The role of microbial flora on the ocular surface.

PubMed

Miller, Darlene; Iovieno, Alfonso

2009-10-01

Presence and interplay of microbial flora at the ocular surface reveal dynamic and evolving interactions with implications for both ocular surface health and disease. Data in this area are scarce or non-existent. The purpose of this review is to provide a snapshot of new and emerging developments in this area over the last 12 months. Recent findings signal potential roles for ocular surface microbial flora in both the preservation and extension of ocular surface health and in the initiation of new or escalation of common surface disorders. Contributions range from priming surface epithelial immune cells to regulating mucin composition and production. Other findings explore the emergent role of ocular microbial flora cross talk with pattern recognition receptors to protect and strengthen local and adaptive mucosal immunity while preserving vision. Deciphering the functional role of microbial communities at the ocular surface could bring new insights into and clarify the epidemiology and pathology of ocular surface dynamics in health and disease.

The role of pattern recognition receptors in lung sarcoidosis.

PubMed

Mortaz, Esmaeil; Adcock, Ian M; Abedini, Atefhe; Kiani, Arda; Kazempour-Dizaji, Mehdi; Movassaghi, Masoud; Garssen, Johan

2017-08-05

Sarcoidosis is a granulomatous disorder of unknown etiology. Infection, genetic factors, autoimmunity and an aberrant innate immune system have been explored as potential causes of sarcoidosis. The etiology of sarcoidosis remains unknown, and it is thought that it might be caused by an infectious agent in a genetically predisposed, susceptible host. Inflammation results from recognition of evolutionarily conserved structures of pathogens (Pathogen-associated molecular patterns, PAMPs) and/or from reaction to tissue damage associated patterns (DAMPs) through recognition by a limited number of germ line-encoded pattern recognition receptors (PRRs). Due to the similar clinical and histopathological picture of sarcoidosis and tuberculosis, Mycobacterium tuberculosis antigens such early secreted antigen (ESAT-6), heat shock proteins (Mtb-HSP), catalase-peroxidase (katG) enzyme and superoxide dismutase A peptide (sodA) have been often considered as factors in the etiopathogenesis of sarcoidosis. Potential non-TB-associated PAMPs include lipopolysaccharide (LPS) from the outer membrane of Gram-negative bacteria, peptidoglycan, lipoteichoic acid, bacterial DNA, viral DNA/RNA, chitin, flagellin, leucine-rich repeats (LRR), mannans in the yeast cell wall, and microbial HSPs. Furthermore, exogenous non-organic antigens such as metals, silica, pigments with/without aluminum in tattoos, pesticides, and pollen have been evoked as potential causes of sarcoidosis. Exposure of the airways to diverse infectious and non-infectious agents may be important in the pathogenesis of sarcoidosis. The current review provides and update on the role of PPRs and DAMPs in the pathogenesis of sarcoidsis. Copyright © 2017 Elsevier B.V. All rights reserved.

Co-factors Required for TLR7- and TLR9- dependent Innate Immune Responses

PubMed Central

Chiang, Chih-yuan; Engel, Alex; Opaluch, Amanda M.; Ramos, Irene; Maestre, Ana M.; Secundino, Ismael; De Jesus, Paul D.; Nguyen, Quy T.; Welch, Genevieve; Bonamy, Ghislain M.C.; Miraglia, Loren J.; Orth, Anthony P.; Nizet, Victor; Fernandez-Sesma, Ana; Zhou, Yingyao; Barton, Gregory M.; Chanda, Sumit K.

2012-01-01

SUMMARY Pathogens commonly utilize endocytic pathways to gain cellular access. The endosomal pattern recognition receptors TLR7 and TLR9 detect pathogen-encoded nucleic acids to initiate MyD88-dependent pro-inflammatory responses to microbial infection. Using genome-wide RNAi screening and integrative systems-based analysis we identify 190 co-factors required for TLR7- and TLR9-directed signaling responses. A set of co-factors were cross-profiled for their activities downstream of several immunoreceptors, and then functionally mapped based on the known architecture of NF-κB signaling pathways. Protein complexes and pathways involved in ubiquitin-protein ligase activities, sphingolipid metabolism, chromatin modifications, and ancient stress responses were found to modulate innate recognition of endosomal nucleic acids. Additionally, hepatocyte growth factor-regulated tyrosine kinase substrate (HRS) was characterized as necessary for ubiquitin-dependent TLR9 targeting to the endolysosome. Proteins and pathways identified here should prove useful in delineating strategies to manipulate innate responses for treatment of autoimmune disorders and microbial infection. PMID:22423970

Recognition of anaerobic bacterial isolates in vitro using electronic nose technology.

PubMed

Pavlou, A; Turner, A P F; Magan, N

2002-01-01

Use of an electronic nose (e.nose) system to differentiation between anaerobic bacteria grown in vitro on agar media. Cultures of Clostridium spp. (14 strains) and Bacteroides fragilis (12 strains) were grown on blood agar plates and incubated in sampling bags for 30 min before head space analysis of the volatiles. Qualitative analyses of the volatile production patterns was carried out using an e.nose system with 14 conducting polymer sensors. Using data analysis techniques such as principal components analysis (PCA), genetic algorithms and neural networks it was possible to differentiate between agar blanks and individual species which accounted for all the data. A total of eight unknowns were correctly discriminated into the bacterial groups. This is the first report of in vitro complex volatile pattern recognition and differentiation of anaerobic pathogens. These results suggest the potential for application of e.nose technology in early diagnosis of microbial pathogens of medical importance.

Rapid classification of hairtail fish and pork freshness using an electronic nose based on the PCA method.

PubMed

Tian, Xiu-Ying; Cai, Qiang; Zhang, Yong-Ming

2012-01-01

We report a method for building a simple and reproducible electronic nose based on commercially available metal oxide sensors (MOS) to monitor the freshness of hairtail fish and pork stored at 15, 10, and 5 °C. After assembly in the laboratory, the proposed product was tested by a manufacturer. Sample delivery was based on the dynamic headspace method, and two features were extracted from the transient response of each sensor using an unsupervised principal component analysis (PCA) method. The compensation method and pattern recognition based on PCA are discussed in the current paper. PCA compensation can be used for all storage temperatures, however, pattern recognition differs according to storage conditions. Total volatile basic nitrogen (TVBN) and aerobic bacterial counts of the samples were measured simultaneously with the standard indicators of hairtail fish and pork freshness. The PCA models based on TVBN and aerobic bacterial counts were used to classify hairtail fish samples as "fresh" (TVBN ≤ 25 g and microbial counts ≤ 10(6) cfu/g) or "spoiled" (TVBN ≥ 25 g and microbial counts ≥ 10(6) cfu/g) and pork samples also as "fresh" (TVBN ≤ 15 g and microbial counts ≤ 10(6) cfu/g) or "spoiled" (TVBN ≥ 15 g and microbial counts ≥ 10(6) cfu/g). Good correlation coefficients between the responses of the electronic nose and the TVBN and aerobic bacterial counts of the samples were obtained. For hairtail fish, correlation coefficients were 0.97 and 0.91, and for pork, correlation coefficients were 0.81 and 0.88, respectively. Through laboratory simulation and field application, we were able to determine that the electronic nose could help ensure the shelf life of hairtail fish and pork, especially when an instrument is needed to take measurements rapidly. The results also showed that the electronic nose could analyze the process and level of spoilage for hairtail fish and pork.

Disifin (sodium tosylchloramide) and Toll-like receptors (TLRs): evolving importance in health and diseases.

PubMed

Ofodile, Okom Nkili F C

2007-12-01

Disifin has emerged as a unique and very effective agent used in disinfection of wounds, disinfection of surfaces, materials and water, and other substances contaminated with almost every type of pathogenic microorganism ranging from viruses, bacteria, fungi and yeast, and, very possibly, protozoan parasites, as well. The major active component of Disifin is tosylchloramide sodium (chloramine T). However, the mechanism by which Disifin suppresses the activities of pathogenic microbial agents remains enigmatic. The molecular mechanisms, and the receptors and the signal transducing pathways responsible for the biological effects of Disifin are largely unknown. Despite considerable advances, enormous investigative efforts and large resources invested in the research on infectious diseases, microbial infection still remains a public health problem in many parts of the world. The exact nature of the pathogenic agents responsible for many infectious diseases, and the nature of the receptors mediating the associated inflammatory events are incompletely understood. Recent advances in understanding the molecular basis for mammalian host immune responses to microbial invasion suggest that the first line of defense against microbes is the recognition of pathogen-associated molecular patterns (PAMPs) by a family of transmembrane pattern-recognizing and signal transducing receptor proteins called Toll-like receptors (TLRs). The TLR family plays an instructive role in innate immune responses against microbial pathogens, as well as the subsequent induction of adaptive immune responses. TLRs mediate recognition and inflammatory responses to a wide range of microbial products and are crucial for effective host defense by eradication of the invading pathogens. Now, recent updates demonstrated the ability of Disifin-derived products, Disifin-Animal and Disifin-Pressant to effectively suppress the progression and activities of Chikungunya fever and that of avian influenza A virus [A/cardialis/Germany/72, H7N1: the agent of a highly pathogenic avian influenza (HPAI)] infection, respectively. Overall, the above findings led me to suggest that Disifin and TLRs may mechanistically overlap in the processes of executing their functions against pathogenic microbial organisms. Thus, elucidating and better understanding of the molecular underpinnings responsible for the biochemical effects of Disifin-products, and the nature and mode of the interaction(s) of Disifin with TLRs in the process of exerting their biological effects may open a novel dimension in the research of infectious diseases, which may provide novel therapeutic targets for the prevention and treatment of a wide range of infectious diseases.

Ecdysone triggered PGRP-LC expression controls Drosophila innate immunity.

PubMed

Rus, Florentina; Flatt, Thomas; Tong, Mei; Aggarwal, Kamna; Okuda, Kendi; Kleino, Anni; Yates, Elisabeth; Tatar, Marc; Silverman, Neal

2013-05-29

Throughout the animal kingdom, steroid hormones have been implicated in the defense against microbial infection, but how these systemic signals control immunity is unclear. Here, we show that the steroid hormone ecdysone controls the expression of the pattern recognition receptor PGRP-LC in Drosophila, thereby tightly regulating innate immune recognition and defense against bacterial infection. We identify a group of steroid-regulated transcription factors as well as two GATA transcription factors that act as repressors and activators of the immune response and are required for the proper hormonal control of PGRP-LC expression. Together, our results demonstrate that Drosophila use complex mechanisms to modulate innate immune responses, and identify a transcriptional hierarchy that integrates steroid signalling and immunity in animals.

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

PubMed

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

2015-07-01

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

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

PubMed Central

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

2015-01-01

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

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.

Directed evolution of FLS2 towards novel flagellin peptide recognition

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

Helft, Laura; Thompson, Mikayla; Bent, Andrew F.

Microbe-associated molecular patterns (MAMPs) are molecules, or domains within molecules, that are conserved across microbial taxa and can be recognized by a plant or animal immune system. Although MAMP receptors have evolved to recognize conserved epitopes, the MAMPs in some microbial species or strains have diverged sufficiently to render them unrecognizable by some host immune systems. In this study, we carried out in vitro evolution of the Arabidopsis thaliana flagellin receptor FLAGELLIN-SENSING 2 (FLS2) to isolate derivatives that recognize one or more flagellin peptides from bacteria for which the wildtype Arabidopsis FLS2 confers little or no response. A targeted approachmore » generated amino acid variation at FLS2 residues in a region previously implicated in flagellin recognition. The primary screen tested for elevated response to the canonical flagellin peptide from Pseudomonas aeruginosa, flg22. From this pool, we then identified five alleles of FLS2 that confer modest (quantitatively partial) recognition of an Erwinia amylovora flagellin peptide. Use of this Erwinia-based flagellin peptide to stimulate Arabidopsis plants expressing the resulting FLS2 alleles did not lead to a detectable reduction of virulent P. syringae pv. tomato growth. However, combination of two identified mutations into a single allele further increased FLS2-mediated responses to the E. amylovora flagellin peptide. Furthermore, these studies demonstrate the potential to raise the sensitivity of MAMP receptors toward particular targets.« less

Directed evolution of FLS2 towards novel flagellin peptide recognition

DOE PAGES

Helft, Laura; Thompson, Mikayla; Bent, Andrew F.

2016-06-06

Microbe-associated molecular patterns (MAMPs) are molecules, or domains within molecules, that are conserved across microbial taxa and can be recognized by a plant or animal immune system. Although MAMP receptors have evolved to recognize conserved epitopes, the MAMPs in some microbial species or strains have diverged sufficiently to render them unrecognizable by some host immune systems. In this study, we carried out in vitro evolution of the Arabidopsis thaliana flagellin receptor FLAGELLIN-SENSING 2 (FLS2) to isolate derivatives that recognize one or more flagellin peptides from bacteria for which the wildtype Arabidopsis FLS2 confers little or no response. A targeted approachmore » generated amino acid variation at FLS2 residues in a region previously implicated in flagellin recognition. The primary screen tested for elevated response to the canonical flagellin peptide from Pseudomonas aeruginosa, flg22. From this pool, we then identified five alleles of FLS2 that confer modest (quantitatively partial) recognition of an Erwinia amylovora flagellin peptide. Use of this Erwinia-based flagellin peptide to stimulate Arabidopsis plants expressing the resulting FLS2 alleles did not lead to a detectable reduction of virulent P. syringae pv. tomato growth. However, combination of two identified mutations into a single allele further increased FLS2-mediated responses to the E. amylovora flagellin peptide. Furthermore, these studies demonstrate the potential to raise the sensitivity of MAMP receptors toward particular targets.« less

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

Vibrio vulnificus quorum-sensing molecule cyclo(Phe-Pro) inhibits RIG-I-mediated antiviral innate immunity.

PubMed

Lee, Wooseong; Lee, Seung-Hoon; Kim, Minwoo; Moon, Jae-Su; Kim, Geon-Woo; Jung, Hae-Gwang; Kim, In Hwang; Oh, Ji Eun; Jung, Hi Eun; Lee, Heung Kyu; Ku, Keun Bon; Ahn, Dae-Gyun; Kim, Seong-Jun; Kim, Kun-Soo; Oh, Jong-Won

2018-04-23

The recognition of pathogen-derived ligands by pattern recognition receptors activates the innate immune response, but the potential interaction of quorum-sensing (QS) signaling molecules with host anti-viral defenses remains largely unknown. Here we show that the Vibrio vulnificus QS molecule cyclo(Phe-Pro) (cFP) inhibits interferon (IFN)-β production by interfering with retinoic-acid-inducible gene-I (RIG-I) activation. Binding of cFP to the RIG-I 2CARD domain induces a conformational change in RIG-I, preventing the TRIM25-mediated ubiquitination to abrogate IFN production. cFP enhances susceptibility to hepatitis C virus (HCV), as well as Sendai and influenza viruses, each known to be sensed by RIG-I but did not affect the melanoma-differentiation-associated gene 5 (MDA5)-recognition of norovirus. Our results reveal an inter-kingdom network between bacteria, viruses and host that dysregulates host innate responses via a microbial quorum-sensing molecule modulating the response to viral infection.

Human NOD2 Recognizes Structurally Unique Muramyl Dipeptides from Mycobacterium leprae

PubMed Central

Schenk, Mirjam; Mahapatra, Sebabrata; Le, Phuonganh; Kim, Hee Jin; Choi, Aaron W.; Brennan, Patrick J.; Belisle, John T.

2016-01-01

The innate immune system recognizes microbial pathogens via pattern recognition receptors. One such receptor, NOD2, via recognition of muramyl dipeptide (MDP), triggers a distinct network of innate immune responses, including the production of interleukin-32 (IL-32), which leads to the differentiation of monocytes into dendritic cells (DC). NOD2 has been implicated in the pathogenesis of human leprosy, yet it is not clear whether Mycobacterium leprae, which has a distinct MDP structure, can activate this pathway. We investigated the effect of MDP structure on the innate immune response, finding that infection of monocytes with M. leprae induces IL-32 and DC differentiation in a NOD2-dependent manner. The presence of the proximal l-Ala instead of Gly in the common configuration of the peptide side chain of M. leprae did not affect recognition by NOD2 or cytokine production. Furthermore, amidation of the d-Glu residue did not alter NOD2 activation. These data provide experimental evidence that NOD2 recognizes naturally occurring structural variants of MDP. PMID:27297389

Molecular recognition of microbial lipid-based antigens by T cells.

PubMed

Gras, Stephanie; Van Rhijn, Ildiko; Shahine, Adam; Le Nours, Jérôme

2018-05-01

The immune system has evolved to protect hosts from pathogens. T cells represent a critical component of the immune system by their engagement in host defence mechanisms against microbial infections. Our knowledge of the molecular recognition by T cells of pathogen-derived peptidic antigens that are presented by the major histocompatibility complex glycoproteins is now well established. However, lipids represent an additional, distinct chemical class of molecules that when presented by the family of CD1 antigen-presenting molecules can serve as antigens, and be recognized by specialized subsets of T cells leading to antigen-specific activation. Over the past decades, numerous CD1-presented self- and bacterial lipid-based antigens have been isolated and characterized. However, our understanding at the molecular level of T cell immunity to CD1 molecules presenting microbial lipid-based antigens is still largely unexplored. Here, we review the insights and the molecular basis underpinning the recognition of microbial lipid-based antigens by T cells.

Lipopolysaccharide Clearance, Bacterial Clearance, and Systemic Inflammatory Responses Are Regulated by Cell Type–Specific Functions of TLR4 during Sepsis

PubMed Central

Deng, Meihong; Loughran, Patricia; Gibson, Gregory; Sodhi, Chhinder; Watkins, Simon; Hackam, David

2013-01-01

The morbidity associated with bacterial sepsis is the result of host immune responses to pathogens, which are dependent on pathogen recognition by pattern recognition receptors, such as TLR4. TLR4 is expressed on a range of cell types, yet the mechanisms by which cell-specific functions of TLR4 lead to an integrated sepsis response are poorly understood. To address this, we generated mice in which TLR4 was specifically deleted from myeloid cells (LysMTLR4KO) or hepatocytes (HCTLR4KO) and then determined survival, bacterial counts, host inflammatory responses, and organ injury in a model of cecal ligation and puncture (CLP), with or without antibiotics. LysM-TLR4 was required for phagocytosis and efficient bacterial clearance in the absence of antibiotics. Survival, the magnitude of the systemic and local inflammatory responses, and liver damage were associated with bacterial levels. HCTLR4 was required for efficient LPS clearance from the circulation, and deletion of HCTLR4 was associated with enhanced macrophage phagocytosis, lower bacterial levels, and improved survival in CLP without antibiotics. Antibiotic administration during CLP revealed an important role for hepatocyte LPS clearance in limiting sepsis-induced inflammation and organ injury. Our work defines cell type–selective roles for TLR4 in coordinating complex immune responses to bacterial sepsis and suggests that future strategies for modulating microbial molecule recognition should account for varying roles of pattern recognition receptors in multiple cell populations. PMID:23562812

Host-induced bacterial cell wall decomposition mediates pattern-triggered immunity in Arabidopsis

PubMed Central

Liu, Xiaokun; Grabherr, Heini M; Willmann, Roland; Kolb, Dagmar; Brunner, Frédéric; Bertsche, Ute; Kühner, Daniel; Franz-Wachtel, Mirita; Amin, Bushra; Felix, Georg; Ongena, Marc; Nürnberger, Thorsten; Gust, Andrea A

2014-01-01

Peptidoglycans (PGNs) are immunogenic bacterial surface patterns that trigger immune activation in metazoans and plants. It is generally unknown how complex bacterial structures such as PGNs are perceived by plant pattern recognition receptors (PRRs) and whether host hydrolytic activities facilitate decomposition of bacterial matrices and generation of soluble PRR ligands. Here we show that Arabidopsis thaliana, upon bacterial infection or exposure to microbial patterns, produces a metazoan lysozyme-like hydrolase (lysozyme 1, LYS1). LYS1 activity releases soluble PGN fragments from insoluble bacterial cell walls and cleavage products are able to trigger responses typically associated with plant immunity. Importantly, LYS1 mutant genotypes exhibit super-susceptibility to bacterial infections similar to that observed on PGN receptor mutants. We propose that plants employ hydrolytic activities for the decomposition of complex bacterial structures, and that soluble pattern generation might aid PRR-mediated immune activation in cell layers adjacent to infection sites. DOI: http://dx.doi.org/10.7554/eLife.01990.001 PMID:24957336

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.

Microbial Transglutaminase Used in Bread Preparation at Standard Bakery Concentrations Does Not Increase Immunodetectable Amounts of Deamidated Gliadin.

PubMed

Heil, Andreas; Ohsam, Jürgen; van Genugten, Bernard; Diez, Oscar; Yokoyama, Keiichi; Kumazawa, Yoshiyuki; Pasternack, Ralf; Hils, Martin

2017-08-16

The effect of standard bakery concentrations of microbial transglutaminase (MTG) in wheat bread preparation on the immunoreactivity of sera of celiac disease (CD) patients was investigated. Immunoblotting using monoclonal antibodies specific to unmodified and/or deamidated gliadin showed no differences between control bread and MTG bread. Deamidation of gliadin could not be detected at standard MTG concentrations. Sera of CD patients were characterized using anti-gliadin and anti-deamidated gliadin peptide (DGP) enzyme-linked immunosorbent assay and grouped into DGP high- and low-titer pools. The recognition pattern obtained after using both CD sera pools for immunoblotting did not reveal differences between control and MTG-treated bread protein extracts. Our results indicate that MTG treatment of wheat bread prepared with typical MTG concentrations used in standard bakery processes does not lead to immunodetectable amounts of CD immunotoxic deamidated gliadins.

Conventional and Non-Conventional Drosophila Toll Signaling

PubMed Central

Lindsay, Scott A.; Wasserman, Steven A.

2013-01-01

The discovery of Toll in Drosophila and of the remarkable conservation in pathway composition and organization catalyzed a transformation in our understanding of innate immune recognition and response. At the center of that picture is a cascade of interactions in which specific microbial cues activate Toll receptors, which then transmit signals driving transcription factor nuclear localization and activity. Experiments gave substance to the vision of pattern recognition receptors, linked phenomena in development, gene regulation, and immunity into a coherent whole, and revealed a rich set of variations for identifying non-self and responding effectively. More recently, research in Drosophila has illuminated the positive and negative regulation of Toll activation, the organization of signaling events at and beneath membranes, the sorting of information flow, and the existence of non-conventional signaling via Toll-related receptors. Here, we provide an overview of the Toll pathway of flies and highlight these ongoing realms of research. PMID:23632253

Human NOD2 Recognizes Structurally Unique Muramyl Dipeptides from Mycobacterium leprae.

PubMed

Schenk, Mirjam; Mahapatra, Sebabrata; Le, Phuonganh; Kim, Hee Jin; Choi, Aaron W; Brennan, Patrick J; Belisle, John T; Modlin, Robert L

2016-09-01

The innate immune system recognizes microbial pathogens via pattern recognition receptors. One such receptor, NOD2, via recognition of muramyl dipeptide (MDP), triggers a distinct network of innate immune responses, including the production of interleukin-32 (IL-32), which leads to the differentiation of monocytes into dendritic cells (DC). NOD2 has been implicated in the pathogenesis of human leprosy, yet it is not clear whether Mycobacterium leprae, which has a distinct MDP structure, can activate this pathway. We investigated the effect of MDP structure on the innate immune response, finding that infection of monocytes with M. leprae induces IL-32 and DC differentiation in a NOD2-dependent manner. The presence of the proximal l-Ala instead of Gly in the common configuration of the peptide side chain of M. leprae did not affect recognition by NOD2 or cytokine production. Furthermore, amidation of the d-Glu residue did not alter NOD2 activation. These data provide experimental evidence that NOD2 recognizes naturally occurring structural variants of MDP. Copyright © 2016 Schenk et al.

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.

Emerging spatial patterns in Antarctic prokaryotes

PubMed Central

Chong, Chun-Wie; Pearce, David A.; Convey, Peter

2015-01-01

Recent advances in knowledge of patterns of biogeography in terrestrial eukaryotic organisms have led to a fundamental paradigm shift in understanding of the controls and history of life on land in Antarctica, and its interactions over the long term with the glaciological and geological processes that have shaped the continent. However, while it has long been recognized that the terrestrial ecosystems of Antarctica are dominated by microbes and their processes, knowledge of microbial diversity and distributions has lagged far behind that of the macroscopic eukaryote organisms. Increasing human contact with and activity in the continent is leading to risks of biological contamination and change in a region whose isolation has protected it for millions of years at least; these risks may be particularly acute for microbial communities which have, as yet, received scant recognition and attention. Even a matter apparently as straightforward as Protected Area designation in Antarctica requires robust biodiversity data which, in most parts of the continent, remain almost completely unavailable. A range of important contributing factors mean that it is now timely to reconsider the state of knowledge of Antarctic terrestrial prokaryotes. Rapid advances in molecular biological approaches are increasingly demonstrating that bacterial diversity in Antarctica may be far greater than previously thought, and that there is overlap in the environmental controls affecting both Antarctic prokaryotic and eukaryotic communities. Bacterial dispersal mechanisms and colonization patterns remain largely unaddressed, although evidence for regional evolutionary differentiation is rapidly accruing and, with this, there is increasing appreciation of patterns in regional bacterial biogeography in this large part of the globe. In this review, we set out to describe the state of knowledge of Antarctic prokaryote diversity patterns, drawing analogy with those of eukaryote groups where appropriate. Based on our synthesis, it is clear that spatial patterns of Antarctic prokaryotes can be unique at local scales, while the limited evidence available to date supports the group exhibiting overall regional biogeographical patterns similar to the eukaryotes. We further consider the applicability of the concept of “functional redundancy” for the Antarctic microbial community and highlight the requirements for proper consideration of their important and distinctive roles in Antarctic terrestrial ecosystems. PMID:26483777

Microbial Ecology of a Regional Flow System: Deep, Aerobic, Fractured Rock Aquifers of the US Basin and Range (Invited)

NASA Astrophysics Data System (ADS)

Moser, D. P.; Hamilton-Brehm, S.; Zhang, G.; Fisher, J.; Hughes, K.; Wheatley, A.; Thomas, J.; Zavarin, M.; Roberts, S. K.; Kryder, L.; McRae, R.; Howard, W.; Walker, J.; Federwisch, R.; King, M.; Friese, R.; Grim, S.; Amend, J.; Momper, L.; Sherwood Lollar, B.; Onstott, T. C.

2013-12-01

Recent decades have revealed anaerobic microbial ecosystems across a range of deep, continental settings; however, aerobic, regional aquifers represent a little-studied habitat for deep life. The US' Basin and Range Province is an extensional zone defined by deep, interconnected fracture systems that span multiple hydrologic basins and host regional aquifers. Here we describe a multi-basin microbiological assessment, applied to the Death Valley Regional Flow System (DVRFS). Our group has surveyed more than thirty deep boreholes (~ 1,000 m depth average) and deeply-sourced springs across a ~170 km inferred flow path from recharge areas in volcanic and carbonate rock highlands of the Nevada National Security Site (NNSS) and the Spring Mountains to discharge zones in Oasis, Amargosa, and Death Valleys. DVRFS waters were characterized by temperatures of 30 - 50 oC and the presence of dissolved O2 (4 - 8 mg/L in the recharge areas and ~0.2 - 2 mg/L in the discharge zones). Planktonic microbial populations, as tracked by molecular DNA approaches (e.g. 454 pyrotag), were of low abundance (e.g. ~ 10e3 ~10e6 per mL) and dominated by Proteobacteria and Nitrospirae. Archaea were also present and dominated by novel Thaumarchaeotes. Patterns of microbial diversity and the hypothesis that these patterns may have utility for recognition of hydrologic connectivity were assessed by statistical tools. At the species level, cosmopolitan, system-wide, and flow-path-specific groupings of both bacteria and archaea were detected. Even when in close proximity to aerobic springs and wells, sites sampling deep, hot, anaerobic groundwaters possessed completely distinct microbial populations (e.g. dominance by Firmicutes, ANME, and predicted methanogens). Among methodological refinements developed from this work, the repeated sampling of one deep borehole over a month-long pump test revealed that well-bore-associated contaminants required several days of pumping for complete removal and enabled the identification of the specific depth that produced most of the water. Our results reveal details of microbial community structure for a common, but little-studied microbial ecosystem and support the concept that regional flow systems possess distinct microbial populations, consistent with their geochemical and hydrologic characteristics. These results generally support the concept that microbial populations may have utility as amplifiable tracers for tracking the connectivity of fluids in the subsurface.

Shape recognition of microbial cells by colloidal cell imprints

NASA Astrophysics Data System (ADS)

Borovička, Josef; Stoyanov, Simeon D.; Paunov, Vesselin N.

2013-08-01

We have engineered a class of colloids which can recognize the shape and size of targeted microbial cells and selectively bind to their surfaces. These imprinted colloid particles, which we called ``colloid antibodies'', were fabricated by partial fragmentation of silica shells obtained by templating the targeted microbial cells. We successfully demonstrated the shape and size recognition between such colloidal imprints and matching microbial cells. High percentage of binding events of colloidal imprints with the size matching target particles was achieved. We demonstrated selective binding of colloidal imprints to target microbial cells in a binary mixture of cells of different shapes and sizes, which also resulted in high binding selectivity. We explored the role of the electrostatic interactions between the target cells and their colloid imprints by pre-coating both of them with polyelectrolytes. Selective binding occurred predominantly in the case of opposite surface charges of the colloid cell imprint and the targeted cells. The mechanism of the recognition is based on the amplification of the surface adhesion in the case of shape and size match due to the increased contact area between the target cell and the colloidal imprint. We also tested the selective binding for colloid imprints of particles of fixed shape and varying sizes. The concept of cell recognition by colloid imprints could be used for development of colloid antibodies for shape-selective binding of microbes. Such colloid antibodies could be additionally functionalized with surface groups to enhance their binding efficiency to cells of specific shape and deliver a drug payload directly to their surface or allow them to be manipulated using external fields. They could benefit the pharmaceutical industry in developing selective antimicrobial therapies and formulations.

Modulation of neonatal microbial recognition: TLR-mediated innate immune responses are specifically and differentially modulated by human milk.

PubMed

LeBouder, Emmanuel; Rey-Nores, Julia E; Raby, Anne-Catherine; Affolter, Michael; Vidal, Karine; Thornton, Catherine A; Labéta, Mario O

2006-03-15

The mechanisms controlling innate microbial recognition in the neonatal gut are still to be fully understood. We have sought specific regulatory mechanisms operating in human breast milk relating to TLR-mediated microbial recognition. In this study, we report a specific and differential modulatory effect of early samples (days 1-5) of breast milk on ligand-induced cell stimulation via TLRs. Although a negative modulation was exerted on TLR2 and TLR3-mediated responses, those via TLR4 and TLR5 were enhanced. This effect was observed in human adult and fetal intestinal epithelial cell lines, monocytes, dendritic cells, and PBMC as well as neonatal blood. In the latter case, milk compensated for the low capacity of neonatal plasma to support responses to LPS. Cell stimulation via the IL-1R or TNFR was not modulated by milk. This, together with the differential effect on TLR activation, suggested that the primary effect of milk is exerted upstream of signaling proximal to TLR ligand recognition. The analysis of TLR4-mediated gene expression, used as a model system, showed that milk modulated TLR-related genes differently, including those coding for signal intermediates and regulators. A proteinaceous milk component of > or =80 kDa was found to be responsible for the effect on TLR4. Notably, infant milk formulations did not reproduce the modulatory activity of breast milk. Together, these findings reveal an unrecognized function of human milk, namely, its capacity to influence neonatal microbial recognition by modulating TLR-mediated responses specifically and differentially. This in turn suggests the existence of novel mechanisms regulating TLR activation.

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.

Plant immunity triggered by microbial molecular signatures.

PubMed

Zhang, Jie; Zhou, Jian-Min

2010-09-01

Pathogen/microbe-associated molecular patterns (PAMPs/MAMPs) are recognized by host cell surface-localized pattern-recognition receptors (PRRs) to activate plant immunity. PAMP-triggered immunity (PTI) constitutes the first layer of plant immunity that restricts pathogen proliferation. PTI signaling components often are targeted by various Pseudomonas syringae virulence effector proteins, resulting in diminished plant defenses and increased bacterial virulence. Some of the proteins targeted by pathogen effectors have evolved to sense the effector activity by associating with cytoplasmic immune receptors classically known as resistance proteins. This allows plants to activate a second layer of immunity termed effector-triggered immunity (ETI). Recent studies on PTI regulation and P. syringae effector targets have uncovered new components in PTI signaling. Although MAP kinase (MAPK) cascades have been considered crucial for PTI, emerging evidence indicates that a MAPK-independent pathway also plays an important role in PTI signaling.

Binding of a C-type lectin’s coiled-coil domain to the Domeless receptor directly activates the JAK/STAT pathway in the shrimp immune response to bacterial infection

PubMed Central

Zhao, Xiao-Fan; Vasta, Gerardo R.

2017-01-01

C-type lectins (CTLs) are characterized by the presence of a C-type carbohydrate recognition domain (CTLD) that by recognizing microbial glycans, is responsible for their roles as pattern recognition receptors in the immune response to bacterial infection. In addition to the CTLD, however, some CTLs display additional domains that can carry out effector functions, such as the collagenous domain of the mannose-binding lectin. While in vertebrates, the mechanisms involved in these effector functions have been characterized in considerable detail, in invertebrates they remain poorly understood. In this study, we identified in the kuruma shrimp (Marsupenaeus japonicus) a structurally novel CTL (MjCC-CL) that in addition to the canonical CTLD, contains a coiled-coil domain (CCD) responsible for the effector functions that are key to the shrimp’s antibacterial response mediated by antimicrobial peptides (AMPs). By the use of in vitro and in vivo experimental approaches we elucidated the mechanism by which the recognition of bacterial glycans by the CTLD of MjCC-CL leads to activation of the JAK/STAT pathway via interaction of the CCD with the surface receptor Domeless, and upregulation of AMP expression. Thus, our study of the shrimp MjCC-CL revealed a striking functional difference with vertebrates, in which the JAK/STAT pathway is indirectly activated by cell death and stress signals through cytokines or growth factors. Instead, by cross-linking microbial pathogens with the cell surface receptor Domeless, a lectin directly activates the JAK/STAT pathway, which plays a central role in the shrimp antibacterial immune responses by upregulating expression of selected AMPs. PMID:28931061

Cross-specificity of protective human antibodies against Klebsiella pneumoniae LPS O-antigen.

PubMed

Rollenske, Tim; Szijarto, Valeria; Lukasiewicz, Jolanta; Guachalla, Luis M; Stojkovic, Katarina; Hartl, Katharina; Stulik, Lukas; Kocher, Simone; Lasitschka, Felix; Al-Saeedi, Mohammed; Schröder-Braunstein, Jutta; von Frankenberg, Moritz; Gaebelein, Gereon; Hoffmann, Peter; Klein, Sabrina; Heeg, Klaus; Nagy, Eszter; Nagy, Gabor; Wardemann, Hedda

2018-06-01

Humoral immune responses to microbial polysaccharide surface antigens can prevent bacterial infection but are typically strain specific and fail to mediate broad protection against different serotypes. Here we describe a panel of affinity-matured monoclonal human antibodies from peripheral blood immunoglobulin M-positive (IgM + ) and IgA + memory B cells and clonally related intestinal plasmablasts, directed against the lipopolysaccharide (LPS) O-antigen of Klebsiella pneumoniae, an opportunistic pathogen and major cause of antibiotic-resistant nosocomial infections. The antibodies showed distinct patterns of in vivo cross-specificity and protection against different clinically relevant K. pneumoniae serotypes. However, cross-specificity was not limited to K. pneumoniae, as K. pneumoniae-specific antibodies recognized diverse intestinal microbes and neutralized not only K. pneumoniae LPS but also non-K. pneumoniae LPS. Our data suggest that the recognition of minimal glycan epitopes abundantly expressed on microbial surfaces might serve as an efficient humoral immunological mechanism to control invading pathogens and the large diversity of the human microbiota with a limited set of cross-specific antibodies.

Microbial transglutaminase treatment in pasta-production does not affect the immunoreactivity of gliadin with celiac disease patients' sera.

PubMed

Ruh, Tobias; Ohsam, Jürgen; Pasternack, Ralf; Yokoyama, Keiichi; Kumazawa, Yoshiyuki; Hils, Martin

2014-07-30

The effect of microbial transglutaminase (MTG)-treatment of pasta-dough on the immunoreactivity with celiac disease patient's sera has been investigated. Modification by MTG has been proven by determination of the MTG reaction product ε-(γ-glutamyl)lysine (3.63 μmol/g protein), which was not detectable in non-MTG-treated pasta. Antigenicity has been analyzed by immunoblotting and ELISA using gliadin-extracts from pasta and MTG-treated pasta. Immunoblotting showed that the antibody-population (antigliadin antibodies and antideamidated gliadin antibodies) of the sera is specific for every individual patient. Immunoblotting and ELISA showed that there is no difference in immunoreactivity of gliadin extracted from pasta and MTG-pasta. Recognition pattern and intensity in Western blot as well as antibody titer has also been identical even for sera with a high antideamidated gliadin antibody titer. These results indicate no difference between pasta-gliadin and MTG-pasta-gliadin and especially no increased deamidation in pasta-gliadin by MTG-treatment.

Expanded functions for a family of plant intracellular immune receptors beyond specific recognition of pathogen effectors

PubMed Central

Bonardi, Vera; Tang, Saijun; Stallmann, Anna; Roberts, Melinda; Cherkis, Karen; Dangl, Jeffery L.

2011-01-01

Plants and animals deploy intracellular immune receptors that perceive specific pathogen effector proteins and microbial products delivered into the host cell. We demonstrate that the ADR1 family of Arabidopsis nucleotide-binding leucine-rich repeat (NB-LRR) receptors regulates accumulation of the defense hormone salicylic acid during three different types of immune response: (i) ADRs are required as “helper NB-LRRs” to transduce signals downstream of specific NB-LRR receptor activation during effector-triggered immunity; (ii) ADRs are required for basal defense against virulent pathogens; and (iii) ADRs regulate microbial-associated molecular pattern-dependent salicylic acid accumulation induced by infection with a disarmed pathogen. Remarkably, these functions do not require an intact P-loop motif for at least one ADR1 family member. Our results suggest that some NB-LRR proteins can serve additional functions beyond canonical, P-loop–dependent activation by specific virulence effectors, extending analogies between intracellular innate immune receptor function from plants and animals. PMID:21911370

Immunity in Drosophila melanogaster--from microbial recognition to whole-organism physiology.

PubMed

Buchon, Nicolas; Silverman, Neal; Cherry, Sara

2014-12-01

Since the discovery of antimicrobial peptide responses 40 years ago, the fruit fly Drosophila melanogaster has proven to be a powerful model for the study of innate immunity. Early work focused on innate immune mechanisms of microbial recognition and subsequent nuclear factor-κB signal transduction. More recently, D. melanogaster has been used to understand how the immune response is regulated and coordinated at the level of the whole organism. For example, researchers have used this model in studies investigating interactions between the microbiota and the immune system at barrier epithelial surfaces that ensure proper nutritional and immune homeostasis both locally and systemically. In addition, studies in D. melanogaster have been pivotal in uncovering how the immune response is regulated by both endocrine and metabolic signalling systems, and how the immune response modifies these systems as part of a homeostatic circuit. In this Review, we briefly summarize microbial recognition and antiviral immunity in D. melanogaster, and we highlight recent studies that have explored the effects of organism-wide regulation of the immune response and, conversely, the effects of the immune response on organism physiology.

Pseudomonas HopU1 modulates plant immune receptor levels by blocking the interaction of their mRNAs with GRP7.

PubMed

Nicaise, Valerie; Joe, Anna; Jeong, Byeong-ryool; Korneli, Christin; Boutrot, Freddy; Westedt, Isa; Staiger, Dorothee; Alfano, James R; Zipfel, Cyril

2013-03-06

Pathogens target important components of host immunity to cause disease. The Pseudomonas syringae type III-secreted effector HopU1 is a mono-ADP-ribosyltransferase required for full virulence on Arabidopsis thaliana. HopU1 targets several RNA-binding proteins including GRP7, whose role in immunity is still unclear. Here, we show that GRP7 associates with translational components, as well as with the pattern recognition receptors FLS2 and EFR. Moreover, GRP7 binds specifically FLS2 and EFR transcripts in vivo through its RNA recognition motif. HopU1 does not affect the protein-protein associations between GRP7, FLS2 and translational components. Instead, HopU1 blocks the interaction between GRP7 and FLS2 and EFR transcripts in vivo. This inhibition correlates with reduced FLS2 protein levels upon Pseudomonas infection in a HopU1-dependent manner. Our results reveal a novel virulence strategy used by a microbial effector to interfere with host immunity.

TLR9-based immunotherapy for the treatment of allergic diseases.

PubMed

Farrokhi, Shokrollah; Abbasirad, Narjes; Movahed, Ali; Khazaei, Hossein Ali; Pishjoo, Masoud; Rezaei, Nima

2017-03-01

Toll-like receptors (TLRs), a family of pattern recognition receptors expressed on many cell types of innate immunity, recognize the pathogen-associated molecular patterns of microbes. The hygiene hypothesis suggests that a reduced microbial exposure in early childhood increases the susceptibility to allergic diseases due to deviation in development of the immune system. TLRs are key roles in the right and healthy direction of adaptive immunity with the induction of T-helper 2 toward Th1 immune responses and regulatory T cells. TLR ligand CpG-ODN-based immunomodulation is independent of allergen and it mainly affects innate immune system. While, CpG-oligodeoxynucleotide-based vaccination is allergen specific and induces adaptive immune system. The use of agonists of TLR9 in two distinct strategies of immunotherapy, immunomodulation and vaccination, could be presented as the curative method for the treatment of allergic diseases.

Ionotropic glutamate receptor (iGluR)-like channels mediate MAMP-induced calcium influx in Arabidopsis thaliana.

PubMed

Kwaaitaal, Mark; Huisman, Rik; Maintz, Jens; Reinstädler, Anja; Panstruga, Ralph

2011-12-15

Binding of specific microbial epitopes [MAMPs (microbe-associated molecular patterns)] to PRRs (pattern recognition receptors) and subsequent receptor kinase activation are key steps in plant innate immunity. One of the earliest detectable events after MAMP perception is a rapid and transient rise in cytosolic Ca2+ levels. In plants, knowledge about the signalling events leading to Ca2+ influx and on the molecular identity of the channels involved is scarce. We used a transgenic Arabidopsis thaliana line stably expressing the luminescent aequorin Ca2+ biosensor to monitor pharmacological interference with Ca2+ signatures following treatment with the bacterial peptide MAMPs flg22 and elf18, and the fungal carbohydrate MAMP chitin. Using a comprehensive set of compounds known to impede Ca2+-transport processes in plants and animals we found strong evidence for a prominent role of amino acid-controlled Ca2+ fluxes, probably through iGluR (ionotropic glutamate receptor)-like channels. Interference with amino acid-mediated Ca2+ fluxes modulates MAMP-triggered MAPK (mitogen-activated protein kinase) activity and affects MAMP-induced accumulation of defence gene transcripts. We conclude that the initiation of innate immune responses upon flg22, elf18 and chitin recognition involves apoplastic Ca2+ influx via iGluR-like channels.

Bench-to-bedside review: Toll-like receptors and their role in septic shock

PubMed Central

Opal, Steven M; Huber, Christian E

2002-01-01

The Toll-like receptors (TLRs) are essential transmembrane signaling receptors of the innate immune system that alert the host to the presence of a microbial invader. The recent discovery of the TLRs has rapidly expanded our knowledge of molecular events that initiate host–pathogen interactions. These functional attributes of the cellular receptors provide insights into the nature of pattern recognition receptors that activate the human antimicrobial defense systems. The fundamental significance of the TLRs in the generation of systemic inflammation and the pathogenesis of septic shock is reviewed. The potential clinical implications of therapeutic modulation of these recently characterized receptors of innate immunity are also discussed. PMID:11983038

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.

Sensing of dangerous DNA.

PubMed

Gasser, Stephan; Zhang, Wendy Y L; Tan, Nikki Yi Jie; Tripathi, Shubhita; Suter, Manuel A; Chew, Zhi Huan; Khatoo, Muznah; Ngeow, Joanne; Cheung, Florence S G

2017-07-01

The presence of damaged and microbial DNA can pose a threat to the survival of organisms. Cells express various sensors that recognize specific aspects of such potentially dangerous DNA. Recognition of damaged or microbial DNA by sensors induces cellular processes that are important for DNA repair and inflammation. Here, we review recent evidence that the cellular response to DNA damage and microbial DNA are tightly intertwined. We also discuss insights into the parameters that enable DNA sensors to distinguish damaged and microbial DNA from DNA present in healthy cells. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Uncoupling of microbial community structure and function in decomposing litter across beech forest ecosystems in Central Europe.

PubMed

Purahong, Witoon; Schloter, Michael; Pecyna, Marek J; Kapturska, Danuta; Däumlich, Veronika; Mital, Sanchit; Buscot, François; Hofrichter, Martin; Gutknecht, Jessica L M; Krüger, Dirk

2014-11-12

The widespread paradigm in ecology that community structure determines function has recently been challenged by the high complexity of microbial communities. Here, we investigate the patterns of and connections between microbial community structure and microbially-mediated ecological function across different forest management practices and temporal changes in leaf litter across beech forest ecosystems in Central Europe. Our results clearly indicate distinct pattern of microbial community structure in response to forest management and time. However, those patterns were not reflected when potential enzymatic activities of microbes were measured. We postulate that in our forest ecosystems, a disconnect between microbial community structure and function may be present due to differences between the drivers of microbial growth and those of microbial function.

Microbial host interactions and impaired wound healing in mice and humans: defining a role for BD14 and NOD2.

PubMed

Williams, Helen; Campbell, Laura; Crompton, Rachel A; Singh, Gurdeep; McHugh, Brian J; Davidson, Donald J; McBain, Andrew J; Cruickshank, Sheena M; Hardman, Matthew J

2018-04-30

Chronic wounds cause significant patient morbidity and mortality. A key factor in their etiology is microbial infection, yet skin host-microbiota interactions during wound repair remain poorly understood. Microbiome profiles of non-infected human chronic wounds are associated with subsequent healing outcome. Furthermore, poor clinical healing outcome was associated with increased local expression of the pattern recognition receptor NOD2. To investigate NOD2 function in the context of cutaneous healing, we treated mice with the NOD2 ligand muramyl dipeptide (MDP) and analyzed wound repair parameters and expression of anti-microbial peptides. MDP treatment of littermate controls significantly delayed wound repair associated with reduced re-epithelialization, heightened inflammation and upregulation of murine β-Defensins (mBD) 1, 3 and particularly 14. We postulated that although BD14 might impact on local skin microbial communities it may further impact other healing parameters. Indeed, exogenously administered mBD14 directly delayed mouse primary keratinocyte scratch wound closure in vitro. To further explore the role of mBD14 in wound repair, we employed Defb14 -/- mice, and showed they had a global delay in healing in vivo, associated with alterations in wound microbiota. Taken together these studies suggest a key role for NOD2-mediated regulation of local skin microbiota which in turn impacts on chronic wound etiology. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Recognition of DHN-melanin by a C-type lectin receptor is required for immunity to Aspergillus.

PubMed

Stappers, Mark H T; Clark, Alexandra E; Aimanianda, Vishukumar; Bidula, Stefan; Reid, Delyth M; Asamaphan, Patawee; Hardison, Sarah E; Dambuza, Ivy M; Valsecchi, Isabel; Kerscher, Bernhard; Plato, Anthony; Wallace, Carol A; Yuecel, Raif; Hebecker, Betty; da Glória Teixeira Sousa, Maria; Cunha, Cristina; Liu, Yan; Feizi, Ten; Brakhage, Axel A; Kwon-Chung, Kyung J; Gow, Neil A R; Zanda, Matteo; Piras, Monica; Zanato, Chiara; Jaeger, Martin; Netea, Mihai G; van de Veerdonk, Frank L; Lacerda, João F; Campos, António; Carvalho, Agostinho; Willment, Janet A; Latgé, Jean-Paul; Brown, Gordon D

2018-03-15

Resistance to infection is critically dependent on the ability of pattern recognition receptors to recognize microbial invasion and induce protective immune responses. One such family of receptors are the C-type lectins, which are central to antifungal immunity. These receptors activate key effector mechanisms upon recognition of conserved fungal cell-wall carbohydrates. However, several other immunologically active fungal ligands have been described; these include melanin, for which the mechanism of recognition is hitherto undefined. Here we identify a C-type lectin receptor, melanin-sensing C-type lectin receptor (MelLec), that has an essential role in antifungal immunity through recognition of the naphthalene-diol unit of 1,8-dihydroxynaphthalene (DHN)-melanin. MelLec recognizes melanin in conidial spores of Aspergillus fumigatus as well as in other DHN-melanized fungi. MelLec is ubiquitously expressed by CD31 + endothelial cells in mice, and is also expressed by a sub-population of these cells that co-express epithelial cell adhesion molecule and are detected only in the lung and the liver. In mouse models, MelLec was required for protection against disseminated infection with A. fumigatus. In humans, MelLec is also expressed by myeloid cells, and we identified a single nucleotide polymorphism of this receptor that negatively affected myeloid inflammatory responses and significantly increased the susceptibility of stem-cell transplant recipients to disseminated Aspergillus infections. MelLec therefore recognizes an immunologically active component commonly found on fungi and has an essential role in protective antifungal immunity in both mice and humans.

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.

Control of adaptive immunity by the innate immune system.

PubMed

Iwasaki, Akiko; Medzhitov, Ruslan

2015-04-01

Microbial infections are recognized by the innate immune system both to elicit immediate defense and to generate long-lasting adaptive immunity. To detect and respond to vastly different groups of pathogens, the innate immune system uses several recognition systems that rely on sensing common structural and functional features associated with different classes of microorganisms. These recognition systems determine microbial location, viability, replication and pathogenicity. Detection of these features by recognition pathways of the innate immune system is translated into different classes of effector responses though specialized populations of dendritic cells. Multiple mechanisms for the induction of immune responses are variations on a common design principle wherein the cells that sense infections produce one set of cytokines to induce lymphocytes to produce another set of cytokines, which in turn activate effector responses. Here we discuss these emerging principles of innate control of adaptive immunity.

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.

Probiotics drive gut microbiome triggering emotional brain signatures.

PubMed

Bagga, Deepika; Reichert, Johanna Louise; Koschutnig, Karl; Aigner, Christoph Stefan; Holzer, Peter; Koskinen, Kaisa; Eichinger, Christine Moissl; Schöpf, Veronika

2018-05-03

Experimental manipulation of the gut microbiome was found to modify emotional and cognitive behavior, neurotransmitter expression and brain function in rodents, but corresponding human data remain scarce. The present double-blind, placebo-controlled randomised study aimed at investigating the effects of 4 weeks' probiotic administration on behavior, brain function and gut microbial composition in healthy volunteers. Forty-five healthy participants divided equally into three groups (probiotic, placebo and no intervention) underwent functional MRI (emotional decision-making and emotional recognition memory tasks). In addition, stool samples were collected to investigate the gut microbial composition. Probiotic administration for 4 weeks was associated with changes in brain activation patterns in response to emotional memory and emotional decision-making tasks, which were also accompanied by subtle shifts in gut microbiome profile. Microbiome composition mirrored self-reported behavioral measures and memory performance. This is the first study reporting a distinct influence of probiotic administration at behavioral, neural, and microbiome levels at the same time in healthy volunteers. The findings provide a basis for future investigations into the role of the gut microbiota and potential therapeutic application of probiotics.

A resurgence in field research is essential to better understand the diversity, ecology, and evolution of microbial eukaryotes.

PubMed

Heger, Thierry J; Edgcomb, Virginia P; Kim, Eunsoo; Lukeš, Julius; Leander, Brian S; Yubuki, Naoji

2014-01-01

The discovery and characterization of protist communities from diverse environments are crucial for understanding the overall evolutionary history of life on earth. However, major questions about the diversity, ecology, and evolutionary history of protists remain unanswered, notably because data obtained from natural protist communities, especially of heterotrophic species, remain limited. In this review, we discuss the challenges associated with "field protistology", defined here as the exploration, characterization, and interpretation of microbial eukaryotic diversity within the context of natural environments or field experiments, and provide suggestions to help fill this important gap in knowledge. We also argue that increased efforts in field studies that combine molecular and microscopical methods offer the most promising path toward (1) the discovery of new lineages that expand the tree of eukaryotes; (2) the recognition of novel evolutionary patterns and processes; (3) the untangling of ecological interactions and functions, and their roles in larger ecosystem processes; and (4) the evaluation of protist adaptations to a changing climate. © 2013 The Author(s) Journal of Eukaryotic Microbiology © 2013 International Society of Protistologists.

Cheese rind communities provide tractable systems for in situ and in vitro studies of microbial diversity

PubMed Central

Wolfe, Benjamin E.; Button, Julie E.; Santarelli, Marcela; Dutton, Rachel J.

2014-01-01

SUMMARY Tractable microbial communities are needed to bridge the gap between observations of patterns of microbial diversity and mechanisms that can explain these patterns. We developed cheese rinds as model microbial communities by characterizing in situ patterns of diversity and by developing an in vitro system for community reconstruction. Sequencing of 137 different rind communities across 10 countries revealed 24 widely distributed and culturable genera of bacteria and fungi as dominant community members. Reproducible community types formed independent of geographic location of production. Intensive temporal sampling demonstrated that assembly of these communities is highly reproducible. Patterns of community composition and succession observed in situ can be recapitulated in a simple in vitro system. Widespread positive and negative interactions were identified between bacterial and fungal community members. Cheese rind microbial communities represent an experimentally tractable system for defining mechanisms that influence microbial community assembly and function. PMID:25036636

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques

PubMed Central

Mande, Sharmila S.

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm. PMID:27124399

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.

PubMed

Tandon, Disha; Haque, Mohammed Monzoorul; Mande, Sharmila S

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm.

Analysis of gut microbial regulation of host gene expression along the length of the gut and regulation of gut microbial ecology through MyD88.

PubMed

Larsson, Erik; Tremaroli, Valentina; Lee, Ying Shiuan; Koren, Omry; Nookaew, Intawat; Fricker, Ashwana; Nielsen, Jens; Ley, Ruth E; Bäckhed, Fredrik

2012-08-01

The gut microbiota has profound effects on host physiology but local host-microbial interactions in the gut are only poorly characterised and are likely to vary from the sparsely colonised duodenum to the densely colonised colon. Microorganisms are recognised by pattern recognition receptors such as Toll-like receptors, which signal through the adaptor molecule MyD88. To identify host responses induced by gut microbiota along the length of the gut and whether these required MyD88, transcriptional profiles of duodenum, jejunum, ileum and colon were compared from germ-free and conventionally raised wild-type and Myd88-/- mice. The gut microbial ecology was assessed by 454-based pyrosequencing and viruses were analysed by PCR. The gut microbiota modulated the expression of a large set of genes in the small intestine and fewer genes in the colon but surprisingly few microbiota-regulated genes required MyD88 signalling. However, MyD88 was essential for microbiota-induced colonic expression of the antimicrobial genes Reg3β and Reg3γ in the epithelium, and Myd88 deficiency was associated with both a shift in bacterial diversity and a greater proportion of segmented filamentous bacteria in the small intestine. In addition, conventionally raised Myd88-/- mice had increased expression of antiviral genes in the colon, which correlated with norovirus infection in the colonic epithelium. This study provides a detailed description of tissue-specific host transcriptional responses to the normal gut microbiota along the length of the gut and demonstrates that the absence of MyD88 alters gut microbial ecology.

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.

The soluble pattern recognition receptor PTX3 links humoral innate and adaptive immune responses by helping marginal zone B cells

PubMed Central

Sintes, Jordi; Polentarutti, Nadia; Walland, A. Cooper; Yeiser, John R.; Cunha, Cristina; Lacerda, João F.; Salvatori, Giovanni; Blander, J. Magarian

2016-01-01

Pentraxin 3 (PTX3) is a fluid-phase pattern recognition receptor of the humoral innate immune system with ancestral antibody-like properties but unknown antibody-inducing function. In this study, we found binding of PTX3 to splenic marginal zone (MZ) B cells, an innate-like subset of antibody-producing lymphocytes strategically positioned at the interface between the circulation and the adaptive immune system. PTX3 was released by a subset of neutrophils that surrounded the splenic MZ and expressed an immune activation–related gene signature distinct from that of circulating neutrophils. Binding of PTX3 promoted homeostatic production of IgM and class-switched IgG antibodies to microbial capsular polysaccharides, which decreased in PTX3-deficient mice and humans. In addition, PTX3 increased IgM and IgG production after infection with blood-borne encapsulated bacteria or immunization with bacterial carbohydrates. This immunogenic effect stemmed from the activation of MZ B cells through a neutrophil-regulated pathway that elicited class switching and plasmablast expansion via a combination of T cell–independent and T cell–dependent signals. Thus, PTX3 may bridge the humoral arms of the innate and adaptive immune systems by serving as an endogenous adjuvant for MZ B cells. This property could be harnessed to develop more effective vaccines against encapsulated pathogens. PMID:27621420

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

Microbial community pattern detection in human body habitats via ensemble clustering framework.

PubMed

Yang, Peng; Su, Xiaoquan; Ou-Yang, Le; Chua, Hon-Nian; Li, Xiao-Li; Ning, Kang

2014-01-01

The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome.

Microbial community pattern detection in human body habitats via ensemble clustering framework

PubMed Central

2014-01-01

Background The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. Results To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. Conclusions In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome. PMID:25521415

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.

Environmental Filtering Process Has More Important Roles than Dispersal Limitation in Shaping Large-Scale Prokaryotic Beta Diversity Patterns of Grassland Soils.

PubMed

Cao, Peng; Wang, Jun-Tao; Hu, Hang-Wei; Zheng, Yuan-Ming; Ge, Yuan; Shen, Ju-Pei; He, Ji-Zheng

2016-07-01

Despite the utmost importance of microorganisms in maintaining ecosystem functioning and their ubiquitous distribution, our knowledge of the large-scale pattern of microbial diversity is limited, particularly in grassland soils. In this study, the microbial communities of 99 soil samples spanning over 3000 km across grassland ecosystems in northern China were investigated using high-throughput sequencing to analyze the beta diversity pattern and the underlying ecological processes. The microbial communities were dominated by Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, and Planctomycetes across all the soil samples. Spearman's correlation analysis indicated that climatic factors and soil pH were significantly correlated with the dominant microbial taxa, while soil microbial richness was positively linked to annual precipitation. The environmental divergence-dissimilarity relationship was significantly positive, suggesting the importance of environmental filtering processes in shaping soil microbial communities. Structural equation modeling found that the deterministic process played a more important role than the stochastic process on the pattern of soil microbial beta diversity, which supported the predictions of niche theory. Partial mantel test analysis have showed that the contribution of independent environmental variables has a significant effect on beta diversity, while independent spatial distance has no such relationship, confirming that the deterministic process was dominant in structuring soil microbial communities. Overall, environmental filtering process has more important roles than dispersal limitation in shaping microbial beta diversity patterns in the grassland soils.

Demonstrating microbial co-occurrence pattern analyses within and between ecosystems

PubMed Central

Williams, Ryan J.; Howe, Adina; Hofmockel, Kirsten S.

2014-01-01

Co-occurrence patterns are used in ecology to explore interactions between organisms and environmental effects on coexistence within biological communities. Analysis of co-occurrence patterns among microbial communities has ranged from simple pairwise comparisons between all community members to direct hypothesis testing between focal species. However, co-occurrence patterns are rarely studied across multiple ecosystems or multiple scales of biological organization within the same study. Here we outline an approach to produce co-occurrence analyses that are focused at three different scales: co-occurrence patterns between ecosystems at the community scale, modules of co-occurring microorganisms within communities, and co-occurring pairs within modules that are nested within microbial communities. To demonstrate our co-occurrence analysis approach, we gathered publicly available 16S rRNA amplicon datasets to compare and contrast microbial co-occurrence at different taxonomic levels across different ecosystems. We found differences in community composition and co-occurrence that reflect environmental filtering at the community scale and consistent pairwise occurrences that may be used to infer ecological traits about poorly understood microbial taxa. However, we also found that conclusions derived from applying network statistics to microbial relationships can vary depending on the taxonomic level chosen and criteria used to build co-occurrence networks. We present our statistical analysis and code for public use in analysis of co-occurrence patterns across microbial communities. PMID:25101065

GIS-based analysis of drinking-water supply structures: a module for microbial risk assessment.

PubMed

Kistemann, T; Herbst, S; Dangendorf, F; Exner, M

2001-05-01

Water-related infections constitute an important health impact world-wide. A set of tools serving for Microbial Risk Assessment (MRA) of waterborne diseases should comprise the entire drinking-water management system and take into account the Hazard Analysis and Critical Control Point (HACCP) concept which provides specific Critical Control Points (CCPs) reflecting each step of drinking-water provision. A Geographical Information System (GIS) study concerning water-supply structure (WSS) was conducted in the Rhein-Berg District (North Rhine-Westphalia, Germany). As a result, suitability of the existing water databases HYGRIS (hydrological basis geo-information system) and TEIS (drinking-water recording and information system) for the development of a WSS-GIS module could be demonstrated. Spatial patterns within the integrated raw and drinking-water data can easily be uncovered by GIS-specific options. The application of WSS-GIS allows a rapid visualization and analysis of drinking-water supply structure and offers huge advantages concerning microbial monitoring of raw and drinking water as well as recognition and investigation of incidents and outbreaks. Increasing requests regarding health protection and health reporting, demands for a better outbreak management and water-related health impacts of global climate change are major challenges of future water management to be tackled with methods including spatial analysis. GIS is assumed to be a very useful tool to meet these requirements.

Type II NKT Cells in Inflammation, Autoimmunity, Microbial Immunity, and Cancer

PubMed Central

Marrero, Idania; Ware, Randle; Kumar, Vipin

2015-01-01

Natural killer T cells (NKT) recognize self and microbial lipid antigens presented by non-polymorphic CD1d molecules. Two major NKT cell subsets, type I and II, express different types of antigen receptors (TCR) with distinct mode of CD1d/lipid recognition. Though type II NKT cells are less frequent in mice and difficult to study, they are predominant in human. One of the major subsets of type II NKT cells reactive to the self-glycolipid sulfatide is the best characterized and has been shown to induce a dominant immune regulatory mechanism that controls inflammation in autoimmunity and in anti-cancer immunity. Recently, type II NKT cells reactive to other self-glycolipids and phospholipids have been identified suggesting both promiscuous and specific TCR recognition in microbial immunity as well. Since the CD1d pathway is highly conserved, a detailed understanding of the biology and function of type II NKT cells as well as their interplay with type I NKT cells or other innate and adaptive T cells will have major implications for potential novel interventions in inflammatory and autoimmune diseases, microbial immunity, and cancer. PMID:26136748

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 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.

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.

Microbial colonization and lung function in adolescents with cystic fibrosis.

PubMed

Hector, Andreas; Kirn, Tobias; Ralhan, Anjali; Graepler-Mainka, Ute; Berenbrinker, Sina; Riethmueller, Joachim; Hogardt, Michael; Wagner, Marlies; Pfleger, Andreas; Autenrieth, Ingo; Kappler, Matthias; Griese, Matthias; Eber, Ernst; Martus, Peter; Hartl, Dominik

2016-05-01

With intensified antibiotic therapy and longer survival, patients with cystic fibrosis (CF) are colonized with a more complex pattern of bacteria and fungi. However, the clinical relevance of these emerging pathogens for lung function remains poorly defined. The aim of this study was to assess the association of bacterial and fungal colonization patterns with lung function in adolescent patients with CF. Microbial colonization patterns and lung function parameters were assessed in 770 adolescent European (German/Austrian) CF patients in a retrospective study (median follow-up time: 10years). Colonization with Pseudomonas aeruginosa and MRSA were most strongly associated with loss of lung function, while mainly colonization with Haemophilus influenzae was associated with preserved lung function. Aspergillus fumigatus was the only species that was associated with an increased risk for infection with P. aeruginosa. Microbial interaction analysis revealed three distinct microbial clusters within the longitudinal course of CF lung disease. Collectively, this study identified potentially protective and harmful microbial colonization patterns in adolescent CF patients. Further studies in different patient cohorts are required to evaluate these microbial patterns and to assess their clinical relevance. Copyright © 2016 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

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.

Host gene-microbiome interactions: molecular mechanisms in inflammatory bowel disease.

PubMed

Chu, Hiutung

2017-07-24

Recent studies have identified links between host genetic variants and microbial recognition of the microbiome. Defects in host-microbiome interactions in individuals harboring inflammatory bowel disease risk alleles may result in imbalances of the microbial community, impaired pathogen clearance, and failure to sense beneficial commensal microbes. These findings highlight the importance of maintaining bi-directional communication at the mucosal interface during intestinal homeostasis.

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.

Tomato Prenylated RAB Acceptor Protein 1 Modulates Trafficking and Degradation of the Pattern Recognition Receptor LeEIX2, Affecting the Innate Immune Response

PubMed Central

Pizarro, Lorena; Leibman-Markus, Meirav; Schuster, Silvia; Bar, Maya; Meltz, Tal; Avni, Adi

2018-01-01

Plants recognize microbial/pathogen associated molecular patterns (MAMP/PAMP) through pattern recognition receptors (PRRs) triggering an immune response against pathogen progression. MAMP/PAMP triggered immune response requires PRR endocytosis and trafficking for proper deployment. LeEIX2 is a well-known Solanum lycopersicum RLP-PRR, able to recognize and respond to the fungal MAMP/PAMP ethylene-inducing xylanase (EIX), and its function is highly dependent on intracellular trafficking. Identifying protein machinery components regulating LeEIX2 intracellular trafficking is crucial to our understanding of LeEIX2 mediated immune responses. In this work, we identified a novel trafficking protein, SlPRA1A, a predicted regulator of RAB, as an interactor of LeEIX2. Overexpression of SlPRA1A strongly decreases LeEIX2 endosomal localization, as well as LeEIX2 protein levels. Accordingly, the innate immune responses to EIX are markedly reduced by SlPRA1A overexpression, presumably due to a decreased LeEIX2 availability. Studies into the role of SlPRA1A in LeEIX2 trafficking revealed that LeEIX2 localization in multivesicular bodies/late endosomes is augmented by SlPRA1A. Furthermore, inhibiting vacuolar function prevents the LeEIX2 protein level reduction mediated by SlPRA1A, suggesting that SlPRA1A may redirect LeEIX2 trafficking to the vacuole for degradation. Interestingly, SlPRA1A overexpression reduces the amount of several RLP-PRRs, but does not affect the protein level of receptor-like kinase PRRs, suggesting a specific role of SlPRA1A in RLP-PRR trafficking and degradation. PMID:29545816

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

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.

Evasion Mechanisms Used by Pathogens to Escape the Lectin Complement Pathway.

PubMed

Rosbjerg, Anne; Genster, Ninette; Pilely, Katrine; Garred, Peter

2017-01-01

The complement system is a crucial defensive network that protects the host against invading pathogens. It is part of the innate immune system and can be initiated via three pathways: the lectin, classical and alternative activation pathway. Overall the network compiles a group of recognition molecules that bind specific patterns on microbial surfaces, a group of associated proteases that initiates the complement cascade, and a group of proteins that interact in proteolytic complexes or the terminal pore-forming complex. In addition, various regulatory proteins are important for controlling the level of activity. The result is a pro-inflammatory response meant to combat foreign microbes. Microbial elimination is, however, not a straight forward procedure; pathogens have adapted to their environment by evolving a collection of evasion mechanisms that circumvent the human complement system. Complement evasion strategies features different ways of exploiting human complement proteins and moreover features different pathogen-derived proteins that interfere with the normal processes. Accumulated, these mechanisms target all three complement activation pathways as well as the final common part of the cascade. This review will cover the currently known lectin pathway evasion mechanisms and give examples of pathogens that operate these to increase their chance of invasion, survival and dissemination.

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

Commensal-Associated Molecular Patterns Induce Selective Toll-Like Receptor-Trafficking from Apical Membrane to Cytoplasmic Compartments in Polarized Intestinal Epithelium

PubMed Central

Cario, Elke; Brown, Dennis; McKee, Mary; Lynch-Devaney, Kathryn; Gerken, Guido; Podolsky, Daniel K.

2002-01-01

Commensal-associated molecular patterns, the major products of nonpathogenic bacteria, are present at high concentrations at the apical surface of the intestinal epithelium. However, the nature of the interaction of commensal-associated molecular patterns with the lumenal surface of the epithelium has not been defined. We have recently demonstrated that intestinal epithelial cells constitutively express several Toll-like receptors (TLRs) in vitro and in vivo that seem to be the key receptors responsible for immune cell activation in response to various bacterial products. In this study we characterize the subcellular distribution of two major TLRs, TLR2 and TLR4, and their ligand-specific dynamic regulation in the model human intestinal epithelial cell line T84. Immunocytochemical studies indicate that TLR2 and TLR4 are constitutively expressed at the apical pole of differentiated T84 cells. After stimulation with lipopolysaccharide or peptidoglycan, TLRs selectively traffic to cytoplasmic compartments near the basolateral membrane. Thus, we demonstrate that TLRs are positioned at the apical pole where they are poised to monitor the sensitive balance of the lumenal microbial array. The results of this dynamic epithelial surveillance can then be conveyed to the underlying cell populations of the lamina propria via these innate immune pattern recognition receptors. PMID:11786410

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.

Bacterial Stimulation of Toll-Like Receptor 4 Drives Macrophages To Hemophagocytose

PubMed Central

McDonald, Erin M.; Pilonieta, M. Carolina; Nick, Heidi J.

2015-01-01

During acute infection with bacteria, viruses or parasites, a fraction of macrophages engulf large numbers of red and white blood cells, a process called hemophagocytosis. Hemophagocytes persist into the chronic stage of infection and have an anti-inflammatory phenotype. Salmonella enterica serovar Typhimurium infection of immunocompetent mice results in acute followed by chronic infection, with the accumulation of hemophagocytes. The mechanism(s) that triggers a macrophage to become hemophagocytic is unknown, but it has been reported that the proinflammatory cytokine gamma interferon (IFN-γ) is responsible. We show that primary macrophages become hemophagocytic in the absence or presence of IFN-γ upon infection with Gram-negative bacterial pathogens or prolonged exposure to heat-killed Salmonella enterica, the Gram-positive bacterium Bacillus subtilis, or Mycobacterium marinum. Moreover, conserved microbe-associated molecular patterns are sufficient to stimulate macrophages to hemophagocytose. Purified bacterial lipopolysaccharide (LPS) induced hemophagocytosis in resting and IFN-γ-pretreated macrophages, whereas lipoteichoic acid and synthetic unmethylated deoxycytidine-deoxyguanosine dinucleotides, which mimic bacterial DNA, induced hemophagocytosis only in IFN-γ-pretreated macrophages. Chemical inhibition or genetic deletion of Toll-like receptor 4, a pattern recognition receptor responsive to LPS, prevented both Salmonella- and LPS-stimulated hemophagocytosis. Inhibition of NF-κB also prevented hemophagocytosis. These results indicate that recognition of microbial products by Toll-like receptors stimulates hemophagocytosis, a novel outcome of prolonged Toll-like receptor signaling, suggesting hemophagocytosis is a highly conserved innate immune response. PMID:26459510

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.

New insights into the role of siderophores as triggers of plant immunity: what can we learn from animals?

PubMed

Aznar, Aude; Dellagi, Alia

2015-06-01

Microorganisms use siderophores to obtain iron from the environment. In pathogenic interactions, siderophores are involved in iron acquisition from the host and are sometimes necessary for the expression of full virulence. This review summarizes the main data describing the role of these iron scavengers in animal and plant defence systems. To protect themselves against iron theft, mammalian hosts have developed a hypoferremia strategy that includes siderophore-binding molecules called siderocalins. In addition to microbial ferri-siderophore sequestration, siderocalins are involved in triggering immunity. In plants, no similar mechanisms have been described and many fewer data are available, although recent advances have shed light on the role of siderophores in plant-pathogen interactions. Siderophores can trigger immunity in plants in several contexts. The most frequently described situation involving siderophores is induced systemic resistance (ISR) triggered by plant-growth-promoting rhizobacteria. Although ISR responses have been observed after treating roots with certain siderophores, the underlying mechanisms are poorly understood. Immunity can also be triggered by siderophores in leaves. Siderophore perception in plants appears to be different from the well-known perception mechanisms of other microbial compounds, known as microbe-associated molecular patterns. Scavenging iron per se appears to be a novel mechanism of immunity activation, involving complex disturbance of metal homeostasis. Receptor-specific recognition of siderophores has been described in animals, but not in plants. The review closes with an overview of the possible mechanisms of defence activation, via iron scavenging by siderophores or specific siderophore recognition by the plant host. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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.

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.

Dynamical footprint of cross-reactivity in a human autoimmune T-cell receptor

NASA Astrophysics Data System (ADS)

Kumar, Amit; Delogu, Francesco

2017-02-01

The present work focuses on the dynamical aspects of cross-reactivity between myelin based protein (MBP) self-peptide and two microbial peptides (UL15, PMM) for Hy.1B11 T-cell receptor (TCR). This same TCR was isolated from a patient suffering from multiple sclerosis (MS). The study aims at highlighting the chemical interactions underlying recognition mechanisms between TCR and the peptides presented by Major Histocompatibility Complex (MHC) proteins, which form a crucial component in adaptive immune response against foreign antigens. Since the ability of a TCR to recognize different peptide antigens presented by MHC depends on its cross-reactivity, we used molecular dynamics methods to obtain atomistic detail on TCR-peptide-MHC complexes. Our results show how the dynamical basis of Hy.1B11 TCR’s cross-reactivity is rooted in a similar bridging interaction pattern across the TCR-peptide-MHC interface. Our simulations confirm the importance of TCR CDR3α E98 residue interaction with MHC and a predominant role of P6 peptide residue in MHC binding affinity. Altogether, our study provides energetic and dynamical insights into factors governing peptide recognition by the cross-reactive Hy.1B11 TCR, found in MS patient.

Influence of aeolian activities on the distribution of microbial abundance in glacier ice

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, X.-K.; Si, J.; Wu, G.-J.; Tian, L.-D.; Xiang, S.-R.

2014-10-01

Microorganisms are continuously blown onto the glacier snow, and thus the glacial depth profiles provide excellent archives of microbial communities and climatic and environmental changes. However, it is uncertain about how aeolian processes that cause climatic changes control the distribution of microorganisms in the glacier ice. In the present study, microbial density, stable isotopic ratios, 18O / 16O in the precipitation, and mineral particle concentrations along the glacial depth profiles were collected from ice cores from the Muztag Ata glacier and the Dunde ice cap. The ice core data showed that microbial abundance was often, but not always associated with high concentrations of particles. Results also revealed clear seasonal patterning with high microbial abundance occurring in both the cooling autumn and warming spring-summer seasons. Microbial comparisons among the neighbouring glaciers display a heterogeneous spatial pattern, with the highest microbial cell density in the glaciers lying adjacent to the central Asian deserts and lowest microbial density in the southwestern margin of the Tibetan Plateau. In conclusion, microbial data of the glaciers indicates the aeolian deposits of microorganisms in the glacier ice and that the spatial patterns of microorgansisms are related to differences in sources of microbial flux and intensity of aeolian activities in the current regions. The results strongly support our hypothesis of aeolian activities being the main agents controlling microbial load in the glacier ice.

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

Research-derived insights into surface geochemical hydrocarbon exploration

USGS Publications Warehouse

Price, L.C.

1996-01-01

Research studies based on foreland basins (mainly in eastern Colorado) examined three surface geochemical exploration (SGE) methods as possible hydrocarbon (HC) exploration techniques. The first method, microbial soil surveying, has high potential as an exploration tool, especially hi development and enhanced recovery operations. Integrative adsorption, the second technique, is not effective as a quantitative SGE method because water, carbon dioxide, nitrous oxide, unsaturated hydrocarbons, and organic compounds are collected by the adsorbent (activated charcoal) much more strongly than covalently bonded microseeping Q-Cs thermogenic HCs. Qualitative comparisons (pattern recognition) of C8+ mass spectra cannot gauge HC gas microseepage that involves only the Q-Cs HCs. The third method, soil cakite surveying, also has no potential as an exploration tool. Soil calcite concentrations had patterns with pronounced areal contrasts, but these patterns had no geometric relationship to surface traces of established or potential production, that is, the patterns were random. Microscopic examination of thousands of soils revealed that soil calcite was an uncrystallized caliche coating soil particles. During its precipitation, caliche captures or occludes any gases, elements, or compounds in its immediate vicinity. Thus, increased signal intensity of some SGE methods should depend on increasing soil calcite concentrations. Analyses substantiate this hypothesis. Because soil calcite has no utility as a surface exploration tool, any surface method that depends on soil calcite has a diminished utility as an SGE tool. Isotopic analyses of soil calcites revealed carbonate carbon ??13C values of -4.0 to +2.07co (indicating a strong influence of atmospheric CO2) as opposed to expected values of-45 to -30%c if the carbonate carbon had originated from microbial oxidation of microseeping HC gases. These analyses confirm a surface origin for this soil calcite (caliche), which is not necessarily related to HC gas microseepage. This previously unappreciated pivotal role of caliche is hypothesized to contribute significantly to the poor and inconsistent results of some SGE methods.

Lectins of beneficial microbes: system organisation, functioning and functional superfamily.

PubMed

Lakhtin, M; Lakhtin, V; Alyoshkin, V; Afanasyev, S

2011-06-01

In this review our last results and proposals with respect to general aspects of lectin studies are summarised and compared. System presence, organisation and functioning of lectins are proposed, and accents on beneficial symbiotic microbial lectins studies are presented. The proposed general principles of lectin functioning allows for a comparison of lectins with other carbohydrate-recognition systems. A new structure-functional superfamily of symbiotic microbial lectins is proposed and its main properties are described. The proposed superfamily allows for extended searches of the biological activities of any microbial member. Prospects of lectins of beneficial symbiotic microorganisms are discussed.

Trophic interactions induce spatial self-organization of microbial consortia on rough surfaces.

PubMed

Wang, Gang; Or, Dani

2014-10-24

The spatial context of microbial interactions common in natural systems is largely absent in traditional pure culture-based microbiology. The understanding of how interdependent microbial communities assemble and coexist in limited spatial domains remains sketchy. A mechanistic model of cell-level interactions among multispecies microbial populations grown on hydrated rough surfaces facilitated systematic evaluation of how trophic dependencies shape spatial self-organization of microbial consortia in complex diffusion fields. The emerging patterns were persistent irrespective of initial conditions and resilient to spatial and temporal perturbations. Surprisingly, the hydration conditions conducive for self-assembly are extremely narrow and last only while microbial cells remain motile within thin aqueous films. The resulting self-organized microbial consortia patterns could represent optimal ecological templates for the architecture that underlie sessile microbial colonies on natural surfaces. Understanding microbial spatial self-organization offers new insights into mechanisms that sustain small-scale soil microbial diversity; and may guide the engineering of functional artificial microbial consortia.

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.

Microbial biogeography: putting microorganisms on the map.

PubMed

Martiny, Jennifer B Hughes; Bohannan, Brendan J M; Brown, James H; Colwell, Robert K; Fuhrman, Jed A; Green, Jessica L; Horner-Devine, M Claire; Kane, Matthew; Krumins, Jennifer Adams; Kuske, Cheryl R; Morin, Peter J; Naeem, Shahid; Ovreås, Lise; Reysenbach, Anna-Louise; Smith, Val H; Staley, James T

2006-02-01

We review the biogeography of microorganisms in light of the biogeography of macroorganisms. A large body of research supports the idea that free-living microbial taxa exhibit biogeographic patterns. Current evidence confirms that, as proposed by the Baas-Becking hypothesis, 'the environment selects' and is, in part, responsible for spatial variation in microbial diversity. However, recent studies also dispute the idea that 'everything is everywhere'. We also consider how the processes that generate and maintain biogeographic patterns in macroorganisms could operate in the microbial world.

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.

Ecological Patterns Among Bacteria and Microbial Eukaryotes Derived from Network Analyses in a Low-Salinity Lake.

PubMed

Jones, Adriane Clark; Hambright, K David; Caron, David A

2018-05-01

Microbial communities are comprised of complex assemblages of highly interactive taxa. We employed network analyses to identify and describe microbial interactions and co-occurrence patterns between microbial eukaryotes and bacteria at two locations within a low salinity (0.5-3.5 ppt) lake over an annual cycle. We previously documented that the microbial diversity and community composition within Lake Texoma, southwest USA, were significantly affected by both seasonal forces and a site-specific bloom of the harmful alga, Prymnesium parvum. We used network analyses to answer ecological questions involving both the bacterial and microbial eukaryotic datasets and to infer ecological relationships within the microbial communities. Patterns of connectivity at both locations reflected the seasonality of the lake including a large rain disturbance in May, while a comparison of the communities between locations revealed a localized response to the algal bloom. A network built from shared nodes (microbial operational taxonomic units and environmental variables) and correlations identified conserved associations at both locations within the lake. Using network analyses, we were able to detect disturbance events, characterize the ecological extent of a harmful algal bloom, and infer ecological relationships not apparent from diversity statistics alone.

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.

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.

Innate immune memory in plants.

PubMed

Reimer-Michalski, Eva-Maria; Conrath, Uwe

2016-08-01

The plant innate immune system comprises local and systemic immune responses. Systemic plant immunity develops after foliar infection by microbial pathogens, upon root colonization by certain microbes, or in response to physical injury. The systemic plant immune response to localized foliar infection is associated with elevated levels of pattern-recognition receptors, accumulation of dormant signaling enzymes, and alterations in chromatin state. Together, these systemic responses provide a memory to the initial infection by priming the remote leaves for enhanced defense and immunity to reinfection. The plant innate immune system thus builds immunological memory by utilizing mechanisms and components that are similar to those employed in the trained innate immune response of jawed vertebrates. Therefore, there seems to be conservation, or convergence, in the evolution of innate immune memory in plants and vertebrates. Copyright © 2016 Elsevier Ltd. All rights reserved.

Testicular defense systems: immune privilege and innate immunity

PubMed Central

Zhao, Shutao; Zhu, Weiwei; Xue, Shepu; Han, Daishu

2014-01-01

The mammalian testis possesses a special immunological environment because of its properties of remarkable immune privilege and effective local innate immunity. Testicular immune privilege protects immunogenic germ cells from systemic immune attack, and local innate immunity is important in preventing testicular microbial infections. The breakdown of local testicular immune homeostasis may lead to orchitis, an etiological factor of male infertility. The mechanisms underlying testicular immune privilege have been investigated for a long time. Increasing evidence shows that both a local immunosuppressive milieu and systemic immune tolerance are involved in maintaining testicular immune privilege status. The mechanisms underlying testicular innate immunity are emerging based on the investigation of the pattern recognition receptor-mediated innate immune response in testicular cells. This review summarizes our current understanding of testicular defense mechanisms and identifies topics that merit further investigation. PMID:24954222

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.

Research advances on microbial genetics in China in 2015.

PubMed

Xie, Jian-ping; Han, Yu-bo; Liu, Gang; Bai, Lin-quan

2016-09-01

In 2015, there are significant progresses in many aspects of the microbial genetics in China. To showcase the contribution of Chinese scientists in microbial genetics, this review surveys several notable progresses in microbial genetics made largely by Chinese scientists, and some key findings are highlighted. For the basic microbial genetics, the components, structures and functions of many macromolecule complexes involved in gene expression regulation have been elucidated. Moreover, the molecular basis underlying the recognition of foreign nucleic acids by microbial immune systems was unveiled. We also illustrated the biosynthetic pathways and regulators of multiple microbial compounds, novel enzyme reactions, and new mechanisms regulating microbial gene expression. And new findings were obtained in the microbial development, evolution and population genetics. For the industrial microbiology, more understanding on the molecular basis of the microbial factory has been gained. For the pathogenic microbiology, the genetic circuits of several pathogens were depicted, and significant progresses were achieved for understanding the pathogen-host interaction and revealing the genetic mechanisms underlying antimicrobial resistance, emerging pathogens and environmental microorganisms at the genomic level. In future, the genetic diversity of microbes can be used to obtain specific products, while gut microbiome is gathering momentum.

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

Phylogenetic factorization of compositional data yields lineage-level associations in microbiome datasets.

PubMed

Washburne, Alex D; Silverman, Justin D; Leff, Jonathan W; Bennett, Dominic J; Darcy, John L; Mukherjee, Sayan; Fierer, Noah; David, Lawrence A

2017-01-01

Marker gene sequencing of microbial communities has generated big datasets of microbial relative abundances varying across environmental conditions, sample sites and treatments. These data often come with putative phylogenies, providing unique opportunities to investigate how shared evolutionary history affects microbial abundance patterns. Here, we present a method to identify the phylogenetic factors driving patterns in microbial community composition. We use the method, "phylofactorization," to re-analyze datasets from the human body and soil microbial communities, demonstrating how phylofactorization is a dimensionality-reducing tool, an ordination-visualization tool, and an inferential tool for identifying edges in the phylogeny along which putative functional ecological traits may have arisen.

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.

Seasonality and vertical structure of microbial communities in an ocean gyre.

PubMed

Treusch, Alexander H; Vergin, Kevin L; Finlay, Liam A; Donatz, Michael G; Burton, Robert M; Carlson, Craig A; Giovannoni, Stephen J

2009-10-01

Vertical, seasonal and geographical patterns in ocean microbial communities have been observed in many studies, but the resolution of community dynamics has been limited by the scope of data sets, which are seldom up to the task of illuminating the highly structured and rhythmic patterns of change found in ocean ecosystems. We studied vertical and temporal patterns in the microbial community composition in a set of 412 samples collected from the upper 300 m of the water column in the northwestern Sargasso Sea, on cruises between 1991 and 2004. The region sampled spans the extent of deep winter mixing and the transition between the euphotic and the upper mesopelagic zones, where most carbon fixation and reoxidation occurs. A bioinformatic pipeline was developed to de-noise, normalize and align terminal restriction fragment length polymorphism (T-RFLP) data from three restriction enzymes and link T-RFLP peaks to microbial clades. Non-metric multidimensional scaling statistics resolved three microbial communities with distinctive composition during seasonal stratification: a surface community in the region of lowest nutrients, a deep chlorophyll maximum community and an upper mesopelagic community. A fourth microbial community was associated with annual spring blooms of eukaryotic phytoplankton that occur in the northwestern Sargasso Sea as a consequence of winter convective mixing that entrains nutrients to the surface. Many bacterial clades bloomed in seasonal patterns that shifted with the progression of stratification. These richly detailed patterns of community change suggest that highly specialized adaptations and interactions govern the success of microbial populations in the oligotrophic ocean.

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.

Compositions and Methods for the Treatment of Pierce's Disease

DOEpatents

Gupta, Goutam

2008-10-07

Chimeric anti-microbial proteins, compositions, and methods for the therapeutic and prophylactic treatment of plant diseases caused by the bacterial pathogen Xylella fastidiosa are provided. The anti-microbial proteins of the invention generally comprise a surface recognition domain polypeptide, capable of binding to a bacterial membrane component, fused to a bacterial lysis domain polypeptide, capable of affecting lysis or rupture of the bacterial membrane, typically via a fused polypeptide linker. In particular, methods and compositions for the treatment or prevention of Pierce's disease of grapevines are provided. Methods for the generation of transgenic Vitus vinefera plants expressing xylem-secreted anti-microbial chimeras are also provided.

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.

Microbial eukaryotic distributions and diversity patterns in a deep-sea methane seep ecosystem.

PubMed

Pasulka, Alexis L; Levin, Lisa A; Steele, Josh A; Case, David H; Landry, Michael R; Orphan, Victoria J

2016-09-01

Although chemosynthetic ecosystems are known to support diverse assemblages of microorganisms, the ecological and environmental factors that structure microbial eukaryotes (heterotrophic protists and fungi) are poorly characterized. In this study, we examined the geographic, geochemical and ecological factors that influence microbial eukaryotic composition and distribution patterns within Hydrate Ridge, a methane seep ecosystem off the coast of Oregon using a combination of high-throughput 18S rRNA tag sequencing, terminal restriction fragment length polymorphism fingerprinting, and cloning and sequencing of full-length 18S rRNA genes. Microbial eukaryotic composition and diversity varied as a function of substrate (carbonate versus sediment), activity (low activity versus active seep sites), sulfide concentration, and region (North versus South Hydrate Ridge). Sulfide concentration was correlated with changes in microbial eukaryotic composition and richness. This work also revealed the influence of oxygen content in the overlying water column and water depth on microbial eukaryotic composition and diversity, and identified distinct patterns from those previously observed for bacteria, archaea and macrofauna in methane seep ecosystems. Characterizing the structure of microbial eukaryotic communities in response to environmental variability is a key step towards understanding if and how microbial eukaryotes influence seep ecosystem structure and function. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Microbial Fossils from Terrestrial Subsurface Hydrothermal Environments: Examples and Implications for Mars

NASA Technical Reports Server (NTRS)

Hofmann, Beda A.; Farmer, Jack; Chang, Sherwood (Technical Monitor)

1997-01-01

The recognition of biological signatures in ancient epithermal deposits has special relevance for studies of early blaspheme evolution and in exploring for past life on Mars. Recently, proposals for the existence of an extensive subsurface blaspheme on Earth, dominated by chemoautotrophic microbial life, has gained prominence. However, reports of fossilized microbial remains, or biosedimentary structures (e.g. stromatolites) from the deposits of ancient subsurface systems, are rare. Microbial preservation is favoured where high population densities co-exist with rapid mineral precipitation. Near-surface epithetical systems with strong gradients in temperature and redox are good candidates for the abundant growth and fossilization of microorganisms, and are also favorable environments for the precipitation of ore minerals. Therefore, we might expect microbial remain, to be particularly well preserved in various kinds of hydrothermal and diagenetic mineral precipitates that formed below the upper temperature limit for life (approx. 120 C).

A bacterial tyrosine phosphatase inhibits plant pattern recognition receptor activation

USDA-ARS?s Scientific Manuscript database

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

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

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

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

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

Infrared face recognition based on LBP histogram and KW feature selection

NASA Astrophysics Data System (ADS)

Xie, Zhihua

2014-07-01

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

2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

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

Optical Pattern Recognition for Missile Guidance.

DTIC Science & Technology

1982-11-15

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

Microbial functional diversity plays an important role in the degradation of polyhydroxybutyrate (PHB) in soil.

PubMed

Dey, Samrat; Tribedi, Prosun

2018-03-01

Towards bioremediation of recalcitrant materials like synthetic polymer, soil has been recognized as a traditional site for disposal and subsequent degradation as some microorganisms in soil can degrade the polymer in a non-toxic, cost-effective, and environment friendly way. Microbial functional diversity is a constituent of biodiversity that includes wide range of metabolic activities that can influence numerous aspects of ecosystem functioning like ecosystem stability, nutrient availability, ecosystem dynamics, etc. Thus, in the current study, we assumed that microbial functional diversity could play an important role in polymer degradation in soil. To verify this hypothesis, we isolated soil from five different sites of landfill and examined several microbiological parameters wherein we observed a significant variation in heterotrophic microbial count as well as microbial activities among the soil microcosms tested. Multivariate analysis (principle component analysis) based on the carbon sources utilization pattern revealed that soil microcosms showed different metabolic patterns suggesting the variable distribution of microorganisms among the soil microcosms tested. Since microbial functional diversity depends on both microbial richness and evenness, Shannon diversity index was determined to measure microbial richness and Gini coefficient was determined to measure microbial evenness. The tested soil microcosms exhibited variation in both microbial richness and evenness suggesting the considerable difference in microbial functional diversity among the tested microcosms. We then measured polyhydroxybutyrate (PHB) degradation in soil microcosms after desired period of incubation of PHB in soil wherein we found that soil microcosms having higher functional diversity showed enhanced PHB degradation and soil microcosms having lower functional diversity showed reduced PHB degradation. We also noticed that all the tested soil microcosms showed similar pattern in both microbial functional diversity and PHB degradation suggesting a strong positive correlation ( r  = 0.95) between microbial functional diversity and PHB degradation. Thus, the results demonstrate that microbial functional diversity plays an important role in PHB degradation in soil by exhibiting versatile microbial metabolic potentials that lead to the enhanced degradation of PHB.

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…

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...

Patterns of Nitrogen Fixation and Related Genetic Diversity (nifH) in Microbial Mats and Stromatolites from Different Environments

NASA Astrophysics Data System (ADS)

Beltrán, Y. Y.; Centeno, C.; Falcón, L. I.

2010-04-01

We want to estimate the patterns of nitrogen fixation and the related genetic diversity (nifH) of microbial mats and microbialites on dial and temporal scales along a physicochemical and geographical gradient.

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

Patterns and Processes of Microbial Community Assembly

PubMed Central

Schmidt, Steven K.; Fukami, Tadashi; O'Neill, Sean P.; Bilinski, Teresa M.; Stanish, Lee F.; Knelman, Joseph E.; Darcy, John L.; Lynch, Ryan C.; Wickey, Phillip; Ferrenberg, Scott

2013-01-01

SUMMARY Recent research has expanded our understanding of microbial community assembly. However, the field of community ecology is inaccessible to many microbial ecologists because of inconsistent and often confusing terminology as well as unnecessarily polarizing debates. Thus, we review recent literature on microbial community assembly, using the framework of Vellend (Q. Rev. Biol. 85:183–206, 2010) in an effort to synthesize and unify these contributions. We begin by discussing patterns in microbial biogeography and then describe four basic processes (diversification, dispersal, selection, and drift) that contribute to community assembly. We also discuss different combinations of these processes and where and when they may be most important for shaping microbial communities. The spatial and temporal scales of microbial community assembly are also discussed in relation to assembly processes. Throughout this review paper, we highlight differences between microbes and macroorganisms and generate hypotheses describing how these differences may be important for community assembly. We end by discussing the implications of microbial assembly processes for ecosystem function and biodiversity. PMID:24006468

Divergence in plant and microbial allocation strategies explains continental patterns in microbial allocation and biogeochemical fluxes.

PubMed

Averill, Colin

2014-10-01

Allocation trade-offs shape ecological and biogeochemical phenomena at local to global scale. Plant allocation strategies drive major changes in ecosystem carbon cycling. Microbial allocation to enzymes that decompose carbon vs. organic nutrients may similarly affect ecosystem carbon cycling. Current solutions to this allocation problem prioritise stoichiometric tradeoffs implemented in plant ecology. These solutions may not maximise microbial growth and fitness under all conditions, because organic nutrients are also a significant carbon resource for microbes. I created multiple allocation frameworks and simulated microbial growth using a microbial explicit biogeochemical model. I demonstrate that prioritising stoichiometric trade-offs does not optimise microbial allocation, while exploiting organic nutrients as carbon resources does. Analysis of continental-scale enzyme data supports the allocation patterns predicted by this framework, and modelling suggests large deviations in soil C loss based on which strategy is implemented. Therefore, understanding microbial allocation strategies will likely improve our understanding of carbon cycling and climate. © 2014 John Wiley & Sons Ltd/CNRS.

Evasion Mechanisms Used by Pathogens to Escape the Lectin Complement Pathway

PubMed Central

Rosbjerg, Anne; Genster, Ninette; Pilely, Katrine; Garred, Peter

2017-01-01

The complement system is a crucial defensive network that protects the host against invading pathogens. It is part of the innate immune system and can be initiated via three pathways: the lectin, classical and alternative activation pathway. Overall the network compiles a group of recognition molecules that bind specific patterns on microbial surfaces, a group of associated proteases that initiates the complement cascade, and a group of proteins that interact in proteolytic complexes or the terminal pore-forming complex. In addition, various regulatory proteins are important for controlling the level of activity. The result is a pro-inflammatory response meant to combat foreign microbes. Microbial elimination is, however, not a straight forward procedure; pathogens have adapted to their environment by evolving a collection of evasion mechanisms that circumvent the human complement system. Complement evasion strategies features different ways of exploiting human complement proteins and moreover features different pathogen-derived proteins that interfere with the normal processes. Accumulated, these mechanisms target all three complement activation pathways as well as the final common part of the cascade. This review will cover the currently known lectin pathway evasion mechanisms and give examples of pathogens that operate these to increase their chance of invasion, survival and dissemination. PMID:28553281

Graft-versus-host disease: regulation by microbe-associated molecules and innate immune receptors.

PubMed

Penack, Olaf; Holler, Ernst; van den Brink, Marcel R M

2010-03-11

Acute graft-versus-host disease (GVHD) remains the major obstacle to a more favorable therapeutic outcome of allogeneic hematopoietic stem cell transplantation (HSCT). GVHD is characterized by tissue damage in gut, liver, and skin, caused by donor T cells that are critical for antitumor and antimicrobial immunity after HSCT. One obstacle in combating GVHD used to be the lack of understanding the molecular mechanisms that are involved in the initiation phase of this syndrome. Recent research has demonstrated that interactions between microbial-associated molecules (pathogen-associated molecular patterns [PAMPs]) and innate immune receptors (pathogen recognition receptors [PRRs]), such as NOD-like receptors (NLRs) and Toll-like receptors (TLRs), control adaptive immune responses in inflammatory disorders. Polymorphisms of the genes encoding NOD2 and TLR4 are associated with a higher incidence of GVHD in HSC transplant recipients. Interestingly, NOD2 regulates GVHD through its inhibitory effect on antigen-presenting cell (APC) function. These insights identify important mechanisms regarding the induction of GVHD through the interplay of microbial molecules and innate immunity, thus opening a new area for future therapeutic approaches. This review covers current knowledge of the role of PAMPs and PRRs in the control of adaptive immune responses during inflammatory diseases, particularly GVHD.

The crystal structure of human soluble CD14 reveals a bent solenoid with a hydrophobic amino-terminal pocket1

PubMed Central

Kelley, Stacy L.; Lukk, Tiit; Nair, Satish K.; Tapping, Richard I.

2012-01-01

Human monocyte differentiation antigen CD14 is a pattern recognition receptor that enhances innate immune responses to infection by sensitizing host cells to bacterial lipopolysaccharide (LPS; endotoxin), lipoproteins, lipoteichoic acid and other acylated microbial products. CD14 physically delivers these lipidated microbial products to various Toll-like receptor signaling complexes that subsequently induce intracellular proinflammatory signaling cascades upon ligand binding. The ensuing cellular responses are usually protective to the host, but can also result in host fatality through sepsis. In this work, we have determined the X-ray crystal structure of human CD14. The structure reveals a bent solenoid typical of leucine rich repeat proteins with an amino terminal pocket that presumably binds acylated ligands including LPS. Comparison of human and mouse CD14 structures show great similarity in overall protein fold. However, compared to mouse CD14, human CD14 contains an expanded pocket and alternative rim residues that are likely to be important for LPS binding and cell activation. The X-ray crystal structure of human CD14 presented herein may foster additional ligand bound structural studies, virtual docking studies, and drug design efforts to mitigate LPS induced sepsis and other inflammatory diseases. PMID:23264655

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.

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.

Spatial patterns of cyanobacterial mat growth on sand ripples

NASA Astrophysics Data System (ADS)

Mariotti, G.; Klepac-Ceraj, V.; Perron, J. T.; Bosak, T.

2016-02-01

Photosynthetic microbial mats produce organic matter, cycle nutrients, bind pollutants and stabilize sediment in sandy marine environments. Here, we investigate the influence of bedforms and wave motion on the growth rate, composition and spatial variability of microbial mats by growing cyanobacterial mats on a rippled bed of carbonate sand in a wave tank. The tank was forced with an oscillatory flow with velocities below the threshold for sediment motion yet able to induce a porewater flow within the sediment. Different spatial patterns developed in mats depending on the initial biochemistry of the water medium. When growing in a medium rich in nitrogen, phosphorous and micronutrients, mats grew faster on ripple troughs than on ripple crests. After two months, mats covered the bed surface uniformly, and the microbial communities on the crests and in the troughs had similar compositions. Differences in bed shear stress and nutrient availability between crests and troughs were not able to explain the faster growth in the troughs. We hypothesize that this growth pattern is due to a "strainer" effect, i.e. the suspended bacteria from the inoculum were preferentially delivered to troughs by the wave-induced porewater flow. In the experiments initiated in a medium previously used up by a microbial mat and thus depleted in nutrients, mats grew preferentially on the ripple crests. This spatial pattern persisted for nearly two years, and the microbial composition on troughs and crests was different. We attribute this pattern to the upwelling of porewater in the crests, which increased the delivery of nutrients from sediment to the cyanobacteria on the bed surface. Thus, the macroscopic patterns formed by photosynthetic microbial mats on sand ripples may be used to infer whether mats are nutrient-limited and whether they are recently colonized or older than a month.

Peptidoglycan recognition protein genes and their roles in the innate immune pathways of the red flour beetle, Tribolium castaneum.

PubMed

Koyama, Hiroaki; Kato, Daiki; Minakuchi, Chieka; Tanaka, Toshiharu; Yokoi, Kakeru; Miura, Ken

2015-11-01

We have previously demonstrated that the functional Toll and IMD innate immune pathways indeed exist in the model beetle, Tribolium castaneum while the beetle's pathways have broader specificity in terms of microbial activation than that of Drosophila. To elucidate the molecular basis of this broad microbial activation, we here focused on potential upstream sensors of the T. castaneum innate immune pathways, peptidoglycan recognition proteins (PGRPs). Our phenotype analyses utilizing RNA interference-based comprehensive gene knockdown followed by bacterial challenge suggested: PGRP-LA functions as a pivotal sensor of the IMD pathway for both Gram-negative and Gram-positive bacteria; PGRP-LC acts as an IMD pathway-associated sensor mainly for Gram-negative bacteria; PGRP-LE also has some roles in Gram-negative bacterial recognition of the IMD pathway. On the other hand, we did not obtain clear phenotype changes by gene knockdown of short-type PGRP genes, probably because of highly inducible nature of these genes. Our results may collectively account for the promiscuous bacterial activation of the T. castaneum innate immune pathways at least in part. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Microbial source tracking: a forensic technique for microbial source identification?

PubMed

Stapleton, Carl M; Wyer, Mark D; Kay, David; Crowther, John; McDonald, Adrian T; Walters, Martin; Gawler, Andrew; Hindle, Terry

2007-05-01

As the requirements of the Water Framework Directive (WFD) and the US Clean Water Act (USCWA) for the maintenance of microbiological water quality in 'protected areas' highlight, there is a growing recognition that integrated management of point and diffuse sources of microbial pollution is essential. New information on catchment microbial dynamics and, in particular, the sources of faecal indicator bacteria found in bathing and shellfish harvesting waters is a pre-requisite for the design of any 'programme of measures' at the drainage basin scale to secure and maintain compliance with existing and new health-based microbiological standards. This paper reports on a catchment-scale microbial source tracking (MST) study in the Leven Estuary drainage basin, northwest England, an area for which quantitative faecal indicator source apportionment empirical data and land use information were also collected. Since previous MST studies have been based on laboratory trials using 'manufactured' samples or analyses of spot environmental samples without the contextual microbial flux data (under high and low flow conditions) and source information, such background data are needed to evaluate the utility of MST in USCWA total maximum daily load (TMDL) assessments or WFD 'Programmes of Measures'. Thus, the operational utility of MST remains in some doubt. The results of this investigation, using genotyping of Bacteroidetes using polymerase chain reaction (PCR) and male-specific ribonucleic acid coliphage (F + RNA coliphage) using hybridisation, suggest some discrimination is possible between livestock- and human-derived faecal indicator concentrations but, in inter-grade areas, the degree to which the tracer picture reflected the land use pattern and probable faecal indicator loading were less distinct. Interestingly, the MST data was more reliable on high flow samples when much of the faecal indicator flux from catchment systems occurs. Whilst a useful supplementary tool, the MST information did not provide quantitative source apportionment for the study catchment. Thus, it could not replace detailed empirical measurement of microbial flux at key catchment outlets to underpin faecal indicator source apportionment. Therefore, the MST techniques reported herein currently may not meet the standards required to be a useful forensic tool, although continued development of the methods and further catchment scale studies could increase confidence in such methods for future application.

Childhood pneumonia as a global health priority and the strategic interest of the Bill & Melinda Gates Foundation.

PubMed

Adegbola, Richard A

2012-04-01

Pneumonia kills more children than any other disease--more than HIV/AIDS, malaria, and measles combined. Introduction of vaccines against pneumococcus and Haemophilus influenzae type b (the most important causes of severe pneumonia in young children), increasing resistance to antibiotics, and changes in HIV prevalence will likely change patterns of pneumonia etiology in developing countries. Studies such as Pneumonia Etiology Research for Child Health (PERCH) that take advantage of new diagnostic technologies are needed to provide an updated and more precise description of the microbial causes of pneumonia and to inform decisions around treatment algorithms and vaccine development and introduction. In recognition of its importance for global health and especially its significance as an ongoing cause of gross inequity in risks, The Bill & Melinda Gates Foundation has made pneumonia an important part of its global health strategy and PERCH a centerpiece of its Pneumonia Program.

Cnidarian-microbe interactions and the origin of innate immunity in metazoans.

PubMed

Bosch, Thomas C G

2013-01-01

Most epithelia in animals are colonized by microbial communities. These resident microbes influence fitness and thus ecologically important traits of their hosts, ultimately forming a metaorganism consisting of a multicellular host and a community of associated microorganisms. Recent discoveries in the cnidarian Hydra show that components of the innate immune system as well as transcriptional regulators of stem cells are involved in maintaining homeostasis between animals and their resident microbiota. Here I argue that components of the innate immune system with its host-specific antimicrobial peptides and a rich repertoire of pattern recognition receptors evolved in early-branching metazoans because of the need to control the resident beneficial microbes, not because of invasive pathogens. I also propose a mutual intertwinement between the stem cell regulatory machinery of the host and the resident microbiota composition, such that disturbances in one trigger a restructuring and resetting of the other.

Microbial pattern of pressure ulcer in pediatric patients

NASA Astrophysics Data System (ADS)

Paramita, D. A.; Khairina; Lubis, N. Z.

2018-03-01

Pressure ulcer (PU) is a localized trauma to the skin and or tissue beneath which lies in bony prominence due to pressure or pressure that combines with a sharp surface. Several studies have found that PU is a common problem in pediatrics population. Infection at the site of a PU is the most common complication in which the PU may host a resistant microorganism and may turn into a local infection that will be the source of bacteremia in hospitalized patients. To reveal which is the most common microbial species that underlie in pressure ulcer of pediatrics patients.A cross-sectional study was conducted in July-September 2017, involving 18 PU pediatric patients in Haji Adam Malik Hospital. To each subject, swab culture from the ulcer was madein microbial laboratory in Haji Adam Malik Hospital to determine the microbial pattern. This study found that the most common microbial pattern in pressure ulcers of pediatrics patient in Haji Adam Malik Hospital is Acinetobacter baumannii (22.2%).

The Biogeography of Putative Microbial Antibiotic Production

PubMed Central

Bryant, Jessica A.; Charkoudian, Louise K.; Docherty, Kathryn M.; Jones, Evan; Kembel, Steven W.; Green, Jessica L.; Bohannan, Brendan J. M.

2015-01-01

Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. PMID:26102275

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

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

Injury enhances TLR2 function and antimicrobial peptide expression through a vitamin D–dependent mechanism

PubMed Central

Schauber, Jürgen; Dorschner, Robert A.; Coda, Alvin B.; Büchau, Amanda S.; Liu, Philip T.; Kiken, David; Helfrich, Yolanda R.; Kang, Sewon; Elalieh, Hashem Z.; Steinmeyer, Andreas; Zügel, Ulrich; Bikle, Daniel D.; Modlin, Robert L.; Gallo, Richard L.

2007-01-01

An essential element of the innate immune response to injury is the capacity to recognize microbial invasion and stimulate production of antimicrobial peptides. We investigated how this process is controlled in the epidermis. Keratinocytes surrounding a wound increased expression of the genes coding for the microbial pattern recognition receptors CD14 and TLR2, complementing an increase in cathelicidin antimicrobial peptide expression. These genes were induced by 1,25(OH)2 vitamin D3 (1,25D3; its active form), suggesting a role for vitamin D3 in this process. How 1,25D3 could participate in the injury response was explained by findings that the levels of CYP27B1, which converts 25OH vitamin D3 (25D3) to active 1,25D3, were increased in wounds and induced in keratinocytes in response to TGF-β1. Blocking the vitamin D receptor, inhibiting CYP27B1, or limiting 25D3 availability prevented TGF-β1 from inducing cathelicidin, CD14, or TLR2 in human keratinocytes, while CYP27B1-deficient mice failed to increase CD14 expression following wounding. The functional consequence of these observations was confirmed by demonstrating that 1,25D3 enabled keratinocytes to recognize microbial components through TLR2 and respond by cathelicidin production. Thus, we demonstrate what we believe to be a previously unexpected role for vitamin D3 in innate immunity, enabling keratinocytes to recognize and respond to microbes and to protect wounds against infection. PMID:17290304

Comparison of microbial taxonomic and functional shift pattern along contamination gradient.

PubMed

Ren, Youhua; Niu, Jiaojiao; Huang, Wenkun; Peng, Deliang; Xiao, Yunhua; Zhang, Xian; Liang, Yili; Liu, Xueduan; Yin, Huaqun

2016-06-14

The interaction mechanism between microbial communities and environment is a key issue in microbial ecology. Microbial communities usually change significantly under environmental stress, which has been studied both phylogenetically and functionally, however which method is more effective in assessing the relationship between microbial communities shift and environmental changes still remains controversial. By comparing the microbial taxonomic and functional shift pattern along heavy metal contamination gradient, we found that both sedimentary composition and function shifted significantly along contamination gradient. For example, the relative abundance of Geobacter and Fusibacter decreased along contamination gradient (from high to low), while Janthinobacterium and Arthrobacter increased their abundances. Most genes involved in heavy metal resistance (e.g., metc, aoxb and mer) showed higher intensity in sites with higher concentration of heavy metals. Comparing the two shift patterns, there were correlations between them, because functional and phylogenetic β-diversities were significantly correlated, and many heavy metal resistance genes were derived from Geobacter, explaining their high abundance in heavily contaminated sites. However, there was a stronger link between functional composition and environmental drivers, while stochasticity played an important role in formation and succession of phylogenetic composition demonstrated by null model test. Overall our research suggested that the responses of functional traits depended more on environmental changes, while stochasticity played an important role in formation and succession of phylogenetic composition for microbial communities. So profiling microbial functional composition seems more appropriate to study the relationship between microbial communities and environment, as well as explore the adaptation and remediation mechanism of microbial communities to heavy metal contamination.

Eicosanoid-mediated immunity in insects

USDA-ARS?s Scientific Manuscript database

Eicosanoid is a collective term for oxygenated metabolites of C20 polyunsaturated fatty acids. As seen in mammals, eicosanoids play crucial roles in mediating various physiological processes, including immune responses, in insects. Upon microbial pathogen infection, non-self recognition signals are ...

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

Pan-Arctic patterns of planktonic heterotrophic microbial abundance and processes: Controlling factors and potential impacts of warming

NASA Astrophysics Data System (ADS)

Maranger, Roxane; Vaqué, Dolors; Nguyen, Dan; Hébert, Marie-Pier; Lara, Elena

2015-12-01

The Arctic Ocean is rapidly changing where increasing water temperatures and rapid loss of summer sea-ice will likely influence the structure and functioning of the entire ecosystem. The aim of this study was to synthesize the current state of knowledge on microbial abundances and processes from a regional Pan-Arctic perspective, characterize regulating factors and attempt to predict how patterns may change under a warming scenario. Here we identify some generalized patterns of different microbial variables between the Pacific-fed and the Atlantic-fed sectors of the Arctic Ocean. Bacterial production (BP), abundance and grazing rates by protists (GT) were all higher in the Atlantic-fed region. Bacterial loss by viral lyses (VL) was proportionally more important in the Pacific-fed sector, suggesting a reduced C transfer efficiency within the microbial loop of that region. Using a cross-comparative approach and all available data to build Arrhenius plots, we found a differential response to warming temperatures among various microbial processes. BP and GT responded similarly and more strongly to increases in temperature than VL did, suggesting a shift in the overall influence of viral mortality under a warming scenario. However, together with temperature, resource-related factors also exerted an influence in regulating these rates. We identified large information gaps for more classically studied microbial variable from several Arctic seas. Furthermore, there is limited information on less conventional pathways such as grazing by mixotrophic species, which may be playing a significant role in Arctic microbial trophodynamics. Although generalized patterns could be elucidated, more information is needed to predict and understand how a changing Arctic will alter microbial C pathways and major biogeochemical cycles on regional and seasonal scales.

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.

The intracellular nucleotide binding leucine-rich repeat receptor - SlNRC4a enhances immune signaling elicited by extracellular perception.

PubMed

Leibman-Markus, Meirav; Pizarro, Lorena; Schuster, Silvia; Lin, Z J Daniel; Gershony, Ofir; Bar, Maya; Coaker, Gitta; Avni, Adi

2018-05-23

Plant recognition and defense against pathogens employs a two-tiered perception system. Surface localized pattern recognition receptors (PRRs) act to recognize microbial features, while intracellular nucleotide binding leucine-rich repeat receptors (NLRs) directly or indirectly recognize pathogen effectors inside host cells. Employing the tomato PRR LeEIX2/EIX model system, we explored the molecular mechanism of signaling pathways. We identified an NLR that can associate with LeEIX2, termed SlNRC4a (NB-LRR Required for HR-associated Cell death-4). Co-immunoprecipitation demonstrates that SlNRC4a is able to associate with different PRRs. Physiological assays with specific elicitors revealed that SlNRC4a generally alters PRR-mediated responses. SlNRC4a overexpression enhances defense responses while silencing SlNRC4 reduces plant immunity. Moreover, the coiled-coil domain of SlNRC4a is able to associate with LeEIX2 and is sufficient to enhance responses upon EIX perception. Based on these findings, we propose that SlNRC4a acts as a non-canonical positive regulator of immunity mediated by diverse PRRs. Thus, SlNRC4a could link both intracellular and extracellular immune perception. This article is protected by copyright. All rights reserved.

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.

Ecological effects of soil properties and metal concentrations on the composition and diversity of microbial communities associated with land use patterns in an electronic waste recycling region.

PubMed

Wu, Wencheng; Dong, Changxun; Wu, Jiahui; Liu, Xiaowen; Wu, Yingxin; Chen, Xianbin; Yu, Shixiao

2017-12-01

Soil microbes play vital roles in ecosystem functions, and soil microbial communities may be strongly structured by land use patterns associated with electronic waste (e-waste) recycling activities, which can increase the heavy metal concentration in soils. In this study, a suite of soils from five land use types (paddy field, vegetable field, dry field, forest field, and e-waste recycling site) were collected in Longtang Town, Guangdong Province, South China. Soil physicochemical properties and heavy metal concentrations were measured, and the indigenous microbial assemblages were profiled using 16S rRNA high-throughput sequencing and clone library analyses. The results showed that mercury concentration was positively correlated with both Faith's PD and Chao1 estimates, suggesting that the soil microbial alpha diversity was predominantly regulated by mercury. In addition, redundancy analysis indicated that available phosphorus, soil moisture, and mercury were the three major drivers affecting the microbial assemblages. Overall, the microbial composition was determined primarily by land use patterns, and this study provides a novel insight on the composition and diversity of microbial communities in soils associated with e-waste recycling activities. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

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.

Spatial pattern formation of microbes at the soil microscale affect soil C and N turnover in an individual-based microbial community model

NASA Astrophysics Data System (ADS)

Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie

2016-04-01

At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these pattern can be explained by the Turing mechanism. These pattern formation had strong consequences for process rates, as well as for C and N storage in the soil at the steady state: Scenarios that exhibited pattern formation were generally associated with higher C storage at steady state compared to those without pattern formation (i.e. at non-limiting conditions for microbes). Moreover, pattern formation lead to a spatial decoupling of C and N turnover processes, and to a spatial decoupling of microbial N mineralization and N immobilization. Taken together, our theoretical analysis shows that self-organisation may be a feature of the soil decomposer system, with consequences for process rates of microbial C and N turnover. Pattern formation through spatial self-organization, which has been observed on larger spatial scales in other resource-limited communities (e.g., vegetation patterns in arid or wetland eco-systems), may also occur at the soil microscale, leaving its mark on the soil's storage capacity for C and N.

Dramatic Increases of Soil Microbial Functional Gene Diversity at the Treeline Ecotone of Changbai Mountain.

PubMed

Shen, Congcong; Shi, Yu; Ni, Yingying; Deng, Ye; Van Nostrand, Joy D; He, Zhili; Zhou, Jizhong; Chu, Haiyan

2016-01-01

The elevational and latitudinal diversity patterns of microbial taxa have attracted great attention in the past decade. Recently, the distribution of functional attributes has been in the spotlight. Here, we report a study profiling soil microbial communities along an elevation gradient (500-2200 m) on Changbai Mountain. Using a comprehensive functional gene microarray (GeoChip 5.0), we found that microbial functional gene richness exhibited a dramatic increase at the treeline ecotone, but the bacterial taxonomic and phylogenetic diversity based on 16S rRNA gene sequencing did not exhibit such a similar trend. However, the β-diversity (compositional dissimilarity among sites) pattern for both bacterial taxa and functional genes was similar, showing significant elevational distance-decay patterns which presented increased dissimilarity with elevation. The bacterial taxonomic diversity/structure was strongly influenced by soil pH, while the functional gene diversity/structure was significantly correlated with soil dissolved organic carbon (DOC). This finding highlights that soil DOC may be a good predictor in determining the elevational distribution of microbial functional genes. The finding of significant shifts in functional gene diversity at the treeline ecotone could also provide valuable information for predicting the responses of microbial functions to climate change.

Diversity in recognition of glycans by F-type lectins and galectins: molecular, structural, and biophysical aspects

PubMed Central

Vasta, Gerardo R.; Ahmed, Hafiz; Bianchet, Mario A.; Fernández-Robledo, José A.; Amzel, L. Mario

2013-01-01

Although lectins are “hard-wired” in the germline, the presence of tandemly arrayed carbohydrate recognition domains (CRDs), of chimeric structures displaying distinct CRDs, of polymorphic genes resulting in multiple isoforms, and in some cases, of a considerable recognition plasticity of their carbohydrate binding sites, significantly expand the lectin ligand-recognition spectrum and lectin functional diversification. Analysis of structural/functional aspects of galectins and F-lectins—the most recently identified lectin family characterized by a unique CRD sequence motif (a distinctive structural fold) and nominal specificity for l-Fuc—has led to a greater understanding of self/nonself recognition by proteins with tandemly arrayed CRDs. For lectins with a single CRD, however, recognition of self and nonself glycans can only be rationalized in terms of protein oligomerization and ligand clustering and presentation. Spatial and temporal changes in lectin expression, secretion, and local concentrations in extracellular microenvironments, as well as structural diversity and spatial display of their carbohydrate ligands on the host or microbial cell surface, are suggestive of a dynamic interplay of their recognition and effector functions in development and immunity. PMID:22973821

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.

Printing-assisted surface modifications of patterned ultrafiltration membranes

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

Wardrip, Nathaniel C.; Dsouza, Melissa; Urgun-Demirtas, Meltem

Understanding and restricting microbial surface attachment will enhance wastewater treatment with membranes. We report a maskless lithographic patterning technique for the generation of patterned polymer coatings on ultrafiltration membranes. Polyethylene glycol, zwitterionic, or negatively charged hydrophilic polymer compositions in parallel- or perpendicular-striped patterns with respect to feed flow were evaluated using wastewater. Membrane fouling was dependent on the orientation and chemical composition of the coatings. Modifications reduced alpha diversity in the attached microbial community (Shannon indices decreased from 2.63 to 1.89) which nevertheless increased with filtration time. Sphingomonas species, which condition membrane surfaces and facilitate cellular adhesion, were depleted inmore » all modified membranes. Microbial community structure was significantly different between control, different patterns, and different chemistries. Lastly, this study broadens the tools for surface modification of membranes with polymer coatings and for understanding and optimization of antifouling surfaces.« less

Printing-assisted surface modifications of patterned ultrafiltration membranes

DOE PAGES

Wardrip, Nathaniel C.; Dsouza, Melissa; Urgun-Demirtas, Meltem; ...

2016-10-17

Understanding and restricting microbial surface attachment will enhance wastewater treatment with membranes. We report a maskless lithographic patterning technique for the generation of patterned polymer coatings on ultrafiltration membranes. Polyethylene glycol, zwitterionic, or negatively charged hydrophilic polymer compositions in parallel- or perpendicular-striped patterns with respect to feed flow were evaluated using wastewater. Membrane fouling was dependent on the orientation and chemical composition of the coatings. Modifications reduced alpha diversity in the attached microbial community (Shannon indices decreased from 2.63 to 1.89) which nevertheless increased with filtration time. Sphingomonas species, which condition membrane surfaces and facilitate cellular adhesion, were depleted inmore » all modified membranes. Microbial community structure was significantly different between control, different patterns, and different chemistries. Lastly, this study broadens the tools for surface modification of membranes with polymer coatings and for understanding and optimization of antifouling surfaces.« less

Microbial Community and Functional Structure Significantly Varied among Distinct Types of Paddy Soils But Responded Differently along Gradients of Soil Depth Layers

PubMed Central

Bai, Ren; Wang, Jun-Tao; Deng, Ye; He, Ji-Zheng; Feng, Kai; Zhang, Li-Mei

2017-01-01

Paddy rice fields occupy broad agricultural area in China and cover diverse soil types. Microbial community in paddy soils is of great interest since many microorganisms are involved in soil functional processes. In the present study, Illumina Mi-Seq sequencing and functional gene array (GeoChip 4.2) techniques were combined to investigate soil microbial communities and functional gene patterns across the three soil types including an Inceptisol (Binhai), an Oxisol (Leizhou), and an Ultisol (Taoyuan) along four profile depths (up to 70 cm in depth) in mesocosm incubation columns. Detrended correspondence analysis revealed that distinctly differentiation in microbial community existed among soil types and profile depths, while the manifest variance in functional structure was only observed among soil types and two rice growth stages, but not across profile depths. Along the profile depth within each soil type, Acidobacteria, Chloroflexi, and Firmicutes increased whereas Cyanobacteria, β-proteobacteria, and Verrucomicrobia declined, suggesting their specific ecophysiological properties. Compared to bacterial community, the archaeal community showed a more contrasting pattern with the predominant groups within phyla Euryarchaeota, Thaumarchaeota, and Crenarchaeota largely varying among soil types and depths. Phylogenetic molecular ecological network (pMEN) analysis further indicated that the pattern of bacterial and archaeal communities interactions changed with soil depth and the highest modularity of microbial community occurred in top soils, implying a relatively higher system resistance to environmental change compared to communities in deeper soil layers. Meanwhile, microbial communities had higher connectivity in deeper soils in comparison with upper soils, suggesting less microbial interaction in surface soils. Structure equation models were developed and the models indicated that pH was the most representative characteristics of soil type and identified as the key driver in shaping both bacterial and archaeal community structure, but did not directly affect microbial functional structure. The distinctive pattern of microbial taxonomic and functional composition along soil profiles implied functional redundancy within these paddy soils. PMID:28611747

Microbial Community and Functional Structure Significantly Varied among Distinct Types of Paddy Soils But Responded Differently along Gradients of Soil Depth Layers.

PubMed

Bai, Ren; Wang, Jun-Tao; Deng, Ye; He, Ji-Zheng; Feng, Kai; Zhang, Li-Mei

2017-01-01

Paddy rice fields occupy broad agricultural area in China and cover diverse soil types. Microbial community in paddy soils is of great interest since many microorganisms are involved in soil functional processes. In the present study, Illumina Mi-Seq sequencing and functional gene array (GeoChip 4.2) techniques were combined to investigate soil microbial communities and functional gene patterns across the three soil types including an Inceptisol (Binhai), an Oxisol (Leizhou), and an Ultisol (Taoyuan) along four profile depths (up to 70 cm in depth) in mesocosm incubation columns. Detrended correspondence analysis revealed that distinctly differentiation in microbial community existed among soil types and profile depths, while the manifest variance in functional structure was only observed among soil types and two rice growth stages, but not across profile depths. Along the profile depth within each soil type, Acidobacteria , Chloroflexi , and Firmicutes increased whereas Cyanobacteria , β -proteobacteria , and Verrucomicrobia declined, suggesting their specific ecophysiological properties. Compared to bacterial community, the archaeal community showed a more contrasting pattern with the predominant groups within phyla Euryarchaeota , Thaumarchaeota , and Crenarchaeota largely varying among soil types and depths. Phylogenetic molecular ecological network (pMEN) analysis further indicated that the pattern of bacterial and archaeal communities interactions changed with soil depth and the highest modularity of microbial community occurred in top soils, implying a relatively higher system resistance to environmental change compared to communities in deeper soil layers. Meanwhile, microbial communities had higher connectivity in deeper soils in comparison with upper soils, suggesting less microbial interaction in surface soils. Structure equation models were developed and the models indicated that pH was the most representative characteristics of soil type and identified as the key driver in shaping both bacterial and archaeal community structure, but did not directly affect microbial functional structure. The distinctive pattern of microbial taxonomic and functional composition along soil profiles implied functional redundancy within these paddy soils.

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.

Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance

PubMed Central

Bokulich, Nicholas A; Bergsveinson, Jordyn; Ziola, Barry; Mills, David A

2015-01-01

Distinct microbial ecosystems have evolved to meet the challenges of indoor environments, shaping the microbial communities that interact most with modern human activities. Microbial transmission in food-processing facilities has an enormous impact on the qualities and healthfulness of foods, beneficially or detrimentally interacting with food products. To explore modes of microbial transmission and spoilage-gene frequency in a commercial food-production scenario, we profiled hop-resistance gene frequencies and bacterial and fungal communities in a brewery. We employed a Bayesian approach for predicting routes of contamination, revealing critical control points for microbial management. Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment. Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk. Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments. DOI: http://dx.doi.org/10.7554/eLife.04634.001 PMID:25756611

Pathogen recognition in the innate immune response.

PubMed

Kumar, Himanshu; Kawai, Taro; Akira, Shizuo

2009-04-28

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

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

PubMed Central

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

2010-01-01

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

Auditory orientation in crickets: Pattern recognition controls reactive steering

NASA Astrophysics Data System (ADS)

Poulet, James F. A.; Hedwig, Berthold

2005-10-01

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

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…

Toll-like receptor agonists are potent inhibitors of human immunodeficiency virus-type 1 replication in peripheral blood mononuclear cells.

PubMed

Buitendijk, Maarten; Eszterhas, Susan K; Howell, Alexandra L

2014-05-01

Innate immune responses to microbial pathogens are initiated following the binding of ligand to specific pattern recognition receptors. Each pattern recognition receptor, which includes members of the Toll-like receptor (TLR) family, is specific for a particular type of pathogen associated molecular pattern ensuring that the organism can respond rapidly to a wide range of pathogens including bacteria, viruses, and fungi. We studied the extent to which agonists to endosomal TLR could induce anti-HIV-1 activity in peripheral blood mononuclear cells (PBMCs). When agonists to TLR3, TLR7, TLR8 and TLR9 were added prior to infection with HIV-1, they significantly reduced infection of peripheral blood mononuclear cells. Interestingly, agonists to TLR8 and TLR9 were highly effective at blocking HIV replication even when added as late as 48 h or 72 h, respectively, after HIV-1 infection, indicating that the anti-viral effect was durable and long lasting. Analysis of the induction of anti-viral genes after agonist activation of TLR indicated that all of the agonists induced expression of the type I interferons and interferon stimulated genes, although to variable levels that depended on the agonist used. Interestingly, only the agonist to TLR9, ODN2395 DNA, induced expression of type II interferon and the anti-HIV proteins Apobec3G and SAMHD1. By blocking TLR activity using an inhibitor to the MyD88 adaptor protein, we demonstrated that, at least for TLR8 and TLR9, the anti-HIV activity was not entirely mediated by TLR activation, but likely by the activation of additional anti-viral sensors in HIV target cells. These findings suggest that agonists to the endosomal TLR function to induce expression of anti-HIV molecules by both TLR-mediated and non-TLR-mediated mechanisms. Moreover, the non-TLR-mediated mechanisms induced by these agonists could potentially be exploited to block HIV-1 replication in recently HIV-exposed individuals.

EVIDENCE FOR MICROBIAL ENHANCED ELECTRICAL CONDUCTIVITY IN HYDROCARBON-CONTAMINATED SEDIMENTS

EPA Science Inventory

Electrical conductivity of sediments during microbial mineralization of diesel was investigated in a mesoscale column experiment consisting of biotic contaminated and uncontaminated columns. Microbial population numbers increased with a clear pattern of depth zonation within the ...

General Model for Retroviral Capsid Pattern Recognition by TRIM5 Proteins.

PubMed

Wagner, Jonathan M; Christensen, Devin E; Bhattacharya, Akash; Dawidziak, Daria M; Roganowicz, Marcin D; Wan, Yueping; Pumroy, Ruth A; Demeler, Borries; Ivanov, Dmitri N; Ganser-Pornillos, Barbie K; Sundquist, Wesley I; Pornillos, Owen

2018-02-15

Restriction factors are intrinsic cellular defense proteins that have evolved to block microbial infections. Retroviruses such as HIV-1 are restricted by TRIM5 proteins, which recognize the viral capsid shell that surrounds, organizes, and protects the viral genome. TRIM5α uses a SPRY domain to bind capsids with low intrinsic affinity ( K D of >1 mM) and therefore requires higher-order assembly into a hexagonal lattice to generate sufficient avidity for productive capsid recognition. TRIMCyp, on the other hand, binds HIV-1 capsids through a cyclophilin A domain, which has a well-defined binding site and higher affinity ( K D of ∼10 μM) for isolated capsid subunits. Therefore, it has been argued that TRIMCyp proteins have dispensed with the need for higher-order assembly to function as antiviral factors. Here, we show that, consistent with its high degree of sequence similarity with TRIM5α, the TRIMCyp B-box 2 domain shares the same ability to self-associate and facilitate assembly of a TRIMCyp hexagonal lattice that can wrap about the HIV-1 capsid. We also show that under stringent experimental conditions, TRIMCyp-mediated restriction of HIV-1 is indeed dependent on higher-order assembly. Both forms of TRIM5 therefore use the same mechanism of avidity-driven capsid pattern recognition. IMPORTANCE Rhesus macaques and owl monkeys are highly resistant to HIV-1 infection due to the activity of TRIM5 restriction factors. The rhesus macaque TRIM5α protein blocks HIV-1 through a mechanism that requires self-assembly of a hexagonal TRIM5α lattice around the invading viral core. Lattice assembly amplifies very weak interactions between the TRIM5α SPRY domain and the HIV-1 capsid. Assembly also promotes dimerization of the TRIM5α RING E3 ligase domain, resulting in synthesis of polyubiquitin chains that mediate downstream steps of restriction. In contrast to rhesus TRIM5α, the owl monkey TRIM5 homolog, TRIMCyp, binds isolated HIV-1 CA subunits much more tightly through its cyclophilin A domain and therefore was thought to act independently of higher-order assembly. Here, we show that TRIMCyp shares the assembly properties of TRIM5α and that both forms of TRIM5 use the same mechanism of hexagonal lattice formation to promote viral recognition and restriction. Copyright © 2018 American Society for Microbiology.

Seasonal dynamics of microbial community composition and function in oak canopy and open grassland soils

USGS Publications Warehouse

Waldrop, M.P.; Firestone, M.K.

2006-01-01

Soil microbial communities are closely associated with aboveground plant communities, with multiple potential drivers of this relationship. Plants can affect available soil carbon, temperature, and water content, which each have the potential to affect microbial community composition and function. These same variables change seasonally, and thus plant control on microbial community composition may be modulated or overshadowed by annual climatic patterns. We examined microbial community composition, C cycling processes, and environmental data in California annual grassland soils from beneath oak canopies and in open grassland areas to distinguish factors controlling microbial community composition and function seasonally and in association with the two plant overstory communities. Every 3 months for up to 2 years, we monitored microbial community composition using phospholipid fatty acid (PLFA) analysis, microbial biomass, respiration rates, microbial enzyme activities, and the activity of microbial groups using isotope labeling of PLFA biomarkers (13C-PLFA) . Distinct microbial communities were associated with oak canopy soils and open grassland soils and microbial communities displayed seasonal patterns from year to year. The effects of plant species and seasonal climate on microbial community composition were similar in magnitude. In this Mediterranean ecosystem, plant control of microbial community composition was primarily due to effects on soil water content, whereas the changes in microbial community composition seasonally appeared to be due, in large part, to soil temperature. Available soil carbon was not a significant control on microbial community composition. Microbial community composition (PLFA) and 13C-PLFA ordination values were strongly related to intra-annual variability in soil enzyme activities and soil respiration, but microbial biomass was not. In this Mediterranean climate, soil microclimate appeared to be the master variable controlling microbial community composition and function. ?? 2006 Springer Science+Business Media, Inc.

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).

Temporal and Spatial Variations in Transcriptional Patterns among Closely Related Marine Microbial Taxa

NASA Astrophysics Data System (ADS)

Shilova, I. N.; Robidart, J.; DeLong, E.; Zehr, J. P.

2016-02-01

Marine microbial communities are complex, and even closely related marine microbial populations are genetically and physiologically diverse. Despite such great diversity, conserved and highly synchronized rhythmic transcriptional patterns have been observed in microbial communities worldwide. The current widely used approaches analyzing high-throughput sequence data from microbiomes are not designed to differentiate transcription at strain or ecotype level. We used a novel MicroArray-inspired Gene-Centric (MAGC) bioinformatics approach to discern daily transcription by individual strains in previously analyzed metatranscriptomes from two oceanic regions, California Current System and central North Pacific. The results demonstrated that marine microbial taxa (within cyanobacteria Prochlorococcus and Synechococcus, Alphaproteobacterium Pelagibacter and picoeukaryote Ostreococcus) have unique transcription patterns and respond differentially to variability in space and time in the ocean. For example, the timing of maximum transcription for the photosynthesis and pigments genes varied among Synechococcus strains in the California Current study, likely for optimizing light utilization based on their differences in genetics and physiology. While several Prochlorococcus genotypes were present in the North Pacific study, transcription of the phosphate transporter gene, pstS, in specific genotypes was negatively correlated with phosphate concentrations. These individual transcriptional patterns underlie whole microbial community responses and may be sensitive indicators of environmental conditions, including those associated with long-term environmental change. The MAGC applied here to ocean ecosystems is a promising complementary approach that can enhance the ability to analyze metatranscriptomic data from a variety of environmental microbiomes.

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.

Contrasting microbial functional genes in two distinct saline-alkali and slightly acidic oil-contaminated sites.

PubMed

Liang, Yuting; Zhao, Huihui; Zhang, Xu; Zhou, Jizhong; Li, Guanghe

2014-07-15

To compare the functional gene structure and diversity of microbial communities in saline-alkali and slightly acidic oil-contaminated sites, 40 soil samples were collected from two typical oil exploration sites in North and South China and analyzed with a comprehensive functional gene array (GeoChip 3.0). The overall microbial pattern was significantly different between the two sites, and a more divergent pattern was observed in slightly acidic soils. Response ratio was calculated to compare the microbial functional genes involved in organic contaminant degradation and carbon, nitrogen, phosphorus, and sulfur cycling. The results indicated a significantly low abundance of most genes involved in organic contaminant degradation and in the cycling of nitrogen and phosphorus in saline-alkali soils. By contrast, most carbon degradation genes and all carbon fixation genes had similar abundance at both sites. Based on the relationship between the environmental variables and microbial functional structure, pH was the major factor influencing the microbial distribution pattern in the two sites. This study demonstrated that microbial functional diversity and heterogeneity in oil-contaminated environments can vary significantly in relation to local environmental conditions. The limitation of nitrogen and phosphorus and the low degradation capacity of organic contaminant should be carefully considered, particularly in most oil-exploration sites with saline-alkali soils. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

An LRR/Malectin Receptor-Like Kinase Mediates Resistance to Non-adapted and Adapted Powdery Mildew Fungi in Barley and Wheat

PubMed Central

Rajaraman, Jeyaraman; Douchkov, Dimitar; Hensel, Götz; Stefanato, Francesca L.; Gordon, Anna; Ereful, Nelzo; Caldararu, Octav F.; Petrescu, Andrei-Jose; Kumlehn, Jochen; Boyd, Lesley A.; Schweizer, Patrick

2016-01-01

Pattern recognition receptors (PRRs) belonging to the multigene family of receptor-like kinases (RLKs) are the sensing devices of plants for microbe- or pathogen-associated molecular patterns released from microbial organisms. Here we describe Rnr8 (for Required for non-host resistance 8) encoding HvLEMK1, a LRR-malectin domain-containing transmembrane RLK that mediates non-host resistance of barley to the non-adapted wheat powdery mildew fungus Blumeria graminis f.sp. tritici. Transgenic barley lines with silenced HvLEMK1 allow entry and colony growth of the non-adapted pathogen, although sporulation was reduced and final colony size did not reach that of the adapted barley powdery mildew fungus B. graminis f.sp. hordei. Transient expression of the barley or wheat LEMK1 genes enhanced resistance in wheat to the adapted wheat powdery mildew fungus while expression of the same genes did not protect barley from attack by the barley powdery mildew fungus. The results suggest that HvLEMK1 is a factor mediating non-host resistance in barley and quantitative host resistance in wheat to the wheat powdery mildew fungus. PMID:28018377

An LRR/Malectin Receptor-Like Kinase Mediates Resistance to Non-adapted and Adapted Powdery Mildew Fungi in Barley and Wheat.

PubMed

Rajaraman, Jeyaraman; Douchkov, Dimitar; Hensel, Götz; Stefanato, Francesca L; Gordon, Anna; Ereful, Nelzo; Caldararu, Octav F; Petrescu, Andrei-Jose; Kumlehn, Jochen; Boyd, Lesley A; Schweizer, Patrick

2016-01-01

Pattern recognition receptors (PRRs) belonging to the multigene family of receptor-like kinases (RLKs) are the sensing devices of plants for microbe- or pathogen-associated molecular patterns released from microbial organisms. Here we describe Rnr8 (for Required for non-host resistance 8 ) encoding HvLEMK1, a LRR-malectin domain-containing transmembrane RLK that mediates non-host resistance of barley to the non-adapted wheat powdery mildew fungus Blumeria graminis f.sp. tritici . Transgenic barley lines with silenced HvLEMK1 allow entry and colony growth of the non-adapted pathogen, although sporulation was reduced and final colony size did not reach that of the adapted barley powdery mildew fungus B. graminis f.sp. hordei . Transient expression of the barley or wheat LEMK1 genes enhanced resistance in wheat to the adapted wheat powdery mildew fungus while expression of the same genes did not protect barley from attack by the barley powdery mildew fungus. The results suggest that HvLEMK1 is a factor mediating non-host resistance in barley and quantitative host resistance in wheat to the wheat powdery mildew fungus.

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

Chemical screening method for the rapid identification of microbial sources of marine invertebrate-associated metabolites.

PubMed

Berrue, Fabrice; Withers, Sydnor T; Haltli, Brad; Withers, Jo; Kerr, Russell G

2011-03-21

Marine invertebrates have proven to be a rich source of secondary metabolites. The growing recognition that marine microorganisms associated with invertebrate hosts are involved in the biosynthesis of secondary metabolites offers new alternatives for the discovery and development of marine natural products. However, the discovery of microorganisms producing secondary metabolites previously attributed to an invertebrate host poses a significant challenge. This study describes an efficient chemical screening method utilizing a 96-well plate-based bacterial cultivation strategy to identify and isolate microbial producers of marine invertebrate-associated metabolites.

The alternative Medicago truncatula defense proteome of ROS—defective transgenic roots during early microbial infection

PubMed Central

Kiirika, Leonard M.; Schmitz, Udo; Colditz, Frank

2014-01-01

ROP-type GTPases of plants function as molecular switches within elementary signal transduction pathways such as the regulation of ROS synthesis via activation of NADPH oxidases (RBOH-respiratory burst oxidase homolog in plants). Previously, we reported that silencing of the Medicago truncatula GTPase MtROP9 led to reduced ROS production and suppressed induction of ROS-related enzymes in transgenic roots (MtROP9i) infected with pathogenic (Aphanomyces euteiches) and symbiotic microorganisms (Glomus intraradices, Sinorhizobium meliloti). While fungal infections were enhanced, S. meliloti infection was drastically impaired. In this study, we investigate the temporal proteome response of M. truncatula MtROP9i transgenic roots during the same microbial interactions under conditions of deprived potential to synthesize ROS. In comparison with control roots (Mtvector), we present a comprehensive proteomic analysis using sensitive MS protein identification. For four early infection time-points (1, 3, 5, 24 hpi), 733 spots were found to be different in abundance: 213 spots comprising 984 proteins (607 unique) were identified after S. meliloti infection, 230 spots comprising 796 proteins (580 unique) after G. intraradices infection, and 290 spots comprising 1240 proteins (828 unique) after A. euteiches infection. Data evaluation by GelMap in combination with a heatmap tool allowed recognition of key proteome changes during microbial interactions under conditions of hampered ROS synthesis. Overall, the number of induced proteins in MtROP9i was low as compared with controls, indicating a dual function of ROS in defense signaling as well as alternative response patterns activated during microbial infection. Qualitative analysis of induced proteins showed that enzymes linked to ROS production and scavenging were highly induced in control roots, while in MtROP9i the majority of proteins were involved in alternative defense pathways such as cell wall and protein degradation. PMID:25101099

Tracking microbial colonization patterns associated with micro-environments of rice

NASA Astrophysics Data System (ADS)

Schmidt, Hannes; Eickhorst, Thilo

2015-04-01

The interface between soil and roots (i.e. the rhizosphere) represents a highly dynamic micro-environment for microbial populations. Root-derived compounds are released into the rhizosphere and may attract, stimulate, or inhibit native soil microorganisms. Microbes associated with the rhizosphere, in turn, may have deleterious, neutral, or promoting effects on the plant. Such influences of microbial populations on the plant and vice versa are likely to be greatest in close vicinity to the root surface. It is therefore essential to detect and visualize preferential micro-sites of microbial root colonization to identify potential areas of microbe-plant interaction. We present a single-cell based approach allowing for the localization, quantification, and visualization of native microbial populations in the rhizosphere and on the rhizoplane of soil-grown roots in situ. Catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) in combination with confocal laser scanning microscopy was applied to observe colonization densities and patterns of microbial populations associated with wetland rice. Hybridizations with domain- and phylum-specific oligonucleotide probes showed that the growth stage of the rice plant as well as the distance to the root surface had a strong influence on microbial colonization patterns. Three-dimensional visualizations of root-associated microbes revealed micro-sites of preferential colonization. Highest cell numbers of archaea and bacteria were found at flowering stage of rice plant development. Irregular distribution patterns of microbiota observed at early growth stages shifted towards more uniform colonization with plant age. Accordingly, the highest colonization densities shifted from the tip to more mature regions of rice roots. Methanogenic archaea and methanotrophic bacteria were found to be co-localized at basal regions of lateral roots. Beneficial effects of a close association with root surfaces were indicated by proportionally higher numbers of methane-oxidizing bacteria on the rhizoplane compared to the rhizosphere. Such spatial effects could not be observed for methanogenic archaea. As a consequence, the detection and visualization of microbial colonization patterns on a micro-scale via CARD-FISH represents an instrumental approach in revealing potential sites of interaction between microbes and plants in soil micro-environments.

Integrating the protein and metabolic engineering toolkits for next-generation chemical biosynthesis.

PubMed

Pirie, Christopher M; De Mey, Marjan; Jones Prather, Kristala L; Ajikumar, Parayil Kumaran

2013-04-19

Through microbial engineering, biosynthesis has the potential to produce thousands of chemicals used in everyday life. Metabolic engineering and synthetic biology are fields driven by the manipulation of genes, genetic regulatory systems, and enzymatic pathways for developing highly productive microbial strains. Fundamentally, it is the biochemical characteristics of the enzymes themselves that dictate flux through a biosynthetic pathway toward the product of interest. As metabolic engineers target sophisticated secondary metabolites, there has been little recognition of the reduced catalytic activity and increased substrate/product promiscuity of the corresponding enzymes compared to those of central metabolism. Thus, fine-tuning these enzymatic characteristics through protein engineering is paramount for developing high-productivity microbial strains for secondary metabolites. Here, we describe the importance of protein engineering for advancing metabolic engineering of secondary metabolism pathways. This pathway integrated enzyme optimization can enhance the collective toolkit of microbial engineering to shape the future of chemical manufacturing.

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.

Recognition of Mannosylated Ligands and Influenza A Virus by Human Surfactant Protein D: Contributions of an Extended Site and Residue 343

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

Crouch, E.; Hartshorn, K; Horlacher, T

2009-01-01

Surfactant protein D (SP-D) plays important roles in antiviral host defense. Although SP-D shows a preference for glucose/maltose, the protein also recognizes d-mannose and a variety of mannose-rich microbial ligands. This latter preference prompted an examination of the mechanisms of mannose recognition, particularly as they relate to high-mannose viral glycans. Trimeric neck plus carbohydrate recognition domains from human SP-D (hNCRD) preferred ?1-2-linked dimannose (DM) over the branched trimannose (TM) core, ?1-3 or ?1-6 DM, or d-mannose. Previous studies have shown residues flanking the carbohydrate binding site can fine-tune ligand recognition. A mutant with valine at 343 (R343V) showed enhanced bindingmore » to mannan relative to wild type and R343A. No alteration in affinity was observed for d-mannose or for ?1-3- or ?1-6-linked DM; however, substantially increased affinity was observed for ?1-2 DM. Both proteins showed efficient recognition of linear and branched subdomains of high-mannose glycans on carbohydrate microarrays, and R343V showed increased binding to a subset of the oligosaccharides. Crystallographic analysis of an R343V complex with 1,2-DM showed a novel mode of binding. The disaccharide is bound to calcium by the reducing sugar ring, and a stabilizing H-bond is formed between the 2-OH of the nonreducing sugar ring and Arg349. Although hNCRDs show negligible binding to influenza A virus (IAV), R343V showed markedly enhanced viral neutralizing activity. Hydrophobic substitutions for Arg343 selectively blocked binding of a monoclonal antibody (Hyb 246-05) that inhibits IAV binding activity. Our findings demonstrate an extended ligand binding site for mannosylated ligands and the significant contribution of the 343 side chain to specific recognition of multivalent microbial ligands, including high-mannose viral glycans.« less

The Biogeographic Pattern of Microbial Functional Genes along an Altitudinal Gradient of the Tibetan Pasture

PubMed Central

Qi, Qi; Zhao, Mengxin; Wang, Shiping; Ma, Xingyu; Wang, Yuxuan; Gao, Ying; Lin, Qiaoyan; Li, Xiangzhen; Gu, Baohua; Li, Guoxue; Zhou, Jizhong; Yang, Yunfeng

2017-01-01

As the highest place of the world, the Tibetan plateau is a fragile ecosystem. Given the importance of microbial communities in driving soil nutrient cycling, it is of interest to document the microbial biogeographic pattern here. We adopted a microarray-based tool named GeoChip 4.0 to investigate grassland microbial functional genes along an elevation gradient from 3200 to 3800 m above sea level open to free grazing by local herdsmen and wild animals. Interestingly, microbial functional diversities increase with elevation, so does the relative abundances of genes associated with carbon degradation, nitrogen cycling, methane production, cold shock and oxygen limitation. The range of Shannon diversities (10.27–10.58) showed considerably smaller variation than what was previously observed at ungrazed sites nearby (9.95–10.65), suggesting the important role of livestock grazing on microbial diversities. Closer examination showed that the dissimilarity of microbial community at our study sites increased with elevations, revealing an elevation-decay relationship of microbial functional genes. Both microbial functional diversity and the number of unique genes increased with elevations. Furthermore, we detected a tight linkage of greenhouse gas (CO2) and relative abundances of carbon cycling genes. Our biogeographic study provides insights on microbial functional diversity and soil biogeochemical cycling in Tibetan pastures. PMID:28659870

Characterization of microbial structures in Setul Limestone

NASA Astrophysics Data System (ADS)

Ezanie, A. S. Mohamad; Aziz, A. Che; Roslan, M. Kamal

2018-04-01

Setul Limestone in Langgun Island and Perlis are lack of sedimentary structures, which makes it difficult for paleoenvironmental study in the study area. The present study of limestone succession at Kaki Bukit and Teluk Mempelam area focuses on microbial related structure in order to constraint its depositional setting. The structures were identified as stromatolites and thrombolites, which resulted from the interaction of microbial with sediments by trapping, binding and/or precipitation of minerals. Both structures can be distinguished based on four main classifications, the megastructure, macrostructure, mesostructure and microstructure scales. These classifications assist in understanding its physical natures and lead to the recognition of paleoenvironment in the study area which is believed to be controlled by several factors such as environment, hydrodynamic, biological and chemical processes.

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

Dramatic Increases of Soil Microbial Functional Gene Diversity at the Treeline Ecotone of Changbai Mountain

PubMed Central

Shen, Congcong; Shi, Yu; Ni, Yingying; Deng, Ye; Van Nostrand, Joy D.; He, Zhili; Zhou, Jizhong; Chu, Haiyan

2016-01-01

The elevational and latitudinal diversity patterns of microbial taxa have attracted great attention in the past decade. Recently, the distribution of functional attributes has been in the spotlight. Here, we report a study profiling soil microbial communities along an elevation gradient (500–2200 m) on Changbai Mountain. Using a comprehensive functional gene microarray (GeoChip 5.0), we found that microbial functional gene richness exhibited a dramatic increase at the treeline ecotone, but the bacterial taxonomic and phylogenetic diversity based on 16S rRNA gene sequencing did not exhibit such a similar trend. However, the β-diversity (compositional dissimilarity among sites) pattern for both bacterial taxa and functional genes was similar, showing significant elevational distance-decay patterns which presented increased dissimilarity with elevation. The bacterial taxonomic diversity/structure was strongly influenced by soil pH, while the functional gene diversity/structure was significantly correlated with soil dissolved organic carbon (DOC). This finding highlights that soil DOC may be a good predictor in determining the elevational distribution of microbial functional genes. The finding of significant shifts in functional gene diversity at the treeline ecotone could also provide valuable information for predicting the responses of microbial functions to climate change. PMID:27524983

Estuarine microbial food web patterns in a Lake Erie coastal wetland.

PubMed

Lavrentyev, P J; McCarthy, M J; Klarer, D M; Jochem, F; Gardner, W S

2004-11-01

Composition and distribution of planktonic protists were examined relative to microbial food web dynamics (growth, grazing, and nitrogen cycling rates) at the Old Woman Creek (OWC) National Estuarine Research Reserve during an episodic storm event in July 2003. More than 150 protistan taxa were identified based on morphology. Species richness and microbial biomass measured via microscopy and flow cytometry increased along a stream-lake (Lake Erie) transect and peaked at the confluence. Water column ammonium (NH4+) uptake (0.06 to 1.82 microM N h(-1)) and regeneration (0.04 to 0.55 microM N h(-1)) rates, measured using 15NH4+ isotope dilution, followed the same pattern. Large light/dark NH4+ uptake differences were observed in the hypereutrophic OWC interior, but not at the phosphorus-limited Lake Erie site, reflecting the microbial community structural shift from net autotrophic to net heterotrophic. Despite this shift, microbial grazers (mostly choreotrich ciliates, taxon-specific growth rates up to 2.9 d(-1)) controlled nanophytoplankton and bacteria at all sites by consuming 76 to 110% and 56 to 97% of their daily production, respectively, in dilution experiments. Overall, distribution patterns and dynamics of microbial communities in OWC resemble those in marine estuaries, where plankton productivity increases along the river-sea gradient and reaches its maximum at the confluence.

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.

Seasonal and interannual dynamics of soil microbial biomass and available nitrogen in an alpine meadow in the eastern part of Qinghai-Tibet Plateau, China

NASA Astrophysics Data System (ADS)

Xu, Bo; Wang, Jinniu; Wu, Ning; Wu, Yan; Shi, Fusun

2018-01-01

Soil microbial activity varies seasonally in frozen alpine soils during cold seasons and plays a crucial role in available N pool accumulation in soil. The intra- and interannual patterns of microbial and nutrient dynamics reflect the influences of changing weather factors, and thus provide important insights into the biogeochemical cycles and ecological functions of ecosystems. We documented the seasonal and interannual dynamics of soil microbial and available N in an alpine meadow in the eastern part of Qinghai-Tibet Plateau, China, between April 2011 and October 2013. Soil was collected in the middle of each month and analyzed for water content, microbial biomass C (MBC) and N (MBN), dissolved organic C and N, and inorganic N. Soil microbial community composition was measured by the dilution-plate method. Fungi and actinomycetes dominated the microbial community during the nongrowing seasons, and the proportion of bacteria increased considerably during the early growing seasons. Trends of consistently increasing MBC and available N pools were observed during the nongrowing seasons. MBC sharply declined during soil thaw and was accompanied by a peak in available N pool. Induced by changes in soil temperatures, significant shifts in the structures and functions of microbial communities were observed during the winter-spring transition and largely contributed to microbial reduction. The divergent seasonal dynamics of different N forms showed a complementary nutrient supply pattern during the growing season. Similarities between the interannual dynamics of microbial biomass and available N pools were observed, and soil temperature and water conditions were the primary environmental factors driving interannual fluctuations. Owing to the changes in climate, seasonal soil microbial activities and nutrient supply patterns are expected to change further, and these changes may have crucial implications for the productivity and biodiversity of alpine ecosystems.

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.

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.

Enhanced methane production via repeated batch bioaugmentation pattern of enriched microbial consortia.

PubMed

Yang, Zhiman; Guo, Rongbo; Xu, Xiaohui; Wang, Lin; Dai, Meng

2016-09-01

Using batch and repeated batch cultivations, this study investigated the effects of bioaugmentation with enriched microbial consortia (named as EMC) on methane production from effluents of hydrogen-producing stage of potato slurry, as well as on the indigenous bacterial community. The results demonstrated that the improved methane production and shift of the indigenous bacterial community structure were dependent on the EMC/sludge ratio and bioaugmentation patterns. The methane yield and production rate in repeated batch bioaugmentation pattern of EMC were, respectively, average 15% and 10% higher than in one-time bioaugmentation pattern of EMC. DNA-sequencing approach showed that the enhanced methane production in the repeated batch bioaugmentation pattern of EMC mainly resulted from the enriched iron-reducing bacteria and the persistence of the introduced Syntrophomonas, which led to a rapid degradation of individual VFAs to methane. The findings contributed to understanding the correlation between the bioaugmentation of microbial consortia, community shift, and methane production. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Chlamydial infection in a high risk population: association with vaginal flora patterns.

PubMed

Marconi, Camila; Donders, Gilbert G G; Martin, Laura F; Ramos, Bruna R A; Duarte, Marli T C; Parada, Cristina M G L; Tristão, Andréa R; Silva, Márcia G

2012-04-01

This study aimed to determine the frequency of Chlamydia trachomatis (CT) infection among high risk Brazilian women and evaluate its association with vaginal flora patterns. This was a cross-sectional study, performed in an outpatient clinic of Bauru State Hospital, São Paulo, Brazil. A total of 142 women were included from 2006 to 2008. Inclusion criteria was dyspareunia, pain during bimanual exam, presence of excessive cervical mucus, cervical ectopy or with three or more episodes of abnormal vaginal flora (AVF) in the previous year before enrollment. Endocervical CT testing was performed by PCR. Vaginal swabs were collected for microscopic assessment of the microbial flora pattern. Gram-stained smears were classified in normal, intermediate or bacterial vaginosis (BV), and recognition of Candida sp. morphotypes. Wet mount smears were used for detection of Trichomonas vaginalis and aerobic vaginitis (AV). Thirty-four of 142 women (23.9%) tested positive for CT. AVF was found in 50 (35.2%) cases. The most frequent type of AVF was BV (17.6%). CT was strongly associated with the presence of AV (n = 7, 4.9%, P = 0.018), but not BV (n = 25, 17.6%, P = 0.80) or intermediate flora (n = 18, 12.7%, P = 0.28). A high rate of chlamydial infection was found in this population. Chlamydia infection is associated with aerobic vaginitis.

An Effective Quality Control of Pharmacologically Active Volatiles of Houttuynia cordata Thunb by Fast Gas Chromatography-Surface Acoustic Wave Sensor.

PubMed

Oh, Se Yeon

2015-06-03

Fast gas chromatography-surface acoustic wave sensor (GC/SAW) has been applied for the detection of the pharmacological volatiles emanated from Houttuynia cordata Thunb which is from South Korea. H. cordata Thunb with unpleasant and fishy odors shows a variety of pharmacological activities such as anti-microbial, anti-inflammatory, anti-cancer, and insect repellent. The aim of this study is to show a novel quality control by GC/SAW methodology for the discrimination of the three different parts of the plant such as leaves, aerial stems, and underground stems for H. cordata Thunb. Sixteen compounds were identified. β-Myrcene, cis-ocimene and decanal are the dominant volatiles for leaves (71.0%) and aerial stems (50.1%). While, monoterpenes (74.6%) are the dominant volatiles for underground stems. 2-Undecanone (1.3%) and lauraldehyde (3.5%) were found to be the characteristic components for leaves. Each part of the plant has its own characteristic fragrance pattern owing to its individual chemical compositions. Moreover, its individual characteristic fragrance patterns are conducive to discrimination of the three different parts of the plant. Consequently, fast GC/SAW can be a useful analytical method for quality control of the different parts of the plant with pharmacological volatiles as it provides second unit analysis, a simple and fragrant pattern recognition.

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.

Infrared and NIR Raman spectroscopy in medical microbiology

NASA Astrophysics Data System (ADS)

Naumann, Dieter

1998-04-01

FTIR and FT-NIR Raman spectra of intact microbial cells are highly specific, fingerprint-like signatures which can be used to (i) discriminate between diverse microbial species and strains, (ii) detect in situ intracellular components or structures such as inclusion bodies, storage materials or endospores, (iii) detect and quantify metabolically released CO2 in response to various different substrate, and (iv) characterize growth-dependent phenomena and cell-drug interactions. The characteristic information is extracted from the spectral contours by applying resolution enhancement techniques, difference spectroscopy, and pattern recognition methods such as factor-, cluster-, linear discriminant analysis, and artificial neural networks. Particularly interesting applications arise by means of a light microscope coupled to the spectrometer. FTIR spectra of micro-colonies containing less than 103 cells can be obtained from colony replica by a stamping technique that transfers micro-colonies growing on culture plates to a special IR-sample holder. Using a computer controlled x, y- stage together with mapping and video techniques, the fundamental tasks of microbiological analysis, namely detection, enumeration, and differentiation of micro- organisms can be integrated in one single apparatus. FTIR and NIR-FT-Raman spectroscopy can also be used in tandem to characterize medically important microorganisms. Currently novel methodologies are tested to take advantage of the complementary information of IR and Raman spectra. Representative examples on medically important microorganisms will be given that highlight the new possibilities of vibrational spectroscopies.

Influence of common mucosal co-factors on HIV infection in the female genital tract.

PubMed

Ferreira, Victor H; Kafka, Jessica K; Kaushic, Charu

2014-06-01

Women constitute almost half of HIV-infected population globally, and the female genital tract (FGT) accounts for approximately 40% of all new HIV infections worldwide. The FGT is composed of upper and lower parts, distinct in their morphological and functional characteristics. Co-factors in the genital microenvironment, such as presence of hormones, semen, and other sexually transmitted infections, can facilitate or deter HIV infection and play a critical role in determining susceptibility to HIV. In this review, we examine some of these co-factors and their potential influence. Presence of physical and chemical barriers such as epithelial tight junctions, mucus, and anti-microbial peptides can actively block and inhibit viral replication, presenting a significant deterrent to HIV. Upon exposure, HIV and other pathogens first encounter the genital epithelium: cells that express a wide repertoire of pattern recognition receptors that can recognize and directly initiate innate immune responses. These and other interactions in the genital tract can lead to direct and indirect inflammation and enhance the number of local target cells, immune activation, and microbial translocation, all of which promote HIV infection and replication. Better understanding of the dynamics of HIV transmission in the female genital tract would be invaluable for improving the design of prophylactic strategies against HIV. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

Post-Fire Spatial Patterns of Soil Nitrogen Mineralization and Microbial Abundance

PubMed Central

Smithwick, Erica A. H.; Naithani, Kusum J.; Balser, Teri C.; Romme, William H.; Turner, Monica G.

2012-01-01

Stand-replacing fires influence soil nitrogen availability and microbial community composition, which may in turn mediate post-fire successional dynamics and nutrient cycling. However, fires create patchiness at both local and landscape scales and do not result in consistent patterns of ecological dynamics. The objectives of this study were to (1) quantify the spatial structure of microbial communities in forest stands recently affected by stand-replacing fire and (2) determine whether microbial variables aid predictions of in situ net nitrogen mineralization rates in recently burned stands. The study was conducted in lodgepole pine (Pinus contorta var. latifolia) and Engelmann spruce/subalpine fir (Picea engelmannii/Abies lasiocarpa) forest stands that burned during summer 2000 in Greater Yellowstone (Wyoming, USA). Using a fully probabilistic spatial process model and Bayesian kriging, the spatial structure of microbial lipid abundance and fungi-to-bacteria ratios were found to be spatially structured within plots two years following fire (for most plots, autocorrelation range varied from 1.5 to 10.5 m). Congruence of spatial patterns among microbial variables, in situ net N mineralization, and cover variables was evident. Stepwise regression resulted in significant models of in situ net N mineralization and included variables describing fungal and bacterial abundance, although explained variance was low (R2<0.29). Unraveling complex spatial patterns of nutrient cycling and the biotic factors that regulate it remains challenging but is critical for explaining post-fire ecosystem function, especially in Greater Yellowstone, which is projected to experience increased fire frequencies by mid 21st Century. PMID:23226324

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

How agricultural management shapes soil microbial communities: patterns emerging from genetic and genomic studies

NASA Astrophysics Data System (ADS)

Daly, Amanda; Grandy, A. Stuart

2016-04-01

Agriculture is a predominant land use and thus a large influence on global carbon (C) and nitrogen (N) balances, climate, and human health. If we are to produce food, fiber, and fuel sustainably we must maximize agricultural yield while minimizing negative environmental consequences, goals towards which we have made great strides through agronomic advances. However, most agronomic strategies have been designed with a view of soil as a black box, largely ignoring the way management is mediated by soil biota. Because soil microbes play a central role in many of the processes that deliver nutrients to crops and support their health and productivity, agricultural management strategies targeted to exploit or support microbial activity should deliver additional benefits. To do this we must determine how microbial community structure and function are shaped by agricultural practices, but until recently our characterizations of soil microbial communities in agricultural soils have been largely limited to broad taxonomic classes due to methodological constraints. With advances in high-throughput genetic and genomic sequencing techniques, better taxonomic resolution now enables us to determine how agricultural management affects specific microbes and, in turn, nutrient cycling outcomes. Here we unite findings from published research that includes genetic or genomic data about microbial community structure (e.g. 454, Illumina, clone libraries, qPCR) in soils under agricultural management regimes that differ in type and extent of tillage, cropping selections and rotations, inclusion of cover crops, organic amendments, and/or synthetic fertilizer application. We delineate patterns linking agricultural management to microbial diversity, biomass, C- and N-content, and abundance of microbial taxa; furthermore, where available, we compare patterns in microbial communities to patterns in soil extracellular enzyme activities, catabolic profiles, inorganic nitrogen pools, and nitrogen transforming processes. Where genetic data are scarce, we further inform our observations with data from phosopholipid fatty acid, ribosomal intergenic spacer, (terminal) restriction fragment length polymorphism, and denaturing gradient gel electrophoresis analyses. By summarizing the most current information about microbial community structure under different agricultural management strategies, we hope to jumpstart a dialogue that could ultimately inspire novel - and sustainable - agronomic approaches that work with and through soil microbes.

Small-scale spatial variability of soil microbial community composition and functional diversity in a mixed forest

NASA Astrophysics Data System (ADS)

Wang, Qiufeng; Tian, Jing; Yu, Guirui

2014-05-01

Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.

Plant diversity predicts beta but not alpha diversity of soil microbes across grasslands worldwide

USGS Publications Warehouse

Prober, Suzanne M.; Leff, Jonathan W.; Bates, Scott T.; Borer, Elizabeth T.; Firn, Jennifer; Harpole, W. Stanley; Lind, Eric M.; Seabloom, Eric W.; Adler, Peter B.; Bakker, Jonathan D.; Cleland, Elsa E.; DeCrappeo, Nicole; DeLorenze, Elizabeth; Hagenah, Nicole; Hautier, Yann; Hofmockel, Kirsten S.; Kirkman, Kevin P.; Knops, Johannes M. H.; La Pierre, Kimberly J.; MacDougall, Andrew S.; McCulley, Rebecca L.; Mitchell, Charles E.; Risch, Anita C.; Schuetz, Martin; Stevens, Carly J.; Williams, Ryan J.; Fierer, Noah

2015-01-01

Aboveground–belowground interactions exert critical controls on the composition and function of terrestrial ecosystems, yet the fundamental relationships between plant diversity and soil microbial diversity remain elusive. Theory predicts predominantly positive associations but tests within single sites have shown variable relationships, and associations between plant and microbial diversity across broad spatial scales remain largely unexplored. We compared the diversity of plant, bacterial, archaeal and fungal communities in one hundred and forty-five 1 m2 plots across 25 temperate grassland sites from four continents. Across sites, the plant alpha diversity patterns were poorly related to those observed for any soil microbial group. However, plant beta diversity (compositional dissimilarity between sites) was significantly correlated with the beta diversity of bacterial and fungal communities, even after controlling for environmental factors. Thus, across a global range of temperate grasslands, plant diversity can predict patterns in the composition of soil microbial communities, but not patterns in alpha diversity.

Biofilm community succession: a neutral perspective.

PubMed

Woodcock, Stephen; Sloan, William T

2017-05-22

Although biofilms represent one of the dominant forms of life in aqueous environments, our understanding of the assembly and development of their microbial communities remains relatively poor. In recent years, several studies have addressed this and have extended the concepts of succession theory in classical ecology into microbial systems. From these datasets, niche-based conceptual models have been developed explaining observed biodiversity patterns and their dynamics. These models have not, however, been formulated mathematically and so remain untested. Here, we further develop spatially resolved neutral community models and demonstrate that these can also explain these patterns and offer alternative explanations of microbial succession. The success of neutral models suggests that stochastic effects alone may have a much greater influence on microbial community succession than previously acknowledged. Furthermore, such models are much more readily parameterised and can be used as the foundation of more complex and realistic models of microbial community succession.

Chemotactic preferences govern competition and pattern formation in simulated two-strain microbial communities.

PubMed

Centler, Florian; Thullner, Martin

2015-01-01

Substrate competition is a common mode of microbial interaction in natural environments. While growth properties play an important and well-studied role in competition, we here focus on the influence of motility. In a simulated two-strain community populating a homogeneous two-dimensional environment, strains competed for a common substrate and only differed in their chemotactic preference, either responding more sensitively to a chemoattractant excreted by themselves or responding more sensitively to substrate. Starting from homogeneous distributions, three possible behaviors were observed depending on the competitors' chemotactic preferences: (i) distributions remained homogeneous, (ii) patterns formed but dissolved at a later time point, resulting in a shifted community composition, and (iii) patterns emerged and led to the extinction of one strain. When patterns formed, the more aggregating strain populated the core of microbial aggregates where starving conditions prevailed, while the less aggregating strain populated the more productive zones at the fringe or outside aggregates, leading to a competitive advantage of the less aggregating strain. The presence of a competitor was found to modulate a strain's behavior, either suppressing or promoting aggregate formation. This observation provides a potential mechanism by which an aggregated lifestyle might evolve even if it is initially disadvantageous. Adverse effects can be avoided as a competitor hinders aggregate formation by a strain which has just acquired this ability. The presented results highlight both, the importance of microbial motility for competition and pattern formation, and the importance of the temporal evolution, or history, of microbial communities when trying to explain an observed distribution.

The Biogeographic Pattern of Microbial Functional Genes along an Altitudinal Gradient of the Tibetan Pasture

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

Qi, Qi; Zhao, Mengxin; Wang, Shiping

As the highest place of the world, the Tibetan plateau is a fragile ecosystem. Given the importance of microbial communities in driving soil nutrient cycling, it is of interest to document the microbial biogeographic pattern here. We adopted a microarray-based tool named GeoChip 4.0 to investigate grassland microbial functional genes along an elevation gradient from 3200 to 3800 m above sea level open to free grazing by local herdsmen and wild animals. Interestingly, microbial functional diversities increase with elevation, so does the relative abundances of genes associated with carbon degradation, nitrogen cycling, methane production, cold shock and oxygen limitation. Themore » range of Shannon diversities (10.27–10.58) showed considerably smaller variation than what was previously observed at ungrazed sites nearby (9.95–10.65), suggesting the important role of livestock grazing on microbial diversities. Closer examination showed that the dissimilarity of microbial community at our study sites increased with elevations, revealing an elevation-decay relationship of microbial functional genes. Both microbial functional diversity and the number of unique genes increased with elevations. Furthermore, we detected a tight linkage of greenhouse gas (CO2) and relative abundances of carbon cycling genes. Our biogeographic study provides insights on microbial functional diversity and soil biogeochemical cycling in Tibetan pastures.« less

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

Role of salivary epithelial toll-like receptors 2 and 4 in modulating innate immune responses in chronic periodontitis.

PubMed

Swaminathan, V; Prakasam, S; Puri, V; Srinivasan, M

2013-12-01

Chronic periodontitis is initiated by sequential colonization with a broad array of bacteria and is perpetuated by an immune-inflammatory response to the changing biofilm. Host recognition of microbes is largely mediated by toll-like receptors (TLRs), which interact with conserved pathogen-associated molecular patterns. Based on ligand recognition, TLR-2 and TLR-4 interact with most periodontal pathogens. Extracrevicular bacterial reservoirs, such as the oral epithelial cells, contribute to the persistence of periodontitis. Human saliva is a rich source of oral epithelial cells that express functional TLRs. In this study we investigated the role of salivary epithelial cell (SEC) TLR-2 and TLR-4 in patients with generalized chronic periodontitis. Unstimulated whole saliva (UWS) was collected from patients with generalized chronic periodontitis and from healthy individuals after obtaining informed consent. Epithelial cells isolated from each UWS sample were assessed for TLR-2, TLR-4, peptidoglycan recognition protein (PGRP)-3 and PGRP-4 by quantitative real-time PCR. In addition, the SECs were stimulated in vitro with microbial products for up to 24 h. The culture supernatant was assessed for cytokines by ELISA. Stimulation with TLR-2- or TLR-4-specific ligands induced cytokine secretion with differential kinetics and up-regulated TLR2 and TLR4 mRNAs, respectively, in cultures of SECs from patients with periodontitis. In addition, the SECs from patients with periodontitis exhibited reduced PGRP3 and PGRP4 mRNAs, the TLR-responsive genes with antibacterial properties. SECs derived from the UWS of patients with chronic periodontitis are phenotypically distinct and could represent potential resources for assessing the epithelial responses to periodontal pathogens in the course of disease progression and persistence. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The role of airway macrophages in apoptotic cell clearance following acute and chronic lung inflammation.

PubMed

Grabiec, Aleksander M; Hussell, Tracy

2016-07-01

Acute and chronic inflammatory responses in the lung are associated with the accumulation of large quantities of immune and structural cells undergoing apoptosis, which need to be engulfed by phagocytes in a process called 'efferocytosis'. Apoptotic cell recognition and removal from the lung is mediated predominantly by airway macrophages, though immature dendritic cells and non-professional phagocytes, such as epithelial cells and mesenchymal cells, can also display this function. Efficient clearance of apoptotic cells from the airways is essential for successful resolution of inflammation and the return to lung homeostasis. Disruption of this process leads to secondary necrosis of accumulating apoptotic cells, release of necrotic cell debris and subsequent uncontrolled inflammatory activation of the innate immune system by the released 'damage associated molecular patterns' (DAMPS). To control the duration of the immune response and prevent autoimmune reactions, anti-inflammatory signalling cascades are initiated in the phagocyte upon apoptotic cell uptake, mediated by a range of receptors that recognise specific phospholipids or proteins externalised on, or secreted by, the apoptotic cell. However, prolonged activation of apoptotic cell recognition receptors, such as the family of receptor tyrosine kinases Tyro3, Axl and MerTK (TAM), may delay or prevent inflammatory responses to subsequent infections. In this review, we will discuss recent advances in our understanding of the mechanism controlling apoptotic cell recognition and removal from the lung in homeostasis and during inflammation, the contribution of defective efferocytosis to chronic inflammatory lung diseases, such as chronic obstructive pulmonary disease, asthma and cystic fibrosis, and implications of the signals triggered by apoptotic cells in the susceptibility to pulmonary microbial infections.

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

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

A trait-based approach for examining microbial community assembly

NASA Astrophysics Data System (ADS)

Prest, T. L.; Nemergut, D.

2015-12-01

Microorganisms regulate all of Earth's major biogeochemical cycles and an understanding of how microbial communities assemble is a key part in evaluating controls over many types of ecosystem processes. Rapid advances in technology and bioinformatics have led to a better appreciation for the variation in microbial community structure in time and space. Yet, advances in theory are necessary to make sense of these data and allow us to generate unifying hypotheses about the causes and consequences of patterns in microbial biodiversity and what they mean for ecosystem function. Here, I will present a metaanalysis of microbial community assembly from a variety of successional and post-disturbance systems. Our analysis shows various distinct patterns in community assembly, and the potential importance of nutrients and dispersal in shaping microbial community beta diversity in these systems. We also used a trait-based approach to generate hypotheses about the mechanisms driving patterns of microbial community assembly and the implications for function. Our work reveals the importance of rRNA operon copy number as a community aggregated trait in helping to reconcile differences in community dynamics between distinct types of successional and disturbed systems. Specifically, our results demonstrate that decreases in average copy number can be a common feature of communities across various drivers of ecological succession, supporting a transition from an r-selected to a K-selected community. Importantly, our work supports the scaling of the copy number trait over multiple levels of biological organization, from cells to populations and communities, and has implications for both ecology and evolution. Trait-based approaches are an important next step to generate and test hypotheses about the forces structuring microbial communities and the subsequent consequences for ecosystem function.

Macroecology of unicellular organisms - patterns and processes.

PubMed

Soininen, Janne

2012-02-01

Macroecology examines the relationship between organisms and their environment at large spatial (and temporal) scales. Typically, macroecologists explain the large-scale patterns of abundance, distribution and diversity. Despite the difficulties in sampling and characterizing microbial diversity, macroecologists have recently also been interested in unicellular organisms. Here, I review the current advances made in microbial macroecology, as well as discuss related ecosystem functions. Overall, it seems that microorganisms suit surprisingly well to known species abundance distributions and show positive relationship between distribution and adundance. Microbial species-area and distance-decay relationships tend to be weaker than for macroorganisms, but nonetheless significant. Few findings on altitudinal gradients in unicellular taxa seem to differ greatly from corresponding findings for larger taxa, whereas latitudinal gradients among microorganisms have either been clearly evident or absent depending on the context. Literature also strongly emphasizes the role of spatial scale for the patterns of diversity and suggests that patterns are affected by species traits as well as ecosystem characteristics. Finally, I discuss the large role of local biotic and abiotic variables driving the community assembly in unicellular taxa and eventually dictating how multiple ecosystem processes are performed. Present review highlights the fact that most microorganisms may not differ fundamentally from larger taxa in their large-scale distribution patterns. Yet, review also shows that many aspects of microbial macroecology are still relatively poorly understood and specific patterns depend on focal taxa and ecosystem concerned. © 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.

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.

Functional diversity of human vaginal APC subsets in directing T cell responses

PubMed Central

Duluc, Dorothée; Gannevat, Julien; Anguiano, Esperanza; Zurawski, Sandra; Carley, Michael; Boreham, Muriel; Stecher, Jack; Dullaers, Melissa; Banchereau, Jacques; Oh, SangKon

2012-01-01

Human vaginal mucosa is the major entry site of sexually transmitted pathogens and thus has long been attractive as a site for mounting mucosal immunity. It is also known as a tolerogenic microenvironment. Here, we demonstrate that immune responses in the vagina are orchestrated by the functional diversity of four major antigen-presenting cell (APC) subsets. Langerhans cells (LCs) and CD14− lamina propria (LP)-DCs polarize CD4+ and CD8+ T cells toward Th2, whereas CD14+ LP-DCs and macrophages polarize CD4+ T cells toward Th1. Both LCs and CD14− LP-DCs are potent inducers of Th22. Due to their functional specialties and the different expression levels of pattern-recognition receptors on the APC subsets, microbial products do not bias them to elicit common types of immune responses (Th1 or Th2). To evoke desired types of adaptive immune responses in the human vagina, antigens may need to be targeted to proper APC subsets with right adjuvants. PMID:23131784

Artificial odor discrimination system using electronic nose and neural networks for the identification of urinary tract infection.

PubMed

Kodogiannis, Vassilis S; Lygouras, John N; Tarczynski, Andrzej; Chowdrey, Hardial S

2008-11-01

Current clinical diagnostics are based on biochemical, immunological, or microbiological methods. However, these methods are operator dependent, time-consuming, expensive, and require special skills, and are therefore, not suitable for point-of-care testing. Recent developments in gas-sensing technology and pattern recognition methods make electronic nose technology an interesting alternative for medical point-of-care devices. An electronic nose has been used to detect urinary tract infection from 45 suspected cases that were sent for analysis in a U.K. Public Health Registry. These samples were analyzed by incubation in a volatile generation test tube system for 4-5 h. Two issues are being addressed, including the implementation of an advanced neural network, based on a modified expectation maximization scheme that incorporates a dynamic structure methodology and the concept of a fusion of multiple classifiers dedicated to specific feature parameters. This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology.

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.

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.

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.

Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate

PubMed Central

Bokulich, Nicholas A.; Thorngate, John H.; Richardson, Paul M.; Mills, David A.

2014-01-01

Wine grapes present a unique biogeography model, wherein microbial biodiversity patterns across viticultural zones not only answer questions of dispersal and community maintenance, they are also an inherent component of the quality, consumer acceptance, and economic appreciation of a culturally important food product. On their journey from the vineyard to the wine bottle, grapes are transformed to wine through microbial activity, with indisputable consequences for wine quality parameters. Wine grapes harbor a wide range of microbes originating from the surrounding environment, many of which are recognized for their role in grapevine health and wine quality. However, determinants of regional wine characteristics have not been identified, but are frequently assumed to stem from viticultural or geological factors alone. This study used a high-throughput, short-amplicon sequencing approach to demonstrate that regional, site-specific, and grape-variety factors shape the fungal and bacterial consortia inhabiting wine-grape surfaces. Furthermore, these microbial assemblages are correlated to specific climatic features, suggesting a link between vineyard environmental conditions and microbial inhabitation patterns. Taken together, these factors shape the unique microbial inputs to regional wine fermentations, posing the existence of nonrandom “microbial terroir” as a determining factor in regional variation among wine grapes. PMID:24277822

Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate.

PubMed

Bokulich, Nicholas A; Thorngate, John H; Richardson, Paul M; Mills, David A

2014-01-07

Wine grapes present a unique biogeography model, wherein microbial biodiversity patterns across viticultural zones not only answer questions of dispersal and community maintenance, they are also an inherent component of the quality, consumer acceptance, and economic appreciation of a culturally important food product. On their journey from the vineyard to the wine bottle, grapes are transformed to wine through microbial activity, with indisputable consequences for wine quality parameters. Wine grapes harbor a wide range of microbes originating from the surrounding environment, many of which are recognized for their role in grapevine health and wine quality. However, determinants of regional wine characteristics have not been identified, but are frequently assumed to stem from viticultural or geological factors alone. This study used a high-throughput, short-amplicon sequencing approach to demonstrate that regional, site-specific, and grape-variety factors shape the fungal and bacterial consortia inhabiting wine-grape surfaces. Furthermore, these microbial assemblages are correlated to specific climatic features, suggesting a link between vineyard environmental conditions and microbial inhabitation patterns. Taken together, these factors shape the unique microbial inputs to regional wine fermentations, posing the existence of nonrandom "microbial terroir" as a determining factor in regional variation among wine grapes.

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.

Oceans and human health: Emerging public health risks n the marine environment

PubMed Central

Fleming, L.E.; Broad, K.; Clement, A.; Dewailly, E.; Elmir, S.; Knap, A.; Pomponi, S.A.; Smith, S.; Gabriele, H. Solo; Walsh, P.

2008-01-01

There has been an increasing recognition of the inter-relationship between human health and the oceans. Traditionally, the focus of research and concern has been on the impact of human activities on the oceans, particularly through anthropogenic pollution and the exploitation of marine resources. More recently, there has been recognition of the potential direct impact of the oceans on human health, both detrimental and beneficial. Areas identified include: global change, harmful algal blooms (HABs), microbial and chemical contamination of marine waters and seafood, and marine models and natural products from the seas. It is hoped that through the recognition of the inter-dependence of the health of both humans and the oceans, efforts will be made to restore and preserve the oceans. PMID:16996542

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.

Effects of lead and cadmium nitrate on biomass and substrate utilization pattern of soil microbial communities.

PubMed

Muhammad, Akmal; Xu, Jianming; Li, Zhaojun; Wang, Haizhen; Yao, Huaiying

2005-07-01

A study was conducted to evaluate the effects of different concentrations of lead (Pb) and cadmium (Cd) applied as their nitrates on soil microbial biomass carbon (C(mic)) and nitrogen (N(mic)), and substrate utilization pattern of soil microbial communities. The C(mic) and N(mic) contents were determined at 0, 14, 28, 42 and 56 days after heavy metal application (DAA). The results showed a significant decline in the C(mic) for all Pb and Cd amended soils from the start to 28 DAA. From 28 to 56 DAA, C(mic) contents changed non-significantly for all other treatments except for 600 mgkg(-1) Pb and 100 mgkg(-1) Cd in which it declined significantly from 42 to 56 DAA. The N(mic) contents also decreased significantly from start to 28 DAA for all other Pb and Cd treatments except for 200 mgkg(-1) Pb which did not show significant difference from the control. Control and 200 mgkg(-1) Pb had significantly lower soil microbial biomass C:N ratio as compared with other Pb treatments from 14 to 42 DAA, however at 56 DAA, only 1000 mgkg(-1) Pb showed significantly higher C:N ratio compared with other treatments. No significant difference in C:N ratio for all Cd treated soils was seen from start to 28 DAA, however from 42 to 56 DAA, 100 mgkg(-1) Pb showed significantly higher C:N ratio compared with other treatments. On 56 DAA, substrate utilization pattern of soil microbial communities was determined by inoculating Biolog ECO plates. The results indicated that Pb and Cd addition inhibited the functional activity of soil microbial communities as indicated by the intensity of average well color development (AWCD) during 168 h of incubation. Multivariate analysis of sole carbon source utilization pattern demonstrated that higher levels of heavy metal application had significantly affected soil microbial community structure.

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.

Microbial communities may modify how litter quality affects potential decomposition rates as tree species migrate

Treesearch

Ashley D. Keiser; Jennifer D. Knoepp; Mark A. Bradford

2013-01-01

Background and aims Climate change alters regional plant species distributions, creating new combinations of litter species and soil communities. Biogeographic patterns in microbial communities relate to dissimilarity in microbial community function, meaning novel litters to communities may decompose differently than predicted from their chemical composition. Therefore...

A communal catalogue reveals Earth’s multiscale microbial diversity

DOE PAGES

Thompson, Luke R.; Sanders, Jon G.; McDonald, Daniel; ...

2017-11-01

Our growing awareness of the importance and diversity of the microbial world contrasts starkly with our limited understanding of its fundamental structure. Despite remarkable advances in DNA sequence generation, a lack of standardized protocols and common analytical framework impede useful comparison between studies, hindering development of global inferences about microbial life on Earth. Here, we show that with coordinated protocols, exact microbial 16S rRNA gene sequences can be followed across scores of individual studies, revealing patterns of diversity, community structure, and life history strategy at a planetary scale. Using 27,751 crowdsourced environmental samples comprising more than 2.2 billion reads, wemore » find sharp divides between host-associated and free-living communities. We show that the distribution of taxonomic and sequence diversity follows consistent trends across samples types and along gradients of environmental parameters, highlighting some of the global evolutionary patterns and ecological principles that underpin Earth’s microbiome. Here, this dataset provides the most complete environmental survey of our microbial world to date, and serves as a growing reference to provide immediate global context to future microbial surveys.« less

A communal catalogue reveals Earth’s multiscale microbial diversity

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

Thompson, Luke R.; Sanders, Jon G.; McDonald, Daniel

Our growing awareness of the importance and diversity of the microbial world contrasts starkly with our limited understanding of its fundamental structure. Despite remarkable advances in DNA sequence generation, a lack of standardized protocols and common analytical framework impede useful comparison between studies, hindering development of global inferences about microbial life on Earth. Here, we show that with coordinated protocols, exact microbial 16S rRNA gene sequences can be followed across scores of individual studies, revealing patterns of diversity, community structure, and life history strategy at a planetary scale. Using 27,751 crowdsourced environmental samples comprising more than 2.2 billion reads, wemore » find sharp divides between host-associated and free-living communities. We show that the distribution of taxonomic and sequence diversity follows consistent trends across samples types and along gradients of environmental parameters, highlighting some of the global evolutionary patterns and ecological principles that underpin Earth’s microbiome. Here, this dataset provides the most complete environmental survey of our microbial world to date, and serves as a growing reference to provide immediate global context to future microbial surveys.« less

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.

Fabrication of three dimensional patterns of wide dimensional range using microbes and their applications

NASA Astrophysics Data System (ADS)

Mehta, Sunita; Murugeson, Saravanan; Prakash, Balaji; Deepak

2015-10-01

Inspired by the wound healing property of certain trees, we report a novel microbes based additive process for producing three dimensional patterns, which has a potential of engineering applications in a variety of fields. Imposing a two dimensional pattern of microbes on a gel media and allowing them to grow in the third dimension is known from its use in biological studies. Instead, we have introduced an intermediate porous substrate between the gel media and the microbial growth, which enables three dimensional patterns in specific forms that can be lifted off and used in engineering applications. In order to demonstrate the applicability of this idea in a diverse set of areas, two applications are selected. In one, using this method of microbial growth, we have fabricated microlenses for enhanced light extraction in organic light emitting diodes, where densely packed microlenses of the diameters of hundreds of microns lead to luminance increase by a factor of 1.24X. In another entirely different type of application, braille text patterns are prepared on a normal office paper where the grown microbial colonies serve as braille tactile dots. Braille dot patterns thus prepared meet the standard specifications (size and spacing) for braille books.

Functions of galectins as 'self/non-self'-recognition and effector factors.

PubMed

Vasta, Gerardo R; Feng, Chiguang; González-Montalbán, Nuria; Mancini, Justin; Yang, Lishi; Abernathy, Kelsey; Frost, Graeme; Palm, Cheyenne

2017-07-31

Carbohydrate structures on the cell surface encode complex information that through specific recognition by carbohydrate-binding proteins (lectins) modulates interactions between cells, cells and the extracellular matrix, or mediates recognition of potential microbial pathogens. Galectins are a family of ß-galactoside-binding lectins, which are evolutionary conserved and have been identified in most organisms, from fungi to invertebrates and vertebrates, including mammals. Since their discovery in the 1970s, their biological roles, initially understood as limited to recognition of endogenous carbohydrate ligands in embryogenesis and development, have expanded in recent years by the discovery of their roles in tissue repair and regulation of immune homeostasis. More recently, evidence has accumulated to support the notion that galectins can also bind glycans on the surface of potentially pathogenic microbes, and function as recognition and effector factors in innate immunity, thus establishing a new paradigm. Furthermore, some parasites 'subvert' the recognition roles of the vector/host galectins for successful attachment or invasion. These recent findings have revealed a striking functional diversification in this structurally conserved lectin family. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Anoxia stimulates microbially catalyzed metal release from Animas River sediments.

PubMed

Saup, Casey M; Williams, Kenneth H; Rodríguez-Freire, Lucía; Cerrato, José M; Johnston, Michael D; Wilkins, Michael J

2017-04-19

The Gold King Mine spill in August 2015 released 11 million liters of metal-rich mine waste to the Animas River watershed, an area that has been previously exposed to historical mining activity spanning more than a century. Although adsorption onto fluvial sediments was responsible for rapid immobilization of a significant fraction of the spill-associated metals, patterns of longer-term mobility are poorly constrained. Metals associated with river sediments collected downstream of the Gold King Mine in August 2015 exhibited distinct presence and abundance patterns linked to location and mineralogy. Simulating riverbed burial and development of anoxic conditions, sediment microcosm experiments amended with Animas River dissolved organic carbon revealed the release of specific metal pools coupled to microbial Fe- and SO 4 2- -reduction. Results suggest that future sedimentation and burial of riverbed materials may drive longer-term changes in patterns of metal remobilization linked to anaerobic microbial metabolism, potentially driving decreases in downstream water quality. Such patterns emphasize the need for long-term water monitoring efforts in metal-impacted watersheds.

Spatial and temporal microbial pollution patterns in a tropical estuary during high and low river flow conditions.

PubMed

Wiegner, T N; Edens, C J; Abaya, L M; Carlson, K M; Lyon-Colbert, A; Molloy, S L

2017-01-30

Spatial and temporal patterns of coastal microbial pollution are not well documented. Our study examined these patterns through measurements of fecal indicator bacteria (FIB), nutrients, and physiochemical parameters in Hilo Bay, Hawai'i, during high and low river flow. >40% of samples tested positive for the human-associated Bacteroides marker, with highest percentages near rivers. Other FIB were also higher near rivers, but only Clostridium perfringens concentrations were related to discharge. During storms, FIB concentrations were three times to an order of magnitude higher, and increased with decreasing salinity and water temperature, and increasing turbidity. These relationships and high spatial resolution data for these parameters were used to create Enterococcus spp. and C. perfringens maps that predicted exceedances with 64% and 95% accuracy, respectively. Mapping microbial pollution patterns and predicting exceedances is a valuable tool that can improve water quality monitoring and aid in visualizing FIB hotspots for management actions. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Structure and co-occurrence patterns in microbial communities under acute environmental stress reveal ecological factors fostering resilience.

PubMed

Mandakovic, Dinka; Rojas, Claudia; Maldonado, Jonathan; Latorre, Mauricio; Travisany, Dante; Delage, Erwan; Bihouée, Audrey; Jean, Géraldine; Díaz, Francisca P; Fernández-Gómez, Beatriz; Cabrera, Pablo; Gaete, Alexis; Latorre, Claudio; Gutiérrez, Rodrigo A; Maass, Alejandro; Cambiazo, Verónica; Navarrete, Sergio A; Eveillard, Damien; González, Mauricio

2018-04-12

Understanding the factors that modulate bacterial community assembly in natural soils is a longstanding challenge in microbial community ecology. In this work, we compared two microbial co-occurrence networks representing bacterial soil communities from two different sections of a pH, temperature and humidity gradient occurring along a western slope of the Andes in the Atacama Desert. In doing so, a topological graph alignment of co-occurrence networks was used to determine the impact of a shift in environmental variables on OTUs taxonomic composition and their relationships. We observed that a fraction of association patterns identified in the co-occurrence networks are persistent despite large environmental variation. This apparent resilience seems to be due to: (1) a proportion of OTUs that persist across the gradient and maintain similar association patterns within the community and (2) bacterial community ecological rearrangements, where an important fraction of the OTUs come to fill the ecological roles of other OTUs in the other network. Actually, potential functional features suggest a fundamental role of persistent OTUs along the soil gradient involving nitrogen fixation. Our results allow identifying factors that induce changes in microbial assemblage configuration, altering specific bacterial soil functions and interactions within the microbial communities in natural environments.

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.

Co-occurrence Networks Among Bacteria and Microbial Eukaryotes of Lake Baikal During a Spring Phytoplankton Bloom.

PubMed

Mikhailov, Ivan S; Zakharova, Yulia R; Bukin, Yuri S; Galachyants, Yuri P; Petrova, Darya P; Sakirko, Maria V; Likhoshway, Yelena V

2018-06-07

The pelagic zone of Lake Baikal is an ecological niche where phytoplankton bloom causes increasing microbial abundance in spring which plays a key role in carbon turnover in the freshwater lake. Co-occurrence patterns revealed among different microbes can be applied to predict interactions between the microbes and environmental conditions in the ecosystem. We used 454 pyrosequencing of 16S rRNA and 18S rRNA genes to study bacterial and microbial eukaryotic communities and their co-occurrence patterns at the pelagic zone of Lake Baikal during a spring phytoplankton bloom. We found that microbes within one domain mostly correlated positively with each other and are highly interconnected. The highly connected taxa in co-occurrence networks were operational taxonomic units (OTUs) of Actinobacteria, Bacteroidetes, Alphaproteobacteria, and autotrophic and unclassified Eukaryota which might be analogous to microbial keystone taxa. Constrained correspondence analysis revealed the relationships of bacterial and microbial eukaryotic communities with geographical location.

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.

Sepsis and septic shock

PubMed Central

Hotchkiss, Richard S.; Moldawer, Lyle L.; Opal, Steven M.; Reinhart, Konrad; Turnbull, Isaiah R.; Vincent, Jean-Louis

2017-01-01

For more than two decades, sepsis was defined as a microbial infection that produces fever (or hypothermia), tachycardia, tachypnoea and blood leukocyte changes. Sepsis is now increasingly being considered a dysregulated systemic inflammatory and immune response to microbial invasion that produces organ injury for which mortality rates are declining to 15–25%. Septic shock remains defined as sepsis with hyperlactataemia and concurrent hypotension requiring vasopressor therapy, with in-hospital mortality rates approaching 30–50%. With earlier recognition and more compliance to best practices, sepsis has become less of an immediate life-threatening disorder and more of a long-term chronic critical illness, often associated with prolonged inflammation, immune suppression, organ injury and lean tissue wasting. Furthermore, patients who survive sepsis have continuing risk of mortality after discharge, as well as long-term cognitive and functional deficits. Earlier recognition and improved implementation of best practices have reduced in-hospital mortality, but results from the use of immunomodulatory agents to date have been disappointing. Similarly, no biomarker can definitely diagnose sepsis or predict its clinical outcome. Because of its complexity, improvements in sepsis outcomes are likely to continue to be slow and incremental. PMID:28117397

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.

The intestinal complement system in inflammatory bowel disease: Shaping intestinal barrier function.

PubMed

Sina, Christian; Kemper, Claudia; Derer, Stefanie

2018-06-01

The complement system is part of innate sensor and effector systems such as the Toll-like receptors (TLRs). It recognizes and quickly systemically and/or locally respond to microbial-associated molecular patterns (MAMPs) with a tailored defense reaction. MAMP recognition by intestinal epithelial cells (IECs) and appropriate immune responses are of major importance for the maintenance of intestinal barrier function. Enterocytes highly express various complement components that are suggested to be pivotal for proper IEC function. Appropriate activation of the intestinal complement system seems to play an important role in the resolution of chronic intestinal inflammation, while over-activation and/or dysregulation may worsen intestinal inflammation. Mice deficient for single complement components suffer from enhanced intestinal inflammation mimicking the phenotype of patients with chronic inflammatory bowel disease (IBD) such as Crohn's disease (CD) or ulcerative colitis (UC). However, the mechanisms leading to complement expression in IECs seem to differ markedly between UC and CD patients. Hence, how IECs, intestinal bacteria and epithelial cell expressed complement components interact in the course of IBD still remains to be mostly elucidated to define potential unique patterns contributing to the distinct subtypes of intestinal inflammation observed in CD and UC. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

Soil microbial community successional patterns during forest ecosystem restoration.

PubMed

Banning, Natasha C; Gleeson, Deirdre B; Grigg, Andrew H; Grant, Carl D; Andersen, Gary L; Brodie, Eoin L; Murphy, D V

2011-09-01

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables.

Soil Microbial Community Successional Patterns during Forest Ecosystem Restoration ▿†

PubMed Central

Banning, Natasha C.; Gleeson, Deirdre B.; Grigg, Andrew H.; Grant, Carl D.; Andersen, Gary L.; Brodie, Eoin L.; Murphy, D. V.

2011-01-01

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables. PMID:21724890

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.

Innate and cytokine-driven signals, rather than microbial antigens, dominate in natural killer T cell activation during microbial infection.

PubMed

Brigl, Manfred; Tatituri, Raju V V; Watts, Gerald F M; Bhowruth, Veemal; Leadbetter, Elizabeth A; Barton, Nathaniel; Cohen, Nadia R; Hsu, Fong-Fu; Besra, Gurdyal S; Brenner, Michael B

2011-06-06

Invariant natural killer T cells (iNKT cells) are critical for host defense against a variety of microbial pathogens. However, the central question of how iNKT cells are activated by microbes has not been fully explained. The example of adaptive MHC-restricted T cells, studies using synthetic pharmacological α-galactosylceramides, and the recent discovery of microbial iNKT cell ligands have all suggested that recognition of foreign lipid antigens is the main driver for iNKT cell activation during infection. However, when we compared the role of microbial antigens versus innate cytokine-driven mechanisms, we found that iNKT cell interferon-γ production after in vitro stimulation or infection with diverse bacteria overwhelmingly depended on toll-like receptor-driven IL-12. Importantly, activation of iNKT cells in vivo during infection with Sphingomonas yanoikuyae or Streptococcus pneumoniae, pathogens which are known to express iNKT cell antigens and which require iNKT cells for effective protection, also predominantly depended on IL-12. Constitutive expression of high levels of IL-12 receptor by iNKT cells enabled instant IL-12-induced STAT4 activation, demonstrating that among T cells, iNKT cells are uniquely equipped for immediate, cytokine-driven activation. These findings reveal that innate and cytokine-driven signals, rather than cognate microbial antigen, dominate in iNKT cell activation during microbial infections.

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.

Q&A: Friends (but sometimes foes) within: the complex evolutionary ecology of symbioses between host and microbes.

PubMed

Gerardo, Nicole; Hurst, Gregory

2017-12-27

Over the past decade, there has been a pronounced shift in the study of host-microbe associations, with recognition that many of these associations are beneficial, and often critical, for a diverse array of hosts. There may also be pronounced benefits for the microbes, though this is less well empirically understood. Significant progress has been made in understanding how ecology and evolution shape simple associations between hosts and one or a few microbial species, and this work can serve as a foundation to study the ecology and evolution of host associations with their often complex microbial communities (microbiomes).

Innate immunity in rice

PubMed Central

Chen, Xuewei; Ronald, Pamela C.

2011-01-01

Advances in studies of rice innate immunity have led to the identification and characterization of host sensors encoding receptor kinases that perceive conserved microbial signatures. The non-RD domain, a newly recognized hallmark of these receptor kinases is highly expanded in rice (Oryza sativa) compared with Arabidopsis (Arabidopsis thaliana). Researchers have also identified a diverse array of microbial effectors from bacterial and fungal pathogens that triggers immune responses upon perception. These include both, effectors that indirectly target host Nucleotide binding site/Leucine rice repeat (NBS-LRR) proteins and transcription activator-like (TAL) effectors that directly bind promoters of host genes. Here we review the recognition and signaling events that govern rice innate immunity. PMID:21602092

Functional gene diversity of soil microbial communities from five oil-contaminated fields in China.

PubMed

Liang, Yuting; Van Nostrand, Joy D; Deng, Ye; He, Zhili; Wu, Liyou; Zhang, Xu; Li, Guanghe; Zhou, Jizhong

2011-03-01

To compare microbial functional diversity in different oil-contaminated fields and to know the effects of oil contaminant and environmental factors, soil samples were taken from typical oil-contaminated fields located in five geographic regions of China. GeoChip, a high-throughput functional gene array, was used to evaluate the microbial functional genes involved in contaminant degradation and in other major biogeochemical/metabolic processes. Our results indicated that the overall microbial community structures were distinct in each oil-contaminated field, and samples were clustered by geographic locations. The organic contaminant degradation genes were most abundant in all samples and presented a similar pattern under oil contaminant stress among the five fields. In addition, alkane and aromatic hydrocarbon degradation genes such as monooxygenase and dioxygenase were detected in high abundance in the oil-contaminated fields. Canonical correspondence analysis indicated that the microbial functional patterns were highly correlated to the local environmental variables, such as oil contaminant concentration, nitrogen and phosphorus contents, salt and pH. Finally, a total of 59% of microbial community variation from GeoChip data can be explained by oil contamination, geographic location and soil geochemical parameters. This study provided insights into the in situ microbial functional structures in oil-contaminated fields and discerned the linkages between microbial communities and environmental variables, which is important to the application of bioremediation in oil-contaminated sites.

Functional gene diversity of soil microbial communities from five oil-contaminated fields in China

PubMed Central

Liang, Yuting; Van Nostrand, Joy D; Deng, Ye; He, Zhili; Wu, Liyou; Zhang, Xu; Li, Guanghe; Zhou, Jizhong

2011-01-01

To compare microbial functional diversity in different oil-contaminated fields and to know the effects of oil contaminant and environmental factors, soil samples were taken from typical oil-contaminated fields located in five geographic regions of China. GeoChip, a high-throughput functional gene array, was used to evaluate the microbial functional genes involved in contaminant degradation and in other major biogeochemical/metabolic processes. Our results indicated that the overall microbial community structures were distinct in each oil-contaminated field, and samples were clustered by geographic locations. The organic contaminant degradation genes were most abundant in all samples and presented a similar pattern under oil contaminant stress among the five fields. In addition, alkane and aromatic hydrocarbon degradation genes such as monooxygenase and dioxygenase were detected in high abundance in the oil-contaminated fields. Canonical correspondence analysis indicated that the microbial functional patterns were highly correlated to the local environmental variables, such as oil contaminant concentration, nitrogen and phosphorus contents, salt and pH. Finally, a total of 59% of microbial community variation from GeoChip data can be explained by oil contamination, geographic location and soil geochemical parameters. This study provided insights into the in situ microbial functional structures in oil-contaminated fields and discerned the linkages between microbial communities and environmental variables, which is important to the application of bioremediation in oil-contaminated sites. PMID:20861922

Patterns and drivers of soil microbial communities in temperate grasslands on the Mongolian plateau

NASA Astrophysics Data System (ADS)

Yang, Y.; Hu, H.; Hao, B.; Liu, Y.; Chen, Y.; Ma, W.

2016-12-01

Soil microorganisms play key roles in regulating many important ecosystem processes. However, our understanding of the patterns and drivers of soil microbial communities at the regional scale remains limited. In this study, on the basis of phospholipid fatty acid (PLFA) analysis, we investigated large-scale patterns and drivers of soil microbial communities using data from 78 sites between two depths (0-10 cm and 10-20 cm) within three major grassland types (desert steppe, typical steppe, and meadow steppe) on the Mongolian Plateau. Our findings demonstrated that, at the regional scale, the total soil microbial biomass, fungal biomass, bacterial biomass, and actinomycete biomass in Inner Mongolian temperate grasslands were all positively associated with mean annual precipitation (MAP), soil organic carbon (SOC), soil total nitrogen (TN), C:N ratio, plant aboveground biomass (AGB), and plant species richness (SR), but negatively correlated with mean annual temperature (MAT), soil bulk density (BD), and soil pH in both depths, except actinomycete biomass with MAP and BD in 10-20 cm. A stepwise regression analysis revealed that soil microbial community variations in Inner Mongolian temperate grasslands were mainly explained by C : N ratio in 0-10 cm, but by SR (total soil microbial biomass, fungal biomass, and actinomycete biomass) and MAT (bacterial biomass) in 10-20 cm. Our findings strongly indicate that the dominant drivers of spatial variations in soil microbial communities between 0-10 cm and 10-20 cm in the Inner Mongolia grasslands are significantly different, with edaphic factors (e.g., C: N ratio) in 0-10 cm but climatic (e.g, MAT) and/or biotic (e.g, SR) in 10-20 cm.

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

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.

Microbial biomass carbon and enzyme activities of urban soils in Beijing.

PubMed

Wang, Meie; Markert, Bernd; Shen, Wenming; Chen, Weiping; Peng, Chi; Ouyang, Zhiyun

2011-07-01

To promote rational and sustainable use of soil resources and to maintain the urban soil quality, it is essential to assess urban ecosystem health. In this study, the microbiological properties of urban soils in Beijing and their spatial distribution patterns across the city were evaluated based on measurements of microbial biomass carbon and urease and invertase activities of the soils for the purpose of assessing the urban ecosystem health of Beijing. Grid sampling design, normal Kriging technique, and the multiple comparisons among different land use types were used in soil sampling and data treatment. The inherent chemical characteristics of urban soils in Beijing, e.g., soil pH, electronic conductivity, heavy metal contents, total N, P and K contents, and soil organic matter contents were detected. The size and diversity of microbial community and the extent of microbial activity in Beijing urban soils were measured as the microbial biomass carbon content and the ratio of microbial biomass carbon content to total soil organic carbon. The microbial community health measured in terms of microbial biomass carbon, urease, and invertase activities varied with the organic substrate and nutrient contents of the soils and were not adversely affected by the presence of heavy metals at p < 0.01. It was shown that the older and the biologically more stable part of city exhibited higher microbial activity levels than the more recently developed part of the city and the road areas of heavy traffic. It was concluded that the land use patterns in Beijing urban soils influenced the nature and activities of the microbial communities.

Successional and seasonal variations in soil and litter microbial community structure and function during tropical postagricultural forest regeneration: a multiyear study.

PubMed

Smith, A Peyton; Marín-Spiotta, Erika; Balser, Teri

2015-09-01

Soil microorganisms regulate fundamental biochemical processes in plant litter decomposition and soil organic matter (SOM) transformations. Understanding how microbial communities respond to changes in vegetation is critical for improving predictions of how land-cover change affects belowground carbon storage and nutrient availability. We measured intra- and interannual variability in soil and forest litter microbial community composition and activity via phospholipid fatty acid analysis (PLFA) and extracellular enzyme activity across a well-replicated, long-term chronosequence of secondary forests growing on abandoned pastures in the wet subtropical forest life zone of Puerto Rico. Microbial community PLFA structure differed between young secondary forests and older secondary and primary forests, following successional shifts in tree species composition. These successional patterns held across seasons, but the microbial groups driving these patterns differed over time. Microbial community composition from the forest litter differed greatly from those in the soil, but did not show the same successional trends. Extracellular enzyme activity did not differ with forest succession, but varied by season with greater rates of potential activity in the dry seasons. We found few robust significant relationships among microbial community parameters and soil pH, moisture, carbon, and nitrogen concentrations. Observed inter- and intrannual variability in microbial community structure and activity reveal the importance of a multiple, temporal sampling strategy when investigating microbial community dynamics with land-use change. Successional control over microbial composition with forest recovery suggests strong links between above and belowground communities. © 2015 John Wiley & Sons Ltd.

Oestrogen promotes healing in a bacterial LPS model of delayed cutaneous wound repair.

PubMed

Crompton, Rachel; Williams, Helen; Ansell, David; Campbell, Laura; Holden, Kirsty; Cruickshank, Sheena; Hardman, Matthew J

2016-04-01

Wound infection is a major clinical problem, yet understanding of bacterial host interactions in the skin remains limited. Microbe-derived molecules, known as pathogen-associated molecular patterns, are recognised in barrier tissues by pattern-recognition receptors. In particular, the pathogen-associated molecular pattern, lipopolysaccharide (LPS), a component of microbial cell walls and a specific ligand for Toll-like receptor 4, has been widely used to mimic systemic and local infection across a range of tissues. Here we administered LPS derived from Klebsiella pneumoniae, a species of bacteria that is emerging as a wound-associated pathogen, to full-thickness cutaneous wounds in C57/BL6 mice. Early in healing, LPS-treated wounds displayed increased local apoptosis and reduced proliferation. Subsequent healing progression was delayed with reduced re-epithelialisation, increased proliferation, a heightened inflammatory response and perturbed wound matrix deposition. Our group and others have previously demonstrated the beneficial effects of 17β-estradiol treatment across a range of preclinical wound models. Here we asked whether oestrogen would effectively promote healing in our LPS bacterial infection model. Intriguingly, co-treatment with 17β-estradiol was able to promote re-epithelialisation, dampen inflammation and induce collagen deposition in our LPS-delayed healing model. Collectively, these studies validate K. pneumoniae-derived LPS treatment as a simple yet effective model of bacterial wound infection, while providing the first indication that oestrogen could promote cutaneous healing in the presence of infection, further strengthening the case for its therapeutic use.

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…

The macrophage soluble receptor AIM/Api6/CD5L displays a broad pathogen recognition spectrum and is involved in early response to microbial aggression

PubMed Central

Martinez, Vanesa G.; Escoda-Ferran, Cristina; Tadeu Simões, Inês; Arai, Satoko; Orta Mascaró, Marc; Carreras, Esther; Martínez-Florensa, Mario; Yelamos, José; Miyazaki, Toru; Lozano, Francisco

2014-01-01

Apoptosis inhibitor of macrophages (AIMs), a homologue of human Spα, is a mouse soluble member of the scavenger receptor cysteine-rich superfamily (SRCR-SF). This family integrates a group of proteins expressed by innate and adaptive immune cells for which no unifying function has yet been described. Pleiotropic functions have been ascribed to AIM, from viability support in lymphocytes during thymic selection to lipid metabolism and anti-inflammatory effects in autoimmune pathologies. In the present report, the pathogen binding properties of AIM have been explored. By using a recombinant form of AIM (rAIM) expressed in mammalian cells, it is shown that this protein is able to bind and aggregate Gram-positive and Gram-negative bacteria, as well as pathogenic and saprophytic fungal species. Importantly, endogenous AIM from mouse serum also binds to microorganisms and secretion of AIM was rapidly induced in mouse spleen macrophages following exposure to conserved microbial cell wall components. Cytokine release induced by well-known bacterial and fungal Toll-like receptor (TLR) ligands on mouse splenocytes was also inhibited in the presence of rAIM. Furthermore, mouse models of pathogen-associated molecular patterns (PAMPs)-induced septic shock of bacterial and fungal origin showed that serum AIM levels changed in a time-dependent manner. Altogether, these data suggest that AIM plays a general homeostatic role by supporting innate humoral defense during pathogen aggression. PMID:24583716

Dynamic metabolic response of mice to acute mequindox exposure.

PubMed

Zhao, Xiu-Ju; Huang, Chongyang; Lei, Hehua; Nie, Xiu; Tang, Huiru; Wang, Yulan

2011-11-04

Mequindox is used as a veterinary antibiotic drug. As part of systematic investigations into mequindox as a veterinary medicine and its subsequent applications in food safety, we conducted the investigation to assess the metabolic response of mice to mequindox using metabonomics, which combines NMR metabolic profiles of biofluids or tissues and pattern recognition data analysis. In this study, we delivered a single dose of mequindox to mice with dosage levels of 15, 75, and 350 mg/kg body weight and collected urine samples over a 7 day period, as well as plasma and liver tissues at 7 days postdose. Principal components analysis (PCA) and orthogonal projection to latent structure discriminant analysis (O-PLS-DA) were performed on (1)H NMR spectra of biofluids and liver, showing that low dose levels of mequindox exposure had no adverse effects, consistent with histological observations of the liver. High and moderate levels of mequindox exposure caused suppression of glycolysis and stimulation of fatty acid oxidation accompanied with increased levels of oxidative stress. Our metabonomic analyses also showed disruption of amino acid metabolism, consistent with liver damage observed from histopathological examinations. Furthermore, mequindox perturbed gut microbial activity manifested in the altered excretion of urinary trimethylamine (TMA), trimethylamine-N-oxide (TMAO), hippurate, phenylacetylglycine (PAG), and phenylacetate. The putative gut microbial function may also contribute to the assembly and secretion of very-low-density lipoproteins from the liver to the plasma. Our work provides important insights on the metabolic responses of mequindox.

Iron microbial mats in modern and phanerozoic environments

NASA Astrophysics Data System (ADS)

Baele, Jean-Marc; Bouvain, Frédéric; De Jong, Jeroen; Matielli, Nadine; Papier, Séverine; Préat, Alain

2008-08-01

The recognition of iron microbial mats in terrestrial environments is of great relevance for the search for extraterrestrial life, especially on mars where significant iron minerals were identified in the subsurface. Most researches focused on very ancient microbial mats (e.g. BIFs) since they formed on Earth at a time where similar conditions are supposed to have prevailed on Mars too. However, environmental proxies are often difficult to use for these deposits on Earth which, in addition, may be heavily transformed due to diagenesis or even metamorphism. Here we present modern and phanerozoic iron microbial mats occurrences illustrating the wide variety of environments in which they form, including many marine settings, ponds, creeks, caves, volcanoes, etc. Contrarily to their Precambrian counterparts, Modern and Phanerozoic deposits are usually less affected by diagenesis and the environmental conditions likely to be better constrained. Therefore, their investigation may help for the search for morphological and geochemical biosignatures (e.g. iron isotopes) in ancient iron microbial occurrences on Earth but also on other Planets. In particular, many of the case studies presented here show that microstromatolithe-like morphologies may be valuable targets for screening potential biosignatures in various rock types.

Habitat generalists and specialists in microbial communities across a terrestrial-freshwater gradient

NASA Astrophysics Data System (ADS)

Monard, C.; Gantner, S.; Bertilsson, S.; Hallin, S.; Stenlid, J.

2016-11-01

Observations of distributions of microorganisms and their differences in community composition across habitats provide evidence of biogeographical patterns. However, little is known about the processes controlling transfers across habitat gradients. By analysing the overall microbial community composition (bacteria, fungi, archaea) across a terrestrial-freshwater gradient, the aim of this study was to understand the spatial distribution patterns of populations and identify taxa capable of crossing biome borders. Barcoded 454 pyrosequencing of taxonomic gene markers was used to describe the microbial communities in adjacent soil, freshwater and sediment samples and study the role of biotic and spatial factors in shaping their composition. Few habitat generalists but a high number of specialists were detected indicating that microbial community composition was mainly regulated by species sorting and niche partitioning. Biotic interactions within microbial groups based on an association network underlined the importance of Actinobacteria, Sordariomycetes, Agaricomycetes and Nitrososphaerales in connecting among biomes. Even if dispersion seemed limited, the shore of the lake represented a transition area, allowing populations to cross the biome boundaries. In finding few broadly distributed populations, our study points to biome specialization within microbial communities with limited potential for dispersal and colonization of new habitats along the terrestrial-freshwater continuum.

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.

[Toll-like receptor in lung response to pathogens].

PubMed

Rivas-Santiago, Bruno; Juárez, Esmeralda

2007-01-01

Innate immunity plays a central role in antimicrobial defense. Advances in the understanding of pathogen recognition systems of innate cells have yielded the identification of Toll like receptors (TLR) as key elements of the lung defense mechanisms which is heavily exposed to a variety of stimuli. TLR recognition of several microbial compounds induces proinflammatory cytokines production whose contribution to the host may be either protective or detrimental. Human immune response diversity may explain the differences observed between patients facing bacterial, viral and fungal lung infections. New strategies designs that modify innate immune response may be useful to limit detrimental consequences of inflammatory processes in the lung.

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.

Microbial Invasion vs. Tick Immune Regulation.

PubMed

Sonenshine, Daniel E; Macaluso, Kevin R

2017-01-01

Ticks transmit a greater variety of pathogenic agents that cause disease in humans and animals than any other haematophagous arthropod, including Lyme disease, Rocky Mountain spotted fever, human granulocytic anaplasmosis, babesiosis, tick-borne encephalitis, Crimean Congo haemorhagic fever, and many others (Gulia-Nuss et al., 2016). Although diverse explanations have been proposed to explain their remarkable vectorial capacity, among the most important are their blood feeding habit, their long term off-host survival, the diverse array of bioactive molecules that disrupt the host's natural hemostatic mechanisms, facilitate blood flow, pain inhibitors, and minimize inflammation to prevent immune rejection (Hajdušek et al., 2013). Moreover, the tick's unique intracellular digestive processes allow the midgut to provide a relatively permissive microenvironment for survival of invading microbes. Although tick-host-pathogen interactions have evolved over more than 300 million years (Barker and Murrell, 2008), few microbes have been able to overcome the tick's innate immune system, comprising both humoral and cellular processes that reject them. Similar to most eukaryotes, the signaling pathways that regulate the innate immune response, i.e., the Toll, IMD (Immunodeficiency) and JAK-STAT (Janus Kinase/ Signal Transducers and Activators of Transcription) also occur in ticks (Gulia-Nuss et al., 2016). Recognition of pathogen-associated molecular patterns (PAMPs) on the microbial surface triggers one or the other of these pathways. Consequently, ticks are able to mount an impressive array of humoral and cellular responses to microbial challenge, including anti-microbial peptides (AMPs), e.g., defensins, lysozymes, microplusins, etc., that directly kill, entrap or inhibit the invaders. Equally important are cellular processes, primarily phagocytosis, that capture, ingest, or encapsulate invading microbes, regulated by a primordial system of thioester-containing proteins, fibrinogen-related lectins and convertase factors (Hajdušek et al., 2013). Ticks also express reactive oxygen species (ROS) as well as glutathione-S-transferase, superoxide dismutase, heat shock proteins and even protease inhibitors that kill or inhibit microbes. Nevertheless, many tick-borne microorganisms are able to evade the tick's innate immune system and survive within the tick's body. The examples that follow describe some of the many different strategies that have evolved to enable ticks to transmit the agents of human and/or animal disease.

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.

Fabrication of three dimensional patterns of wide dimensional range using microbes and their applications

PubMed Central

Mehta, Sunita; Murugeson, Saravanan; Prakash, Balaji; Deepak

2015-01-01

Inspired by the wound healing property of certain trees, we report a novel microbes based additive process for producing three dimensional patterns, which has a potential of engineering applications in a variety of fields. Imposing a two dimensional pattern of microbes on a gel media and allowing them to grow in the third dimension is known from its use in biological studies. Instead, we have introduced an intermediate porous substrate between the gel media and the microbial growth, which enables three dimensional patterns in specific forms that can be lifted off and used in engineering applications. In order to demonstrate the applicability of this idea in a diverse set of areas, two applications are selected. In one, using this method of microbial growth, we have fabricated microlenses for enhanced light extraction in organic light emitting diodes, where densely packed microlenses of the diameters of hundreds of microns lead to luminance increase by a factor of 1.24X. In another entirely different type of application, braille text patterns are prepared on a normal office paper where the grown microbial colonies serve as braille tactile dots. Braille dot patterns thus prepared meet the standard specifications (size and spacing) for braille books. PMID:26486847

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

Global investigation of composition and interaction networks in gut microbiomes of individuals belonging to diverse geographies and age-groups.

PubMed

Yadav, Deepak; Ghosh, Tarini Shankar; Mande, Sharmila S

2016-01-01

Factors like ethnicity, diet and age of an individual have been hypothesized to play a role in determining the makeup of gut microbiome. In order to investigate the gut microbiome structure as well as the inter-microbial associations present therein, we have performed a comprehensive global comparative profiling of the structure (composition, relative heterogeneity and diversity) and the inter-microbial networks in the gut microbiomes of 399 individuals of eight different nationalities. The study identified certain geography-specific trends with respect to composition, intra-group heterogeneity and diversity of the gut microbiomes. Interestingly, the gut microbial association/mutual-exlusion networks were observed to exhibit several cross-geography trends. It was seen that though the composition of gut microbiomes of the American and European individuals were similar, there were distinct patterns in their microbial interaction networks. Amongst European gut-microbiomes, the co-occurrence network obtained for the Danish population was observed to be most dense. Distinct patterns were also observed within Chinese, Japanese and Indian datasets. While performing an age-wise comparison, it was observed that the microbial interactions increased with the age of individuals. Furthermore, certain bacterial groups were identified to be present only in the older age groups. The trends observed in gut microbial networks could be due to the inherent differences in the diet of individuals belonging to different nationalities. For example, the higher number of microbial associations in the Danish population as compared to the Spanish population, may be attributed to the evenly distributed diet of the later. This is in line with previously reported findings which indicate an increase in functional interdependency of microbes in individuals with higher nutritional status. To summarise, the present study identifies geography and age specific patterns in the composition as well as microbial interactions in gut microbiomes.

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 microbial perspective of human developmental biology.

PubMed

Charbonneau, Mark R; Blanton, Laura V; DiGiulio, Daniel B; Relman, David A; Lebrilla, Carlito B; Mills, David A; Gordon, Jeffrey I

2016-07-07

When most people think of human development, they tend to consider only human cells and organs. Yet there is another facet that involves human-associated microbial communities. A microbial perspective of human development provides opportunities to refine our definitions of healthy prenatal and postnatal growth and to develop innovative strategies for disease prevention and treatment. Given the dramatic changes in lifestyles and disease patterns that are occurring with globalization, we issue a call for the establishment of 'human microbial observatories' designed to examine microbial community development in birth cohorts representing populations with diverse anthropological characteristics, including those undergoing rapid change.

Human developmental biology viewed from a microbial perspective

PubMed Central

Charbonneau, Mark R.; Blanton, Laura V.; DiGiulio, Daniel B.; Relman, David A.; Lebrilla, Carlito B.; Mills, David A.; Gordon, Jeffrey I.

2017-01-01

Preface Most people think of human development only in terms of ‘human’ cells and organs. Here, we discuss another facet involving human-associated microbial communities. A microbial perspective of human development provides opportunities to refine our definitions of healthy pre- and postnatal growth and to develop new strategies for disease prevention and treatment. Considering the dramatic changes in lifestyles and disease patterns that are occurring with globalization, we issue a call for human microbial observatory programs designed to examine microbial community development in birth cohorts representing populations with diverse anthropologic characteristics, including those undergoing rapid change. PMID:27383979

Microbial Biogeography on the Legacies of Historical Events in the Arctic Subsurface Sediments

NASA Astrophysics Data System (ADS)

Han, Dukki; Nam, Seung-Il; Hur, Hor-Gil

2017-04-01

The Arctic marine environment consists of various microbial habitats. The niche preference of microbial assemblages in the Arctic Ocean has been surveyed with the modern environmental change by oceanographic traits such as sea-ice dynamics, current circulation, and sedimentation. The North Pacific inflow from the shallow and narrow Bering Strait is highly susceptible to sea-level fluctuations, and thus the water mass exchange mediated by the history of sea-ice between the North Pacific and the Chukchi Sea in the Arctic Ocean. Over geological timescale, the climate change may provide putative evidences for ecological niche for the Arctic microbial assemblages as well as geological records in response to the paleoclimate change. In the present study, the multidisciplinary approach, based on microbiology, geology, and geochemistry, was applied to survey the microbial assemblages in the Arctic subsurface sediments and help further integrate the microbial biogeography and biogeochemical patterns in the Arctic subsurface biosphere. Our results describe microbial assemblages with high-resolution paleoceanographic records in the Chukchi Sea sediment core (ARA02B/01A-GC; 5.4 mbsf) to show the processes that drive microbial biogeographic patterns in the Arctic subsurface sediments. We found microbial habitat preferences closely linked to Holocene paleoclimate records as well as geological, geochemical, and microbiological evidence for the inference of the sulphate-methane transition zone (SMTZ) in the Chukchi Sea. Especially, the vertically distributed predominant populations of Gammaproteobacteria and Marine Group II Euryarchaeota in the ARA02B/01A-GC consistent with the patterns of the known global SMTZs and Holocene sedimentary records, suggesting that in-depth microbiological profiles integrated with geological records may be indirectly useful for reconstructing Arctic paleoclimate changes. In the earliest phase of Mid Holocene in the ARA02B/01A-GC with concentrated crenarchaeol (a unique biomarker for Marine Group I Thaumarchaea), the most abundant archaeal population was Marine Group II Euryarchaeota rather than Marine Group I Thaumarchaea, suggesting that the interpretation of archaeal tetraether lipids in subsurface sediments needs careful consideration for paleoceanography. In conclusion, our findings have important implications for the availability of microbial biogeography in the sedimentary record. The present study offers a deeper understanding of the legacies of historical events during the Holocene and implies that the survey of microbial biogeography may be an appropriate tool to monitor potential effects from the climate change in the Arctic Ocean.

Policing the intestinal epithelial barrier: Innate immune functions of intraepithelial lymphocytes.

PubMed

Hu, Madeleine D; Jia, Luo; Edelblum, Karen L

2018-03-01

This review will explore the contribution of IELs to mucosal innate immunity and highlight the similarities in IEL functional responses to bacteria, viruses and protozoan parasite invasion. IELs rapidly respond to microbial invasion by activating host defense responses, including the production of mucus and antimicrobial peptides to prevent microbes from reaching the epithelial surface. During active infection, IELs promote epithelial cytolysis, cytokine and chemokine production to limit pathogen invasion, replication and dissemination. Commensal-induced priming of IEL effector function or continuous surveillance of the epithelium may be important contributing factors to the rapidity of response. Impaired microbial recognition, dysregulated innate immune signaling or microbial dysbiosis may limit the protective function of IELs and increase susceptibility to disease. Further understanding of the mechanisms regulating IEL surveillance and sentinel function may provide insight into the development of more effective targeted therapies designed to reinforce the mucosal barrier.

What can microbial genetics teach sociobiology?

PubMed Central

Foster, Kevin R.; Parkinson, Katie; Thompson, Christopher R.L.

2009-01-01

Progress in our understanding of sociobiology has occurred with little knowledge of the genetic mechanisms that underlie social traits. However, several recent studies have described microbial genes that affect social traits, thereby bringing genetics to sociobiology. A key finding is that simple genetic changes can have marked social consequences, and mutations that affect cheating and recognition behaviors have been discovered. The study of these mutants confirms a central theoretical prediction of social evolution: that genetic relatedness promotes cooperation. Microbial genetics also provides an important new perspective: that the genome-to-phenome mapping of social organisms might be organized to constrain the evolution of social cheaters. This constraint can occur both through pleiotropic genes that link cheating to a personal cost and through the existence of phoenix genes, which rescue cooperative systems from selfish and destructive strategies. These new insights show the power of studying microorganisms to improve our understanding of the evolution of cooperation. PMID:17207887

Probiotics and Chronic Gastrointestinal Disease

NASA Astrophysics Data System (ADS)

Guarner, Francisco

Human beings are associated in a symbiotic relationship with a huge population of microorganisms. During millennia, a considerable number of microbes have evolved and adapted to live and grow in the human intestine. The intestinal habitat of an individual contains billions of microorganisms including bacteria, protozoa, archaea, fungi, and viruses (Guarner and Malagelada, 2003; Ley et al., 2006), and the number of microbial cells within the gut lumen appears to be ten times larger than the number of eukaryotic cells of the human body. Some of these bacteria are potential pathogens and can be a source of infection and sepsis under some circumstances, for instance when the integrity of the bowel barrier is physically or functionally breached. However, growing evidence suggests that important health benefits to the human host derive from the constant interaction with its microbial guests. Recognition of these benefits in recent years is drawing particular attention to the functional implications of the gut microbial communities in host physiology.

High Carbon Use Efficiency is Not Explained by Production of Storage Compounds

NASA Astrophysics Data System (ADS)

Dijkstra, Paul; van Groenigen, Kees-Jan

2015-04-01

The efficiency with which microbes use substrate to make new microbial biomass (Carbon Use Efficiency or CUE; mol C / mol C) is an important variable in soil and ecosystem C cycling models. Estimates of CUE in soil microbial communities vary widely. It has been hypothesized that high values of CUE are associated with production of storage compounds following a sudden increases in substrate availability during CUE measurements. In that case, these high CUE values would not be representative for balanced microbial growth (i.e. the production of all compounds needed to make new microbial cells). To test this hypothesis, we added position-specific 13C-labeled glucose isotopomers in parallel incubations of a ponderosa pine and piñon-juniper soil. We compared the measured pattern of CO2 release for the six glucose C atoms with patterns of CO2 production expected for balanced growth with a low, medium, or high CUE, and with CO2 production patterns associated with production of storage compounds (glycogen, lipids, or polyhydroxybutyrate). The measured position-specific CO2 production did not match that for production of glycogen, lipids, or polyhydroxybutyrate, but agreed closely with that expected for balanced growth at high CUE and high pentose phosphate pathway activity. We conclude that soil microbial communities utilize glucose substrate for biomass growth with high CUE, and that addition of small amounts of 13C-labeled glucose tracers do not affect CUE or induce storage compounds production. We submit that the measurement of position-specific CO2 production offers a quick and easy way to test biochemically explicit hypotheses concerning microbial growth metabolism.

Single-cell measurement of archaeal and bacterial carbon assimilation in dark Pacific Ocean waters

NASA Astrophysics Data System (ADS)

Dekas, A. E.; Mayali, X.; Parada, A. E.; Fuhrman, J. A.; Weber, P. K.; Pett-Ridge, J.

2016-02-01

Microbial activity in the dark ocean plays a critical role in nutrient and elemental cycling. Here, we investigated the activity of archaea and bacteria on the single-cell level during dark incubations of Pacific Ocean water, and specifically their capacity for chemoautotrophy. Samples were collected 19 km off the coast of Los Angeles, at a depth of 150 m, and off the coast of San Francisco, at the surface. Incubations were amended with isotopically-labeled organic or inorganic carbon (13C-bicarbonate, 15N-amino acids or dual-labeled 13C-15N-amino acids), and uptake was detected using nanoscale secondary ion mass spectrometry (NanoSIMS). We analyzed 4,968 individual cells using an automated NanoSIMS analysis with particle-recognition software. After 7 days, 95% and 89% of cells (deep and shallow, respectively) demonstrated anabolic activity, i.e., incorporation of at least one isotopically-labeled substrate. Chemoautotrophy was detected at both sites, with 36% and 9% of cells (deep and shallow, respectively) assimilating 13C-bicarbonate in the dark. Fluorescence in situ hybridization coupled to NanoSIMS analysis was performed to link 16S rRNA phylogeny to patterns of C-assimilation. Thaumarchaea were found to dominate chemoautotrophy at both sites, with 13C-bicarbonate assimilation in nearly all cells hybridized with the Cren537 probe, but none hybridized with a general bacterial probe (Eub338). Conversely, widespread assimilation of both 15N and 13C from 15N-13C-amino acids was observed in the bacterial assemblage, but not in the Thaumarchaea. Interestingly, Thaumarchaeal cells were enriched in 15N after incubation with 15N-13C-amino acids, but not 13C, suggesting selective N assimilation from amino acids or substrate recycling. Together, our results demonstrate the value of single-cell measurements in characterizing patterns of C metabolism in mixed microbial community, and underscore the importance of Thaumarchaea in marine chemoautotrophy.

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.

Gut microbiota and cardiometabolic outcomes: influence of dietary patterns and their associated components.

PubMed

Wong, Julia M W

2014-07-01

Many dietary patterns have been associated with cardiometabolic risk reduction. A commonality between these dietary patterns is the emphasis on plant-based foods. Studies in individuals who consume vegetarian and vegan diets have shown a reduced risk of cardiovascular events and incidence of diabetes. Plant-based dietary patterns may promote a more favorable gut microbial profile. Such diets are high in dietary fiber and fermentable substrate (ie, nondigestible or undigested carbohydrates), which are sources of metabolic fuel for gut microbial fermentation and, in turn, result in end products that may be used by the host (eg, short-chain fatty acids). These end products may have direct or indirect effects on modulating the health of their host. Modulation of the gut microbiota is an area of growing interest, and it has been suggested to have the potential to reduce risk factors associated with chronic diseases. Examples of dietary components that alter the gut microbial composition include prebiotics and resistant starches. Emerging evidence also suggests a potential link between interindividual differences in the gut microbiota and variations in physiology or predisposition to certain chronic disease risk factors. Alterations in the gut microbiota may also stimulate certain populations and may assist in biotransformation of bioactive components found in plant foods. Strategies to modify microbial communities may therefore provide a novel approach in the treatment and management of chronic diseases. © 2014 American Society for Nutrition.

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 a microbial high-throughput screening instrument based on elastic light scatter patterns

NASA Astrophysics Data System (ADS)

Bae, Euiwon; Patsekin, Valery; Rajwa, Bartek; Bhunia, Arun K.; Holdman, Cheryl; Davisson, V. Jo; Hirleman, E. Daniel; Robinson, J. Paul

2012-04-01

A microbial high-throughput screening (HTS) system was developed that enabled high-speed combinatorial studies directly on bacterial colonies. The system consists of a forward scatterometer for elastic light scatter (ELS) detection, a plate transporter for sample handling, and a robotic incubator for automatic incubation. To minimize the ELS pattern-capturing time, a new calibration plate and correction algorithms were both designed, which dramatically reduced correction steps during acquisition of the circularly symmetric ELS patterns. Integration of three different control software programs was implemented, and the performance of the system was demonstrated with single-species detection for library generation and with time-resolved measurement for understanding ELS colony growth correlation, using Escherichia coli and Listeria. An in-house colony-tracking module enabled researchers to easily understand the time-dependent variation of the ELS from identical colony, which enabled further analysis in other biochemical experiments. The microbial HTS system provided an average scan time of 4.9 s per colony and the capability of automatically collecting more than 4000 ELS patterns within a 7-h time span.

Anoxia stimulates microbially catalyzed metal release from Animas River sediments

DOE PAGES

Saup, Casey M.; Williams, Kenneth H.; Rodríguez-Freire, Lucía; ...

2017-03-06

The Gold King Mine spill in August 2015 released 11 million liters of metal-rich mine waste to the Animas River watershed, an area that has been previously exposed to historical mining activity spanning more than a century. Although adsorption onto fluvial sediments was responsible for rapid immobilization of a significant fraction of the spill-associated metals, patterns of longer-term mobility are poorly constrained. Metals associated with river sediments collected downstream of the Gold King Mine in August 2015 exhibited distinct presence and abundance patterns linked to location and mineralogy. Simulating riverbed burial and development of anoxic conditions, sediment microcosm experiments amendedmore » with Animas River dissolved organic carbon revealed the release of specific metal pools coupled to microbial Fe- and SO 4 2-reduction. Results suggest that future sedimentation and burial of riverbed materials may drive longer-term changes in patterns of metal remobilization linked to anaerobic microbial metabolism, potentially driving decreases in downstream water quality. Such patterns emphasize the need for long-term water monitoring efforts in metal-impacted watersheds.« less

Anoxia stimulates microbially catalyzed metal release from Animas River sediments

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

Saup, Casey M.; Williams, Kenneth H.; Rodríguez-Freire, Lucía

The Gold King Mine spill in August 2015 released 11 million liters of metal-rich mine waste to the Animas River watershed, an area that has been previously exposed to historical mining activity spanning more than a century. Although adsorption onto fluvial sediments was responsible for rapid immobilization of a significant fraction of the spill-associated metals, patterns of longer-term mobility are poorly constrained. Metals associated with river sediments collected downstream of the Gold King Mine in August 2015 exhibited distinct presence and abundance patterns linked to location and mineralogy. Simulating riverbed burial and development of anoxic conditions, sediment microcosm experiments amendedmore » with Animas River dissolved organic carbon revealed the release of specific metal pools coupled to microbial Fe- and SO 4 2-reduction. Results suggest that future sedimentation and burial of riverbed materials may drive longer-term changes in patterns of metal remobilization linked to anaerobic microbial metabolism, potentially driving decreases in downstream water quality. Such patterns emphasize the need for long-term water monitoring efforts in metal-impacted watersheds.« less

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,

Seasonal Changes in Bacterial and Archaeal Gene Expression Patterns across Salinity Gradients in the Columbia River Coastal Margin

PubMed Central

Smith, Maria W.; Herfort, Lydie; Tyrol, Kaitlin; Suciu, Dominic; Campbell, Victoria; Crump, Byron C.; Peterson, Tawnya D.; Zuber, Peter; Baptista, Antonio M.; Simon, Holly M.

2010-01-01

Through their metabolic activities, microbial populations mediate the impact of high gradient regions on ecological function and productivity of the highly dynamic Columbia River coastal margin (CRCM). A 2226-probe oligonucleotide DNA microarray was developed to investigate expression patterns for microbial genes involved in nitrogen and carbon metabolism in the CRCM. Initial experiments with the environmental microarrays were directed toward validation of the platform and yielded high reproducibility in multiple tests. Bioinformatic and experimental validation also indicated that >85% of the microarray probes were specific for their corresponding target genes and for a few homologs within the same microbial family. The validated probe set was used to query gene expression responses by microbial assemblages to environmental variability. Sixty-four samples from the river, estuary, plume, and adjacent ocean were collected in different seasons and analyzed to correlate the measured variability in chemical, physical and biological water parameters to differences in global gene expression profiles. The method produced robust seasonal profiles corresponding to pre-freshet spring (April) and late summer (August). Overall relative gene expression was high in both seasons and was consistent with high microbial abundance measured by total RNA, heterotrophic bacterial production, and chlorophyll a. Both seasonal patterns involved large numbers of genes that were highly expressed relative to background, yet each produced very different gene expression profiles. April patterns revealed high differential gene expression in the coastal margin samples (estuary, plume and adjacent ocean) relative to freshwater, while little differential gene expression was observed along the river-to-ocean transition in August. Microbial gene expression profiles appeared to relate, in part, to seasonal differences in nutrient availability and potential resource competition. Furthermore, our results suggest that highly-active particle-attached microbiota in the Columbia River water column may perform dissimilatory nitrate reduction (both dentrification and DNRA) within anoxic particle microniches. PMID:20967204

Lineage-specific responses of microbial communities to environmental change.

PubMed

Youngblut, Nicholas D; Shade, Ashley; Read, Jordan S; McMahon, Katherine D; Whitaker, Rachel J

2013-01-01

A great challenge facing microbial ecology is how to define ecologically relevant taxonomic units. To address this challenge, we investigated how changing the definition of operational taxonomic units (OTUs) influences the perception of ecological patterns in microbial communities as they respond to a dramatic environmental change. We used pyrosequenced tags of the bacterial V2 16S rRNA region, as well as clone libraries constructed from the cytochrome oxidase C gene ccoN, to provide additional taxonomic resolution for the common freshwater genus Polynucleobacter. At the most highly resolved taxonomic scale, we show that distinct genotypes associated with the abundant Polynucleobacter lineages exhibit divergent spatial patterns and dramatic changes over time, while the also abundant Actinobacteria OTUs are highly coherent. This clearly demonstrates that different bacterial lineages demand different taxonomic definitions to capture ecological patterns. Based on the temporal distribution of highly resolved taxa in the hypolimnion, we demonstrate that change in the population structure of a single genotype can provide additional insight into the mechanisms of community-level responses. These results highlight the importance and feasibility of examining ecological change in microbial communities across taxonomic scales while also providing valuable insight into the ecological characteristics of ecologically coherent groups in this system.

Two-dimensional distribution of microbial activity and flow patterns within naturally fractured chalk.

PubMed

Arnon, Shai; Ronen, Zeev; Adar, Eilon; Yakirevich, Alexander; Nativ, Ronit

2005-10-01

The two-dimensional distribution of flow patterns and their dynamic change due to microbial activity were investigated in naturally fractured chalk cores. Long-term biodegradation experiments were conducted in two cores ( approximately 20 cm diameter, 31 and 44 cm long), intersected by a natural fracture. 2,4,6-tribromophenol (TBP) was used as a model contaminant and as the sole carbon source for aerobic microbial activity. The transmissivity of the fractures was continuously reduced due to biomass accumulation in the fracture concurrent with TBP biodegradation. From multi-tracer experiments conducted prior to and following the microbial activity, it was found that biomass accumulation causes redistribution of the preferential flow channels. Zones of slow flow near the fracture inlet were clogged, thus further diverting the flow through zones of fast flow, which were also partially clogged. Quantitative evaluation of biodegradation and bacterial counts supported the results of the multi-tracer tests, indicating that most of the bacterial activity occurs close to the inlet. The changing flow patterns, which control the nutrient supply, resulted in variations in the concentrations of the chemical constituents (TBP, bromide and oxygen), used as indicators of biodegradation.

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.

Nitrogen controls spatial and temporal variability of substrate-induced respiration within seven years of bare fallow

NASA Astrophysics Data System (ADS)

Meyer, Nele; Bornemann, Ludger; Welp, Gerhard; Amelung, Wulf

2015-04-01

Bare fallow management goes along with lacking supply of new C sources; yet, little is known on the spatio-temporal controls of microbial adaptation processes. Here we hypothesized that microbial activity parameters decline upon bare fallow but that their spatial patterns are increasingly controlled by nutrient status as fallow management proceeds. To test these hypotheses, we investigated spatial and temporal patterns of substrate-induced respiration (SIR) and basal respiration curves in an arable field after 1, 3, and 7 years of bare fallow but with large within-field heterogeneity of physicochemical soil parameters. The analyses comprised the contents of SOC, mineral nitrogen (Nmin), particulate organic matter (POM), texture of the fine earth, and the proportion of rock fragments as well as basal respiration and several SIR fitting parameters (microbial biomass, microbial growth rates, peak respiration rates, cumulative CO2 release) each with and without additions of mineral N and P. We also repeated substrate (i.e. glucose) additions following the first SIR measurement. The results revealed that most respiration parameters like basal respiration, microbial biomass, and growth rates showed no or inconsistent responses to spatial and temporal patterns of basic soil properties like SOC, Nmin or texture. However, bare fallow changed the shape of the SIR curves; it developed two distinct microbial growth peaks at advanced stages of fallow, i.e. a delayed CO2 release. Likewise, the maximum respiration rate during the first growth phase declined during 7 years of fallow by 47% but its spatial distribution was always correlated with Nmin contents (r = 0.43 - 0.79). The nutrient additions suggested that these changes in SIR curves were caused by N deficiency; the first peak increased after N additions while the second growth phase diminished. Intriguingly, a repeated glucose addition had a similar effect on the SIR curves as the glucose+N addition. Thus, N deficiency apparently subsided during SIR. The results suggested that soil microbes acquire nitrogen from refractory SOM pools (i.e. microbial nitrogen mining). Hence, there was no significant decrease in cumulative CO2 evolution with proceeding time of fallow. As soil microorganisms maintained their functionality there was no overall loss in potential microbial activity, irrespective of the spatial patterns of other soil properties.

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.

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

Contrasting Microbial Community Assembly Hypotheses: A Reconciling Tale from the Río Tinto

PubMed Central

Palacios, Carmen; Zettler, Erik; Amils, Ricardo; Amaral-Zettler, Linda

2008-01-01

Background The Río Tinto (RT) is distinguished from other acid mine drainage systems by its natural and ancient origins. Microbial life from all three domains flourishes in this ecosystem, but bacteria dominate metabolic processes that perpetuate environmental extremes. While the patchy geochemistry of the RT likely influences the dynamics of bacterial populations, demonstrating which environmental variables shape microbial diversity and unveiling the mechanisms underlying observed patterns, remain major challenges in microbial ecology whose answers rely upon detailed assessments of community structures coupled with fine-scale measurements of physico-chemical parameters. Methodology/Principal Findings By using high-throughput environmental tag sequencing we achieved saturation of richness estimators for the first time in the RT. We found that environmental factors dictate the distribution of the most abundant taxa in this system, but stochastic niche differentiation processes, such as mutation and dispersal, also contribute to observed diversity patterns. Conclusions/Significance We predict that studies providing clues to the evolutionary and ecological processes underlying microbial distributions will reconcile the ongoing debate between the Baas Becking vs. Hubbell community assembly hypotheses. PMID:19052647

Contrasting microbial community assembly hypotheses: a reconciling tale from the Río Tinto.

PubMed

Palacios, Carmen; Zettler, Erik; Amils, Ricardo; Amaral-Zettler, Linda

2008-01-01

The Río Tinto (RT) is distinguished from other acid mine drainage systems by its natural and ancient origins. Microbial life from all three domains flourishes in this ecosystem, but bacteria dominate metabolic processes that perpetuate environmental extremes. While the patchy geochemistry of the RT likely influences the dynamics of bacterial populations, demonstrating which environmental variables shape microbial diversity and unveiling the mechanisms underlying observed patterns, remain major challenges in microbial ecology whose answers rely upon detailed assessments of community structures coupled with fine-scale measurements of physico-chemical parameters. By using high-throughput environmental tag sequencing we achieved saturation of richness estimators for the first time in the RT. We found that environmental factors dictate the distribution of the most abundant taxa in this system, but stochastic niche differentiation processes, such as mutation and dispersal, also contribute to observed diversity patterns. We predict that studies providing clues to the evolutionary and ecological processes underlying microbial distributions will reconcile the ongoing debate between the Baas Becking vs. Hubbell community assembly hypotheses.

Seasonal Patterns in Microbial Community Composition in Denitrifying Bioreactors Treating Subsurface Agricultural Drainage.

PubMed

Porter, Matthew D; Andrus, J Malia; Bartolerio, Nicholas A; Rodriguez, Luis F; Zhang, Yuanhui; Zilles, Julie L; Kent, Angela D

2015-10-01

Denitrifying bioreactors, consisting of water flow control structures and a woodchip-filled trench, are a promising approach for removing nitrate from agricultural subsurface or tile drainage systems. To better understand the seasonal dynamics and the ecological drivers of the microbial communities responsible for denitrification in these bioreactors, we employed microbial community "fingerprinting" techniques in a time-series examination of three denitrifying bioreactors over 2 years, looking at bacteria, fungi, and the denitrifier functional group responsible for the final step of complete denitrification. Our analysis revealed that microbial community composition responds to depth and seasonal variation in moisture content and inundation of the bioreactor media, as well as temperature. Using a geostatistical analysis approach, we observed recurring temporal patterns in bacterial and denitrifying bacterial community composition in these bioreactors, consistent with annual cycling. The fungal communities were more stable, having longer temporal autocorrelations, and did not show significant annual cycling. These results suggest a recurring seasonal cycle in the denitrifying bioreactor microbial community, likely due to seasonal variation in moisture content.

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.

Direct effects of temperature on forest nitrogen cycling revealed through analysis of long-term watershed records

Treesearch

E.N. Jack Brookshire; Stefan Gerber; Jackson R. Webster; James M. Vose; Wayne T. Swank

2010-01-01

The microbial conversion of organic nitrogen (N) to plant available forms is a critical determinant of plant growth and carbon sequestration in forests worldwide. In temperate zones, microbial activity is coupled to variations in temperature, yet at the ecosystem level, microbial N mineralization seems to play a minor role in determining patterns of N loss. Rather, N...

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

Microbial Communities as Environmental Indicators of Ecological Disturbance in Restored Carbonate Fen-Results of 10 Years of Studies.

PubMed

Mieczan, Tomasz; Tarkowska-Kukuryk, Monika

2017-08-01

Interactions between bacteria and protists are essential to the ecosystem ecology of fens. Until now, however, there has been almost no information on how restoration procedures in carbonate fens affect the functioning of microbial food webs. Changes in vegetation patterns resulting from restoration may take years to be observed, whereas microbial processes display effects even after short-term exposure to changes in environmental conditions caused by restoration. Therefore, microbial processes and patterns can be used as sensitive indicators of changes in environmental conditions. The present study attempts to verify the hypothesis that the species richness and abundance of microbial loop components would differ substantially before and after restoration. The effect of restoration processes on the functioning of the food web was investigated for a 10 years in a carbonate-rich fen, before and after restoration. The restoration procedure (particularly the improvement in hydrological conditions) distinctly modified the taxonomic composition and functioning of microbial food webs. This is reflected in the increased abundance and diversity of testate amoeba, i.e. top predators, within the microbial food web and in the pronounced increase in the abundance of bacteria. This study suggests potential use of microbial loop components as bio-indicators and bio-monitoring tools for hydrological status of fens and concentrations of nutrients. Better understanding of what regulates microbial populations and activity in fens and unravelling of these fundamental mechanisms are particularly critical in order to more accurately predict how fens will respond to global change or anthropogenic disturbances.

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.

Self-identity reprogrammed by a single residue switch in a cell surface receptor of a social bacterium.

PubMed

Cao, Pengbo; Wall, Daniel

2017-04-04

The ability to recognize close kin confers survival benefits on single-celled microbes that live in complex and changing environments. Microbial kinship detection relies on perceptible cues that reflect relatedness between individuals, although the mechanisms underlying recognition in natural populations remain poorly understood. In myxobacteria, cells identify related individuals through a polymorphic cell surface receptor, TraA. Recognition of compatible receptors leads to outer membrane exchange among clonemates and fitness consequences. Here, we investigated how a single receptor creates a diversity in recognition across myxobacterial populations. We first show that TraA requires its partner protein TraB to function in cell-cell adhesion. Recognition is shown to be traA allele-specific, where polymorphisms within TraA dictate binding selectivity. We reveal the malleability of TraA recognition, and seemingly minor changes to its variable region reprogram recognition outcomes. Strikingly, we identify a single residue (A/P205) as a molecular switch for TraA recognition. Substitutions at this position change the specificity of a diverse panel of environmental TraA receptors. In addition, we engineered a receptor with unique specificity by simply creating an A205P substitution, suggesting that modest changes in TraA can lead to diversification of new recognition groups in nature. We hypothesize that the malleable property of TraA has allowed it to evolve and create social barriers between myxobacterial populations and in turn avoid adverse interactions with relatives.

Similar soil microbial community structure across different environments after long-term succession: evidence from volcanoes of different ages.

PubMed

Xu, Shangqi; Zhang, Jianfeng; Luo, Shasha; Zhou, Xue; Shi, Shaohua; Tian, Chunjie

2018-06-08

Soil microbes play critical roles in global biogeochemical cycles, but their succession patterns across long temporal scales have rarely been studied. In this study, soil samples were collected from three volcanoes in Wudalianchi, northeastern China: Laoheishan (LH, approximately 240 years old), Dongjiaodebushan (DJ, 0.45-0.6 million years old), and Nangelaqiushan (NG, 0.8-1.3 million years old). For each volcano, both southern (S) and northern (N) slope aspects were sampled. Soil microbial communities were analyzed using phospholipid fatty acid analysis (PLFA). The results showed that soil properties and microbial biomass changed perceptibly among different volcanoes and different slope aspects. Almost all of the detected soil nutrient contents of LH were lowest, and total microbial biomass of LH was 40 and 36% lower than those of NG and DJ, respectively. LH was significantly different from NG and DJ in soil microbial community structure with a higher relative abundance of fungi and a lower relative abundance of actinomycetes and bacteria. However, for the two ancient volcanoes (NG and DJ), soil microbial community structures were highly similar among different ages and different slope aspects. No difference was detected in any of the measured microbial indices, including richness, evenness, Shannon's diversity, Simpson's diversity and the relative abundance of different microbial groups. The results indicated that while soil microbial biomass may change across different soil environments after long-term succession, soil microbial community structure can remain relatively stable. The results further indicated that soil microbes may show different successional patterns in different stages of succession. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Distinct microbial communities in the active and permafrost layers on the Tibetan Plateau.

PubMed

Chen, Yong-Liang; Deng, Ye; Ding, Jin-Zhi; Hu, Hang-Wei; Xu, Tian-Le; Li, Fei; Yang, Gui-Biao; Yang, Yuan-He

2017-12-01

Permafrost represents an important understudied genetic resource. Soil microorganisms play important roles in regulating biogeochemical cycles and maintaining ecosystem function. However, our knowledge of patterns and drivers of permafrost microbial communities is limited over broad geographic scales. Using high-throughput Illumina sequencing, this study compared soil bacterial, archaeal and fungal communities between the active and permafrost layers on the Tibetan Plateau. Our results indicated that microbial alpha diversity was significantly higher in the active layer than in the permafrost layer with the exception of fungal Shannon-Wiener index and Simpson's diversity index, and microbial community structures were significantly different between the two layers. Our results also revealed that environmental factors such as soil fertility (soil organic carbon, dissolved organic carbon and total nitrogen contents) were the primary drivers of the beta diversity of bacterial, archaeal and fungal communities in the active layer. In contrast, environmental variables such as the mean annual precipitation and total phosphorus played dominant roles in driving the microbial beta diversity in the permafrost layer. Spatial distance was important for predicting the bacterial and archaeal beta diversity in both the active and permafrost layers, but not for fungal communities. Collectively, these results demonstrated different driving factors of microbial beta diversity between the active layer and permafrost layer, implying that the drivers of the microbial beta diversity observed in the active layer cannot be used to predict the biogeographic patterns of the microbial beta diversity in the permafrost layer. © 2017 John Wiley & Sons Ltd.

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.

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.

Nucleic acid is a novel ligand for innate, immune pattern recognition collectins surfactant proteins A and D and mannose-binding lectin.

PubMed

Palaniyar, Nades; Nadesalingam, Jeya; Clark, Howard; Shih, Michael J; Dodds, Alister W; Reid, Kenneth B M

2004-07-30

Collectins are a family of innate immune proteins that contain fibrillar collagen-like regions and globular carbohydrate recognition domains (CRDs). The CRDs of these proteins recognize various microbial surface-specific carbohydrate patterns, particularly hexoses. We hypothesized that collectins, such as pulmonary surfactant proteins (SPs) SP-A and SP-D and serum protein mannose-binding lectin, could recognize nucleic acids, pentose-based anionic phosphate polymers. Here we show that collectins bind DNA from a variety of origins, including bacteria, mice, and synthetic oligonucleotides. Pentoses, such as arabinose, ribose, and deoxyribose, inhibit the interaction between SP-D and mannan, one of the well-studied hexose ligands for SP-D, and biologically relevant d-forms of the pentoses are better competitors than the l-forms. In addition, DNA and RNA polymer-related compounds, such as nucleotide diphosphates and triphosphates, also inhibit the carbohydrate binding ability of SP-D, or approximately 60 kDa trimeric recombinant fragments of SP-D that are composed of the alpha-helical coiled-coil neck region and three CRDs (SP-D(n/CRD)) or SP-D(n/CRD) with eight GXY repeats (SPD(GXY)(8)(n/CRD)). Direct binding and competition studies suggest that collectins bind nucleic acid via their CRDs as well as by their collagen-like regions, and that SP-D binds DNA more effectively than do SP-A and mannose-binding lectin at physiological salt conditions. Furthermore, the SP-D(GXY)(8)(n/CRD) fragments co-localize with DNA, and the protein competes the interaction between propidium iodide, a DNA-binding dye, and apoptotic cells. In conclusion, we show that collectins are a new class of proteins that bind free DNA and the DNA present on apoptotic cells by both their globular CRDs and collagen-like regions. Collectins may therefore play an important role in decreasing the inflammation caused by DNA in lungs and other tissues.

TAM receptor-dependent regulation of SOCS3 and MAPKs contributes to proinflammatory cytokine downregulation following chronic NOD2 stimulation of human macrophages.

PubMed

Zheng, Shasha; Hedl, Matija; Abraham, Clara

2015-02-15

Microbial-induced cytokine regulation is critical to intestinal immune homeostasis. Acute stimulation of nucleotide-binding oligomerization domain 2 (NOD2), the Crohn's disease-associated sensor of bacterial peptidoglycan, induces cytokines. However, cytokines are attenuated after chronic NOD2 and pattern recognition receptor stimulation of macrophages; similar attenuation is observed in intestinal macrophages. The role of Tyro3, Axl, and Mer (TAM) receptors in regulating chronic pattern recognition receptor stimulation and NOD2-induced outcomes has not been examined. Moreover, TAM receptors have been relatively less investigated in human macrophages. Whereas TAM receptors did not downregulate acute NOD2-induced cytokines in primary human macrophages, they were essential for downregulating signaling and proinflammatory cytokine secretion after chronic NOD2 and TLR4 stimulation. Axl and Mer were similarly required in mice for cytokine downregulation after chronic NOD2 stimulation in vivo and in intestinal tissues. Consistently, TAM expression was increased in human intestinal myeloid-derived cells. Chronic NOD2 stimulation led to IL-10- and TGF-β-dependent TAM upregulation in human macrophages, which, in turn, upregulated suppressor of cytokine signaling 3 expression. Restoring suppressor of cytokine signaling 3 expression under TAM knockdown conditions restored chronic NOD2-mediated proinflammatory cytokine downregulation. In contrast to the upregulated proinflammatory cytokines, attenuated IL-10 secretion was maintained in TAM-deficient macrophages upon chronic NOD2 stimulation. The level of MAPK activation in TAM-deficient macrophages after chronic NOD2 stimulation was insufficient to upregulate IL-10 secretion; however, full restoration of MAPK activation under these conditions restored c-Fos, c-Jun, musculoaponeurotic fibrosarcoma oncogene homolog K, and PU.1 binding to the IL-10 promoter and IL-10 secretion. Therefore, TAM receptors are critical for downregulating proinflammatory cytokines under the chronic NOD2 stimulation conditions observed in the intestinal environment. Copyright © 2015 by The American Association of Immunologists, Inc.

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.

Mechanistic links between gut microbial community dynamics, microbial functions and metabolic health.

PubMed

Ha, Connie W Y; Lam, Yan Y; Holmes, Andrew J

2014-11-28

Gut microbes comprise a high density, biologically active community that lies at the interface of an animal with its nutritional environment. Consequently their activity profoundly influences many aspects of the physiology and metabolism of the host animal. A range of microbial structural components and metabolites directly interact with host intestinal cells and tissues to influence nutrient uptake and epithelial health. Endocrine, neuronal and lymphoid cells in the gut also integrate signals from these microbial factors to influence systemic responses. Dysregulation of these host-microbe interactions is now recognised as a major risk factor in the development of metabolic dysfunction. This is a two-way process and understanding the factors that tip host-microbiome homeostasis over to dysbiosis requires greater appreciation of the host feedbacks that contribute to regulation of microbial community composition. To date, numerous studies have employed taxonomic profiling approaches to explore the links between microbial composition and host outcomes (especially obesity and its comorbidities), but inconsistent host-microbe associations have been reported. Available data indicates multiple factors have contributed to discrepancies between studies. These include the high level of functional redundancy in host-microbiome interactions combined with individual variation in microbiome composition; differences in study design, diet composition and host system between studies; and inherent limitations to the resolution of rRNA-based community profiling. Accounting for these factors allows for recognition of the common microbial and host factors driving community composition and development of dysbiosis on high fat diets. New therapeutic intervention options are now emerging.

Mechanistic links between gut microbial community dynamics, microbial functions and metabolic health

PubMed Central

Ha, Connie WY; Lam, Yan Y; Holmes, Andrew J

2014-01-01

Gut microbes comprise a high density, biologically active community that lies at the interface of an animal with its nutritional environment. Consequently their activity profoundly influences many aspects of the physiology and metabolism of the host animal. A range of microbial structural components and metabolites directly interact with host intestinal cells and tissues to influence nutrient uptake and epithelial health. Endocrine, neuronal and lymphoid cells in the gut also integrate signals from these microbial factors to influence systemic responses. Dysregulation of these host-microbe interactions is now recognised as a major risk factor in the development of metabolic dysfunction. This is a two-way process and understanding the factors that tip host-microbiome homeostasis over to dysbiosis requires greater appreciation of the host feedbacks that contribute to regulation of microbial community composition. To date, numerous studies have employed taxonomic profiling approaches to explore the links between microbial composition and host outcomes (especially obesity and its comorbidities), but inconsistent host-microbe associations have been reported. Available data indicates multiple factors have contributed to discrepancies between studies. These include the high level of functional redundancy in host-microbiome interactions combined with individual variation in microbiome composition; differences in study design, diet composition and host system between studies; and inherent limitations to the resolution of rRNA-based community profiling. Accounting for these factors allows for recognition of the common microbial and host factors driving community composition and development of dysbiosis on high fat diets. New therapeutic intervention options are now emerging. PMID:25469018

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...

Multitrophic microbial interactions for eco- and agro-biotechnological processes: theory and practice.

PubMed

Saleem, Muhammad; Moe, Luke A

2014-10-01

Multitrophic level microbial loop interactions mediated by protist predators, bacteria, and viruses drive eco- and agro-biotechnological processes such as bioremediation, wastewater treatment, plant growth promotion, and ecosystem functioning. To what extent these microbial interactions are context-dependent in performing biotechnological and ecosystem processes remains largely unstudied. Theory-driven research may advance the understanding of eco-evolutionary processes underlying the patterns and functioning of microbial interactions for successful development of microbe-based biotechnologies for real world applications. This could also be a great avenue to test the validity or limitations of ecology theory for managing diverse microbial resources in an era of altering microbial niches, multitrophic interactions, and microbial diversity loss caused by climate and land use changes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development and application of the microbial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

NASA Astrophysics Data System (ADS)

Hong, E.; Park, Y.; Muirhead, R.; Jeong, J.; Pachepsky, Y. A.

2017-12-01

Pathogenic microorganisms in recreational and irrigation waters remain the subject of concern. Water quality models are used to estimate microbial quality of water sources, to evaluate microbial contamination-related risks, to guide the microbial water quality monitoring, and to evaluate the effect of agricultural management on the microbial water quality. The Agricultural Policy/Environmental eXtender (APEX) is the watershed-scale water quality model that includes highly detailed representation of agricultural management. The APEX currently does not have microbial fate and transport simulation capabilities. The objective of this work was to develop the first APEX microbial fate and transport module that could use the APEX conceptual model of manure removal together with recently introduced conceptualizations of the in-stream microbial fate and transport. The module utilizes manure erosion rates found in the APEX. Bacteria survival in soil-manure mixing layer was simulated with the two-stage survival model. Individual survival patterns were simulated for each manure application date. Simulated in-stream microbial fate and transport processes included the reach-scale passive release of bacteria with resuspended bottom sediment during high flow events, the transport of bacteria from bottom sediment due to the hyporheic exchange during low flow periods, the deposition with settling sediment, and the two-stage survival. Default parameter values were available from recently published databases. The APEX model with the newly developed microbial fate and transport module was applied to simulate seven years of monitoring data for the Toenepi watershed in New Zealand. Based on calibration and testing results, the APEX with the microbe module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water under various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.