

Effect of physical workload and modality of information presentation on pattern recognition and navigation task performance by high-fit young males.

PubMed

Zahabi, Maryam; Zhang, Wenjuan; Pankok, Carl; Lau, Mei Ying; Shirley, James; Kaber, David

2017-11-01

Many occupations require both physical exertion and cognitive task performance. Knowledge of any interaction between physical demands and modalities of cognitive task information presentation can provide a basis for optimising performance. This study examined the effect of physical exertion and modality of information presentation on pattern recognition and navigation-related information processing. Results indicated males of equivalent high fitness, between the ages of 18 and 34, rely more on visual cues vs auditory or haptic for pattern recognition when exertion level is high. We found that navigation response time was shorter under low and medium exertion levels as compared to high intensity. Navigation accuracy was lower under high level exertion compared to medium and low levels. In general, findings indicated that use of the haptic modality for cognitive task cueing decreased accuracy in pattern recognition responses. Practitioner Summary: An examination was conducted on the effect of physical exertion and information presentation modality in pattern recognition and navigation. In occupations requiring information presentation to workers, who are simultaneously performing a physical task, the visual modality appears most effective under high level exertion while haptic cueing degrades performance.

A strip chart recorder pattern recognition tool kit for Shuttle operations

NASA Technical Reports Server (NTRS)

Hammen, David G.; Moebes, Travis A.; Shelton, Robert O.; Savely, Robert T.

1993-01-01

During Space Shuttle operations, Mission Control personnel monitor numerous mission-critical systems such as electrical power; guidance, navigation, and control; and propulsion by means of paper strip chart recorders. For example, electrical power controllers monitor strip chart recorder pen traces to identify onboard electrical equipment activations and deactivations. Recent developments in pattern recognition technologies coupled with new capabilities that distribute real-time Shuttle telemetry data to engineering workstations make it possible to develop computer applications that perform some of the low-level monitoring now performed by controllers. The number of opportunities for such applications suggests a need to build a pattern recognition tool kit to reduce software development effort through software reuse. We are building pattern recognition applications while keeping such a tool kit in mind. We demonstrated the initial prototype application, which identifies electrical equipment activations, during three recent Shuttle flights. This prototype was developed to test the viability of the basic system architecture, to evaluate the performance of several pattern recognition techniques including those based on cross-correlation, neural networks, and statistical methods, to understand the interplay between an advanced automation application and human controllers to enhance utility, and to identify capabilities needed in a more general-purpose tool kit.

Type III restriction-modification enzymes: a historical perspective.

PubMed

Rao, Desirazu N; Dryden, David T F; Bheemanaik, Shivakumara

2014-01-01

Restriction endonucleases interact with DNA at specific sites leading to cleavage of DNA. Bacterial DNA is protected from restriction endonuclease cleavage by modifying the DNA using a DNA methyltransferase. Based on their molecular structure, sequence recognition, cleavage position and cofactor requirements, restriction-modification (R-M) systems are classified into four groups. Type III R-M enzymes need to interact with two separate unmethylated DNA sequences in inversely repeated head-to-head orientations for efficient cleavage to occur at a defined location (25-27 bp downstream of one of the recognition sites). Like the Type I R-M enzymes, Type III R-M enzymes possess a sequence-specific ATPase activity for DNA cleavage. ATP hydrolysis is required for the long-distance communication between the sites before cleavage. Different models, based on 1D diffusion and/or 3D-DNA looping, exist to explain how the long-distance interaction between the two recognition sites takes place. Type III R-M systems are found in most sequenced bacteria. Genome sequencing of many pathogenic bacteria also shows the presence of a number of phase-variable Type III R-M systems, which play a role in virulence. A growing number of these enzymes are being subjected to biochemical and genetic studies, which, when combined with ongoing structural analyses, promise to provide details for mechanisms of DNA recognition and catalysis.

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

PubMed Central

Pi, Yiming

2017-01-01

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. PMID:29267249

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

PubMed

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.

The Hepatitis C Virus-Induced Membranous Web and Associated Nuclear Transport Machinery Limit Access of Pattern Recognition Receptors to Viral Replication Sites

PubMed Central

Neufeldt, Christopher J.; Joyce, Michael A.; Van Buuren, Nicholas; Levin, Aviad; Kirkegaard, Karla; Gale Jr., Michael; Tyrrell, D. Lorne J.; Wozniak, Richard W.

2016-01-01

Hepatitis C virus (HCV) is a positive-strand RNA virus of the Flaviviridae family and a major cause of liver disease worldwide. HCV replicates in the cytoplasm, and the synthesis of viral proteins induces extensive rearrangements of host cell membranes producing structures, collectively termed the membranous web (MW). The MW contains the sites of viral replication and assembly, and we have identified distinct membrane fractions derived from HCV-infected cells that contain replication and assembly complexes enriched for viral RNA and infectious virus, respectively. The complex membrane structure of the MW is thought to protect the viral genome limiting its interactions with cytoplasmic pattern recognition receptors (PRRs) and thereby preventing activation of cellular innate immune responses. Here we show that PRRs, including RIG-I and MDA5, and ribosomes are excluded from viral replication and assembly centers within the MW. Furthermore, we present evidence that components of the nuclear transport machinery regulate access of proteins to MW compartments. We show that the restricted assess of RIG-I to the MW can be overcome by the addition of a nuclear localization signal sequence, and that expression of a NLS-RIG-I construct leads to increased immune activation and the inhibition of viral replication. PMID:26863439

Phylogeography and population genetic structure of double-crested cormorants (Phalacrocorax auritus)

USGS Publications Warehouse

Mercer, Dacey; Haig, Susan M.; Roby, Daniel D.

2013-01-01

is genetically divergent from other populations in North America (net sequence divergence = 5.85 %;UST for mitochondrial control region = 0.708; FST for microsatellite loci = 0.052). Historical records, contemporary population estimates, and field observations are consistent with recognition of the Alaskan subspecies as distinct and potentially of conservation interest. Our data also indicated the presence of another divergent lineage, associated with the southwestern portion of the species range, as evidenced by highly unique haplotypes sampled in southern California. In contrast, there was little support for recognition of subspecies within the conterminous U.S. and Canada. Rather than genetically distinct regions corresponding to the putative subspecies [P. a. albociliatus (Pacific), P. a. auritus (Interior and North Atlantic), and P. a. floridanus (Southeast)], we observed a distribution of genetic variation consistent with a pattern of isolation by distance. This pattern implies that genetic differences across the range are due to geographic distance, rather than discrete subspecific breaks. Although three of the four traditional subspecies were not genetically distinct, possible demographic separation, habitat differences, and documented declines at some colonies within the regions, suggests that the Pacific and possibly North Atlantic portions of the breeding range may warrant differential consideration from the Interior and Southeast breeding regions.

A dynamical pattern recognition model of gamma activity in auditory cortex

PubMed Central

Zavaglia, M.; Canolty, R.T.; Schofield, T.M.; Leff, A.P.; Ursino, M.; Knight, R.T.; Penny, W.D.

2012-01-01

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75–150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain. PMID:22327049

Visual cluster analysis and pattern recognition methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

2001-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

Proceedings of the NASA/MPRIA Workshop: Pattern Recognition

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

Outlines of talks presented at the workshop conducted at Texas A & M University on February 3 and 4, 1983 are presented. Emphasis was given to the application of Mathematics to image processing and pattern recognition.

Ab initio DNA synthesis by Bst polymerase in the presence of nicking endonucleases Nt.AlwI, Nb.BbvCI, and Nb.BsmI.

PubMed

Antipova, Valeriya N; Zheleznaya, Lyudmila A; Zyrina, Nadezhda V

2014-08-01

In the absence of added DNA, thermophilic DNA polymerases synthesize double-stranded DNA from free dNTPs, which consist of numerous repetitive units (ab initio DNA synthesis). The addition of thermophilic restriction endonuclease (REase), or nicking endonuclease (NEase), effectively stimulates ab initio DNA synthesis and determines the nucleotide sequence of reaction products. We have found that NEases Nt.AlwI, Nb.BbvCI, and Nb.BsmI with non-palindromic recognition sites stimulate the synthesis of sequences organized mainly as palindromes. Moreover, the nucleotide sequence of the palindromes appeared to be dependent on NEase recognition/cleavage modes. Thus, the heterodimeric Nb.BbvCI stimulated the synthesis of palindromes composed of two recognition sites of this NEase, which were separated by AT-reach sequences or (A)n (T)m spacers. Palindromic DNA sequences obtained in the ab initio DNA synthesis with the monomeric NEases Nb.BsmI and Nt.AlwI contained, along with the sites of these NEases, randomly synthesized sequences consisted of blocks of short repeats. These findings could help investigation of the potential abilities of highly productive ab initio DNA synthesis for the creation of DNA molecules with desirable sequence. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Polymer adsorption-driven self-assembly of nanostructures.

PubMed

Chakraborty, A K; Golumbfskie, A J

2001-01-01

Driven by prospective applications, there is much interest in developing materials that can perform specific functions in response to external conditions. One way to design such materials is to create systems which, in response to external inputs, can self-assemble to form structures that are functionally useful. This review focuses on the principles that can be employed to design macromolecules that when presented with an appropriate two-dimensional surface, will self-assemble to form nanostructures that may be functionally useful. We discuss three specific examples: (a) biomimetic recognition between polymers and patterned surfaces. (b) control and manipulation of nanomechanical motion generated by biopolymer adsorption and binding, and (c) creation of patterned nanostructuctures by exposing molten diblock copolymers to patterned surfaces. The discussion serves to illustrate how polymer sequence can be manipulated to affect self-assembly characteristics near adsorbing surfaces. The focus of this review is on theoretical and computational work aimed toward elucidating the principles underlying the phenomena pertinent to the three topics noted above. However, synergistic experiments are also described in the appropriate context.

Molecular population dynamics of DNA structures in a bcl-2 promoter sequence is regulated by small molecules and the transcription factor hnRNP LL

PubMed Central

Cui, Yunxi; Koirala, Deepak; Kang, HyunJin; Dhakal, Soma; Yangyuoru, Philip; Hurley, Laurence H.; Mao, Hanbin

2014-01-01

Minute difference in free energy change of unfolding among structures in an oligonucleotide sequence can lead to a complex population equilibrium, which is rather challenging for ensemble techniques to decipher. Herein, we introduce a new method, molecular population dynamics (MPD), to describe the intricate equilibrium among non-B deoxyribonucleic acid (DNA) structures. Using mechanical unfolding in laser tweezers, we identified six DNA species in a cytosine (C)-rich bcl-2 promoter sequence. Population patterns of these species with and without a small molecule (IMC-76 or IMC-48) or the transcription factor hnRNP LL are compared to reveal the MPD of different species. With a pattern recognition algorithm, we found that IMC-48 and hnRNP LL share 80% similarity in stabilizing i-motifs with 60 s incubation. In contrast, IMC-76 demonstrates an opposite behavior, preferring flexible DNA hairpins. With 120–180 s incubation, IMC-48 and hnRNP LL destabilize i-motifs, which has been previously proposed to activate bcl-2 transcriptions. These results provide strong support, from the population equilibrium perspective, that small molecules and hnRNP LL can modulate bcl-2 transcription through interaction with i-motifs. The excellent agreement with biochemical results firmly validates the MPD analyses, which, we expect, can be widely applicable to investigate complex equilibrium of biomacromolecules. PMID:24609386

Brain processing of meter and rhythm in music. Electrophysiological evidence of a common network.

PubMed

Kuck, Heleln; Grossbach, Michael; Bangert, Marc; Altenmüller, Eckart

2003-11-01

To determine cortical structures involved in "global" meter and "local" rhythm processing, slow brain potentials (DC potentials) were recorded from the scalp of 18 musically trained subjects while listening to pairs of monophonic sequences with both metric structure and rhythmic variations. The second sequence could be either identical to or different from the first one. Differences were either of a metric or a rhythmic nature. The subjects' task was to judge whether the sequences were identical or not. During processing of the auditory tasks, brain activation patterns along with the subjects' performance were assessed using 32-channel DC electroencephalography. Data were statistically analyzed using MANOVA. Processing of both meter and rhythm produced sustained cortical activation over bilateral frontal and temporal brain regions. A shift towards right hemispheric activation was pronounced during presentation of the second stimulus. Processing of rhythmic differences yielded a more centroparietal activation compared to metric processing. These results do not support Lerdhal and Jackendoff's two-component model, predicting a dissociation of left hemispheric rhythm and right hemispheric meter processing. We suggest that the uniform right temporofrontal predominance reflects auditory working memory and a pattern recognition module, which participates in both rhythm and meter processing. More pronounced parietal activation during rhythm processing may be related to switching of task-solving strategies towards mental imagination of the score.

Using pattern recognition as a method for predicting extreme events in natural and socio-economic systems

NASA Astrophysics Data System (ADS)

Intriligator, M.

2011-12-01

Vladimir (Volodya) Keilis-Borok has pioneered the use of pattern recognition as a technique for analyzing and forecasting developments in natural as well as socio-economic systems. Keilis-Borok's work on predicting earthquakes and landslides using this technique as a leading geophysicist has been recognized around the world. Keilis-Borok has also been a world leader in the application of pattern recognition techniques to the analysis and prediction of socio-economic systems. He worked with Allan Lichtman of American University in using such techniques to predict presidential elections in the U.S. Keilis-Borok and I have worked together with others on the use of pattern recognition techniques to analyze and to predict socio-economic systems. We have used this technique to study the pattern of macroeconomic indicators that would predict the end of an economic recession in the U.S. We have also worked with officers in the Los Angeles Police Department to use this technique to predict surges of homicides in Los Angeles.

Running Improves Pattern Separation during Novel Object Recognition.

PubMed

Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

2015-10-09

Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

Cerebellar contribution to feedforward control of locomotion

PubMed Central

Pisotta, Iolanda; Molinari, Marco

2014-01-01

The cerebellum is an important contributor to feedforward control mechanisms of the central nervous system, and sequencing—the process that allows spatial and temporal relationships between events to be recognized—has been implicated as the fundamental cerebellar mode of operation. By adopting such a mode and because cerebellar activity patterns are sensitive to a variety of sensorimotor-related tasks, the cerebellum is believed to support motor and cognitive functions that are encoded in the frontal and parietal lobes of the cerebral cortex. In this model, the cerebellum is hypothesized to make predictions about the consequences of a motor or cognitive command that originates from the cortex to prepare the entire system to cope with ongoing changes. In this framework, cerebellar predictive mechanisms for locomotion are addressed, focusing on sensorial and motoric sequencing. The hypothesis that sequence recognition is the mechanism by which the cerebellum functions in gait control is presented and discussed. PMID:25009490

A Compact Prototype of an Optical Pattern Recognition System

NASA Technical Reports Server (NTRS)

Jin, Y.; Liu, H. K.; Marzwell, N. I.

1996-01-01

In the Technology 2006 Case Studies/Success Stories presentation, we will describe and demonstrate a prototype of a compact optical pattern recognition system as an example of a successful technology transfer and continuuing development of state-of-the-art know-how by the close collaboration among government, academia, and small business via the NASA SBIR program. The prototype consists of a complete set of optical pattern recognition hardware with multi-channel storage and retrieval capability that is compactly configured inside a portable 1'X 2'X 3' aluminum case.

Textual emotion recognition for enhancing enterprise computing

NASA Astrophysics Data System (ADS)

Quan, Changqin; Ren, Fuji

2016-05-01

The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

High throughput profile-profile based fold recognition for the entire human proteome.

PubMed

McGuffin, Liam J; Smith, Richard T; Bryson, Kevin; Sørensen, Søren-Aksel; Jones, David T

2006-06-07

In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power. In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

QR-on-a-chip: a computer-recognizable micro-pattern engraved microfluidic device for high-throughput image acquisition.

PubMed

Yun, Kyungwon; Lee, Hyunjae; Bang, Hyunwoo; Jeon, Noo Li

2016-02-21

This study proposes a novel way to achieve high-throughput image acquisition based on a computer-recognizable micro-pattern implemented on a microfluidic device. We integrated the QR code, a two-dimensional barcode system, onto the microfluidic device to simplify imaging of multiple ROIs (regions of interest). A standard QR code pattern was modified to arrays of cylindrical structures of polydimethylsiloxane (PDMS). Utilizing the recognition of the micro-pattern, the proposed system enables: (1) device identification, which allows referencing additional information of the device, such as device imaging sequences or the ROIs and (2) composing a coordinate system for an arbitrarily located microfluidic device with respect to the stage. Based on these functionalities, the proposed method performs one-step high-throughput imaging for data acquisition in microfluidic devices without further manual exploration and locating of the desired ROIs. In our experience, the proposed method significantly reduced the time for the preparation of an acquisition. We expect that the method will innovatively improve the prototype device data acquisition and analysis.

Learning effect of computerized cognitive tests in older adults

PubMed Central

de Oliveira, Rafaela Sanches; Trezza, Beatriz Maria; Busse, Alexandre Leopold; Jacob-Filho, Wilson

2014-01-01

ABSTRACT Objective: To evaluate the learning effect of computerized cognitive testing in the elderly. Methods: Cross-sectional study with 20 elderly, 10 women and 10 men, with average age of 77.5 (±4.28) years. The volunteers performed two series of computerized cognitive tests in sequence and their results were compared. The applied tests were: Trail Making A and B, Spatial Recognition, Go/No Go, Memory Span, Pattern Recognition Memory and Reverse Span. Results: Based on the comparison of the results, learning effects were observed only in the Trail Making A test (p=0.019). Other tests performed presented no significant performance improvements. There was no correlation between learning effect and age (p=0.337) and education (p=0.362), as well as differences between genders (p=0.465). Conclusion: The computerized cognitive tests repeated immediately afterwards, for elderly, revealed no change in their performance, with the exception of the Trail Making test, demonstrating high clinical applicability, even in short intervals. PMID:25003917

Robust Feature Matching in Terrestrial Image Sequences

NASA Astrophysics Data System (ADS)

Abbas, A.; Ghuffar, S.

2018-04-01

From the last decade, the feature detection, description and matching techniques are most commonly exploited in various photogrammetric and computer vision applications, which includes: 3D reconstruction of scenes, image stitching for panoramic creation, image classification, or object recognition etc. However, in terrestrial imagery of urban scenes contains various issues, which include duplicate and identical structures (i.e. repeated windows and doors) that cause the problem in feature matching phase and ultimately lead to failure of results specially in case of camera pose and scene structure estimation. In this paper, we will address the issue related to ambiguous feature matching in urban environment due to repeating patterns.

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

1999-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Photonic correlator pattern recognition: Application to autonomous docking

NASA Technical Reports Server (NTRS)

Sjolander, Gary W.

1991-01-01

Optical correlators for real-time automatic pattern recognition applications have recently become feasible due to advances in high speed devices and filter formulation concepts. The devices are discussed in the context of their use in autonomous docking.

Pediatric neurology: the diagnostic process.

PubMed

Neville, Brian G R

2013-01-01

Pediatric neurology comprises a very large of number of conditions exhibiting symptoms and signs in several functional domains arising from damage and dysfunction to the developing nervous system. The diagnostic process involves ensuring that data from all possible domains are sought including those that are unaffected. The subsequent analysis involves fitting these data into patterns of classical natural history and rigorous investigation of the aspects that do not appear to fit. There may be a pattern of illness that is immediately recognized or something that is a fairly close fit. However, the aim is to develop a pathogenic sequence for the condition particularly so that conditions that have been lumped together for convenience are separated into distinct disease entities. The major presentations of pediatric neurology of fixed central motor impairments (the cerebral palsies), the epilepsies, and the progressive degenerative diseases are in the process of being split into such pathogenic sequences so that definitive treatments and possible primary prevention can be added to aims of simple diagnostic recognition. Much of this is at an early stage and pediatric neurology is still a young and fast developing specialty. Copyright © 2013 Elsevier B.V. All rights reserved.

Conformational landscape of the HIV-V3 hairpin loop from all-atom free-energy simulations

NASA Astrophysics Data System (ADS)

Verma, Abhinav; Wenzel, Wolfgang

2008-03-01

Small beta hairpins have many distinct biological functions, including their involvement in chemokine and viral receptor recognition. The relevance of structural similarities between different hairpin loops with near homologous sequences is not yet understood, calling for the development of methods for de novo hairpin structure prediction and simulation. De novo folding of beta strands is more difficult than that of helical proteins because of nonlocal hydrogen bonding patterns that connect amino acids that are distant in the amino acid sequence and there is a large variety of possible hydrogen bond patterns. Here we use a greedy version of the basin hopping technique with our free-energy forcefield PFF02 to reproducibly and predictively fold the hairpin structure of a HIV-V3 loop. We performed 20 independent basin hopping runs for 500cycles corresponding to 7.4×107 energy evaluations each. The lowest energy structure found in the simulation has a backbone root mean square deviation (bRMSD) of only 2.04Å to the native conformation. The lowest 9 out of the 20 simulations converged to conformations deviating less than 2.5Å bRMSD from native.

Conformational landscape of the HIV-V3 hairpin loop from all-atom free-energy simulations.

PubMed

Verma, Abhinav; Wenzel, Wolfgang

2008-03-14

Small beta hairpins have many distinct biological functions, including their involvement in chemokine and viral receptor recognition. The relevance of structural similarities between different hairpin loops with near homologous sequences is not yet understood, calling for the development of methods for de novo hairpin structure prediction and simulation. De novo folding of beta strands is more difficult than that of helical proteins because of nonlocal hydrogen bonding patterns that connect amino acids that are distant in the amino acid sequence and there is a large variety of possible hydrogen bond patterns. Here we use a greedy version of the basin hopping technique with our free-energy forcefield PFF02 to reproducibly and predictively fold the hairpin structure of a HIV-V3 loop. We performed 20 independent basin hopping runs for 500 cycles corresponding to 7.4 x 10(7) energy evaluations each. The lowest energy structure found in the simulation has a backbone root mean square deviation (bRMSD) of only 2.04 A to the native conformation. The lowest 9 out of the 20 simulations converged to conformations deviating less than 2.5 A bRMSD from native.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM.

PubMed

Rodriguez, Mario; Orrite, Carlos; Medrano, Carlos; Makris, Dimitrios

2016-05-10

This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results.

Finger Vein Recognition Based on a Personalized Best Bit Map

PubMed Central

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition. PMID:22438735

Finger vein recognition based on a personalized best bit map.

PubMed

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition.

Large-memory real-time multichannel multiplexed pattern recognition

NASA Technical Reports Server (NTRS)

Gregory, D. A.; Liu, H. K.

1984-01-01

The principle and experimental design of a real-time multichannel multiplexed optical pattern recognition system via use of a 25-focus dichromated gelatin holographic lens (hololens) are described. Each of the 25 foci of the hololens may have a storage and matched filtering capability approaching that of a single-lens correlator. If the space-bandwidth product of an input image is limited, as is true in most practical cases, the 25-focus hololens system has 25 times the capability of a single lens. Experimental results have shown that the interfilter noise is not serious. The system has already demonstrated the storage and recognition of over 70 matched filters - which is a larger capacity than any optical pattern recognition system reported to date.

Zinc-binding Domain of the Bacteriophage T7 DNA Primase Modulates Binding to the DNA Template*

PubMed Central

Lee, Seung-Joo; Zhu, Bin; Akabayov, Barak; Richardson, Charles C.

2012-01-01

The zinc-binding domain (ZBD) of prokaryotic DNA primases has been postulated to be crucial for recognition of specific sequences in the single-stranded DNA template. To determine the molecular basis for this role in recognition, we carried out homolog-scanning mutagenesis of the zinc-binding domain of DNA primase of bacteriophage T7 using a bacterial homolog from Geobacillus stearothermophilus. The ability of T7 DNA primase to catalyze template-directed oligoribonucleotide synthesis is eliminated by substitution of any five-amino acid residue-long segment within the ZBD. The most significant defect occurs upon substitution of a region (Pro-16 to Cys-20) spanning two cysteines that coordinate the zinc ion. The role of this region in primase function was further investigated by generating a protein library composed of multiple amino acid substitutions for Pro-16, Asp-18, and Asn-19 followed by genetic screening for functional proteins. Examination of proteins selected from the screening reveals no change in sequence-specific recognition. However, the more positively charged residues in the region facilitate DNA binding, leading to more efficient oligoribonucleotide synthesis on short templates. The results suggest that the zinc-binding mode alone is not responsible for sequence recognition, but rather its interaction with the RNA polymerase domain is critical for DNA binding and for sequence recognition. Consequently, any alteration in the ZBD that disturbs its conformation leads to loss of DNA-dependent oligoribonucleotide synthesis. PMID:23024359

Invariant recognition drives neural representations of action sequences

PubMed Central

Poggio, Tomaso

2017-01-01

Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences. PMID:29253864

Evidence of automatic processing in sequence learning using process-dissociation

PubMed Central

Mong, Heather M.; McCabe, David P.; Clegg, Benjamin A.

2012-01-01

This paper proposes a way to apply process-dissociation to sequence learning in addition and extension to the approach used by Destrebecqz and Cleeremans (2001). Participants were trained on two sequences separated from each other by a short break. Following training, participants self-reported their knowledge of the sequences. A recognition test was then performed which required discrimination of two trained sequences, either under the instructions to call any sequence encountered in the experiment “old” (the inclusion condition), or only sequence fragments from one half of the experiment “old” (the exclusion condition). The recognition test elicited automatic and controlled process estimates using the process dissociation procedure, and suggested both processes were involved. Examining the underlying processes supporting performance may provide more information on the fundamental aspects of the implicit and explicit constructs than has been attainable through awareness testing. PMID:22679465

Listening for Recollection: A Multi-Voxel Pattern Analysis of Recognition Memory Retrieval Strategies

PubMed Central

Quamme, Joel R.; Weiss, David J.; Norman, Kenneth A.

2010-01-01

Recent studies of recognition memory indicate that subjects can strategically vary how much they rely on recollection of specific details vs. feelings of familiarity when making recognition judgments. One possible explanation of these results is that subjects can establish an internally directed attentional state (“listening for recollection”) that enhances retrieval of studied details; fluctuations in this attentional state over time should be associated with fluctuations in subjects’ recognition behavior. In this study, we used multi-voxel pattern analysis of fMRI data to identify brain regions that are involved in listening for recollection. We looked for brain regions that met the following criteria: (1) Distinct neural patterns should be present when subjects are instructed to rely on recollection vs. familiarity, and (2) fluctuations in these neural patterns should be related to recognition behavior in the manner predicted by dual-process theories of recognition: Specifically, the presence of the recollection pattern during the pre-stimulus interval (indicating that subjects are “listening for recollection” at that moment) should be associated with a selective decrease in false alarms to related lures. We found that pre-stimulus activity in the right supramarginal gyrus met all of these criteria, suggesting that this region proactively establishes an internally directed attentional state that fosters recollection. We also found other regions (e.g., left middle temporal gyrus) where the pattern of neural activity was related to subjects’ responding to related lures after stimulus onset (but not before), suggesting that these regions implement processes that are engaged in a reactive fashion to boost recollection. PMID:20740073

Auditory orientation in crickets: Pattern recognition controls reactive steering

NASA Astrophysics Data System (ADS)

Poulet, James F. A.; Hedwig, Berthold

2005-10-01

Many groups of insects are specialists in exploiting sensory cues to locate food resources or conspecifics. To achieve orientation, bees and ants analyze the polarization pattern of the sky, male moths orient along the females' odor plume, and cicadas, grasshoppers, and crickets use acoustic signals to locate singing conspecifics. In comparison with olfactory and visual orientation, where learning is involved, auditory processing underlying orientation in insects appears to be more hardwired and genetically determined. In each of these examples, however, orientation requires a recognition process identifying the crucial sensory pattern to interact with a localization process directing the animal's locomotor activity. Here, we characterize this interaction. Using a sensitive trackball system, we show that, during cricket auditory behavior, the recognition process that is tuned toward the species-specific song pattern controls the amplitude of auditory evoked steering responses. Females perform small reactive steering movements toward any sound patterns. Hearing the male's calling song increases the gain of auditory steering within 2-5 s, and the animals even steer toward nonattractive sound patterns inserted into the speciesspecific pattern. This gain control mechanism in the auditory-to-motor pathway allows crickets to pursue species-specific sound patterns temporarily corrupted by environmental factors and may reflect the organization of recognition and localization networks in insects. localization | phonotaxis

A dinucleotide motif in oligonucleotides shows potent immunomodulatory activity and overrides species-specific recognition observed with CpG motif.

PubMed

Kandimalla, Ekambar R; Bhagat, Lakshmi; Zhu, Fu-Gang; Yu, Dong; Cong, Yan-Ping; Wang, Daqing; Tang, Jimmy X; Tang, Jin-Yan; Knetter, Cathrine F; Lien, Egil; Agrawal, Sudhir

2003-11-25

Bacterial and synthetic DNAs containing CpG dinucleotides in specific sequence contexts activate the vertebrate immune system through Toll-like receptor 9 (TLR9). In the present study, we used a synthetic nucleoside with a bicyclic heterobase [1-(2'-deoxy-beta-d-ribofuranosyl)-2-oxo-7-deaza-8-methyl-purine; R] to replace the C in CpG, resulting in an RpG dinucleotide. The RpG dinucleotide was incorporated in mouse- and human-specific motifs in oligodeoxynucleotides (oligos) and 3'-3-linked oligos, referred to as immunomers. Oligos containing the RpG motif induced cytokine secretion in mouse spleen-cell cultures. Immunomers containing RpG dinucleotides showed activity in transfected-HEK293 cells stably expressing mouse TLR9, suggesting direct involvement of TLR9 in the recognition of RpG motif. In J774 macrophages, RpG motifs activated NF-kappa B and mitogen-activated protein kinase pathways. Immunomers containing the RpG dinucleotide induced high levels of IL-12 and IFN-gamma, but lower IL-6 in time- and concentration-dependent fashion in mouse spleen-cell cultures costimulated with IL-2. Importantly, immunomers containing GTRGTT and GARGTT motifs were recognized to a similar extent by both mouse and human immune systems. Additionally, both mouse- and human-specific RpG immunomers potently stimulated proliferation of peripheral blood mononuclear cells obtained from diverse vertebrate species, including monkey, pig, horse, sheep, goat, rat, and chicken. An immunomer containing GTRGTT motif prevented conalbumin-induced and ragweed allergen-induced allergic inflammation in mice. We show that a synthetic bicyclic nucleotide is recognized in the C position of a CpG dinucleotide by immune cells from diverse vertebrate species without bias for flanking sequences, suggesting a divergent nucleotide motif recognition pattern of TLR9.

A new C-type lectin (FcLec5) from the Chinese white shrimp Fenneropenaeus chinensis.

PubMed

Xu, Wen-Teng; Wang, Xian-Wei; Zhang, Xiao-Wen; Zhao, Xiao-Fan; Yu, Xiao-Qiang; Wang, Jin-Xing

2010-11-01

C-type lectins are one family of pattern recognition receptors (PRRs) that play important roles in innate immunity. In this work, cDNA and genomic sequences for a new C-type lectin (FcLec5) were obtained from the Chinese white shrimp Fenneropenaeus chinensis. FcLec5 cDNA contains an open reading frame of 1,008 bp and its genomic sequence is 1,137 bp with 4 exons and 3 introns. The predicted FcLec5 protein contains a signal peptide and two carbohydrate recognition domains (CRDs). The N-terminal CRD of FcLec5 has a predicted carbohydrate recognition motif of Gln-Pro-Asp (QPD), while the C-terminal CRD contains a motif of Glu-Pro-Gln (EPQ). Northern blot analysis showed that FcLec5 mRNA was specifically expressed in hepatopancreas. FcLec5 protein was expressed in hepatopancreas and secreted into hemolymph. Real-time PCR showed that FcLec5 transcript exhibited different expression profiles after immune-challenged with Vibrio anguillarum or White Spot Syndrome Virus (WSSV). Recombinant FcLec5 and its two individual CRDs could agglutinate most bacteria tested, and the agglutinating activity was Ca2+-dependent. Besides, the agglutinating activity to gram-negative bacteria is higher than that to gram-positive bacteria. Direct binding assay showed that recombinant FcLec5 could bind to all microorganisms tested (five gram-positive and four gram-negative bacteria, as well as yeast) in a Ca2+-independent manner. Recombinant FcLec5 also directly bound to bacterial peptidoglycan, lipopolysaccharide and lipoteichoic acids. These results suggest that FcLec5 may act as a PRR for bacteria via binding to bacterial cell wall polysaccharides in Chinese white shrimp.

Receptor-like cytoplasmic kinases are pivotal components in pattern recognition receptor-mediated signaling in plant immunity.

PubMed

Yamaguchi, Koji; Yamada, Kenta; Kawasaki, Tsutomu

2013-10-01

Innate immunity is generally initiated with recognition of conserved pathogen-associated molecular patterns (PAMPs). PAMPs are perceived by pattern recognition receptors (PRRs), leading to activation of a series of immune responses, including the expression of defense genes, ROS production and activation of MAP kinase. Recent progress has indicated that receptor-like cytoplasmic kinases (RLCKs) are directly activated by ligand-activated PRRs and initiate pattern-triggered immunity (PTI) in both Arabidopsis and rice. To suppress PTI, pathogens inhibit the RLCKs by many types of effectors, including AvrAC, AvrPphB and Xoo1488. In this review, we summarize recent advances in RLCK-mediated PTI in plants.

Recognition of microbial molecular patterns and stimulation of prophenoloxidase activation by a β-1,3-glucanase-related protein in Manduca sexta larval plasma

PubMed Central

Wang, Yang; Sumathipala, Niranji; Rayaprolu, Subrahmanyam; Jiang, Haobo

2011-01-01

Detection of pathogenic invaders is the essential first step of a successful defense response in multicellular organisms. In this study, we have identified a new member of the β-1,3-glucanase-related protein superfamily from the tobacco hornworm Manduca sexta. This protein, designated microbe binding protein (MBP), is 61% identical in sequence to Bombyx mori Gram-negative bacteria binding protein, but only 34-36% identical to M. sexta β-1,3-glucan recognition protein-1 and 2. Its mRNA levels were strongly up-regulated in hemocytes and fat body of immune challenged larvae, along with an increase in concentration of the plasma protein. We expressed M. sexta MBP in a baculovirus-insect cell system. The purified protein associated with intact bacteria and fungi. It specifically bound to lipoteichoic acid, lipopolysaccharide, diaminopimelic acid-type peptidoglycans (DAP-PGs) from Escherichia coli and Bacillus subtilis, but less so to laminarin or Lys-type PG from Staphylococcus aureus. The complex binding pattern was influenced by other plasma factors and additional microbial surface molecules. After different amounts of MBP had been incubated with larval plasma on ice, a concentration-dependent increase in phenoloxidase (PO) activity occurred in the absence of any microbial elicitor. The activity increase was also observed in the mixture of plasma and a bacterial or fungal cell wall component. The prophenoloxidase (proPO) activation became more prominent when DAP-PGs, Micrococcus luteus Lys-PG, or lipoteichoic acid was included in the mixture of MBP and plasma. Statistic analysis suggested that a synergistic enhancement of proPO activation was caused by an interaction between MBP and these elicitors, but not S. aureus Lys-PG, lipopolysaccharide, curdlan, or laminarin. These data indicate that M. sexta MBP is a component of the surveillance mechanism and, by working together with other pattern recognition molecules and serine proteinases, triggers the proPO activation system. PMID:21296155

Proceedings of the NASA Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

The application of mathematical and statistical analyses techniques to imagery obtained by remote sensors is described by Principal Investigators. Scene-to-map registration, geometric rectification, and image matching are among the pattern recognition aspects discussed.

Students' Dichotomous Experiences of the Illuminating and Illusionary Nature of Pattern Recognition in Mathematics

ERIC Educational Resources Information Center

Mhlolo, Michael Kainose

2016-01-01

The concept of pattern recognition lies at the heart of numerous deliberations concerned with new mathematics curricula, because it is strongly linked to improved generalised thinking. However none of these discussions has made the deceptive nature of patterns an object of exploration and understanding. Yet there is evidence showing that pattern…

Novel proteases from the genome of the carnivorous plant Drosera capensis: structural prediction and comparative analysis

PubMed Central

Butts, Carter T.; Bierma, Jan C.; Martin, Rachel W.

2016-01-01

In his 1875 monograph on insectivorous plants, Darwin described the feeding reactions of Drosera flypaper traps and predicted that their secretions contained a “ferment” similar to mammalian pepsin, an aspartic protease. Here we report a high-quality draft genome sequence for the cape sundew, Drosera capensis, the first genome of a carnivorous plant from order Caryophyllales, which also includes the Venus flytrap (Dionaea) and the tropical pitcher plants (Nepenthes). This species was selected in part for its hardiness and ease of cultivation, making it an excellent model organism for further investigations of plant carnivory. Analysis of predicted protein sequences yields genes encoding proteases homologous to those found in other plants, some of which display sequence and structural features that suggest novel functionalities. Because the sequence similarity to proteins of known structure is in most cases too low for traditional homology modeling, 3D structures of representative proteases are predicted using comparative modeling with all-atom refinement. Although the overall folds and active residues for these proteins are conserved, we find structural and sequence differences consistent with a diversity of substrate recognition patterns. Finally, we predict differences in substrate specificities using in silico experiments, providing targets for structure/function studies of novel enzymes with biological and technological significance. PMID:27353064

Methods and means of diagnostics of oncological diseases on the basis of pattern recognition: intelligent morphological systems - problems and solutions

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.

2017-01-01

The development of methods of pattern recognition in modern intelligent systems of clinical cancer diagnosis are discussed. The histological (morphological) diagnosis - primary diagnosis for medical setting with cancer are investigated. There are proposed: interactive methods of recognition and structure of intellectual morphological complexes based on expert training-diagnostic and telemedicine systems. The proposed approach successfully implemented in clinical practice.

Homology to peptide pattern for annotation of carbohydrate-active enzymes and prediction of function.

PubMed

Busk, P K; Pilgaard, B; Lezyk, M J; Meyer, A S; Lange, L

2017-04-12

Carbohydrate-active enzymes are found in all organisms and participate in key biological processes. These enzymes are classified in 274 families in the CAZy database but the sequence diversity within each family makes it a major task to identify new family members and to provide basis for prediction of enzyme function. A fast and reliable method for de novo annotation of genes encoding carbohydrate-active enzymes is to identify conserved peptides in the curated enzyme families followed by matching of the conserved peptides to the sequence of interest as demonstrated for the glycosyl hydrolase and the lytic polysaccharide monooxygenase families. This approach not only assigns the enzymes to families but also provides functional prediction of the enzymes with high accuracy. We identified conserved peptides for all enzyme families in the CAZy database with Peptide Pattern Recognition. The conserved peptides were matched to protein sequence for de novo annotation and functional prediction of carbohydrate-active enzymes with the Hotpep method. Annotation of protein sequences from 12 bacterial and 16 fungal genomes to families with Hotpep had an accuracy of 0.84 (measured as F1-score) compared to semiautomatic annotation by the CAZy database whereas the dbCAN HMM-based method had an accuracy of 0.77 with optimized parameters. Furthermore, Hotpep provided a functional prediction with 86% accuracy for the annotated genes. Hotpep is available as a stand-alone application for MS Windows. Hotpep is a state-of-the-art method for automatic annotation and functional prediction of carbohydrate-active enzymes.

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models

PubMed Central

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner’s faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals. PMID:27191162

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models.

PubMed

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner's faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals.

Postprocessing for character recognition using pattern features and linguistic information

NASA Astrophysics Data System (ADS)

Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

1993-04-01

We propose a new method of post-processing for character recognition using pattern features and linguistic information. This method corrects errors in the recognition of handwritten Japanese sentences containing Kanji characters. This post-process method is characterized by having two types of character recognition. Improving the accuracy of the character recognition rate of Japanese characters is made difficult by the large number of characters, and the existence of characters with similar patterns. Therefore, it is not practical for a character recognition system to recognize all characters in detail. First, this post-processing method generates a candidate character table by recognizing the simplest features of characters. Then, it selects words corresponding to the character from the candidate character table by referring to a word and grammar dictionary before selecting suitable words. If the correct character is included in the candidate character table, this process can correct an error, however, if the character is not included, it cannot correct an error. Therefore, if this method can presume a character does not exist in a candidate character table by using linguistic information (word and grammar dictionary). It then can verify a presumed character by character recognition using complex features. When this method is applied to an online character recognition system, the accuracy of character recognition improves 93.5% to 94.7%. This proved to be the case when it was used for the editorials of a Japanese newspaper (Asahi Shinbun).

Facial emotion recognition in patients with focal and diffuse axonal injury.

PubMed

Yassin, Walid; Callahan, Brandy L; Ubukata, Shiho; Sugihara, Genichi; Murai, Toshiya; Ueda, Keita

2017-01-01

Facial emotion recognition impairment has been well documented in patients with traumatic brain injury. Studies exploring the neural substrates involved in such deficits have implicated specific grey matter structures (e.g. orbitofrontal regions), as well as diffuse white matter damage. Our study aims to clarify whether different types of injuries (i.e. focal vs. diffuse) will lead to different types of impairments on facial emotion recognition tasks, as no study has directly compared these patients. The present study examined performance and response patterns on a facial emotion recognition task in 14 participants with diffuse axonal injury (DAI), 14 with focal injury (FI) and 22 healthy controls. We found that, overall, participants with FI and DAI performed more poorly than controls on the facial emotion recognition task. Further, we observed comparable emotion recognition performance in participants with FI and DAI, despite differences in the nature and distribution of their lesions. However, the rating response pattern between the patient groups was different. This is the first study to show that pure DAI, without gross focal lesions, can independently lead to facial emotion recognition deficits and that rating patterns differ depending on the type and location of trauma.

33 CFR 106.205 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

... security related communications; (7) Knowledge of current security threats and patterns; (8) Recognition and detection of dangerous substances and devices; (9) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (10) Techniques used to circumvent security...

33 CFR 106.205 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

... security related communications; (7) Knowledge of current security threats and patterns; (8) Recognition and detection of dangerous substances and devices; (9) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (10) Techniques used to circumvent security...

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, G.C.; Martinez, R.F.

1999-05-04

A method of clustering using a novel template to define a region of influence is disclosed. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques. 30 figs.

Multiple degree of freedom optical pattern recognition

NASA Technical Reports Server (NTRS)

Casasent, D.

1987-01-01

Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

Ultrasonography of ovarian masses using a pattern recognition approach

PubMed Central

Jung, Sung Il

2015-01-01

As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to be diagnosed as benign or malignant with even greater confidence. In order to differentiate benign and malignant ovarian masses, it is necessary to categorize ovarian masses into unilocular cyst, unilocular solid cyst, multilocular cyst, multilocular solid cyst, and solid tumor, and then to detect typical US features that demonstrate malignancy based on pattern recognition approach. PMID:25797108

Application of pattern recognition techniques to crime analysis

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

Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

1976-08-15

The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

DESIGN OF A PATTERN RECOGNITION DIGITAL COMPUTER WITH APPLICATION TO THE AUTOMATIC SCANNING OF BUBBLE CHAMBER NEGATIVES

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

McCormick, B.H.; Narasimhan, R.

1963-01-01

The overall computer system contains three main parts: an input device, a pattern recognition unit (PRU), and a control computer. The bubble chamber picture is divided into a grid of st run. Concent 1-mm squares on the film. It is then processed in parallel in a two-dimensional array of 1024 identical processing modules (stalactites) of the PRU. The array can function as a two- dimensional shift register in which results of successive shifting operations can be accumulated. The pattern recognition process is generally controlled by a conventional arithmetic computer. (A.G.W.)

Directing an appropriate immune response: the role of defense collagens and other soluble pattern recognition molecules.

PubMed

Fraser, D A; Tenner, A J

2008-02-01

Defense collagens and other soluble pattern recognition receptors contain the ability to recognize and bind molecular patterns associated with pathogens (PAMPs) or apoptotic cells (ACAMPs) and signal appropriate effector-function responses. PAMP recognition by defense collagens C1q, MBL and ficolins leads to rapid containment of infection via complement activation. However, in the absence of danger, such as during the clearance of apoptotic cells, defense collagens such as C1q, MBL, ficolins, SP-A, SP-D and even adiponectin have all been shown to facilitate enhanced phagocytosis and modulate induction of cytokines towards an anti-inflammatory profile. In this way, cellular debris can be removed without provoking an inflammatory immune response which may be important in the prevention of autoimmunity and/or resolving inflammation. Indeed, deficiencies and/or knock-out mouse studies have highlighted critical roles for soluble pattern recognition receptors in the clearance of apoptotic bodies and protection from autoimmune diseases along with mediating protection from specific infections. Understanding the mechanisms involved in defense collagen and other soluble pattern recognition receptor modulation of the immune response may provide important novel insights into therapeutic targets for infectious and/or autoimmune diseases and additionally may identify avenues for more effective vaccine design.

A split recognition mode combined with cascade signal amplification strategy for highly specific, sensitive detection of microRNA.

PubMed

Wang, Rui; Wang, Lei; Zhao, Haiyan; Jiang, Wei

2016-12-15

MicroRNAs (miRNAs) are vital for many biological processes and have been regarded as cancer biomarkers. Specific and sensitive detection of miRNAs is essential for cancer diagnosis and therapy. Herein, a split recognition mode combined with cascade signal amplification strategy is developed for highly specific and sensitive detection of miRNA. The split recognition mode possesses two specific recognition processes, which are based on toehold-mediated strand displacement reaction (TSDR) and direct hybridization reaction. Two recognition probes, hairpin probe (HP) with overhanging toehold domain and assistant probe (AP), are specially designed. Firstly, the toehold domain of HP and AP recognize part of miRNA simultaneously, accompanied with TSDR to unfold the HP and form the stable DNA Y-shaped junction structure (YJS). Then, the AP in YJS can further act as primer to initiate strand displacement amplification, releasing numerous trigger sequences. Finally, the trigger sequences hybridize with padlock DNA to initiate circular rolling circle amplification and generate enhanced fluorescence responses. In this strategy, the dual recognition effect of split recognition mode guarantees the excellent selectivity to discriminate let-7b from high-homology sequences. Furthermore, the high amplification efficiency of cascade signal amplification guarantees a high sensitivity with the detection limit of 3.2 pM and the concentration of let-7b in total RNA sample extracted from Hela cells is determined. These results indicate our strategy will be a promising miRNA detection strategy in clinical diagnosis and disease treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

The memory is in the details: relations between memory for the specific features of events and long-term recall during infancy.

PubMed

Bauer, Patricia J; Lukowski, Angela F

2010-09-01

The second year of life is marked by pronounced changes in the length of time over which events are remembered. We tested whether the age-related differences are related to differences in memory for the specific features of events. In our study, 16- and 20-month-olds were tested for immediate and long-term recall of individual actions and temporal order of actions of three-step sequences in an elicited imitation paradigm as well as for forced-choice recognition of the specific feature of the props used to produce the sequences. Memory for the props was related to long-term recall of the events only for the 20-month-olds. It accounted for unique variance above and beyond the variance explained by immediate recall of the individual actions and the temporal order of actions of the sequences. The different pattern of relations in the older and younger infants seemingly reflects a developmental difference in the determinants of long-term recall over the second year of life. Copyright 2010 Elsevier Inc. All rights reserved.

Visual scanning behavior is related to recognition performance for own- and other-age faces

PubMed Central

Proietti, Valentina; Macchi Cassia, Viola; dell’Amore, Francesca; Conte, Stefania; Bricolo, Emanuela

2015-01-01

It is well-established that our recognition ability is enhanced for faces belonging to familiar categories, such as own-race faces and own-age faces. Recent evidence suggests that, for race, the recognition bias is also accompanied by different visual scanning strategies for own- compared to other-race faces. Here, we tested the hypothesis that these differences in visual scanning patterns extend also to the comparison between own and other-age faces and contribute to the own-age recognition advantage. Participants (young adults with limited experience with infants) were tested in an old/new recognition memory task where they encoded and subsequently recognized a series of adult and infant faces while their eye movements were recorded. Consistent with findings on the other-race bias, we found evidence of an own-age bias in recognition which was accompanied by differential scanning patterns, and consequently differential encoding strategies, for own-compared to other-age faces. Gaze patterns for own-age faces involved a more dynamic sampling of the internal features and longer viewing time on the eye region compared to the other regions of the face. This latter strategy was extensively employed during learning (vs. recognition) and was positively correlated to discriminability. These results suggest that deeply encoding the eye region is functional for recognition and that the own-age bias is evident not only in differential recognition performance, but also in the employment of different sampling strategies found to be effective for accurate recognition. PMID:26579056

Application of optical correlation techniques to particle imaging velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1988-01-01

Pulsed laser sheet velocimetry yields nonintrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usually MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the partical image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.

Developmental Considerations of Sperm Protein 17 Gene Expression in Rheumatoid Arthritis Synoviocytes

PubMed Central

Takeoka, Yuichi; Kenny, Thomas P.; Yago, Hisashi; Naiki, Mitsuru; Gershwin, M. Eric; Robbins, Dick L.

2002-01-01

Rheumatoid arthritis (RA) is an autoimmune disease characterized by proliferative synovial tissue. We used mRNA differential display and library subtraction to compare mRNA expression in RA and osteoarthritis (OA) synoviocytes. We initially compared the mRNA expression patterns in 1 female RA and 1 OA synovia and found a differentially expressed 350 bp transcript in the RA synoviocytes which was, by sequence analysis, 100% homologous to sperm protein 17 (Sp17). Moreover, the Sp17 transcript was found differentially expressed in a RA synovial library that was subtracted with an OA synovial library. Using specific primers for full length Sp17, a 1.1 kb transcript was amplified from the synoviocytes of 7 additional female RA patients, sequenced and found to 100% homologous to Sp17. Thus, we found the unexpected expression of Sp17, a thought to be gamete-specific protein, in the synoviocytes of 8/8 female RA patients in contrast to control OA synoviocytes. Interestingly, Sp17's structural relationship with cell-binding and recognition proteins, suggests that Sp17 may function in cell-cell recognition and signaling in the RA synoviocyte. Further, Sp17 could have a significant regulatory role in RA synoviocyte gene transcription and/or signal transduction. Thus, Sp17 could have an important role in RA synoviocyte proliferation or defective apoptosis. Finally, the presence of Sp17 in synoviocytes has interesting developmental considerations. PMID:12739786

Iterative cross section sequence graph for handwritten character segmentation.

PubMed

Dawoud, Amer

2007-08-01

The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.

CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

NASA Astrophysics Data System (ADS)

Gong, Qian; Qu, Zhiyi; Hao, Kun

2017-07-01

Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

Training the max-margin sequence model with the relaxed slack variables.

PubMed

Niu, Lingfeng; Wu, Jianmin; Shi, Yong

2012-09-01

Sequence models are widely used in many applications such as natural language processing, information extraction and optical character recognition, etc. We propose a new approach to train the max-margin based sequence model by relaxing the slack variables in this paper. With the canonical feature mapping definition, the relaxed problem is solved by training a multiclass Support Vector Machine (SVM). Compared with the state-of-the-art solutions for the sequence learning, the new method has the following advantages: firstly, the sequence training problem is transformed into a multiclassification problem, which is more widely studied and already has quite a few off-the-shelf training packages; secondly, this new approach reduces the complexity of training significantly and achieves comparable prediction performance compared with the existing sequence models; thirdly, when the size of training data is limited, by assigning different slack variables to different microlabel pairs, the new method can use the discriminative information more frugally and produces more reliable model; last but not least, by employing kernels in the intermediate multiclass SVM, nonlinear feature space can be easily explored. Experimental results on the task of named entity recognition, information extraction and handwritten letter recognition with the public datasets illustrate the efficiency and effectiveness of our method. Copyright © 2012 Elsevier Ltd. All rights reserved.

Emotional Faces in Context: Age Differences in Recognition Accuracy and Scanning Patterns

PubMed Central

Noh, Soo Rim; Isaacowitz, Derek M.

2014-01-01

While age-related declines in facial expression recognition are well documented, previous research relied mostly on isolated faces devoid of context. We investigated the effects of context on age differences in recognition of facial emotions and in visual scanning patterns of emotional faces. While their eye movements were monitored, younger and older participants viewed facial expressions (i.e., anger, disgust) in contexts that were emotionally congruent, incongruent, or neutral to the facial expression to be identified. Both age groups had highest recognition rates of facial expressions in the congruent context, followed by the neutral context, and recognition rates in the incongruent context were worst. These context effects were more pronounced for older adults. Compared to younger adults, older adults exhibited a greater benefit from congruent contextual information, regardless of facial expression. Context also influenced the pattern of visual scanning characteristics of emotional faces in a similar manner across age groups. In addition, older adults initially attended more to context overall. Our data highlight the importance of considering the role of context in understanding emotion recognition in adulthood. PMID:23163713

Comparing the visual spans for faces and letters

PubMed Central

He, Yingchen; Scholz, Jennifer M.; Gage, Rachel; Kallie, Christopher S.; Liu, Tingting; Legge, Gordon E.

2015-01-01

The visual span—the number of adjacent text letters that can be reliably recognized on one fixation—has been proposed as a sensory bottleneck that limits reading speed (Legge, Mansfield, & Chung, 2001). Like reading, searching for a face is an important daily task that involves pattern recognition. Is there a similar limitation on the number of faces that can be recognized in a single fixation? Here we report on a study in which we measured and compared the visual-span profiles for letter and face recognition. A serial two-stage model for pattern recognition was developed to interpret the data. The first stage is characterized by factors limiting recognition of isolated letters or faces, and the second stage represents the interfering effect of nearby stimuli on recognition. Our findings show that the visual span for faces is smaller than that for letters. Surprisingly, however, when differences in first-stage processing for letters and faces are accounted for, the two visual spans become nearly identical. These results suggest that the concept of visual span may describe a common sensory bottleneck that underlies different types of pattern recognition. PMID:26129858

Training Strategies for Mitigating the Effect of Proportional Control on Classification in Pattern Recognition Based Myoelectric Control

PubMed Central

Scheme, Erik; Englehart, Kevin

2013-01-01

The performance of pattern recognition based myoelectric control has seen significant interest in the research community for many years. Due to a recent surge in the development of dexterous prosthetic devices, determining the clinical viability of multifunction myoelectric control has become paramount. Several factors contribute to differences between offline classification accuracy and clinical usability, but the overriding theme is that the variability of the elicited patterns increases greatly during functional use. Proportional control has been shown to greatly improve the usability of conventional myoelectric control systems. Typically, a measure of the amplitude of the electromyogram (a rectified and smoothed version) is used to dictate the velocity of control of a device. The discriminatory power of myoelectric pattern classifiers, however, is also largely based on amplitude features of the electromyogram. This work presents an introductory look at the effect of contraction strength and proportional control on pattern recognition based control. These effects are investigated using typical pattern recognition data collection methods as well as a real-time position tracking test. Training with dynamically force varying contractions and appropriate gain selection is shown to significantly improve (p<0.001) the classifier’s performance and tolerance to proportional control. PMID:23894224

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

Addressing the issue of insufficient information in data-based bridge health monitoring : final report.

DOT National Transportation Integrated Search

2015-11-01

One of the most efficient ways to solve the damage detection problem using the statistical pattern recognition : approach is that of exploiting the methods of outlier analysis. Cast within the pattern recognition framework, : damage detection assesse...

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217

Functional specificity of a Hox protein mediated by the recognition of minor groove structure.

PubMed

Joshi, Rohit; Passner, Jonathan M; Rohs, Remo; Jain, Rinku; Sosinsky, Alona; Crickmore, Michael A; Jacob, Vinitha; Aggarwal, Aneel K; Honig, Barry; Mann, Richard S

2007-11-02

The recognition of specific DNA-binding sites by transcription factors is a critical yet poorly understood step in the control of gene expression. Members of the Hox family of transcription factors bind DNA by making nearly identical major groove contacts via the recognition helices of their homeodomains. In vivo specificity, however, often depends on extended and unstructured regions that link Hox homeodomains to a DNA-bound cofactor, Extradenticle (Exd). Using a combination of structure determination, computational analysis, and in vitro and in vivo assays, we show that Hox proteins recognize specific Hox-Exd binding sites via residues located in these extended regions that insert into the minor groove but only when presented with the correct DNA sequence. Our results suggest that these residues, which are conserved in a paralog-specific manner, confer specificity by recognizing a sequence-dependent DNA structure instead of directly reading a specific DNA sequence.

Action recognition using mined hierarchical compound features.

PubMed

Gilbert, Andrew; Illingworth, John; Bowden, Richard

2011-05-01

The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single-frame object recognition and adapting them for temporal-based action recognition. Inspired by the success of interest points in the 2D spatial domain, their 3D (space-time) counterparts typically form the basic components used to describe actions, and in action recognition the features used are often engineered to fire sparsely. This is to ensure that the problem is tractable; however, this can sacrifice recognition accuracy as it cannot be assumed that the optimum features in terms of class discrimination are obtained from this approach. In contrast, we propose to initially use an overcomplete set of simple 2D corners in both space and time. These are grouped spatially and temporally using a hierarchical process, with an increasing search area. At each stage of the hierarchy, the most distinctive and descriptive features are learned efficiently through data mining. This allows large amounts of data to be searched for frequently reoccurring patterns of features. At each level of the hierarchy, the mined compound features become more complex, discriminative, and sparse. This results in fast, accurate recognition with real-time performance on high-resolution video. As the compound features are constructed and selected based upon their ability to discriminate, their speed and accuracy increase at each level of the hierarchy. The approach is tested on four state-of-the-art data sets, the popular KTH data set to provide a comparison with other state-of-the-art approaches, the Multi-KTH data set to illustrate performance at simultaneous multiaction classification, despite no explicit localization information provided during training. Finally, the recent Hollywood and Hollywood2 data sets provide challenging complex actions taken from commercial movie sequences. For all four data sets, the proposed hierarchical approach outperforms all other methods reported thus far in the literature and can achieve real-time operation.

Use of designed sequences in protein structure recognition.

PubMed

Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

2018-05-09

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

Iris recognition based on key image feature extraction.

PubMed

Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

2008-01-01

In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

Quantum pattern recognition with multi-neuron interactions

NASA Astrophysics Data System (ADS)

Fard, E. Rezaei; Aghayar, K.; Amniat-Talab, M.

2018-03-01

We present a quantum neural network with multi-neuron interactions for pattern recognition tasks by a combination of extended classic Hopfield network and adiabatic quantum computation. This scheme can be used as an associative memory to retrieve partial patterns with any number of unknown bits. Also, we propose a preprocessing approach to classifying the pattern space S to suppress spurious patterns. The results of pattern clustering show that for pattern association, the number of weights (η ) should equal the numbers of unknown bits in the input pattern ( d). It is also remarkable that associative memory function depends on the location of unknown bits apart from the d and load parameter α.

Dictionary-driven prokaryotic gene finding

PubMed Central

Shibuya, Tetsuo; Rigoutsos, Isidore

2002-01-01

Gene identification, also known as gene finding or gene recognition, is among the important problems of molecular biology that have been receiving increasing attention with the advent of large scale sequencing projects. Previous strategies for solving this problem can be categorized into essentially two schools of thought: one school employs sequence composition statistics, whereas the other relies on database similarity searches. In this paper, we propose a new gene identification scheme that combines the best characteristics from each of these two schools. In particular, our method determines gene candidates among the ORFs that can be identified in a given DNA strand through the use of the Bio-Dictionary, a database of patterns that covers essentially all of the currently available sample of the natural protein sequence space. Our approach relies entirely on the use of redundant patterns as the agents on which the presence or absence of genes is predicated and does not employ any additional evidence, e.g. ribosome-binding site signals. The Bio-Dictionary Gene Finder (BDGF), the algorithm’s implementation, is a single computational engine able to handle the gene identification task across distinct archaeal and bacterial genomes. The engine exhibits performance that is characterized by simultaneous very high values of sensitivity and specificity, and a high percentage of correctly predicted start sites. Using a collection of patterns derived from an old (June 2000) release of the Swiss-Prot/TrEMBL database that contained 451 602 proteins and fragments, we demonstrate our method’s generality and capabilities through an extensive analysis of 17 complete archaeal and bacterial genomes. Examples of previously unreported genes are also shown and discussed in detail. PMID:12060689

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

Pathogen recognition of a novel C-type lectin from Marsupenaeus japonicus reveals the divergent sugar-binding specificity of QAP motif.

PubMed

Alenton, Rod Russel R; Koiwai, Keiichiro; Miyaguchi, Kohei; Kondo, Hidehiro; Hirono, Ikuo

2017-04-04

C-type lectins (CTLs) are calcium-dependent carbohydrate-binding proteins known to assist the innate immune system as pattern recognition receptors (PRRs). The binding specificity of CTLs lies in the motif of their carbohydrate recognition domain (CRD), the tripeptide motifs EPN and QPD bind to mannose and galactose, respectively. However, variants of these motifs were discovered including a QAP sequence reported in shrimp believed to have the same carbohydrate specificity as QPD. Here, we characterized a novel C-type lectin (MjGCTL) possessing a CRD with a QAP motif. The recombinant MjGCTL has a calcium-dependent agglutinating capability against both Gram-negative and Gram-positive bacteria, and its sugar specificity did not involve either mannose or galactose. In an encapsulation assay, agarose beads coated with rMjGCTL were immediately encapsulated from 0 h followed by melanization at 4 h post-incubation with hemocytes. These results confirm that MjGCTL functions as a classical CTL. The structure of QAP motif and carbohydrate-specificity of rMjGCTL was found to be different to both EPN and QPD, suggesting that QAP is a new motif. Furthermore, MjGCTL acts as a PRR binding to hemocytes to activate their adherent state and initiate encapsulation.

Pathogen recognition of a novel C-type lectin from Marsupenaeus japonicus reveals the divergent sugar-binding specificity of QAP motif

PubMed Central

Alenton, Rod Russel R.; Koiwai, Keiichiro; Miyaguchi, Kohei; Kondo, Hidehiro; Hirono, Ikuo

2017-01-01

C-type lectins (CTLs) are calcium-dependent carbohydrate-binding proteins known to assist the innate immune system as pattern recognition receptors (PRRs). The binding specificity of CTLs lies in the motif of their carbohydrate recognition domain (CRD), the tripeptide motifs EPN and QPD bind to mannose and galactose, respectively. However, variants of these motifs were discovered including a QAP sequence reported in shrimp believed to have the same carbohydrate specificity as QPD. Here, we characterized a novel C-type lectin (MjGCTL) possessing a CRD with a QAP motif. The recombinant MjGCTL has a calcium-dependent agglutinating capability against both Gram-negative and Gram-positive bacteria, and its sugar specificity did not involve either mannose or galactose. In an encapsulation assay, agarose beads coated with rMjGCTL were immediately encapsulated from 0 h followed by melanization at 4 h post-incubation with hemocytes. These results confirm that MjGCTL functions as a classical CTL. The structure of QAP motif and carbohydrate-specificity of rMjGCTL was found to be different to both EPN and QPD, suggesting that QAP is a new motif. Furthermore, MjGCTL acts as a PRR binding to hemocytes to activate their adherent state and initiate encapsulation. PMID:28374848

A bio-inspired system for spatio-temporal recognition in static and video imagery

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

2007-04-01

This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

Word Recognition in Auditory Cortex

ERIC Educational Resources Information Center

DeWitt, Iain D. J.

2013-01-01

Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…

Incoherent optical generalized Hough transform: pattern recognition and feature extraction applications

NASA Astrophysics Data System (ADS)

Fernández, Ariel; Ferrari, José A.

2017-05-01

Pattern recognition and feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital-only methods. We explore an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a pupil mask implemented on a high-contrast spatial light modulator for orientation/shape variation of the template. Real-time can also be achieved. In addition, by thresholding of the GHT and optically inverse transforming, the previously detected features of interest can be extracted.

33 CFR 104.220 - Company or vessel personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... the following, as appropriate: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Techniques used to circumvent security...

33 CFR 104.220 - Company or vessel personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... the following, as appropriate: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Techniques used to circumvent security...

Genetic dissection of the maize (Zea mays L.) MAMP response

USDA-ARS?s Scientific Manuscript database

Microbe-associated molecular patterns (MAMPs) are highly conserved molecules commonly found in microbes which can be recognized by plant pattern recognition receptors (PRRs). Recognition triggers a suite of responses including production of reactive oxygen species (ROS) and nitric oxide (NO) and ex...

The Functional Architecture of Visual Object Recognition

DTIC Science & Technology

1991-07-01

different forms of agnosia can provide clues to the representations underlying normal object recognition (Farah, 1990). For example, the pair-wise...patterns of deficit and sparing occur. In a review of 99 published cases of agnosia , the observed patterns of co- occurrence implicated two underlying

Utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information

DOT National Transportation Integrated Search

2009-01-01

This report describes a study conducted to explore the utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information. The study gathered data from a large number of pilots who conduct all type...

Spatial pattern recognition of seismic events in South West Colombia

NASA Astrophysics Data System (ADS)

Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

2013-09-01

Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

Multivariate pattern recognition for diagnosis and prognosis in clinical neuroimaging: state of the art, current challenges and future trends.

PubMed

Haller, Sven; Lovblad, Karl-Olof; Giannakopoulos, Panteleimon; Van De Ville, Dimitri

2014-05-01

Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.

Molecular Recognition Profiles and Clinical Patterns of PR-10 Sensitization in a Birch-Free Mediterranean Area.

PubMed

Scala, Enrico; Abeni, Damiano; Cecchi, Lorenzo; Guerra, Emma Cristina; Locanto, Maria; Pirrotta, Lia; Giani, Mauro; Asero, Riccardo

2017-01-01

The order Fagales represents an important cause of tree-pollen allergy in northern countries. We investigated the IgE recognition profiles, mutual relationships, and association with clinical symptoms of a panel of allergens belonging to the PR-10 family, the main proteins responsible for Fagales allergy (Act d 8, Aln g 1, Api g 1, Ara h 8, Bet v 1, Cor a 1.0101, Cor a 1.0401, Gly m 4, Mal d 1, and Pru p 1). A total of 526 PR-10-reactive subjects living in central and southern Italy were studied by ImmunoCAP-ISAC-112 microarray analysis. Overall, Bet v 1 reactivity was the most commonly (74%) observed among PR-10 proteins, but Cor a 1.0101 was the most prevalent in participants aged <6 years, and between 15 and 65 years. Overall, 26% of the PR-10-reactive persons were Bet v 1 negative, whilst 93.6% of the PR-10 polyreactive individuals were Bet v 1 positive. Among the 10 PR-10s evaluated, 100 combinations were recorded. The strongest association was observed between molecules with the highest sequence identities (Bet v 1 and Cor a 1.0101, Cor a 1.0401 or Aln g 1; Mal d 1 and Pru p 1). Bet v 1-, Cor a 1.0101-, and Aln g 1-specific IgE recognition was associated with respiratory symptoms, whilst Ara h 8, Cor a 1.0401, Gly m 4, Mal d 1, and Pru p 1 were selectively linked to an oral allergic syndrome. Testing IgE reactivity to a panel of PR-10s in a birch-free area discloses peculiar relationships between clinical phenotypes and sensitization profiles, allowing the identification of novel cluster patterns. © 2017 S. Karger AG, Basel.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Study and response time for the visual recognition of 'similarity' and identity

NASA Technical Reports Server (NTRS)

Derks, P. L.; Bauer, T. M.

1974-01-01

Four subjects compared successively presented pairs of line patterns for a match between any lines in the pattern (similarity) and for a match between all lines (identity). The encoding or study times for pattern recognition from immediate memory and the latency in responses to comparison stimuli were examined. Qualitative differences within and between subjects were most evident in study times.

Hypothesis Support Mechanism for Mid-Level Visual Pattern Recognition

NASA Technical Reports Server (NTRS)

Amador, Jose J (Inventor)

2007-01-01

A method of mid-level pattern recognition provides for a pose invariant Hough Transform by parametrizing pairs of points in a pattern with respect to at least two reference points, thereby providing a parameter table that is scale- or rotation-invariant. A corresponding inverse transform may be applied to test hypothesized matches in an image and a distance transform utilized to quantify the level of match.

Sequence-Specific Recognition of DNA by Proteins: Binding Motifs Discovered Using a Novel Statistical/Computational Analysis

PubMed Central

Jakubec, David; Laskowski, Roman A.; Vondrasek, Jiri

2016-01-01

Decades of intensive experimental studies of the recognition of DNA sequences by proteins have provided us with a view of a diverse and complicated world in which few to no features are shared between individual DNA-binding protein families. The originally conceived direct readout of DNA residue sequences by amino acid side chains offers very limited capacity for sequence recognition, while the effects of the dynamic properties of the interacting partners remain difficult to quantify and almost impossible to generalise. In this work we investigated the energetic characteristics of all DNA residue—amino acid side chain combinations in the conformations found at the interaction interface in a very large set of protein—DNA complexes by the means of empirical potential-based calculations. General specificity-defining criteria were derived and utilised to look beyond the binding motifs considered in previous studies. Linking energetic favourability to the observed geometrical preferences, our approach reveals several additional amino acid motifs which can distinguish between individual DNA bases. Our results remained valid in environments with various dielectric properties. PMID:27384774

Identification of Biomolecular Building Blocks by Recognition Tunneling: Stride towards Nanopore Sequencing of Biomolecules

NASA Astrophysics Data System (ADS)

Sen, Suman

DNA, RNA and Protein are three pivotal biomolecules in human and other organisms, playing decisive roles in functionality, appearance, diseases development and other physiological phenomena. Hence, sequencing of these biomolecules acquires the prime interest in the scientific community. Single molecular identification of their building blocks can be done by a technique called Recognition Tunneling (RT) based on Scanning Tunneling Microscope (STM). A single layer of specially designed recognition molecule is attached to the STM electrodes, which trap the targeted molecules (DNA nucleoside monophosphates, RNA nucleoside monophosphates or amino acids) inside the STM nanogap. Depending on their different binding interactions with the recognition molecules, the analyte molecules generate stochastic signal trains accommodating their "electronic fingerprints". Signal features are used to detect the molecules using a machine learning algorithm and different molecules can be identified with significantly high accuracy. This, in turn, paves the way for rapid, economical nanopore sequencing platform, overcoming the drawbacks of Next Generation Sequencing (NGS) techniques. To read DNA nucleotides with high accuracy in an STM tunnel junction a series of nitrogen-based heterocycles were designed and examined to check their capabilities to interact with naturally occurring DNA nucleotides by hydrogen bonding in the tunnel junction. These recognition molecules are Benzimidazole, Imidazole, Triazole and Pyrrole. Benzimidazole proved to be best among them showing DNA nucleotide classification accuracy close to 99%. Also, Imidazole reader can read an abasic monophosphate (AP), a product from depurination or depyrimidination that occurs 10,000 times per human cell per day. In another study, I have investigated a new universal reader, 1-(2-mercaptoethyl)pyrene (Pyrene reader) based on stacking interactions, which should be more specific to the canonical DNA nucleosides. In addition, Pyrene reader showed higher DNA base-calling accuracy compare to Imidazole reader, the workhorse in our previous projects. In my other projects, various amino acids and RNA nucleoside monophosphates were also classified with significantly high accuracy using RT. Twenty naturally occurring amino acids and various RNA nucleosides (four canonical and two modified) were successfully identified. Thus, we envision nanopore sequencing biomolecules using Recognition Tunneling (RT) that should provide comprehensive betterment over current technologies in terms of time, chemical and instrumental cost and capability of de novo sequencing.

An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Kim, Hye-Young; Junkins, John L.

2003-01-01

A new star pattern recognition method is developed using singular value decomposition of a measured unit column vector matrix in a measurement frame and the corresponding cataloged vector matrix in a reference frame. It is shown that singular values and right singular vectors are invariant with respect to coordinate transformation and robust under uncertainty. One advantage of singular value comparison is that a pairing process for individual measured and cataloged stars is not necessary, and the attitude estimation and pattern recognition process are not separated. An associated method for mission catalog design is introduced and simulation results are presented.

Fourier transform magnitudes are unique pattern recognition templates.

PubMed

Gardenier, P H; McCallum, B C; Bates, R H

1986-01-01

Fourier transform magnitudes are commonly used in the generation of templates in pattern recognition applications. We report on recent advances in Fourier phase retrieval which are relevant to pattern recognition. We emphasise in particular that the intrinsic form of a finite, positive image is, in general, uniquely related to the magnitude of its Fourier transform. We state conditions under which the Fourier phase can be reconstructed from samples of the Fourier magnitude, and describe a method of achieving this. Computational examples of restoration of Fourier phase (and hence, by Fourier transformation, the intrinsic form of the image) from samples of the Fourier magnitude are also presented.

Detection and recognition of analytes based on their crystallization patterns

DOEpatents

Morozov, Victor [Manassas, VA; Bailey, Charles L [Cross Junction, VA; Vsevolodov, Nikolai N [Kensington, MD; Elliott, Adam [Manassas, VA

2008-05-06

The invention contemplates a method for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization pattern") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. It has been shown that changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. It was also found that both the character of changer in the crystallization patter and the fact of such changes can be used as recognition elements in analysis of protein molecules.

Recognition of neural brain activity patterns correlated with complex motor activity

NASA Astrophysics Data System (ADS)

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.

Perception of pathogenic or beneficial bacteria and their evasion of host immunity: pattern recognition receptors in the frontline

PubMed Central

Trdá, Lucie; Boutrot, Freddy; Claverie, Justine; Brulé, Daphnée; Dorey, Stephan; Poinssot, Benoit

2015-01-01

Plants are continuously monitoring the presence of microorganisms to establish an adapted response. Plants commonly use pattern recognition receptors (PRRs) to perceive microbe- or pathogen-associated molecular patterns (MAMPs/PAMPs) which are microorganism molecular signatures. Located at the plant plasma membrane, the PRRs are generally receptor-like kinases (RLKs) or receptor-like proteins (RLPs). MAMP detection will lead to the establishment of a plant defense program called MAMP-triggered immunity (MTI). In this review, we overview the RLKs and RLPs that assure early recognition and control of pathogenic or beneficial bacteria. We also highlight the crucial function of PRRs during plant-microbe interactions, with a special emphasis on the receptors of the bacterial flagellin and peptidoglycan. In addition, we discuss the multiple strategies used by bacteria to evade PRR-mediated recognition. PMID:25904927

Peptidoglycan recognition proteins in Drosophila immunity.

PubMed

Kurata, Shoichiro

2014-01-01

Innate immunity is the front line of self-defense against infectious non-self in vertebrates and invertebrates. The innate immune system is mediated by germ-line encoding pattern recognition molecules (pathogen sensors) that recognize conserved molecular patterns present in the pathogens but absent in the host. Peptidoglycans (PGN) are essential cell wall components of almost all bacteria, except mycoplasma lacking a cell wall, which provides the host immune system an advantage for detecting invading bacteria. Several families of pattern recognition molecules that detect PGN and PGN-derived compounds have been indentified, and the role of PGRP family members in host defense is relatively well-characterized in Drosophila. This review focuses on the role of PGRP family members in the recognition of invading bacteria and the activation and modulation of immune responses in Drosophila. Copyright © 2013 Elsevier Ltd. All rights reserved.

Automatic micropropagation of plants--the vision-system: graph rewriting as pattern recognition

NASA Astrophysics Data System (ADS)

Schwanke, Joerg; Megnet, Roland; Jensch, Peter F.

1993-03-01

The automation of plant-micropropagation is necessary to produce high amounts of biomass. Plants have to be dissected on particular cutting-points. A vision-system is needed for the recognition of the cutting-points on the plants. With this background, this contribution is directed to the underlying formalism to determine cutting-points on abstract-plant models. We show the usefulness of pattern recognition by graph-rewriting along with some examples in this context.

Age-related increases in false recognition: the role of perceptual and conceptual similarity.

PubMed

Pidgeon, Laura M; Morcom, Alexa M

2014-01-01

Older adults (OAs) are more likely to falsely recognize novel events than young adults, and recent behavioral and neuroimaging evidence points to a reduced ability to distinguish overlapping information due to decline in hippocampal pattern separation. However, other data suggest a critical role for semantic similarity. Koutstaal et al. [(2003) false recognition of abstract vs. common objects in older and younger adults: testing the semantic categorization account, J. Exp. Psychol. Learn. 29, 499-510] reported that OAs were only vulnerable to false recognition of items with pre-existing semantic representations. We replicated Koutstaal et al.'s (2003) second experiment and examined the influence of independently rated perceptual and conceptual similarity between stimuli and lures. At study, young and OAs judged the pleasantness of pictures of abstract (unfamiliar) and concrete (familiar) items, followed by a surprise recognition test including studied items, similar lures, and novel unrelated items. Experiment 1 used dichotomous "old/new" responses at test, while in Experiment 2 participants were also asked to judge lures as "similar," to increase explicit demands on pattern separation. In both experiments, OAs showed a greater increase in false recognition for concrete than abstract items relative to the young, replicating Koutstaal et al.'s (2003) findings. However, unlike in the earlier study, there was also an age-related increase in false recognition of abstract lures when multiple similar images had been studied. In line with pattern separation accounts of false recognition, OAs were more likely to misclassify concrete lures with high and moderate, but not low degrees of rated similarity to studied items. Results are consistent with the view that OAs are particularly susceptible to semantic interference in recognition memory, and with the possibility that this reflects age-related decline in pattern separation.

Age-related increases in false recognition: the role of perceptual and conceptual similarity

PubMed Central

Pidgeon, Laura M.; Morcom, Alexa M.

2014-01-01

Older adults (OAs) are more likely to falsely recognize novel events than young adults, and recent behavioral and neuroimaging evidence points to a reduced ability to distinguish overlapping information due to decline in hippocampal pattern separation. However, other data suggest a critical role for semantic similarity. Koutstaal et al. [(2003) false recognition of abstract vs. common objects in older and younger adults: testing the semantic categorization account, J. Exp. Psychol. Learn. 29, 499–510] reported that OAs were only vulnerable to false recognition of items with pre-existing semantic representations. We replicated Koutstaal et al.’s (2003) second experiment and examined the influence of independently rated perceptual and conceptual similarity between stimuli and lures. At study, young and OAs judged the pleasantness of pictures of abstract (unfamiliar) and concrete (familiar) items, followed by a surprise recognition test including studied items, similar lures, and novel unrelated items. Experiment 1 used dichotomous “old/new” responses at test, while in Experiment 2 participants were also asked to judge lures as “similar,” to increase explicit demands on pattern separation. In both experiments, OAs showed a greater increase in false recognition for concrete than abstract items relative to the young, replicating Koutstaal et al.’s (2003) findings. However, unlike in the earlier study, there was also an age-related increase in false recognition of abstract lures when multiple similar images had been studied. In line with pattern separation accounts of false recognition, OAs were more likely to misclassify concrete lures with high and moderate, but not low degrees of rated similarity to studied items. Results are consistent with the view that OAs are particularly susceptible to semantic interference in recognition memory, and with the possibility that this reflects age-related decline in pattern separation. PMID:25368576

Song pattern recognition in crickets based on a delay-line and coincidence-detector mechanism

PubMed Central

Sarmiento-Ponce, Edith Julieta

2017-01-01

Acoustic communication requires filter mechanisms to process and recognize key features of the perceived signals. We analysed such a filter mechanism in field crickets (Gryllus bimaculatus), which communicate with species-specific repetitive patterns of sound pulses and chirps. A delay-line and coincidence-detection mechanism, in which each sound pulse has an impact on the processing of the following pulse, is implicated to underlie the recognition of the species-specific pulse pattern. Based on this concept, we hypothesized that altering the duration of a single pulse or inter-pulse interval in three-pulse chirps will lead to different behavioural responses. Phonotaxis was tested in female crickets walking on a trackball exposed to different sound paradigms. Changing the duration of either the first, second or third pulse of the chirps led to three different characteristic tuning curves. Long first pulses decreased the phonotactic response whereas phonotaxis remained strong when the third pulse was long. Chirps with three pulses of increasing duration of 5, 20 and 50 ms elicited phonotaxis, but the chirps were not attractive when played in reverse order. This demonstrates specific, pulse duration-dependent effects while sequences of pulses are processed. The data are in agreement with a mechanism in which processing of a sound pulse has an effect on the processing of the subsequent pulse, as outlined in the flow of activity in a delay-line and coincidence-detector circuit. Additionally our data reveal a substantial increase in the gain of phonotaxis, when the number of pulses of a chirp is increased from two to three. PMID:28539524

Song pattern recognition in crickets based on a delay-line and coincidence-detector mechanism.

PubMed

Hedwig, Berthold; Sarmiento-Ponce, Edith Julieta

2017-05-31

Acoustic communication requires filter mechanisms to process and recognize key features of the perceived signals. We analysed such a filter mechanism in field crickets ( Gryllus bimaculatus ), which communicate with species-specific repetitive patterns of sound pulses and chirps. A delay-line and coincidence-detection mechanism, in which each sound pulse has an impact on the processing of the following pulse, is implicated to underlie the recognition of the species-specific pulse pattern. Based on this concept, we hypothesized that altering the duration of a single pulse or inter-pulse interval in three-pulse chirps will lead to different behavioural responses. Phonotaxis was tested in female crickets walking on a trackball exposed to different sound paradigms. Changing the duration of either the first, second or third pulse of the chirps led to three different characteristic tuning curves. Long first pulses decreased the phonotactic response whereas phonotaxis remained strong when the third pulse was long. Chirps with three pulses of increasing duration of 5, 20 and 50 ms elicited phonotaxis, but the chirps were not attractive when played in reverse order. This demonstrates specific, pulse duration-dependent effects while sequences of pulses are processed. The data are in agreement with a mechanism in which processing of a sound pulse has an effect on the processing of the subsequent pulse, as outlined in the flow of activity in a delay-line and coincidence-detector circuit. Additionally our data reveal a substantial increase in the gain of phonotaxis, when the number of pulses of a chirp is increased from two to three. © 2017 The Authors.

Music Perception in Dementia.

PubMed

Golden, Hannah L; Clark, Camilla N; Nicholas, Jennifer M; Cohen, Miriam H; Slattery, Catherine F; Paterson, Ross W; Foulkes, Alexander J M; Schott, Jonathan M; Mummery, Catherine J; Crutch, Sebastian J; Warren, Jason D

2017-01-01

Despite much recent interest in music and dementia, music perception has not been widely studied across dementia syndromes using an information processing approach. Here we addressed this issue in a cohort of 30 patients representing major dementia syndromes of typical Alzheimer's disease (AD, n = 16), logopenic aphasia (LPA, an Alzheimer variant syndrome; n = 5), and progressive nonfluent aphasia (PNFA; n = 9) in relation to 19 healthy age-matched individuals. We designed a novel neuropsychological battery to assess perception of musical patterns in the dimensions of pitch and temporal information (requiring detection of notes that deviated from the established pattern based on local or global sequence features) and musical scene analysis (requiring detection of a familiar tune within polyphonic harmony). Performance on these tests was referenced to generic auditory (timbral) deviance detection and recognition of familiar tunes and adjusted for general auditory working memory performance. Relative to healthy controls, patients with AD and LPA had group-level deficits of global pitch (melody contour) processing while patients with PNFA as a group had deficits of local (interval) as well as global pitch processing. There was substantial individual variation within syndromic groups. Taking working memory performance into account, no specific deficits of musical temporal processing, timbre processing, musical scene analysis, or tune recognition were identified. The findings suggest that particular aspects of music perception such as pitch pattern analysis may open a window on the processing of information streams in major dementia syndromes. The potential selectivity of musical deficits for particular dementia syndromes and particular dimensions of processing warrants further systematic investigation.

Image-based automatic recognition of larvae

NASA Astrophysics Data System (ADS)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Enemy at the gates: traffic at the plant cell pathogen interface.

PubMed

Hoefle, Caroline; Hückelhoven, Ralph

2008-12-01

The plant apoplast constitutes a space for early recognition of potentially harmful non-self. Basal pathogen recognition operates via dynamic sensing of conserved microbial patterns by pattern recognition receptors or of elicitor-active molecules released from plant cell walls during infection. Recognition elicits defence reactions depending on cellular export via SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) complex-mediated vesicle fusion or plasma membrane transporter activity. Lipid rafts appear also involved in focusing immunity-associated proteins to the site of pathogen contact. Simultaneously, pathogen effectors target recognition, apoplastic host proteins and transport for cell wall-associated defence. This microreview highlights most recent reports on the arms race for plant disease and immunity at the cell surface.

Mitochondrial genome sequencing reveals potential origins of the scabies mite Sarcoptes scabiei infesting two iconic Australian marsupials.

PubMed

Fraser, Tamieka A; Shao, Renfu; Fountain-Jones, Nicholas M; Charleston, Michael; Martin, Alynn; Whiteley, Pam; Holme, Roz; Carver, Scott; Polkinghorne, Adam

2017-11-28

Debilitating skin infestations caused by the mite, Sarcoptes scabiei, have a profound impact on human and animal health globally. In Australia, this impact is evident across different segments of Australian society, with a growing recognition that it can contribute to rapid declines of native Australian marsupials. Cross-host transmission has been suggested to play a significant role in the epidemiology and origin of mite infestations in different species but a chronic lack of genetic resources has made further inferences difficult. To investigate the origins and molecular epidemiology of S. scabiei in Australian wildlife, we sequenced the mitochondrial genomes of S. scabiei from diseased wombats (Vombatus ursinus) and koalas (Phascolarctos cinereus) spanning New South Wales, Victoria and Tasmania, and compared them with the recently sequenced mitochondrial genome sequences of S. scabiei from humans. We found unique S. scabiei haplotypes among individual wombat and koala hosts with high sequence similarity (99.1% - 100%). Phylogenetic analysis of near full-length mitochondrial genomes revealed three clades of S. scabiei (one human and two marsupial), with no apparent geographic or host species pattern, suggestive of multiple introductions. The availability of additional mitochondrial gene sequences also enabled a re-evaluation of a range of putative molecular markers of S. scabiei, revealing that cox1 is the most informative gene for molecular epidemiological investigations. Utilising this gene target, we provide additional evidence to support cross-host transmission between different animal hosts. Our results suggest a history of parasite invasion through colonisation of Australia from hosts across the globe and the potential for cross-host transmission being a common feature of the epidemiology of this neglected pathogen. If this is the case, comparable patterns may exist elsewhere in the 'New World'. This work provides a basis for expanded molecular studies into mange epidemiology in humans and animals in Australia and other geographic regions.

Geographic Patterns of Genetic Variation in a Broadly Distributed Marine Vertebrate: New Insights into Loggerhead Turtle Stock Structure from Expanded Mitochondrial DNA Sequences

PubMed Central

Shamblin, Brian M.; Bolten, Alan B.; Abreu-Grobois, F. Alberto; Bjorndal, Karen A.; Cardona, Luis; Carreras, Carlos; Clusa, Marcel; Monzón-Argüello, Catalina; Nairn, Campbell J.; Nielsen, Janne T.; Nel, Ronel; Soares, Luciano S.; Stewart, Kelly R.; Vilaça, Sibelle T.; Türkozan, Oguz; Yilmaz, Can; Dutton, Peter H.

2014-01-01

Previous genetic studies have demonstrated that natal homing shapes the stock structure of marine turtle nesting populations. However, widespread sharing of common haplotypes based on short segments of the mitochondrial control region often limits resolution of the demographic connectivity of populations. Recent studies employing longer control region sequences to resolve haplotype sharing have focused on regional assessments of genetic structure and phylogeography. Here we synthesize available control region sequences for loggerhead turtles from the Mediterranean Sea, Atlantic, and western Indian Ocean basins. These data represent six of the nine globally significant regional management units (RMUs) for the species and include novel sequence data from Brazil, Cape Verde, South Africa and Oman. Genetic tests of differentiation among 42 rookeries represented by short sequences (380 bp haplotypes from 3,486 samples) and 40 rookeries represented by long sequences (∼800 bp haplotypes from 3,434 samples) supported the distinction of the six RMUs analyzed as well as recognition of at least 18 demographically independent management units (MUs) with respect to female natal homing. A total of 59 haplotypes were resolved. These haplotypes belonged to two highly divergent global lineages, with haplogroup I represented primarily by CC-A1, CC-A4, and CC-A11 variants and haplogroup II represented by CC-A2 and derived variants. Geographic distribution patterns of haplogroup II haplotypes and the nested position of CC-A11.6 from Oman among the Atlantic haplotypes invoke recent colonization of the Indian Ocean from the Atlantic for both global lineages. The haplotypes we confirmed for western Indian Ocean RMUs allow reinterpretation of previous mixed stock analysis and further suggest that contemporary migratory connectivity between the Indian and Atlantic Oceans occurs on a broader scale than previously hypothesized. This study represents a valuable model for conducting comprehensive international cooperative data management and research in marine ecology. PMID:24465810

Recognition, correlation, and hierarchical stacking patterns of cycles in the Ferry Lake - Uppe Glen Rose, East Texas Basin: Implications for grainstone reservoir distribution

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

Fitchen, W.M.; Bebout, D.G.; Hoffman, C.L.

1994-12-31

Core descriptions and regional log correlation/interpretation of Ferry Lake-Upper Glen Rose strata in the East Texas Basin exhibit the uniformity of cyclicity in these shelf units. The cyclicity is defined by an upward decrease in shale content within each cycle accompanied by an upward increase in anhydrite (Ferry Lake) or carbonate (Upper Glen Rose). Core-to-log calibration of facies indicates that formation resistivity is inversely proportional to shale content and thus is a potential proxy for facies identification beyond core control. Cycles (delineated by resistivity log patterns) were correlated for 90 mi across the shelf; they show little change in logmore » signature despite significant updip thinning due to the regional subsidence gradient. The Ferry-Lake-Upper Glen Rose intervals is interpreted as a composite sequence composed of 13 high-frequency sequences (4 in the Ferry Lake and 9 in the Upper Glen Rose). High-frequency sequences contain approximately 20 ({+-}5) cycles; in the Upper Glen Rose, successive cycles exhibit decreasing proportions of shale and increasing proportions of grain-rich carbonate. High-frequency sequences were terminated by terrigenous inundation, possibly preceded by subaerial exposure. Cycle and high-frequency sequence composition is interpreted to reflect composite, periodic(?) fluctuations is terrigeneous dilution from nearby source areas. Grainstones typically occur (stratigraphically) within the upper cycles of high-frequency sequences, where terrigeneous dilution and turbidity were least and potential for carbonate production and shoaling was greatest. Published mid-Cretaceous geographic reconstructions and climate models suggest that precipitation and runoff in the area were controlled by the seasonal amplitude in solar insolation. In this model, orbital variations, combined with subsidence, hydrography, and bathymetry, were in primary controls on Ferry Lake-Upper Glen Rose facies architecture and stratigraphic development.« less

Utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information

DOT National Transportation Integrated Search

2009-04-28

A study was conducted to explore the utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information, such as electronic charts and moving map displays. The goal of this research is to support t...

Analysis of chemical signals in red fire ants by gas chromatography and pattern recognition techniques

USDA-ARS?s Scientific Manuscript database

The combination of gas chromatography and pattern recognition (GC/PR) analysis is a powerful tool for investigating complicated biological problems. Clustering, mapping, discriminant development, etc. are necessary to analyze realistically large chromatographic data sets and to seek meaningful relat...

Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns.

PubMed

Viswanathan, Jayalakshmi; Rémy, Florence; Bacon-Macé, Nadège; Thorpe, Simon J

2016-01-01

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10- and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities. Significance Statement Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities.

Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns

PubMed Central

Viswanathan, Jayalakshmi; Rémy, Florence; Bacon-Macé, Nadège; Thorpe, Simon J.

2016-01-01

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10− and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities. Significance Statement Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities. PMID:27932941

Learning and Recognition of a Non-conscious Sequence of Events in Human Primary Visual Cortex.

PubMed

Rosenthal, Clive R; Andrews, Samantha K; Antoniades, Chrystalina A; Kennard, Christopher; Soto, David

2016-03-21

Human primary visual cortex (V1) has long been associated with learning simple low-level visual discriminations [1] and is classically considered outside of neural systems that support high-level cognitive behavior in contexts that differ from the original conditions of learning, such as recognition memory [2, 3]. Here, we used a novel fMRI-based dichoptic masking protocol-designed to induce activity in V1, without modulation from visual awareness-to test whether human V1 is implicated in human observers rapidly learning and then later (15-20 min) recognizing a non-conscious and complex (second-order) visuospatial sequence. Learning was associated with a change in V1 activity, as part of a temporo-occipital and basal ganglia network, which is at variance with the cortico-cerebellar network identified in prior studies of "implicit" sequence learning that involved motor responses and visible stimuli (e.g., [4]). Recognition memory was associated with V1 activity, as part of a temporo-occipital network involving the hippocampus, under conditions that were not imputable to mechanisms associated with conscious retrieval. Notably, the V1 responses during learning and recognition separately predicted non-conscious recognition memory, and functional coupling between V1 and the hippocampus was enhanced for old retrieval cues. The results provide a basis for novel hypotheses about the signals that can drive recognition memory, because these data (1) identify human V1 with a memory network that can code complex associative serial visuospatial information and support later non-conscious recognition memory-guided behavior (cf. [5]) and (2) align with mouse models of experience-dependent V1 plasticity in learning and memory [6]. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular population dynamics of DNA structures in a bcl-2 promoter sequence is regulated by small molecules and the transcription factor hnRNP LL.

PubMed

Cui, Yunxi; Koirala, Deepak; Kang, HyunJin; Dhakal, Soma; Yangyuoru, Philip; Hurley, Laurence H; Mao, Hanbin

2014-05-01

Minute difference in free energy change of unfolding among structures in an oligonucleotide sequence can lead to a complex population equilibrium, which is rather challenging for ensemble techniques to decipher. Herein, we introduce a new method, molecular population dynamics (MPD), to describe the intricate equilibrium among non-B deoxyribonucleic acid (DNA) structures. Using mechanical unfolding in laser tweezers, we identified six DNA species in a cytosine (C)-rich bcl-2 promoter sequence. Population patterns of these species with and without a small molecule (IMC-76 or IMC-48) or the transcription factor hnRNP LL are compared to reveal the MPD of different species. With a pattern recognition algorithm, we found that IMC-48 and hnRNP LL share 80% similarity in stabilizing i-motifs with 60 s incubation. In contrast, IMC-76 demonstrates an opposite behavior, preferring flexible DNA hairpins. With 120-180 s incubation, IMC-48 and hnRNP LL destabilize i-motifs, which has been previously proposed to activate bcl-2 transcriptions. These results provide strong support, from the population equilibrium perspective, that small molecules and hnRNP LL can modulate bcl-2 transcription through interaction with i-motifs. The excellent agreement with biochemical results firmly validates the MPD analyses, which, we expect, can be widely applicable to investigate complex equilibrium of biomacromolecules. © 2014 The Author(s). Published by Oxford University Press [on behalf of Nucleic Acids Research].

Cutaneous Nod2 Expression Regulates the Skin Microbiome and Wound Healing in a Murine Model.

PubMed

Williams, Helen; Crompton, Rachel A; Thomason, Helen A; Campbell, Laura; Singh, Gurdeep; McBain, Andrew J; Cruickshank, Sheena M; Hardman, Matthew J

2017-11-01

The skin microbiome exists in dynamic equilibrium with the host, but when the skin is compromised, bacteria can colonize the wound and impair wound healing. Thus, the interplay between normal skin microbial interactions versus pathogenic microbial interactions in wound repair is important. Bacteria are recognized by innate host pattern recognition receptors, and we previously showed an important role for the pattern recognition receptor NOD2 in skin wound repair. NOD2 is implicated in changes in the composition of the intestinal microbiota in Crohn's disease, but its role on skin microbiota is unknown. Nod2-deficient (Nod2 -/- ) mice had an inherently altered skin microbiome compared with wild-type controls. Furthermore, we found that Nod2 -/- skin microbiome dominated and caused impaired healing, shown in cross-fostering experiments of wild-type pups with Nod2 -/- pups, which then acquired altered cutaneous bacteria and delayed healing. High-throughput sequencing and quantitative real-time PCR showed a significant compositional shift, specifically in the genus Pseudomonas in Nod2 -/- mice. To confirm whether Pseudomonas species directly impair wound healing, wild-type mice were infected with Pseudomonas aeruginosa biofilms and, akin to Nod2 -/- mice, were found to exhibit a significant delay in wound repair. Collectively, these studies show the importance of the microbial communities in skin wound healing outcome. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

MAMPs and MIMPs: proposed classifications for inducers of innate immunity.

PubMed

Mackey, David; McFall, Aidan J

2006-09-01

Plants encode a sophisticated innate immune system. Resistance against potential pathogens often relies on active responses. Prerequisite to the induction of defences is recognition of the pathogenic threat. Significant advances have been made in our understanding of the non-self molecules that are recognized by plants and the means by which plants perceive them. Established terms describing these recognition events, including microbe-associated molecular pattern (MAMP), MAMP-receptor, effector, and resistance (R) protein, need clarification to represent our current knowledge adequately. In this review we propose criteria to classify inducers of plant defence as either MAMPs or microbe-induced molecular patterns (MIMPs). We refine the definition of MAMP to mean a molecular sequence or structure in ANY pathogen-derived molecule that is perceived via direct interaction with a host defence receptor. MIMPs are modifications of host-derived molecules that are induced by an intrinsic activity of a pathogen-derived effector and are perceived by a host defence receptor. MAMP-receptors have previously been classified separately from R-proteins as a discrete class of surveillance molecules. However, MAMP-receptors and R-proteins cannot be distinguished on the basis of their protein structures or their induced responses. We propose that MAMP-receptors and MIMP-receptors are each a subset of R-proteins. Although our review is based on examples from plant pathogens and plants, the principles discussed might prove applicable to other organisms.

Identification of full length bovine TLR1 and functional characterization of lipopeptide recognition by bovine TLR2/1 heterodimer

PubMed Central

Farhat, Katja; Riekenberg, Sabine; Jung, Günther; Wiesmüller, Karl-Heinz; Jungi, Thomas W.; Ulmer, Artur J.

2010-01-01

Toll-like receptors (TLR) are highly conserved pattern recognition receptors of the innate immune system. Toll-like receptor 2 (TLR2) recognizes bacterial lipopeptides in a heterodimeric complex with TLR6 or TLR1, thereby discriminating between di- or triacylated lipopeptides, respectively. Previously, we found that HEK293 cells transfected with bovine TLR2 (boTLR2) were able to respond to diacylated lipopeptides but did not recognize triacylated lipopeptides, even after cotransfection with the so far published sequence of boTLR1. In this study we now could show that primary bovine cells were in general able to detect triacylated lipopetides. A closer investigation of the boTLR1 gene locus revealed an additional ATG 195 base pairs upstream from the published start codon. Its transcription would result in an N-terminus with high identity to human and murine TLR1 (huTLR1, muTLR1). Cloning and cotransfection of this longer boTLR1 with boTLR2 now resulted in the recognition of triacylated lipopeptides by HEK293 cells, thereby resembling the ex vivo observation. Analysis of the structure-activity relationship showed that the ester-bound acid chains of these lipopeptides need to consist of at least 12 carbon atoms to activate the bovine heterodimer showing similarity to the recognition by huTLR2/huTLR1. In contrast, HEK293 cell cotransfected with muTLR2 and muTLR1 could already be activated by lipopeptides with shorter fatty acids of only 6 carbon atoms. Thus, our data indicate that the additional N-terminal nucleotides belong to the full length and functionally active boTLR1 (boTLR1-fl) which participates in a species-specific recognition of bacterial lipopeptides. PMID:20167196

Chemical modifications of Au/SiO2 template substrates for patterned biofunctional surfaces.

PubMed

Briand, Elisabeth; Humblot, Vincent; Landoulsi, Jessem; Petronis, Sarunas; Pradier, Claire-Marie; Kasemo, Bengt; Svedhem, Sofia

2011-01-18

The aim of this work was to create patterned surfaces for localized and specific biochemical recognition. For this purpose, we have developed a protocol for orthogonal and material-selective surface modifications of microfabricated patterned surfaces composed of SiO(2) areas (100 μm diameter) surrounded by Au. The SiO(2) spots were chemically modified by a sequence of reactions (silanization using an amine-terminated silane (APTES), followed by amine coupling of a biotin analogue and biospecific recognition) to achieve efficient immobilization of streptavidin in a functional form. The surrounding Au was rendered inert to protein adsorption by modification by HS(CH(2))(10)CONH(CH(2))(2)(OCH(2)CH(2))(7)OH (thiol-OEG). The surface modification protocol was developed by testing separately homogeneous SiO(2) and Au surfaces, to obtain the two following results: (i) SiO(2) surfaces which allowed the grafting of streptavidin, and subsequent immobilization of biotinylated antibodies, and (ii) Au surfaces showing almost no affinity for the same streptavidin and antibody solutions. The surface interactions were monitored by quartz crystal microbalance with dissipation monitoring (QCM-D), and chemical analyses were performed by polarization modulation-reflexion absorption infrared spectroscopy (PM-RAIRS) and X-ray photoelectron spectroscopy (XPS) to assess the validity of the initial orthogonal assembly of APTES and thiol-OEG. Eventually, microscopy imaging of the modified Au/SiO(2) patterned substrates validated the specific binding of streptavidin on the SiO(2)/APTES areas, as well as the subsequent binding of biotinylated anti-rIgG and further detection of fluorescent rIgG on the functionalized SiO(2) areas. These results demonstrate a successful protocol for the preparation of patterned biofunctional surfaces, based on microfabricated Au/SiO(2) templates and supported by careful surface analysis. The strong immobilization of the biomolecules resulting from the described protocol is advantageous in particular for micropatterned substrates for cell-surface interactions.

The Psychophysics of Algebra Expertise: Mathematics Perceptual Learning Interventions Produce Durable Encoding Changes

ERIC Educational Resources Information Center

Bufford, Carolyn A.; Mettler, Everett; Geller, Emma H.; Kellman, Philip J.

2014-01-01

Mathematics requires thinking but also pattern recognition. Recent research indicates that perceptual learning (PL) interventions facilitate discovery of structure and recognition of patterns in mathematical domains, as assessed by tests of mathematical competence. Here we sought direct evidence that a brief perceptual learning module (PLM)…

Summary of 1971 pattern recognition program development

NASA Technical Reports Server (NTRS)

Whitley, S. L.

1972-01-01

Eight areas related to pattern recognition analysis at the Earth Resources Laboratory are discussed: (1) background; (2) Earth Resources Laboratory goals; (3) software problems/limitations; (4) operational problems/limitations; (5) immediate future capabilities; (6) Earth Resources Laboratory data analysis system; (7) general program needs and recommendations; and (8) schedule and milestones.

Pattern Recognition by Retina-Like Devices.

ERIC Educational Resources Information Center

Weiman, Carl F. R.; Rothstein, Jerome

This study has investigated some pattern recognition capabilities of devices consisting of arrays of cooperating elements acting in parallel. The problem of recognizing straight lines in general position on the quadratic lattice has been completely solved by applying parallel acting algorithms to a special code for lines on the lattice. The…

Cognitive Development and Reading Processes. Developmental Program Report Number 76.

ERIC Educational Resources Information Center

West, Richard F.

In discussing the relationship between cognitive development (perception, pattern recognition, and memory) and reading processes, this paper especially emphasizes developmental factors. After an overview of some issues that bear on how written language is processed, the paper presents a discussion of pattern recognition, including general pattern…

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Editor); Schenker, Paul (Editor)

1987-01-01

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Codebook-based electrooculography data analysis towards cognitive activity recognition.

PubMed

Lagodzinski, P; Shirahama, K; Grzegorzek, M

2018-04-01

With the advancement in mobile/wearable technology, people started to use a variety of sensing devices to track their daily activities as well as health and fitness conditions in order to improve the quality of life. This work addresses an idea of eye movement analysis, which due to the strong correlation with cognitive tasks can be successfully utilized in activity recognition. Eye movements are recorded using an electrooculographic (EOG) system built into the frames of glasses, which can be worn more unobtrusively and comfortably than other devices. Since the obtained information is low-level sensor data expressed as a sequence representing values in constant intervals (100 Hz), the cognitive activity recognition problem is formulated as sequence classification. However, it is unclear what kind of features are useful for accurate cognitive activity recognition. Thus, a machine learning algorithm like a codebook approach is applied, which instead of focusing on feature engineering is using a distribution of characteristic subsequences (codewords) to describe sequences of recorded EOG data, where the codewords are obtained by clustering a large number of subsequences. Further, statistical analysis of the codeword distribution results in discovering features which are characteristic to a certain activity class. Experimental results demonstrate good accuracy of the codebook-based cognitive activity recognition reflecting the effective usage of the codewords. Copyright © 2017 Elsevier Ltd. All rights reserved.

Performance Study of the First 2D Prototype of Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

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

Deptuch, Gregory; Hoff, James; Jindariani, Sergo

Extremely fast pattern recognition capabilities are necessary to find and fit billions of tracks at the hardware trigger level produced every second anticipated at high luminosity LHC (HL-LHC) running conditions. Associative Memory (AM) based approaches for fast pattern recognition have been proposed as a potential solution to the tracking trigger. However, at the HL-LHC, there is much less time available and speed performance must be improved over previous systems while maintaining a comparable number of patterns. The Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) Project aims to achieve the target pattern density and performance goal using 3DIC technology. The firstmore » step taken in the VIPRAM work was the development of a 2D prototype (protoVIPRAM00) in which the associative memory building blocks were designed to be compatible with the 3D integration. In this paper, we present the results from extensive performance studies of the protoVIPRAM00 chip in both realistic HL-LHC and extreme conditions. Results indicate that the chip operates at the design frequency of 100 MHz with perfect correctness in realistic conditions and conclude that the building blocks are ready for 3D stacking. We also present performance boundary characterization of the chip under extreme conditions.« less

Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model

PubMed Central

Eum, Hyukmin; Yoon, Changyong; Lee, Heejin; Park, Mignon

2015-01-01

In this paper, we propose a new method for spotting and recognizing continuous human actions using a vision sensor. The method is comprised of depth-MHI-HOG (DMH), action modeling, action spotting, and recognition. First, to effectively separate the foreground from background, we propose a method called DMH. It includes a standard structure for segmenting images and extracting features by using depth information, MHI, and HOG. Second, action modeling is performed to model various actions using extracted features. The modeling of actions is performed by creating sequences of actions through k-means clustering; these sequences constitute HMM input. Third, a method of action spotting is proposed to filter meaningless actions from continuous actions and to identify precise start and end points of actions. By employing the spotter model, the proposed method improves action recognition performance. Finally, the proposed method recognizes actions based on start and end points. We evaluate recognition performance by employing the proposed method to obtain and compare probabilities by applying input sequences in action models and the spotter model. Through various experiments, we demonstrate that the proposed method is efficient for recognizing continuous human actions in real environments. PMID:25742172

An Indoor Pedestrian Positioning Method Using HMM with a Fuzzy Pattern Recognition Algorithm in a WLAN Fingerprint System

PubMed Central

Ni, Yepeng; Liu, Jianbo; Liu, Shan; Bai, Yaxin

2016-01-01

With the rapid development of smartphones and wireless networks, indoor location-based services have become more and more prevalent. Due to the sophisticated propagation of radio signals, the Received Signal Strength Indicator (RSSI) shows a significant variation during pedestrian walking, which introduces critical errors in deterministic indoor positioning. To solve this problem, we present a novel method to improve the indoor pedestrian positioning accuracy by embedding a fuzzy pattern recognition algorithm into a Hidden Markov Model. The fuzzy pattern recognition algorithm follows the rule that the RSSI fading has a positive correlation to the distance between the measuring point and the AP location even during a dynamic positioning measurement. Through this algorithm, we use the RSSI variation trend to replace the specific RSSI value to achieve a fuzzy positioning. The transition probability of the Hidden Markov Model is trained by the fuzzy pattern recognition algorithm with pedestrian trajectories. Using the Viterbi algorithm with the trained model, we can obtain a set of hidden location states. In our experiments, we demonstrate that, compared with the deterministic pattern matching algorithm, our method can greatly improve the positioning accuracy and shows robust environmental adaptability. PMID:27618053

Quantitative Photochemical Immobilization of Biomolecules on Planar and Corrugated Substrates: A Versatile Strategy for Creating Functional Biointerfaces

PubMed Central

Martin, Teresa A.; Herman, Christine T.; Limpoco, Francis T.; Michael, Madeline C.; Potts, Gregory K.; Bailey, Ryan C.

2014-01-01

Methods for the generation of substrates presenting biomolecules in a spatially controlled manner are enabling tools for applications in biosensor systems, microarray technologies, fundamental biological studies and biointerface science. We have implemented a method to create biomolecular patterns by using light to control the direct covalent immobilization of biomolecules onto benzophenone-modified glass substrates. We have generated substrates presenting up to three different biomolecules patterned in sequence, and demonstrate biomolecular photopatterning on corrugated substrates. The chemistry of the underlying monolayer was optimized to incorporate poly(ethylene glycol) to enable adhesive cell adhesion onto patterned extracellular matrix proteins. Substrates were characterized with contact angle goniometry, AFM, and immunofluorescence microscopy. Importantly, radioimmunoassays were performed to quantify the site density of immobilized biomolecules on photopatterned substrates. Retention of function of photopatterned proteins was demonstrated both by native ligand recognition and cell adhesion to photopatterned substrates, revealing that substrates generated with this method are suitable for probing specific cell receptor-ligand interactions. This molecularly general photochemical patterning method is an enabling tool that will allow the creation of substrates presenting both biochemical and topographical variation, which is an important feature of many native biointerfaces. PMID:21793535

STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

DTIC Science & Technology

ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

Face Recognition Using Local Quantized Patterns and Gabor Filters

NASA Astrophysics Data System (ADS)

Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

2015-05-01

The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

Speaker normalization for chinese vowel recognition in cochlear implants.

PubMed

Luo, Xin; Fu, Qian-Jie

2005-07-01

Because of the limited spectra-temporal resolution associated with cochlear implants, implant patients often have greater difficulty with multitalker speech recognition. The present study investigated whether multitalker speech recognition can be improved by applying speaker normalization techniques to cochlear implant speech processing. Multitalker Chinese vowel recognition was tested with normal-hearing Chinese-speaking subjects listening to a 4-channel cochlear implant simulation, with and without speaker normalization. For each subject, speaker normalization was referenced to the speaker that produced the best recognition performance under conditions without speaker normalization. To match the remaining speakers to this "optimal" output pattern, the overall frequency range of the analysis filter bank was adjusted for each speaker according to the ratio of the mean third formant frequency values between the specific speaker and the reference speaker. Results showed that speaker normalization provided a small but significant improvement in subjects' overall recognition performance. After speaker normalization, subjects' patterns of recognition performance across speakers changed, demonstrating the potential for speaker-dependent effects with the proposed normalization technique.

Aging and visual 3-D shape recognition from motion.

PubMed

Norman, J Farley; Adkins, Olivia C; Dowell, Catherine J; Hoyng, Stevie C; Shain, Lindsey M; Pedersen, Lauren E; Kinnard, Jonathan D; Higginbotham, Alexia J; Gilliam, Ashley N

2017-11-01

Two experiments were conducted to evaluate the ability of younger and older adults to recognize 3-D object shape from patterns of optical motion. In Experiment 1, participants were required to identify dotted surfaces that rotated in depth (i.e., surface structure portrayed using the kinetic depth effect). The task difficulty was manipulated by limiting the surface point lifetimes within the stimulus apparent motion sequences. In Experiment 2, the participants identified solid, naturally shaped objects (replicas of bell peppers, Capsicum annuum) that were defined by occlusion boundary contours, patterns of specular highlights, or combined optical patterns containing both boundary contours and specular highlights. Significant and adverse effects of increased age were found in both experiments. Despite the fact that previous research has found that increases in age do not reduce solid shape discrimination, our current results indicated that the same conclusion does not hold for shape identification. We demonstrated that aging results in a reduction in the ability to visually recognize 3-D shape independent of how the 3-D structure is defined (motions of isolated points, deformations of smooth optical fields containing specular highlights, etc.).

Foundations for Streaming Model Transformations by Complex Event Processing.

PubMed

Dávid, István; Ráth, István; Varró, Dániel

2018-01-01

Streaming model transformations represent a novel class of transformations to manipulate models whose elements are continuously produced or modified in high volume and with rapid rate of change. Executing streaming transformations requires efficient techniques to recognize activated transformation rules over a live model and a potentially infinite stream of events. In this paper, we propose foundations of streaming model transformations by innovatively integrating incremental model query, complex event processing (CEP) and reactive (event-driven) transformation techniques. Complex event processing allows to identify relevant patterns and sequences of events over an event stream. Our approach enables event streams to include model change events which are automatically and continuously populated by incremental model queries. Furthermore, a reactive rule engine carries out transformations on identified complex event patterns. We provide an integrated domain-specific language with precise semantics for capturing complex event patterns and streaming transformations together with an execution engine, all of which is now part of the Viatra reactive transformation framework. We demonstrate the feasibility of our approach with two case studies: one in an advanced model engineering workflow; and one in the context of on-the-fly gesture recognition.

Structural basis of UGUA recognition by the Nudix protein CFIm25 and implications for a regulatory role in mRNA 3′ processing

PubMed Central

Yang, Qin; Gilmartin, Gregory M.; Doublié, Sylvie

2010-01-01

Human Cleavage Factor Im (CFIm) is an essential component of the pre-mRNA 3′ processing complex that functions in the regulation of poly(A) site selection through the recognition of UGUA sequences upstream of the poly(A) site. Although the highly conserved 25 kDa subunit (CFIm25) of the CFIm complex possesses a characteristic α/β/α Nudix fold, CFIm25 has no detectable hydrolase activity. Here we report the crystal structures of the human CFIm25 homodimer in complex with UGUAAA and UUGUAU RNA sequences. CFIm25 is the first Nudix protein to be reported to bind RNA in a sequence-specific manner. The UGUA sequence contributes to binding specificity through an intramolecular G:A Watson–Crick/sugar-edge base interaction, an unusual pairing previously found to be involved in the binding specificity of the SAM-III riboswitch. The structures, together with mutational data, suggest a novel mechanism for the simultaneous sequence-specific recognition of two UGUA elements within the pre-mRNA. Furthermore, the mutually exclusive binding of RNA and the signaling molecule Ap4A (diadenosine tetraphosphate) by CFIm25 suggests a potential role for small molecules in the regulation of mRNA 3′ processing. PMID:20479262

Structural basis of UGUA recognition by the Nudix protein CFI(m)25 and implications for a regulatory role in mRNA 3' processing.

PubMed

Yang, Qin; Gilmartin, Gregory M; Doublié, Sylvie

2010-06-01

Human Cleavage Factor Im (CFI(m)) is an essential component of the pre-mRNA 3' processing complex that functions in the regulation of poly(A) site selection through the recognition of UGUA sequences upstream of the poly(A) site. Although the highly conserved 25 kDa subunit (CFI(m)25) of the CFI(m) complex possesses a characteristic alpha/beta/alpha Nudix fold, CFI(m)25 has no detectable hydrolase activity. Here we report the crystal structures of the human CFI(m)25 homodimer in complex with UGUAAA and UUGUAU RNA sequences. CFI(m)25 is the first Nudix protein to be reported to bind RNA in a sequence-specific manner. The UGUA sequence contributes to binding specificity through an intramolecular G:A Watson-Crick/sugar-edge base interaction, an unusual pairing previously found to be involved in the binding specificity of the SAM-III riboswitch. The structures, together with mutational data, suggest a novel mechanism for the simultaneous sequence-specific recognition of two UGUA elements within the pre-mRNA. Furthermore, the mutually exclusive binding of RNA and the signaling molecule Ap(4)A (diadenosine tetraphosphate) by CFI(m)25 suggests a potential role for small molecules in the regulation of mRNA 3' processing.

Sequence stratigraphy and high-frequency cycles: New aspects for a quantitative evaluation of the Gulf of Suez basin, Egypt

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

Nio, S.D.; Yang, C.S.; Tewfik, N.

1993-09-01

A new development in the application of sequence stratigraphic concepts in marine as well as continental basins is the recognition of high-frequency cyclic patterns in rock successions in the subsurface. Studies of six wells from the northern, central, and southern parts of the Gulf of Suez show the presence of well-preserved, high-frequency cycles with periodicities similar to the orbitally forced Malankovitch parameters. Subsurface rock successions, third-order sequences, and high-frequency cycles were compared with outcrops. After establishing the biostratigraphic framework for the above-mentioned wells, a sequence analysis was performed. Sequence boundaries and maximum flooding positions in each well were calibrated withmore » the occurrences and evaluation of the high-frequency cycles. It became obvious that there is an intimate relationship between these high-frequency Milankovitch cycles and sequence organization. In addition, a close relationship can be observed in the subsurface as well as in outcrops between high-frequency climatic changes (connected to the Milankovitch cycles) and (litho)facies variability. Quantitative evaluations of each sequence and/or systems tract can be computed with the International Geoservices' cyclicity analysis tool (MILABAR). The results are summarized in a well composite chart, rate (NAR), and ratio of preserved time. In correlations between the wells, an accuracy of 500-100 Ka can be obtained. The quantitative evaluation of the sequence and high-frequency cycle analysis gave some new aspects concerning the (litho)facies and geodynamic development during the pre- as well as the synrift stages of the Gulf of Suez Basin.« less

Molecular and functional characterization of peptidoglycan-recognition protein SC2 (PGRP-SC2) from Nile tilapia (Oreochromis niloticus) involved in the immune response to Streptococcus agalactiae.

PubMed

Gan, Zhen; Chen, Shannan; Hou, Jing; Huo, Huijun; Zhang, Xiaolin; Ruan, Baiye; Laghari, Zubair Ahmed; Li, Li; Lu, Yishan; Nie, Pin

2016-07-01

PGRP-SC2, the member of PGRP family, plays an important role in regulation of innate immune response. In this paper, a PGRP-SC2 gene of Nile tilapia, Oreochromis niloticus (designated as On-PGRP-SC2) was cloned and its expression pattern under the infection of Streptococcus agalactiae was investigated. Sequence analysis showed main structural features required for amidase activity were detected in the deduced amino acid sequence of On-PGRP-SC2. In healthy tilapia, the On-PGRP-SC2 transcripts could be detected in all the examined tissues, with the most abundant expression in the muscle. When infected with S. agalactiae, there was a clear time-dependent expression pattern of On-PGRP-SC2 in the spleen, head kidney and brain. The assays for the amidase activity suggested that recombinant On-PGRP-SC2 protein had a Zn(2+)-dependent PGN-degrading activity. Moreover, our works showed that recombinant On-PGRP-SC2 protein could significantly reduce bacterial load in target organs attacked by S. agalactiae. These findings indicated that On-PGRP-SC2 may play important roles in the immune response to S. agalactiae in Nile tilapia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Origin Replication Complex Binding, Nucleosome Depletion Patterns, and a Primary Sequence Motif Can Predict Origins of Replication in a Genome with Epigenetic Centromeres

PubMed Central

Tsai, Hung-Ji; Baller, Joshua A.; Liachko, Ivan; Koren, Amnon; Burrack, Laura S.; Hickman, Meleah A.; Thevandavakkam, Mathuravani A.; Rusche, Laura N.

2014-01-01

ABSTRACT Origins of DNA replication are key genetic elements, yet their identification remains elusive in most organisms. In previous work, we found that centromeres contain origins of replication (ORIs) that are determined epigenetically in the pathogenic yeast Candida albicans. In this study, we used origin recognition complex (ORC) binding and nucleosome occupancy patterns in Saccharomyces cerevisiae and Kluyveromyces lactis to train a machine learning algorithm to predict the position of active arm (noncentromeric) origins in the C. albicans genome. The model identified bona fide active origins as determined by the presence of replication intermediates on nondenaturing two-dimensional (2D) gels. Importantly, these origins function at their native chromosomal loci and also as autonomously replicating sequences (ARSs) on a linear plasmid. A “mini-ARS screen” identified at least one and often two ARS regions of ≥100 bp within each bona fide origin. Furthermore, a 15-bp AC-rich consensus motif was associated with the predicted origins and conferred autonomous replicating activity to the mini-ARSs. Thus, while centromeres and the origins associated with them are epigenetic, arm origins are dependent upon critical DNA features, such as a binding site for ORC and a propensity for nucleosome exclusion. PMID:25182328

Visual Scanning Patterns and Executive Function in Relation to Facial Emotion Recognition in Aging

PubMed Central

Circelli, Karishma S.; Clark, Uraina S.; Cronin-Golomb, Alice

2012-01-01

Objective The ability to perceive facial emotion varies with age. Relative to younger adults (YA), older adults (OA) are less accurate at identifying fear, anger, and sadness, and more accurate at identifying disgust. Because different emotions are conveyed by different parts of the face, changes in visual scanning patterns may account for age-related variability. We investigated the relation between scanning patterns and recognition of facial emotions. Additionally, as frontal-lobe changes with age may affect scanning patterns and emotion recognition, we examined correlations between scanning parameters and performance on executive function tests. Methods We recorded eye movements from 16 OA (mean age 68.9) and 16 YA (mean age 19.2) while they categorized facial expressions and non-face control images (landscapes), and administered standard tests of executive function. Results OA were less accurate than YA at identifying fear (p<.05, r=.44) and more accurate at identifying disgust (p<.05, r=.39). OA fixated less than YA on the top half of the face for disgust, fearful, happy, neutral, and sad faces (p’s<.05, r’s≥.38), whereas there was no group difference for landscapes. For OA, executive function was correlated with recognition of sad expressions and with scanning patterns for fearful, sad, and surprised expressions. Conclusion We report significant age-related differences in visual scanning that are specific to faces. The observed relation between scanning patterns and executive function supports the hypothesis that frontal-lobe changes with age may underlie some changes in emotion recognition. PMID:22616800

Skeleton-based human action recognition using multiple sequence alignment

NASA Astrophysics Data System (ADS)

Ding, Wenwen; Liu, Kai; Cheng, Fei; Zhang, Jin; Li, YunSong

2015-05-01

Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.

Fibronectin tetrapeptide is target for syphilis spirochete cytadherence

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

Thomas, D.D.; Baseman, J.B.; Alderete, J.F.

1985-11-01

The syphilis bacterium, Treponema pallidum, parasitizes host cells through recognition of fibronectin (Fn) on cell surfaces. The active site of the Fn molecule has been identified as a four-amino acid sequence, arg-gly-asp-ser (RGDS), located on each monomer of the cell-binding domain. The synthetic heptapeptide gly-arg-gly-asp-ser-pro-cys (GRGDSPC), with the active site sequence RGDS, specifically competed with SVI-labeled cell-binding domain acquisition by T. pallidum. Additionally, the same heptapeptide with the RGDS sequence diminished treponemal attachment to HEp-2 and HT1080 cell monolayers. Related heptapeptides altered in one key amino acid within the RGDS sequence failed to inhibit Fn cell-binding domain acquisition or parasitismmore » of host cells by T. pallidum. The data support the view that T. pallidum cytadherence of host cells is through recognition of the RGDS sequence also important for eukaryotic cell-Fn binding.« less

Extrinsic Cognitive Load Impairs Spoken Word Recognition in High- and Low-Predictability Sentences.

PubMed

Hunter, Cynthia R; Pisoni, David B

Listening effort (LE) induced by speech degradation reduces performance on concurrent cognitive tasks. However, a converse effect of extrinsic cognitive load on recognition of spoken words in sentences has not been shown. The aims of the present study were to (a) examine the impact of extrinsic cognitive load on spoken word recognition in a sentence recognition task and (b) determine whether cognitive load and/or LE needed to understand spectrally degraded speech would differentially affect word recognition in high- and low-predictability sentences. Downstream effects of speech degradation and sentence predictability on the cognitive load task were also examined. One hundred twenty young adults identified sentence-final spoken words in high- and low-predictability Speech Perception in Noise sentences. Cognitive load consisted of a preload of short (low-load) or long (high-load) sequences of digits, presented visually before each spoken sentence and reported either before or after identification of the sentence-final word. LE was varied by spectrally degrading sentences with four-, six-, or eight-channel noise vocoding. Level of spectral degradation and order of report (digits first or words first) were between-participants variables. Effects of cognitive load, sentence predictability, and speech degradation on accuracy of sentence-final word identification as well as recall of preload digit sequences were examined. In addition to anticipated main effects of sentence predictability and spectral degradation on word recognition, we found an effect of cognitive load, such that words were identified more accurately under low load than high load. However, load differentially affected word identification in high- and low-predictability sentences depending on the level of sentence degradation. Under severe spectral degradation (four-channel vocoding), the effect of cognitive load on word identification was present for high-predictability sentences but not for low-predictability sentences. Under mild spectral degradation (eight-channel vocoding), the effect of load was present for low-predictability sentences but not for high-predictability sentences. There were also reliable downstream effects of speech degradation and sentence predictability on recall of the preload digit sequences. Long digit sequences were more easily recalled following spoken sentences that were less spectrally degraded. When digits were reported after identification of sentence-final words, short digit sequences were recalled more accurately when the spoken sentences were predictable. Extrinsic cognitive load can impair recognition of spectrally degraded spoken words in a sentence recognition task. Cognitive load affected word identification in both high- and low-predictability sentences, suggesting that load may impact both context use and lower-level perceptual processes. Consistent with prior work, LE also had downstream effects on memory for visual digit sequences. Results support the proposal that extrinsic cognitive load and LE induced by signal degradation both draw on a central, limited pool of cognitive resources that is used to recognize spoken words in sentences under adverse listening conditions.

Recognition of surface lithologic and topographic patterns in southwest Colorado with ADP techniques

NASA Technical Reports Server (NTRS)

Melhorn, W. N.; Sinnock, S.

1973-01-01

Analysis of ERTS-1 multispectral data by automatic pattern recognition procedures is applicable toward grappling with current and future resource stresses by providing a means for refining existing geologic maps. The procedures used in the current analysis already yield encouraging results toward the eventual machine recognition of extensive surface lithologic and topographic patterns. Automatic mapping of a series of hogbacks, strike valleys, and alluvial surfaces along the northwest flank of the San Juan Basin in Colorado can be obtained by minimal man-machine interaction. The determination of causes for separable spectral signatures is dependent upon extensive correlation of micro- and macro field based ground truth observations and aircraft underflight data with the satellite data.

Infrared Ship Classification Using A New Moment Pattern Recognition Concept

NASA Astrophysics Data System (ADS)

Casasent, David; Pauly, John; Fetterly, Donald

1982-03-01

An analysis of the statistics of the moments and the conventional invariant moments shows that the variance of the latter become quite large as the order of the moments and the degree of invariance increases. Moreso, the need to whiten the error volume increases with the order and degree, but so does the computational load associated with computing the whitening operator. We thus advance a new estimation approach to the use of moments in pattern recog-nition that overcomes these problems. This work is supported by experimental verification and demonstration on an infrared ship pattern recognition problem. The computational load associated with our new algorithm is also shown to be very low.

In vitro excision of adeno-associated virus DNA from recombinant plasmids: Isolation of an enzyme fraction from HeLa cells that cleaves DNA at poly(G) sequences

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

Gottlieb, J.; Muzyczka, N.

1988-06-01

When circular recombinant plasmids containing adeno-associated virus (AAV) DNA sequences are transfected into human cells, the AAV provirus is rescued. Using these circular AAV plasmids as substrates, the authors isolated an enzyme fraction from HeLa cell nuclear extracts that excises intact AAV DNA in vitro from vector DNA and produces linear DNA products. The recognition signal for the enzyme is a polypurine-polypyrimidine sequence which is at least 9 residues long and rich in G . C base pairs. Such sequences are present in AAV recombinant plasmids as part of the first 15 base pairs of the AAV terminal repeat andmore » in some cases as the result of cloning the AAV genome by G . C tailing. The isolated enzyme fraction does not have significant endonucleolytic activity on single-stranded or double-stranded DNA. Plasmid DNA that is transfected into tissue culture cells is cleaved in vivo to produce a pattern of DNA fragments similar to that seen with purified enzyme in vitro. The activity has been called endo R for rescue, and its behavior suggests that it may have a role in recombination of cellular chromosomes.« less

Cloning and restriction enzyme mapping of ribosomal DNA of Giardia duodenalis, Giardia ardeae and Giardia muris.

PubMed

van Keulen, H; Campbell, S R; Erlandsen, S L; Jarroll, E L

1991-06-01

In an attempt to study Giardia at the DNA sequence level, the rRNA genes of three species, Giardia duodenalis, Giardia ardeae and Giardia muris were cloned and restriction enzyme maps were constructed. The rDNA repeats of these Giardia show completely different restriction enzyme recognition patterns. The size of the rDNA repeat ranges from approximately 5.6 kb in G. duodenalis to 7.6 kb in both G. muris and G. ardeae. These size differences are mainly attributable to the variation in length of the spacer. Minor differences exist among these Giardia in the sizes of their small subunit rRNA and the internal transcribed spacer between small and large subunit rRNA. The genetic maps were constructed by sequence analysis of the DNA around the 5' and 3' ends of the mature rRNA genes and between the rRNA covering the 5.8S rRNA gene and internal transcribed spacer. Comparison of the 5.8S rDNA and 3' end of large subunit rDNA from these three Giardia species showed considerable sequence variation, but the rDNA sequences of G. duodenalis and G. ardeae appear more closely related to each other than to G. muris.

Aplysia attractin: biophysical characterization and modeling of a water-borne pheromone.

PubMed Central

Schein, C H; Nagle, G T; Page, J S; Sweedler, J V; Xu, Y; Painter, S D; Braun, W

2001-01-01

Attractin, a 58-residue protein secreted by the mollusk Aplysia californica, stimulates sexually mature animals to approach egg cordons. Attractin from five different Aplysia species are approximately 40% identical in sequence. Recombinant attractin, expressed in insect cells and purified by reverse-phase high-performance liquid chromatography (RP-HPLC), is active in a bioassay using A. brasiliana; its circular dichroism (CD) spectrum indicates a predominantly alpha-helical structure. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) characterization of proteolytic fragments identified disulfide bonds between the six conserved cysteines (I-VI, II-V, III-IV, where the Roman numeral indicates the order of occurrence in the primary sequence). Attractin has no significant similarity to any other sequence in the database. The protozoan Euplotes pheromones were selected by fold recognition as possible templates. These diverse proteins have three alpha-helices, with six cysteine residues disulfide-bonded in a different pattern from attractin. Model structures with good stereochemical parameters were prepared using the EXDIS/DIAMOD/FANTOM program suite and constraints based on sequence alignments with the Euplotes templates and the attractin disulfide bonds. A potential receptor-binding site is suggested based on these data. Future structural characterization of attractin will be needed to confirm these models. PMID:11423429

Intelligent data processing of an ultrasonic sensor system for pattern recognition improvements

NASA Astrophysics Data System (ADS)

Na, Seung You; Park, Min-Sang; Hwang, Won-Gul; Kee, Chang-Doo

1999-05-01

Though conventional time-of-flight ultrasonic sensor systems are popular due to the advantages of low cost and simplicity, the usage of the sensors is rather narrowly restricted within object detection and distance readings. There is a strong need to enlarge the amount of environmental information for mobile applications to provide intelligent autonomy. Wide sectors of such neighboring object recognition problems can be satisfactorily handled with coarse vision data such as sonar maps instead of accurate laser or optic measurements. For the usage of object pattern recognition, ultrasonic senors have inherent shortcomings of poor directionality and specularity which result in low spatial resolution and indistinctiveness of object patterns. To resolve these problems an array of increased number of sensor elements has been used for large objects. In this paper we propose a method of sensor array system with improved recognition capability using electronic circuits accompanying the sensor array and neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. Relying upon the known sensor characteristics, a set of different return signals from neighboring senors is manipulated to provide an enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

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

PubMed

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.

Influence of High Hydrostatic Pressure on Epitope Mapping of Tobacco Mosaic Virus Coat Protein

PubMed Central

Bonafe, Carlos Francisco Sampaio; Arns, Clarice Weis

2014-01-01

Abstract In this study, we investigated the effect of high hydrostatic pressure (HHP) on tobacco mosaic virus (TMV), a model virus in immunology and one of the most studied viruses to date. Exposure to HHP significantly altered the recognition epitopes when compared to sera from mice immunized with native virus. These alterations were studied further by combining HHP with urea or low temperature and then inoculating the altered virions into Balb-C mice. The antibody titers and cross-reactivity of the resulting sera were determined by ELISA. The antigenicity of the viral particles was maintained, as assessed by using polyclonal antibodies against native virus. The antigenicity of canonical epitopes was maintained, although binding intensities varied among the treatments. The patterns of recognition determined by epitope mapping were cross checked with the prediction algorithms for the TMVcp amino acid sequence to infer which alterations had occurred. These findings suggest that different cleavage sites were exposed after the treatments and this was confirmed by epitope mapping using sera from mice immunized with virus previously exposed to HHP. PMID:24605789

Determinants for DNA target structure selectivity of the human LINE-1 retrotransposon endonuclease.

PubMed

Repanas, Kostas; Zingler, Nora; Layer, Liliana E; Schumann, Gerald G; Perrakis, Anastassis; Weichenrieder, Oliver

2007-01-01

The human LINE-1 endonuclease (L1-EN) is the targeting endonuclease encoded by the human LINE-1 (L1) retrotransposon. L1-EN guides the genomic integration of new L1 and Alu elements that presently account for approximately 28% of the human genome. L1-EN bears considerable technological interest, because its target selectivity may ultimately be engineered to allow the site-specific integration of DNA into defined genomic locations. Based on the crystal structure, we generated L1-EN mutants to analyze and manipulate DNA target site recognition. Crystal structures and their dynamic and functional analysis show entire loop grafts to be feasible, resulting in altered specificity, while individual point mutations do not change the nicking pattern of L1-EN. Structural parameters of the DNA target seem more important for recognition than the nucleotide sequence, and nicking profiles on DNA oligonucleotides in vitro are less well defined than the respective integration site consensus in vivo. This suggests that additional factors other than the DNA nicking specificity of L1-EN contribute to the targeted integration of non-LTR retrotransposons.

Using infrared HOG-based pedestrian detection for outdoor autonomous searching UAV with embedded system

NASA Astrophysics Data System (ADS)

Shao, Yanhua; Mei, Yanying; Chu, Hongyu; Chang, Zhiyuan; He, Yuxuan; Zhan, Huayi

2018-04-01

Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Unmanned Aerial Vehicles (UAVs) have become a major field of research in recent years. In this paper, an algorithm for a robust pedestrian detection method based on the combination of the infrared HOG (IR-HOG) feature and SVM is proposed for highly complex outdoor scenarios on the basis of airborne IR image sequences from UAV. The basic flow of our application operation is as follows. Firstly, the thermal infrared imager (TAU2-336), which was installed on our Outdoor Autonomous Searching (OAS) UAV, is used for taking pictures of the designated outdoor area. Secondly, image sequences collecting and processing were accomplished by using high-performance embedded system with Samsung ODROID-XU4 and Ubuntu as the core and operating system respectively, and IR-HOG features were extracted. Finally, the SVM is used to train the pedestrian classifier. Experiment show that, our method shows promising results under complex conditions including strong noise corruption, partial occlusion etc.

Mitochondrial DNA polymorphism in a maternal lineage of Holstein cows.

PubMed Central

Hauswirth, W W; Laipis, P J

1982-01-01

Two mitochondrial genotypes are shown to exist within one Holstein cow maternal lineage. They were detected by the appearance of an extra Hae III recognition site in one genotype. The nucleotide sequence of this region has been determined and the genotypes are distinguished by an adenine/guanine base transition which creates the new Hae III site. This point mutation occurs within an open reading frame at the third position of a glycine codon and therefore does not alter the amino acid sequence. The present pattern of genotypes within the lineage demands that multiple shifts between genotypes must have occurred within the past 20 years with the most rapid shift taking place in no more than 4 years and indicates that mitochondrial DNA polymorphism can occur between maternally related mammals. The process that gave rise to different genotypes in one lineage is clearly of fundamental importance in understanding intraspecific mitochondrial polymorphism and evolution in mammals. Several potential mechanisms for rapid mitochondrial DNA variation are discussed in light of these results. Images PMID:6289312

Mechanisms and Neural Basis of Object and Pattern Recognition: A Study with Chess Experts

ERIC Educational Resources Information Center

Bilalic, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-01-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and…

Designing Clinical Examples To Promote Pattern Recognition: Nursing Education-Based Research and Practical Applications.

ERIC Educational Resources Information Center

Welk, Dorette Sugg

2002-01-01

Sophomore nursing students (n=162) examined scenarios depicting typical and atypical signs of heart attack. Examples were structured to include essential and nonessential symptoms, enabling pattern recognition and improved performance. The method provides a way to prepare students to anticipate and recognize life-threatening situations. (Contains…

PATTERN RECOGNITION APPROACH TO MEDICAL DIAGNOSIS,

DTIC Science & Technology

A sequential method of pattern recognition was used to recognize hyperthyroidism in a sample of 2219 patients being treated at the Straub Clinic in...the most prominent class features are selected. Thus, the symptoms which best distinguish hyperthyroidism are extracted at every step and the number of tests required to reach a diagnosis is reduced. (Author)

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory

PubMed Central

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high–low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. PMID:25146374

Measurement Marker Recognition In A Time Sequence Of Infrared Images For Biomedical Applications

NASA Astrophysics Data System (ADS)

Fiorini, A. R.; Fumero, R.; Marchesi, R.

1986-03-01

In thermographic measurements, quantitative surface temperature evaluation is often uncertain. The main reason is in the lack of available reference points in transient conditions. Reflective markers were used for automatic marker recognition and pixel coordinate computations. An algorithm selects marker icons to match marker references where particular luminance conditions are satisfied. Automatic marker recognition allows luminance compensation and temperature calibration of recorded infrared images. A biomedical application is presented: the dynamic behaviour of the surface temperature distributions is investigated in order to study the performance of two different pumping systems for extracorporeal circulation. Sequences of images are compared and results are discussed. Finally, the algorithm allows to monitor the experimental environment and to alert for the presence of unusual experimental conditions.

Aptamer Recognition of Multiplexed Small-Molecule-Functionalized Substrates.

PubMed

Nakatsuka, Nako; Cao, Huan H; Deshayes, Stephanie; Melkonian, Arin Lucy; Kasko, Andrea M; Weiss, Paul S; Andrews, Anne M

2018-05-31

Aptamers are chemically synthesized oligonucleotides or peptides with molecular recognition capabilities. We investigated recognition of substrate-tethered small-molecule targets, using neurotransmitters as examples, and fluorescently labeled DNA aptamers. Substrate regions patterned via microfluidic channels with dopamine or L-tryptophan were selectively recognized by previously identified dopamine or L-tryptophan aptamers, respectively. The on-substrate dissociation constant determined for the dopamine aptamer was comparable to, though slightly greater than the previously determined solution dissociation constant. Using pre-functionalized neurotransmitter-conjugated oligo(ethylene glycol) alkanethiols and microfluidics patterning, we produced multiplexed substrates to capture and to sort aptamers. Substrates patterned with L-DOPA, L-DOPS, and L-5-HTP enabled comparison of the selectivity of the dopamine aptamer for different targets via simultaneous determination of in situ binding constants. Thus, beyond our previous demonstrations of recognition by protein binding partners (i.e., antibodies and G-protein-coupled receptors), strategically optimized small-molecule-functionalized substrates show selective recognition of nucleic acid binding partners. These substrates are useful for side-by-side target comparisons, and future identification and characterization of novel aptamers targeting neurotransmitters or other important small-molecules.

Classifier dependent feature preprocessing methods

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M., II; Peterson, Gilbert L.

2008-04-01

In mobile applications, computational complexity is an issue that limits sophisticated algorithms from being implemented on these devices. This paper provides an initial solution to applying pattern recognition systems on mobile devices by combining existing preprocessing algorithms for recognition. In pattern recognition systems, it is essential to properly apply feature preprocessing tools prior to training classification models in an attempt to reduce computational complexity and improve the overall classification accuracy. The feature preprocessing tools extended for the mobile environment are feature ranking, feature extraction, data preparation and outlier removal. Most desktop systems today are capable of processing a majority of the available classification algorithms without concern of processing while the same is not true on mobile platforms. As an application of pattern recognition for mobile devices, the recognition system targets the problem of steganalysis, determining if an image contains hidden information. The measure of performance shows that feature preprocessing increases the overall steganalysis classification accuracy by an average of 22%. The methods in this paper are tested on a workstation and a Nokia 6620 (Symbian operating system) camera phone with similar results.

Complex auditory behaviour emerges from simple reactive steering

NASA Astrophysics Data System (ADS)

Hedwig, Berthold; Poulet, James F. A.

2004-08-01

The recognition and localization of sound signals is fundamental to acoustic communication. Complex neural mechanisms are thought to underlie the processing of species-specific sound patterns even in animals with simple auditory pathways. In female crickets, which orient towards the male's calling song, current models propose pattern recognition mechanisms based on the temporal structure of the song. Furthermore, it is thought that localization is achieved by comparing the output of the left and right recognition networks, which then directs the female to the pattern that most closely resembles the species-specific song. Here we show, using a highly sensitive method for measuring the movements of female crickets, that when walking and flying each sound pulse of the communication signal releases a rapid steering response. Thus auditory orientation emerges from reactive motor responses to individual sound pulses. Although the reactive motor responses are not based on the song structure, a pattern recognition process may modulate the gain of the responses on a longer timescale. These findings are relevant to concepts of insect auditory behaviour and to the development of biologically inspired robots performing cricket-like auditory orientation.

Memory Distortion and Its Avoidance: An Event-Related Potentials Study on False Recognition and Correct Rejection

PubMed Central

Beato, Maria Soledad

2016-01-01

Memory researchers have long been captivated by the nature of memory distortions and have made efforts to identify the neural correlates of true and false memories. However, the underlying mechanisms of avoiding false memories by correctly rejecting related lures remains underexplored. In this study, we employed a variant of the Deese/Roediger-McDermott paradigm to explore neural signatures of committing and avoiding false memories. ERP were obtained for True recognition, False recognition, Correct rejection of new items, and, more importantly, Correct rejection of related lures. With these ERP data, early-frontal, left-parietal, and late right-frontal old/new effects (associated with familiarity, recollection, and monitoring processes, respectively) were analysed. Results indicated that there were similar patterns for True and False recognition in all three old/new effects analysed in our study. Also, False recognition and Correct rejection of related lures activities seemed to share common underlying familiarity-based processes. The ERP similarities between False recognition and Correct rejection of related lures disappeared when recollection processes were examined because only False recognition presented a parietal old/new effect. This finding supported the view that actual false recollections underlie false memories, providing evidence consistent with previous behavioural research and with most ERP and neuroimaging studies. Later, with the onset of monitoring processes, False recognition and Correct rejection of related lures waveforms presented, again, clearly dissociated patterns. Specifically, False recognition and True recognition showed more positive going patterns than Correct rejection of related lures signal and Correct rejection of new items signature. Since False recognition and Correct rejection of related lures triggered familiarity-recognition processes, our results suggest that deciding which items are studied is based more on recollection processes, which are later supported by monitoring processes. Results are discussed in terms of Activation-Monitoring Framework and Fuzzy Trace-Theory, the most prominent explanatory theories of false memory raised with the Deese/Roediger-McDermott paradigm. PMID:27711125

Memory Distortion and Its Avoidance: An Event-Related Potentials Study on False Recognition and Correct Rejection.

PubMed

Cadavid, Sara; Beato, Maria Soledad

2016-01-01

Memory researchers have long been captivated by the nature of memory distortions and have made efforts to identify the neural correlates of true and false memories. However, the underlying mechanisms of avoiding false memories by correctly rejecting related lures remains underexplored. In this study, we employed a variant of the Deese/Roediger-McDermott paradigm to explore neural signatures of committing and avoiding false memories. ERP were obtained for True recognition, False recognition, Correct rejection of new items, and, more importantly, Correct rejection of related lures. With these ERP data, early-frontal, left-parietal, and late right-frontal old/new effects (associated with familiarity, recollection, and monitoring processes, respectively) were analysed. Results indicated that there were similar patterns for True and False recognition in all three old/new effects analysed in our study. Also, False recognition and Correct rejection of related lures activities seemed to share common underlying familiarity-based processes. The ERP similarities between False recognition and Correct rejection of related lures disappeared when recollection processes were examined because only False recognition presented a parietal old/new effect. This finding supported the view that actual false recollections underlie false memories, providing evidence consistent with previous behavioural research and with most ERP and neuroimaging studies. Later, with the onset of monitoring processes, False recognition and Correct rejection of related lures waveforms presented, again, clearly dissociated patterns. Specifically, False recognition and True recognition showed more positive going patterns than Correct rejection of related lures signal and Correct rejection of new items signature. Since False recognition and Correct rejection of related lures triggered familiarity-recognition processes, our results suggest that deciding which items are studied is based more on recollection processes, which are later supported by monitoring processes. Results are discussed in terms of Activation-Monitoring Framework and Fuzzy Trace-Theory, the most prominent explanatory theories of false memory raised with the Deese/Roediger-McDermott paradigm.

Talker variability in audio-visual speech perception

PubMed Central

Heald, Shannon L. M.; Nusbaum, Howard C.

2014-01-01

A change in talker is a change in the context for the phonetic interpretation of acoustic patterns of speech. Different talkers have different mappings between acoustic patterns and phonetic categories and listeners need to adapt to these differences. Despite this complexity, listeners are adept at comprehending speech in multiple-talker contexts, albeit at a slight but measurable performance cost (e.g., slower recognition). So far, this talker variability cost has been demonstrated only in audio-only speech. Other research in single-talker contexts have shown, however, that when listeners are able to see a talker’s face, speech recognition is improved under adverse listening (e.g., noise or distortion) conditions that can increase uncertainty in the mapping between acoustic patterns and phonetic categories. Does seeing a talker’s face reduce the cost of word recognition in multiple-talker contexts? We used a speeded word-monitoring task in which listeners make quick judgments about target word recognition in single- and multiple-talker contexts. Results show faster recognition performance in single-talker conditions compared to multiple-talker conditions for both audio-only and audio-visual speech. However, recognition time in a multiple-talker context was slower in the audio-visual condition compared to audio-only condition. These results suggest that seeing a talker’s face during speech perception may slow recognition by increasing the importance of talker identification, signaling to the listener a change in talker has occurred. PMID:25076919

Talker variability in audio-visual speech perception.

PubMed

Heald, Shannon L M; Nusbaum, Howard C

2014-01-01

A change in talker is a change in the context for the phonetic interpretation of acoustic patterns of speech. Different talkers have different mappings between acoustic patterns and phonetic categories and listeners need to adapt to these differences. Despite this complexity, listeners are adept at comprehending speech in multiple-talker contexts, albeit at a slight but measurable performance cost (e.g., slower recognition). So far, this talker variability cost has been demonstrated only in audio-only speech. Other research in single-talker contexts have shown, however, that when listeners are able to see a talker's face, speech recognition is improved under adverse listening (e.g., noise or distortion) conditions that can increase uncertainty in the mapping between acoustic patterns and phonetic categories. Does seeing a talker's face reduce the cost of word recognition in multiple-talker contexts? We used a speeded word-monitoring task in which listeners make quick judgments about target word recognition in single- and multiple-talker contexts. Results show faster recognition performance in single-talker conditions compared to multiple-talker conditions for both audio-only and audio-visual speech. However, recognition time in a multiple-talker context was slower in the audio-visual condition compared to audio-only condition. These results suggest that seeing a talker's face during speech perception may slow recognition by increasing the importance of talker identification, signaling to the listener a change in talker has occurred.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Classifying performance impairment in response to sleep loss using pattern recognition algorithms on single session testing

PubMed Central

St. Hilaire, Melissa A.; Sullivan, Jason P.; Anderson, Clare; Cohen, Daniel A.; Barger, Laura K.; Lockley, Steven W.; Klerman, Elizabeth B.

2012-01-01

There is currently no “gold standard” marker of cognitive performance impairment resulting from sleep loss. We utilized pattern recognition algorithms to determine which features of data collected under controlled laboratory conditions could most reliably identify cognitive performance impairment in response to sleep loss using data from only one testing session, such as would occur in the “real world” or field conditions. A training set for testing the pattern recognition algorithms was developed using objective Psychomotor Vigilance Task (PVT) and subjective Karolinska Sleepiness Scale (KSS) data collected from laboratory studies during which subjects were sleep deprived for 26 – 52 hours. The algorithm was then tested in data from both laboratory and field experiments. The pattern recognition algorithm was able to identify performance impairment with a single testing session in individuals studied under laboratory conditions using PVT, KSS, length of time awake and time of day information with sensitivity and specificity as high as 82%. When this algorithm was tested on data collected under real-world conditions from individuals whose data were not in the training set, accuracy of predictions for individuals categorized with low performance impairment were as high as 98%. Predictions for medium and severe performance impairment were less accurate. We conclude that pattern recognition algorithms may be a promising method for identifying performance impairment in individuals using only current information about the individual’s behavior. Single testing features (e.g., number of PVT lapses) with high correlation with performance impairment in the laboratory setting may not be the best indicators of performance impairment under real-world conditions. Pattern recognition algorithms should be further tested for their ability to be used in conjunction with other assessments of sleepiness in real-world conditions to quantify performance impairment in response to sleep loss. PMID:22959616

Imaging in gynaecology: How good are we in identifying endometriomas?

PubMed Central

Van Holsbeke, C.; Van Calster, B.; Guerriero, S.; Savelli, L.; Leone, F.; Fischerova, D; Czekierdowski, A.; Fruscio, R.; Veldman, J.; Van de Putte, G.; Testa, A.C.; Bourne, T.; Valentin, L.; Timmerman, D.

2009-01-01

Aim: To evaluate the performance of subjective evaluation of ultrasound findings (pattern recognition) to discriminate endometriomas from other types of adnexal masses and to compare the demographic and ultrasound characteristics of the true positive cases with those cases that were presumed to be an endometrioma but proved to have a different histology (false positive cases) and the endometriomas missed by pattern recognition (false negative cases). Methods: All patients in the International Ovarian Tumor Analysis (IOTA ) studies were included for analysis. In the IOTA studies, patients with an adnexal mass that were preoperatively examined by expert sonologists following the same standardized ultrasound protocol were prospectively included in 21 international centres. Sensitivity and specificity to discriminate endometriomas from other types of adnexal masses using pattern recognition were calculated. Ultrasound and some demographic variables of the masses presumed to be an endometrioma were analysed (true positives and false positives) and compared with the variables of the endometriomas missed by pattern recognition (false negatives) as well as the true negatives. Results: IOTA phase 1, 1b and 2 included 3511 patients of which 2560 were benign (73%) and 951 malignant (27%). The dataset included 713 endometriomas. Sensitivity and specificity for pattern recognition were 81% (577/713) and 97% (2723/2798). The true positives were more often unilocular with ground glass echogenicity than the masses in any other category. Among the 75 false positive cases, 66 were benign but 9 were malignant (5 borderline tumours, 1 rare primary invasive tumour and 3 endometrioid adenocarcinomas). The presumed diagnosis suggested by the sonologist in case of a missed endometrioma was mostly functional cyst or cystadenoma. Conclusion: Expert sonologists can quite accurately discriminate endometriomas from other types of adnexal masses, but in this dataset 1% of the masses that were classified as endometrioma by pattern recognition proved to be malignancies. PMID:25478066

Remote Video Monitor of Vehicles in Cooperative Information Platform

NASA Astrophysics Data System (ADS)

Qin, Guofeng; Wang, Xiaoguo; Wang, Li; Li, Yang; Li, Qiyan

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.

Musicians' working memory for tones, words, and pseudowords.

PubMed

Benassi-Werke, Mariana E; Queiroz, Marcelo; Araújo, Rúben S; Bueno, Orlando F A; Oliveira, Maria Gabriela M

2012-01-01

Studies investigating factors that influence tone recognition generally use recognition tests, whereas the majority of the studies on verbal material use self-generated responses in the form of serial recall tests. In the present study we intended to investigate whether tonal and verbal materials share the same cognitive mechanisms, by presenting an experimental instrument that evaluates short-term and working memories for tones, using self-generated sung responses that may be compared to verbal tests. This paradigm was designed according to the same structure of the forward and backward digit span tests, but using digits, pseudowords, and tones as stimuli. The profile of amateur singers and professional singers in these tests was compared in forward and backward digit, pseudoword, tone, and contour spans. In addition, an absolute pitch experimental group was included, in order to observe the possible use of verbal labels in tone memorization tasks. In general, we observed that musical schooling has a slight positive influence on the recall of tones, as opposed to verbal material, which is not influenced by musical schooling. Furthermore, the ability to reproduce melodic contours (up and down patterns) is generally higher than the ability to reproduce exact tone sequences. However, backward spans were lower than forward spans for all stimuli (digits, pseudowords, tones, contour). Curiously, backward spans were disproportionately lower for tones than for verbal material-that is, the requirement to recall sequences in backward rather than forward order seems to differentially affect tonal stimuli. This difference does not vary according to musical expertise.

Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.

PubMed

Ibrahim, Wisam; Abadeh, Mohammad Saniee

2017-05-21

Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid sequences to obtain better classifiers. In this paper, we have proposed six descriptors to extract features from protein sequences. These descriptors are applied in the first stage of a three-stage framework PCA-DELM-LDA to extract feature vectors from the amino-acid sequences. Principal Component Analysis PCA has been implemented to reduce the number of extracted features. The extracted feature vectors have been used with original features to improve the performance of the Deep Extreme Learning Machine DELM in the second stage. Four new features have been extracted from the second stage and used in the third stage by Linear Discriminant Analysis LDA to classify the instances into 27 folds. The proposed framework is implemented on the independent and combined feature sets in SCOP datasets. The experimental results show that extracted feature vectors in the first stage could improve the performance of DELM in extracting new useful features in second stage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Molecular evolution of the CYP2D subfamily in primates: purifying selection on substrate recognition sites without the frequent or long-tract gene conversion.

PubMed

Yasukochi, Yoshiki; Satta, Yoko

2015-03-25

The human cytochrome P450 (CYP) 2D6 gene is a member of the CYP2D gene subfamily, along with the CYP2D7P and CYP2D8P pseudogenes. Although the CYP2D6 enzyme has been studied extensively because of its clinical importance, the evolution of the CYP2D subfamily has not yet been fully understood. Therefore, the goal of this study was to reveal the evolutionary process of the human drug metabolic system. Here, we investigate molecular evolution of the CYP2D subfamily in primates by comparing 14 CYP2D sequences from humans to New World monkey genomes. Window analysis and statistical tests revealed that entire genomic sequences of paralogous genes were extensively homogenized by gene conversion during molecular evolution of CYP2D genes in primates. A neighbor-joining tree based on genomic sequences at the nonsubstrate recognition sites showed that CYP2D6 and CYP2D8 genes were clustered together due to gene conversion. In contrast, a phylogenetic tree using amino acid sequences at substrate recognition sites did not cluster the CYP2D6 and CYP2D8 genes, suggesting that the functional constraint on substrate specificity is one of the causes for purifying selection at the substrate recognition sites. Our results suggest that the CYP2D gene subfamily in primates has evolved to maintain the regioselectivity for a substrate hydroxylation activity between individual enzymes, even though extensive gene conversion has occurred across CYP2D coding sequences. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Molecular Evolution of the CYP2D Subfamily in Primates: Purifying Selection on Substrate Recognition Sites without the Frequent or Long-Tract Gene Conversion

PubMed Central

Yasukochi, Yoshiki; Satta, Yoko

2015-01-01

The human cytochrome P450 (CYP) 2D6 gene is a member of the CYP2D gene subfamily, along with the CYP2D7P and CYP2D8P pseudogenes. Although the CYP2D6 enzyme has been studied extensively because of its clinical importance, the evolution of the CYP2D subfamily has not yet been fully understood. Therefore, the goal of this study was to reveal the evolutionary process of the human drug metabolic system. Here, we investigate molecular evolution of the CYP2D subfamily in primates by comparing 14 CYP2D sequences from humans to New World monkey genomes. Window analysis and statistical tests revealed that entire genomic sequences of paralogous genes were extensively homogenized by gene conversion during molecular evolution of CYP2D genes in primates. A neighbor-joining tree based on genomic sequences at the nonsubstrate recognition sites showed that CYP2D6 and CYP2D8 genes were clustered together due to gene conversion. In contrast, a phylogenetic tree using amino acid sequences at substrate recognition sites did not cluster the CYP2D6 and CYP2D8 genes, suggesting that the functional constraint on substrate specificity is one of the causes for purifying selection at the substrate recognition sites. Our results suggest that the CYP2D gene subfamily in primates has evolved to maintain the regioselectivity for a substrate hydroxylation activity between individual enzymes, even though extensive gene conversion has occurred across CYP2D coding sequences. PMID:25808902

The Characteristics of Binary Spike-Time-Dependent Plasticity in HfO2-Based RRAM and Applications for Pattern Recognition

NASA Astrophysics Data System (ADS)

Zhou, Zheng; Liu, Chen; Shen, Wensheng; Dong, Zhen; Chen, Zhe; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2017-04-01

A binary spike-time-dependent plasticity (STDP) protocol based on one resistive-switching random access memory (RRAM) device was proposed and experimentally demonstrated in the fabricated RRAM array. Based on the STDP protocol, a novel unsupervised online pattern recognition system including RRAM synapses and CMOS neurons is developed. Our simulations show that the system can efficiently compete the handwritten digits recognition task, which indicates the feasibility of using the RRAM-based binary STDP protocol in neuromorphic computing systems to obtain good performance.

Developmentally programmed DNA splicing in Paramecium reveals short-distance crosstalk between DNA cleavage sites

PubMed Central

Gratias, Ariane; Lepère, Gersende; Garnier, Olivier; Rosa, Sarah; Duharcourt, Sandra; Malinsky, Sophie; Meyer, Eric; Bétermier, Mireille

2008-01-01

Somatic genome assembly in the ciliate Paramecium involves the precise excision of thousands of short internal eliminated sequences (IESs) that are scattered throughout the germline genome and often interrupt open reading frames. Excision is initiated by double-strand breaks centered on the TA dinucleotides that are conserved at each IES boundary, but the factors that drive cleavage site recognition remain unknown. A degenerate consensus was identified previously at IES ends and genetic analyses confirmed the participation of their nucleotide sequence in efficient excision. Even for wild-type IESs, however, variant excision patterns (excised or nonexcised) may be inherited maternally through sexual events, in a homology-dependent manner. We show here that this maternal epigenetic control interferes with the targeting of DNA breaks at IES ends. Furthermore, we demonstrate that a mutation in the TA at one end of an IES impairs DNA cleavage not only at the mutant end but also at the wild-type end. We conclude that crosstalk between both ends takes place prior to their cleavage and propose that the ability of an IES to adopt an excision-prone conformation depends on the combination of its nucleotide sequence and of additional determinants. PMID:18420657

Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

NASA Technical Reports Server (NTRS)

Saleeb, A. F.; Prabhu, M.; Arnold, S. M. (Technical Monitor)

2002-01-01

Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

Resolution of Site-Specific Conformational Heterogeneity in Proline-Rich Molecular Recognition by Src Homology 3 Domains.

PubMed

Horness, Rachel E; Basom, Edward J; Mayer, John P; Thielges, Megan C

2016-02-03

Conformational heterogeneity and dynamics are increasingly evoked in models of protein molecular recognition but are challenging to experimentally characterize. Here we combine the inherent temporal resolution of infrared (IR) spectroscopy with the spatial resolution afforded by selective incorporation of carbon-deuterium (C-D) bonds, which provide frequency-resolved absorptions within a protein IR spectrum, to characterize the molecular recognition of the Src homology 3 (SH3) domain of the yeast protein Sho1 with its cognate proline-rich (PR) sequence of Pbs2. The IR absorptions of C-D bonds introduced at residues along a peptide of the Pbs2 PR sequence report on the changes in the local environments upon binding to the SH3 domain. Interestingly, upon forming the complex the IR spectra of the peptides labeled with C-D bonds at either of the two conserved prolines of the PXXP consensus recognition sequence show more absorptions than there are C-D bonds, providing evidence for the population of multiple states. In contrast, the NMR spectra of the peptides labeled with (13)C at the same residues show only single resonances, indicating rapid interconversion on the NMR time scale. Thus, the data suggest that the SH3 domain recognizes its cognate peptide with a component of induced fit molecular recognition involving the adoption of multiples states, which have previously gone undetected due to interconversion between the populated states that is too fast to resolve using conventional methods.

Conformal Predictions in Multimedia Pattern Recognition

ERIC Educational Resources Information Center

Nallure Balasubramanian, Vineeth

2010-01-01

The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

Behavioral and Physiological Neural Network Analyses: A Common Pathway toward Pattern Recognition and Prediction

ERIC Educational Resources Information Center

Ninness, Chris; Lauter, Judy L.; Coffee, Michael; Clary, Logan; Kelly, Elizabeth; Rumph, Marilyn; Rumph, Robin; Kyle, Betty; Ninness, Sharon K.

2012-01-01

Using 3 diversified datasets, we explored the pattern-recognition ability of the Self-Organizing Map (SOM) artificial neural network as applied to diversified nonlinear data distributions in the areas of behavioral and physiological research. Experiment 1 employed a dataset obtained from the UCI Machine Learning Repository. Data for this study…

Pattern Recognition Receptors in Innate Immunity, Host Defense, and Immunopathology

ERIC Educational Resources Information Center

Suresh, Rahul; Mosser, David M.

2013-01-01

Infection by pathogenic microbes initiates a set of complex interactions between the pathogen and the host mediated by pattern recognition receptors. Innate immune responses play direct roles in host defense during the early stages of infection, and they also exert a profound influence on the generation of the adaptive immune responses that ensue.…

Machine Learning Through Signature Trees. Applications to Human Speech.

ERIC Educational Resources Information Center

White, George M.

A signature tree is a binary decision tree used to classify unknown patterns. An attempt was made to develop a computer program for manipulating signature trees as a general research tool for exploring machine learning and pattern recognition. The program was applied to the problem of speech recognition to test its effectiveness for a specific…

Spectral pattern recognition of controlled substances in street samples using artificial neural network system

NASA Astrophysics Data System (ADS)

Poryvkina, Larisa; Aleksejev, Valeri; Babichenko, Sergey M.; Ivkina, Tatjana

2011-04-01

The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

Real-Time Pattern Recognition - An Industrial Example

NASA Astrophysics Data System (ADS)

Fitton, Gary M.

1981-11-01

Rapid advancements in cost effective sensors and micro computers are now making practical the on-line implementation of pattern recognition based systems for a variety of industrial applications requiring high processing speeds. One major application area for real time pattern recognition is in the sorting of packaged/cartoned goods at high speed for automated warehousing and return goods cataloging. While there are many OCR and bar code readers available to perform these functions, it is often impractical to use such codes (package too small, adverse esthetics, poor print quality) and an approach which recognizes an item by its graphic content alone is desirable. This paper describes a specific application within the tobacco industry, that of sorting returned cigarette goods by brand and size.

Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

PubMed

Hipp, Jason D; Cheng, Jerome Y; Toner, Mehmet; Tompkins, Ronald G; Balis, Ulysses J

2011-02-26

HISTORICALLY, EFFECTIVE CLINICAL UTILIZATION OF IMAGE ANALYSIS AND PATTERN RECOGNITION ALGORITHMS IN PATHOLOGY HAS BEEN HAMPERED BY TWO CRITICAL LIMITATIONS: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution. We anticipate that SIVQ, and other related class-independent pattern recognition algorithms, will become part of the overall armamentarium of digital image analysis approaches that are immediately available to practicing pathologists, without the need for the immediate availability of an image analysis expert.

Receptor Kinases in Plant-Pathogen Interactions: More Than Pattern Recognition[OPEN

PubMed Central

2017-01-01

Receptor-like kinases (RLKs) and Receptor-like proteins (RLPs) play crucial roles in plant immunity, growth, and development. Plants deploy a large number of RLKs and RLPs as pattern recognition receptors (PRRs) that detect microbe- and host-derived molecular patterns as the first layer of inducible defense. Recent advances have uncovered novel PRRs, their corresponding ligands, and mechanisms underlying PRR activation and signaling. In general, PRRs associate with other RLKs and function as part of multiprotein immune complexes at the cell surface. Innovative strategies have emerged for the rapid identification of microbial patterns and their cognate PRRs. Successful pathogens can evade or block host recognition by secreting effector proteins to “hide” microbial patterns or inhibit PRR-mediated signaling. Furthermore, newly identified pathogen effectors have been shown to manipulate RLKs controlling growth and development by mimicking peptide hormones of host plants. The ongoing studies illustrate the importance of diverse plant RLKs in plant disease resistance and microbial pathogenesis. PMID:28302675

Developing Signal-Pattern-Recognition Programs

NASA Technical Reports Server (NTRS)

Shelton, Robert O.; Hammen, David

2006-01-01

Pattern Interpretation and Recognition Application Toolkit Environment (PIRATE) is a block-oriented software system that aids the development of application programs that analyze signals in real time in order to recognize signal patterns that are indicative of conditions or events of interest. PIRATE was originally intended for use in writing application programs to recognize patterns in space-shuttle telemetry signals received at Johnson Space Center's Mission Control Center: application programs were sought to (1) monitor electric currents on shuttle ac power busses to recognize activations of specific power-consuming devices, (2) monitor various pressures and infer the states of affected systems by applying a Kalman filter to the pressure signals, (3) determine fuel-leak rates from sensor data, (4) detect faults in gyroscopes through analysis of system measurements in the frequency domain, and (5) determine drift rates in inertial measurement units by regressing measurements against time. PIRATE can also be used to develop signal-pattern-recognition software for different purposes -- for example, to monitor and control manufacturing processes.

Document Form and Character Recognition using SVM

NASA Astrophysics Data System (ADS)

Park, Sang-Sung; Shin, Young-Geun; Jung, Won-Kyo; Ahn, Dong-Kyu; Jang, Dong-Sik

2009-08-01

Because of development of computer and information communication, EDI (Electronic Data Interchange) has been developing. There is OCR (Optical Character Recognition) of Pattern recognition technology for EDI. OCR contributed to changing many manual in the past into automation. But for the more perfect database of document, much manual is needed for excluding unnecessary recognition. To resolve this problem, we propose document form based character recognition method in this study. Proposed method is divided into document form recognition part and character recognition part. Especially, in character recognition, change character into binarization by using SVM algorithm and extract more correct feature value.

Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic.

PubMed

Hou, Shi-Wang; Feng, Shunxiao; Wang, Hui

2016-01-01

Locating the assignable causes by use of the abnormal patterns of control chart is a widely used technology for manufacturing quality control. If there are uncertainties about the occurrence degree of abnormal patterns, the diagnosis process is impossible to be carried out. Considering four common abnormal control chart patterns, this paper proposed a characteristic numbers based recognition method point by point to quantify the occurrence degree of abnormal patterns under uncertain conditions and a fuzzy inference system based on fuzzy logic to calculate the contribution degree of assignable causes with fuzzy abnormal patterns. Application case results show that the proposed approach can give a ranked causes list under fuzzy control chart abnormal patterns and support the abnormity eliminating.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

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

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

The immunotranscriptome of the Caribbean reef-building coral Pseudodiploria strigosa.

PubMed

Ocampo, Iván D; Zárate-Potes, Alejandra; Pizarro, Valeria; Rojas, Cristian A; Vera, Nelson E; Cadavid, Luis F

2015-09-01

The viability of coral reefs worldwide has been seriously compromised in the last few decades due in part to the emergence of coral diseases of infectious nature. Despite important efforts to understand the etiology and the contribution of environmental factors associated to coral diseases, the mechanisms of immune response in corals are just beginning to be studied systematically. In this study, we analyzed the set of conserved immune response genes of the Caribbean reef-building coral Pseudodiploria strigosa by Illumina-based transcriptome sequencing and annotation of healthy colonies challenged with whole live Gram-positive and Gram-negative bacteria. Searching the annotated transcriptome with immune-related terms yielded a total of 2782 transcripts predicted to encode conserved immune-related proteins that were classified into three modules: (a) the immune recognition module, containing a wide diversity of putative pattern recognition receptors including leucine-rich repeat-containing proteins, immunoglobulin superfamily receptors, representatives of various lectin families, and scavenger receptors; (b) the intracellular signaling module, containing components from the Toll-like receptor, transforming growth factor, MAPK, and apoptosis signaling pathways; and (3) the effector module, including the C3 and factor B complement components, a variety of proteases and protease inhibitors, and the melanization-inducing phenoloxidase. P. strigosa displays a highly variable and diverse immune recognition repertoire that has likely contributed to its resilience to coral diseases.

Phenotypic and genotypic expression of self-incompatibility haplotypes in Arabidopsis lyrata suggests unique origin of alleles in different dominance classes.

PubMed

Prigoda, Nadia L; Nassuth, Annette; Mable, Barbara K

2005-07-01

The highly divergent alleles of the SRK gene in outcrossing Arabidopsis lyrata have provided important insights into the evolutionary history of self-incompatibility (SI) alleles and serve as an ideal model for studies of the evolutionary and molecular interactions between alleles in cell-cell recognition systems in general. One tantalizing question is how new specificities arise in systems that require coordination between male and female components. Allelic recruitment via gene conversion has been proposed as one possibility, based on the division of DNA sequences at the SRK locus into two distinctive groups: (1) sequences whose relationships are not well resolved and display the long branch lengths expected for a gene under balancing selection (Class A); and (2) sequences falling into a well-supported group with shorter branch lengths (Class B) that are closely related to an unlinked paralogous locus. The purpose of this study was to determine if differences in phenotype (site of expression assayed using allele-specific reverse transcription-polymerase chain reaction) or function (dominance relationships assayed through controlled pollinations) accompany the sequence-based classification. Expression of Class A alleles was restricted to floral tissues, as predicted for genes involved in the SI response. In contrast, Class B alleles, despite being tightly linked to the SI phenotype, were unexpectedly expressed in both leaves and floral tissues; the same pattern found for a related unlinked paralogous sequence. Whereas Class A included haplotypes in three different dominance classes, all Class B haplotypes were found to be recessive to all except one Class A haplotype. In addition, mapping of expression and dominance patterns onto an S-domain-based genealogy suggested that allelic dominance may be determined more by evolutionary history than by frequency-dependent selection for lowered dominance as some theories suggest. The possibility that interlocus gene conversion might have contributed to allelic diversity is discussed.

Direct protein interaction underlies gene-for-gene specificity and coevolution of the flax resistance genes and flax rust avirulence genes

PubMed Central

Dodds, Peter N.; Lawrence, Gregory J.; Catanzariti, Ann-Maree; Teh, Trazel; Wang, Ching-I. A.; Ayliffe, Michael A.; Kobe, Bostjan; Ellis, Jeffrey G.

2006-01-01

Plant resistance proteins (R proteins) recognize corresponding pathogen avirulence (Avr) proteins either indirectly through detection of changes in their host protein targets or through direct R–Avr protein interaction. Although indirect recognition imposes selection against Avr effector function, pathogen effector molecules recognized through direct interaction may overcome resistance through sequence diversification rather than loss of function. Here we show that the flax rust fungus AvrL567 genes, whose products are recognized by the L5, L6, and L7 R proteins of flax, are highly diverse, with 12 sequence variants identified from six rust strains. Seven AvrL567 variants derived from Avr alleles induce necrotic responses when expressed in flax plants containing corresponding resistance genes (R genes), whereas five variants from avr alleles do not. Differences in recognition specificity between AvrL567 variants and evidence for diversifying selection acting on these genes suggest they have been involved in a gene-specific arms race with the corresponding flax R genes. Yeast two-hybrid assays indicate that recognition is based on direct R–Avr protein interaction and recapitulate the interaction specificity observed in planta. Biochemical analysis of Escherichia coli-produced AvrL567 proteins shows that variants that escape recognition nevertheless maintain a conserved structure and stability, suggesting that the amino acid sequence differences directly affect the R–Avr protein interaction. We suggest that direct recognition associated with high genetic diversity at corresponding R and Avr gene loci represents an alternative outcome of plant–pathogen coevolution to indirect recognition associated with simple balanced polymorphisms for functional and nonfunctional R and Avr genes. PMID:16731621

p53 Specifically Binds Triplex DNA In Vitro and in Cells

PubMed Central

Brázdová, Marie; Tichý, Vlastimil; Helma, Robert; Bažantová, Pavla; Polášková, Alena; Krejčí, Aneta; Petr, Marek; Navrátilová, Lucie; Tichá, Olga; Nejedlý, Karel; Bennink, Martin L.; Subramaniam, Vinod; Bábková, Zuzana; Martínek, Tomáš; Lexa, Matej; Adámik, Matej

2016-01-01

Triplex DNA is implicated in a wide range of biological activities, including regulation of gene expression and genomic instability leading to cancer. The tumor suppressor p53 is a central regulator of cell fate in response to different type of insults. Sequence and structure specific modes of DNA recognition are core attributes of the p53 protein. The focus of this work is the structure-specific binding of p53 to DNA containing triplex-forming sequences in vitro and in cells and the effect on p53-driven transcription. This is the first DNA binding study of full-length p53 and its deletion variants to both intermolecular and intramolecular T.A.T triplexes. We demonstrate that the interaction of p53 with intermolecular T.A.T triplex is comparable to the recognition of CTG-hairpin non-B DNA structure. Using deletion mutants we determined the C-terminal DNA binding domain of p53 to be crucial for triplex recognition. Furthermore, strong p53 recognition of intramolecular T.A.T triplexes (H-DNA), stabilized by negative superhelicity in plasmid DNA, was detected by competition and immunoprecipitation experiments, and visualized by AFM. Moreover, chromatin immunoprecipitation revealed p53 binding T.A.T forming sequence in vivo. Enhanced reporter transactivation by p53 on insertion of triplex forming sequence into plasmid with p53 consensus sequence was observed by luciferase reporter assays. In-silico scan of human regulatory regions for the simultaneous presence of both consensus sequence and T.A.T motifs identified a set of candidate p53 target genes and p53-dependent activation of several of them (ABCG5, ENOX1, INSR, MCC, NFAT5) was confirmed by RT-qPCR. Our results show that T.A.T triplex comprises a new class of p53 binding sites targeted by p53 in a DNA structure-dependent mode in vitro and in cells. The contribution of p53 DNA structure-dependent binding to the regulation of transcription is discussed. PMID:27907175

Quantum Mechanics, Pattern Recognition, and the Mammalian Brain

NASA Astrophysics Data System (ADS)

Chapline, George

2008-10-01

Although the usual way of representing Markov processes is time asymmetric, there is a way of describing Markov processes, due to Schrodinger, which is time symmetric. This observation provides a link between quantum mechanics and the layered Bayesian networks that are often used in automated pattern recognition systems. In particular, there is a striking formal similarity between quantum mechanics and a particular type of Bayesian network, the Helmholtz machine, which provides a plausible model for how the mammalian brain recognizes important environmental situations. One interesting aspect of this relationship is that the "wake-sleep" algorithm for training a Helmholtz machine is very similar to the problem of finding the potential for the multi-channel Schrodinger equation. As a practical application of this insight it may be possible to use inverse scattering techniques to study the relationship between human brain wave patterns, pattern recognition, and learning. We also comment on whether there is a relationship between quantum measurements and consciousness.

Autoregressive statistical pattern recognition algorithms for damage detection in civil structures

NASA Astrophysics Data System (ADS)

Yao, Ruigen; Pakzad, Shamim N.

2012-08-01

Statistical pattern recognition has recently emerged as a promising set of complementary methods to system identification for automatic structural damage assessment. Its essence is to use well-known concepts in statistics for boundary definition of different pattern classes, such as those for damaged and undamaged structures. In this paper, several statistical pattern recognition algorithms using autoregressive models, including statistical control charts and hypothesis testing, are reviewed as potentially competitive damage detection techniques. To enhance the performance of statistical methods, new feature extraction techniques using model spectra and residual autocorrelation, together with resampling-based threshold construction methods, are proposed. Subsequently, simulated acceleration data from a multi degree-of-freedom system is generated to test and compare the efficiency of the existing and proposed algorithms. Data from laboratory experiments conducted on a truss and a large-scale bridge slab model are then used to further validate the damage detection methods and demonstrate the superior performance of proposed algorithms.

Fuel spill identification using solid-phase extraction and solid-phase microextraction. 1. Aviation turbine fuels.

PubMed

Lavine, B K; Brzozowski, D M; Ritter, J; Moores, A J; Mayfield, H T

2001-12-01

The water-soluble fraction of aviation jet fuels is examined using solid-phase extraction and solid-phase microextraction. Gas chromatographic profiles of solid-phase extracts and solid-phase microextracts of the water-soluble fraction of kerosene- and nonkerosene-based jet fuels reveal that each jet fuel possesses a unique profile. Pattern recognition analysis reveals fingerprint patterns within the data characteristic of fuel type. By using a novel genetic algorithm (GA) that emulates human pattern recognition through machine learning, it is possible to identify features characteristic of the chromatographic profile of each fuel class. The pattern recognition GA identifies a set of features that optimize the separation of the fuel classes in a plot of the two largest principal components of the data. Because principal components maximize variance, the bulk of the information encoded by the selected features is primarily about the differences between the fuel classes.

Comparative study of methods for recognition of an unknown person's action from a video sequence

NASA Astrophysics Data System (ADS)

Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun

2009-02-01

This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.

Fuzzy tree automata and syntactic pattern recognition.

PubMed

Lee, E T

1982-04-01

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

Complex Event Recognition Architecture

NASA Technical Reports Server (NTRS)

Fitzgerald, William A.; Firby, R. James

2009-01-01

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

Cross-Cultural Patterns in Dynamic Ratings of Positive and Negative Natural Emotional Behaviour

PubMed Central

Sneddon, Ian; McKeown, Gary; McRorie, Margaret; Vukicevic, Tijana

2011-01-01

Background Studies of cross-cultural variations in the perception of emotion have typically compared rates of recognition of static posed stimulus photographs. That research has provided evidence for universality in the recognition of a range of emotions but also for some systematic cross-cultural variation in the interpretation of emotional expression. However, questions remain about how widely such findings can be generalised to real life emotional situations. The present study provides the first evidence that the previously reported interplay between universal and cultural influences extends to ratings of natural, dynamic emotional stimuli. Methodology/Principal Findings Participants from Northern Ireland, Serbia, Guatemala and Peru used a computer based tool to continuously rate the strength of positive and negative emotion being displayed in twelve short video sequences by people from the United Kingdom engaged in emotional conversations. Generalized additive mixed models were developed to assess the differences in perception of emotion between countries and sexes. Our results indicate that the temporal pattern of ratings is similar across cultures for a range of emotions and social contexts. However, there are systematic differences in intensity ratings between the countries, with participants from Northern Ireland making the most extreme ratings in the majority of the clips. Conclusions/Significance The results indicate that there is strong agreement across cultures in the valence and patterns of ratings of natural emotional situations but that participants from different cultures show systematic variation in the intensity with which they rate emotion. Results are discussed in terms of both ‘in-group advantage’ and ‘display rules’ approaches. This study indicates that examples of natural spontaneous emotional behaviour can be used to study cross-cultural variations in the perception of emotion. PMID:21364739