Oral candidosis in relation to oral immunity.

PubMed

Feller, L; Khammissa, R A G; Chandran, R; Altini, M; Lemmer, J

2014-09-01

Symptomatic oral infection with Candida albicans is characterized by invasion of the oral epithelium by virulent hyphae that cause tissue damage releasing the inflammatory mediators that initiate and sustain local inflammation. Candida albicans triggers pattern-recognition receptors of keratinocytes, macrophages, monocytes and dendritic cells, stimulating the production of IL-1β, IL-6 and IL-23. These cytokines induce the differentiation of Th17 cells and the generation of IL-17- and/or IL-22-mediated antifungal protective immuno-inflammatory responses in infected mucosa. Some immune cells including NKT cells, γδ T cells and lymphoid cells that are innate to the oral mucosa have the capacity to produce large quantities of IL-17 in response to C. albicans, sufficient to mediate effective protective immunity against C. albicans. On the other hand, molecular structures of commensal C. albicans blastoconidia, although detected by pattern-recognition receptors, are avirulent, do not invade the oral epithelium, do not elicit inflammatory responses in a healthy host, but induce regulatory immune responses that maintain tissue tolerance to the commensal fungi. The type, specificity and sensitivity of the protective immune response towards C. albicans is determined by the outcome of the integrated interactions between the intracellular signalling pathways of specific combinations of activated pattern-recognition receptors (TLR2, TLR4, Dectin-1 and Dectin-2). IL-17-mediated protective immune response is essential for oral mucosal immunity to C. albicans infection. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Modeling the Regulatory Mechanisms by Which NLRX1 Modulates Innate Immune Responses to Helicobacter pylori Infection

PubMed Central

Philipson, Casandra W.; Bassaganya-Riera, Josep; Viladomiu, Monica; Kronsteiner, Barbara; Abedi, Vida; Hoops, Stefan; Michalak, Pawel; Kang, Lin; Girardin, Stephen E.; Hontecillas, Raquel

2015-01-01

Helicobacter pylori colonizes half of the world’s population as the dominant member of the gastric microbiota resulting in a lifelong chronic infection. Host responses toward the bacterium can result in asymptomatic, pathogenic or even favorable health outcomes; however, mechanisms underlying the dual role of H. pylori as a commensal versus pathogenic organism are not well characterized. Recent evidence suggests mononuclear phagocytes are largely involved in shaping dominant immunity during infection mediating the balance between host tolerance and succumbing to overt disease. We combined computational modeling, bioinformatics and experimental validation in order to investigate interactions between macrophages and intracellular H. pylori. Global transcriptomic analysis on bone marrow-derived macrophages (BMDM) in a gentamycin protection assay at six time points unveiled the presence of three sequential host response waves: an early transient regulatory gene module followed by sustained and late effector responses. Kinetic behaviors of pattern recognition receptors (PRRs) are linked to differential expression of spatiotemporal response waves and function to induce effector immunity through extracellular and intracellular detection of H. pylori. We report that bacterial interaction with the host intracellular environment caused significant suppression of regulatory NLRC3 and NLRX1 in a pattern inverse to early regulatory responses. To further delineate complex immune responses and pathway crosstalk between effector and regulatory PRRs, we built a computational model calibrated using time-series RNAseq data. Our validated computational hypotheses are that: 1) NLRX1 expression regulates bacterial burden in macrophages; and 2) early host response cytokines down-regulate NLRX1 expression through a negative feedback circuit. This paper applies modeling approaches to characterize the regulatory role of NLRX1 in mechanisms of host tolerance employed by macrophages to respond to and/or to co-exist with intracellular H. pylori. PMID:26367386

Self-organization principles of intracellular pattern formation.

PubMed

Halatek, J; Brauns, F; Frey, E

2018-05-26

Dynamic patterning of specific proteins is essential for the spatio-temporal regulation of many important intracellular processes in prokaryotes, eukaryotes and multicellular organisms. The emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for self-organization. In this article, we review quantitative models for intracellular Min protein patterns in Escherichia coli , Cdc42 polarization in Saccharomyces cerevisiae and the bipolar PAR protein patterns found in Caenorhabditis elegans By analysing the molecular processes driving these systems we derive a theoretical perspective on general principles underlying self-organized pattern formation. We argue that intracellular pattern formation is not captured by concepts such as 'activators', 'inhibitors' or 'substrate depletion'. Instead, intracellular pattern formation is based on the redistribution of proteins by cytosolic diffusion, and the cycling of proteins between distinct conformational states. Therefore, mass-conserving reaction-diffusion equations provide the most appropriate framework to study intracellular pattern formation. We conclude that directed transport, e.g. cytosolic diffusion along an actively maintained cytosolic gradient, is the key process underlying pattern formation. Thus the basic principle of self-organization is the establishment and maintenance of directed transport by intracellular protein dynamics.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Authors.

Porphyromonas gingivalis evasion of autophagy and intracellular killing by human myeloid dendritic cells involves DC-SIGN-TLR2 crosstalk.

PubMed

El-Awady, Ahmed R; Miles, Brodie; Scisci, Elizabeth; Kurago, Zoya B; Palani, Chithra D; Arce, Roger M; Waller, Jennifer L; Genco, Caroline A; Slocum, Connie; Manning, Matthew; Schoenlein, Patricia V; Cutler, Christopher W

2015-02-01

Signaling via pattern recognition receptors (PRRs) expressed on professional antigen presenting cells, such as dendritic cells (DCs), is crucial to the fate of engulfed microbes. Among the many PRRs expressed by DCs are Toll-like receptors (TLRs) and C-type lectins such as DC-SIGN. DC-SIGN is targeted by several major human pathogens for immune-evasion, although its role in intracellular routing of pathogens to autophagosomes is poorly understood. Here we examined the role of DC-SIGN and TLRs in evasion of autophagy and survival of Porphyromonas gingivalis in human monocyte-derived DCs (MoDCs). We employed a panel of P. gingivalis isogenic fimbriae deficient strains with defined defects in Mfa-1 fimbriae, a DC-SIGN ligand, and FimA fimbriae, a TLR2 agonist. Our results show that DC-SIGN dependent uptake of Mfa1+P. gingivalis strains by MoDCs resulted in lower intracellular killing and higher intracellular content of P. gingivalis. Moreover, Mfa1+P. gingivalis was mostly contained within single membrane vesicles, where it survived intracellularly. Survival was decreased by activation of TLR2 and/or autophagy. Mfa1+P. gingivalis strain did not induce significant levels of Rab5, LC3-II, and LAMP1. In contrast, P. gingivalis uptake through a DC-SIGN independent manner was associated with early endosomal routing through Rab5, increased LC3-II and LAMP-1, as well as the formation of double membrane intracellular phagophores, a characteristic feature of autophagy. These results suggest that selective engagement of DC-SIGN by Mfa-1+P. gingivalis promotes evasion of antibacterial autophagy and lysosome fusion, resulting in intracellular persistence in myeloid DCs; however TLR2 activation can overcome autophagy evasion and pathogen persistence in DCs.

Phosphorylation of Arabidopsis MAP Kinase Phosphatase 1 (MKP1) Is Required for PAMP Responses and Resistance against Bacteria1[OPEN

PubMed Central

Jiang, Lingyan; Anderson, Jeffrey C.; Besteiro, Marina A. González

2017-01-01

Plants perceive potential pathogens via the recognition of pathogen-associated molecular patterns (PAMPs) by surface-localized pattern recognition receptors, which initiates a series of intracellular responses that ultimately limit bacterial growth. PAMP responses include changes in intracellular protein phosphorylation, including the activation of mitogen-activated protein kinase (MAPK) cascades. MAP kinase phosphatases (MKPs), such as Arabidopsis (Arabidopsis thaliana) MKP1, are important negative regulators of MAPKs and play a crucial role in controlling the intensity and duration of MAPK activation during innate immune signaling. As such, the mkp1 mutant lacking MKP1 displays enhanced PAMP responses and resistance against the virulent bacterium Pseudomonas syringae pv tomato DC3000. Previous in vitro studies showed that MKP1 can be phosphorylated and activated by MPK6, suggesting that phosphorylation may be an important mechanism for regulating MKP1. We found that MKP1 was phosphorylated during PAMP elicitation and that phosphorylation stabilized the protein, resulting in protein accumulation after elicitation. MKP1 also can be stabilized by the proteasome inhibitor MG132, suggesting that MKP1 is constitutively degraded through the proteasome in the resting state. In addition, we investigated the role of MKP1 posttranslational regulation in plant defense by testing whether phenotypes of the mkp1 Arabidopsis mutant could be complemented by expressing phosphorylation site mutations of MKP1. The phosphorylation of MKP1 was found to be required for some, but not all, of MKP1’s functions in PAMP responses and defense against bacteria. Together, our results provide insight into the roles of phosphorylation in the regulation of MKP1 during PAMP signaling and resistance to bacteria. PMID:29070514

Eosinophils Subvert Host Resistance to an Intracellular Pathogen by Instigating Non-Protective IL-4 in CCR2−/− Mice

PubMed Central

Verma, Akash H.; Bueter, Chelsea L.; Rothenberg, Marc E.; Deepe, George S.

2016-01-01

Eosinophils contribute to type II immune responses in helminth infections and allergic diseases, however, their influence on intracellular pathogens is less clear. We previously reported that CCR2−/− mice exposed to the intracellular fungal pathogen Histoplasma capsulatum exhibit dampened immunity caused by an early exaggerated IL-4 response. We sought to identify the cellular source promulgating interleukin (IL)-4 in infected mutant animals. Eosinophils were the principal instigators of non-protective IL-4 and depleting this granulocyte population improved fungal clearance in CCR2−/− animals. The deleterious impact of eosinophilia on mycosis was also recapitulated in transgenic animals overexpressing eosinophils. Mechanistic examination of IL-4 induction revealed that phagocytosis of H. capsulatum via the pattern recognition receptor complement receptor (CR) 3 triggered the heightened IL-4 response in murine eosinophils. This phenomenon was conserved in human eosinophils; exposure of cells to the fungal pathogen elicited a robust IL-4 response. Thus, our findings elucidate a detrimental attribute of eosinophil biology in fungal infections that could potentially trigger a collapse in host defenses by instigating type II immunity. PMID:27049063

Influx of extracellular Zn(2+) into the hippocampal CA1 neurons is required for cognitive performance via long-term potentiation.

PubMed

Takeda, A; Suzuki, M; Tempaku, M; Ohashi, K; Tamano, H

2015-09-24

Physiological significance of synaptic Zn(2+) signaling was examined in the CA1 of young rats. In vivo CA1 long-term potentiation (LTP) was induced using a recording electrode attached to a microdialysis probe and the recording region was locally perfused with artificial cerebrospinal fluid (ACSF) via the microdialysis probe. In vivo CA1 LTP was inhibited under perfusion with CaEDTA and ZnAF-2DA, extracellular and intracellular Zn(2+) chelators, respectively, suggesting that the influx of extracellular Zn(2+) is required for in vivo CA1 LTP induction. The increase in intracellular Zn(2+) was chelated with intracellular ZnAF-2 in the CA1 1h after local injection of ZnAF-2DA into the CA1, suggesting that intracellular Zn(2+) signaling induced during learning is blocked with intracellular ZnAF-2 when the learning was performed 1h after ZnAF-2DA injection. Object recognition was affected when training of object recognition test was performed 1h after ZnAF-2DA injection. These data suggest that intracellular Zn(2+) signaling in the CA1 is required for object recognition memory via LTP. Surprisingly, in vivo CA1 LTP was affected under perfusion with 0.1-1μM ZnCl2, unlike the previous data that in vitro CA1 LTP was enhanced in the presence of 1-5μM ZnCl2. The influx of extracellular Zn(2+) into CA1 pyramidal cells has bidirectional action in CA1 LTP. The present study indicates that the degree of extracellular Zn(2+) influx into CA1 neurons is critical for LTP and cognitive performance. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

The phenotype and function of preterm infant monocytes: implications for susceptibility to infection.

PubMed

de Jong, Emma; Strunk, Tobias; Burgner, David; Lavoie, Pascal M; Currie, Andrew

2017-09-01

The extreme vulnerability of preterm infants to invasive microbial infections has been attributed to "immature" innate immune defenses. Monocytes are important innate immune sentinel cells critical in the defense against infection in blood. They achieve this via diverse mechanisms that include pathogen recognition receptor- and inflammasome-mediated detection of microbes, migration into infected tissues, and differentiation into Mϕs and dendritic cells, initiation of the inflammatory cascade by free radicals and cytokine/chemokine production, pathogen clearance by phagocytosis and intracellular killing, and the removal of apoptotic cells. Relatively little is known about these cells in preterm infants, especially about how their phenotype adapts to changes in the microbial environment during the immediate postnatal period. Overall, preterm monocytes exhibit attenuated proinflammatory cytokine responses following stimulation by whole bacterial or specific microbial components in vitro. These attenuated cytokine responses cannot be explained by a lack of intracellular signaling events downstream of pattern recognition receptors. This hyporesponsiveness also contrasts with mature, term-like phagocytosis capabilities detectable even in the most premature infant. Finally, human data on the effects of fetal chorioamnionitis on monocyte biology are incomplete and inconsistent. In this review, we present an integrated view of human studies focused on monocyte functions in preterm infants. We discuss how a developmental immaturity of these cells may contribute to preterm infants' susceptibility to infections. © Society for Leukocyte Biology.

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

Innate immunity of fish (overview).

PubMed

Magnadóttir, Bergljót

2006-02-01

The innate immune system is the only defence weapon of invertebrates and a fundamental defence mechanism of fish. The innate system also plays an instructive role in the acquired immune response and homeostasis and is therefore equally important in higher vertebrates. The innate system's recognition of non-self and danger signals is served by a limited number of germ-line encoded pattern recognition receptors/proteins, which recognise pathogen associated molecular patterns like bacterial and fungal glycoproteins and lipopolysaccharides and intracellular components released through injury or infection. The innate immune system is divided into physical barriers, cellular and humoral components. Humoral parameters include growth inhibitors, various lytic enzymes and components of the complement pathways, agglutinins and precipitins (opsonins, primarily lectins), natural antibodies, cytokines, chemokines and antibacterial peptides. Several external and internal factors can influence the activity of innate immune parameters. Temperature changes, handling and crowding stress can have suppressive effects on innate parameters, whereas several food additives and immunostimulants can enhance different innate factors. There is limited data available about the ontogenic development of the innate immunological system in fish. Active phagocytes, complement components and enzyme activity, like lysozyme and cathepsins, are present early in the development, before or soon after hatching.

Structure and Functional Characterization of the RNA-Binding Element of the NLRX1 Innate Immune Modulator

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

Hong, Minsun; Yoon, Sung-il; Wilson, Ian A.

2012-06-20

Mitochondrial NLRX1 is a member of the family of nucleotide-binding domain and leucine-rich-repeat-containing proteins (NLRs) that mediate host innate immunity as intracellular surveillance sensors against common molecular patterns of invading pathogens. NLRX1 functions in antiviral immunity, but the molecular mechanism of its ligand-induced activation is largely unknown. The crystal structure of the C-terminal fragment (residues 629975) of human NLRX1 (cNLRX1) at 2.65 {angstrom} resolution reveals that cNLRX1 consists of an N-terminal helical (LRRNT) domain, central leucine-rich repeat modules (LRRM), and a C-terminal three-helix bundle (LRRCT). cNLRX1 assembles into a compact hexameric architecture that is stabilized by intersubunit and interdomain interactionsmore » of LRRNT and LRRCT in the trimer and dimer components of the hexamer, respectively. Furthermore, we find that cNLRX1 interacts directly with RNA and supports a role for NLRX1 in recognition of intracellular viral RNA in antiviral immunity.« less

Viral evasion of intracellular DNA and RNA sensing

PubMed Central

Chan, Ying Kai; Gack, Michaela U.

2016-01-01

The co-evolution of viruses with their hosts has led to the emergence of viral pathogens that are adept at evading or actively suppressing host immunity. Pattern recognition receptors (PRRs) are key components of antiviral immunity that detect conserved molecular features of viral pathogens and initiate signalling that results in the expression of antiviral genes. In this Review, we discuss the strategies that viruses use to escape immune surveillance by key intracellular sensors of viral RNA or DNA, with a focus on RIG-I-like receptors (RLRs), cyclic GMP–AMP synthase (cGAS) and interferon-γ (IFNγ)-inducible protein 16 (IFI16). Such viral strategies include the sequestration or modification of viral nucleic acids, interference with specific post-translational modifications of PRRs or their adaptor proteins, the degradation or cleavage of PRRs or their adaptors, and the sequestration or relocalization of PRRs. An understanding of viral immune-evasion mechanisms at the molecular level may guide the development of vaccines and antivirals. PMID:27174148

The Tandem CARDs of NOD2: Intramolecular Interactions and Recognition of RIP2

PubMed Central

Fridh, Veronica; Rittinger, Katrin

2012-01-01

Caspase recruitment domains (CARDs) are homotypic protein interaction modules that link the stimulus-dependent assembly of large signaling platforms such as inflammasomes to the activation of downstream effectors that often include caspases and kinases and thereby play an important role in the regulation of inflammatory and apoptotic signaling pathways. NOD2 belongs to the NOD-like (NLR) family of intracellular pattern recognition receptors (PRR) and induces activation of the NF-κB pathway in response to the recognition of bacterial components. This process requires the specific recognition of the CARD of the protein kinase RIP2 by the tandem CARDs of NOD2. Here we demonstrate that the tandem CARDs of NOD2 are engaged in an intramolecular interaction that is important for the structural stability of this region. Using a combination of ITC and pull-down experiments we identify distinct surface areas that are involved in the intramolecular tandem CARD interaction and the interaction with the downstream effector RIP2. Our findings indicate that while CARDa of NOD2 might be the primary binding partner of RIP2 the two CARDs of NOD2 do not act independently of one another but may cooperate to from a binding surface that is distinct from that of single CARDs. PMID:22470564

The Janus face of α-toxin: a potent mediator of cytoprotection in staphylococci-infected macrophages.

PubMed

Koziel, Joanna; Chmiest, Daniela; Bryzek, Danuta; Kmiecik, Katarzyna; Mizgalska, Danuta; Maciag-Gudowska, Agnieszka; Shaw, Lindsey N; Potempa, Jan

2015-01-01

After phagocytosis by macrophages, Staphylococcus aureus evades killing in an α-toxin-dependent manner, and then prevents apoptosis of infected cells by upregulating expression of antiapoptotic genes like MCL-1 (myeloid cell leukemia-1). Here, using purified α-toxin and a set of hla-deficient strains, we show that α-toxin is critical for the induction of MCL-1 expression and the cytoprotection of infected macrophages. Extracellular or intracellular treatment of macrophages with α-toxin alone did not induce cytoprotection conferred by increased Mcl-1, suggesting that the process is dependent on the production of α-toxin by intracellular bacteria. The increased expression of MCL-1 in infected cells was associated with enhanced NFκB activation, and subsequent IL-6 secretion. This effect was only partially inhibited by blocking TLR2, which suggests the participation of intracellular receptors in the specific recognition of S. aureus strains secreting α-toxin. Thus, S. aureus recognition by intracellular receptors and/or activation of downstream pathways leading to Mcl-1 expression is facilitated by α-toxin released by intracellular bacteria which permeabilize phagosomes, ensuring pathogen access to the cytoplasmatic compartment. Given that the intracellular survival of S. aureus depends on α-toxin, we propose a novel role for this agent in the protection of the intracellular niche, and further dissemination of staphylococci by infected macrophages. © 2014 S. Karger AG, Basel.

Innate signaling by mycobacterial cell wall components and relevance for development of adjuvants for subunit vaccines.

PubMed

Tima, Hermann Giresse; Huygen, Kris; Romano, Marta

2016-11-01

Pathogen recognition receptors (PRRs) recognize pathogen-associated molecular patterns, triggering the induction of inflammatory innate responses and contributing to the development of specific adaptive immune responses. Novel adjuvants have been developed based on agonists of PRRs. Areas covered: Lipid pathogen-associated molecular patterns (PAMPs) present in the cell wall of mycobacteria are revised, with emphasis on agonists of C-type lectin receptors, signaling pathways, and preclinical data supporting their use as novel adjuvants inducing cell-mediated immune responses. Their potential use as lipid antigens in novel tuberculosis subunit vaccines is also discussed. Expert commentary: Few adjuvants are licensed for human use and mainly favour antibody-mediated protective immunity. Use of lipid PAMPs that trigger cell-mediated immune responses could lead to the development of adjuvants for vaccines against intracellular pathogens and cancer.

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.

Whole CMV Proteome Pattern Recognition Analysis after HSCT Identifies Unique Epitope Targets Associated with the CMV Status

PubMed Central

Pérez-Bercoff, Lena; Valentini, Davide; Gaseitsiwe, Simani; Mahdavifar, Shahnaz; Schutkowski, Mike; Poiret, Thomas; Pérez-Bercoff, Åsa; Ljungman, Per; Maeurer, Markus J.

2014-01-01

Cytomegalovirus (CMV) infection represents a vital complication after Hematopoietic Stem Cell Transplantation (HSCT). We screened the entire CMV proteome to visualize the humoral target epitope-focus profile in serum after HSCT. IgG profiling from four patient groups (donor and/or recipient +/− for CMV) was performed at 6, 12 and 24 months after HSCT using microarray slides containing 17174 of 15mer-peptides overlapping by 4 aa covering 214 proteins from CMV. Data were analyzed using maSigPro, PAM and the ‘exclusive recognition analysis (ERA)’ to identify unique CMV epitope responses for each patient group. The ‘exclusive recognition analysis’ of serum epitope patterns segregated best 12 months after HSCT for the D+/R+ group (versus D−/R−). Epitopes were derived from UL123 (IE1), UL99 (pp28), UL32 (pp150), this changed at 24 months to 2 strongly recognized peptides provided from UL123 and UL100. Strongly (IgG) recognized CMV targets elicited also robust cytokine production in T-cells from patients after HSCT defined by intracellular cytokine staining (IL-2, TNF, IFN and IL-17). High-content peptide microarrays allow epitope profiling of entire viral proteomes; this approach can be useful to map relevant targets for diagnostics and therapy in patients with well defined clinical endpoints. Peptide microarray analysis visualizes the breadth of B-cell immune reconstitution after HSCT and provides a useful tool to gauge immune reconstitution. PMID:24740411

RNA Binding of T-cell Intracellular Antigen-1 (TIA-1) C-terminal RNA Recognition Motif Is Modified by pH Conditions*

PubMed Central

Cruz-Gallardo, Isabel; Aroca, Ángeles; Persson, Cecilia; Karlsson, B. Göran; Díaz-Moreno, Irene

2013-01-01

T-cell intracellular antigen-1 (TIA-1) is a DNA/RNA-binding protein that regulates critical events in cell physiology by the regulation of pre-mRNA splicing and mRNA translation. TIA-1 is composed of three RNA recognition motifs (RRMs) and a glutamine-rich domain and binds to uridine-rich RNA sequences through its C-terminal RRM2 and RRM3 domains. Here, we show that RNA binding mediated by either isolated RRM3 or the RRM23 construct is controlled by slight environmental pH changes due to the protonation/deprotonation of TIA-1 RRM3 histidine residues. The auxiliary role of the C-terminal RRM3 domain in TIA-1 RNA recognition is poorly understood, and this work provides insight into its binding mechanisms. PMID:23902765

Emerging Role and Characterization of Immunometabolism: Relevance to HIV Pathogenesis, Serious Non-AIDS Events, and a Cure.

PubMed

Palmer, Clovis S; Henstridge, Darren C; Yu, Di; Singh, Amit; Balderson, Brad; Duette, Gabriel; Cherry, Catherine L; Anzinger, Joshua J; Ostrowski, Matias; Crowe, Suzanne M

2016-06-01

Immune cells cycle between a resting and an activated state. Their metabolism is tightly linked to their activation status and, consequently, functions. Ag recognition induces T lymphocyte activation and proliferation and acquisition of effector functions that require and depend on cellular metabolic reprogramming. Likewise, recognition of pathogen-associated molecular patterns by monocytes and macrophages induces changes in cellular metabolism. As obligate intracellular parasites, viruses manipulate the metabolism of infected cells to meet their structural and functional requirements. For example, HIV-induced changes in immune cell metabolism and redox state are associated with CD4(+) T cell depletion, immune activation, and inflammation. In this review, we highlight how HIV modifies immunometabolism with potential implications for cure research and pathogenesis of comorbidities observed in HIV-infected patients, including those with virologic suppression. In addition, we highlight recently described key methods that can be applied to study the metabolic dysregulation of immune cells in disease states. Copyright © 2016 by The American Association of Immunologists, Inc.

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.

Self/nonself perception in plants in innate immunity and defense

PubMed Central

Sanabria, Natasha M; Huang, Ju-Chi

2010-01-01

The ability to distinguish ‘self’ from ‘nonself’ is the most fundamental aspect of any immune system. The evolutionary solution in plants to the problems of perceiving and responding to pathogens involves surveillance of nonself, damaged-self and altered-self as danger signals. This is reflected in basal resistance or non-host resistance, which is the innate immune response that protects plants against the majority of pathogens. In the case of surveillance of nonself, plants utilize receptor-like proteins or -kinases (RLP/Ks) as pattern recognition receptors (PRRs), which can detect conserved pathogen/microbe-associated molecular pattern (P/MAMP) molecules. P/MAMP detection serves as an early warning system for the presence of a wide range of potential pathogens and the timely activation of plant defense mechanisms. However, adapted microbes express a suite of effector proteins that often interfere or act as suppressors of these defenses. In response, plants have evolved a second line of defense that includes intracellular nucleotide binding leucine-rich repeat (NB-LRR)-containing resistance proteins, which recognize isolate-specific pathogen effectors once the cell wall has been compromised. This host-immunity acts within the species level and is controlled by polymorphic host genes, where resistance protein-mediated activation of defense is based on an ‘altered-self’ recognition mechanism. PMID:21559176

Single cell analysis of innate cytokine responses to pattern recognition receptor stimulation in children across four continents

PubMed Central

Smolen, Kinga K; Cai, Bing; Fortuno, Edgardo S; Gelinas, Laura; Larsen, Martin; Speert, David P; Chamekh, Mustapha; Kollmann, Tobias R

2014-01-01

Innate immunity instructs adaptive immunity, and suppression of innate immunity is associated with increased risk for infection. We had previously shown that whole blood cellular components from a cohort of South African children secreted significantly lower levels of most cytokines following stimulation of pattern recognition receptors (PRR) as compared to whole blood from cohorts of Ecuadorian, Belgian, or Canadian children. To begin dissecting the responsible molecular mechanisms, we now set out to identify the relevant cellular source of these differences. Across the four cohorts represented in our study, we identified significant variation in the cellular composition of whole blood; however, significant reduction of the intracellular cytokine production on the single cell level was only detected in South African childrens’ monocytes, cDC, and pDC. We also uncovered a marked reduction in polyfunctionality for each of these cellular compartments in South African children as compared to children from other continents. Together our data identify differences in cell composition as well as profoundly lower functional responses of innate cells in our cohort of South African children. A possible link between altered innate immunity and increased risk for infection or lower response to vaccines in South African infants needs to be explored. PMID:25135829

LIPS database with LIPService: a microscopic image database of intracellular structures in Arabidopsis guard cells.

PubMed

Higaki, Takumi; Kutsuna, Natsumaro; Hasezawa, Seiichiro

2013-05-16

Intracellular configuration is an important feature of cell status. Recent advances in microscopic imaging techniques allow us to easily obtain a large number of microscopic images of intracellular structures. In this circumstance, automated microscopic image recognition techniques are of extreme importance to future phenomics/visible screening approaches. However, there was no benchmark microscopic image dataset for intracellular organelles in a specified plant cell type. We previously established the Live Images of Plant Stomata (LIPS) database, a publicly available collection of optical-section images of various intracellular structures of plant guard cells, as a model system of environmental signal perception and transduction. Here we report recent updates to the LIPS database and the establishment of a database table, LIPService. We updated the LIPS dataset and established a new interface named LIPService to promote efficient inspection of intracellular structure configurations. Cell nuclei, microtubules, actin microfilaments, mitochondria, chloroplasts, endoplasmic reticulum, peroxisomes, endosomes, Golgi bodies, and vacuoles can be filtered using probe names or morphometric parameters such as stomatal aperture. In addition to the serial optical sectional images of the original LIPS database, new volume-rendering data for easy web browsing of three-dimensional intracellular structures have been released to allow easy inspection of their configurations or relationships with cell status/morphology. We also demonstrated the utility of the new LIPS image database for automated organelle recognition of images from another plant cell image database with image clustering analyses. The updated LIPS database provides a benchmark image dataset for representative intracellular structures in Arabidopsis guard cells. The newly released LIPService allows users to inspect the relationship between organellar three-dimensional configurations and morphometrical parameters.

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.

What pharmacological interventions indicate concerning the role of the perirhinal cortex in recognition memory

PubMed Central

Brown, M.W.; Barker, G.R.I.; Aggleton, J.P.; Warburton, E.C.

2012-01-01

Findings of pharmacological studies that have investigated the involvement of specific regions of the brain in recognition memory are reviewed. The particular emphasis of the review concerns what such studies indicate concerning the role of the perirhinal cortex in recognition memory. Most of the studies involve rats and most have investigated recognition memory for objects. Pharmacological studies provide a large body of evidence supporting the essential role of the perirhinal cortex in the acquisition, consolidation and retrieval of object recognition memory. Such studies provide increasingly detailed evidence concerning both the neurotransmitter systems and the underlying intracellular mechanisms involved in recognition memory processes. They have provided evidence in support of synaptic weakening as a major synaptic plastic process within perirhinal cortex underlying object recognition memory. They have also supplied confirmatory evidence that that there is more than one synaptic plastic process involved. The demonstrated necessity to long-term recognition memory of intracellular signalling mechanisms related to synaptic modification within perirhinal cortex establishes a central role for the region in the information storage underlying such memory. Perirhinal cortex is thereby established as an information storage site rather than solely a processing station. Pharmacological studies have also supplied new evidence concerning the detailed roles of other regions, including the hippocampus and the medial prefrontal cortex in different types of recognition memory tasks that include a spatial or temporal component. In so doing, they have also further defined the contribution of perirhinal cortex to such tasks. To date it appears that the contribution of perirhinal cortex to associative and temporal order memory reflects that in simple object recognition memory, namely that perirhinal cortex provides information concerning objects and their prior occurrence (novelty/familiarity). PMID:22841990

DNA Dendrimer: An Efficient Nanocarrier of Functional Nucleic Acids for Intracellular Molecular Sensing

PubMed Central

2015-01-01

Functional nucleic acid (FNA)-based sensing systems have been developed for efficient detection of a wide range of biorelated analytes by employing DNAzymes or aptamers as recognition units. However, their intracellular delivery has always been a concern, mainly in delivery efficiency, kinetics, and the amount of delivered FNAs. Here we report a DNA dendrimer scaffold as an efficient nanocarrier to deliver FNAs and to conduct in situ monitoring of biological molecules in living cells. A histidine-dependent DNAzyme and an anti-ATP aptamer were chosen separately as the model FNAs to make the FNA dendrimer. The FNA-embedded DNA dendrimers maintained the catalytic activity of the DNAzyme or the aptamer recognition function toward ATP in the cellular environment, with no change in sensitivity or specificity. Moreover, these DNA dendrimeric nanocarriers show excellent biocompatibility, high intracellular delivery efficiency, and sufficient stability in a cellular environment. This FNA dendrimeric nanocarrier may find a broad spectrum of applications in biomedical diagnosis and therapy. PMID:24806614

Ubiquitination in the antiviral immune response.

PubMed

Davis, Meredith E; Gack, Michaela U

2015-05-01

Ubiquitination has long been known to regulate fundamental cellular processes through the induction of proteasomal degradation of target proteins. More recently, 'atypical' non-degradative types of polyubiquitin chains have been appreciated as important regulatory moieties by modulating the activity or subcellular localization of key signaling proteins. Intriguingly, many of these non-degradative types of ubiquitination regulate the innate sensing pathways initiated by pattern recognition receptors (PRRs), ultimately coordinating an effective antiviral immune response. Here we discuss recent advances in understanding the functional roles of degradative and atypical types of ubiquitination in innate immunity to viral infections, with a specific focus on the signaling pathways triggered by RIG-I-like receptors, Toll-like receptors, and the intracellular viral DNA sensor cGAS. Copyright © 2015 Elsevier Inc. All rights reserved.

Effector-triggered defence against apoplastic fungal pathogens

PubMed Central

Stotz, Henrik U.; Mitrousia, Georgia K.; de Wit, Pierre J.G.M.; Fitt, Bruce D.L.

2014-01-01

R gene-mediated host resistance against apoplastic fungal pathogens is not adequately explained by the terms pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) or effector-triggered immunity (ETI). Therefore, it is proposed that this type of resistance is termed ‘effector-triggered defence’ (ETD). Unlike PTI and ETI, ETD is mediated by R genes encoding cell surface-localised receptor-like proteins (RLPs) that engage the receptor-like kinase SOBIR1. In contrast to this extracellular recognition, ETI is initiated by intracellular detection of pathogen effectors. ETI is usually associated with fast, hypersensitive host cell death, whereas ETD often triggers host cell death only after an elapsed period of endophytic pathogen growth. In this opinion, we focus on ETD responses against foliar fungal pathogens of crops. PMID:24856287

Role of TRP ion channels in cancer and tumorigenesis.

PubMed

Shapovalov, George; Ritaine, Abigael; Skryma, Roman; Prevarskaya, Natalia

2016-05-01

Transient receptor potential (TRP) channels are recently identified proteins that form a versatile family of ion channels, the majority of which are calcium permeable and exhibit complex regulatory patterns with sensitivity to multiple environmental factors. While this sensitivity has captured early attention, leading to recognition of TRP channels as environmental and chemical sensors, many later studies concentrated on the regulation of intracellular calcium by TRP channels. Due to mutations, dysregulation of ion channel gating or expression levels, normal spatiotemporal patterns of local Ca(2+) distribution become distorted. This causes deregulation of downstream effectors sensitive to changes in Ca(2+) homeostasis that, in turn, promotes pathophysiological cancer hallmarks, such as enhanced survival, proliferation and invasion. These observations give rise to the appreciation of the important contributions that TRP channels make to many cellular processes controlling cell fate and positioning these channels as important players in cancer regulation. This review discusses the accumulated scientific knowledge focused on TRP channel involvement in regulation of cell fate in various transformed tissues.

Long-term modifications of synaptic efficacy in the human inferior and middle temporal cortex

NASA Technical Reports Server (NTRS)

Chen, W. R.; Lee, S.; Kato, K.; Spencer, D. D.; Shepherd, G. M.; Williamson, A.

1996-01-01

The primate temporal cortex has been demonstrated to play an important role in visual memory and pattern recognition. It is of particular interest to investigate whether activity-dependent modification of synaptic efficacy, a presumptive mechanism for learning and memory, is present in this cortical region. Here we address this issue by examining the induction of synaptic plasticity in surgically resected human inferior and middle temporal cortex. The results show that synaptic strength in the human temporal cortex could undergo bidirectional modifications, depending on the pattern of conditioning stimulation. High frequency stimulation (100 or 40 Hz) in layer IV induced long-term potentiation (LTP) of both intracellular excitatory postsynaptic potentials and evoked field potentials in layers II/III. The LTP induced by 100 Hz tetanus was blocked by 50-100 microM DL-2-amino-5-phosphonovaleric acid, suggesting that N-methyl-D-aspartate receptors were responsible for its induction. Long-term depression (LTD) was elicited by prolonged low frequency stimulation (1 Hz, 15 min). It was reduced, but not completely blocked, by DL-2-amino-5-phosphonovaleric acid, implying that some other mechanisms in addition to N-methyl-DL-aspartate receptors were involved in LTD induction. LTD was input-specific, i.e., low frequency stimulation of one pathway produced LTD of synaptic transmission in that pathway only. Finally, the LTP and LTD could reverse each other, suggesting that they can act cooperatively to modify the functional state of cortical network. These results suggest that LTP and LTD are possible mechanisms for the visual memory and pattern recognition functions performed in the human temporal cortex.

Innate immunity against HIV-1 infection.

PubMed

Altfeld, Marcus; Gale, Michael

2015-06-01

During acute HIV-1 infection, viral pathogen-associated molecular patterns are recognized by pathogen-recognition receptors (PRRs) of infected cells, which triggers a signaling cascade that initiates innate intracellular antiviral defenses aimed at restricting the replication and spread of the virus. This cell-intrinsic response propagates outward via the action of secreted factors such as cytokines and chemokines that activate innate immune cells and attract them to the site of infection and to local lymphatic tissue. Antiviral innate effector cells can subsequently contribute to the control of viremia and modulate the quality of the adaptive immune response to HIV-1. The concerted actions of PRR signaling, specific viral-restriction factors, innate immune cells, innate-adaptive immune crosstalk and viral evasion strategies determine the outcome of HIV-1 infection and immune responses.

Imaging and quantification of amyloid fibrillation in the cell nucleus.

PubMed

Arnhold, Florian; Scharf, Andrea; von Mikecz, Anna

2015-01-01

Xenobiotics, as well as intrinsic processes such as cellular aging, contribute to an environment that constantly challenges nuclear organization and function. While it becomes increasingly clear that proteasome-dependent proteolysis is a major player, the topology and molecular mechanisms of nuclear protein homeostasis remain largely unknown. We have shown previously that (1) proteasome-dependent protein degradation is organized in focal microenvironments throughout the nucleoplasm and (2) heavy metals as well as nanoparticles induce nuclear protein fibrillation with amyloid characteristics. Here, we describe methods to characterize the landscape of intranuclear amyloid on the global and local level in different systems such as cultures of mammalian cells and the soil nematode Caenorhabditis elegans. Application of discrete mathematics to imaging data is introduced as a tool to develop pattern recognition of intracellular protein fibrillation. Since stepwise fibrillation of otherwise soluble proteins to insoluble amyloid-like protein aggregates is a hallmark of neurodegenerative protein-misfolding disorders including Alzheimer's disease, CAG repeat diseases, and the prion encephalopathies, investigation of intracellular amyloid may likewise aid to a better understanding of the pathomechanisms involved. We consider aggregate profiling as an important experimental approach to determine if nuclear amyloid has toxic or protective roles in various disease processes.

β-N-Methylamino-L-alanine (BMAA) perturbs alanine, aspartate and glutamate metabolism pathways in human neuroblastoma cells as determined by metabolic profiling.

PubMed

Engskog, Mikael K R; Ersson, Lisa; Haglöf, Jakob; Arvidsson, Torbjörn; Pettersson, Curt; Brittebo, Eva

2017-05-01

β-Methylamino-L-alanine (BMAA) is a non-proteinogenic amino acid that induces long-term cognitive deficits, as well as an increased neurodegeneration and intracellular fibril formation in the hippocampus of adult rodents following short-time neonatal exposure and in vervet monkey brain following long-term exposure. It has also been proposed to be involved in the etiology of neurodegenerative disease in humans. The aim of this study was to identify metabolic effects not related to excitotoxicity or oxidative stress in human neuroblastoma SH-SY5Y cells. The effects of BMAA (50, 250, 1000 µM) for 24 h on cells differentiated with retinoic acid were studied. Samples were analyzed using LC-MS and NMR spectroscopy to detect altered intracellular polar metabolites. The analysis performed, followed by multivariate pattern recognition techniques, revealed significant perturbations in protein biosynthesis, amino acid metabolism pathways and citrate cycle. Of specific interest were the BMAA-induced alterations in alanine, aspartate and glutamate metabolism and as well as alterations in various neurotransmitters/neuromodulators such as GABA and taurine. The results indicate that BMAA can interfere with metabolic pathways involved in neurotransmission in human neuroblastoma cells.

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.

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.

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.

Defects in intracellular trafficking of fungal cell wall synthases lead to aberrant host immune recognition.

PubMed

Esher, Shannon K; Ost, Kyla S; Kohlbrenner, Maria A; Pianalto, Kaila M; Telzrow, Calla L; Campuzano, Althea; Nichols, Connie B; Munro, Carol; Wormley, Floyd L; Alspaugh, J Andrew

2018-06-01

The human fungal pathogen, Cryptococcus neoformans, dramatically alters its cell wall, both in size and composition, upon entering the host. This cell wall remodeling is essential for host immune avoidance by this pathogen. In a genetic screen for mutants with changes in their cell wall, we identified a novel protein, Mar1, that controls cell wall organization and immune evasion. Through phenotypic studies of a loss-of-function strain, we have demonstrated that the mar1Δ mutant has an aberrant cell surface and a defect in polysaccharide capsule attachment, resulting in attenuated virulence. Furthermore, the mar1Δ mutant displays increased staining for exposed cell wall chitin and chitosan when the cells are grown in host-like tissue culture conditions. However, HPLC analysis of whole cell walls and RT-PCR analysis of cell wall synthase genes demonstrated that this increased chitin exposure is likely due to decreased levels of glucans and mannans in the outer cell wall layers. We observed that the Mar1 protein differentially localizes to cellular membranes in a condition dependent manner, and we have further shown that the mar1Δ mutant displays defects in intracellular trafficking, resulting in a mislocalization of the β-glucan synthase catalytic subunit, Fks1. These cell surface changes influence the host-pathogen interaction, resulting in increased macrophage activation to microbial challenge in vitro. We established that several host innate immune signaling proteins are required for the observed macrophage activation, including the Card9 and MyD88 adaptor proteins, as well as the Dectin-1 and TLR2 pattern recognition receptors. These studies explore novel mechanisms by which a microbial pathogen regulates its cell surface in response to the host, as well as how dysregulation of this adaptive response leads to defective immune avoidance.

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.

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

PubMed

Pareja, Maria Eugenia Mansilla; Colombo, Maria I

2013-01-01

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

Transgenic expression of the dicotyledonous pattern recognition receptor EFR in rice leads to ligand-dependent activation of defense responses.

PubMed

Schwessinger, Benjamin; Bahar, Ofir; Thomas, Nicholas; Thomas, Nicolas; Holton, Nicolas; Nekrasov, Vladimir; Ruan, Deling; Canlas, Patrick E; Daudi, Arsalan; Petzold, Christopher J; Singan, Vasanth R; Kuo, Rita; Chovatia, Mansi; Daum, Christopher; Heazlewood, Joshua L; Zipfel, Cyril; Ronald, Pamela C

2015-03-01

Plant plasma membrane localized pattern recognition receptors (PRRs) detect extracellular pathogen-associated molecules. PRRs such as Arabidopsis EFR and rice XA21 are taxonomically restricted and are absent from most plant genomes. Here we show that rice plants expressing EFR or the chimeric receptor EFR::XA21, containing the EFR ectodomain and the XA21 intracellular domain, sense both Escherichia coli- and Xanthomonas oryzae pv. oryzae (Xoo)-derived elf18 peptides at sub-nanomolar concentrations. Treatment of EFR and EFR::XA21 rice leaf tissue with elf18 leads to MAP kinase activation, reactive oxygen production and defense gene expression. Although expression of EFR does not lead to robust enhanced resistance to fully virulent Xoo isolates, it does lead to quantitatively enhanced resistance to weakly virulent Xoo isolates. EFR interacts with OsSERK2 and the XA21 binding protein 24 (XB24), two key components of the rice XA21-mediated immune response. Rice-EFR plants silenced for OsSERK2, or overexpressing rice XB24 are compromised in elf18-induced reactive oxygen production and defense gene expression indicating that these proteins are also important for EFR-mediated signaling in transgenic rice. Taken together, our results demonstrate the potential feasibility of enhancing disease resistance in rice and possibly other monocotyledonous crop species by expression of dicotyledonous PRRs. Our results also suggest that Arabidopsis EFR utilizes at least a subset of the known endogenous rice XA21 signaling components.

Transgenic Expression of the Dicotyledonous Pattern Recognition Receptor EFR in Rice Leads to Ligand-Dependent Activation of Defense Responses

PubMed Central

Thomas, Nicolas; Holton, Nicolas; Nekrasov, Vladimir; Ruan, Deling; Canlas, Patrick E.; Daudi, Arsalan; Petzold, Christopher J.; Singan, Vasanth R.; Kuo, Rita; Chovatia, Mansi; Daum, Christopher; Heazlewood, Joshua L.; Zipfel, Cyril; Ronald, Pamela C.

2015-01-01

Plant plasma membrane localized pattern recognition receptors (PRRs) detect extracellular pathogen-associated molecules. PRRs such as Arabidopsis EFR and rice XA21 are taxonomically restricted and are absent from most plant genomes. Here we show that rice plants expressing EFR or the chimeric receptor EFR::XA21, containing the EFR ectodomain and the XA21 intracellular domain, sense both Escherichia coli- and Xanthomonas oryzae pv. oryzae (Xoo)-derived elf18 peptides at sub-nanomolar concentrations. Treatment of EFR and EFR::XA21 rice leaf tissue with elf18 leads to MAP kinase activation, reactive oxygen production and defense gene expression. Although expression of EFR does not lead to robust enhanced resistance to fully virulent Xoo isolates, it does lead to quantitatively enhanced resistance to weakly virulent Xoo isolates. EFR interacts with OsSERK2 and the XA21 binding protein 24 (XB24), two key components of the rice XA21-mediated immune response. Rice-EFR plants silenced for OsSERK2, or overexpressing rice XB24 are compromised in elf18-induced reactive oxygen production and defense gene expression indicating that these proteins are also important for EFR-mediated signaling in transgenic rice. Taken together, our results demonstrate the potential feasibility of enhancing disease resistance in rice and possibly other monocotyledonous crop species by expression of dicotyledonous PRRs. Our results also suggest that Arabidopsis EFR utilizes at least a subset of the known endogenous rice XA21 signaling components. PMID:25821973

Phagocytosis and phagosome acidification are required for pathogen processing and MyD88-dependent responses to Staphylococcus aureus

PubMed Central

Ip, WK Eddie; Sokolovska, Anna; Charriere, Guillaume M; Boyer, Laurent; Dejardin, Stephanie; Cappillino, Michael P; Yantosca, L Michael; Takahashi, Kazue; Moore, Kathryn J; Lacy-Hulbert, Adam; Stuart, Lynda M

2010-01-01

Innate immunity is vital for protection from microbes and is mediated by both humoral effectors, such as cytokines, and cellular immune defenses, including phagocytic cells such as macrophages. After internalization by phagocytes, microbes are delivered into a phagosome, a complex intracellular organelle with a well-established and important role in microbial killing. However, the role of this organelle in cytokine responses and microbial sensing is less well defined. Here we assess the role of the phagosome in innate immune sensing and demonstrate the critical interdependence of phagocytosis and pattern recognition receptor signaling during response to the Gram-positive bacteria Staphylococcus aureus. We show that phagocytosis is essential to initiate optimal MyD88-dependent response to Staphylococcus aureus. Prior to TLR-dependent cytokine production bacteria must not only be engulfed but also delivered into acidic phagosomes. Here acid-activated host enzymes digest the internalized bacteria to liberate otherwise cryptic bacterial-derived ligands that initiate responses from the vacuole. Importantly, in macrophages in which phagosome acidification is perturbed, the impaired response to Staphylococcus aureus can be rescued by addition of lysostaphin, a bacterial endopeptidase active at neutral pH that can substitute for the acid-activated host enzymes. Together these observations delineate the inter-dependence of phagocytosis with pattern recognition receptor signaling and suggest that therapeutics to augment functions and signaling from the vacuole may be useful strategies to increase host responses to Staphylococcus aureus. PMID:20483752

The molecular chaperone HSP70 binds to and stabilizes NOD2, an important protein involved in Crohn disease.

PubMed

Mohanan, Vishnu; Grimes, Catherine Leimkuhler

2014-07-04

Microbes are detected by the pathogen-associated molecular patterns through specific host pattern recognition receptors. Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) is an intracellular pattern recognition receptor that recognizes fragments of the bacterial cell wall. NOD2 is important to human biology; when it is mutated it loses the ability to respond properly to bacterial cell wall fragments. To determine the mechanisms of misactivation in the NOD2 Crohn mutants, we developed a cell-based system to screen for protein-protein interactors of NOD2. We identified heat shock protein 70 (HSP70) as a protein interactor of both wild type and Crohn mutant NOD2. HSP70 has previously been linked to inflammation, especially in the regulation of anti-inflammatory molecules. Induced HSP70 expression in cells increased the response of NOD2 to bacterial cell wall fragments. In addition, an HSP70 inhibitor, KNK437, was capable of decreasing NOD2-mediated NF-κB activation in response to bacterial cell wall stimulation. We found HSP70 to regulate the half-life of NOD2, as increasing the HSP70 level in cells increased the half-life of NOD2, and down-regulating HSP70 decreased the half-life of NOD2. The expression levels of the Crohn-associated NOD2 variants were less compared with wild type. The overexpression of HSP70 significantly increased NOD2 levels as well as the signaling capacity of the mutants. Thus, our study shows that restoring the stability of the NOD2 Crohn mutants is sufficient for rescuing the ability of these mutations to signal the presence of a bacterial cell wall ligand. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

The Molecular Chaperone HSP70 Binds to and Stabilizes NOD2, an Important Protein Involved in Crohn Disease*

PubMed Central

Mohanan, Vishnu; Grimes, Catherine Leimkuhler

2014-01-01

Microbes are detected by the pathogen-associated molecular patterns through specific host pattern recognition receptors. Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) is an intracellular pattern recognition receptor that recognizes fragments of the bacterial cell wall. NOD2 is important to human biology; when it is mutated it loses the ability to respond properly to bacterial cell wall fragments. To determine the mechanisms of misactivation in the NOD2 Crohn mutants, we developed a cell-based system to screen for protein-protein interactors of NOD2. We identified heat shock protein 70 (HSP70) as a protein interactor of both wild type and Crohn mutant NOD2. HSP70 has previously been linked to inflammation, especially in the regulation of anti-inflammatory molecules. Induced HSP70 expression in cells increased the response of NOD2 to bacterial cell wall fragments. In addition, an HSP70 inhibitor, KNK437, was capable of decreasing NOD2-mediated NF-κB activation in response to bacterial cell wall stimulation. We found HSP70 to regulate the half-life of NOD2, as increasing the HSP70 level in cells increased the half-life of NOD2, and down-regulating HSP70 decreased the half-life of NOD2. The expression levels of the Crohn-associated NOD2 variants were less compared with wild type. The overexpression of HSP70 significantly increased NOD2 levels as well as the signaling capacity of the mutants. Thus, our study shows that restoring the stability of the NOD2 Crohn mutants is sufficient for rescuing the ability of these mutations to signal the presence of a bacterial cell wall ligand. PMID:24790089

Oxidation-Specific Epitopes are Danger Associated Molecular Patterns Recognized by Pattern Recognition Receptors of Innate Immunity

PubMed Central

Miller, Yury I.; Choi, Soo-Ho; Wiesner, Philipp; Fang, Longhou; Harkewicz, Richard; Hartvigsen, Karsten; Boullier, Agnès; Gonen, Ayelet; Diehl, Cody J.; Que, Xuchu; Montano, Erica; Shaw, Peter X.; Tsimikas, Sotirios; Binder, Christoph J.; Witztum, Joseph L.

2010-01-01

Oxidation reactions are vital parts of metabolism and signal transduction. However, they also produce reactive oxygen species, which damage lipids, proteins and DNA, generating “oxidation-specific” epitopes. In this review, we will discuss the hypothesis that such common oxidation-specific epitopes are a major target of innate immunity, recognized by a variety of “pattern recognition receptors” (PRRs). By analogy with microbial “pathogen associated molecular patterns” (PAMPs), we postulate that host-derived, oxidation-specific epitopes can be considered to represent “danger (or damage) associated molecular patterns” (DAMPs). We also argue that oxidation-specific epitopes present on apoptotic cells and their cellular debris provided the primary evolutionary pressure for the selection of such PRRs. Further, because many PAMPs on microbes share molecular identity and/or mimicry with oxidation-specific epitopes, such PAMPs provided a strong secondary selecting pressure for the same set of oxidation-specific PRRs as well. Because lipid peroxidation is ubiquitous and a major component of the inflammatory state associated with atherosclerosis, the understanding that oxidation-specific epitopes are DAMPs, and thus the target of multiple arcs of innate immunity, provides novel insights into the pathogenesis of atherosclerosis. As examples, we show that both cellular and soluble PRRs, such as CD36, toll-like receptor-4, natural antibodies, and CRP recognize common oxidation-specific DAMPs, such as oxidized phospholipids and oxidized cholesteryl esters, and mediate a variety of immune responses, from expression of proinflammatory genes to excessive intracellular lipoprotein accumulation to atheroprotective humoral immunity. These insights may lead to improved understanding of inflammation and atherogenesis and suggest new approaches to diagnosis and therapy. PMID:21252151

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.

Spatial distribution and expression of intracellular and extracellular acid phosphatases of cluster roots at different developmental stages in white lupin.

PubMed

Tang, Hongliang; Li, Xiaoqing; Zu, Chao; Zhang, Fusuo; Shen, Jianbo

2013-09-15

Acid phosphatases (APases) play a key role in phosphorus (P) acquisition and recycling in plants. White lupin (Lupinus albus L.) forms cluster roots (CRs) and produces large amounts of APases under P deficiency. However, the relationships between the activity of intracellular and extracellular APases (EC 3.1.3.2) and CR development are not fully understood. Here, comparative studies were conducted to examine the spatial variation pattern of APase activity during CR development using the enzyme-labelled fluorescence-97 (ELF-97) and the p-nitrophenyl phosphate methods. The activity of intracellular and extracellular APases was significantly enhanced under P deficiency in the non-CRs and CRs at different developmental stages. These two APases exhibited different spatial distribution patterns during CR development, and these distribution patterns were highly modified by P deficiency. The activity of extracellular APase increased steadily with CR development from meristematic, juvenile, mature to senescent stages under P deficiency. In comparison, P deficiency-induced increase in the activity of intracellular APase remained relatively constant during CR development. Increased activity of intracellular and extracellular APases was associated with enhanced expression of LaSAP1 encoding intracellular APase and LaSAP2 encoding extracellular APase. The expression levels of these two genes were significantly higher at transcriptional level in both mature and senescent CRs. Taken together, these findings demonstrate that both activity and gene expression of intracellular or extracellular APases exhibit a differential response pattern during CR development, depending on root types, CR developmental stages and P supply. Simultaneous in situ determination of intracellular and extracellular APase activity has proved to be an effective approach for studying spatial variation of APases during CR development. Copyright © 2013 Elsevier GmbH. All rights reserved.

Emerging Role of Ubiquitination in Antiviral RIG-I Signaling

PubMed Central

Maelfait, Jonathan

2012-01-01

Summary: Detection of viruses by the innate immune system involves the action of specialized pattern recognition receptors. Intracellular RIG-I receptors sense the presence of viral nucleic acids in infected cells and trigger signaling pathways that lead to the production of proinflammatory and antiviral proteins. Over the past few years, posttranslational modification of RIG-I and downstream signaling proteins by different types of ubiquitination has been found to be a key event in the regulation of RIG-I-induced NF-κB and interferon regulatory factor 3 (IRF3) activation. Multiple ubiquitin ligases, deubiquitinases, and ubiquitin binding scaffold proteins contribute to both positive and negative regulation of the RIG-I-induced antiviral immune response. A better understanding of the function and activity of these proteins might eventually lead to the development of novel therapeutic approaches for management of viral diseases. PMID:22390971

NOD-like receptor cooperativity in effector-triggered immunity.

PubMed

Griebel, Thomas; Maekawa, Takaki; Parker, Jane E

2014-11-01

Intracellular nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) are basic elements of innate immunity in plants and animals. Whereas animal NLRs react to conserved microbe- or damage-associated molecular patterns, plant NLRs intercept the actions of diverse pathogen virulence factors (effectors). In this review, we discuss recent genetic and molecular evidence for functional NLR pairs, and discuss the significance of NLR self-association and heteromeric NLR assemblies in the triggering of downstream signaling pathways. We highlight the versatility and impact of cooperating NLR pairs that combine pathogen sensing with the initiation of defense signaling in both plant and animal immunity. We propose that different NLR receptor molecular configurations provide opportunities for fine-tuning resistance pathways and enhancing the host's pathogen recognition spectrum to keep pace with rapidly evolving microbial populations. Copyright © 2014. Published by Elsevier Ltd.

Viral Inhibition of PRR-Mediated Innate Immune Response: Learning from KSHV Evasion Strategies.

PubMed

Lee, Hye-Ra; Choi, Un Yung; Hwang, Sung-Woo; Kim, Stephanie; Jung, Jae U

2016-11-30

The innate immune system has evolved to detect and destroy invading pathogens before they can establish systemic infection. To successfully eradicate pathogens, including viruses, host innate immunity is activated through diverse pattern recognition receptors (PRRs) which detect conserved viral signatures and trigger the production of type I interferon (IFN) and pro-inflammatory cytokines to mediate viral clearance. Viral persistence requires that viruses co-opt cellular pathways and activities for their benefit. In particular, due to the potent antiviral activities of IFN and cytokines, viruses have developed various strategies to meticulously modulate intracellular innate immune sensing mechanisms to facilitate efficient viral replication and persistence. In this review, we highlight recent advances in the study of viral immune evasion strategies with a specific focus on how Kaposi's sarcoma-associated herpesvirus (KSHV) effectively targets host PRR signaling pathways.

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.

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

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.

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.

The bacterial pigment pyocyanin inhibits the NLRP3 inflammasome through intracellular reactive oxygen and nitrogen species

PubMed Central

Virreira Winter, Sebastian; Zychlinsky, Arturo

2018-01-01

Inflammasomes are cytosolic complexes that mature and secrete the inflammatory cytokines interleukin 1β (IL-1β) and IL-18 and induce pyroptosis. The NLRP3 (NACHT, LRR, and PYD domains–containing protein 3) inflammasome detects many pathogen- and danger-associated molecular patterns, and reactive oxygen species (ROS)/reactive nitrogen species (RNS) have been implicated in its activation. The phenazine pyocyanin (PCN) is a virulence factor of Pseudomonas aeruginosa and generates superoxide in cells. Here we report that PCN inhibits IL-1β and IL-18 release and pyroptosis upon NLRP3 inflammasome activation in macrophages by preventing speck formation and Caspase-1 maturation. Of note, PCN did not regulate the AIM2 (absent in melanoma 2) or NLRC4 inflammasomes or tumor necrosis factor (TNF) secretion. Imaging of the fluorescent glutathione redox potential sensor Grx1-roGFP2 indicated that PCN provokes cytosolic and nuclear but not mitochondrial redox changes. PCN-induced intracellular ROS/RNS inhibited the NLRP3 inflammasome posttranslationally, and hydrogen peroxide or peroxynitrite alone were sufficient to block its activation. We propose that cytosolic ROS/RNS inhibit the NLRP3 inflammasome and that PCN's anti-inflammatory activity may help P. aeruginosa evade immune recognition. PMID:29414783

Recognition of chromatin by the plant alkaloid, ellipticine as a dual binder

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

Banerjee, Amrita; Sanyal, Sulagna; Majumder, Parijat

Recognition of core histone components of chromatin along with chromosomal DNA by a class of small molecule modulators is worth examining to evaluate their intracellular mode of action. A plant alkaloid ellipticine (ELP) which is a putative anticancer agent has so far been reported to function via DNA intercalation, association with topoisomerase II and binding to telomere region. However, its effect upon the potential intracellular target, chromatin is hitherto unreported. Here we have characterized the biomolecular recognition between ELP and different hierarchical levels of chromatin. The significant result is that in addition to DNA, it binds to core histone(s) andmore » can be categorized as a ‘dual binder’. As a sequel to binding with histone(s) and core octamer, it alters post-translational histone acetylation marks. We have further demonstrated that it has the potential to modulate gene expression thereby regulating several key biological processes such as nuclear organization, transcription, translation and histone modifications. - Highlights: • Ellipticine acts a dual binder binding to both DNA and core histone(s). • It induces structural perturbations in chromatin, chromatosome and histone octamer. • It alters histones acetylation and affects global gene expression.« less

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.

Transient increase in Zn2+ in hippocampal CA1 pyramidal neurons causes reversible memory deficit.

PubMed

Takeda, Atsushi; Takada, Shunsuke; Nakamura, Masatoshi; Suzuki, Miki; Tamano, Haruna; Ando, Masaki; Oku, Naoto

2011-01-01

The translocation of synaptic Zn(2+) to the cytosolic compartment has been studied to understand Zn(2+) neurotoxicity in neurological diseases. However, it is unknown whether the moderate increase in Zn(2+) in the cytosolic compartment affects memory processing in the hippocampus. In the present study, the moderate increase in cytosolic Zn(2+) in the hippocampus was induced with clioquinol (CQ), a zinc ionophore. Zn(2+) delivery by Zn-CQ transiently attenuated CA1 long-term potentiation (LTP) in hippocampal slices prepared 2 h after i.p. injection of Zn-CQ into rats, when intracellular Zn(2+) levels was transiently increased in the CA1 pyramidal cell layer, followed by object recognition memory deficit. Object recognition memory was transiently impaired 30 min after injection of ZnCl(2) into the CA1, but not after injection into the dentate gyrus that did not significantly increase intracellular Zn(2+) in the granule cell layer of the dentate gyrus. Object recognition memory deficit may be linked to the preferential increase in Zn(2+) and/or the preferential vulnerability to Zn(2+) in CA1 pyramidal neurons. In the case of the cytosolic increase in endogenous Zn(2+) in the CA1 induced by 100 mM KCl, furthermore, object recognition memory was also transiently impaired, while ameliorated by co-injection of CaEDTA to block the increase in cytosolic Zn(2+). The present study indicates that the transient increase in cytosolic Zn(2+) in CA1 pyramidal neurons reversibly impairs object recognition memory.

Transient Increase in Zn2+ in Hippocampal CA1 Pyramidal Neurons Causes Reversible Memory Deficit

PubMed Central

Takeda, Atsushi; Takada, Shunsuke; Nakamura, Masatoshi; Suzuki, Miki; Tamano, Haruna; Ando, Masaki; Oku, Naoto

2011-01-01

The translocation of synaptic Zn2+ to the cytosolic compartment has been studied to understand Zn2+ neurotoxicity in neurological diseases. However, it is unknown whether the moderate increase in Zn2+ in the cytosolic compartment affects memory processing in the hippocampus. In the present study, the moderate increase in cytosolic Zn2+ in the hippocampus was induced with clioquinol (CQ), a zinc ionophore. Zn2+ delivery by Zn-CQ transiently attenuated CA1 long-term potentiation (LTP) in hippocampal slices prepared 2 h after i.p. injection of Zn-CQ into rats, when intracellular Zn2+ levels was transiently increased in the CA1 pyramidal cell layer, followed by object recognition memory deficit. Object recognition memory was transiently impaired 30 min after injection of ZnCl2 into the CA1, but not after injection into the dentate gyrus that did not significantly increase intracellular Zn2+ in the granule cell layer of the dentate gyrus. Object recognition memory deficit may be linked to the preferential increase in Zn2+ and/or the preferential vulnerability to Zn2+ in CA1 pyramidal neurons. In the case of the cytosolic increase in endogenous Zn2+ in the CA1 induced by 100 mM KCl, furthermore, object recognition memory was also transiently impaired, while ameliorated by co-injection of CaEDTA to block the increase in cytosolic Zn2+. The present study indicates that the transient increase in cytosolic Zn2+ in CA1 pyramidal neurons reversibly impairs object recognition memory. PMID:22163318

LYK4, a Lysin Motif Receptor-Like Kinase, Is Important for Chitin Signaling and Plant Innate Immunity in Arabidopsis1[C][W][OA

PubMed Central

Wan, Jinrong; Tanaka, Kiwamu; Zhang, Xue-Cheng; Son, Geon Hui; Brechenmacher, Laurent; Nguyen, Tran Hong Nha; Stacey, Gary

2012-01-01

Chitin is commonly found in fungal cell walls and is one of the well-studied microbe/pathogen-associated molecular patterns. Previous studies showed that lysin motif (LysM)-containing proteins are essential for plant recognition of chitin, leading to the activation of plant innate immunity. In Arabidopsis (Arabidopsis thaliana), the LYK1/CERK1 (for LysM-containing receptor-like kinase1/chitin elicitor receptor kinase1) was shown to be essential for chitin recognition, whereas in rice (Oryza sativa), the LysM-containing protein, CEBiP (for chitin elicitor-binding protein), was shown to be involved in chitin recognition. Unlike LYK1/CERK1, CEBiP lacks an intracellular kinase domain. Arabidopsis possesses three CEBiP-like genes. Our data show that mutations in these genes, either singly or in combination, did not compromise the response to chitin treatment. Arabidopsis also contains five LYK genes. Analysis of mutations in LYK2, -3, -4, or -5 showed that LYK4 is also involved in chitin signaling. The lyk4 mutants showed reduced induction of chitin-responsive genes and diminished chitin-induced cytosolic calcium elevation as well as enhanced susceptibility to both the bacterial pathogen Pseudomonas syringae pv tomato DC3000 and the fungal pathogen Alternaria brassicicola, although these phenotypes were not as dramatic as that seen in the lyk1/cerk1 mutants. Similar to LYK1/CERK1, the LYK4 protein was also localized to the plasma membrane. Therefore, LYK4 may play a role in the chitin recognition receptor complex to assist chitin signal transduction and plant innate immunity. PMID:22744984

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.

The ability to survive intracellular freezing in nematodes is related to the pattern and distribution of ice formed.

PubMed

Raymond, Méliane R; Wharton, David A

2016-07-01

A few species of nematodes can survive extensive intracellular freezing throughout all their tissues, an event that is usually thought to be fatal to cells. How are they able to survive in this remarkable way? The pattern and distribution of ice formed, after freezing at -10°C, can be observed using freeze substitution and transmission electron microscopy, which preserves the former position of ice as white spaces. We compared the pattern and distribution of ice formed in a nematode that survives intracellular freezing well (Panagrolaimus sp. DAW1), one that survives poorly (Panagrellus redivivus) and one with intermediate levels of survival (Plectus murrayi). We also examined Panagrolaimus sp. in which the survival of freezing had been compromised by starvation. Levels of survival were as expected and the use of vital dyes indicated cellular damage in those that survived poorly (starved Panagrolaimus sp. and P. murrayi). In fed Panagrolaimus sp. the intracellular ice spaces were small and uniform, whereas in P. redivivus and starved Panagrolaimus sp. there were some large spaces that may be causing cellular damage. The pattern and distribution of ice formed was different in P. murrayi, with a greater number of individuals having no ice or only small intracellular ice spaces. Control of the size of the ice formed is thus important for the survival of intracellular freezing in nematodes. © 2016. Published by The Company of Biologists Ltd.

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.

Brucella canis Is an Intracellular Pathogen That Induces a Lower Proinflammatory Response than Smooth Zoonotic Counterparts

PubMed Central

Chacón-Díaz, Carlos; Altamirano-Silva, Pamela; González-Espinoza, Gabriela; Medina, María-Concepción; Alfaro-Alarcón, Alejandro; Bouza-Mora, Laura; Jiménez-Rojas, César; Wong, Melissa; Barquero-Calvo, Elías; Rojas, Norman; Guzmán-Verri, Caterina

2015-01-01

Canine brucellosis caused by Brucella canis is a disease of dogs and a zoonotic risk. B. canis harbors most of the virulence determinants defined for the genus, but its pathogenic strategy remains unclear since it has not been demonstrated that this natural rough bacterium is an intracellular pathogen. Studies of B. canis outbreaks in kennel facilities indicated that infected dogs displaying clinical signs did not present hematological alterations. A virulent B. canis strain isolated from those outbreaks readily replicated in different organs of mice for a protracted period. However, the levels of tumor necrosis factor alpha, interleukin-6 (IL-6), and IL-12 in serum were close to background levels. Furthermore, B. canis induced lower levels of gamma interferon, less inflammation of the spleen, and a reduced number of granulomas in the liver in mice than did B. abortus. When the interaction of B. canis with cells was studied ex vivo, two patterns were observed, a predominant scattered cell-associated pattern of nonviable bacteria and an infrequent intracellular replicative pattern of viable bacteria in a perinuclear location. The second pattern, responsible for the increase in intracellular multiplication, was dependent on the type IV secretion system VirB and was seen only if the inoculum used for cell infections was in early exponential phase. Intracellular replicative B. canis followed an intracellular trafficking route undistinguishable from that of B. abortus. Although B. canis induces a lower proinflammatory response and has a stealthier replication cycle, it still displays the pathogenic properties of the genus and the ability to persist in infected organs based on the ability to multiply intracellularly. PMID:26438796

Molecular cloning, characterization, and functional analysis of pigeon (Columba livia) Toll-like receptor 5.

PubMed

Xiong, Dan; Song, Li; Pan, Zhiming; Jiao, Xinan

2018-06-26

Toll-like receptors (TLRs) are pattern recognition receptors that are vital for the recognition of pathogen-associated molecular patterns. TLR5 is responsible for the recognition of bacterial flagellin to induce the NF-κB activation and innate immune responses. In this study, we cloned and identified the TLR5 gene from the King pigeon (Columba livia) designated as PiTLR5. Full-length PiTLR5 cDNA (2583 bp) encoded an 860-amino acid protein containing a signal peptide sequence, 10 leucine-rich repeat domains, a leucine-rich repeat C-terminal domain, a transmembrane domain, and an intracellular Toll-interleukin-1 receptor domain. Pigeon TLR5 mRNA expression was quantified by performing quantitative real-time PCR (qRT-PCR), which showed that PiTLR5 was broadly expressed in all examined tissues, with the highest expression in the liver, peripheral blood mononuclear cells, and spleen. PiTLR5-mediated innate immune responses were measured by determining its effects on NF-κB activation and cytokine expression. The results showed that HEK293T cells transfected with PiTLR5 robustly activated the NF-κB response to flagellin, but not other TLR stimuli, and induced significant upregulation of IL-1β, IL-8, TNF-α, and IFN-γ, indicating that PiTLR5 is a functional TLR5 homolog. Additionally, following flagellin stimulation of pigeon splenic lymphocytes, the levels of TLR5, NF-κB, IL-6, IL-8, CCL5, and IFN-γ mRNA, assessed using qRT-PCR, were significantly upregulated. Besides, TLR5 knockdown resulted in the significantly downregulated expression of NF-κB and related cytokines/chemokines. Triggering pigeon TLR5 contributes to significant upregulation of inflammatory cytokines and chemokines, suggesting that pigeon TLR5 plays an important role in the innate immune responses.

AFM force spectroscopy reveals how subtle structural differences affect the interaction strength between Candida albicans and DC-SIGN.

PubMed

te Riet, Joost; Reinieren-Beeren, Inge; Figdor, Carl G; Cambi, Alessandra

2015-11-01

The fungus Candida albicans is the most common cause of mycotic infections in immunocompromised hosts. Little is known about the initial interactions between Candida and immune cell receptors, such as the C-type lectin dendritic cell-specific intracellular cell adhesion molecule-3 (ICAM-3)-grabbing non-integrin (DC-SIGN), because a detailed characterization at the structural level is lacking. DC-SIGN recognizes specific Candida-associated molecular patterns, that is, mannan structures present in the cell wall of Candida. The molecular recognition mechanism is however poorly understood. We postulated that small differences in mannan-branching may result in considerable differences in the binding affinity. Here, we exploit atomic force microscope-based dynamic force spectroscopy with single Candida cells to gain better insight in the carbohydrate recognition capacity of DC-SIGN. We demonstrate that slight differences in the N-mannan structure of Candida, that is, the absence or presence of a phosphomannan side chain, results in differences in the recognition by DC-SIGN as follows: (i) it contributes to the compliance of the outer cell wall of Candida, and (ii) its presence results in a higher binding energy of 1.6 kB T. The single-bond affinity of tetrameric DC-SIGN for wild-type C. albicans is ~10.7 kB T and a dissociation constant kD of 23 μM, which is relatively strong compared with other carbohydrate-protein interactions described in the literature. In conclusion, this study shows that DC-SIGN specifically recognizes mannan patterns on C. albicans with high affinity. Knowledge on the binding pocket of DC-SIGN and its pathogenic ligands will lead to a better understanding of how fungal-associated carbohydrate structures are recognized by receptors of the immune system and can ultimately contribute to the development of new anti-fungal drugs. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Intracellular delivery of poly(I:C) induces apoptosis of fibroblast-like synoviocytes via an unknown dsRNA sensor

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

Karpus, Olga N.; Hsiao, Cheng-Chih; Kort, Hanneke de

Fibroblast-like synoviocytes (FLS) express functional membranous and cytoplasmic sensors for double-stranded (ds)RNA. Notably, FLS undergo apoptosis upon transfection with the synthetic dsRNA analog poly(I:C). We here studied the mechanism of intracellular poly(I:C) recognition and subsequent cell death in FLS. FLS responded similarly to poly(I:C) or 3pRNA transfection; however, only intracellular delivery of poly(I:C) induced significant cell death, accompanied by upregulation of pro-apoptotic proteins Puma and Noxa, caspase 3 cleavage, and nuclear segregation. Knockdown of the DExD/H-box helicase MDA5 did not affect the response to intracellular poly(I:C); in contrast, knockdown of RIG-I abrogated the response to 3pRNA. Knockdown of the downstreammore » adaptor proteins IPS, STING, and TRIF or inhibition of TBK1 did not affect the response to intracellular poly(I:C), while knockdown of IFNAR blocked intracellular poly(I:C)-mediated signaling and cell death. We conclude that a so far unknown intracellular sensor recognizes linear dsRNA and induces apoptosis in FLS. - Highlights: • Intracellular poly(I:C) and 3pRNA evoke immune responses in FLS. • Only intracellular delivery of poly(I:C) induces FLS apoptosis. • FLS do not require MDA5 for their response to intracellular poly(I:C). • FLS respond to intracellular poly(I:C) independent of IPS and STING. • An unknown intracellular sensor recognizes linear dsRNA in FLS.« less

Role of Innate Immunity in Neonatal Infection

PubMed Central

Cuenca, Alex G; Wynn, James L; Moldawer, Lyle L; Levy, Ofer

2014-01-01

Newborns are at increased risk of infection due to genetic, epigenetic, and environmental factors. Herein we examine the roles of the neonatal innate immune system in host defense against bacterial and viral infections. Full-term newborns express a distinct innate immune system biased towards TH2/TH17-polarizing and anti-inflammatory cytokine production with relative impairment in TH1-polarizing cytokine production that leaves them particularly vulnerable to infection with intracellular pathogens. In addition to these distinct features, preterm newborns also have fragile skin, impaired TH17-polarizing cytokine production and deficient expression of complement and of antimicrobial proteins and peptides (APPs) that likely contribute to susceptibility to pyogenic bacteria. Ongoing research is identifying APPs, including bacterial/permeability-increasing protein and lactoferrin, as well as pattern recognition receptor (PRR) agonists that may serve to enhance protective newborn and infant immune responses as stand alone immune response modifiers or vaccine adjuvants. PMID:23297181

Molecular regulation of cell fate in cerebral ischemia: role of the inflammasome and connected pathways

PubMed Central

Trendelenburg, George

2014-01-01

Analogous to Toll-like receptors, NOD-like receptors represent a class of pattern recognition receptors, which are cytosolic and constitute part of different inflammasomes. These large protein complexes are activated not only by different pathogens, but also by sterile inflammation or by specific metabolic conditions. Mutations can cause hereditary autoinflammatory systemic diseases, and inflammasome activation has been linked to many multifactorial diseases, such as diabetes or cardiovascular diseases. Increasing data also support an important role in different central nervous diseases such as stroke. Thus, the current knowledge of the functional role of this intracellular ‘master switch' of inflammation is discussed with a focus on its role in ischemic stroke, neurodegeneration, and also with regard to the recent data which argues for a relevant role in other organs or biologic systems which influence stroke incidence or prognosis. PMID:25227604

Subverting Toll-Like Receptor Signaling by Bacterial Pathogens

PubMed Central

McGuire, Victoria A.; Arthur, J. Simon C.

2015-01-01

Pathogenic bacteria are detected by pattern-recognition receptors (PRRs) expressed on innate immune cells, which activate intracellular signal transduction pathways to elicit an immune response. Toll-like receptors are, perhaps, the most studied of the PRRs and can activate the mitogen-activated protein kinase (MAPK) and Nuclear Factor-κB (NF-κB) pathways. These pathways are critical for mounting an effective immune response. In order to evade detection and promote virulence, many pathogens subvert the host immune response by targeting components of these signal transduction pathways. This mini-review highlights the diverse mechanisms that bacterial pathogens have evolved to manipulate the innate immune response, with a particular focus on those that target MAPK and NF-κB signaling pathways. Understanding the elaborate strategies that pathogens employ to subvert the immune response not only highlights the importance of these proteins in mounting effective immune responses, but may also identify novel approaches for treatment or prevention of infection. PMID:26648936

No Love Lost Between Viruses and Interferons.

PubMed

Fensterl, Volker; Chattopadhyay, Saurabh; Sen, Ganes C

2015-11-01

The interferon system protects mammals against virus infections. There are several types of interferons, which are characterized by their ability to inhibit virus replication and resultant pathogenesis by triggering both innate and cell-mediated immune responses. Virus infection is sensed by a variety of cellular pattern-recognition receptors and triggers the synthesis of interferons, which are secreted by the infected cells. In uninfected cells, cell surface receptors recognize the secreted interferons and activate intracellular signaling pathways that induce the expression of interferon-stimulated genes; the proteins encoded by these genes inhibit different stages of virus replication. To avoid extinction, almost all viruses have evolved mechanisms to defend themselves against the interferon system. Consequently, a dynamic equilibrium of survival is established between the virus and its host, an equilibrium that can be shifted to the host's favor by the use of exogenous interferon as a therapeutic antiviral agent.

MicroRNA-132 regulates recognition memory and synaptic plasticity in the perirhinal cortex

PubMed Central

Scott, Helen L; Tamagnini, Francesco; Narduzzo, Katherine E; Howarth, Joanna L; Lee, Youn-Bok; Wong, Liang-Fong; Brown, Malcolm W; Warburton, Elizabeth C; Bashir, Zafar I; Uney, James B

2012-01-01

Evidence suggests that the acquisition of recognition memory depends upon CREB-dependent long-lasting changes in synaptic plasticity in the perirhinal cortex. The CREB-responsive microRNA miR-132 has been shown to regulate synaptic transmission and we set out to investigate a role for this microRNA in recognition memory and its underlying plasticity mechanisms. To this end we mediated the specific overexpression of miR-132 selectively in the rat perirhinal cortex and demonstrated impairment in short-term recognition memory. This functional deficit was associated with a reduction in both long-term depression and long-term potentiation. These results confirm that microRNAs are key coordinators of the intracellular pathways that mediate experience-dependent changes in the brain. In addition, these results demonstrate a role for miR-132 in the neuronal mechanisms underlying the formation of short-term recognition memory. PMID:22845676

Transgenic expression of the dicotyledonous pattern recognition receptor EFR in rice leads to ligand-dependent activation of defense responses

DOE PAGES

Schwessinger, Benjamin; Bahar, Ofir; Thomas, Nicolas; ...

2015-03-30

Plant plasma membrane localized pattern recognition receptors (PRRs) detect extracellular pathogen-associated molecules. PRRs such as Arabidopsis EFR and rice XA21 are taxonomically restricted and are absent from most plant genomes. Here we show that rice plants expressing EFR or the chimeric receptor EFR::XA21, containing the EFR ectodomain and the XA21 intracellular domain, sense both Escherichia coli- and Xanthomonas oryzae pv. oryzae (Xoo)-derived elf18 peptides at sub-nanomolar concentrations. Treatment of EFR and EFR::XA21 rice leaf tissue with elf18 leads to MAP kinase activation, reactive oxygen production and defense gene expression. Although expression of EFR does not lead to robust enhanced resistancemore » to fully virulent Xoo isolates, it does lead to quantitatively enhanced resistance to weakly virulent Xoo isolates. EFR interacts with OsSERK2 and the XA21 binding protein 24 (XB24), two key components of the rice XA21-mediated immune response. Rice-EFR plants silenced for OsSERK2, or overexpressing rice XB24 are compromised in elf18-induced reactive oxygen production and defense gene expression indicating that these proteins are also important for EFR-mediated signaling in transgenic rice. Taken together, our results demonstrate the potential feasibility of enhancing disease resistance in rice and possibly other monocotyledonous crop species by expression of dicotyledonous PRRs. Our results also suggest that Arabidopsis EFR utilizes at least a subset of the known endogenous rice XA21 signaling components.« less

Transgenic expression of the dicotyledonous pattern recognition receptor EFR in rice leads to ligand-dependent activation of defense responses

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

Schwessinger, Benjamin; Bahar, Ofir; Thomas, Nicolas

Plant plasma membrane localized pattern recognition receptors (PRRs) detect extracellular pathogen-associated molecules. PRRs such as Arabidopsis EFR and rice XA21 are taxonomically restricted and are absent from most plant genomes. Here we show that rice plants expressing EFR or the chimeric receptor EFR::XA21, containing the EFR ectodomain and the XA21 intracellular domain, sense both Escherichia coli- and Xanthomonas oryzae pv. oryzae (Xoo)-derived elf18 peptides at sub-nanomolar concentrations. Treatment of EFR and EFR::XA21 rice leaf tissue with elf18 leads to MAP kinase activation, reactive oxygen production and defense gene expression. Although expression of EFR does not lead to robust enhanced resistancemore » to fully virulent Xoo isolates, it does lead to quantitatively enhanced resistance to weakly virulent Xoo isolates. EFR interacts with OsSERK2 and the XA21 binding protein 24 (XB24), two key components of the rice XA21-mediated immune response. Rice-EFR plants silenced for OsSERK2, or overexpressing rice XB24 are compromised in elf18-induced reactive oxygen production and defense gene expression indicating that these proteins are also important for EFR-mediated signaling in transgenic rice. Taken together, our results demonstrate the potential feasibility of enhancing disease resistance in rice and possibly other monocotyledonous crop species by expression of dicotyledonous PRRs. Our results also suggest that Arabidopsis EFR utilizes at least a subset of the known endogenous rice XA21 signaling components.« less

The Brassicaceae Family Displays Divergent, Shoot-Skewed NLR Resistance Gene Expression.

PubMed

Munch, David; Gupta, Vikas; Bachmann, Asger; Busch, Wolfgang; Kelly, Simon; Mun, Terry; Andersen, Stig Uggerhøj

2018-02-01

Nucleotide-binding site leucine-rich repeat resistance genes (NLRs) allow plants to detect microbial effectors. We hypothesized that NLR expression patterns could reflect organ-specific differences in effector challenge and tested this by carrying out a meta-analysis of expression data for 1,235 NLRs from nine plant species. We found stable NLR root/shoot expression ratios within species, suggesting organ-specific hardwiring of NLR expression patterns in anticipation of distinct challenges. Most monocot and dicot plant species preferentially expressed NLRs in roots. In contrast, Brassicaceae species, including oilseed rape ( Brassica napus ) and the model plant Arabidopsis ( Arabidopsis thaliana ), were unique in showing NLR expression skewed toward the shoot across multiple phylogenetically distinct groups of NLRs. The Brassicaceae are also outliers in the sense that they have lost the common symbiosis signaling pathway, which enables intracellular infection by root symbionts. While it is unclear if these two events are related, the NLR expression shift identified here suggests that the Brassicaceae may have evolved unique pattern-recognition receptors and antimicrobial root metabolites to substitute for NLR protection. Such innovations in root protection could potentially be exploited in crop rotation schemes or for enhancing root defense systems of non-Brassicaceae crops. © 2018 American Society of Plant Biologists. All Rights Reserved.

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

Functional diversification of structurally alike NLR proteins in plants.

PubMed

Chakraborty, Joydeep; Jain, Akansha; Mukherjee, Dibya; Ghosh, Suchismita; Das, Sampa

2018-04-01

In due course of evolution many pathogens alter their effector molecules to modulate the host plants' metabolism and immune responses triggered upon proper recognition by the intracellular nucleotide-binding oligomerization domain containing leucine-rich repeat (NLR) proteins. Likewise, host plants have also evolved with diversified NLR proteins as a survival strategy to win the battle against pathogen invasion. NLR protein indeed detects pathogen derived effector proteins leading to the activation of defense responses associated with programmed cell death (PCD). In this interactive process, genome structure and plasticity play pivotal role in the development of innate immunity. Despite being quite conserved with similar biological functions in all eukaryotes, the intracellular NLR immune receptor proteins happen to be structurally distinct. Recent studies have made progress in identifying transcriptional regulatory complexes activated by NLR proteins. In this review, we attempt to decipher the intracellular NLR proteins mediated surveillance across the evolutionarily diverse taxa, highlighting some of the recent updates on NLR protein compartmentalization, molecular interactions before and after activation along with insights into the finer role of these receptor proteins to combat invading pathogens upon their recognition. Latest information on NLR sensors, helpers and NLR proteins with integrated domains in the context of plant pathogen interactions are also discussed. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

PubMed

Ming, Yue; Wang, Guangchao; Fan, Chunxiao

2015-01-01

With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition.

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.

Silencing and innate immunity in plant defense against viral and non-viral pathogens.

PubMed

Zvereva, Anna S; Pooggin, Mikhail M

2012-10-29

The frontline of plant defense against non-viral pathogens such as bacteria, fungi and oomycetes is provided by transmembrane pattern recognition receptors that detect conserved pathogen-associated molecular patterns (PAMPs), leading to pattern-triggered immunity (PTI). To counteract this innate defense, pathogens deploy effector proteins with a primary function to suppress PTI. In specific cases, plants have evolved intracellular resistance (R) proteins detecting isolate-specific pathogen effectors, leading to effector-triggered immunity (ETI), an amplified version of PTI, often associated with hypersensitive response (HR) and programmed cell death (PCD). In the case of plant viruses, no conserved PAMP was identified so far and the primary plant defense is thought to be based mainly on RNA silencing, an evolutionary conserved, sequence-specific mechanism that regulates gene expression and chromatin states and represses invasive nucleic acids such as transposons. Endogenous silencing pathways generate 21-24 nt small (s)RNAs, miRNAs and short interfering (si)RNAs, that repress genes post-transcriptionally and/or transcriptionally. Four distinct Dicer-like (DCL) proteins, which normally produce endogenous miRNAs and siRNAs, all contribute to the biogenesis of viral siRNAs in infected plants. Growing evidence indicates that RNA silencing also contributes to plant defense against non-viral pathogens. Conversely, PTI-based innate responses may contribute to antiviral defense. Intracellular R proteins of the same NB-LRR family are able to recognize both non-viral effectors and avirulence (Avr) proteins of RNA viruses, and, as a result, trigger HR and PCD in virus-resistant hosts. In some cases, viral Avr proteins also function as silencing suppressors. We hypothesize that RNA silencing and innate immunity (PTI and ETI) function in concert to fight plant viruses. Viruses counteract this dual defense by effectors that suppress both PTI-/ETI-based innate responses and RNA silencing to establish successful infection.

Automated analysis of calcium spiking profiles with CaSA software: two case studies from root-microbe symbioses.

PubMed

Russo, Giulia; Spinella, Salvatore; Sciacca, Eva; Bonfante, Paola; Genre, Andrea

2013-12-26

Repeated oscillations in intracellular calcium (Ca2+) concentration, known as Ca2+ spiking signals, have been described in plants for a limited number of cellular responses to biotic or abiotic stimuli and most notably the common symbiotic signaling pathway (CSSP) which mediates the recognition by their plant hosts of two endosymbiotic microbes, arbuscular mycorrhizal (AM) fungi and nitrogen fixing rhizobia. The detailed analysis of the complexity and variability of the Ca2+ spiking patterns which have been revealed in recent studies requires both extensive datasets and sophisticated statistical tools. As a contribution, we have developed automated Ca2+ spiking analysis (CaSA) software that performs i) automated peak detection, ii) statistical analyses based on the detected peaks, iii) autocorrelation analysis of peak-to-peak intervals to highlight major traits in the spiking pattern.We have evaluated CaSA in two experimental studies. In the first, CaSA highlighted unpredicted differences in the spiking patterns induced in Medicago truncatula root epidermal cells by exudates of the AM fungus Gigaspora margarita as a function of the phosphate concentration in the growth medium of both host and fungus. In the second study we compared the spiking patterns triggered by either AM fungal or rhizobial symbiotic signals. CaSA revealed the existence of different patterns in signal periodicity, which are thought to contribute to the so-called Ca2+ signature. We therefore propose CaSA as a useful tool for characterizing oscillatory biological phenomena such as Ca2+ spiking.

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.

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.

The Relationship between Respiration-Related Membrane Potential Slow Oscillations and Discharge Patterns in Mitral/Tufted Cells: What Are the Rules?

PubMed Central

Briffaud, Virginie; Fourcaud-Trocmé, Nicolas; Messaoudi, Belkacem; Buonviso, Nathalie; Amat, Corine

2012-01-01

Background A slow respiration-related rhythm strongly shapes the activity of the olfactory bulb. This rhythm appears as a slow oscillation that is detectable in the membrane potential, the respiration-related spike discharge of the mitral/tufted cells and the bulbar local field potential. Here, we investigated the rules that govern the manifestation of membrane potential slow oscillations (MPSOs) and respiration-related discharge activities under various afferent input conditions and cellular excitability states. Methodology and Principal Findings We recorded the intracellular membrane potential signals in the mitral/tufted cells of freely breathing anesthetized rats. We first demonstrated the existence of multiple types of MPSOs, which were influenced by odor stimulation and discharge activity patterns. Complementary studies using changes in the intracellular excitability state and a computational model of the mitral cell demonstrated that slow oscillations in the mitral/tufted cell membrane potential were also modulated by the intracellular excitability state, whereas the respiration-related spike activity primarily reflected the afferent input. Based on our data regarding MPSOs and spike patterns, we found that cells exhibiting an unsynchronized discharge pattern never exhibited an MPSO. In contrast, cells with a respiration-synchronized discharge pattern always exhibited an MPSO. In addition, we demonstrated that the association between spike patterns and MPSO types appeared complex. Conclusion We propose that both the intracellular excitability state and input strength underlie specific MPSOs, which, in turn, constrain the types of spike patterns exhibited. PMID:22952828

Structural and Functional Analysis of DDX41: a bispecific immune receptor for DNA and cyclic dinucleotide

PubMed Central

Omura, Hiroki; Oikawa, Daisuke; Nakane, Takanori; Kato, Megumi; Ishii, Ryohei; Ishitani, Ryuichiro; Tokunaga, Fuminori; Nureki, Osamu

2016-01-01

In the innate immune system, pattern recognition receptors (PRRs) specifically recognize ligands derived from bacteria or viruses, to trigger the responsible downstream pathways. DEAD box protein 41 (DDX41) is an intracellular PRR that triggers the downstream pathway involving the adapter STING, the kinase TBK1, and the transcription factor IRF3, to activate the type I interferon response. DDX41 is unique in that it recognizes two different ligands; i.e., double-stranded DNA (dsDNA) and cyclic dinucleotides (CDN), via its DEAD domain. However, the structural basis for the ligand recognition by the DDX41 DEAD domain has remained elusive. Here, we report two crystal structures of the DDX41 DEAD domain in apo forms, at 1.5 and 2.2 Å resolutions. A comparison of the two crystal structures revealed the flexibility in the ATP binding site, suggesting its formation upon ATP binding. Structure-guided functional analyses in vitro and in vivo demonstrated the overlapped binding surface for dsDNA and CDN, which is distinct from the ATP-binding site. We propose that the structural rearrangement of the ATP binding site is crucial for the release of ADP, enabling the fast turnover of DDX41 for the dsDNA/CDN-induced STING activation pathway. PMID:27721487

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

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.

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.

Differential regulation of the Epr3 receptor coordinates membrane-restricted rhizobial colonization of root nodule primordia

PubMed Central

Kawaharada, Yasuyuki; Nielsen, Mette W.; Kelly, Simon; James, Euan K.; Andersen, Kasper R.; Rasmussen, Sheena R.; Füchtbauer, Winnie; Madsen, Lene H.; Heckmann, Anne B.; Radutoiu, Simona; Stougaard, Jens

2017-01-01

In Lotus japonicus, a LysM receptor kinase, EPR3, distinguishes compatible and incompatible rhizobial exopolysaccharides at the epidermis. However, the role of this recognition system in bacterial colonization of the root interior is unknown. Here we show that EPR3 advances the intracellular infection mechanism that mediates infection thread invasion of the root cortex and nodule primordia. At the cellular level, Epr3 expression delineates progression of infection threads into nodule primordia and cortical infection thread formation is impaired in epr3 mutants. Genetic dissection of this developmental coordination showed that Epr3 is integrated into the symbiosis signal transduction pathways. Further analysis showed differential expression of Epr3 in the epidermis and cortical primordia and identified key transcription factors controlling this tissue specificity. These results suggest that exopolysaccharide recognition is reiterated during the progressing infection and that EPR3 perception of compatible exopolysaccharide promotes an intracellular cortical infection mechanism maintaining bacteria enclosed in plant membranes. PMID:28230048

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.

Intracellular GPCRs Play Key Roles in Synaptic Plasticity.

PubMed

Jong, Yuh-Jiin I; Harmon, Steven K; O'Malley, Karen L

2018-02-16

The trillions of synaptic connections within the human brain are shaped by experience and neuronal activity, both of which underlie synaptic plasticity and ultimately learning and memory. G protein-coupled receptors (GPCRs) play key roles in synaptic plasticity by strengthening or weakening synapses and/or shaping dendritic spines. While most studies of synaptic plasticity have focused on cell surface receptors and their downstream signaling partners, emerging data point to a critical new role for the very same receptors to signal from inside the cell. Intracellular receptors have been localized to the nucleus, endoplasmic reticulum, lysosome, and mitochondria. From these intracellular positions, such receptors may couple to different signaling systems, display unique desensitization patterns, and/or show distinct patterns of subcellular distribution. Intracellular GPCRs can be activated at the cell surface, endocytosed, and transported to an intracellular site or simply activated in situ by de novo ligand synthesis, diffusion of permeable ligands, or active transport of non-permeable ligands. Current findings reinforce the notion that intracellular GPCRs play a dynamic role in synaptic plasticity and learning and memory. As new intracellular GPCR roles are defined, the need to selectively tailor agonists and/or antagonists to both intracellular and cell surface receptors may lead to the development of more effective therapeutic tools.

Identification of Candida glabrata genes involved in pH modulation and modification of the phagosomal environment in macrophages.

PubMed

Kasper, Lydia; Seider, Katja; Gerwien, Franziska; Allert, Stefanie; Brunke, Sascha; Schwarzmüller, Tobias; Ames, Lauren; Zubiria-Barrera, Cristina; Mansour, Michael K; Becken, Ulrike; Barz, Dagmar; Vyas, Jatin M; Reiling, Norbert; Haas, Albert; Haynes, Ken; Kuchler, Karl; Hube, Bernhard

2014-01-01

Candida glabrata currently ranks as the second most frequent cause of invasive candidiasis. Our previous work has shown that C. glabrata is adapted to intracellular survival in macrophages and replicates within non-acidified late endosomal-stage phagosomes. In contrast, heat killed yeasts are found in acidified matured phagosomes. In the present study, we aimed at elucidating the processes leading to inhibition of phagosome acidification and maturation. We show that phagosomes containing viable C. glabrata cells do not fuse with pre-labeled lysosomes and possess low phagosomal hydrolase activity. Inhibition of acidification occurs independent of macrophage type (human/murine), differentiation (M1-/M2-type) or activation status (vitamin D3 stimulation). We observed no differential activation of macrophage MAPK or NFκB signaling cascades downstream of pattern recognition receptors after internalization of viable compared to heat killed yeasts, but Syk activation decayed faster in macrophages containing viable yeasts. Thus, delivery of viable yeasts to non-matured phagosomes is likely not triggered by initial recognition events via MAPK or NFκB signaling, but Syk activation may be involved. Although V-ATPase is abundant in C. glabrata phagosomes, the influence of this proton pump on intracellular survival is low since blocking V-ATPase activity with bafilomycin A1 has no influence on fungal viability. Active pH modulation is one possible fungal strategy to change phagosome pH. In fact, C. glabrata is able to alkalinize its extracellular environment, when growing on amino acids as the sole carbon source in vitro. By screening a C. glabrata mutant library we identified genes important for environmental alkalinization that were further tested for their impact on phagosome pH. We found that the lack of fungal mannosyltransferases resulted in severely reduced alkalinization in vitro and in the delivery of C. glabrata to acidified phagosomes. Therefore, protein mannosylation may play a key role in alterations of phagosomal properties caused by C. glabrata.

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.

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.

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.

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.

Targeting Cytosolic Nucleic Acid-Sensing Pathways for Cancer Immunotherapies.

PubMed

Iurescia, Sandra; Fioretti, Daniela; Rinaldi, Monica

2018-01-01

The innate immune system provides the first line of defense against pathogen infection though also influences pathways involved in cancer immunosurveillance. The innate immune system relies on a limited set of germ line-encoded sensors termed pattern recognition receptors (PRRs), signaling proteins and immune response factors. Cytosolic receptors mediate recognition of danger damage-associated molecular patterns (DAMPs) signals. Once activated, these sensors trigger multiple signaling cascades, converging on the production of type I interferons and proinflammatory cytokines. Recent studies revealed that PRRs respond to nucleic acids (NA) released by dying, damaged, cancer cells, as danger DAMPs signals, and presence of signaling proteins across cancer types suggests that these signaling mechanisms may be involved in cancer biology. DAMPs play important roles in shaping adaptive immune responses through the activation of innate immune cells and immunological response to danger DAMPs signals is crucial for the host response to cancer and tumor rejection. Furthermore, PRRs mediate the response to NA in several vaccination strategies, including DNA immunization. As route of double-strand DNA intracellular entry, DNA immunization leads to expression of key components of cytosolic NA-sensing pathways. The involvement of NA-sensing mechanisms in the antitumor response makes these pathways attractive drug targets. Natural and synthetic agonists of NA-sensing pathways can trigger cell death in malignant cells, recruit immune cells, such as DCs, CD8 + T cells, and NK cells, into the tumor microenvironment and are being explored as promising adjuvants in cancer immunotherapies. In this minireview, we discuss how cGAS-STING and RIG-I-MAVS pathways have been targeted for cancer treatment in preclinical translational researches. In addition, we present a targeted selection of recent clinical trials employing agonists of cytosolic NA-sensing pathways showing how these pathways are currently being targeted for clinical application in oncology.

Scavenger Receptor C Mediates Phagocytosis of White Spot Syndrome Virus and Restricts Virus Proliferation in Shrimp

PubMed Central

Yang, Ming-Chong; Shi, Xiu-Zhen; Yang, Hui-Ting; Sun, Jie-Jie; Xu, Ling; Wang, Xian-Wei; Zhao, Xiao-Fan

2016-01-01

Scavenger receptors are an important class of pattern recognition receptors that play several important roles in host defense against pathogens. The class C scavenger receptors (SRCs) have only been identified in a few invertebrates, and their role in the immune response against viruses is seldom studied. In this study, we firstly identified an SRC from kuruma shrimp, Marsupenaeus japonicus, designated MjSRC, which was significantly upregulated after white spot syndrome virus (WSSV) challenge at the mRNA and protein levels in hemocytes. The quantity of WSSV increased in shrimp after knockdown of MjSRC, compared with the controls. Furthermore, overexpression of MjSRC led to enhanced WSSV elimination via phagocytosis by hemocytes. Pull-down and co-immunoprecipitation assays demonstrated the interaction between MjSRC and the WSSV envelope protein. Electron microscopy observation indicated that the colloidal gold-labeled extracellular domain of MjSRC was located on the outer surface of WSSV. MjSRC formed a trimer and was internalized into the cytoplasm after WSSV challenge, and the internalization was strongly inhibited after knockdown of Mjβ-arrestin2. Further studies found that Mjβ-arrestin2 interacted with the intracellular domain of MjSRC and induced the internalization of WSSV in a clathrin-dependent manner. WSSV were co-localized with lysosomes in hemocytes and the WSSV quantity in shrimp increased after injection of lysosome inhibitor, chloroquine. Collectively, this study demonstrated that MjSRC recognized WSSV via its extracellular domain and invoked hemocyte phagocytosis to restrict WSSV systemic infection. This is the first study to report an SRC as a pattern recognition receptor promoting phagocytosis of a virus. PMID:28027319

Improvement of In Vivo Expression of Genes Delivered by Self-Amplifying RNA Using Vaccinia Virus Immune Evasion Proteins

PubMed Central

Beissert, Tim; Koste, Lars; Perkovic, Mario; Walzer, Kerstin C.; Erbar, Stephanie; Selmi, Abderraouf; Diken, Mustafa; Kreiter, Sebastian; Türeci, Özlem; Sahin, Ugur

2017-01-01

Among nucleic acid–based delivery platforms, self-amplifying RNA (saRNA) vectors are of increasing interest for applications such as transient expression of recombinant proteins and vaccination. saRNA is safe and, due to its capability to amplify intracellularly, high protein levels can be produced from even minute amounts of transfected templates. However, it is an obstacle to full exploitation of this platform that saRNA induces a strong innate host immune response. In transfected cells, pattern recognition receptors sense double-stranded RNA intermediates and via activation of protein kinase R (PKR) and interferon signaling initiate host defense measures including a translational shutdown. To reduce pattern recognition receptor stimulation and unleash suppressed saRNA translation, this study co-delivered non-replicating mRNA encoding vaccinia virus immune evasion proteins E3, K3, and B18. It was shown that E3 is far superior to K3 or B18 as a highly potent blocker of PKR activation and of interferon (IFN)-β upregulation. B18, in contrast, is superior in controlling OAS1, a key IFN-inducible gene involved in viral RNA degradation. By combining all three vaccinia proteins, the study achieved significant suppression of PKR and IFN pathway activation in vitro and enhanced expression of saRNA-encoded genes of interest both in vitro and in vivo. This approach promises to overcome key hurdles of saRNA gene delivery. Its application may improve the bioavailability of the encoded protein, and reduce the effective dose and correspondingly the cost of goods of manufacture in the various fields where saRNA utilization is envisioned. PMID:28877647

Improvement of In Vivo Expression of Genes Delivered by Self-Amplifying RNA Using Vaccinia Virus Immune Evasion Proteins.

PubMed

Beissert, Tim; Koste, Lars; Perkovic, Mario; Walzer, Kerstin C; Erbar, Stephanie; Selmi, Abderraouf; Diken, Mustafa; Kreiter, Sebastian; Türeci, Özlem; Sahin, Ugur

2017-12-01

Among nucleic acid-based delivery platforms, self-amplifying RNA (saRNA) vectors are of increasing interest for applications such as transient expression of recombinant proteins and vaccination. saRNA is safe and, due to its capability to amplify intracellularly, high protein levels can be produced from even minute amounts of transfected templates. However, it is an obstacle to full exploitation of this platform that saRNA induces a strong innate host immune response. In transfected cells, pattern recognition receptors sense double-stranded RNA intermediates and via activation of protein kinase R (PKR) and interferon signaling initiate host defense measures including a translational shutdown. To reduce pattern recognition receptor stimulation and unleash suppressed saRNA translation, this study co-delivered non-replicating mRNA encoding vaccinia virus immune evasion proteins E3, K3, and B18. It was shown that E3 is far superior to K3 or B18 as a highly potent blocker of PKR activation and of interferon (IFN)-β upregulation. B18, in contrast, is superior in controlling OAS1, a key IFN-inducible gene involved in viral RNA degradation. By combining all three vaccinia proteins, the study achieved significant suppression of PKR and IFN pathway activation in vitro and enhanced expression of saRNA-encoded genes of interest both in vitro and in vivo. This approach promises to overcome key hurdles of saRNA gene delivery. Its application may improve the bioavailability of the encoded protein, and reduce the effective dose and correspondingly the cost of goods of manufacture in the various fields where saRNA utilization is envisioned.

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.

Automated analysis of calcium spiking profiles with CaSA software: two case studies from root-microbe symbioses

PubMed Central

2013-01-01

Background Repeated oscillations in intracellular calcium (Ca2+) concentration, known as Ca2+ spiking signals, have been described in plants for a limited number of cellular responses to biotic or abiotic stimuli and most notably the common symbiotic signaling pathway (CSSP) which mediates the recognition by their plant hosts of two endosymbiotic microbes, arbuscular mycorrhizal (AM) fungi and nitrogen fixing rhizobia. The detailed analysis of the complexity and variability of the Ca2+ spiking patterns which have been revealed in recent studies requires both extensive datasets and sophisticated statistical tools. Results As a contribution, we have developed automated Ca2+ spiking analysis (CaSA) software that performs i) automated peak detection, ii) statistical analyses based on the detected peaks, iii) autocorrelation analysis of peak-to-peak intervals to highlight major traits in the spiking pattern. We have evaluated CaSA in two experimental studies. In the first, CaSA highlighted unpredicted differences in the spiking patterns induced in Medicago truncatula root epidermal cells by exudates of the AM fungus Gigaspora margarita as a function of the phosphate concentration in the growth medium of both host and fungus. In the second study we compared the spiking patterns triggered by either AM fungal or rhizobial symbiotic signals. CaSA revealed the existence of different patterns in signal periodicity, which are thought to contribute to the so-called Ca2+ signature. Conclusions We therefore propose CaSA as a useful tool for characterizing oscillatory biological phenomena such as Ca2+ spiking. PMID:24369773

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

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…

Eyes on MEGDEL: distinctive basal ganglia involvement in dystonia deafness syndrome.

PubMed

Wortmann, Saskia B; van Hasselt, Peter M; Barić, Ivo; Burlina, Alberto; Darin, Niklas; Hörster, Friederike; Coker, Mahmut; Ucar, Sema Kalkan; Krumina, Zita; Naess, Karin; Ngu, Lock H; Pronicka, Ewa; Riordan, Gilian; Santer, Rene; Wassmer, Evangeline; Zschocke, Johannes; Schiff, Manuel; de Meirleir, Linda; Alowain, Mohammed A; Smeitink, Jan A M; Morava, Eva; Kozicz, Tamas; Wevers, Ron A; Wolf, Nicole I; Willemsen, Michel A

2015-04-01

Pediatric movement disorders are still a diagnostic challenge, as many patients remain without a (genetic) diagnosis. Magnetic resonance imaging (MRI) pattern recognition can lead to the diagnosis. MEGDEL syndrome (3-MethylGlutaconic aciduria, Deafness, Encephalopathy, Leigh-like syndrome MIM #614739) is a clinically and biochemically highly distinctive dystonia deafness syndrome accompanied by 3-methylglutaconic aciduria, severe developmental delay, and progressive spasticity. Mutations are found in SERAC1, encoding a phosphatidylglycerol remodeling enzyme essential for both mitochondrial function and intracellular cholesterol trafficking. Based on the homogenous phenotype, we hypothesized an accordingly characteristic MRI pattern. A total of 43 complete MRI studies of 30 patients were systematically reevaluated. All patients presented a distinctive brain MRI pattern with five characteristic disease stages affecting the basal ganglia, especially the putamen. In stage 1, T2 signal changes of the pallidum are present. In stage 2, swelling of the putamen and caudate nucleus is seen. The dorsal putamen contains an "eye" that shows no signal alteration and (thus) seems to be spared during this stage of the disease. It later increases, reflecting progressive putaminal involvement. This "eye" was found in all patients with MEGDEL syndrome during a specific age range, and has not been reported in other disorders, making it pathognomonic for MEDGEL and allowing diagnosis based on MRI findings. Georg Thieme Verlag KG Stuttgart · New York.

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...

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

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

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.

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

The Intracellular Life of Cryptococcus neoformans

PubMed Central

Coelho, Carolina; Bocca, Anamelia L.; Casadevall, Arturo

2016-01-01

Cryptococcus neoformans is a fungal pathogen with worldwide distribution. Serological studies of human populations show a high prevalence of human infection, which rarely progresses to disease in immunocompetent hosts. However, decreased host immunity places individuals at high risk for cryptococcal disease. The disease can result from acute infection or reactivation of latent infection, in which yeasts within granulomas and host macrophages emerge to cause disease. In this review, we summarize what is known about the cellular recognition, ingestion, and killing of C. neoformans and discuss the unique and remarkable features of its intracellular life, including the proposed mechanisms for fungal persistence and killing in phagocytic cells. PMID:24050625

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

Modular Activating Receptors in Innate and Adaptive Immunity.

PubMed

Berry, Richard; Call, Matthew E

2017-03-14

Triggering of cell-mediated immunity is largely dependent on the recognition of foreign or abnormal molecules by a myriad of cell surface-bound receptors. Many activating immune receptors do not possess any intrinsic signaling capacity but instead form noncovalent complexes with one or more dimeric signaling modules that communicate with a common set of kinases to initiate intracellular information-transfer pathways. This modular architecture, where the ligand binding and signaling functions are detached from one another, is a common theme that is widely employed throughout the innate and adaptive arms of immune systems. The evolutionary advantages of this highly adaptable platform for molecular recognition are visible in the variety of ligand-receptor interactions that can be linked to common signaling pathways, the diversification of receptor modules in response to pathogen challenges, and the amplification of cellular responses through incorporation of multiple signaling motifs. Here we provide an overview of the major classes of modular activating immune receptors and outline the current state of knowledge regarding how these receptors assemble, recognize their ligands, and ultimately trigger intracellular signal transduction pathways that activate immune cell effector functions.

A study on ice crystal formation behavior at intracellular freezing of plant cells using a high-speed camera.

PubMed

Ninagawa, Takako; Eguchi, Akemi; Kawamura, Yukio; Konishi, Tadashi; Narumi, Akira

2016-08-01

Intracellular ice crystal formation (IIF) causes several problems to cryopreservation, and it is the key to developing improved cryopreservation techniques that can ensure the long-term preservation of living tissues. Therefore, the ability to capture clear intracellular freezing images is important for understanding both the occurrence and the IIF behavior. The authors developed a new cryomicroscopic system that was equipped with a high-speed camera for this study and successfully used this to capture clearer images of the IIF process in the epidermal tissues of strawberry geranium (Saxifraga stolonifera Curtis) leaves. This system was then used to examine patterns in the location and formation of intracellular ice crystals and to evaluate the degree of cell deformation because of ice crystals inside the cell and the growing rate and grain size of intracellular ice crystals at various cooling rates. The results showed that an increase in cooling rate influenced the formation pattern of intracellular ice crystals but had less of an effect on their location. Moreover, it reduced the degree of supercooling at the onset of intracellular freezing and the degree of cell deformation; the characteristic grain size of intracellular ice crystals was also reduced, but the growing rate of intracellular ice crystals was increased. Thus, the high-speed camera images could expose these changes in IIF behaviors with an increase in the cooling rate, and these are believed to have been caused by an increase in the degree of supercooling. Copyright © 2016 Elsevier Inc. All rights reserved.

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

A Peptide-Based Method for 13C Metabolic Flux Analysis in Microbial Communities

PubMed Central

Ghosh, Amit; Nilmeier, Jerome; Weaver, Daniel; Adams, Paul D.; Keasling, Jay D.; Mukhopadhyay, Aindrila; Petzold, Christopher J.; Martín, Héctor García

2014-01-01

The study of intracellular metabolic fluxes and inter-species metabolite exchange for microbial communities is of crucial importance to understand and predict their behaviour. The most authoritative method of measuring intracellular fluxes, 13C Metabolic Flux Analysis (13C MFA), uses the labeling pattern obtained from metabolites (typically amino acids) during 13C labeling experiments to derive intracellular fluxes. However, these metabolite labeling patterns cannot easily be obtained for each of the members of the community. Here we propose a new type of 13C MFA that infers fluxes based on peptide labeling, instead of amino acid labeling. The advantage of this method resides in the fact that the peptide sequence can be used to identify the microbial species it originates from and, simultaneously, the peptide labeling can be used to infer intracellular metabolic fluxes. Peptide identity and labeling patterns can be obtained in a high-throughput manner from modern proteomics techniques. We show that, using this method, it is theoretically possible to recover intracellular metabolic fluxes in the same way as through the standard amino acid based 13C MFA, and quantify the amount of information lost as a consequence of using peptides instead of amino acids. We show that by using a relatively small number of peptides we can counter this information loss. We computationally tested this method with a well-characterized simple microbial community consisting of two species. PMID:25188426

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.

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.

The machinery of Nod-like receptors: refining the paths to immunity and cell death.

PubMed

Saleh, Maya

2011-09-01

One of the fundamental aspects of the innate immune system is its capacity to discriminate between self and non-self or altered self, and to quickly respond by eliciting effector mechanisms that act in concert to restore normalcy. This capacity is determined by a set of evolutionarily conserved pattern recognition receptors (PRRs) that sense the presence of microbial motifs or endogenous danger signals, including tissue damage, cellular transformation or metabolic perturbation, and orchestrate the nature, duration and intensity of the innate immune response. Nod-like receptors (NLRs), a group of intracellular PRRs, are particularly essential as evident by the high incidence of genetic variations in their genes in various diseases of homeostasis. Here, I overview the signaling mechanisms of NLRs and discuss the mounting evidence of evolutionary conservation between their pathways and the cell death machinery. I also describe their effector functions that link the sensing of danger to the induction of inflammation, autophagy or cell death. © 2011 John Wiley & Sons A/S.

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.

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.

Fluorescent hydroxylamine derived from the fragmentation of PAMAM dendrimers for intracellular hypochlorite recognition.

PubMed

Wu, Te-Haw; Liu, Ching-Ping; Chien, Chih-Te; Lin, Shu-Yi

2013-08-26

Herein, a promising sensing approach based on the structure fragmentation of poly(amidoamine) (PAMAM) dendrimers for the selective detection of intracellular hypochlorite (OCl(-)) is reported. PAMAM dendrimers were easily disrupted by a cascade of oxidations in the tertiary amines of the dendritic core to produce an unsaturated hydroxylamine with blue fluorescence. Specially, the novel fluorophore was only sensitive to OCl(-), one of reactive oxygen species (ROS), resulting in an irreversible fluorescence turn-off. The fluorescent hydroxylamine was selectively oxidised by OCl(-) to form a labile oxoammonium cation that underwent further degradation. Without using any troublesomely synthetic steps, the novel sensing platform based on the fragmentation of PAMAM dendrimers, can be applied to detect OCl(-) in macrophage cells. The results suggest that the sensing approach may be useful for the detection of intracellular OCl(-) with minimal interference from biological matrixes. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Different antigen processing activities in dendritic cells, macrophages and monocytes lead to uneven production of HIV epitopes and affect CTL recognition

PubMed Central

Duong, Ellen; Bracho-Sanchez, Edith; Rucevic, Marijana; Liebesny, Paul H.; Xu, Yang; Shimada, Mariko; Ghebremichael, Musie; Kavanagh, Daniel G.; Le Gall, Sylvie

2014-01-01

Dendritic cells (DCs), macrophages (MPs) and monocytes are permissive to HIV. Whether they similarly process and present HIV epitopes to HIV-specific CD8 T cells is unknown despite the critical role of peptide processing and presentation for recognition and clearance of infected cells. Cytosolic peptidases degrade endogenous proteins originating from self or pathogens, exogenous antigens preprocessed in endolysosomes, thus shaping the peptidome available for endoplasmic reticulum (ER) translocation, trimming and MHC-I presentation. Here we compared the capacity of DCs, MPs and monocyte cytosolic extracts to produce epitope precursors and epitopes. We showed differences in the proteolytic activities and expression levels of cytosolic proteases between monocyte-derived DCs and MPs and upon maturation with LPS, R848 and CL097, with mature MPs having the highest activities. Using cytosol as a source of proteases to degrade epitope-containing HIV peptides, we showed by mass spectrometry that the degradation patterns of long peptides and the kinetics and amount of antigenic peptides produced differed among DCs, MPs and monocytes. Additionally, variable intracellular stability of HIV peptides prior to loading onto MHC may accentuate the differences in epitope availability for presentation by MHC-I between these subsets. Differences in peptide degradation led to 2- to 25-fold differences in the CTL responses elicited by the degradation peptides generated in DCs, MPs and monocytes. Differences in antigen processing activities between these subsets might lead to variations in the timing and efficiency of recognition of HIV-infected cells by CTLs and contribute to the unequal capacity of HIV-specific CTLs to control viral load. PMID:25230751

Hit-and-run, hit-and-stay, and commensal bacteria present different peptide content when viewed from the perspective of the T cell.

PubMed

He, Lu; De Groot, Anne S; Bailey-Kellogg, Chris

2015-11-27

Different types of bacteria face different pressures from the immune system, with those that persist ("hit-and-stay") potentially having to adapt more in order to escape than those prone to short-lived infection ("hit-and-run"), and with commensal bacteria potentially different from both due to additional physical mechanisms for avoiding immune detection. The Janus Immunogenicity Score (JIS) was recently developed to assess the likelihood of T cell recognition of an antigen, using an analysis that considers both binding of a peptide within the antigen by major histocompatability complex (MHC) and recognition of the peptide:MHC complex by cognate T cell receptor (TCR). This score was shown to be predictive of T effector vs. T regulatory or null responses in experimental data, as well as to distinguish viruses representative of the hit-and-stay vs. hit-and-run phenotypes. Here, JIS-based analyses were conducted in order to characterize the extent to which the pressure to avoid T cell recognition is manifested in genomic differences among representative hit-and-run, hit-and-stay, and commensal bacteria. Overall, extracellular proteins were found to have different JIS profiles from cytoplasmic ones. Contrasting the bacterial groups, extracellular proteins were shown to be quite different across the groups, much more so than intracellular proteins. The differences were evident even at the level of corresponding peptides in homologous protein pairs from hit-and-run and hit-and-stay bacteria. The multi-level analysis of patterns of immunogenicity across different groups of bacteria provides a new way to approach questions of bacterial immune camouflage or escape, as well as to approach the selection and optimization of candidates for vaccine design. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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.

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.

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

Intracellular Ca-carbonate biomineralization is widespread in cyanobacteria.

PubMed

Benzerara, Karim; Skouri-Panet, Feriel; Li, Jinhua; Férard, Céline; Gugger, Muriel; Laurent, Thierry; Couradeau, Estelle; Ragon, Marie; Cosmidis, Julie; Menguy, Nicolas; Margaret-Oliver, Isabel; Tavera, Rosaluz; López-García, Purificación; Moreira, David

2014-07-29

Cyanobacteria have played a significant role in the formation of past and modern carbonate deposits at the surface of the Earth using a biomineralization process that has been almost systematically considered induced and extracellular. Recently, a deep-branching cyanobacterial species, Candidatus Gloeomargarita lithophora, was reported to form intracellular amorphous Ca-rich carbonates. However, the significance and diversity of the cyanobacteria in which intracellular biomineralization occurs remain unknown. Here, we searched for intracellular Ca-carbonate inclusions in 68 cyanobacterial strains distributed throughout the phylogenetic tree of cyanobacteria. We discovered that diverse unicellular cyanobacterial taxa form intracellular amorphous Ca-carbonates with at least two different distribution patterns, suggesting the existence of at least two distinct mechanisms of biomineralization: (i) one with Ca-carbonate inclusions scattered within the cell cytoplasm such as in Ca. G. lithophora, and (ii) another one observed in strains belonging to the Thermosynechococcus elongatus BP-1 lineage, in which Ca-carbonate inclusions lie at the cell poles. This pattern seems to be linked with the nucleation of the inclusions at the septum of the cells, showing an intricate and original connection between cell division and biomineralization. These findings indicate that intracellular Ca-carbonate biomineralization by cyanobacteria has been overlooked by past studies and open new perspectives on the mechanisms and the evolutionary history of intra- and extracellular Ca-carbonate biomineralization by cyanobacteria.

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

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.

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…

Global proteomic analysis of two tick-borne emerging zoonotic agents: Anaplasma phagocytophilum and Ehrlichia chaffeensis

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

Lin, Mingqun ..; Kikuchi, Takane; Brewer, Heather M.

2011-02-17

Anaplasma phagocytophilum and Ehrlichia chaffeensis are obligatory intracellular {alpha}-proteobacteria that infect human leukocytes and cause potentially fatal emerging zoonoses. In the present study, we determined global protein expression profiles of these bacteria cultured in the human promyelocytic leukemia cell line, HL-60. Mass spectrometric (MS) analyses identified a total of 1,212 A. phagocytophilum and 1,021 E. chaffeensis proteins, representing 89.3 and 92.3% of the predicted bacterial proteomes, respectively. Nearly all bacterial proteins ({approx}99%) with known functions were expressed, whereas only approximately 80% of hypothetical proteins were detected in infected human cells. Quantitative MS/MS analyses indicated that highly expressed proteins in bothmore » bacteria included chaperones, enzymes involved in biosynthesis and metabolism, and outer membrane proteins, such as A. phagocytophilum P44 and E. chaffeensis P28/OMP-1. Among 113 A. phagocytophilum p44 paralogous genes, 110 of them were expressed and 88 of them were encoded by pseudogenes. In addition, bacterial infection of HL-60 cells up-regulated the expression of human proteins involved mostly in cytoskeleton components, vesicular trafficking, cell signaling, and energy metabolism, but down regulated some pattern recognition receptors involved in innate immunity. Our proteomics data represent a comprehensive analysis of A. phagocytophilum and E. chaffeensis proteomes, and provide a quantitative view of human host protein expression profiles regulated by bacterial infection. The availability of these proteomic data will provide new insights into biology and pathogenesis of these obligatory intracellular pathogens.« less

Analysis of host-pathogen modulators of autophagy during Mycobacterium Tuberculosis infection and therapeutic repercussions.

PubMed

Khan, Arshad; Jagannath, Chinnaswamy

2017-09-03

Mycobacterium tuberculosis is one of the most deadly human pathogens known today in modern world, responsible for about 1.5 million deaths annually. Development of TB disease occurs only in 1 out of 10 individuals exposed to the pathogen which indicates that the competent host defense mechanisms exist in majority of the hosts to control the infection. In the last decade, autophagy has emerged as a key host immune defense mechanism against intracellular M. tuberculosis infection. Autophagy has been demonstrated not only as an effective antimicrobial mechanism for the clearance of M. tuberculosis, but the process has also been suggested to prevent excessive inflammation to avoid the adverse effects of infection on host. Nevertheless, increasing evidences also show that in order to enhance its intracellular survival, M. tuberculosis has also evolved multiple strategies to compromise the optimal functioning of host autophagic machinery. This review describes an overview of the various host signaling pathways such as pattern recognition receptors, cytokines, nutrient starvation and other cellular stress that have been implicated in induction of autophagy during M. tuberculosis infection. The review also chalk out the complex interplay of several bacterial factors of M. tuberculosis that are known to be involved in compromising autophagy mediated defense of the host. A comprehensive understanding of the interaction of bacterial and host factors at the intersections of autophagic pathways could provide integrative insights for the development of autophagy-based prophylactics and novel therapeutic interventions for TB.

Reconstituted AIM2 inflammasome in cell-free system.

PubMed

Kaneko, Naoe; Ito, Yuki; Iwasaki, Tomoyuki; Takeda, Hiroyuki; Sawasaki, Tatsuya; Migita, Kiyoshi; Agematsu, Kazunaga; Kawakami, Atsushi; Morikawa, Shinnosuke; Mokuda, Sho; Kurata, Mie; Masumoto, Junya

2015-11-01

Absent in melanoma 2 (AIM2) is an intracellular pattern-recognition receptor, which is a member of the PYHIN protein family, consisting of a PYD domain and an IFN-inducible nuclear localization (HIN) domain. AIM2 is reported to oligomerize with adaptor protein ASC upon sensing bacterial and viral cytosolic DNA in order to form the AIM2 inflammasome, which activates caspase-1 leading to IL-1β secretion. Dysregulation of AIM2 inflammasome is supposed to result in autoinflammatory and autoimmune diseases. Thus, the development of new targeted drugs against AIM2 inflammasome would be important for the treatment of these diseases. However, since AIM2 inflammasome is an intracellular receptor, enforced internalization of both ligands and candidate molecules is necessary for the screening of AIM2-inflammasome-targeted molecules. We developed a reconstituted AIM2 inflammasome in a cell-free system with amplified luminescent proximity homogeneous assay (Alpha). Strong Alpha signal was detected upon incubation with poly-deoxyadenylic-deoxythymidylic acid, poly(dA:dT), whereas no Alpha signal was detected upon incubation with muramyl dipeptide, one of the NLR ligands of Nod2 ligand. The interaction between AIM2 and ASC was disrupted by an anti-human ASC monoclonal antibody, CRID3, a class of diarylsulfonylurea-containing compounds, and glycyrrhizin, a substance found in liquorice root. Thus, the reconstituted AIM2 inflammasome in a cell-free system is useful for screening AIM2-inflammasome-targeted therapeutic molecules. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

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.

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

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.

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

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

Early activation of teleost B cells in response to rhabdovirus infection.

PubMed

Abós, Beatriz; Castro, Rosario; González Granja, Aitor; Havixbeck, Jeffrey J; Barreda, Daniel R; Tafalla, Carolina

2015-02-01

To date, the response of teleost B cells to specific pathogens has been only scarcely addressed. In this work, we have demonstrated that viral hemorrhagic septicemia virus (VHSV), a fish rhabdovirus, has the capacity to infect rainbow trout spleen IgM-positive (IgM(+)) cells, although the infection is not productive. Consequently, we have studied the effects of VHSV on IgM(+) cell functionality, comparing these effects to those elicited by a Toll-like receptor 3 (TLR3) ligand, poly(I·C). We found that poly(I·C) and VHSV significantly upregulated TLR3 and type I interferon (IFN) transcription in spleen and blood IgM(+) cells. Further effects included the upregulated transcription of the CK5B chemokine. The significant inhibition of some of these effects in the presence of bafilomycin A1 (BAF), an inhibitor of endosomal acidification, suggests the involvement of an intracellular TLR in these responses. In the case of VHSV, these transcriptional effects were dependent on viral entry into B cells and the initiation of viral transcription. VHSV also provoked the activation of NF-κB and the upregulation of major histocompatibility complex class II (MHC-II) cell surface expression on IgM(+) cells, which, along with the increased transcription of the costimulatory molecules CD80/86 and CD83, pointed to VHSV-induced IgM(+) cell activation toward an antigen-presenting profile. Finally, despite the moderate effects of VHSV on IgM(+) cell proliferation, a consistent effect on IgM(+) cell survival was detected. Innate immune responses to pathogens established through their recognition by pattern recognition receptors (PRRs) have been traditionally ascribed to innate cells. However, recent evidence in mammals has revealed that innate pathogen recognition by B lymphocytes is a crucial factor in shaping the type of immune response that is mounted. In teleosts, these immediate effects of viral encounter on B lymphocytes have not been addressed to date. In our study, we have demonstrated that VHSV infection provoked immediate transcriptional effects on B cells, at least partially mediated by intracellular PRR signaling. VHSV also activated NF-κB and increased IgM(+) cell survival. Interestingly, VHSV activated B lymphocytes toward an antigen-presenting profile, suggesting an important role of IgM(+) cells in VHSV presentation. Our results provide a first description of the effects provoked by fish rhabdoviruses through their early interaction with teleost B cells. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

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.

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.

Epilepsy and innate immune system: A possible immunogenic predisposition and related therapeutic implications.

PubMed

Matin, Nassim; Tabatabaie, Omidreza; Falsaperla, Raffaele; Lubrano, Riccardo; Pavone, Piero; Mahmood, Fahad; Gullotta, Melissa; Serra, Agostino; Di Mauro, Paola; Cocuzza, Salvatore; Vitaliti, Giovanna

2015-01-01

Recent experimental studies and pathological analyses of patient brain tissue samples with refractory epilepsy suggest that inflammatory processes and neuroinflammation plays a key-role in the etiopathology of epilepsy and convulsive disorders. These inflammatory processes lead to the secretion of pro-inflammatory cytokines responsible for blood-brain-barrier disruption and involvement of resident immune cells in the inflammation pathway, occurring within the Central Nervous System (CNS). These elements are produced through activation of Toll-Like Receptors (TLRs) by exogenous and endogenous ligands thereby increasing expression of cytokines and co-stimulatory molecules through the activation of TLRs 2, 3, 4, and 9 as reported in murine studies.It has been demonstrated that IL-1β intracellular signaling and cascade is able to alter the neuronal excitability without cell loss. The activation of the IL-1β/ IL-1β R axis is strictly linked to the secretion of the intracellular protein MyD88, which interacts with other cell surface receptors, such as TLR4 during pathogenic recognition. Furthermore, TLR-signaling pathways are able to recognize molecules released from damaged tissues, such as damage-associated molecular patterns/proteins (DAMPs). Among these molecules, High-mobility group box-1 (HMGB1) is a component of chromatin that is passively released from necrotic cells and actively released by cells that are subject to profound stress. Moreover, recent studies have described models of epilepsy induced by the administration of bicuculline and kainic acid that highlight the nature of HMGB1-TLR4 interactions, their intracellular signaling pathway as well as their role in ictiogenesis and epileptic recurrence.The aim of our review is to focus on different branches of innate immunity and their role in epilepsy, emphasizing the role of immune related molecules in epileptogenesis and highlighting the research implications for novel therapeutic strategies.

The Increase in Mannose Receptor Recycling Favors Arginase Induction and Trypanosoma Cruzi Survival in Macrophages

PubMed Central

Garrido, Vanina V.; Dulgerian, Laura R.; Stempin, Cinthia C.; Cerbán, Fabio M.

2011-01-01

The macrophage mannose receptor (MR) is a pattern recognition receptor of the innate immune system that binds to microbial structures bearing mannose, fucose and N-acetylglucosamine on their surface. Trypanosoma cruzi antigen cruzipain (Cz) is found in the different developmental forms of the parasite. This glycoprotein has a highly mannosylated C-terminal domain that participates in the host-antigen contact. Our group previously demonstrated that Cz-macrophage (Mo) interaction could modulate the immune response against T. cruzi through the induction of a preferential metabolic pathway. In this work, we have studied in Mo the role of MR in arginase induction and in T. cruzi survival using different MR ligands. We have showed that pre-incubation of T. cruzi infected cells with mannose-Bovine Serum Albumin (Man-BSA, MR specific ligand) biased nitric oxide (NO)/urea balance towards urea production and increased intracellular amastigotes growth. The study of intracellular signals showed that pre-incubation with Man-BSA in T. cruzi J774 infected cells induced down-regulation of JNK and p44/p42 phosphorylation and increased of p38 MAPK phosphorylation. These results are coincident with previous data showing that Cz also modifies the MAPK phosphorylation profile induced by the parasite. In addition, we have showed by confocal microscopy that Cz and Man-BSA enhance MR recycling. Furthermore, we studied MR behavior during T. cruzi infection in vivo. MR was up-regulated in F4/80+ cells from T. cruzi infected mice at 13 and 15 days post infection. Besides, we investigated the effect of MR blocking antibody in T. cruzi infected peritoneal Mo. Arginase activity and parasite growth were decreased in infected cells pre-incubated with anti-MR antibody as compared with infected cells treated with control antibody. Therefore, we postulate that during T. cruzi infection, Cz may contact with MR, increasing MR recycling which leads to arginase activity up-regulation and intracellular parasite growth. PMID:22110379

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.

Regulated Forms of Cell Death in Fungi

PubMed Central

Gonçalves, A. Pedro; Heller, Jens; Daskalov, Asen; Videira, Arnaldo; Glass, N. Louise

2017-01-01

Cell death occurs in all domains of life. While some cells die in an uncontrolled way due to exposure to external cues, other cells die in a regulated manner as part of a genetically encoded developmental program. Like other eukaryotic species, fungi undergo programmed cell death (PCD) in response to various triggers. For example, exposure to external stress conditions can activate PCD pathways in fungi. Calcium redistribution between the extracellular space, the cytoplasm and intracellular storage organelles appears to be pivotal for this kind of cell death. PCD is also part of the fungal life cycle, in which it occurs during sexual and asexual reproduction, aging, and as part of development associated with infection in phytopathogenic fungi. Additionally, a fungal non-self-recognition mechanism termed heterokaryon incompatibility (HI) also involves PCD. Some of the molecular players mediating PCD during HI show remarkable similarities to major constituents involved in innate immunity in metazoans and plants. In this review we discuss recent research on fungal PCD mechanisms in comparison to more characterized mechanisms in metazoans. We highlight the role of PCD in fungi in response to exogenic compounds, fungal development and non-self-recognition processes and discuss identified intracellular signaling pathways and molecules that regulate fungal PCD. PMID:28983298

The chemical structure of DNA sequence signals for RNA transcription

NASA Technical Reports Server (NTRS)

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

1982-01-01

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

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

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.

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

An intracellular analysis of the visual responses of neurones in cat visual cortex.

PubMed Central

Douglas, R J; Martin, K A; Whitteridge, D

1991-01-01

1. Extracellular and intracellular recordings were made from neurones in the visual cortex of the cat in order to compare the subthreshold membrane potentials, reflecting the input to the neurone, with the output from the neurone seen as action potentials. 2. Moving bars and edges, generated under computer control, were used to stimulate the neurones. The membrane potential was digitized and averaged for a number of trials after stripping the action potentials. Comparison of extracellular and intracellular discharge patterns indicated that the intracellular impalement did not alter the neurones' properties. Input resistance of the neurone altered little during stable intracellular recordings (30 min-2 h 50 min). 3. Intracellular recordings showed two distinct patterns of membrane potential changes during optimal visual stimulation. The patterns corresponded closely to the division of S-type (simple) and C-type (complex) receptive fields. Simple cells had a complex pattern of membrane potential fluctuations, involving depolarizations alternating with hyperpolarizations. Complex cells had a simple single sustained plateau of depolarization that was often followed but not preceded by a hyperpolarization. In both simple and complex cells the depolarizations led to action potential discharges. The hyperpolarizations were associated with inhibition of action potential discharge. 4. Stimulating simple cells with non-optimal directions of motion produced little or no hyperpolarization of the membrane in most cases, despite a lack of action potential output. Directional complex cells always produced a single plateau of depolarization leading to action potential discharge in both the optimal and non-optimal directions of motion. The directionality could not be predicted on the basis of the position of the hyperpolarizing inhibitory potentials found in the optimal direction. 5. Stimulation of simple cells with non-optimal orientations occasionally produced slight hyperpolarizations and inhibition of action potential discharge. Complex cells, which had broader orientation tuning than simple cells, could show marked hyperpolarization for non-optimal orientations, but this was not generally the case. 6. The data do not support models of directionality and orientation that rely solely on strong inhibitory mechanisms to produce stimulus selectivity. PMID:1804981

Mycobacterium tuberculosis Transfer RNA Induces IL-12p70 via Synergistic Activation of Pattern Recognition Receptors within a Cell Network.

PubMed

Keegan, Caroline; Krutzik, Stephan; Schenk, Mirjam; Scumpia, Philip O; Lu, Jing; Pang, Yan Ling Joy; Russell, Brandon S; Lim, Kok Seong; Shell, Scarlet; Prestwich, Erin; Su, Dan; Elashoff, David; Hershberg, Robert M; Bloom, Barry R; Belisle, John T; Fortune, Sarah; Dedon, Peter C; Pellegrini, Matteo; Modlin, Robert L

2018-05-01

Upon recognition of a microbial pathogen, the innate and adaptive immune systems are linked to generate a cell-mediated immune response against the foreign invader. The culture filtrate of Mycobacterium tuberculosis contains ligands, such as M. tuberculosis tRNA, that activate the innate immune response and secreted Ags recognized by T cells to drive adaptive immune responses. In this study, bioinformatics analysis of gene-expression profiles derived from human PBMCs treated with distinct microbial ligands identified a mycobacterial tRNA-induced innate immune network resulting in the robust production of IL-12p70, a cytokine required to instruct an adaptive Th1 response for host defense against intracellular bacteria. As validated by functional studies, this pathway contained a feed-forward loop, whereby the early production of IL-18, type I IFNs, and IL-12p70 primed NK cells to respond to IL-18 and produce IFN-γ, enhancing further production of IL-12p70. Mechanistically, tRNA activates TLR3 and TLR8, and this synergistic induction of IL-12p70 was recapitulated by the addition of a specific TLR8 agonist with a TLR3 ligand to PBMCs. These data indicate that M. tuberculosis tRNA activates a gene network involving the integration of multiple innate signals, including types I and II IFNs, as well as distinct cell types to induce IL-12p70. Copyright © 2018 by The American Association of Immunologists, Inc.

[Perception and selectivity of sound duration in the central auditory midbrain].

PubMed

Wang, Xin; Li, An-An; Wu, Fei-Jian

2010-08-25

Sound duration plays important role in acoustic communication. Information of acoustic signal is mainly encoded in the amplitude and frequency spectrum of different durations. Duration selective neurons exist in the central auditory system including inferior colliculus (IC) of frog, bat, mouse and chinchilla, etc., and they are important in signal recognition and feature detection. Two generally accepted models, which are "coincidence detector model" and "anti-coincidence detector model", have been raised to explain the mechanism of neural selective responses to sound durations based on the study of IC neurons in bats. Although they are different in details, they both emphasize the importance of synaptic integration of excitatory and inhibitory inputs, and are able to explain the responses of most duration-selective neurons. However, both of the hypotheses need to be improved since other sound parameters, such as spectral pattern, amplitude and repetition rate, could affect the duration selectivity of the neurons. The dynamic changes of sound parameters are believed to enable the animal to effectively perform recognition of behavior related acoustic signals. Under free field sound stimulation, we analyzed the neural responses in the IC and auditory cortex of mouse and bat to sounds with different duration, frequency and amplitude, using intracellular or extracellular recording techniques. Based on our work and previous studies, this article reviews the properties of duration selectivity in central auditory system and discusses the mechanisms of duration selectivity and the effect of other sound parameters on the duration coding of auditory neurons.

Type I Interferon Production Induced by Streptococcus pyogenes-Derived Nucleic Acids Is Required for Host Protection

PubMed Central

Gratz, Nina; Hartweger, Harald; Matt, Ulrich; Kratochvill, Franz; Janos, Marton; Sigel, Stefanie; Drobits, Barbara; Li, Xiao-Dong; Knapp, Sylvia; Kovarik, Pavel

2011-01-01

Streptococcus pyogenes is a Gram-positive human pathogen that is recognized by yet unknown pattern recognition receptors (PRRs). Engagement of these receptor molecules during infection with S. pyogenes, a largely extracellular bacterium with limited capacity for intracellular survival, causes innate immune cells to produce inflammatory mediators such as TNF, but also type I interferon (IFN). Here we show that signaling elicited by type I IFNs is required for successful defense of mice against lethal subcutaneous cellulitis caused by S. pyogenes. Type I IFN signaling was accompanied with reduced neutrophil recruitment to the site of infection. Mechanistic analysis revealed that macrophages and conventional dendritic cells (cDCs) employ different signaling pathways leading to IFN-beta production. Macrophages required IRF3, STING, TBK1 and partially MyD88, whereas in cDCs the IFN-beta production was fully dependent on IRF5 and MyD88. Furthermore, IFN-beta production by macrophages was dependent on the endosomal delivery of streptococcal DNA, while in cDCs streptococcal RNA was identified as the IFN-beta inducer. Despite a role of MyD88 in both cell types, the known IFN-inducing TLRs were individually not required for generation of the IFN-beta response. These results demonstrate that the innate immune system employs several strategies to efficiently recognize S. pyogenes, a pathogenic bacterium that succeeded in avoiding recognition by the standard arsenal of TLRs. PMID:21625574

A New Thiosemicarbazone-Based Fluorescence "Turn-on" Sensor for Zn(2+) Recognition with a Large Stokes Shift and its Application in Live Cell Imaging.

PubMed

Tang, Lijun; Huang, Zhenlong; Zheng, Zhuxuan; Zhong, Keli; Bian, Yanjiang

2016-09-01

Selective fluorescence turn on Zn(2+) sensor with long-wavelength emission and a large Stokes shift is highly desirable in Zn(2+) sensing area. We reported herein the synthesis and Zn(2+) recognition properties of a new thiosemicarbazone-based fluorescent sensor L. L displays high selectivity and sensitivity toward Zn(2+) over other metal ions in DMSO-H2O (1:1, v/v, HEPES 10 mM, pH = 7.4) solution with a long-wavelength emission at 572 nm and a large Stokes shift of 222 nm. Confocal fluorescence microscopy experiments demonstrate that L is cell-permeable and capable of monitoring intracellular Zn(2+). Graphical Abstract We report a new thiosemicarbazone-based fluorescent sensor (L) for selective recognition of Zn(2+) with a long wavelength emission and a large Stokes shift.

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.

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

Toll like receptor 4: an important molecule in recognition and induction of appropriate immune responses against Chlamydia infection.

PubMed

Nosratababadi, Reza; Bagheri, Vahid; Zare-Bidaki, Mohammad; Hakimi, Hamid; Zainodini, Nahid; Kazemi Arababadi, Mohammad

2017-04-01

Chlamydia species are obligate intracellular pathogens causing different infectious diseases particularly asymptomatic genital infections and are also responsible for a wide range of complications. Previous studies showed that there are different immune responses to Chlamydia species and their infections are limited to some cases. Moreover, Chlamydia species are able to alter immune responses through modulating the expression of some immune system related molecules including cytokines. Toll like receptors (TLRs) belonge to pathogen recognition receptors (PRRs) and play vital roles in recognition of microbes and stimulation of appropriate immune responses. Therefore, it appears that TLRs may be considered as important sensors for recognition of Chlamydia and promotion of immune responses against these bacterial infections. Accordingly, TLR4 detects several microbial PAMPs such as bacterial lipopolysacharide (LPS) and subsequently activates transcription from pro-inflammatory cytokines in both MYD88 and TRIF pathways dependent manner. The purpose of this review is to provide the recent data about the status and major roles played by TLR4 in Chlamydia species recognition and promotion of immune responses against these infections and also the relationship between TLR4 activities and pathogenesis of Chlamydia infections. Copyright © 2017 Elsevier Ltd. All rights reserved.

The interactions of intracellular Protista and their host cells, with special reference to heterotrophic organisms.

PubMed

Bannister, L H

1979-04-11

Intracellular genera are found in all the major groups of Protista, but are particularly common among the dinoflagellates, trypanosomatid zooflagellates and suctorian ciliates; the Sporozoa are nearly all intracellular at some stage of their life, and the Microspora entirely so. Intracellular forms can dwell in the nucleus, within phagosomal or other vacuoles or may lie free in the hyaloplasm of their host cells. Organisms tend to select their hosts from a restricted taxonomic range although there are some notable exceptions. There is also great variation in the types of host cell inhabited. There are various reasons for both host and cell selectivity including recognition phenomena at the cell surfaces. Invasion of host cells is usually preceded by surface interactions with the invader. Some organisms depend upon phagocytosis for entry, but others induce host cells to engulf them by non-phagocytic means or invade by microinjection through the host plasma membrane. Protista avoid lysosomal destruction by their resistance to enzyme attack, by surrounding themselves with lysosome-inhibiting vacuoles, by escaping from the phagosomal system into the hyaloplasm and by choosing host cells which lack lysosomes. Nutrition of intracellular heterotrophic organisms involves some degree of competition with the host cell's metabolism as well as erosion of host cell cytoplasm. In Plasmodium infections, red cells are made more permeable to required nutrients by the action of the parasite on the host cell membrane. The parasite is often dependent upon the host cell for complex nutrients which it cannot synthesize for itself. Intracellular forms often profoundly modify the structure and metabolism of the host cell or interfere with its growth and multiplication. This may result in the final lysis of the host cell at the end of the intracellular phase or before the infection of other cells. Certain types of intracellular organisms may have arisen initially as forms attached to the cell surface of digestive or other organs, but the intracellular habit appears to have arisen independently in several groups of Protista.

Do pattern recognition skills transfer across sports? A preliminary analysis.

PubMed

Smeeton, Nicholas J; Ward, Paul; Williams, A Mark

2004-02-01

The ability to recognize patterns of play is fundamental to performance in team sports. While typically assumed to be domain-specific, pattern recognition skills may transfer from one sport to another if similarities exist in the perceptual features and their relations and/or the strategies used to encode and retrieve relevant information. A transfer paradigm was employed to compare skilled and less skilled soccer, field hockey and volleyball players' pattern recognition skills. Participants viewed structured and unstructured action sequences from each sport, half of which were randomly represented with clips not previously seen. The task was to identify previously viewed action sequences quickly and accurately. Transfer of pattern recognition skill was dependent on the participant's skill, sport practised, nature of the task and degree of structure. The skilled soccer and hockey players were quicker than the skilled volleyball players at recognizing structured soccer and hockey action sequences. Performance differences were not observed on the structured volleyball trials between the skilled soccer, field hockey and volleyball players. The skilled field hockey and soccer players were able to transfer perceptual information or strategies between their respective sports. The less skilled participants' results were less clear. Implications for domain-specific expertise, transfer and diversity across domains are discussed.

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

Development of Functional Fluorescent Molecular Probes for the Detection of Biological Substances

PubMed Central

Suzuki, Yoshio; Yokoyama, Kenji

2015-01-01

This review is confined to sensors that use fluorescence to transmit biochemical information. Fluorescence is, by far, the most frequently exploited phenomenon for chemical sensors and biosensors. Parameters that define the application of such sensors include intensity, decay time, anisotropy, quenching efficiency, and luminescence energy transfer. To achieve selective (bio)molecular recognition based on these fluorescence phenomena, various fluorescent elements such as small organic molecules, enzymes, antibodies, and oligonucleotides have been designed and synthesized over the past decades. This review describes the immense variety of fluorescent probes that have been designed for the recognitions of ions, small and large molecules, and their biological applications in terms of intracellular fluorescent imaging techniques. PMID:26095660

C-type lectins in immunity: recent developments

PubMed Central

Dambuza, Ivy M; Brown, Gordon D

2015-01-01

C-type lectin receptors (CLRs) comprise a large superfamily of proteins, which recognise a diverse range of ligands, and are defined by the presence of at least one C-type lectin-like domain (CTLD). Of particular interest are the single extracellular CTLD-containing receptors of the ‘Dectin-1’ and ‘Dectin-2’ clusters, which associate with signalling adaptors or possess integral intracellular signalling domains. These CLRs have traditionally been associated with the recognition of fungi, but recent discoveries have revealed diverse and unexpected functions. In this review, we describe their newly identified roles in anti-microbial host defence, homeostasis, autoimmunity, allergy and their functions in the recognition and response to dead and cancerous cells. PMID:25553393

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.

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

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.

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.

Foundations for a syntatic pattern recognition system for genomic DNA sequences

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

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Intercellular ice propagation: experimental evidence for ice growth through membrane pores.

PubMed Central

Acker, J P; Elliott, J A; McGann, L E

2001-01-01

Propagation of intracellular ice between cells significantly increases the prevalence of intracellular ice in confluent monolayers and tissues. It has been proposed that gap junctions facilitate ice propagation between cells. This study develops an equation for capillary freezing-point depression to determine the effect of temperature on the equilibrium radius of an ice crystal sufficiently small to grow through gap junctions. Convection cryomicroscopy and video image analysis were used to examine the incidence and pattern of intracellular ice formation (IIF) in the confluent monolayers of cell lines that do (MDCK) and do not (V-79W) form gap junctions. The effect of gap junctions on intracellular ice propagation was strongly temperature-dependent. For cells with gap junctions, IIF occurred in a directed wave-like pattern in 100% of the cells below -3 degrees C. At temperatures above -3 degrees C, there was a marked drop in the incidence of IIF, with isolated individual cells initially freezing randomly throughout the sample. This random pattern of IIF was also observed in the V-79W monolayers and in MDCK monolayers treated to prevent gap junction formation. The significant change in the low temperature behavior of confluent MDCK monolayers at -3 degrees C is likely the result of the inhibition of gap junction-facilitated ice propagation, and supports the theory that gap junctions facilitate ice nucleation between cells. PMID:11509353

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.

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)

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.

Heat Shock Proteins: A Review of the Molecular Chaperones for Plant Immunity.

PubMed

Park, Chang-Jin; Seo, Young-Su

2015-12-01

As sessile organisms, plants are exposed to persistently changing stresses and have to be able to interpret and respond to them. The stresses, drought, salinity, chemicals, cold and hot temperatures, and various pathogen attacks have interconnected effects on plants, resulting in the disruption of protein homeostasis. Maintenance of proteins in their functional native conformations and preventing aggregation of non-native proteins are important for cell survival under stress. Heat shock proteins (HSPs) functioning as molecular chaperones are the key components responsible for protein folding, assembly, translocation, and degradation under stress conditions and in many normal cellular processes. Plants respond to pathogen invasion using two different innate immune responses mediated by pattern recognition receptors (PRRs) or resistance (R) proteins. HSPs play an indispensable role as molecular chaperones in the quality control of plasma membrane-resident PRRs and intracellular R proteins against potential invaders. Here, we specifically discuss the functional involvement of cytosolic and endoplasmic reticulum (ER) HSPs/chaperones in plant immunity to obtain an integrated understanding of the immune responses in plant cells.

The genome of Aiptasia, a sea anemone model for coral symbiosis

PubMed Central

Baumgarten, Sebastian; Simakov, Oleg; Esherick, Lisl Y.; Liew, Yi Jin; Lehnert, Erik M.; Michell, Craig T.; Li, Yong; Hambleton, Elizabeth A.; Guse, Annika; Oates, Matt E.; Gough, Julian; Weis, Virginia M.; Aranda, Manuel; Pringle, John R.; Voolstra, Christian R.

2015-01-01

The most diverse marine ecosystems, coral reefs, depend upon a functional symbiosis between a cnidarian animal host (the coral) and intracellular photosynthetic dinoflagellate algae. The molecular and cellular mechanisms underlying this endosymbiosis are not well understood, in part because of the difficulties of experimental work with corals. The small sea anemone Aiptasia provides a tractable laboratory model for investigating these mechanisms. Here we report on the assembly and analysis of the Aiptasia genome, which will provide a foundation for future studies and has revealed several features that may be key to understanding the evolution and function of the endosymbiosis. These features include genomic rearrangements and taxonomically restricted genes that may be functionally related to the symbiosis, aspects of host dependence on alga-derived nutrients, a novel and expanded cnidarian-specific family of putative pattern-recognition receptors that might be involved in the animal–algal interactions, and extensive lineage-specific horizontal gene transfer. Extensive integration of genes of prokaryotic origin, including genes for antimicrobial peptides, presumably reflects an intimate association of the animal–algal pair also with its prokaryotic microbiome. PMID:26324906

Identification of proteins derived from Listeria monocytogenes inducing human dendritic cell maturation.

PubMed

Mirzaei, Reza; Saei, Azad; Torkashvand, Fatemeh; Azarian, Bahareh; Jalili, Ahmad; Noorbakhsh, Farshid; Vaziri, Behrouz; Hadjati, Jamshid

2016-08-01

Dendritic cells (DCs) are potent antigen-presenting cells (APCs) that can promote antitumor immunity when pulsed with tumor antigens and then matured by stimulatory agents. Despite apparent progress in DC-based cancer immunotherapy, some discrepancies were reported in generating potent DCs. Listeria monocytogenes as an intracellular microorganism is able to effectively activate DCs through engaging pattern-recognition receptors (PRRs). This study aimed to find the most potent components derived from L. monocytogenes inducing DC maturation. The preliminary results demonstrated that the ability of protein components is higher than DNA components to promote DC maturation and activation. Protein lysate fractionation demonstrated that fraction 2 HIC (obtained by hydrophobic interaction chromatography) was able to efficiently mature DCs. F2HIC-matured DCs are able to induce allogeneic CD8(+) T cells proliferation better than LPS-matured DCs and induce IFN-γ producing CD8(+) T cells. Mass spectrometry results showed that F2HIC contains 109 proteins. Based on the bioinformatics analysis for these 109 proteins, elongation factor Tu (EF-Tu) could be considered as a PRR ligand for stimulating DC maturation.

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.

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.

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.

OsCERK1-Mediated Chitin Perception and Immune Signaling Requires Receptor-like Cytoplasmic Kinase 185 to Activate an MAPK Cascade in Rice.

PubMed

Wang, Chao; Wang, Gang; Zhang, Chi; Zhu, Pinkuan; Dai, Huiling; Yu, Nan; He, Zuhua; Xu, Ling; Wang, Ertao

2017-04-03

Conserved pathogen-associated molecular patterns (PAMPs), such as chitin, are perceived by pattern recognition receptors (PRRs) located at the host cell surface and trigger rapid activation of mitogen-activated protein kinase (MAPK) cascades, which are required for plant resistance to pathogens. However, the direct links from PAMP perception to MAPK activation in plants remain largely unknown. In this study, we found that the PRR-associated receptor-like cytoplasmic kinase Oryza sativa RLCK185 transmits immune signaling from the PAMP receptor OsCERK1 to an MAPK signaling cascade through interaction with an MAPK kinase kinase, OsMAPKKKε, which is the initial kinase of the MAPK cascade. OsRLCK185 interacts with and phosphorylates the C-terminal regulatory domain of OsMAPKKKε. Coexpression of phosphomimetic OsRLCK185 and OsMAPKKKε activates MAPK3/6 phosphorylation in Nicotiana benthamiana leaves. Moreover, OsMAPKKKε interacts with and phosphorylates OsMKK4, a key MAPK kinase that transduces the chitin signal. Overexpression of OsMAPKKKε increases chitin-induced MAPK3/6 activation, whereas OsMAPKKKε knockdown compromises chitin-induced MAPK3/6 activation and resistance to rice blast fungus. Taken together, our results suggest the existence of a phospho-signaling pathway from cell surface chitin perception to intracellular activation of an MAPK cascade in rice. Copyright © 2017 The Author. Published by Elsevier Inc. All rights reserved.

An entomopathogenic bacterium, Xenorhabdus nematophila, suppresses expression of antimicrobial peptides controlled by Toll and Imd pathways by blocking eicosanoid biosynthesis.

PubMed

Hwang, Jihyun; Park, Youngjin; Kim, Yonggyun; Hwang, Jihyun; Lee, Daeweon

2013-07-01

Immune-associated genes of the beet armyworm, Spodoptera exigua, were predicted from 454 pyrosequencing transcripts of hemocytes collected from fifth instar larvae challenged with bacteria. Out of 22,551 contigs and singletons, 36% of the transcripts had at least one significant hit (E-value cutoff of 1e-20) and used to predict immune-associated genes implicated in pattern recognition, prophenoloxidase activation, intracellular signaling, and antimicrobial peptides (AMPs). Immune signaling and AMP genes were further confirmed in their expression patterns in response to different types of microbial challenge. To discriminate the AMP expression signaling between Toll and Imd pathways, RNA interference was applied to specifically knockdown each signal pathway; the separate silencing treatments resulted in differential suppression of AMP genes. An entomopathogenic bacterium, Xenorhabdus nematophila, suppressed expression of most AMP genes controlled by Toll and Imd pathways, while challenge with heat-killed X. nematophila induced expression of all AMPs in experimental larvae. Benzylideneacetone (BZA), a metabolite of X. nematophila, suppressed the AMP gene inductions when it was co-injected with the heat-killed X. nematophila. However, arachidonic acid, a catalytic product of PLA2 , significantly reversed the inhibitory effect of BZA on the AMP gene expression. This study suggests that X. nematophila suppresses AMP production controlled by Toll and Imd pathways by inhibiting eicosanoid biosynthesis in S. exigua. © 2013 Wiley Periodicals, Inc.

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.

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.

Mining sequential patterns for protein fold recognition.

PubMed

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

2008-02-01

Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. Protein classification in terms of fold recognition plays an important role in computational protein analysis, since it can contribute to the determination of the function of a protein whose structure is unknown. Specifically, one of the most efficient SPM algorithms, cSPADE, is employed for the analysis of protein sequence. A classifier uses the extracted sequential patterns to classify proteins in the appropriate fold category. For training and evaluating the proposed method we used the protein sequences from the Protein Data Bank and the annotation of the SCOP database. The method exhibited an overall accuracy of 25% in a classification problem with 36 candidate categories. The classification performance reaches up to 56% when the five most probable protein folds are considered.

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.

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.

Facial emotion recognition deficits in relatives of children with autism are not associated with 5HTTLPR.

PubMed

Neves, Maila de Castro Lourenço das; Tremeau, Fabien; Nicolato, Rodrigo; Lauar, Hélio; Romano-Silva, Marco Aurélio; Correa, Humberto

2011-09-01

A large body of evidence suggests that several aspects of face processing are impaired in autism and that this impairment might be hereditary. This study was aimed at assessing facial emotion recognition in parents of children with autism and its associations with a functional polymorphism of the serotonin transporter (5HTTLPR). We evaluated 40 parents of children with autism and 41 healthy controls. All participants were administered the Penn Emotion Recognition Test (ER40) and were genotyped for 5HTTLPR. Our study showed that parents of children with autism performed worse in the facial emotion recognition test than controls. Analyses of error patterns showed that parents of children with autism over-attributed neutral to emotional faces. We found evidence that 5HTTLPR polymorphism did not influence the performance in the Penn Emotion Recognition Test, but that it may determine different error patterns. Facial emotion recognition deficits are more common in first-degree relatives of autistic patients than in the general population, suggesting that facial emotion recognition is a candidate endophenotype for autism.

An investigation of potential applications of OP-SAPS: Operational Sampled Analog Processors

NASA Technical Reports Server (NTRS)

Parrish, E. A.; Mcvey, E. S.

1977-01-01

The application of OP-SAP's (operational sampled analog processors) in pattern recognition system is summarized. Areas investigated include: (1) human face recognition; (2) a high-speed programmable transversal filter system; (3) discrete word (speech) recognition; and (4) a resolution enhancement system.

Foundations for a syntatic pattern recognition system for genomic DNA sequences. [Annual] report, 1 December 1991--31 March 1993

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

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

NASA Technical Reports Server (NTRS)

Mellstrom, J. A.; Smyth, P.

1991-01-01

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

PubMed Central

Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A.; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing. PMID:24800230

Primary stability recognition of the newly designed cementless femoral stem using digital signal processing.

PubMed

Baharuddin, Mohd Yusof; Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

PubMed

Põder, Endel

2014-11-06

Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data. © 2014 ARVO.

Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

PubMed Central

Huo, Guanying

2017-01-01

As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

Cellular repressor of E1A-stimulated genes is a bona fide lysosomal protein which undergoes proteolytic maturation during its biosynthesis

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

Schaehs, Philipp; Weidinger, Petra; Probst, Olivia C.

2008-10-01

Cellular repressor of E1A-stimulated genes (CREG) has been reported to be a secretory glycoprotein implicated in cellular growth and differentiation. We now show that CREG is predominantly localized within intracellular compartments. Intracellular CREG was found to lack an N-terminal peptide present in the secreted form of the protein. In contrast to normal cells, CREG is largely secreted by fibroblasts missing both mannose 6-phosphate receptors. This is not observed in cells lacking only one of them. Mass spectrometric analysis of recombinant CREG revealed that the protein contains phosphorylated oligosaccharides at either of its two N-glycosylation sites. Cellular CREG was found tomore » cosediment with lysosomal markers upon subcellular fractionation by density-gradient centrifugation. In fibroblasts expressing a CREG-GFP fusion construct, the heterologous protein was detected in compartments containing lysosomal proteins. Immunolocalization of endogenous CREG confirmed that intracellular CREG is localized in lysosomes. Proteolytic processing of intracellular CREG involves the action of lysosomal cysteine proteinases. These results establish that CREG is a lysosomal protein that undergoes proteolytic maturation in the course of its biosynthesis, carries the mannose 6-phosphate recognition marker and depends on the interaction with mannose 6-phosphate receptors for efficient delivery to lysosomes.« less

Listeriolysin O Regulates the Expression of Optineurin, an Autophagy Adaptor That Inhibits the Growth of Listeria monocytogenes.

PubMed

Puri, Madhu; La Pietra, Luigi; Mraheil, Mobarak Abu; Lucas, Rudolf; Chakraborty, Trinad; Pillich, Helena

2017-09-05

Autophagy, a well-established defense mechanism, enables the elimination of intracellular pathogens including Listeria monocytogenes . Host cell recognition results in ubiquitination of L . monocytogenes and interaction with autophagy adaptors p62/SQSTM1 and NDP52, which target bacteria to autophagosomes by binding to microtubule-associated protein 1 light chain 3 (LC3). Although studies have indicated that L . monocytogenes induces autophagy, the significance of this process in the infectious cycle and the mechanisms involved remain poorly understood. Here, we examined the role of the autophagy adaptor optineurin (OPTN), the phosphorylation of which by the TANK binding kinase 1 (TBK1) enhances its affinity for LC3 and promotes autophagosomal degradation, during L . monocytogenes infection. In LC3- and OPTN-depleted host cells, intracellular replicating L . monocytogenes increased, an effect not seen with a mutant lacking the pore-forming toxin listeriolysin O (LLO). LLO induced the production of OPTN. In host cells expressing an inactive TBK1, bacterial replication was also inhibited. Our studies have uncovered an OPTN-dependent pathway in which L . monocytogenes uses LLO to restrict bacterial growth. Hence, manipulation of autophagy by L . monocytogenes , either through induction or evasion, represents a key event in its intracellular life style and could lead to either cytosolic growth or persistence in intracellular vacuolar structures.

Apparatus for detecting and recognizing analytes based on their crystallization patterns

DOEpatents

Morozov, Victor; Bailey, Charles L.; Vsevolodov, Nikolai N.; Elliott, Adam

2010-12-14

The invention contemplates apparatuses 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 patterns") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. Changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. Also, changes in the crystallization patterns, as well as the character of such changes, can be used as recognition elements in analysis of protein molecules.

Intraspecific Variation in Learning: Worker Wasps Are Less Able to Learn and Remember Individual Conspecific Faces than Queen Wasps.

PubMed

Tibbetts, Elizabeth A; Injaian, Allison; Sheehan, Michael J; Desjardins, Nicole

2018-05-01

Research on individual recognition often focuses on species-typical recognition abilities rather than assessing intraspecific variation in recognition. As individual recognition is cognitively costly, the capacity for recognition may vary within species. We test how individual face recognition differs between nest-founding queens (foundresses) and workers in Polistes fuscatus paper wasps. Individual recognition mediates dominance interactions among foundresses. Three previously published experiments have shown that foundresses (1) benefit by advertising their identity with distinctive facial patterns that facilitate recognition, (2) have robust memories of individuals, and (3) rapidly learn to distinguish between face images. Like foundresses, workers have variable facial patterns and are capable of individual recognition. However, worker dominance interactions are muted. Therefore, individual recognition may be less important for workers than for foundresses. We find that (1) workers with unique faces receive amounts of aggression similar to those of workers with common faces, indicating that wasps do not benefit from advertising their individual identity with a unique appearance; (2) workers lack robust memories for individuals, as they cannot remember unique conspecifics after a 6-day separation; and (3) workers learn to distinguish between facial images more slowly than foundresses during training. The recognition differences between foundresses and workers are notable because Polistes lack discrete castes; foundresses and workers are morphologically similar, and workers can take over as queens. Overall, social benefits and receiver capacity for individual recognition are surprisingly plastic.

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

NASA Astrophysics Data System (ADS)

Lhamon, Michael Earl

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

Variability in the impairment of recognition memory in patients with frontal lobe lesions.

PubMed

Bastin, Christine; Van der Linden, Martial; Lekeu, Françoise; Andrés, Pilar; Salmon, Eric

2006-10-01

Fourteen patients with frontal lobe lesions and 14 normal subjects were tested on a recognition memory task that required discriminating between target words, new words that are synonyms of the targets and unrelated distractors. A deficit was found in 12 of the patients. Moreover, three different patterns of recognition impairment were identified: (I) poor memory for targets, (II) normal hits but increased false recognitions for both types of distractors, (III) normal hit rates, but increased false recognitions for synonyms only. Differences in terms of location of the damage and behavioral characteristics between these subgroups were examined. An encoding deficit was proposed to explain the performance of patients in subgroup I. The behavioral patterns of the patients in subgroups II and III could be interpreted as deficient post-retrieval verification processes and an inability to recollect item-specific information, respectively.

Effects of Cooperative Group Work Activities on Pre-School Children's Pattern Recognition Skills

ERIC Educational Resources Information Center

Tarim, Kamuran

2015-01-01

The aim of this research is twofold; to investigate the effects of cooperative group-based work activities on children's pattern recognition skills in pre-school and to examine the teachers' opinions about the implementation process. In line with this objective, for the study, 57 children (25 girls and 32 boys) were chosen from two private schools…

VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Lue, Jaw-Chyng

2009-01-01

A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

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

NASA Astrophysics Data System (ADS)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

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

Training Spiking Neural Models Using Artificial Bee Colony

PubMed Central

Vazquez, Roberto A.; Garro, Beatriz A.

2015-01-01

Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

Multiclassifier information fusion methods for microarray pattern recognition

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Glina, Yan; Judson, Nicholas; Herzig-Marx, Rachel

2004-04-01

This paper addresses automatic recognition of microarray patterns, a capability that could have a major significance for medical diagnostics, enabling development of diagnostic tools for automatic discrimination of specific diseases. The paper presents multiclassifier information fusion methods for microarray pattern recognition. The input space partitioning approach based on fitness measures that constitute an a-priori gauging of classification efficacy for each subspace is investigated. Methods for generation of fitness measures, generation of input subspaces and their use in the multiclassifier fusion architecture are presented. In particular, two-level quantification of fitness that accounts for the quality of each subspace as well as the quality of individual neighborhoods within the subspace is described. Individual-subspace classifiers are Support Vector Machine based. The decision fusion stage fuses the information from mulitple SVMs along with the multi-level fitness information. Final decision fusion stage techniques, including weighted fusion as well as Dempster-Shafer theory based fusion are investigated. It should be noted that while the above methods are discussed in the context of microarray pattern recognition, they are applicable to a broader range of discrimination problems, in particular to problems involving a large number of information sources irreducible to a low-dimensional feature space.

Pattern Recognition Control Design

NASA Technical Reports Server (NTRS)

Gambone, Elisabeth A.

2018-01-01

Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

Conditional random fields for pattern recognition applied to structured data

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

Burr, Tom; Skurikhin, Alexei

In order to predict labels from an output domain, Y, pattern recognition is used to gather measurements from an input domain, X. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features betweenmore » parts of the model are often correlated. Thus, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. Our paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.« less

Recognition memory strength is predicted by pupillary responses at encoding while fixation patterns distinguish recollection from familiarity.

PubMed

Kafkas, Alexandros; Montaldi, Daniela

2011-10-01

Thirty-five healthy participants incidentally encoded a set of man-made and natural object pictures, while their pupil response and eye movements were recorded. At retrieval, studied and new stimuli were rated as novel, familiar (strong, moderate, or weak), or recollected. We found that both pupil response and fixation patterns at encoding predict later recognition memory strength. The extent of pupillary response accompanying incidental encoding was found to be predictive of subsequent memory. In addition, the number of fixations was also predictive of later recognition memory strength, suggesting that the accumulation of greater visual detail, even for single objects, is critical for the creation of a strong memory. Moreover, fixation patterns at encoding distinguished between recollection and familiarity at retrieval, with more dispersed fixations predicting familiarity and more clustered fixations predicting recollection. These data reveal close links between the autonomic control of pupil responses and eye movement patterns on the one hand and memory encoding on the other. Moreover, the data illustrate quantitative as well as qualitative differences in the incidental visual processing of stimuli, which are differentially predictive of the strength and the kind of memory experienced at recognition.

STATUS OF THE SYSTEM OF SIGNALING PATTERN RECOGNITION RECEPTORS OF MONOCYTES AND GRANULOCYTES IN COSMONAUTS' PERIPHERAL BLOOD BEFORE AND AFTER LONG-DURATION MISSIONS TO THE INTERNATIONAL SPACE STATION.

PubMed

Ponomarev, S A; Berendeeva, T A; Kalinin, S A; Muranova, A V

The system of signaling pattern recognition receptors was studied in 8 cosmonauts aged 35 to 56 years before and after (R+) long-duration missions to the International space station. Peripheral blood samples were analyzed for the content of monocytes and granulocytes that express the signaling pattern recognition Toll- like (TLR) receptors localized as on cell surface (TLR1, TLR2, TLR4, TLR5, TLR6), so inside cells (TLR3, TLR8, TLR9). In parallel, serum concentrations of TLR2 (HSP60) and TLR4 ligands (HSP70, HMGB1) were measured. The results of investigations showed growth of HSP60, HSP70 and HMGB1 concentrations on R+1. In the;majority of cosmonauts increases in endogenous ligands were followed by growth in the number of both monocytes and granulocytes that express TLR2 1 TLR4. This consistency gives ground to assume that changes in the system of signaling pattern recognition receptors can stem .from the predominantly endogenous ligands' response to the effects of long-duration space flight on human organism.

Conditional random fields for pattern recognition applied to structured data

DOE PAGES

Burr, Tom; Skurikhin, Alexei

2015-07-14

In order to predict labels from an output domain, Y, pattern recognition is used to gather measurements from an input domain, X. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features betweenmore » parts of the model are often correlated. Thus, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. Our paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.« less

Neonatal Recognition Processes and Attachment: The Masking Experiment.

ERIC Educational Resources Information Center

Cassel, Thomas Z. K.; Sander, Louis W.

This research project was designed to determine whether 1-week-old neonates would indicate biological recognition of their mothers. Biological recognition is defined as the particular configuration of sensory, kinesthetic, and motor cues and the temporal patterning of these cues which characterizes infants' exchange processes with their…

Elastic Face, An Anatomy-Based Biometrics Beyond Visible Cue

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

Tsap, L V; Zhang, Y; Kundu, S J

2004-03-29

This paper describes a face recognition method that is designed based on the consideration of anatomical and biomechanical characteristics of facial tissues. Elastic strain pattern inferred from face expression can reveal an individual's biometric signature associated with the underlying anatomical structure, and thus has the potential for face recognition. A method based on the continuum mechanics in finite element formulation is employed to compute the strain pattern. Experiments show very promising results. The proposed method is quite different from other face recognition methods and both its advantages and limitations, as well as future research for improvement are discussed.

Context-aware mobile health monitoring: evaluation of different pattern recognition methods for classification of physical activity.

PubMed

Jatobá, Luciana C; Grossmann, Ulrich; Kunze, Chistophe; Ottenbacher, Jörg; Stork, Wilhelm

2008-01-01

There are various applications of physical activity monitoring for medical purposes, such as therapeutic rehabilitation, fitness enhancement or the use of physical activity as context information for evaluation of other vital data. Physical activity can be estimated using acceleration sensor-systems fixed on a person's body. By means of pattern recognition methods, it is possible to identify with certain accuracy which movement is being performed. This work presents a comparison of different methods for recognition of daily-life activities, which will serve as basis for the development of an online activity monitoring system.

A new approach for cancelable iris recognition

NASA Astrophysics Data System (ADS)

Yang, Kai; Sui, Yan; Zhou, Zhi; Du, Yingzi; Zou, Xukai

2010-04-01

The iris is a stable and reliable biometric for positive human identification. However, the traditional iris recognition scheme raises several privacy concerns. One's iris pattern is permanently bound with him and cannot be changed. Hence, once it is stolen, this biometric is lost forever as well as all the applications where this biometric is used. Thus, new methods are desirable to secure the original pattern and ensure its revocability and alternatives when compromised. In this paper, we propose a novel scheme which incorporates iris features, non-invertible transformation and data encryption to achieve "cancelability" and at the same time increases iris recognition accuracy.

Recognition of building group patterns in topographic maps based on graph partitioning and random forest

NASA Astrophysics Data System (ADS)

He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

2018-02-01

Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence essential to a wide range of downstream applications such as map generalization. Most of the existing methods develop rigid rules based on the topographic relationships between building pairs to identify building group patterns and thus their applications are often limited. This study proposes a method to identify a variety of building group patterns that allow for map generalization. The method first identifies building group patterns from potential building clusters based on a machine-learning algorithm and further partitions the building clusters with no recognized patterns based on the graph partitioning method. The proposed method is applied to the datasets of three cities that are representative of the complex urban environment in Southern China. Assessment of the results based on the reference data suggests that the proposed method is able to recognize both regular (e.g., the collinear, curvilinear, and rectangular patterns) and irregular (e.g., the L-shaped, H-shaped, and high-density patterns) building group patterns well, given that the correctness values are consistently nearly 90% and the completeness values are all above 91% for three study areas. The proposed method shows promises in automated recognition of building group patterns that allows for map generalization.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

PubMed

Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

Neural network-based system for pattern recognition through a fiber optic bundle

NASA Astrophysics Data System (ADS)

Gamo-Aranda, Javier; Rodriguez-Horche, Paloma; Merchan-Palacios, Miguel; Rosales-Herrera, Pablo; Rodriguez, M.

2001-04-01

A neural network based system to identify images transmitted through a Coherent Fiber-optic Bundle (CFB) is presented. Patterns are generated in a computer, displayed on a Spatial Light Modulator, imaged onto the input face of the CFB, and recovered optically by a CCD sensor array for further processing. Input and output optical subsystems were designed and used to that end. The recognition step of the transmitted patterns is made by a powerful, widely-used, neural network simulator running on the control PC. A complete PC-based interface was developed to control the different tasks involved in the system. An optical analysis of the system capabilities was carried out prior to performing the recognition step. Several neural network topologies were tested, and the corresponding numerical results are also presented and discussed.

Intarsia-sensorized band and textrodes for real-time myoelectric pattern recognition.

PubMed

Brown, Shannon; Ortiz-Catalan, Max; Petersson, Joel; Rodby, Kristian; Seoane, Fernando

2016-08-01

Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation. Self-adhesive Ag/AgCl are the electrodes preferentially used to capture sEMG in short-term studies, however their long-term application is limited. In this study we designed and evaluated a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques and knitted textile electrodes. Real-time myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes. After a comprehending measurement and performance comparison of the sEMG recordings, no significant differences were found between the textile and the Ag-AgCl electrodes in SNR and prediction accuracy obtained from pattern recognition classifiers.

Pathogenic mechanisms of intracellular bacteria.

PubMed

Niller, Hans Helmut; Masa, Roland; Venkei, Annamária; Mészáros, Sándor; Minarovits, Janos

2017-06-01

We wished to overview recent data on a subset of epigenetic changes elicited by intracellular bacteria in human cells. Reprogramming the gene expression pattern of various host cells may facilitate bacterial growth, survival, and spread. DNA-(cytosine C5)-methyltransferases of Mycoplasma hyorhinis targeting cytosine-phosphate-guanine (CpG) dinucleotides and a Mycobacterium tuberculosis methyltransferase targeting non-CpG sites methylated the host cell DNA and altered the pattern of gene expression. Gene silencing by CpG methylation and histone deacetylation, mediated by cellular enzymes, also occurred in M. tuberculosis-infected macrophages. M. tuberculosis elicited cell type-specific epigenetic changes: it caused increased DNA methylation in macrophages, but induced demethylation, deposition of euchromatic histone marks and activation of immune-related genes in dendritic cells. A secreted transposase of Acinetobacter baumannii silenced a cellular gene, whereas Mycobacterium leprae altered the epigenotype, phenotype, and fate of infected Schwann cells. The 'keystone pathogen' oral bacterium Porphyromonas gingivalis induced local DNA methylation and increased the level of histone acetylation in host cells. These epigenetic changes at the biofilm-gingiva interface may contribute to the development of periodontitis. Epigenetic regulators produced by intracellular bacteria alter the epigenotype and gene expression pattern of host cells and play an important role in pathogenesis.

The globally disseminated M1T1 clone of Group A Streptococcus evades autophagy for intracellular replication

PubMed Central

Barnett, Timothy C.; Liebl, David; Seymour, Lisa M.; Gillen, Christine M.; Lim, Jin Yan; LaRock, Christopher N.; Davies, Mark R.; Schulz, Benjamin L.; Nizet, Victor; Teasdale, Rohan D.; Walker, Mark J.

2014-01-01

SUMMARY Autophagy is reported to be an important innate immune defence against the intracellular bacterial pathogen Group A Streptococcus (GAS). However, the GAS strains examined to-date belong to serotypes infrequently associated with human disease. We find that the globally disseminated serotype M1T1 clone of GAS can evade autophagy and replicate efficiently in the cytosol of infected cells. Cytosolic M1T1 GAS (strain 5448), but not M6 GAS (strain JRS4), avoids ubiquitylation and recognition by the host autophagy marker LC3 and ubiquitin-LC3 adaptor proteins NDP52, p62 and NBR1. Expression of SpeB, a streptococcal cysteine protease, is critical for this process, as an isogenic M1T1 ΔspeB mutant is targeted to autophagy and attenuated for intracellular replication. SpeB degrades p62, NDP52 and NBR1 in vitro and within the host cell cytosol. These results uncover a proteolytic mechanism utilized by GAS to escape the host autophagy pathway which may underpin the success of the M1T1 clone. PMID:24331465

Poly-adenine-mediated fluorescent spherical nucleic acid probes for live-cell imaging of endogenous tumor-related mRNA.

PubMed

Zhu, Dan; Zhao, Dongxia; Huang, Jiaxuan; Zhu, Yu; Chao, Jie; Su, Shao; Li, Jiang; Wang, Lihua; Shi, Jiye; Zuo, Xiaolei; Weng, Lixing; Li, Qian; Wang, Lianhui

2018-05-16

Identification of tumor-related mRNA in living cells hold great promise for early cancer diagnosis and pathological research. Herein, we present poly-adenine (polyA)-mediated fluorescent spherical nucleic acid (FSNA) probes for intracellular mRNA detection with regulable sensitivities by programmably adjusting the loading density of DNA on gold nano-interface. Gold nanoparticles (AuNPs) functionalized with polyA-tailed recognition sequences were hybridized to fluorescent "reporter" strands to fabricate fluorescence-quenched FSNA probes. While exposed to target gene, the "reporter" strands were released from FSNA through strand displacement and fluorescence was recovered. With polyA20 tail as the attaching block, the detection limit of FSNA probes was calculated to be 0.31 nM, which is ~55 fold lower than that of thiolated probes without surface density regulation. Quantitative intracellular mRNA detection and imaging could be achieved with polyA-mediated FSNA probes within 2 hours, indicating their application potential in rapid and sensitive intracellular target imaging. Copyright © 2018. Published by Elsevier Inc.

United States Homeland Security and National Biometric Identification

DTIC Science & Technology

2002-04-09

security number. Biometrics is the use of unique individual traits such as fingerprints, iris eye patterns, voice recognition, and facial recognition to...technology to control access onto their military bases using a Defense Manpower Management Command developed software application. FACIAL Facial recognition systems...installed facial recognition systems in conjunction with a series of 200 cameras to fight street crime and identify terrorists. The cameras, which are

Identification of exosite residues of factor Xa involved in recognition of PAR-2 on endothelial cells.

PubMed

Manithody, Chandrashekhara; Yang, Likui; Rezaie, Alireza R

2012-03-27

Recent results have indicated that factor Xa (FXa) cleaves protease-activated receptor 2 (PAR-2) to elicit protective intracellular signaling responses in endothelial cells. In this study, we investigated the molecular determinants of the specificity of FXa interaction with PAR-2 by monitoring the cleavage of PAR-2 by FXa in endothelial cells transiently transfected with a PAR-2 cleavage reporter construct in which the extracellular domain of the receptor was fused to cDNA encoding for alkaline phosphatase. Comparison of the cleavage efficiency of PAR-2 by a series of FXa mutants containing mutations in different surface loops indicated that the acidic residues of 39-loop (Glu-36, Glu-37, and Glu-39) and the basic residues of 60-loop (Lys-62 and Arg-63), 148-loop (Arg-143, Arg-150, and Arg-154), and 162-helix (Arg-165 and Lys-169) contribute to the specificity of receptor recognition by FXa on endothelial cells. This was evidenced by significantly reduced activity of mutants toward PAR-2 expressed on transfected cells. The extent of loss in the PAR-2 cleavage activity of FXa mutants correlated with the extent of loss in their PAR-2-dependent intracellular signaling activity. Further characterization of FXa mutants indicated that, with the exception of basic residues of 162-helix, which play a role in the recognition specificity of the prothrombinase complex, none of the surface loop residues under study makes a significant contribution to the activity of FXa in the prothrombinase complex. These results provide new insight into mechanisms through which FXa specifically interacts with its macromolecular substrates in the clotting and signaling pathways.

The Wireless Ubiquitous Surveillance Testbed

DTIC Science & Technology

2003-03-01

c. Eye Patterns.............................................................................17 d. Facial Recognition ..................................................................19...27). ...........................................98 Table F.4. Facial Recognition Products. (After: Polemi, p. 25 and BiometriTech, 15 May 2002...it applies to homeland security. C. RESEARCH TASKS The main goals of this thesis are to: • Set up the biometric sensors and facial recognition surveillance

33 CFR 106.220 - Security training for all other OCS facility personnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; and (e) Recognition of techniques used to circumvent security measures. (f) Familiarity with all relevant aspects of...

33 CFR 106.220 - Security training for all other OCS facility personnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; and (e) Recognition of techniques used to circumvent security measures. (f) Familiarity with all relevant aspects of...

Asymmetries in Early Word Recognition: The Case of Stops and Fricatives

ERIC Educational Resources Information Center

Altvater-Mackensen, Nicole; van der Feest, Suzanne V. H.; Fikkert, Paula

2014-01-01

Toddlers' discrimination of native phonemic contrasts is generally unproblematic. Yet using those native contrasts in word learning and word recognition can be more challenging. In this article, we investigate perceptual versus phonological explanations for asymmetrical patterns found in early word recognition. We systematically investigated the…

A Tail of Two Sites: A Bipartite Mechanism for Recognition of Notch Ligands by Mind Bomb E3 Ligases

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

McMillan, Brian J.; Schnute, Björn; Ohlenhard, Nadja

Mind bomb (Mib) proteins are large, multi-domain E3 ligases that promote ubiquitination of the cytoplasmic tails of Notch ligands. This ubiquitination step marks the ligand proteins for epsin-dependent endocytosis, which is critical for in vivo Notch receptor activation. Here we present crystal structures of the substrate recognition domains of Mib1, both in isolation and in complex with peptides derived from Notch ligands. The structures, in combination with biochemical, cellular, and in vivo assays, show that Mib1 contains two independent substrate recognition domains that engage two distinct epitopes from the cytoplasmic tail of the ligand Jagged1, one in the intracellular membranemore » proximal region and the other near the C terminus. Together, these studies provide insights into the mechanism of ubiquitin transfer by Mind bomb E3 ligases, illuminate a key event in ligand-induced activation of Notch receptors, and identify a potential target for therapeutic modulation of Notch signal transduction in disease.« less

A Tail of Two Sites: A Bipartite Mechanism for Recognition of Notch Ligands by Mind Bomb E3 Ligases

PubMed Central

McMillan, Brian J.; Schnute, Björn; Ohlenhard, Nadja; Zimmerman, Brandon; Miles, Laura; Beglova, Natalia; Klein, Thomas; Blacklow, Stephen C.

2015-01-01

Summary Mind bomb (Mib) proteins are large, multi-domain E3 ligases that promote ubiquitination of the cytoplasmic tails of Notch ligands. This ubiquitination step marks the ligand proteins for epsin-dependent endocytosis, which is critical for in vivo Notch receptor activation. We present here crystal structures of the substrate recognition domains of Mib1, both in isolation and in complex with peptides derived from Notch ligands. The structures, in combination with biochemical, cellular and in vivo assays, show that Mib1 contains two independent substrate recognition domains that engage two distinct epitopes from the cytoplasmic tail of the ligand Jagged1, one in the intracellular membrane proximal region and the other near the C-terminus. Together, these studies provide new insights into the mechanism of ubiquitin transfer by Mind bomb E3 ligases, illuminate a key event in ligand-induced activation of Notch receptors, and identify a potential new target for therapeutic modulation of Notch signal transduction in disease. PMID:25747658

How paramagnetic and diamagnetic LMOCs detect picric acid from surface water and the intracellular environment: a combined experimental and DFT-D3 study.

PubMed

Ghosh, Pritam; Banerjee, Priyabrata

2016-08-17

Diamagnetic and Paramagnetic Luminescent Metal Organic Complexes (LMOCs) have been reported for Explosive and Pollutant Nitro Aromatic (epNAC) recognition. The diamagnetic complex shows a highly intense AIE induced by NEt3H(+), which disappears after picric acid recognition and subsequently RET will quench the emission intensity. Radical stabilized paramagnetic LMOCs seem to be active but show lower sensing efficiency in comparison with diamagnetic LMOCs. Solution and solid state spectroscopy studies along with DFT-D3 have been executed to enlighten the host guest interaction. Limit of PA detection is ∼250 ppb with a binding constant of 1.2 × 10(5) M(-1). Time-stepping, i.e. intervening in the problem of picric acid recognition from surface water collected from several places of West Bengal, India, has been performed. Mutagenic picric acid has been successfully detected in an aqueous medium inside both prokaryotic and eukaryotic cells at a ppm level using fluorescence microscopy.

A Tail of Two Sites: A Bipartite Mechanism for Recognition of Notch Ligands by Mind Bomb E3 Ligases

DOE PAGES

McMillan, Brian J.; Schnute, Björn; Ohlenhard, Nadja; ...

2015-03-05

Mind bomb (Mib) proteins are large, multi-domain E3 ligases that promote ubiquitination of the cytoplasmic tails of Notch ligands. This ubiquitination step marks the ligand proteins for epsin-dependent endocytosis, which is critical for in vivo Notch receptor activation. Here we present crystal structures of the substrate recognition domains of Mib1, both in isolation and in complex with peptides derived from Notch ligands. The structures, in combination with biochemical, cellular, and in vivo assays, show that Mib1 contains two independent substrate recognition domains that engage two distinct epitopes from the cytoplasmic tail of the ligand Jagged1, one in the intracellular membranemore » proximal region and the other near the C terminus. Together, these studies provide insights into the mechanism of ubiquitin transfer by Mind bomb E3 ligases, illuminate a key event in ligand-induced activation of Notch receptors, and identify a potential target for therapeutic modulation of Notch signal transduction in disease.« less

Inconsistent emotion recognition deficits across stimulus modalities in Huntington׳s disease.

PubMed

Rees, Elin M; Farmer, Ruth; Cole, James H; Henley, Susie M D; Sprengelmeyer, Reiner; Frost, Chris; Scahill, Rachael I; Hobbs, Nicola Z; Tabrizi, Sarah J

2014-11-01

Recognition of negative emotions is impaired in Huntington׳s Disease (HD). It is unclear whether these emotion-specific problems are driven by dissociable cognitive deficits, emotion complexity, test cue difficulty, or visuoperceptual impairments. This study set out to further characterise emotion recognition in HD by comparing patterns of deficits across stimulus modalities; notably including for the first time in HD, the more ecologically and clinically relevant modality of film clips portraying dynamic facial expressions. Fifteen early HD and 17 control participants were tested on emotion recognition from static facial photographs, non-verbal vocal expressions and one second dynamic film clips, all depicting different emotions. Statistically significant evidence of impairment of anger, disgust and fear recognition was seen in HD participants compared with healthy controls across multiple stimulus modalities. The extent of the impairment, as measured by the difference in the number of errors made between HD participants and controls, differed according to the combination of emotion and modality (p=0.013, interaction test). The largest between-group difference was seen in the recognition of anger from film clips. Consistent with previous reports, anger, disgust and fear were the most poorly recognised emotions by the HD group. This impairment did not appear to be due to task demands or expression complexity as the pattern of between-group differences did not correspond to the pattern of errors made by either group; implicating emotion-specific cognitive processing pathology. There was however evidence that the extent of emotion recognition deficits significantly differed between stimulus modalities. The implications in terms of designing future tests of emotion recognition and care giving are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Development of Pattern Recognition Techniques for the Evaluation of Toxicant Impacts to Multispecies Systems

DTIC Science & Technology

1993-06-18

the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and clustering methods...rule rather than the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and...experiments using two microcosm protocols. We use nonmetric clustering, a multivariate pattern recognition technique developed by Matthews and Heame (1991

Pattern recognition for Space Applications Center director's discretionary fund

NASA Technical Reports Server (NTRS)

Singley, M. E.

1984-01-01

Results and conclusions are presented on the application of recent developments in pattern recognition to spacecraft star mapping systems. Sensor data for two representative starfields are processed by an adaptive shape-seeking version of the Fc-V algorithm with good results. Cluster validity measures are evaluated, but not found especially useful to this application. Recommendations are given two system configurations worthy of additional study,

Method of synthesized phase objects for pattern recognition with rotation invariance

NASA Astrophysics Data System (ADS)

Ostroukh, Alexander P.; Butok, Alexander M.; Shvets, Rostislav A.; Yezhov, Pavel V.; Kim, Jin-Tae; Kuzmenko, Alexander V.

2015-11-01

We present a development of the method of synthesized phase objects (SPO-method) [1] for the rotation-invariant pattern recognition. For the standard method of recognition and the SPO-method, the comparison of the parameters of correlation signals for a number of amplitude objects is executed at the realization of a rotation in an optical-digital correlator with the joint Fourier transformation. It is shown that not only the invariance relative to a rotation at a realization of the joint correlation for synthesized phase objects (SP-objects) but also the main advantage of the method of SP-objects over the reference one such as the unified δ-like recognition signal with the largest possible signal-to-noise ratio independent of the type of an object are attained.

Hypothesis on interactions of macromolecules based on molecular vibration patterns in cells and tissues.

PubMed

Jaross, Werner

2018-01-01

The molecular vibration patterns of structure-forming macromolecules in the living cell create very specific electromagnetic frequency patterns which might be used for information on spatial position in the three-dimensional structure as well as the chemical characteristics. Chemical change of a molecule results in a change of the vibration pattern and thus in a change of the emitted electromagnetic frequency pattern. These patterns have to be received by proteins responsible for the necessary interactions and functions. Proteins can function as resonators for frequencies in the range of 1013-1015 Hz. The individual frequency pattern is defined by the amino acid sequence and the polarity of every amino acid caused by their functional groups. If the arriving electromagnetic signal pattern and the emitted pattern of the absorbing protein are matched in relevant parts and in opposite phase, photon energy in the characteristic frequencies can be transferred resulting in a conformational change of that molecule and respectively in an increase of its specific activity. The electromagnetic radiation is very weak. The possibilities to overcome intracellular distances are shown. The motor-driven directed transport of macromolecules starts in the Golgi apparatus. The relevance of molecular interactions based on this signaling for the induction and navigation in the intracellular transport is discussed.

Effects of emotional and perceptual-motor stress on a voice recognition system's accuracy: An applied investigation

NASA Astrophysics Data System (ADS)

Poock, G. K.; Martin, B. J.

1984-02-01

This was an applied investigation examining the ability of a speech recognition system to recognize speakers' inputs when the speakers were under different stress levels. Subjects were asked to speak to a voice recognition system under three conditions: (1) normal office environment, (2) emotional stress, and (3) perceptual-motor stress. Results indicate a definite relationship between voice recognition system performance and the type of low stress reference patterns used to achieve recognition.

Brain angiogenesis inhibitor 1 (BAI1) is a pattern recognition receptor that mediates macrophage binding and engulfment of Gram-negative bacteria

PubMed Central

Das, Soumita; Owen, Katherine A.; Ly, Kim T.; Park, Daeho; Black, Steven G.; Wilson, Jeffrey M.; Sifri, Costi D.; Ravichandran, Kodi S.; Ernst, Peter B.; Casanova, James E.

2011-01-01

Bacterial recognition by host cells is essential for initiation of infection and the host response. Bacteria interact with host cells via multiple pattern recognition receptors that recognize microbial products or pathogen-associated molecular patterns. In response to this interaction, host cell signaling cascades are activated that lead to inflammatory responses and/or phagocytic clearance of attached bacteria. Brain angiogenesis inhibitor 1 (BAI1) is a receptor that recognizes apoptotic cells through its conserved type I thrombospondin repeats and triggers their engulfment through an ELMO1/Dock/Rac1 signaling module. Because thrombospondin repeats in other proteins have been shown to bind bacterial surface components, we hypothesized that BAI1 may also mediate the recognition and clearance of pathogenic bacteria. We found that preincubation of bacteria with recombinant soluble BAI1 ectodomain or knockdown of endogenous BAI1 in primary macrophages significantly reduced binding and internalization of the Gram-negative pathogen Salmonella typhimurium. Conversely, overexpression of BAI1 enhanced attachment and engulfment of Salmonella in macrophages and in heterologous nonphagocytic cells. Bacterial uptake is triggered by the BAI1-mediated activation of Rac through an ELMO/Dock-dependent mechanism, and inhibition of the BAI1/ELMO1 interaction prevents both Rac activation and bacterial uptake. Moreover, inhibition of ELMO1 or Rac function significantly impairs the proinflammatory response to infection. Finally, we show that BAI1 interacts with a variety of Gram-negative, but not Gram-positive, bacteria through recognition of their surface lipopolysaccharide. Together these findings identify BAI1 as a pattern recognition receptor that mediates nonopsonic phagocytosis of Gram-negative bacteria by macrophages and directly affects the host response to infection. PMID:21245295

Do subitizing deficits in developmental dyscalculia involve pattern recognition weakness?

PubMed

Ashkenazi, Sarit; Mark-Zigdon, Nitza; Henik, Avishai

2013-01-01

The abilities of children diagnosed with developmental dyscalculia (DD) were examined in two types of object enumeration: subitizing, and small estimation (5-9 dots). Subitizing is usually defined as a fast and accurate assessment of a number of small dots (range 1 to 4 dots), and estimation is an imprecise process to assess a large number of items (range 5 dots or more). Based on reaction time (RT) and accuracy analysis, our results indicated a deficit in the subitizing and small estimation range among DD participants in relation to controls. There are indications that subitizing is based on pattern recognition, thus presenting dots in a canonical shape in the estimation range should result in a subitizing-like pattern. In line with this theory, our control group presented a subitizing-like pattern in the small estimation range for canonically arranged dots, whereas the DD participants presented a deficit in the estimation of canonically arranged dots. The present finding indicates that pattern recognition difficulties may play a significant role in both subitizing and subitizing deficits among those with DD. © 2012 Blackwell Publishing Ltd.

Beyond sensory images: Object-based representation in the human ventral pathway

PubMed Central

Pietrini, Pietro; Furey, Maura L.; Ricciardi, Emiliano; Gobbini, M. Ida; Wu, W.-H. Carolyn; Cohen, Leonardo; Guazzelli, Mario; Haxby, James V.

2004-01-01

We investigated whether the topographically organized, category-related patterns of neural response in the ventral visual pathway are a representation of sensory images or a more abstract representation of object form that is not dependent on sensory modality. We used functional MRI to measure patterns of response evoked during visual and tactile recognition of faces and manmade objects in sighted subjects and during tactile recognition in blind subjects. Results showed that visual and tactile recognition evoked category-related patterns of response in a ventral extrastriate visual area in the inferior temporal gyrus that were correlated across modality for manmade objects. Blind subjects also demonstrated category-related patterns of response in this “visual” area, and in more ventral cortical regions in the fusiform gyrus, indicating that these patterns are not due to visual imagery and, furthermore, that visual experience is not necessary for category-related representations to develop in these cortices. These results demonstrate that the representation of objects in the ventral visual pathway is not simply a representation of visual images but, rather, is a representation of more abstract features of object form. PMID:15064396

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.

Reading recognition of pointer meter based on pattern recognition and dynamic three-points on a line

NASA Astrophysics Data System (ADS)

Zhang, Yongqiang; Ding, Mingli; Fu, Wuyifang; Li, Yongqiang

2017-03-01

Pointer meters are frequently applied to industrial production for they are directly readable. They should be calibrated regularly to ensure the precision of the readings. Currently the method of manual calibration is most frequently adopted to accomplish the verification of the pointer meter, and professional skills and subjective judgment may lead to big measurement errors and poor reliability and low efficiency, etc. In the past decades, with the development of computer technology, the skills of machine vision and digital image processing have been applied to recognize the reading of the dial instrument. In terms of the existing recognition methods, all the parameters of dial instruments are supposed to be the same, which is not the case in practice. In this work, recognition of pointer meter reading is regarded as an issue of pattern recognition. We obtain the features of a small area around the detected point, make those features as a pattern, divide those certified images based on Gradient Pyramid Algorithm, train a classifier with the support vector machine (SVM) and complete the pattern matching of the divided mages. Then we get the reading of the pointer meter precisely under the theory of dynamic three points make a line (DTPML), which eliminates the error caused by tiny differences of the panels. Eventually, the result of the experiment proves that the proposed method in this work is superior to state-of-the-art works.

Pattern recognition monitoring of PEM fuel cell

DOEpatents

Meltser, M.A.

1999-08-31

The CO-concentration in the H{sub 2} feed stream to a PEM fuel cell stack is monitored by measuring current and voltage behavior patterns from an auxiliary cell attached to the end of the stack. The auxiliary cell is connected to the same oxygen and hydrogen feed manifolds that supply the stack, and discharges through a constant load. Pattern recognition software compares the current and voltage patterns from the auxiliary cell to current and voltage signature determined from a reference cell similar to the auxiliary cell and operated under controlled conditions over a wide range of CO-concentrations in the H{sub 2} fuel stream. 4 figs.

Pattern recognition monitoring of PEM fuel cell

DOEpatents

Meltser, Mark Alexander

1999-01-01

The CO-concentration in the H.sub.2 feed stream to a PEM fuel cell stack is monitored by measuring current and voltage behavior patterns from an auxiliary cell attached to the end of the stack. The auxiliary cell is connected to the same oxygen and hydrogen feed manifolds that supply the stack, and discharges through a constant load. Pattern recognition software compares the current and voltage patterns from the auxiliary cell to current and voltage signature determined from a reference cell similar to the auxiliary cell and operated under controlled conditions over a wide range of CO-concentrations in the H.sub.2 fuel stream.

Symbol Recognition Using a Concept Lattice of Graphical Patterns

NASA Astrophysics Data System (ADS)

Rusiñol, Marçal; Bertet, Karell; Ogier, Jean-Marc; Lladós, Josep

In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.

Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection

PubMed Central

Gottschlich, Carsten

2016-01-01

We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification. PMID:26844544

An RLP23-SOBIR1-BAK1 complex mediates NLP-triggered immunity.

PubMed

Albert, Isabell; Böhm, Hannah; Albert, Markus; Feiler, Christina E; Imkampe, Julia; Wallmeroth, Niklas; Brancato, Caterina; Raaymakers, Tom M; Oome, Stan; Zhang, Heqiao; Krol, Elzbieta; Grefen, Christopher; Gust, Andrea A; Chai, Jijie; Hedrich, Rainer; Van den Ackerveken, Guido; Nürnberger, Thorsten

2015-10-05

Plants and animals employ innate immune systems to cope with microbial infection. Pattern-triggered immunity relies on the recognition of microbe-derived patterns by pattern recognition receptors (PRRs). Necrosis and ethylene-inducing peptide 1-like proteins (NLPs) constitute plant immunogenic patterns that are unique, as these proteins are produced by multiple prokaryotic (bacterial) and eukaryotic (fungal, oomycete) species. Here we show that the leucine-rich repeat receptor protein (LRR-RP) RLP23 binds in vivo to a conserved 20-amino-acid fragment found in most NLPs (nlp20), thereby mediating immune activation in Arabidopsis thaliana. RLP23 forms a constitutive, ligand-independent complex with the LRR receptor kinase (LRR-RK) SOBIR1 (Suppressor of Brassinosteroid insensitive 1 (BRI1)-associated kinase (BAK1)-interacting receptor kinase 1), and recruits a second LRR-RK, BAK1, into a tripartite complex upon ligand binding. Stable, ectopic expression of RLP23 in potato (Solanum tuberosum) confers nlp20 pattern recognition and enhanced immunity to destructive oomycete and fungal plant pathogens, such as Phytophthora infestans and Sclerotinia sclerotiorum. PRRs that recognize widespread microbial patterns might be particularly suited for engineering immunity in crop plants.

Model driven mobile care for patients with type 1 diabetes.

PubMed

Skrøvseth, Stein Olav; Arsand, Eirik; Godtliebsen, Fred; Joakimsen, Ragnar M

2012-01-01

We gathered a data set from 30 patients with type 1 diabetes by giving the patients a mobile phone application, where they recorded blood glucose measurements, insulin injections, meals, and physical activity. Using these data as a learning data set, we describe a new approach of building a mobile feedback system for these patients based on periodicities, pattern recognition, and scale-space trends. Most patients have important patterns for periodicities and trends, though better resolution of input variables is needed to provide useful feedback using pattern recognition.

Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition.

PubMed

Juang, Chia-Feng; Chiou, Chyi-Tian; Lai, Chun-Lung

2007-05-01

This paper proposes noisy speech recognition using hierarchical singleton-type recurrent neural fuzzy networks (HSRNFNs). The proposed HSRNFN is a hierarchical connection of two singleton-type recurrent neural fuzzy networks (SRNFNs), where one is used for noise filtering and the other for recognition. The SRNFN is constructed by recurrent fuzzy if-then rules with fuzzy singletons in the consequences, and their recurrent properties make them suitable for processing speech patterns with temporal characteristics. In n words recognition, n SRNFNs are created for modeling n words, where each SRNFN receives the current frame feature and predicts the next one of its modeling word. The prediction error of each SRNFN is used as recognition criterion. In filtering, one SRNFN is created, and each SRNFN recognizer is connected to the same SRNFN filter, which filters noisy speech patterns in the feature domain before feeding them to the SRNFN recognizer. Experiments with Mandarin word recognition under different types of noise are performed. Other recognizers, including multilayer perceptron (MLP), time-delay neural networks (TDNNs), and hidden Markov models (HMMs), are also tested and compared. These experiments and comparisons demonstrate good results with HSRNFN for noisy speech recognition tasks.

The effect of inversion on face recognition in adults with autism spectrum disorder.

PubMed

Hedley, Darren; Brewer, Neil; Young, Robyn

2015-05-01

Face identity recognition has widely been shown to be impaired in individuals with autism spectrum disorders (ASD). In this study we examined the influence of inversion on face recognition in 26 adults with ASD and 33 age and IQ matched controls. Participants completed a recognition test comprising upright and inverted faces. Participants with ASD performed worse than controls on the recognition task but did not show an advantage for inverted face recognition. Both groups directed more visual attention to the eye than the mouth region and gaze patterns were not found to be associated with recognition performance. These results provide evidence of a normal effect of inversion on face recognition in adults with ASD.

Recognition without Awareness: Encoding and Retrieval Factors

ERIC Educational Resources Information Center

Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

2015-01-01

The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

Determination of polychlorinated biphenyl levels in the serum of residents and in the homogenates of seafood from the New Bedford, Massachusetts Area: A comparison of exposure sources through pattern recognition techniques

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

Burse, V.W.; Groce, D.F.; Caudill, S.P.

1994-01-01

Gas chromatographic patterns of polychlorinated biophenyls (PCBs) found in the serum of New Bedford, MA residents with high serum PCBs were compared to patterns found in lobsters and bluefish taken from local waters, and goats fed selected technical Aroclors (e.g., Aroclors 1016, 1242, 1254, or 1260) using Jaccard measures of similarity and Principal Component Analysis. Pattern in humans were silimar to patterns in lobsters and both were more similar to those in the goat fed Aroclor 1254 as demonstrated by both pattern recognition techniques. However, patterns observed in humans, lobsters and bluefish all exhibited some presence of PCBs more characteristicmore » of Aroclors 1016 and/or 1242 or 1260.« less

Parallel and orthogonal stimulus in ultradiluted neural networks

NASA Astrophysics Data System (ADS)

Sobral, G. A., Jr.; Vieira, V. M.; Lyra, M. L.; da Silva, C. R.

2006-10-01

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonal to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0 .

Multi-texture local ternary pattern for face recognition

NASA Astrophysics Data System (ADS)

Essa, Almabrok; Asari, Vijayan

2017-05-01

In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

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

Sobral, G. A. Jr.; Vieira, V. M.; Lyra, M. L.

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonalmore » to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0.« less

Artificial Immune System for Recognizing Patterns

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2005-01-01

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Collocation and Pattern Recognition Effects on System Failure Remediation

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Press, Hayes N.

2007-01-01

Previous research found that operators prefer to have status, alerts, and controls located on the same screen. Unfortunately, that research was done with displays that were not designed specifically for collocation. In this experiment, twelve subjects evaluated two displays specifically designed for collocating system information against a baseline that consisted of dial status displays, a separate alert area, and a controls panel. These displays differed in the amount of collocation, pattern matching, and parameter movement compared to display size. During the data runs, subjects kept a randomly moving target centered on a display using a left-handed joystick and they scanned system displays to find a problem in order to correct it using the provided checklist. Results indicate that large parameter movement aided detection and then pattern recognition is needed for diagnosis but the collocated displays centralized all the information subjects needed, which reduced workload. Therefore, the collocated display with large parameter movement may be an acceptable display after familiarization because of the possible pattern recognition developed with training and its use.

Problems Associated with Statistical Pattern Recognition of Acoustic Emission Signals in a Compact Tension Fatigue Specimen

NASA Technical Reports Server (NTRS)

Hinton, Yolanda L.

1999-01-01

Acoustic emission (AE) data were acquired during fatigue testing of an aluminum 2024-T4 compact tension specimen using a commercially available AE system. AE signals from crack extension were identified and separated from noise spikes, signals that reflected from the specimen edges, and signals that saturated the instrumentation. A commercially available software package was used to train a statistical pattern recognition system to classify the signals. The software trained a network to recognize signals with a 91-percent accuracy when compared with the researcher's interpretation of the data. Reasons for the discrepancies are examined and it is postulated that additional preprocessing of the AE data to focus on the extensional wave mode and eliminate other effects before training the pattern recognition system will result in increased accuracy.

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

PubMed Central

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-01-01

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

PubMed

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-07-07

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

33 CFR 104.225 - Security training for all other vessel personnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (MARSEC) Levels, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

33 CFR 104.225 - Security training for all other vessel personnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (MARSEC) Levels, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words.

PubMed

Gordon-Salant, Sandra; Yeni-Komshian, Grace H; Fitzgibbons, Peter J; Cohen, Julie I

2015-02-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech.

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words

PubMed Central

Gordon-Salant, Sandra; Yeni-Komshian, Grace H.; Fitzgibbons, Peter J.; Cohen, Julie I.

2015-01-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech. PMID:25698021

Ultrafast learning in a hard-limited neural network pattern recognizer

NASA Astrophysics Data System (ADS)

Hu, Chia-Lun J.

1996-03-01

As we published in the last five years, the supervised learning in a hard-limited perceptron system can be accomplished in a noniterative manner if the input-output mapping to be learned satisfies a certain positive-linear-independency (or PLI) condition. When this condition is satisfied (for most practical pattern recognition applications, this condition should be satisfied,) the connection matrix required to meet this mapping can be obtained noniteratively in one step. Generally, there exist infinitively many solutions for the connection matrix when the PLI condition is satisfied. We can then select an optimum solution such that the recognition of any untrained patterns will become optimally robust in the recognition mode. The learning speed is very fast and close to real-time because the learning process is noniterative and one-step. This paper reports the theoretical analysis and the design of a practical charter recognition system for recognizing hand-written alphabets. The experimental result is recorded in real-time on an unedited video tape for demonstration purposes. It is seen from this real-time movie that the recognition of the untrained hand-written alphabets is invariant to size, location, orientation, and writing sequence, even the training is done with standard size, standard orientation, central location and standard writing sequence.

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Image processing and recognition for biological images

PubMed Central

Uchida, Seiichi

2013-01-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. PMID:23560739

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

PubMed Central

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition.

PubMed

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-06-13

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle).

Consonant-recognition patterns and self-assessment of hearing handicap.

PubMed

Hustedde, C G; Wiley, T L

1991-12-01

Two companion experiments were conducted with normal-hearing subjects and subjects with high-frequency, sensorineural hearing loss. In Experiment 1, the validity of a self-assessment device of hearing handicap was evaluated in two groups of hearing-impaired listeners with significantly different consonant-recognition ability. Data for the Hearing Performance Inventory--Revised (Lamb, Owens, & Schubert, 1983) did not reveal differences in self-perceived handicap for the two groups of hearing-impaired listeners; it was sensitive to perceived differences in hearing abilities for listeners who did and did not have a hearing loss. Experiment 2 was aimed at evaluation of consonant error patterns that accounted for observed group differences in consonant-recognition ability. Error patterns on the Nonsense-Syllable Test (NST) across the two subject groups differed in both degree and type of error. Listeners in the group with poorer NST performance always demonstrated greater difficulty with selected low-frequency and high-frequency syllables than did listeners in the group with better NST performance. Overall, the NST was sensitive to differences in consonant-recognition ability for normal-hearing and hearing-impaired listeners.

Syntactic/semantic techniques for feature description and character recognition

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

Gonzalez, R.C.

1983-01-01

The Pattern Analysis Branch, Mapping, Charting and Geodesy (MC/G) Division, of the Naval Ocean Research and Development Activity (NORDA) has been involved over the past several years in the development of algorithms and techniques for computer recognition of free-form handprinted symbols as they appear on the Defense Mapping Agency (DMA) maps and charts. NORDA has made significant contributions to the automation of MC/G through advancing the state of the art in such information extraction techniques. In particular, new concepts in character (symbol) skeletonization, rugged feature measurements, and expert system-oriented decision logic have allowed the development of a very high performancemore » Handprinted Symbol Recognition (HSR) system for identifying depth soundings from naval smooth sheets (accuracies greater than 99.5%). The study reported in this technical note is part of NORDA's continuing research and development in pattern and shape analysis as it applies to Navy and DMA ocean/environment problems. The issue addressed in this technical note deals with emerging areas of syntactic and semantic techniques in pattern recognition as they might apply to the free-form symbol problem.« less

Higher-order neural network software for distortion invariant object recognition

NASA Technical Reports Server (NTRS)

Reid, Max B.; Spirkovska, Lilly

1991-01-01

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Star Pattern Recognition and Spacecraft Attitude Determination.

DTIC Science & Technology

1978-10-01

Mr. Lawrence D. Ziems, Computer Programuer Prepared For: ,ti U.S. Army Engineer Topographic Laboratories Fort Belvoir, Virginia 22060 Contract No...CONTENTS PORIVAD i SIMARY iii 1.0 Introduction and System Overviev 1 2.0 Reference Frames Geometry and Kinematics 9 3.0 Star Pattern Recognition/Attitude...Laboratories (USAETL). The authors appreciate the capable guidance of Mr. L. A. Gambino, Director of the Computer Science Laboratory (USAETL), who served as

Linear Programming and Its Application to Pattern Recognition Problems

NASA Technical Reports Server (NTRS)

Omalley, M. J.

1973-01-01

Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.

Learning and Inductive Inference

DTIC Science & Technology

1982-07-01

a set of graph grammars to describe visual scenes . Other researchers have applied graph grammars to the pattern recognition of handwritten characters...345 1. Issues / 345 2. Mostows’ operationalizer / 350 0. Learning from ezamples / 360 1. Issues / 3t60 2. Learning in control and pattern recognition ...art.icleis on rote learntinig and ailvice- tAik g. K(ennieth Clarkson contributed Ltte article on grmvit atical inference, anid Geoff’ lroiney wrote

DYNAMIC PATTERN RECOGNITION BY MEANS OF THRESHOLD NETS,

DTIC Science & Technology

A method is expounded for the recognition of visual patterns. A circuit diagram of a device is described which is based on a multilayer threshold ...structure synthesized in accordance with the proposed method. Coded signals received each time an image is displayed are transmitted to the threshold ...circuit which distinguishes the signs, and from there to the layers of threshold resolving elements. The image at each layer is made to correspond

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

PubMed Central

Yoshioka, Nayuta; Zangerl, Barbara; Nivison-Smith, Lisa; Khuu, Sieu K.; Jones, Bryan W.; Pfeiffer, Rebecca L.; Marc, Robert E.; Kalloniatis, Michael

2017-01-01

Purpose To characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease. Methods Single eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort. Results Pattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm). Conclusions Pattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease. PMID:28632847

Local Context Finder (LCF) reveals multidimensional relationships among mRNA expression profiles of Arabidopsis responding to pathogen infection

PubMed Central

Katagiri, Fumiaki; Glazebrook, Jane

2003-01-01

A major task in computational analysis of mRNA expression profiles is definition of relationships among profiles on the basis of similarities among them. This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. Some drawbacks of commonly used pattern recognition algorithms stem from their use of a globally linear space and/or limited degrees of freedom. A pattern recognition method called Local Context Finder (LCF) is described here. LCF uses nonlinear dimensionality reduction for pattern recognition. Then it builds a network of profiles based on the nonlinear dimensionality reduction results. LCF was used to analyze mRNA expression profiles of the plant host Arabidopsis interacting with the bacterial pathogen Pseudomonas syringae. In one case, LCF revealed two dimensions essential to explain the effects of the NahG transgene and the ndr1 mutation on resistant and susceptible responses. In another case, plant mutants deficient in responses to pathogen infection were classified on the basis of LCF analysis of their profiles. The classification by LCF was consistent with the results of biological characterization of the mutants. Thus, LCF is a powerful method for extracting information from expression profile data. PMID:12960373

VIPRAM_L1CMS: a 2-Tier 3D Architecture for Pattern Recognition for Track Finding

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

Hoff, J. R.; Joshi, Joshi,S.; Liu, Liu,

In HEP tracking trigger applications, flagging an individual detector hit is not important. Rather, the path of a charged particle through many detector layers is what must be found. Moreover, given the increased luminosity projected for future LHC experiments, this type of track finding will be required within the Level 1 Trigger system. This means that future LHC experiments require not just a chip capable of high-speed track finding but also one with a high-speed readout architecture. VIPRAM_L1CMS is 2-Tier Vertically Integrated chip designed to fulfill these requirements. It is a complete pipelined Pattern Recognition Associative Memory (PRAM) architecture includingmore » pattern recognition, result sparsification, and readout for Level 1 trigger applications in CMS with 15-bit wide detector addresses and eight detector layers included in the track finding. Pattern recognition is based on classic Content Addressable Memories with a Current Race Scheme to reduce timing complexity and a 4-bit Selective Precharge to minimize power consumption. VIPRAM_L1CMS uses a pipelined set of priority-encoded binary readout structures to sparsify and readout active road flags at frequencies of at least 100MHz. VIPRAM_L1CMS is designed to work directly with the Pulsar2b Architecture.« less

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control.

PubMed

Adewuyi, Adenike A; Hargrove, Levi J; Kuiken, Todd A

2016-04-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control

PubMed Central

Adewuyi, Adenike A.; Hargrove, Levi J.; Kuiken, Todd A.

2015-01-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for partial-hand applications. PMID:25955989

Pattern Recognition Control Design

NASA Technical Reports Server (NTRS)

Gambone, Elisabeth

2016-01-01

Spacecraft control algorithms must know the expected spacecraft response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach can be used to investigate the relationship between the control effector commands and the spacecraft responses. Instead of supplying the approximated vehicle properties and the effector performance characteristics, a database of information relating the effector commands and the desired vehicle response can be used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands can be analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center (Ref. 1) to analyze flight dynamics Monte Carlo data sets through pattern recognition methods can be used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands is established, it can be used in place of traditional control laws and gains set. This pattern recognition approach can be compared with traditional control algorithms to determine the potential benefits and uses.

Within-individual variation in bullfrog vocalizations: implications for a vocally mediated social recognition system.

PubMed

Bee, Mark A

2004-12-01

Acoustic signals provide a basis for social recognition in a wide range of animals. Few studies, however, have attempted to relate the patterns of individual variation in signals to behavioral discrimination thresholds used by receivers to discriminate among individuals. North American bullfrogs (Rana catesbeiana) discriminate among familiar and unfamiliar individuals based on individual variation in advertisement calls. The sources, patterns, and magnitudes of variation in eight acoustic properties of multiple-note advertisement calls were examined to understand how patterns of within-individual variation might either constrain, or provide additional cues for, vocal recognition. Six of eight acoustic properties exhibited significant note-to-note variation within multiple-note calls. Despite this source of within-individual variation, all call properties varied significantly among individuals, and multivariate analyses indicated that call notes were individually distinct. Fine-temporal and spectral call properties exhibited less within-individual variation compared to gross-temporal properties and contributed most toward statistically distinguishing among individuals. Among-individual differences in the patterns of within-individual variation in some properties suggest that within-individual variation could also function as a recognition cue. The distributions of among-individual and within-individual differences were used to generate hypotheses about the expected behavioral discrimination thresholds of receivers.

A Fuzzy Logic Prompting Mechanism Based on Pattern Recognition and Accumulated Activity Effective Index Using a Smartphone Embedded Sensor.

PubMed

Liu, Chung-Tse; Chan, Chia-Tai

2016-08-19

Sufficient physical activity can reduce many adverse conditions and contribute to a healthy life. Nevertheless, inactivity is prevalent on an international scale. Improving physical activity is an essential concern for public health. Reminders that help people change their health behaviors are widely applied in health care services. However, timed-based reminders deliver periodic prompts suffer from flexibility and dependency issues which may decrease prompt effectiveness. We propose a fuzzy logic prompting mechanism, Accumulated Activity Effective Index Reminder (AAEIReminder), based on pattern recognition and activity effective analysis to manage physical activity. AAEIReminder recognizes activity levels using a smartphone-embedded sensor for pattern recognition and analyzing the amount of physical activity in activity effective analysis. AAEIReminder can infer activity situations such as the amount of physical activity and days spent exercising through fuzzy logic, and decides whether a prompt should be delivered to a user. This prompting system was implemented in smartphones and was used in a short-term real-world trial by seventeenth participants for validation. The results demonstrated that the AAEIReminder is feasible. The fuzzy logic prompting mechanism can deliver prompts automatically based on pattern recognition and activity effective analysis. AAEIReminder provides flexibility which may increase the prompts' efficiency.

Benefits of using culturally unfamiliar stimuli in ambiguous emotion identification: A cross-cultural study.

PubMed

Koelkebeck, Katja; Kohl, Waldemar; Luettgenau, Julia; Triantafillou, Susanna; Ohrmann, Patricia; Satoh, Shinji; Minoshita, Seiko

2015-07-30

A novel emotion recognition task that employs photos of a Japanese mask representing a highly ambiguous stimulus was evaluated. As non-Asians perceive and/or label emotions differently from Asians, we aimed to identify patterns of task-performance in non-Asian healthy volunteers with a view to future patient studies. The Noh mask test was presented to 42 adult German participants. Reaction times and emotion attribution patterns were recorded. To control for emotion identification abilities, a standard emotion recognition task was used among others. Questionnaires assessed personality traits. Finally, results were compared to age- and gender-matched Japanese volunteers. Compared to other tasks, German participants displayed slowest reaction times on the Noh mask test, indicating higher demands of ambiguous emotion recognition. They assigned more positive emotions to the mask than Japanese volunteers, demonstrating culture-dependent emotion identification patterns. As alexithymic and anxious traits were associated with slower reaction times, personality dimensions impacted on performance, as well. We showed an advantage of ambiguous over conventional emotion recognition tasks. Moreover, we determined emotion identification patterns in Western individuals impacted by personality dimensions, suggesting performance differences in clinical samples. Due to its properties, the Noh mask test represents a promising tool in the differential diagnosis of psychiatric disorders, e.g. schizophrenia. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

33 CFR 105.215 - Security training for all other facility personnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... apply to them, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

33 CFR 105.215 - Security training for all other facility personnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... apply to them, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

The software peculiarities of pattern recognition in track detectors

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

Starkov, N.

The different kinds of nuclear track recognition algorithms are represented. Several complicated samples of use them in physical experiments are considered. The some processing methods of complicated images are described.

Intracellular calcium dynamics permit a Purkinje neuron model to perform toggle and gain computations upon its inputs

PubMed Central

Forrest, Michael D.

2014-01-01

Without synaptic input, Purkinje neurons can spontaneously fire in a repeating trimodal pattern that consists of tonic spiking, bursting and quiescence. Climbing fiber input (CF) switches Purkinje neurons out of the trimodal firing pattern and toggles them between a tonic firing and a quiescent state, while setting the gain of their response to Parallel Fiber (PF) input. The basis to this transition is unclear. We investigate it using a biophysical Purkinje cell model under conditions of CF and PF input. The model can replicate these toggle and gain functions, dependent upon a novel account of intracellular calcium dynamics that we hypothesize to be applicable in real Purkinje cells. PMID:25191262

A multimodal approach to emotion recognition ability in autism spectrum disorders.

PubMed

Jones, Catherine R G; Pickles, Andrew; Falcaro, Milena; Marsden, Anita J S; Happé, Francesca; Scott, Sophie K; Sauter, Disa; Tregay, Jenifer; Phillips, Rebecca J; Baird, Gillian; Simonoff, Emily; Charman, Tony

2011-03-01

Autism spectrum disorders (ASD) are characterised by social and communication difficulties in day-to-day life, including problems in recognising emotions. However, experimental investigations of emotion recognition ability in ASD have been equivocal, hampered by small sample sizes, narrow IQ range and over-focus on the visual modality. We tested 99 adolescents (mean age 15;6 years, mean IQ 85) with an ASD and 57 adolescents without an ASD (mean age 15;6 years, mean IQ 88) on a facial emotion recognition task and two vocal emotion recognition tasks (one verbal; one non-verbal). Recognition of happiness, sadness, fear, anger, surprise and disgust were tested. Using structural equation modelling, we conceptualised emotion recognition ability as a multimodal construct, measured by the three tasks. We examined how the mean levels of recognition of the six emotions differed by group (ASD vs. non-ASD) and IQ (≥ 80 vs. < 80). We found no evidence of a fundamental emotion recognition deficit in the ASD group and analysis of error patterns suggested that the ASD group were vulnerable to the same pattern of confusions between emotions as the non-ASD group. However, recognition ability was significantly impaired in the ASD group for surprise. IQ had a strong and significant effect on performance for the recognition of all six emotions, with higher IQ adolescents outperforming lower IQ adolescents. The findings do not suggest a fundamental difficulty with the recognition of basic emotions in adolescents with ASD. © 2010 The Authors. Journal of Child Psychology and Psychiatry © 2010 Association for Child and Adolescent Mental Health.

The Boundaries of Hemispheric Processing in Visual Pattern Recognition

DTIC Science & Technology

1989-11-01

Allen, M. W. (1968). Impairment in facial recognition in patients cerebral disease. Cortex, 4, 344-358. Bogen, J. E. (1969). The other side of the brain...effects on a facial recognition task in normal subjects. Cortex, 9, 246-258. tliscock, M. (1988). Behavioral asymmetries in normal children. In D. L... facial recognition . Neuropsychologia, 22, 471-477. Ross-Kossak, P., & Turkewitz, G. (1986). A micro and macro developmental view of the nature of changes

Control of antiviral immunity by pattern recognition and the microbiome

PubMed Central

Pang, Iris K.; Iwasaki, Akiko

2013-01-01

Summary Human skin and mucosal surfaces are in constant contact with resident and invasive microbes. Recognition of microbial products by receptors of the innate immune system triggers rapid innate defense and transduces signals necessary for initiating and maintaining the adaptive immune responses. Microbial sensing by innate pattern recognition receptors is not restricted to pathogens. Rather, proper development, function, and maintenance of innate and adaptive immunity rely on continuous recognition of products derived from the microorganisms indigenous to the internal and external surfaces of mammalian host. Tonic immune activation by the resident microbiota governs host susceptibility to intestinal and extra-intestinal infections including those caused by viruses. This review highlights recent developments in innate viral recognition leading to adaptive immunity, and discusses potential link between viruses, microbiota and the host immune system. Further, we discuss the possible roles of microbiome in chronic viral infection and pathogenesis of autoimmune disease, and speculate on the benefit for probiotic therapies against such diseases. PMID:22168422

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.

Gesture recognition for smart home applications using portable radar sensors.

PubMed

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

2014-01-01

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

Accurate, fast, and secure biometric fingerprint recognition system utilizing sensor fusion of fingerprint patterns

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Alsharif, Salim; Jagapathi, Rajendarreddy

2011-04-01

Fingerprint recognition is one of the first techniques used for automatically identifying people and today it is still one of the most popular and effective biometric techniques. With this increase in fingerprint biometric uses, issues related to accuracy, security and processing time are major challenges facing the fingerprint recognition systems. Previous work has shown that polarization enhancementencoding of fingerprint patterns increase the accuracy and security of fingerprint systems without burdening the processing time. This is mainly due to the fact that polarization enhancementencoding is inherently a hardware process and does not have detrimental time delay effect on the overall process. Unpolarized images, however, posses a high visual contrast and when fused (without digital enhancement) properly with polarized ones, is shown to increase the recognition accuracy and security of the biometric system without any significant processing time delay.

Design Fragments

DTIC Science & Technology

2007-04-19

define the patterns and are better at analyzing behavior. SPQR (System for Pattern Query and Recognition) [18, 58] can recognize pattern vari- ants...Stotts. SPQR : Flexible automated design pattern extraction from source code. ase, 00:215, 2003. ISSN 1527-1366. doi: http://doi.ieeecomputersociety. org

Infrared sensing of non-observable human biometrics

NASA Astrophysics Data System (ADS)

Willmore, Michael R.

2005-05-01

Interest and growth of biometric recognition technologies surged after 9/11. Once a technology mainly used for identity verification in law enforcement, biometrics are now being considered as a secure means of providing identity assurance in security related applications. Biometric recognition in law enforcement must, by necessity, use attributes of human uniqueness that are both observable and vulnerable to compromise. Privacy and protection of an individual's identity is not assured during criminal activity. However, a security system must rely on identity assurance for access control to physical or logical spaces while not being vulnerable to compromise and protecting the privacy of an individual. The solution resides in the use of non-observable attributes of human uniqueness to perform the biometric recognition process. This discussion will begin by presenting some key perspectives about biometric recognition and the characteristic differences between observable and non-observable biometric attributes. An introduction to the design, development, and testing of the Thermo-ID system will follow. The Thermo-ID system is an emerging biometric recognition technology that uses non-observable patterns of infrared energy naturally emanating from within the human body. As with all biometric systems, the infrared patterns recorded and compared within the Thermo-ID system are unique and individually distinguishable permitting a link to be confirmed between an individual and a claimed or previously established identity. The non-observable characteristics of infrared patterns of human uniqueness insure both the privacy and protection of an individual using this type of biometric recognition system.

Aptamer loaded MoS2 nanoplates as nanoprobes for detection of intracellular ATP and controllable photodynamic therapy

NASA Astrophysics Data System (ADS)

Jia, Li; Ding, Lin; Tian, Jiangwei; Bao, Lei; Hu, Yaoping; Ju, Huangxian; Yu, Jun-Sheng

2015-09-01

In this work we designed a MoS2 nanoplate-based nanoprobe for fluorescence imaging of intracellular ATP and photodynamic therapy (PDT) via ATP-mediated controllable release of 1O2. The nanoprobe was prepared by simply assembling a chlorine e6 (Ce6) labelled ATP aptamer on MoS2 nanoplates, which have favorable biocompatibility, unusual surface-area-to-mass ratio, strong affinity to single-stranded DNA, and can quench the fluorescence of Ce6. After the nanoprobe was internalized into the cells and entered ATP-abundant lysosomes, its recognition to ATP led to the release of the single-stranded aptamer from MoS2 nanoplates and thus recovered the fluorescence of Ce6 at an excitation wavelength of 633 nm, which produced a highly sensitive and selective method for imaging of intracellular ATP. Meanwhile, the ATP-mediated release led to the generation of 1O2 under 660 nm laser irradiation, which could induce tumor cell death with a lysosomal pathway. The controllable PDT provided a model approach for design of multifunctional theranostic nanoprobes. These results also promoted the development and application of MoS2 nanoplate-based platforms in biomedicine.In this work we designed a MoS2 nanoplate-based nanoprobe for fluorescence imaging of intracellular ATP and photodynamic therapy (PDT) via ATP-mediated controllable release of 1O2. The nanoprobe was prepared by simply assembling a chlorine e6 (Ce6) labelled ATP aptamer on MoS2 nanoplates, which have favorable biocompatibility, unusual surface-area-to-mass ratio, strong affinity to single-stranded DNA, and can quench the fluorescence of Ce6. After the nanoprobe was internalized into the cells and entered ATP-abundant lysosomes, its recognition to ATP led to the release of the single-stranded aptamer from MoS2 nanoplates and thus recovered the fluorescence of Ce6 at an excitation wavelength of 633 nm, which produced a highly sensitive and selective method for imaging of intracellular ATP. Meanwhile, the ATP-mediated release led to the generation of 1O2 under 660 nm laser irradiation, which could induce tumor cell death with a lysosomal pathway. The controllable PDT provided a model approach for design of multifunctional theranostic nanoprobes. These results also promoted the development and application of MoS2 nanoplate-based platforms in biomedicine. Electronic supplementary information (ESI) available: Supplementary figures. See DOI: 10.1039/c5nr02224j

Facial expression recognition based on improved deep belief networks

NASA Astrophysics Data System (ADS)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

Terrain type recognition using ERTS-1 MSS images

NASA Technical Reports Server (NTRS)

Gramenopoulos, N.

1973-01-01

For the automatic recognition of earth resources from ERTS-1 digital tapes, both multispectral and spatial pattern recognition techniques are important. Recognition of terrain types is based on spatial signatures that become evident by processing small portions of an image through selected algorithms. An investigation of spatial signatures that are applicable to ERTS-1 MSS images is described. Artifacts in the spatial signatures seem to be related to the multispectral scanner. A method for suppressing such artifacts is presented. Finally, results of terrain type recognition for one ERTS-1 image are presented.

Italians Use Abstract Knowledge about Lexical Stress during Spoken-Word Recognition

ERIC Educational Resources Information Center

Sulpizio, Simone; McQueen, James M.

2012-01-01

In two eye-tracking experiments in Italian, we investigated how acoustic information and stored knowledge about lexical stress are used during the recognition of tri-syllabic spoken words. Experiment 1 showed that Italians use acoustic cues to a word's stress pattern rapidly in word recognition, but only for words with antepenultimate stress.…

Specific Patterns of Emotion Recognition from Faces in Children with ASD: Results of a Cross-Modal Matching Paradigm

ERIC Educational Resources Information Center

Golan, Ofer; Gordon, Ilanit; Fichman, Keren; Keinan, Giora

2018-01-01

Children with ASD show emotion recognition difficulties, as part of their social communication deficits. We examined facial emotion recognition (FER) in intellectually disabled children with ASD and in younger typically developing (TD) controls, matched on mental age. Our emotion-matching paradigm employed three different modalities: facial, vocal…

Quantum Model of Emerging Grammars

NASA Technical Reports Server (NTRS)

Zak, M.

1999-01-01

A special class of quantum recurrent nets simulating Markov chains with absorbing states is introduced. The absorbing states are exploited for pattern recognition: each class of patterns, each combination of patterns acquires its own meaning.

Heterodimerization of TLR2 with TLR1 or TLR6 expands the ligand spectrum but does not lead to differential signaling.

PubMed

Farhat, Katja; Riekenberg, Sabine; Heine, Holger; Debarry, Jennifer; Lang, Roland; Mages, Jörg; Buwitt-Beckmann, Ute; Röschmann, Kristina; Jung, Günther; Wiesmüller, Karl-Heinz; Ulmer, Artur J

2008-03-01

TLR are primary triggers of the innate immune system by recognizing various microorganisms through conserved pathogen-associated molecular patterns. TLR2 is the receptor for a functional recognition of bacterial lipopeptides (LP) and is up-regulated during various disorders such as chronic obstructive pulmonary disease and sepsis. This receptor is unique in its ability to form heteromers with TLR1 or TLR6 to mediate intracellular signaling. According to the fatty acid pattern as well as the assembling of the polypeptide tail, LP can signal through TLR2 in a TLR1- or TLR6-dependent manner. There are also di- and triacylated LP, which stimulate TLR1-deficient cells and TLR6-deficient cells. In this study, we investigated whether heterodimerization evolutionarily developed to broaden the ligand spectrum or to induce different immune responses. We analyzed the signal transduction pathways activated through the different TLR2 dimers using the three LP, palmitic acid (Pam)octanoic acid (Oct)(2)C-(VPGVG)(4)VPGKG, fibroblast-stimulating LP-1, and Pam(2)C-SK(4). Dominant-negative forms of signaling molecules, immunoblotting of MAPK, as well as microarray analysis indicate that all dimers use the same signaling cascade, leading to an identical pattern of gene activation. We conclude that heterodimerization of TLR2 with TLR1 or TLR6 evolutionarily developed to expand the ligand spectrum to enable the innate immune system to recognize the numerous, different structures of LP present in various pathogens. Thus, although mycoplasma and Gram-positive and Gram-negative bacteria may activate different TLR2 dimers, the development of different signal pathways in response to different LP does not seem to be of vital significance for the innate defense system.

Using Pattern Recognition and Discriminance Analysis to Predict Critical Events in Large Signal Databases

NASA Astrophysics Data System (ADS)

Feller, Jens; Feller, Sebastian; Mauersberg, Bernhard; Mergenthaler, Wolfgang

2009-09-01

Many applications in plant management require close monitoring of equipment performance, in particular with the objective to prevent certain critical events. At each point in time, the information available to classify the criticality of the process, is represented through the historic signal database as well as the actual measurement. This paper presents an approach to detect and predict critical events, based on pattern recognition and discriminance analysis.

Background characterization techniques for target detection using scene metrics and pattern recognition

NASA Astrophysics Data System (ADS)

Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

1990-09-01

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

Fundamental remote sensing science research program. Part 1: Status report of the mathematical pattern recognition and image analysis project

NASA Technical Reports Server (NTRS)

Heydorn, R. D.

1984-01-01

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of the Earth from remotely sensed measurement of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inference about the Earth.

CNN: a speaker recognition system using a cascaded neural network.

PubMed

Zaki, M; Ghalwash, A; Elkouny, A A

1996-05-01

The main emphasis of this paper is to present an approach for combining supervised and unsupervised neural network models to the issue of speaker recognition. To enhance the overall operation and performance of recognition, the proposed strategy integrates the two techniques, forming one global model called the cascaded model. We first present a simple conventional technique based on the distance measured between a test vector and a reference vector for different speakers in the population. This particular distance metric has the property of weighting down the components in those directions along which the intraspeaker variance is large. The reason for presenting this method is to clarify the discrepancy in performance between the conventional and neural network approach. We then introduce the idea of using unsupervised learning technique, presented by the winner-take-all model, as a means of recognition. Due to several tests that have been conducted and in order to enhance the performance of this model, dealing with noisy patterns, we have preceded it with a supervised learning model--the pattern association model--which acts as a filtration stage. This work includes both the design and implementation of both conventional and neural network approaches to recognize the speakers templates--which are introduced to the system via a voice master card and preprocessed before extracting the features used in the recognition. The conclusion indicates that the system performance in case of neural network is better than that of the conventional one, achieving a smooth degradation in respect of noisy patterns, and higher performance in respect of noise-free patterns.

Extracting semantics from audio-visual content: the final frontier in multimedia retrieval.

PubMed

Naphade, M R; Huang, T S

2002-01-01

Multimedia understanding is a fast emerging interdisciplinary research area. There is tremendous potential for effective use of multimedia content through intelligent analysis. Diverse application areas are increasingly relying on multimedia understanding systems. Advances in multimedia understanding are related directly to advances in signal processing, computer vision, pattern recognition, multimedia databases, and smart sensors. We review the state-of-the-art techniques in multimedia retrieval. In particular, we discuss how multimedia retrieval can be viewed as a pattern recognition problem. We discuss how reliance on powerful pattern recognition and machine learning techniques is increasing in the field of multimedia retrieval. We review the state-of-the-art multimedia understanding systems with particular emphasis on a system for semantic video indexing centered around multijects and multinets. We discuss how semantic retrieval is centered around concepts and context and the various mechanisms for modeling concepts and context.

Learning pattern recognition and decision making in the insect brain

NASA Astrophysics Data System (ADS)

Huerta, R.

2013-01-01

We revise the current model of learning pattern recognition in the Mushroom Bodies of the insects using current experimental knowledge about the location of learning, olfactory coding and connectivity. We show that it is possible to have an efficient pattern recognition device based on the architecture of the Mushroom Bodies, sparse code, mutual inhibition and Hebbian leaning only in the connections from the Kenyon cells to the output neurons. We also show that despite the conventional wisdom that believes that artificial neural networks are the bioinspired model of the brain, the Mushroom Bodies actually resemble very closely Support Vector Machines (SVMs). The derived SVM learning rules are situated in the Mushroom Bodies, are nearly identical to standard Hebbian rules, and require inhibition in the output. A very particular prediction of the model is that random elimination of the Kenyon cells in the Mushroom Bodies do not impair the ability to recognize odorants previously learned.

Pattern recognition of visible and near-infrared spectroscopy from bayberry juice by use of partial least squares and a backpropagation neural network

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

Cen Haiyan; Bao Yidan; He Yong

2006-10-10

Visible and near-infrared reflectance (visible-NIR) spectroscopy is applied to discriminate different varieties of bayberry juices. The discrimination of visible-NIR spectra from samples is a matter of pattern recognition. By partial least squares (PLS), the spectrum is reduced to certain factors, which are then taken as the input of the backpropagation neural network (BPNN). Through training and prediction, three different varieties of bayberry juice are classified based on the output of the BPNN. In addition, a mathematical model is built and the algorithm is optimized. With proper parameters in the training set,100% accuracy is obtained by the BPNN. Thus it ismore » concluded that the PLS analysis combined with the BPNN is an alternative for pattern recognition based on visible and NIR spectroscopy.« less

Photonics: From target recognition to lesion detection

NASA Technical Reports Server (NTRS)

Henry, E. Michael

1994-01-01

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Speech therapy and voice recognition instrument

NASA Technical Reports Server (NTRS)

Cohen, J.; Babcock, M. L.

1972-01-01

Characteristics of electronic circuit for examining variations in vocal excitation for diagnostic purposes and in speech recognition for determiniog voice patterns and pitch changes are described. Operation of the circuit is discussed and circuit diagram is provided.

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.

Protein degradation machinery is present broadly during early development in the sea urchin.

PubMed

Zazueta-Novoa, Vanesa; Wessel, Gary M

2014-07-01

Ubiquitin-dependent proteosome-mediated proteolysis is an important pathway of degradation that controls the timed destruction of cellular proteins in all tissues. All intracellular proteins and many extracellular proteins are continually being hydrolyzed to their constituent amino acids as a result of their recognition by E3 ligases for specific targeting of ubiquitination. Gustavus is a member of an ECS-type E3 ligase which interacts with Vasa, a DEAD-box RNA helicase, to regulate its localization during sea urchin embryonic development, and Gustavus mRNA accumulation is highly localized and dynamic during development. We tested if the core complex for Gustavus function was present in the embryo and if other SOCS box proteins also had restricted expression profiles that would inform future research. Expression patterns of the key members of the proteasomal function, such as the E3 core complex which interacts with Gustavus, and other E3-SOCS box proteins, are widely spread and dynamic in early development of the embryo suggesting broad core complex availability in the proteasome degradation pathway and temporal/spatial enrichments of various E3 ligase dependent targeting mechanisms. Copyright © 2014 Elsevier B.V. All rights reserved.

Protein degradation machinery is present broadly during early development in the sea urchin

PubMed Central

Zazueta-Novoa, Vanesa; Wessel, Gary M.

2014-01-01

Ubiquitin-dependent proteosome-mediated proteolysis is an important pathway of degradation that controls the timed destruction of cellular proteins in all tissues. All intracellular proteins and many extracellular proteins are continually being hydrolyzed to their constituent amino acids as a result of their recognition by E3 ligases for specific targeting of ubiquitination. Gustavus is a member of an ECS-type E3 ligase which interacts with Vasa, a DEAD-box RNA helicase, to regulate its localization during sea urchin embryonic development, and Gustavus mRNA accumulation is highly localized and dynamic during development. We tested if the core complex for Gustavus function was present in the embryo and if other SOCS box proteins also had restricted expression profiles that would inform future research. Expression patterns of the key members of the proteasomal function, such as the E3 core complex which interacts with Gustavus, and other E3-SOCS box proteins, are widely spread and dynamic in early development of the embryo suggesting broad core complex availability in the proteasome degradation pathway and temporal/spatial enrichments of various E3 ligase dependent targeting mechanisms. PMID:24963879

Multigenic Control of Measles Vaccine Immunity Mediated by Polymorphisms in Measles Receptor, Innate Pathway, and Cytokine Genes

PubMed Central

Kennedy, Richard B.; Ovsyannikova, Inna G.; Haralambieva, Iana H.; O’Byrne, Megan; Jacobson, Robert M.; Pankratz, V. Shane; Poland, Gregory A.

2012-01-01

Measles infection and vaccine response are complex biological processes that involve both viral and host genetic factors. We have previously investigated the influence of genetic polymorphisms on vaccine immune response, including measles vaccines, and have shown that polymorphisms in HLA, cytokine, cytokine receptor, and innate immune response genes are associated with variation in vaccine response but do not account for all of the inter-individual variance seen in vaccinated populations. In the current study we report the findings of a multigenic analysis of measles vaccine immunity, indicating a role for the measles virus receptor CD46, innate pattern-recognition receptors (DDX58, TLR2, 4, 5,7 and 8) and intracellular signaling intermediates (MAP3K7, NFKBIA), and key antiviral molecules (VISA, OAS2, MX1, PKR) as well as cytokines (IFNA1, IL4, IL6, IL8, IL12B) and cytokine receptor genes (IL2RB, IL6R, IL8RA) in the genetic control of both humoral and cellular immune responses. This multivariate approach provided additional insights into the genetic control of measles vaccine responses over and above the information gained by our previous univariate SNP association analyses. PMID:22265947

CpG DNA in the prevention and treatment of infections.

PubMed

Dalpke, Alexander; Zimmermann, Stefan; Heeg, Klaus

2002-01-01

Microbial infection is sensed by Toll-like receptors (TLRs) on innate immune cells. Among the ten so far defined TLRs, TLR9 and its ligand are peculiar. TLR9 recognises bacterial DNA characterised by the abundance of unmethylated CpG dinucleotides, which distinguish bacterial DNA (CpG DNA) from mammalian DNA. Moreover, TLR9 shows a restricted cellular and subcellular pattern of expression. In contrast to other TLR agonists, CpG DNA is superior in activation of dendritic dells and induction of costimulatory cytokines such as interleukin (IL)-12 and IL-18. This qualifies CpG DNA as a Th1-promoting adjuvant. During infection, recognition of CpG DNA of intracellular pathogens skews and fine-tunes the ongoing immune response and induces long-lasting Th1 milieus. Thus, CpG DNA might play an important role in driving the immune system to a Th1 profile, preventing undesired Th2 milieus that might favour induction of allergic responses. Since CpG DNA can be synthesised with high purity and sequence fidelity, synthetic CpG DNA will become an important agent for Th1 instruction and be an effective adjuvant during vaccination.

Infrared and visible fusion face recognition based on NSCT domain

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Impaired Word and Face Recognition in Older Adults with Type 2 Diabetes.

PubMed

Jones, Nicola; Riby, Leigh M; Smith, Michael A

2016-07-01

Older adults with type 2 diabetes mellitus (DM2) exhibit accelerated decline in some domains of cognition including verbal episodic memory. Few studies have investigated the influence of DM2 status in older adults on recognition memory for more complex stimuli such as faces. In the present study we sought to compare recognition memory performance for words, objects and faces under conditions of relatively low and high cognitive load. Healthy older adults with good glucoregulatory control (n = 13) and older adults with DM2 (n = 24) were administered recognition memory tasks in which stimuli (faces, objects and words) were presented under conditions of either i) low (stimulus presented without a background pattern) or ii) high (stimulus presented against a background pattern) cognitive load. In a subsequent recognition phase, the DM2 group recognized fewer faces than healthy controls. Further, the DM2 group exhibited word recognition deficits in the low cognitive load condition. The recognition memory impairment observed in patients with DM2 has clear implications for day-to-day functioning. Although these deficits were not amplified under conditions of increased cognitive load, the present study emphasizes that recognition memory impairment for both words and more complex stimuli such as face are a feature of DM2 in older adults. Copyright © 2016 IMSS. Published by Elsevier Inc. All rights reserved.

Facial emotion recognition in Williams syndrome and Down syndrome: A matching and developmental study.

PubMed

Martínez-Castilla, Pastora; Burt, Michael; Borgatti, Renato; Gagliardi, Chiara

2015-01-01

In this study both the matching and developmental trajectories approaches were used to clarify questions that remain open in the literature on facial emotion recognition in Williams syndrome (WS) and Down syndrome (DS). The matching approach showed that individuals with WS or DS exhibit neither proficiency for the expression of happiness nor specific impairments for negative emotions. Instead, they present the same pattern of emotion recognition as typically developing (TD) individuals. Thus, the better performance on the recognition of positive compared to negative emotions usually reported in WS and DS is not specific of these populations but seems to represent a typical pattern. Prior studies based on the matching approach suggested that the development of facial emotion recognition is delayed in WS and atypical in DS. Nevertheless, and even though performance levels were lower in DS than in WS, the developmental trajectories approach used in this study evidenced that not only individuals with DS but also those with WS present atypical development in facial emotion recognition. Unlike in the TD participants, where developmental changes were observed along with age, in the WS and DS groups, the development of facial emotion recognition was static. Both individuals with WS and those with DS reached an early maximum developmental level due to cognitive constraints.

Multivariate fMRI and Eye Tracking Reveal Differential Effects of Visual Interference on Recognition Memory Judgments for Objects and Scenes.

PubMed

O'Neil, Edward B; Watson, Hilary C; Dhillon, Sonya; Lobaugh, Nancy J; Lee, Andy C H

2015-09-01

Recent work has demonstrated that the perirhinal cortex (PRC) supports conjunctive object representations that aid object recognition memory following visual object interference. It is unclear, however, how these representations interact with other brain regions implicated in mnemonic retrieval and how congruent and incongruent interference influences the processing of targets and foils during object recognition. To address this, multivariate partial least squares was applied to fMRI data acquired during an interference match-to-sample task, in which participants made object or scene recognition judgments after object or scene interference. This revealed a pattern of activity sensitive to object recognition following congruent (i.e., object) interference that included PRC, prefrontal, and parietal regions. Moreover, functional connectivity analysis revealed a common pattern of PRC connectivity across interference and recognition conditions. Examination of eye movements during the same task in a separate study revealed that participants gazed more at targets than foils during correct object recognition decisions, regardless of interference congruency. By contrast, participants viewed foils more than targets for incorrect object memory judgments, but only after congruent interference. Our findings suggest that congruent interference makes object foils appear familiar and that a network of regions, including PRC, is recruited to overcome the effects of interference.

Supra-physiological folic acid concentrations induce aberrant DNA methylation in normal human cells in vitro.

PubMed

Charles, Michelle A; Johnson, Ian T; Belshaw, Nigel J

2012-07-01

The micronutrients folate and selenium may modulate DNA methylation patterns by affecting intracellular levels of the methyl donor S-adenosylmethionine (SAM) and/or the product of methylation reactions S-adenosylhomocysteine (SAH). WI-38 fibroblasts and FHC colon epithelial cells were cultured in the presence of two forms of folate or four forms of selenium at physiologically-relevant doses, and their effects on LINE-1 methylation, gene-specific CpG island (CGI) methylation and intracellular SAM:SAH were determined. At physiologically-relevant doses the forms of folate or selenium had no effect on LINE-1 or CGI methylation, nor on intracellular SAM:SAH. However the commercial cell culture media used for the selenium studies, containing supra-physiological concentrations of folic acid, induced LINE-1 hypomethylation, CGI hypermethylation and decreased intracellular SAM:SAH in both cell lines. We conclude that the exposure of normal human cells to supra-physiological folic acid concentrations present in commercial cell culture media perturbs the intracellular SAM:SAH ratio and induces aberrant DNA methylation.

Perceiving patterns of play in dynamic sport tasks: investigating the essential information underlying skilled performance.

PubMed

Willams, A Mark; Hodges, Nicola J; North, Jamie S; Barton, Gabor

2006-01-01

The perceptual-cognitive information used to support pattern-recognition skill in soccer was examined. In experiment 1, skilled players were quicker and more accurate than less-skilled players at recognising familiar and unfamiliar soccer action sequences presented on film. In experiment 2, these action sequences were converted into point-light displays, with superficial display features removed and the positions of players and the relational information between them made more salient. Skilled players were more accurate than less-skilled players in recognising sequences presented in point-light form, implying that each pattern of play can be defined by the unique relations between players. In experiment 3, various offensive and defensive players were occluded for the duration of each trial in an attempt to identify the most important sources of information underpinning successful performance. A decrease in response accuracy was observed under occluded compared with non-occluded conditions and the expertise effect was no longer observed. The relational information between certain key players, team-mates and their defensive counterparts may provide the essential information for effective pattern-recognition skill in soccer. Structural feature analysis, temporal phase relations, and knowledge-based information are effectively integrated to facilitate pattern recognition in dynamic sport tasks.

Spatial-frequency cutoff requirements for pattern recognition in central and peripheral vision

PubMed Central

Kwon, MiYoung; Legge, Gordon E.

2011-01-01

It is well known that object recognition requires spatial frequencies exceeding some critical cutoff value. People with central scotomas who rely on peripheral vision have substantial difficulty with reading and face recognition. Deficiencies of pattern recognition in peripheral vision, might result in higher cutoff requirements, and may contribute to the functional problems of people with central-field loss. Here we asked about differences in spatial-cutoff requirements in central and peripheral vision for letter and face recognition. The stimuli were the 26 letters of the English alphabet and 26 celebrity faces. Each image was blurred using a low-pass filter in the spatial frequency domain. Critical cutoffs (defined as the minimum low-pass filter cutoff yielding 80% accuracy) were obtained by measuring recognition accuracy as a function of cutoff (in cycles per object). Our data showed that critical cutoffs increased from central to peripheral vision by 20% for letter recognition and by 50% for face recognition. We asked whether these differences could be accounted for by central/peripheral differences in the contrast sensitivity function (CSF). We addressed this question by implementing an ideal-observer model which incorporates empirical CSF measurements and tested the model on letter and face recognition. The success of the model indicates that central/peripheral differences in the cutoff requirements for letter and face recognition can be accounted for by the information content of the stimulus limited by the shape of the human CSF, combined with a source of internal noise and followed by an optimal decision rule. PMID:21854800

Artificial intelligence tools for pattern recognition

NASA Astrophysics Data System (ADS)

Acevedo, Elena; Acevedo, Antonio; Felipe, Federico; Avilés, Pedro

2017-06-01

In this work, we present a system for pattern recognition that combines the power of genetic algorithms for solving problems and the efficiency of the morphological associative memories. We use a set of 48 tire prints divided into 8 brands of tires. The images have dimensions of 200 x 200 pixels. We applied Hough transform to obtain lines as main features. The number of lines obtained is 449. The genetic algorithm reduces the number of features to ten suitable lines that give thus the 100% of recognition. Morphological associative memories were used as evaluation function. The selection algorithms were Tournament and Roulette wheel. For reproduction, we applied one-point, two-point and uniform crossover.

Bringing an Ecological Perspective to the Study of Aging and Recognition of Emotional Facial Expressions: Past, Current, and Future Methods

PubMed Central

Isaacowitz, Derek M.; Stanley, Jennifer Tehan

2011-01-01

Older adults perform worse on traditional tests of emotion recognition accuracy than do young adults. In this paper, we review descriptive research to date on age differences in emotion recognition from facial expressions, as well as the primary theoretical frameworks that have been offered to explain these patterns. We propose that this is an area of inquiry that would benefit from an ecological approach in which contextual elements are more explicitly considered and reflected in experimental methods. Use of dynamic displays and examination of specific cues to accuracy, for example, may reveal more nuanced age-related patterns and may suggest heretofore unexplored underlying mechanisms. PMID:22125354

Interface Prostheses With Classifier-Feedback-Based User Training.

PubMed

Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

2017-11-01

It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.

Bridge Health Monitoring Using a Machine Learning Strategy

DOT National Transportation Integrated Search

2017-01-01

The goal of this project was to cast the SHM problem within a statistical pattern recognition framework. Techniques borrowed from speaker recognition, particularly speaker verification, were used as this discipline deals with problems very similar to...

Exploring a Decrease in Recognition Performance for Non-Antecedents Following the Processing of Anaphors

ERIC Educational Resources Information Center

Dopkins, Stephen; Nordlie, Johanna

2011-01-01

Recognition judgments to the non-antecedents of a repeated-noun anaphor are slower and less accurate after than before the processing of the anaphor. Disagreement exists as to whether this pattern of performance reflects a bias shift carried out by a memory process associated with the recognition of a word that has previously occurred in the…

Artificially intelligent recognition of Arabic speaker using voice print-based local features

NASA Astrophysics Data System (ADS)

Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz

2016-11-01

Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.

Simulation of Biomimetic Recognition between Polymers and Surfaces

NASA Astrophysics Data System (ADS)

Golumbfskie, Aaron J.; Pande, Vijay S.; Chakraborty, Arup K.

1999-10-01

Many biological processes, such as transmembrane signaling and pathogen-host interactions, are initiated by a protein recognizing a specific pattern of binding sites on part of a membrane or cell surface. By recognition, we imply that the polymer quickly finds and then adsorbs strongly on the pattern-matched region and not on others. The development of synthetic systems that can mimic such recognition between polymers and surfaces could have significant impact on advanced applications such as the development of sensors, molecular-scale separation processes, and synthetic viral inhibition agents. Attempting to affect recognition in synthetic systems by copying the detailed chemistries to which nature has been led over millenia of evolution does not seem practical for most applications. This leads us to the following question: Are there any universal strategies that can affect recognition between polymers and surfaces? Such generic strategies may be easier to implement in abiotic applications. We describe results that suggest that biomimetic recognition between synthetic polymers and surfaces is possible by exploiting certain generic strategies, and we elucidate the kinetic mechanisms by which this occurs. Our results suggest convenient model systems for experimental studies of dynamics in free energy landscapes characteristic of frustrated systems.

Facial and prosodic emotion recognition in social anxiety disorder.

PubMed

Tseng, Huai-Hsuan; Huang, Yu-Lien; Chen, Jian-Ting; Liang, Kuei-Yu; Lin, Chao-Cheng; Chen, Sue-Huei

2017-07-01

Patients with social anxiety disorder (SAD) have a cognitive preference to negatively evaluate emotional information. In particular, the preferential biases in prosodic emotion recognition in SAD have been much less explored. The present study aims to investigate whether SAD patients retain negative evaluation biases across visual and auditory modalities when given sufficient response time to recognise emotions. Thirty-one SAD patients and 31 age- and gender-matched healthy participants completed a culturally suitable non-verbal emotion recognition task and received clinical assessments for social anxiety and depressive symptoms. A repeated measures analysis of variance was conducted to examine group differences in emotion recognition. Compared to healthy participants, SAD patients were significantly less accurate at recognising facial and prosodic emotions, and spent more time on emotion recognition. The differences were mainly driven by the lower accuracy and longer reaction times for recognising fearful emotions in SAD patients. Within the SAD patients, lower accuracy of sad face recognition was associated with higher severity of depressive and social anxiety symptoms, particularly with avoidance symptoms. These findings may represent a cross-modality pattern of avoidance in the later stage of identifying negative emotions in SAD. This pattern may be linked to clinical symptom severity.

Supramolecularly Engineered Circular Bivalent Aptamer for Enhanced Functional Protein Delivery.

PubMed

Jiang, Ying; Pan, Xiaoshu; Chang, Jin; Niu, Weijia; Hou, Weijia; Kuai, Hailan; Zhao, Zilong; Liu, Ji; Wang, Ming; Tan, Weihong

2018-06-06

Circular bivalent aptamers (cb-apt) comprise an emerging class of chemically engineered aptamers with substantially improved stability and molecular recognition ability. Its therapeutic application, however, is challenged by the lack of functional modules to control the interactions of cb-apt with therapeutics. We present the design of a β-cyclodextrin-modified cb-apt (cb-apt-βCD) and its supramolecular interaction with molecular therapeutics via host-guest chemistry for targeted intracellular delivery. The supramolecular ensemble exhibits high serum stability and enhanced intracellular delivery efficiency compared to a monomeric aptamer. The cb-apt-βCD ensemble delivers green fluorescent protein into targeted cells with efficiency as high as 80%, or cytotoxic saporin to efficiently inhibit tumor cell growth. The strategy of conjugating βCD to cb-apt, and subsequently modulating the supramolecular chemistry of cb-apt-βCD, provides a general platform to expand and diversify the function of aptamers, enabling new biological and therapeutic applications.

Effector-triggered immunity: from pathogen perception to robust defense.

PubMed

Cui, Haitao; Tsuda, Kenichi; Parker, Jane E

2015-01-01

In plant innate immunity, individual cells have the capacity to sense and respond to pathogen attack. Intracellular recognition mechanisms have evolved to intercept perturbations by pathogen virulence factors (effectors) early in host infection and convert it to rapid defense. One key to resistance success is a polymorphic family of intracellular nucleotide-binding/leucine-rich-repeat (NLR) receptors that detect effector interference in different parts of the cell. Effector-activated NLRs connect, in various ways, to a conserved basal resistance network in order to transcriptionally boost defense programs. Effector-triggered immunity displays remarkable robustness against pathogen disturbance, in part by employing compensatory mechanisms within the defense network. Also, the mobility of some NLRs and coordination of resistance pathways across cell compartments provides flexibility to fine-tune immune outputs. Furthermore, a number of NLRs function close to the nuclear chromatin by balancing actions of defense-repressing and defense-activating transcription factors to program cells dynamically for effective disease resistance.

Slow [Na+]i dynamics impacts arrhythmogenesis and spiral wave reentry in cardiac myocyte ionic model.

PubMed

Krogh-Madsen, Trine; Christini, David J

2017-09-01

Accumulation of intracellular Na + is gaining recognition as an important regulator of cardiac myocyte electrophysiology. The intracellular Na + concentration can be an important determinant of the cardiac action potential duration, can modulate the tissue-level conduction of excitation waves, and can alter vulnerability to arrhythmias. Mathematical models of cardiac electrophysiology often incorporate a dynamic intracellular Na + concentration, which changes much more slowly than the remaining variables. We investigated the dependence of several arrhythmogenesis-related factors on [Na + ] i in a mathematical model of the human atrial action potential. In cell simulations, we found that [Na + ] i accumulation stabilizes the action potential duration to variations in several conductances and that the slow dynamics of [Na + ] i impacts bifurcations to pro-arrhythmic afterdepolarizations, causing intermittency between different rhythms. In long-lasting tissue simulations of spiral wave reentry, [Na + ] i becomes spatially heterogeneous with a decreased area around the spiral wave rotation center. This heterogeneous region forms a functional anchor, resulting in diminished meandering of the spiral wave. Our findings suggest that slow, physiological, rate-dependent variations in [Na + ] i may play complex roles in cellular and tissue-level cardiac dynamics.

Slow [Na+]i dynamics impacts arrhythmogenesis and spiral wave reentry in cardiac myocyte ionic model

NASA Astrophysics Data System (ADS)

Krogh-Madsen, Trine; Christini, David J.

2017-09-01

Accumulation of intracellular Na+ is gaining recognition as an important regulator of cardiac myocyte electrophysiology. The intracellular Na+ concentration can be an important determinant of the cardiac action potential duration, can modulate the tissue-level conduction of excitation waves, and can alter vulnerability to arrhythmias. Mathematical models of cardiac electrophysiology often incorporate a dynamic intracellular Na+ concentration, which changes much more slowly than the remaining variables. We investigated the dependence of several arrhythmogenesis-related factors on [Na+]i in a mathematical model of the human atrial action potential. In cell simulations, we found that [Na+]i accumulation stabilizes the action potential duration to variations in several conductances and that the slow dynamics of [Na+]i impacts bifurcations to pro-arrhythmic afterdepolarizations, causing intermittency between different rhythms. In long-lasting tissue simulations of spiral wave reentry, [Na+]i becomes spatially heterogeneous with a decreased area around the spiral wave rotation center. This heterogeneous region forms a functional anchor, resulting in diminished meandering of the spiral wave. Our findings suggest that slow, physiological, rate-dependent variations in [Na+]i may play complex roles in cellular and tissue-level cardiac dynamics.

Sulfur Modifications of the Wobble U34 in tRNAs and their Intracellular Localization in Eukaryotic Cells

PubMed Central

Nakai, Yumi; Nakai, Masato; Yano, Takato

2017-01-01

The wobble uridine (U34) of transfer RNAs (tRNAs) for two-box codon recognition, i.e., tRNALysUUU, tRNAGluUUC, and tRNAGlnUUG, harbor a sulfur- (thio-) and a methyl-derivative structure at the second and fifth positions of U34, respectively. Both modifications are necessary to construct the proper anticodon loop structure and to enable them to exert their functions in translation. Thio-modification of U34 (s2U34) is found in both cytosolic tRNAs (cy-tRNAs) and mitochondrial tRNAs (mt-tRNAs). Although l-cysteine desulfurase is required in both cases, subsequent sulfur transfer pathways to cy-tRNAs and mt-tRNAs are different due to their distinct intracellular locations. The s2U34 formation in cy-tRNAs involves a sulfur delivery system required for the biosynthesis of iron-sulfur (Fe/S) clusters and certain resultant Fe/S proteins. This review addresses presumed sulfur delivery pathways for the s2U34 formation in distinct intracellular locations, especially that for cy-tRNAs in comparison with that for mt-tRNAs. PMID:28218716

Sulfur Modifications of the Wobble U34 in tRNAs and their Intracellular Localization in Eukaryotic Cells.

PubMed

Nakai, Yumi; Nakai, Masato; Yano, Takato

2017-02-18

The wobble uridine (U 34 ) of transfer RNAs (tRNAs) for two-box codon recognition, i.e., tRNA Lys UUU , tRNA Glu UUC , and tRNA Gln UUG , harbor a sulfur- (thio-) and a methyl-derivative structure at the second and fifth positions of U 34 , respectively. Both modifications are necessary to construct the proper anticodon loop structure and to enable them to exert their functions in translation. Thio-modification of U 34 (s²U 34 ) is found in both cytosolic tRNAs (cy-tRNAs) and mitochondrial tRNAs (mt-tRNAs). Although l-cysteine desulfurase is required in both cases, subsequent sulfur transfer pathways to cy-tRNAs and mt-tRNAs are different due to their distinct intracellular locations. The s²U 34 formation in cy-tRNAs involves a sulfur delivery system required for the biosynthesis of iron-sulfur (Fe/S) clusters and certain resultant Fe/S proteins. This review addresses presumed sulfur delivery pathways for the s²U 34 formation in distinct intracellular locations, especially that for cy-tRNAs in comparison with that for mt-tRNAs.

Understanding the molecular differential recognition of muramyl peptide ligands by LRR domains of human NOD receptors.

PubMed

Vijayrajratnam, Sukhithasri; Pushkaran, Anju Choorakottayil; Balakrishnan, Aathira; Vasudevan, Anil Kumar; Biswas, Raja; Mohan, Chethampadi Gopi

2017-07-27

Human nucleotide-binding oligomerization domain proteins, hNOD1 and hNOD2, are host intracellular receptors with C-terminal leucine-rich repeat (LRR) domains, which recognize specific bacterial peptidoglycan (PG) fragments as their ligands. The specificity of this recognition is dependent on the third amino acid of the stem peptide of the PG ligand, which is usually meso -diaminopimelic acid ( meso DAP) or l-lysine (l-Lys). Since the LRR domains of hNOD receptors had been experimentally shown to confer the PG ligand-sensing specificity, we developed three-dimensional structures of hNOD1-LRR and the hNOD2-LRR to understand the mechanism of differential recognition of muramyl peptide ligands by hNOD receptors. The hNOD1-LRR and hNOD2-LRR receptor models exhibited right-handed curved solenoid shape. The hot-spot residues experimentally proved to be critical for ligand recognition were located in the concavity of the NOD-LRR and formed the recognition site. Our molecular docking analyses and molecular electrostatic potential mapping studies explain the activation of hNOD-LRRs, in response to effective molecular interactions of PG ligands at the recognition site; and conversely, the inability of certain PG ligands to activate hNOD-LRRs, by deviations from the recognition site. Based on molecular docking studies using PG ligands, we propose few residues - G825, D826 and N850 in hNOD1-LRR and L904, G905, W931, L932 and S933 in hNOD2-LRR, evolutionarily conserved across different host species, which may play a major role in ligand recognition. Thus, our integrated experimental and computational approach elucidates the molecular basis underlying the differential recognition of PG ligands by hNOD receptors. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Rapid detection of malignant bio-species using digital holographic pattern recognition and nano-photonics

NASA Astrophysics Data System (ADS)

Sarkisov, Sergey S.; Kukhtareva, Tatiana; Kukhtarev, Nickolai V.; Curley, Michael J.; Edwards, Vernessa; Creer, Marylyn

2013-03-01

There is a great need for rapid detection of bio-hazardous species particularly in applications to food safety and biodefense. It has been recently demonstrated that the colonies of various bio-species could be rapidly detected using culture-specific and reproducible patterns generated by scattered non-coherent light. However, the method heavily relies on a digital pattern recognition algorithm, which is rather complex, requires substantial computational power and is prone to ambiguities due to shift, scale, or orientation mismatch between the analyzed pattern and the reference from the library. The improvement could be made, if, in addition to the intensity of the scattered optical wave, its phase would be also simultaneously recorded and used for the digital holographic pattern recognition. In this feasibility study the research team recorded digital Gabor-type (in-line) holograms of colonies of micro-organisms, such as Salmonella with a laser diode as a low-coherence light source and a lensless high-resolution (2.0x2.0 micron pixel pitch) digital image sensor. The colonies were grown in conventional Petri dishes using standard methods. The digitally recorded holograms were used for computational reconstruction of the amplitude and phase information of the optical wave diffracted on the colonies. Besides, the pattern recognition of the colony fragments using the cross-correlation between the digital hologram was also implemented. The colonies of mold fungi Altenaria sp, Rhizophus, sp, and Aspergillus sp have been also generating nano-colloidal silver during their growth in specially prepared matrices. The silver-specific plasmonic optical extinction peak at 410-nm was also used for rapid detection and growth monitoring of the fungi colonies.

Motion Based Target Acquisition and Evaluation in an Adaptive Machine Vision System

DTIC Science & Technology

1995-05-01

paths in facial recognition and learning. Annals of Neurology, 22, 41-45. Tolman, E.C. (1932) Purposive behavior in Animals and Men. New York: Appleton...Learned scan paths are the active processes of perception. Rizzo et al. (1987) studied the fixation patterns of two patients with impaired facial ... recognition and learning and found an increase in the randomness of the scan patterns compared to controls, indicating that the cortex was failing to direct

Simulation and performance of an artificial retina for 40 MHz track reconstruction

DOE PAGES

Abba, A.; Bedeschi, F.; Citterio, M.; ...

2015-03-05

We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of 40 MHz. Performances of the artificial retina algorithm are assessed using the official Monte Carlo samples of the LHCb experiment. We found performances for the retina pattern-recognition algorithm comparable with the full LHCb reconstruction algorithm.

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

PubMed

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-05-21

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

Pattern recognition tool based on complex network-based approach

NASA Astrophysics Data System (ADS)

Casanova, Dalcimar; Backes, André Ricardo; Martinez Bruno, Odemir

2013-02-01

This work proposed a generalization of the method proposed by the authors: 'A complex network-based approach for boundary shape analysis'. Instead of modelling a contour into a graph and use complex networks rules to characterize it, here, we generalize the technique. This way, the work proposes a mathematical tool for characterization signals, curves and set of points. To evaluate the pattern description power of the proposal, an experiment of plat identification based on leaf veins image are conducted. Leaf vein is a taxon characteristic used to plant identification proposes, and one of its characteristics is that these structures are complex, and difficult to be represented as a signal or curves and this way to be analyzed in a classical pattern recognition approach. Here, we model the veins as a set of points and model as graphs. As features, we use the degree and joint degree measurements in a dynamic evolution. The results demonstrates that the technique has a good power of discrimination and can be used for plant identification, as well as other complex pattern recognition tasks.

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.

Haemophilus ducreyi infection induces activation of the NLRP3 inflammasome in nonpolarized but not in polarized human macrophages.

PubMed

Li, Wei; Katz, Barry P; Bauer, Margaret E; Spinola, Stanley M

2013-08-01

Recognition of microbial infection by certain intracellular pattern recognition receptors leads to the formation of a multiprotein complex termed the inflammasome. Inflammasome assembly activates caspase-1 and leads to cleavage and secretion of the proinflammatory cytokines interleukin-1 beta (IL-1β) and IL-18, which help control many bacterial pathogens. However, excessive inflammation mediated by inflammasome activation can also contribute to immunopathology. Here, we investigated whether Haemophilus ducreyi, a Gram-negative bacterium that causes the genital ulcer disease chancroid, activates inflammasomes in experimentally infected human skin and in monocyte-derived macrophages (MDM). Although H. ducreyi is predominantly extracellular during human infection, several inflammasome-related components were transcriptionally upregulated in H. ducreyi-infected skin. Infection of MDM with live, but not heat-killed, H. ducreyi induced caspase-1- and caspase-5-dependent processing and secretion of IL-1β. Blockage of H. ducreyi uptake by cytochalasin D significantly reduced the amount of secreted IL-1β. Knocking down the expression of the inflammasome components NLRP3 and ASC abolished IL-1β production. Consistent with NLRP3-dependent inflammasome activation, blocking ATP signaling, K(+) efflux, cathepsin B activity, and lysosomal acidification all inhibited IL-1β secretion. However, inhibition of the production and function of reactive oxygen species did not decrease IL-1β production. Polarization of macrophages to classically activated M1 or alternatively activated M2 cells abrogated IL-1β secretion elicited by H. ducreyi. Our study data indicate that H. ducreyi induces NLRP3 inflammasome activation via multiple mechanisms and suggest that the heterogeneity of macrophages within human lesions may modulate inflammasome activation during human infection.

Crystal Structure and Substrate Recognition of Cellobionic Acid Phosphorylase, Which Plays a Key Role in Oxidative Cellulose Degradation by Microbes*

PubMed Central

Nam, Young-Woo; Nihira, Takanori; Arakawa, Takatoshi; Saito, Yuka; Kitaoka, Motomitsu; Nakai, Hiroyuki; Fushinobu, Shinya

2015-01-01

The microbial oxidative cellulose degradation system is attracting significant research attention after the recent discovery of lytic polysaccharide mono-oxygenases. A primary product of the oxidative and hydrolytic cellulose degradation system is cellobionic acid (CbA), the aldonic acid form of cellobiose. We previously demonstrated that the intracellular enzyme belonging to glycoside hydrolase family 94 from cellulolytic fungus and bacterium is cellobionic acid phosphorylase (CBAP), which catalyzes reversible phosphorolysis of CbA into glucose 1-phosphate and gluconic acid (GlcA). In this report, we describe the biochemical characterization and the three-dimensional structure of CBAP from the marine cellulolytic bacterium Saccharophagus degradans. Structures of ligand-free and complex forms with CbA, GlcA, and a synthetic disaccharide product from glucuronic acid were determined at resolutions of up to 1.6 Å. The active site is located near the dimer interface. At subsite +1, the carboxylate group of GlcA and CbA is recognized by Arg-609 and Lys-613. Additionally, one residue from the neighboring protomer (Gln-190) is involved in the carboxylate recognition of GlcA. A mutational analysis indicated that these residues are critical for the binding and catalysis of the aldonic and uronic acid acceptors GlcA and glucuronic acid. Structural and sequence comparisons with other glycoside hydrolase family 94 phosphorylases revealed that CBAPs have a unique subsite +1 with a distinct amino acid residue conservation pattern at this site. This study provides molecular insight into the energetically efficient metabolic pathway of oxidized sugars that links the oxidative cellulolytic pathway to the glycolytic and pentose phosphate pathways in cellulolytic microbes. PMID:26041776

Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

NASA Astrophysics Data System (ADS)

Popko, E. A.; Weinstein, I. A.

2016-08-01

Optical character recognition is one of the important issues in the field of pattern recognition. This paper presents a method for recognizing handwritten digits based on the modeling of convolutional neural network. The integrated fuzzy logic module based on a structural approach was developed. Used system architecture adjusted the output of the neural network to improve quality of symbol identification. It was shown that proposed algorithm was flexible and high recognition rate of 99.23% was achieved.

Identity Recognition Algorithm Using Improved Gabor Feature Selection of Gait Energy Image

NASA Astrophysics Data System (ADS)

Chao, LIANG; Ling-yao, JIA; Dong-cheng, SHI

2017-01-01

This paper describes an effective gait recognition approach based on Gabor features of gait energy image. In this paper, the kernel Fisher analysis combined with kernel matrix is proposed to select dominant features. The nearest neighbor classifier based on whitened cosine distance is used to discriminate different gait patterns. The approach proposed is tested on the CASIA and USF gait databases. The results show that our approach outperforms other state of gait recognition approaches in terms of recognition accuracy and robustness.

Automatic recognition of postural allocations.

PubMed

Sazonov, Edward; Krishnamurthy, Vidya; Makeyev, Oleksandr; Browning, Ray; Schutz, Yves; Hill, James

2007-01-01

A significant part of daily energy expenditure may be attributed to non-exercise activity thermogenesis and exercise activity thermogenesis. Automatic recognition of postural allocations such as standing or sitting can be used in behavioral modification programs aimed at minimizing static postures. In this paper we propose a shoe-based device and related pattern recognition methodology for recognition of postural allocations. Inexpensive technology allows implementation of this methodology as a part of footwear. The experimental results suggest high efficiency and reliability of the proposed approach.