Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition.

Science.gov (United States)

Schlundt, Andreas; Tants, Jan-Niklas; Sattler, Michael

2017-04-15

Recent advances in RNA sequencing technologies have greatly expanded our knowledge of the RNA landscape in cells, often with spatiotemporal resolution. These techniques identified many new (often non-coding) RNA molecules. Large-scale studies have also discovered novel RNA binding proteins (RBPs), which exhibit single or multiple RNA binding domains (RBDs) for recognition of specific sequence or structured motifs in RNA. Starting from these large-scale approaches it is crucial to unravel the molecular principles of protein-RNA recognition in ribonucleoprotein complexes (RNPs) to understand the underlying mechanisms of gene regulation. Structural biology and biophysical studies at highest possible resolution are key to elucidate molecular mechanisms of RNA recognition by RBPs and how conformational dynamics, weak interactions and cooperative binding contribute to the formation of specific, context-dependent RNPs. While large compact RNPs can be well studied by X-ray crystallography and cryo-EM, analysis of dynamics and weak interaction necessitates the use of solution methods to capture these properties. Here, we illustrate methods to study the structure and conformational dynamics of protein-RNA complexes in solution starting from the identification of interaction partners in a given RNP. Biophysical and biochemical techniques support the characterization of a protein-RNA complex and identify regions relevant in structural analysis. Nuclear magnetic resonance (NMR) is a powerful tool to gain information on folding, stability and dynamics of RNAs and characterize RNPs in solution. It provides crucial information that is complementary to the static pictures derived from other techniques. NMR can be readily combined with other solution techniques, such as small angle X-ray and/or neutron scattering (SAXS/SANS), electron paramagnetic resonance (EPR), and Förster resonance energy transfer (FRET), which provide information about overall shapes, internal domain

Molecular Recognition: Detection of Colorless Compounds Based on Color Change

Science.gov (United States)

Khalafi, Lida; Kashani, Samira; Karimi, Javad

2016-01-01

A laboratory experiment is described in which students measure the amount of cetirizine in allergy-treatment tablets based on molecular recognition. The basis of recognition is competition of cetirizine with phenolphthalein to form an inclusion complex with ß-cyclodextrin. Phenolphthalein is pinkish under basic condition, whereas it's complex form…

Bio-specific recognition and applications: from molecular to colloidal scales

International Nuclear Information System (INIS)

Baudry, Jean; Bertrand, Emanuel; Lequeux, Nicolas; Bibette, Jerome

2004-01-01

Biomolecules have the well-known ability to build reversible complexes. Indeed, antigens and antibodies or adhesion molecules are able to recognize one another with a strong affinity and a very high specificity. This paper first reviews the various techniques and related results about binding and unbinding, at the scale of a unique ligand/receptor couple. One important biotechnological application arising from these recognition phenomena concerns immuno-diagnosis, which is essentially based on the formation of these specific complexes. We show how the physics of colloids associated with the growing scientific background concerning molecular recognition helps in rationalizing and inventing new diagnostic strategies. Finally the concept of colloidal self-assembling systems as biosensors is presented as directly impacting the most important questions related to molecular recognition and their biotechnological implications. (topical review)

Signatures of molecular recognition from the topography of ...

Indian Academy of Sciences (India)

Administrator

cules through non-covalent bonding such as hydro- gen bonding ... tion exhibit complementarity of certain properties ... of molecular recognition has been given in terms of .... VA and VB correspond to the monomer MESP in the composite.

Confinement of Aggregation-Induced Emission Molecular Rotors in Ultrathin Two-Dimensional Porous Organic Nanosheets for Enhanced Molecular Recognition.

Science.gov (United States)

Dong, Jinqiao; Li, Xu; Zhang, Kang; Di Yuan, Yi; Wang, Yuxiang; Zhai, Linzhi; Liu, Guoliang; Yuan, Daqiang; Jiang, Jianwen; Zhao, Dan

2018-03-21

Despite the rapid development of molecular rotors over the past decade, it still remains a huge challenge to understand their confined behavior in ultrathin two-dimensional (2D) nanomaterials for molecular recognition. Here, we report an all-carbon, 2D π-conjugated aromatic polymer, named NUS-25, containing flexible tetraphenylethylene (TPE) units as aggregation-induced emission (AIE) molecular rotors. NUS-25 bulk powder can be easily exfoliated into micrometer-sized lamellar freestanding nanosheets with a thickness of 2-5 nm. The dynamic behavior of the TPE rotors is partially restricted through noncovalent interactions in the ultrathin 2D nanosheets, which is proved by comparative experimental studies including AIE characteristics, size-selective molecular recognition, and theoretical calculations of rotary energy barrier. Because of the partially restricted TPE rotors, NUS-25 nanosheets are highly fluorescent. This property allows NUS-25 nanosheets to be used as a chemical sensor for the specific detection of acenaphthylene among a series of polycyclic aromatic hydrocarbons (PAHs) via fluorescent quenching mechanism. Further investigations show that NUS-25 nanosheets have much higher sensitivity and selectivity than their stacked bulk powder and other similar polymers containing dynamic TPE rotors. The highly efficient molecular recognition can be attributed to the photoinduced electron transfer (PET) from NUS-25 nanosheets to acenaphthylene, which is investigated by time-resolved photoluminescence measurements (TRPL), excitation and emission spectra, and density functional theory (DFT) calculations. Our findings demonstrate that confinement of AIE molecular rotors in 2D nanomaterials can enhance the molecular recognition. We anticipate that the material design strategy demonstrated in this study will inspire the development of other ultrathin 2D nanomaterials equipped with smart molecular machines for various applications.

Improved localization of cellular membrane receptors using combined fluorescence microscopy and simultaneous topography and recognition imaging

International Nuclear Information System (INIS)

Duman, M; Pfleger, M; Chtcheglova, L A; Neundlinger, I; Bozna, B L; Ebner, A; Schuetz, G J; Hinterdorfer, P; Zhu, R; Mayer, B; Rankl, C; Moertelmaier, M; Kada, G; Kienberger, F; Salio, M; Shepherd, D; Polzella, P; Cerundolo, V; Dieudonne, M

2010-01-01

The combination of fluorescence microscopy and atomic force microscopy has a great potential in single-molecule-detection applications, overcoming many of the limitations coming from each individual technique. Here we present a new platform of combined fluorescence and simultaneous topography and recognition imaging (TREC) for improved localization of cellular receptors. Green fluorescent protein (GFP) labeled human sodium-glucose cotransporter (hSGLT1) expressed Chinese Hamster Ovary (CHO) cells and endothelial cells (MyEnd) from mouse myocardium stained with phalloidin-rhodamine were used as cell systems to study AFM topography and fluorescence microscopy on the same surface area. Topographical AFM images revealed membrane features such as lamellipodia, cytoskeleton fibers, F-actin filaments and small globular structures with heights ranging from 20 to 30 nm. Combined fluorescence and TREC imaging was applied to detect density, distribution and localization of YFP-labeled CD1d molecules on α-galactosylceramide (αGalCer)-loaded THP1 cells. While the expression level, distribution and localization of CD1d molecules on THP1 cells were detected with fluorescence microscopy, the nanoscale distribution of binding sites was investigated with molecular recognition imaging by using a chemically modified AFM tip. Using TREC on the inverted light microscope, the recognition sites of cell receptors were detected in recognition images with domain sizes ranging from ∼ 25 to ∼ 160 nm, with the smaller domains corresponding to a single CD1d molecule.

Improved localization of cellular membrane receptors using combined fluorescence microscopy and simultaneous topography and recognition imaging

Energy Technology Data Exchange (ETDEWEB)

Duman, M; Pfleger, M; Chtcheglova, L A; Neundlinger, I; Bozna, B L; Ebner, A; Schuetz, G J; Hinterdorfer, P [Institute for Biophysics, University of Linz, Altenbergerstrasse 69, A-4040 Linz (Austria); Zhu, R; Mayer, B [Christian Doppler Laboratory for Nanoscopic Methods in Biophysics, Institute for Biophysics, University of Linz, Altenbergerstrasse 69, A-4040 Linz (Austria); Rankl, C; Moertelmaier, M; Kada, G; Kienberger, F [Agilent Technologies Austria GmbH, Aubrunnerweg 11, A-4040 Linz (Austria); Salio, M; Shepherd, D; Polzella, P; Cerundolo, V [Cancer Research UK Tumor Immunology Group, Weatherall Institute of Molecular Medicine, Nuffield Department of Medicine, University of Oxford, Oxford OX3 9DS (United Kingdom); Dieudonne, M, E-mail: ferry_kienberger@agilent.com [Agilent Technologies Belgium, Wingepark 51, Rotselaar, AN B-3110 (Belgium)

2010-03-19

The combination of fluorescence microscopy and atomic force microscopy has a great potential in single-molecule-detection applications, overcoming many of the limitations coming from each individual technique. Here we present a new platform of combined fluorescence and simultaneous topography and recognition imaging (TREC) for improved localization of cellular receptors. Green fluorescent protein (GFP) labeled human sodium-glucose cotransporter (hSGLT1) expressed Chinese Hamster Ovary (CHO) cells and endothelial cells (MyEnd) from mouse myocardium stained with phalloidin-rhodamine were used as cell systems to study AFM topography and fluorescence microscopy on the same surface area. Topographical AFM images revealed membrane features such as lamellipodia, cytoskeleton fibers, F-actin filaments and small globular structures with heights ranging from 20 to 30 nm. Combined fluorescence and TREC imaging was applied to detect density, distribution and localization of YFP-labeled CD1d molecules on {alpha}-galactosylceramide ({alpha}GalCer)-loaded THP1 cells. While the expression level, distribution and localization of CD1d molecules on THP1 cells were detected with fluorescence microscopy, the nanoscale distribution of binding sites was investigated with molecular recognition imaging by using a chemically modified AFM tip. Using TREC on the inverted light microscope, the recognition sites of cell receptors were detected in recognition images with domain sizes ranging from {approx} 25 to {approx} 160 nm, with the smaller domains corresponding to a single CD1d molecule.

Molecular mechanism for differential recognition of membrane phosphatidylserine by the immune regulatory receptor Tim4.

Science.gov (United States)

Tietjen, Gregory T; Gong, Zhiliang; Chen, Chiu-Hao; Vargas, Ernesto; Crooks, James E; Cao, Kathleen D; Heffern, Charles T R; Henderson, J Michael; Meron, Mati; Lin, Binhua; Roux, Benot; Schlossman, Mark L; Steck, Theodore L; Lee, Ka Yee C; Adams, Erin J

2014-04-15

Recognition of phosphatidylserine (PS) lipids exposed on the extracellular leaflet of plasma membranes is implicated in both apoptotic cell removal and immune regulation. The PS receptor T cell immunoglobulin and mucin-domain-containing molecule 4 (Tim4) regulates T-cell immunity via phagocytosis of both apoptotic (high PS exposure) and nonapoptotic (intermediate PS exposure) activated T cells. The latter population must be removed at lower efficiency to sensitively control immune tolerance and memory cell population size, but the molecular basis for how Tim4 achieves this sensitivity is unknown. Using a combination of interfacial X-ray scattering, molecular dynamics simulations, and membrane binding assays, we demonstrate how Tim4 recognizes PS in the context of a lipid bilayer. Our data reveal that in addition to the known Ca(2+)-coordinated, single-PS binding pocket, Tim4 has four weaker sites of potential ionic interactions with PS lipids. This organization makes Tim4 sensitive to PS surface concentration in a manner capable of supporting differential recognition on the basis of PS exposure level. The structurally homologous, but functionally distinct, Tim1 and Tim3 are significantly less sensitive to PS surface density, likely reflecting the differences in immunological function between the Tim proteins. These results establish the potential for lipid membrane parameters, such as PS surface density, to play a critical role in facilitating selective recognition of PS-exposing cells. Furthermore, our multidisciplinary approach overcomes the difficulties associated with characterizing dynamic protein/membrane systems to reveal the molecular mechanisms underlying Tim4's recognition properties, and thereby provides an approach capable of providing atomic-level detail to uncover the nuances of protein/membrane interactions.

Molecularly imprinted polymers for the recognition of proteins: the state of the art.

Science.gov (United States)

Bossi, A; Bonini, F; Turner, A P F; Piletsky, S A

2007-01-15

Molecular imprinting has proved to be an effective technique for the creation of recognition sites on a polymer scaffold. Protein imprinting has been a focus for many chemists working in the area of molecular recognition, since the creation of synthetic polymers that can specifically recognise proteins is a very challenging but potentially extremely rewarding objective. It is expected that molecularly imprinted polymers (MIPs) with specificity for proteins will find application in medicine, diagnostics, proteomics, environmental analysis, sensors and drug delivery. In this review, the authors provide an overview of the progress achieved in the decade between 1994 and 2005, with respect to the challenging area of MIPs for protein recognition. The discussion furnishes a comparative analysis of different approaches developed, underlining their relative advantages and disadvantages and highlighting trends and possible future directions.

Combined Power Quality Disturbances Recognition Using Wavelet Packet Entropies and S-Transform

Directory of Open Access Journals (Sweden)

Zhigang Liu

2015-08-01

Full Text Available Aiming at the combined power quality +disturbance recognition, an automated recognition method based on wavelet packet entropy (WPE and modified incomplete S-transform (MIST is proposed in this paper. By combining wavelet packet Tsallis singular entropy, energy entropy and MIST, a 13-dimension vector of different power quality (PQ disturbances including single disturbances and combined disturbances is extracted. Then, a ruled decision tree is designed to recognize the combined disturbances. The proposed method is tested and evaluated using a large number of simulated PQ disturbances and some real-life signals, which include voltage sag, swell, interruption, oscillation transient, impulsive transient, harmonics, voltage fluctuation and their combinations. In addition, the comparison of the proposed recognition approach with some existing techniques is made. The experimental results show that the proposed method can effectively recognize the single and combined PQ disturbances.

Combining Semantic and Acoustic Features for Valence and Arousal Recognition in Speech

DEFF Research Database (Denmark)

Karadogan, Seliz; Larsen, Jan

2012-01-01

The recognition of affect in speech has attracted a lot of interest recently; especially in the area of cognitive and computer sciences. Most of the previous studies focused on the recognition of basic emotions (such as happiness, sadness and anger) using categorical approach. Recently, the focus...... has been shifting towards dimensional affect recognition based on the idea that emotional states are not independent from one another but related in a systematic manner. In this paper, we design a continuous dimensional speech affect recognition model that combines acoustic and semantic features. We...... show that combining semantic and acoustic information for dimensional speech recognition improves the results. Moreover, we show that valence is better estimated using semantic features while arousal is better estimated using acoustic features....

Combining heterogenous features for 3D hand-held object recognition

Science.gov (United States)

Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang

2014-10-01

Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.

Effect of buffer at nanoscale molecular recognition interfaces - electrostatic binding of biological polyanions.

Science.gov (United States)

Rodrigo, Ana C; Laurini, Erik; Vieira, Vânia M P; Pricl, Sabrina; Smith, David K

2017-10-19

We investigate the impact of an over-looked component on molecular recognition in water-buffer. The binding of a cationic dye to biological polyanion heparin is shown by isothermal calorimetry to depend on buffer (Tris-HCl > HEPES > PBS). The heparin binding of self-assembled multivalent (SAMul) cationic micelles is even more buffer dependent. Multivalent electrostatic molecular recognition is buffer dependent as a result of competitive interactions between the cationic binding interface and anions present in the buffer.

Molecular tips for scanning tunneling microscopy: intermolecular electron tunneling for single-molecule recognition and electronics.

Science.gov (United States)

Nishino, Tomoaki

2014-01-01

This paper reviews the development of molecular tips for scanning tunneling microscopy (STM). Molecular tips offer many advantages: first is their ability to perform chemically selective imaging because of chemical interactions between the sample and the molecular tip, thus improving a major drawback of conventional STM. Rational design of the molecular tip allows sophisticated chemical recognition; e.g., chiral recognition and selective visualization of atomic defects in carbon nanotubes. Another advantage is that they provide a unique method to quantify electron transfer between single molecules. Understanding such electron transfer is mandatory for the realization of molecular electronics.

Molecular recognition on a cavitand-functionalized silicon surface.

Science.gov (United States)

Biavardi, Elisa; Favazza, Maria; Motta, Alessandro; Fragalà, Ignazio L; Massera, Chiara; Prodi, Luca; Montalti, Marco; Melegari, Monica; Condorelli, Guglielmo G; Dalcanale, Enrico

2009-06-03

A Si(100) surface featuring molecular recognition properties was obtained by covalent functionalization with a tetraphosphonate cavitand (Tiiii), able to complex positively charged species. Tiiii cavitand was grafted onto the Si by photochemical hydrosilylation together with 1-octene as a spatial spectator. The recognition properties of the Si-Tiiii surface were demonstrated through two independent analytical techniques, namely XPS and fluorescence spectroscopy, during the course of reversible complexation-guest exchange-decomplexation cycles with specifically designed ammonium and pyridinium salts. Control experiments employing a Si(100) surface functionalized with a structurally similar, but complexation inactive, tetrathiophosphonate cavitand (TSiiii) demonstrated no recognition events. This provides evidence for the complexation properties of the Si-Tiiii surface, ruling out the possibility of nonspecific interactions between the substrate and the guests. The residual Si-O(-) terminations on the surface replace the guests' original counterions, thus stabilizing the complex ion pairs. These results represent a further step toward the control of self-assembly of complex supramolecular architectures on surfaces.

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

Science.gov (United States)

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

2018-05-01

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

Recognition of conformational changes in beta-lactoglobulin by molecularly imprinted thin films.

Science.gov (United States)

Turner, Nicholas W; Liu, Xiao; Piletsky, Sergey A; Hlady, Vladimir; Britt, David W

2007-09-01

Pathogenesis in protein conformational diseases is initiated by changes in protein secondary structure. This molecular restructuring presents an opportunity for novel shape-based detection approaches, as protein molecular weight and chemistry are otherwise unaltered. Here we apply molecular imprinting to discriminate between distinct conformations of the model protein beta-lactoglobulin (BLG). Thermal- and fluoro-alcohol-induced BLG isoforms were imprinted in thin films of 3-aminophenylboronic acid on quartz crystal microbalance chips. Enhanced rebinding of the template isoform was observed in all cases when compared to the binding of nontemplate isoforms over the concentration range of 1-100 microg mL(-1). Furthermore, it was observed that the greater the changes in the secondary structure of the template protein the lower the binding of native BLG challenges to the imprint, suggesting a strong steric influence in the recognition system. This feasibility study is a first demonstration of molecular imprints for recognition of distinct conformations of the same protein.

Recognition of Conformational Changes in β-Lactoglobulin by Molecularly Imprinted Thin Films

Science.gov (United States)

Turner, Nicholas W.; Liu, Xiao; Piletsky, Sergey A.; Hlady, Vladimir; Britt, David W.

2008-01-01

Pathogenesis in protein conformational diseases is initiated by changes in protein secondary structure. This molecular restructuring presents an opportunity for novel shape-based detection approaches, as protein molecular weight and chemistry are otherwise unaltered. Here we apply molecular imprinting to discriminate between distinct conformations of the model protein β-lactoglobulin (BLG). Thermal- and fluoro-alcohol-induced BLG isoforms were imprinted in thin films of 3-aminophenylboronic acid on quartz crystal microbalance chips. Enhanced rebinding of the template isoform was observed in all cases when compared to the binding of nontemplate isoforms over the concentration range of 1–100 µg mL−1. Furthermore, it was observed that the greater the changes in the secondary structure of the template protein the lower the binding of native BLG challenges to the imprint, suggesting a strong steric influence in the recognition system. This feasibility study is a first demonstration of molecular imprints for recognition of distinct conformations of the same protein. PMID:17665947

Face recognition by combining eigenface method with different wavelet subbands

Institute of Scientific and Technical Information of China (English)

MA Yan; LI Shun-bao

2006-01-01

@@ A method combining eigenface with different wavelet subbands for face recognition is proposed.Each training image is decomposed into multi-subbands for extracting their eigenvector sets and projection vectors.In the recognition process,the inner product distance between the projection vectors of the test image and that of the training image are calculated.The training image,corresponding to the maximum distance under the given threshold condition,is considered as the final result.The experimental results on the ORL and YALE face database show that,compared with the eigenface method directly on the image domain or on a single wavelet subband,the recognition accuracy using the proposed method is improved by 5% without influencing the recognition speed.

Protein-Templated Fragment Ligations-From Molecular Recognition to Drug Discovery.

Science.gov (United States)

Jaegle, Mike; Wong, Ee Lin; Tauber, Carolin; Nawrotzky, Eric; Arkona, Christoph; Rademann, Jörg

2017-06-19

Protein-templated fragment ligation is a novel concept to support drug discovery and can help to improve the efficacy of protein ligands. Protein-templated fragment ligations are chemical reactions between small molecules ("fragments") utilizing a protein's surface as a reaction vessel to catalyze the formation of a protein ligand with increased binding affinity. The approach exploits the molecular recognition of reactive small-molecule fragments by proteins both for ligand assembly and for the identification of bioactive fragment combinations. In this way, chemical synthesis and bioassay are integrated in one single step. This Review discusses the biophysical basis of reversible and irreversible fragment ligations and gives an overview of the available methods to detect protein-templated ligation products. The chemical scope and recent applications as well as future potential of the concept in drug discovery are reviewed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining an Elastic Network With a Coarse-Grained Molecular Force Field : Structure, Dynamics, and Intermolecular Recognition

NARCIS (Netherlands)

Periole, Xavier; Cavalli, Marco; Marrink, Siewert-Jan; Ceruso, Marco A.

Structure-based and physics-based coarse-grained molecular force fields have become attractive approaches to gain mechanistic insight into the function of large biomolecular assemblies. Here, we study how both approaches can be combined into a single representation, that we term ELNEDIN. In this

Signal recognition and parameter estimation of BPSK-LFM combined modulation

Science.gov (United States)

Long, Chao; Zhang, Lin; Liu, Yu

2015-07-01

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

Molecular Recognition Units: Design and diagnostic applications

International Nuclear Information System (INIS)

Alvarez, V.L.; Radcliffe, R.D.; Coughlin, D.J.; Lopes, A.D.; Rodwell, J.D.

1992-01-01

Molecular Recognition Units (MRUs), small peptides derived from complementarity-determining region (CDR) of IgM antibodies, can mimic the recognition site found in the antibody. One example of an MRU fusion peptide designed to image thrombi was derived from PAC 1.1, an IgM monoclonal antibody specific for the GPIIb/IIa receptor on platelets. The peptide sequence from the third CDR of the heavy chain was engineered for optimal binding activity and synthesized with a metal-binding peptide sequence. After labeling with 99m-Tc, the peptides were injected into either animal models of experimentally induced thrombi in order to determine their effectiveness in imaging model thrombi. Data are presented which demonstrate enhanced binding with open-quotes tandem repeatsclose quotes of the MRU domain and no loss of activity after incorporation of the metal-binding domain. These studies have led to a clinical candidate consisting of 17 amino acids. Extension of this concept to other MRUs and fusion peptides is also discussed

Molecular imprinting at walls of silica nanotubes for TNT recognition.

Science.gov (United States)

Xie, Chenggen; Liu, Bianhua; Wang, Zhenyang; Gao, Daming; Guan, Guijian; Zhang, Zhongping

2008-01-15

This paper reports the molecular imprinting at the walls of highly uniform silica nanotubes for the recognition of 2,4,6-trinitrotoluene (TNT). It has been demonstrated that TNT templates were efficiently imprinted into the matrix of silica through the strong acid-base pairing interaction between TNT and 3-aminopropyltriethoxysilane (APTS). TNT-imprinted silica nanotubes were synthesized by the gelation reaction between APTS and tetraethylorthosilicate (TEOS), selectively occurring at the porous walls of APTS-modified alumina membranes. The removal of the original TNT templates leaves the imprinted cavities with covalently anchored amine groups at the cavity walls. A high density of recognition sites with molecular selectivity to the TNT analyte was created at the wall of silica nanotubes. Furthermore, most of these recognition sites are situated at the inside and outside surfaces of tubular walls and in the proximity of the two surfaces due to the ultrathin wall thickness of only 15 nm, providing a better site accessibility and lower mass-transfer resistance. Therefore, greater capacity and faster kinetics of uptaking target species were achieved. The silica nanotube reported herein is an ideal form of material for imprinting various organic or biological molecules toward applications in chemical/biological sensors and bioassay.

Molecular recognition of naphthalene diimide ligands by telomeric quadruplex-DNA: the importance of the protonation state and mediated hydrogen bonds.

Science.gov (United States)

Spinello, A; Barone, G; Grunenberg, J

2016-01-28

In depth Monte Carlo conformational scans in combination with molecular dynamics (MD) simulations and electronic structure calculations were applied in order to study the molecular recognition process between tetrasubstituted naphthalene diimide (ND) guests and G-quadruplex (G4) DNA receptors. ND guests are a promising class of telomere stabilizers due to which they are used in novel anticancer therapeutics. Though several ND guests have been studied experimentally in the past, the protonation state under physiological conditions is still unclear. Based on chemical intuition, in the case of N-methyl-piperazine substitution, different protonation states are possible and might play a crucial role in the molecular recognition process by G4-DNA. Depending on the proton concentration, different nitrogen atoms of the N-methyl-piperazine might (or might not) be protonated. This fact was considered in our simulation in terms of a case by case analysis, since the process of molecular recognition is determined by possible donor or acceptor positions. The results of our simulations show that the electrostatic interactions between the ND ligands and the G4 receptor are maximized in the case of the protonation of the terminal nitrogen atoms, forming compact ND G4 complexes inside the grooves. The influence of different protonation states in terms of the ability to form hydrogen bonds with the sugar-phosphate backbone, as well as the importance of mediated vs. direct hydrogen bonding, was analyzed in detail by MD and relaxed force constant (compliance constant) simulations.

Programmable molecular recognition based on the geometry of DNA nanostructures.

Science.gov (United States)

Woo, Sungwook; Rothemund, Paul W K

2011-07-10

From ligand-receptor binding to DNA hybridization, molecular recognition plays a central role in biology. Over the past several decades, chemists have successfully reproduced the exquisite specificity of biomolecular interactions. However, engineering multiple specific interactions in synthetic systems remains difficult. DNA retains its position as the best medium with which to create orthogonal, isoenergetic interactions, based on the complementarity of Watson-Crick binding. Here we show that DNA can be used to create diverse bonds using an entirely different principle: the geometric arrangement of blunt-end stacking interactions. We show that both binary codes and shape complementarity can serve as a basis for such stacking bonds, and explore their specificity, thermodynamics and binding rules. Orthogonal stacking bonds were used to connect five distinct DNA origami. This work, which demonstrates how a single attractive interaction can be developed to create diverse bonds, may guide strategies for molecular recognition in systems beyond DNA nanostructures.

Adsorption and recognition characteristics of surface molecularly imprinted polymethacrylic acid/silica toward genistein.

Science.gov (United States)

Zhang, Yanyan; Gao, Baojiao; An, Fuqiang; Xu, Zeqing; Zhang, Tingting

2014-09-12

In this paper, on the basis of surface-initiated graft polymerization, a new surface molecular imprinting technique is established by molecular design. And molecularly imprinted polymer MIP-PMAA/SiO2 is successfully prepared with genistein as template. The adsorption and recognition characteristics of MIP-PMAA/SiO2 for genistein are studied in depth by using static method, dynamic method and competitive adsorption experiment. The experimental results show that MIP-PMAA/SiO2 possesses very strong adsorption affinity and specific recognition for genistein. The saturated adsorption capacity could reach to 0.36mmolg(-1). The selectivity coefficients relative to quercetin and rutin are 5.4 and 11.8, respectively. Besides, MIP-PMAA/SiO2 is regenerated easily and exhibits excellent reusability. Copyright © 2014 Elsevier B.V. All rights reserved.

Magnetic-graphene based molecularly imprinted polymer nanocomposite for the recognition of bovine hemoglobin.

Science.gov (United States)

Guo, Junxia; Wang, Yuzhi; Liu, Yanjin; Zhang, Cenjin; Zhou, Yigang

2015-11-01

The protein imprinted technique combining surface imprinting and nanomaterials has been an attractive strategy for recognition and rapid separation of proteins. In this work, magnetic-graphene (MG) was chosen as the supporting substrate for the magnetic nanomaterials, which served to absorb the targeting imprinting molecules, bovine hemoglobin (BHb). Acryl amide (AAm) with a high affinity to BHb and N,N'- methylenebisacrylamide (MBA) were selected as the functional monomer and cross-linking agent, respectively. After in-situ polymerization, the proposed magnetic-graphene based molecularly imprinted polymer (MG-MIP) was obtained with a further extraction step of imprinted BHb. Fourier transform infrared (FT-IR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), raman spectroscopy(RS), X-ray diffraction (XRD) and vibrating sample magnetometer (VSM) were employed to characterize the resulted MG-MIP. The maximum adsorption capability (Qmax) was determined by Langmuir Isotherm Plots and was 186.73 mg/g for imprinted nanomaterials (MIP) with an imprinting factor of 1.96. The selectivity of MG-MIP was investigated by using several proteins that are different in molecular mass and isoelectric points as the reference. The results showed that the shape memory effect of imprinted cavities, the size of proteins and the charge effect of proteins were the major factors for the selective recognition. The proposed method was also employed to specifically capture BHb from a binary protein mixture. Copyright © 2015 Elsevier B.V. All rights reserved.

Support vector machine-based facial-expression recognition method combining shape and appearance

Science.gov (United States)

Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

2010-11-01

Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

Design of supramolecular nanomaterials : from molecular recognition to hierarchical self-assembly

OpenAIRE

El Idrissi, Mohamed

2017-01-01

In the present thesis, are reported new strategies for the design of nanostructures to partly address environmental issues. The work carried out has been divided into three parts: the design of cyclodextrin (CD)-based polymeric materials, the molecular engineering of a pyrene derivative for the formation of self-assembled nanostructures and the design of smart nanocarriers. Considerable efforts have been devoted to the design of molecular receptors capable of specific recognition of a wid...

Molecularly imprinted titania nanoparticles for selective recognition and assay of uric acid

Science.gov (United States)

Mujahid, Adnan; Khan, Aimen Idrees; Afzal, Adeel; Hussain, Tajamal; Raza, Muhammad Hamid; Shah, Asma Tufail; uz Zaman, Waheed

2015-06-01

Molecularly imprinted titania nanoparticles are su ccessfully synthesized by sol-gel method for the selective recognition of uric acid. Atomic force microscopy is used to study the morphology of uric acid imprinted titania nanoparticles with diameter in the range of 100-150 nm. Scanning electron microscopy images of thick titania layer indicate the formation of fine network of titania nanoparticles with uniform distribution. Molecular imprinting of uric acid as well as its subsequent washing is confirmed by Fourier transformation infrared spectroscopy measurements. Uric acid rebinding studies reveal the recognition capability of imprinted particles in the range of 0.01-0.095 mmol, which is applicable in monitoring normal to elevated levels of uric acid in human blood. The optical shift (signal) of imprinted particles is six times higher in comparison with non-imprinted particles for the same concentration of uric acid. Imprinted titania particles have shown substantially reduced binding affinity toward interfering and structurally related substances, e.g. ascorbic acid and guanine. These results suggest the possible application of titania nanoparticles in uric acid recognition and quantification in blood serum.

Recognition of chemical entities: combining dictionary-based and grammar-based approaches

Science.gov (United States)

2015-01-01

Background The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. Results The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. Conclusions We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named

Recognition of chemical entities: combining dictionary-based and grammar-based approaches.

Science.gov (United States)

Akhondi, Saber A; Hettne, Kristina M; van der Horst, Eelke; van Mulligen, Erik M; Kors, Jan A

2015-01-01

The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming

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

Science.gov (United States)

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

2017-02-01

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

Exhibits Recognition System for Combining Online Services and Offline Services

Science.gov (United States)

Ma, He; Liu, Jianbo; Zhang, Yuan; Wu, Xiaoyu

2017-10-01

In order to achieve a more convenient and accurate digital museum navigation, we have developed a real-time and online-to-offline museum exhibits recognition system using image recognition method based on deep learning. In this paper, the client and server of the system are separated and connected through the HTTP. Firstly, by using the client app in the Android mobile phone, the user can take pictures and upload them to the server. Secondly, the features of the picture are extracted using the deep learning network in the server. With the help of the features, the pictures user uploaded are classified with a well-trained SVM. Finally, the classification results are sent to the client and the detailed exhibition’s introduction corresponding to the classification results are shown in the client app. Experimental results demonstrate that the recognition accuracy is close to 100% and the computing time from the image uploading to the exhibit information show is less than 1S. By means of exhibition image recognition algorithm, our implemented exhibits recognition system can combine online detailed exhibition information to the user in the offline exhibition hall so as to achieve better digital navigation.

Piezoelectric sensors based on molecular imprinted polymers for detection of low molecular mass analytes.

Science.gov (United States)

Uludağ, Yildiz; Piletsky, Sergey A; Turner, Anthony P F; Cooper, Matthew A

2007-11-01

Biomimetic recognition elements employed for the detection of analytes are commonly based on proteinaceous affibodies, immunoglobulins, single-chain and single-domain antibody fragments or aptamers. The alternative supra-molecular approach using a molecularly imprinted polymer now has proven utility in numerous applications ranging from liquid chromatography to bioassays. Despite inherent advantages compared with biochemical/biological recognition (which include robustness, storage endurance and lower costs) there are few contributions that describe quantitative analytical applications of molecularly imprinted polymers for relevant small molecular mass compounds in real-world samples. There is, however, significant literature describing the use of low-power, portable piezoelectric transducers to detect analytes in environmental monitoring and other application areas. Here we review the combination of molecularly imprinted polymers as recognition elements with piezoelectric biosensors for quantitative detection of small molecules. Analytes are classified by type and sample matrix presentation and various molecularly imprinted polymer synthetic fabrication strategies are also reviewed.

Conformational Smear Characterization and Binning of Single-Molecule Conductance Measurements for Enhanced Molecular Recognition.

Science.gov (United States)

Korshoj, Lee E; Afsari, Sepideh; Chatterjee, Anushree; Nagpal, Prashant

2017-11-01

Electronic conduction or charge transport through single molecules depends primarily on molecular structure and anchoring groups and forms the basis for a wide range of studies from molecular electronics to DNA sequencing. Several high-throughput nanoelectronic methods such as mechanical break junctions, nanopores, conductive atomic force microscopy, scanning tunneling break junctions, and static nanoscale electrodes are often used for measuring single-molecule conductance. In these measurements, "smearing" due to conformational changes and other entropic factors leads to large variances in the observed molecular conductance, especially in individual measurements. Here, we show a method for characterizing smear in single-molecule conductance measurements and demonstrate how binning measurements according to smear can significantly enhance the use of individual conductance measurements for molecular recognition. Using quantum point contact measurements on single nucleotides within DNA macromolecules, we demonstrate that the distance over which molecular junctions are maintained is a measure of smear, and the resulting variance in unbiased single measurements depends on this smear parameter. Our ability to identify individual DNA nucleotides at 20× coverage increases from 81.3% accuracy without smear analysis to 93.9% with smear characterization and binning (SCRIB). Furthermore, merely 7 conductance measurements (7× coverage) are needed to achieve 97.8% accuracy for DNA nucleotide recognition when only low molecular smear measurements are used, which represents a significant improvement over contemporary sequencing methods. These results have important implications in a broad range of molecular electronics applications from designing robust molecular switches to nanoelectronic DNA sequencing.

DNAzyme Feedback Amplification: Relaying Molecular Recognition to Exponential DNA Amplification.

Science.gov (United States)

Liu, Meng; Yin, Qingxin; McConnell, Erin M; Chang, Yangyang; Brennan, John D; Li, Yingfu

2018-03-26

Technologies capable of linking DNA amplification to molecular recognition are very desirable for ultrasensitive biosensing applications. We have developed a simple but powerful isothermal DNA amplification method, termed DNAzyme feedback amplification (DFA), that is capable of relaying molecular recognition to exponential DNA amplification. The method incorporates both an RNA-cleaving DNAzyme (RCD) and rolling circle amplification (RCA) carried out by a special DNA polymerase using a circular DNA template. DFA begins with a stimulus-dependent RCA reaction, producing tandemly linked RCDs in long-chain DNA products. These RCDs cleave an RNA-containing DNA sequence to form additional primers that hybridize to the circular DNA molecule, giving rise to DNA assemblies that act as the new inputs for RCA. The RCA reaction and the cleavage event keep on feeding each other autonomously, resulting in exponential growth of repetitive DNA sequences that can be easily detected. This method can be used for the detection of both nucleic acid based targets and non-nucleic acid analytes. In this article, we discuss the conceptual framework of the feedback amplification approach, the essential features of this method as well as remaining challenges and possible solutions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Activity Recognition Using A Combination of Category Components And Local Models for Video Surveillance

OpenAIRE

Lin, Weiyao; Sun, Ming-Ting; Poovendran, Radha; Zhang, Zhengyou

2015-01-01

This paper presents a novel approach for automatic recognition of human activities for video surveillance applications. We propose to represent an activity by a combination of category components, and demonstrate that this approach offers flexibility to add new activities to the system and an ability to deal with the problem of building models for activities lacking training data. For improving the recognition accuracy, a Confident-Frame- based Recognition algorithm is also proposed, where th...

Molecular Recognition Involving Anthraquinone Derivatives and Molecular Clips

Science.gov (United States)

Alaparthi, Madhubabu

In the past, we have demonstrated that 1,8-anthraquinone-18-crown-5 (1) and its heterocyclic derivatives act as luminescent hosts for a variety of cations of environmental and clinical concern. We report here a series of heteroatom-substituted macrocycles containing an anthraquinone moiety as a fluorescent signaling unit and a cyclic polyheteroether chain as the receptor. Sulfur, selenium, and tellurium derivatives of 1,8-anthraquinone-18-crown-5 (1) were synthesized by reacting sodium sulfide (Na2S), sodium selenide (Na2Se) and sodium telluride (Na2Te) with 1,8-bis(2-bromoethylethyleneoxy)anthracene - 9,10-dione in a 1:1 ratio (2,3, and 6). These sensors bind metal ions in a 1:1 ratio (7 and 8), and the optical properties of the new complexes were examined and the sulfur and selenium analogues show that selectivity for Pb(II) is markedly improved as compared to the oxygen analogue 1 which was competitive for Ca(II) ion. Selective reduction of 1 yields secondary alcohols where either one or both of the anthraquinone carbonyl groups has been reduced ( 15 and 9). A new mechanism for the fluorescence detection of metal cations in solution is introduced involving a unique keto-enol tautomerization. Reduction of 1 yields the doubly reduced secondary alcohol, 9. 9 acts as a chemodosimeter for Al(III) ion producing a strong blue emission due to the formation of the anthracene fluorophore, 10, via dehydration of the internal secondary alcohol in DMSO/aqueous solution. The enol form is not the most thermodynamically stable form under these conditions however, and slowly converts to the keto form 11.. Currently we are focusing on cucurbituril derivatives, also described as molecular clips due to their folded geometry used as molecular recognition hosts. We first investigated the synthesis and characterization of aromatic methoxy/catechol terminated cucurbituril units that act as hosts for small solvent molecules, such as CH2Cl2, CH3CN, DMF, and MeOH, through dual pi...H-C T

Molecular recognition in myxobacterial outer membrane exchange: functional, social and evolutionary implications.

Science.gov (United States)

Wall, Daniel

2014-01-01

Through cooperative interactions, bacteria can build multicellular communities. To ensure that productive interactions occur, bacteria must recognize their neighbours and respond accordingly. Molecular recognition between cells is thus a fundamental behaviour, and in bacteria important discoveries have been made. This MicroReview focuses on a recently described recognition system in myxobacteria that is governed by a polymorphic cell surface receptor called TraA. TraA regulates outer membrane exchange (OME), whereby myxobacterial cells transiently fuse their OMs to efficiently transfer proteins and lipids between cells. Unlike other transport systems, OME is rather indiscriminate in what OM goods are transferred. In contrast, the recognition of partnering cells is discriminatory and only occurs between cells that bear identical or closely related TraA proteins. Therefore TraA functions in kin recognition and, in turn, OME helps regulate social interactions between myxobacteria. Here, I discuss and speculate on the social and evolutionary implications of OME and suggest it helps to guide their transition from free-living cells into coherent and functional populations. © 2013 John Wiley & Sons Ltd.

Analogies Between Digital Radio and Chemical Orthogonality as a Method for Enhanced Analysis of Molecular Recognition Events

Directory of Open Access Journals (Sweden)

Sang-Hun Lee

2008-02-01

Full Text Available Acoustic wave biosensors are a real-time, label-free biosensor technology, which have been exploited for the detection of proteins and cells. One of the conventional biosensor approaches involves the immobilization of a monolayer of antibodies onto the surface of the acoustic wave device for the detection of a specific analyte. The method described within includes at least two immobilizations of two different antibodies onto the surfaces of two separate acoustic wave devices for the detection of several analogous analytes. The chemical specificity of the molecular recognition event is achieved by virtue of the extremely high (nM to pM binding affinity between the antibody and its antigen. In a standard ELISA (Enzyme-Linked ImmunoSorbent Assay test, there are multiple steps and the end result is a measure of what is bound so tightly that it does not wash away easily. The fact that this “gold standard” is very much not real time, masks the dance that is the molecular recognition event. X-Ray Crystallographer, Ian Wilson, demonstrated more than a decade ago that antibodies undergo conformational change during a binding event[1, 2]. Further, it is known in the arena of immunochemistry that some antibodies exhibit significant cross-reactivity and this is widely termed antibody promiscuity. A third piece of the puzzle that we will exploit in our system of acoustic wave biosensors is the notion of chemical orthogonality. These three biochemical constructs, the dance, antibody promiscuity and chemical orthogonality will be combined in this paper with the notions of Int. J. Mol. Sci. 2008, 9 155 in-phase (I and quadrature (Q signals from digital radio to manifest an approach to molecular recognition that allows a level of discrimination and analysis unobtainable without the aggregate. As an example we present experimental data on the detection of TNT, RDX, C4, ammonium nitrate and musk oil from a system of antibody-coated acoustic

Molecularly Imprinted Polymers: Thermodynamic and Kinetic Considerations on the Specific Sorption and Molecular Recognition

Directory of Open Access Journals (Sweden)

Kejun Tong

2008-04-01

Full Text Available This article presents a work aiming at thermodynamically and kinetically interpreting the specific sorption and recognition by a molecularly imprinted polymer. Using Boc-L-Phe-OH as a template, the imprinted material was prepared. The result indicates that the prepared polymer can well discriminate the imprint species from its analogue (Boc-D-Phe-OH, so as to adsorb more for the former but less for the latter. Kinetic analysis indicates that this specific sorption, in nature, can be a result of a preferential promotion. The imprint within the polymer causes a larger adsorption rate for the template than for the analogue. Thermodynamic study also implies that the molecular induction from the specific imprint to the template is larger than to the analogue, which thus makes the polymer capable of preferentially alluring the template to bind.

Exploring multiple feature combination strategies with a recurrent neural network architecture for off-line handwriting recognition

Science.gov (United States)

Mioulet, L.; Bideault, G.; Chatelain, C.; Paquet, T.; Brunessaux, S.

2015-01-01

The BLSTM-CTC is a novel recurrent neural network architecture that has outperformed previous state of the art algorithms in tasks such as speech recognition or handwriting recognition. It has the ability to process long term dependencies in temporal signals in order to label unsegmented data. This paper describes different ways of combining features using a BLSTM-CTC architecture. Not only do we explore the low level combination (feature space combination) but we also explore high level combination (decoding combination) and mid-level (internal system representation combination). The results are compared on the RIMES word database. Our results show that the low level combination works best, thanks to the powerful data modeling of the LSTM neurons.

Fluorescent and Colorimetric Molecular Recognition Probe for Hydrogen Bond Acceptors

OpenAIRE

Pike, Sarah Jane; Hunter, Christopher Alexander

2018-01-01

The association constants for formation of 1 : 1 complexes between a H-bond donor, 1-naphthol, and a diverse range of charged and neutral H-bond acceptors have been measured using UV/vis absorption and fluorescence emission titrations. The performance of 1-naphthol as a dual colorimetric and fluorescent molecular recognition probe for determining the H-bond acceptor (HBA) parameters of charged and neutral solutes has been investigated in three solvents. The data were employed to establish sel...

Fluorescent and colorimetric molecular recognition probe for hydrogen bond acceptors.

Science.gov (United States)

Pike, Sarah J; Hunter, Christopher A

2017-11-22

The association constants for formation of 1 : 1 complexes between a H-bond donor, 1-naphthol, and a diverse range of charged and neutral H-bond acceptors have been measured using UV/vis absorption and fluorescence emission titrations. The performance of 1-naphthol as a dual colorimetric and fluorescent molecular recognition probe for determining the H-bond acceptor (HBA) parameters of charged and neutral solutes has been investigated in three solvents. The data were employed to establish self-consistent H-bond acceptor parameters (β) for benzoate, azide, chloride, thiocyanate anions, a series of phosphine oxides, phosphate ester, sulfoxide and a tertiary amide. The results demonstrate both the transferability of H-bond parameters between different solvents and the utility of the naphthol-based dual molecular recognition probe to exploit orthogonal spectroscopic techniques to determine the HBA properties of neutral and charged solutes. The benzoate anion is the strongest HBA studied with a β parameter of 15.4, and the neutral tertiary amide is the weakest H-bond acceptor investigated with a β parameter of 8.5. The H-bond acceptor strength of the azide anion is higher than that of chloride (12.8 and 12.2 respectively), and the thiocyanate anion has a β value of 10.8 and thus is a significantly weaker H-bond acceptor than both the azide and chloride anions.

Emotion recognition from speech by combining databases and fusion of classifiers

NARCIS (Netherlands)

Lefter, I.; Rothkrantz, L.J.M.; Wiggers, P.; Leeuwen, D.A. van

2010-01-01

We explore possibilities for enhancing the generality, portability and robustness of emotion recognition systems by combining data-bases and by fusion of classifiers. In a first experiment, we investigate the performance of an emotion detection system tested on a certain database given that it is

Tunable Complex Stability in Surface Molecular Recognition Mediated by Self-Complementary Quadruple Hydrogen Bonds

NARCIS (Netherlands)

Zou, S(han); Zhang, Zhihong; Forch, Renate; Knoll, Wolfgang; Schönherr, Holger; Vancso, Gyula J.

2003-01-01

We show that surfaces modified with asymmetric 2-ureido-4[1H]-pyrimidinone-hydroxyalkane disulfide adsorbates exhibit efficient and controllable self-complementary molecular recognition of the pyrimidinone moieties. Two novel asymmetric 2-ureido-4[1H]-pyrimidinone-hydroxyalkane disulfide adsorbates,

Uyghur face recognition method combining 2DDCT with POEM

Science.gov (United States)

Yi, Lihamu; Ya, Ermaimaiti

2017-11-01

In this paper, in light of the reduced recognition rate and poor robustness of Uyghur face under illumination and partial occlusion, a Uyghur face recognition method combining Two Dimension Discrete Cosine Transform (2DDCT) with Patterns Oriented Edge Magnitudes (POEM) was proposed. Firstly, the Uyghur face images were divided into 8×8 block matrix, and the Uyghur face images after block processing were converted into frequency-domain status using 2DDCT; secondly, the Uyghur face images were compressed to exclude non-sensitive medium frequency parts and non-high frequency parts, so it can reduce the feature dimensions necessary for the Uyghur face images, and further reduce the amount of computation; thirdly, the corresponding POEM histograms of the Uyghur face images were obtained by calculating the feature quantity of POEM; fourthly, the POEM histograms were cascaded together as the texture histogram of the center feature point to obtain the texture features of the Uyghur face feature points; finally, classification of the training samples was carried out using deep learning algorithm. The simulation experiment results showed that the proposed algorithm further improved the recognition rate of the self-built Uyghur face database, and greatly improved the computing speed of the self-built Uyghur face database, and had strong robustness.

All-organic microelectromechanical systems integrating specific molecular recognition--a new generation of chemical sensors.

Science.gov (United States)

Ayela, Cédric; Dubourg, Georges; Pellet, Claude; Haupt, Karsten

2014-09-03

Cantilever-type all-organic microelectromechanical systems based on molecularly imprinted polymers for specific analyte recognition are used as chemical sensors. They are produced by a simple spray-coating-shadow-masking process. Analyte binding to the cantilever generates a measurable change in its resonance frequency. This allows label-free detection by direct mass sensing of low-molecular-weight analytes at nanomolar concentrations. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Molecular recognition in complexes of TRF proteins with telomeric DNA.

Directory of Open Access Journals (Sweden)

Miłosz Wieczór

Full Text Available Telomeres are specialized nucleoprotein assemblies that protect the ends of linear chromosomes. In humans and many other species, telomeres consist of tandem TTAGGG repeats bound by a protein complex known as shelterin that remodels telomeric DNA into a protective loop structure and regulates telomere homeostasis. Shelterin recognizes telomeric repeats through its two major components known as Telomere Repeat-Binding Factors, TRF1 and TRF2. These two homologous proteins are therefore essential for the formation and normal function of telomeres. Indeed, TRF1 and TRF2 are implicated in a plethora of different cellular functions and their depletion leads to telomere dysfunction with chromosomal fusions, followed by apoptotic cell death. More specifically, it was found that TRF1 acts as a negative regulator of telomere length, and TRF2 is involved in stabilizing the loop structure. Consequently, these proteins are of great interest, not only because of their key role in telomere maintenance and stability, but also as potential drug targets. In the current study, we investigated the molecular basis of telomeric sequence recognition by TRF1 and TRF2 and their DNA binding mechanism. We used molecular dynamics (MD to calculate the free energy profiles for binding of TRFs to telomeric DNA. We found that the predicted binding free energies were in good agreement with experimental data. Further, different molecular determinants of binding, such as binding enthalpies and entropies, the hydrogen bonding pattern and changes in surface area, were analyzed to decompose and examine the overall binding free energies at the structural level. With this approach, we were able to draw conclusions regarding the consecutive stages of sequence-specific association, and propose a novel aspartate-dependent mechanism of sequence recognition. Finally, our work demonstrates the applicability of computational MD-based methods to studying protein-DNA interactions.

Synergy of Two Highly Specific Biomolecular Recognition Events

DEFF Research Database (Denmark)

Ejlersen, Maria; Christensen, Niels Johan; Sørensen, Kasper K

2018-01-01

Two highly specific biomolecular recognition events, nucleic acid duplex hybridization and DNA-peptide recognition in the minor groove, were coalesced in a miniature ensemble for the first time by covalently attaching a natural AT-hook peptide motif to nucleic acid duplexes via a 2'-amino......-LNA scaffold. A combination of molecular dynamics simulations and ultraviolet thermal denaturation studies revealed high sequence-specific affinity of the peptide-oligonucleotide conjugates (POCs) when binding to complementary DNA strands, leveraging the bioinformation encrypted in the minor groove of DNA...

Molecularly imprinted poly (methacrylamide-co-methacrylic acid) composite membranes for recognition of curcumin

International Nuclear Information System (INIS)

Wang Ping; Hu Wenming; Su Weike

2008-01-01

In this study, molecularly imprinted poly (methacrylamide-co-methacrylic acid) composite membranes with different ratio of methacrylamide (MAM) versus methacrylic acid (MAA) were prepared via UV initiated photo-copolymerization on the commercial filter paper. Curcumin was chosen as the template molecule. Infra-red (IR) spectroscopy was used to study the binding mechanism between the imprinted sites and the templates. The morphology of the resultant membranes was visualized by scanning electron microscopy (SEM). Static equilibrium binding and recognition properties of the imprinted composite membranes to curcumin (cur-I) and its analogues demethoxycurcumin (cur-II) or bisdemethoxycurcumin (cur-III) were tested. The results showed that curcumin-imprinted membranes had the best recognition ability to curcumin compared to its analogues. From the results, the biggest selectivity factor of α cur-I/cur-II and α cur-I/cur-III were 1.50 and 5.94, and they were obtained from the composite membranes in which MAM/MAA were 1:4 and 0:1, respectively. The results of this study implied that the molecularly imprinted composite membranes could be used as separation membranes for curcumin enrichment

Electrochemical impedimetric sensor based on molecularly imprinted polymers/sol-gel chemistry for methidathion organophosphorous insecticide recognition.

Science.gov (United States)

Bakas, Idriss; Hayat, Akhtar; Piletsky, Sergey; Piletska, Elena; Chehimi, Mohamed M; Noguer, Thierry; Rouillon, Régis

2014-12-01

We report here a novel method to detect methidathion organophosphorous insecticides. The sensing platform was architected by the combination of molecularly imprinted polymers and sol-gel technique on inexpensive, portable and disposable screen printed carbon electrodes. Electrochemical impedimetric detection technique was employed to perform the label free detection of the target analyte on the designed MIP/sol-gel integrated platform. The selection of the target specific monomer by electrochemical impedimetric methods was consistent with the results obtained by the computational modelling method. The prepared electrochemical MIP/sol-gel based sensor exhibited a high recognition capability toward methidathion, as well as a broad linear range and a low detection limit under the optimized conditions. Satisfactory results were also obtained for the methidathion determination in waste water samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparing models of the combined-stimulation advantage for speech recognition.

Science.gov (United States)

Micheyl, Christophe; Oxenham, Andrew J

2012-05-01

The "combined-stimulation advantage" refers to an improvement in speech recognition when cochlear-implant or vocoded stimulation is supplemented by low-frequency acoustic information. Previous studies have been interpreted as evidence for "super-additive" or "synergistic" effects in the combination of low-frequency and electric or vocoded speech information by human listeners. However, this conclusion was based on predictions of performance obtained using a suboptimal high-threshold model of information combination. The present study shows that a different model, based on Gaussian signal detection theory, can predict surprisingly large combined-stimulation advantages, even when performance with either information source alone is close to chance, without involving any synergistic interaction. A reanalysis of published data using this model reveals that previous results, which have been interpreted as evidence for super-additive effects in perception of combined speech stimuli, are actually consistent with a more parsimonious explanation, according to which the combined-stimulation advantage reflects an optimal combination of two independent sources of information. The present results do not rule out the possible existence of synergistic effects in combined stimulation; however, they emphasize the possibility that the combined-stimulation advantages observed in some studies can be explained simply by non-interactive combination of two information sources.

Oxidation-specific epitopes are danger-associated molecular patterns recognized by pattern recognition receptors of innate immunity

DEFF Research Database (Denmark)

Miller, Yury I; Choi, Soo-Ho; Wiesner, Philipp

2011-01-01

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. Furthermore, because many PAMPs on microbes share molecular identity and/or mimicry with oxidation...

Combination of minimum enclosing balls classifier with SVM in coal-rock recognition

Science.gov (United States)

Song, QingJun; Jiang, HaiYan; Song, Qinghui; Zhao, XieGuang; Wu, Xiaoxuan

2017-01-01

Top-coal caving technology is a productive and efficient method in modern mechanized coal mining, the study of coal-rock recognition is key to realizing automation in comprehensive mechanized coal mining. In this paper we propose a new discriminant analysis framework for coal-rock recognition. In the framework, a data acquisition model with vibration and acoustic signals is designed and the caving dataset with 10 feature variables and three classes is got. And the perfect combination of feature variables can be automatically decided by using the multi-class F-score (MF-Score) feature selection. In terms of nonlinear mapping in real-world optimization problem, an effective minimum enclosing ball (MEB) algorithm plus Support vector machine (SVM) is proposed for rapid detection of coal-rock in the caving process. In particular, we illustrate how to construct MEB-SVM classifier in coal-rock recognition which exhibit inherently complex distribution data. The proposed method is examined on UCI data sets and the caving dataset, and compared with some new excellent SVM classifiers. We conduct experiments with accuracy and Friedman test for comparison of more classifiers over multiple on the UCI data sets. Experimental results demonstrate that the proposed algorithm has good robustness and generalization ability. The results of experiments on the caving dataset show the better performance which leads to a promising feature selection and multi-class recognition in coal-rock recognition. PMID:28937987

Combination of minimum enclosing balls classifier with SVM in coal-rock recognition.

Science.gov (United States)

Song, QingJun; Jiang, HaiYan; Song, Qinghui; Zhao, XieGuang; Wu, Xiaoxuan

2017-01-01

Top-coal caving technology is a productive and efficient method in modern mechanized coal mining, the study of coal-rock recognition is key to realizing automation in comprehensive mechanized coal mining. In this paper we propose a new discriminant analysis framework for coal-rock recognition. In the framework, a data acquisition model with vibration and acoustic signals is designed and the caving dataset with 10 feature variables and three classes is got. And the perfect combination of feature variables can be automatically decided by using the multi-class F-score (MF-Score) feature selection. In terms of nonlinear mapping in real-world optimization problem, an effective minimum enclosing ball (MEB) algorithm plus Support vector machine (SVM) is proposed for rapid detection of coal-rock in the caving process. In particular, we illustrate how to construct MEB-SVM classifier in coal-rock recognition which exhibit inherently complex distribution data. The proposed method is examined on UCI data sets and the caving dataset, and compared with some new excellent SVM classifiers. We conduct experiments with accuracy and Friedman test for comparison of more classifiers over multiple on the UCI data sets. Experimental results demonstrate that the proposed algorithm has good robustness and generalization ability. The results of experiments on the caving dataset show the better performance which leads to a promising feature selection and multi-class recognition in coal-rock recognition.

Sensors based on carbon nanotube field-effect transistors and molecular recognition approaches

OpenAIRE

Cid Salavert, Cristina Carlota

2009-01-01

The general objective of this thesis is to develop chemical sensors whose sensing capacities are based on the principle of molecular recognition and where the transduction is carried out by single-walled carbon nanotubes (SWCNT).The sensing device used is the carbon nanotube field-effect transistor (CNTFET). The new structure of the CNTFET allows nanotubes to be integrated at the surface of the devices, thus exploiting SWCNTs' sensitivity to changes in their environment. The functionalization...

Human Activity Recognition by Combining a Small Number of Classifiers.

Science.gov (United States)

Nazabal, Alfredo; Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Ghahramani, Zoubin

2016-09-01

We consider the problem of daily human activity recognition (HAR) using multiple wireless inertial sensors, and specifically, HAR systems with a very low number of sensors, each one providing an estimation of the performed activities. We propose new Bayesian models to combine the output of the sensors. The models are based on a soft outputs combination of individual classifiers to deal with the small number of sensors. We also incorporate the dynamic nature of human activities as a first-order homogeneous Markov chain. We develop both inductive and transductive inference methods for each model to be employed in supervised and semisupervised situations, respectively. Using different real HAR databases, we compare our classifiers combination models against a single classifier that employs all the signals from the sensors. Our models exhibit consistently a reduction of the error rate and an increase of robustness against sensor failures. Our models also outperform other classifiers combination models that do not consider soft outputs and an Markovian structure of the human activities.

Quantum origins of molecular recognition and olfaction in Drosophila.

Science.gov (United States)

Bittner, Eric R; Madalan, Adrian; Czader, Arkadiusz; Roman, Gregg

2012-12-14

The standard model for molecular recognition of an odorant is that receptor sites discriminate by molecular geometry as evidenced that two chiral molecules may smell very differently. However, recent studies of isotopically labeled olfactants indicate that there may be a molecular vibration-sensing component to olfactory reception, specifically in the spectral region around 2300 cm(-1). Here, we present a donor-bridge-acceptor model for olfaction which attempts to explain this effect. Our model, based upon accurate quantum chemical calculations of the olfactant (bridge) in its neutral and ionized states, posits that internal modes of the olfactant are excited impulsively during hole transfer from a donor to acceptor site on the receptor, specifically those modes that are resonant with the tunneling gap. By projecting the impulsive force onto the internal modes, we can determine which modes are excited at a given value of the donor-acceptor tunneling gap. Only those modes resonant with the tunneling gap and are impulsively excited will give a significant contribution to the inelastic transfer rate. Using acetophenone as a test case, our model and experiments on D. melanogaster suggest that isotopomers of a given olfactant give rise to different odorant qualities. These results support the notion that inelastic scattering effects may play a role in discriminating between isotopomers but that this is not a general spectroscopic effect.

Electrochemical sensor for dopamine based on a novel graphene-molecular imprinted polymers composite recognition element

DEFF Research Database (Denmark)

Mao, Yan; Bao, Yu; Gan, Shiyu

2011-01-01

A novel composite of graphene sheets/Congo red-molecular imprinted polymers (GSCR-MIPs) was synthesized through free radical polymerization (FRP) and applied as a molecular recognition element to construct dopamine (DA) electrochemical sensor. The template molecules (DA) were firstly absorbed...... at the GSCR surface due to their excellent affinity, and subsequently, selective copolymerization of methacrylic acid (MAA) and ethylene glycol dimethacrylate (EGDMA) was further achieved at the GSCR surface. Potential scanning was presented to extract DA molecules from the imprinted polymers film...

Specific Electrostatic Molecular Recognition in Water

DEFF Research Database (Denmark)

Li, Ming; Hoeck, Casper; Schoffelen, Sanne

2016-01-01

The identification of pairs of small peptides that recognize each other in water exclusively through electrostatic interactions is reported. The target peptide and a structure-biased combinatorial ligand library consisting of ≈78 125 compounds were synthesized on different sized beads. Peptide......-bead binding assay and by 2D NMR spectroscopy. Molecular dynamics (MD) studies revealed a putative mode of interaction for this unusual electrostatic binding event. High binding specificity occurred through a combination of topological matching and electrostatic and hydrogen-bond complementarities. From MD...

Combination of minimum enclosing balls classifier with SVM in coal-rock recognition.

Directory of Open Access Journals (Sweden)

QingJun Song

Full Text Available Top-coal caving technology is a productive and efficient method in modern mechanized coal mining, the study of coal-rock recognition is key to realizing automation in comprehensive mechanized coal mining. In this paper we propose a new discriminant analysis framework for coal-rock recognition. In the framework, a data acquisition model with vibration and acoustic signals is designed and the caving dataset with 10 feature variables and three classes is got. And the perfect combination of feature variables can be automatically decided by using the multi-class F-score (MF-Score feature selection. In terms of nonlinear mapping in real-world optimization problem, an effective minimum enclosing ball (MEB algorithm plus Support vector machine (SVM is proposed for rapid detection of coal-rock in the caving process. In particular, we illustrate how to construct MEB-SVM classifier in coal-rock recognition which exhibit inherently complex distribution data. The proposed method is examined on UCI data sets and the caving dataset, and compared with some new excellent SVM classifiers. We conduct experiments with accuracy and Friedman test for comparison of more classifiers over multiple on the UCI data sets. Experimental results demonstrate that the proposed algorithm has good robustness and generalization ability. The results of experiments on the caving dataset show the better performance which leads to a promising feature selection and multi-class recognition in coal-rock recognition.

Molecular recognition of malachite green by hemoglobin and their specific interactions: insights from in silico docking and molecular spectroscopy.

Science.gov (United States)

Peng, Wei; Ding, Fei; Peng, Yu-Kui; Sun, Ying

2014-01-01

Malachite green is an organic compound that can be widely used as a dyestuff for various materials; it has also emerged as a controversial agent in aquaculture. Since malachite green is proven to be carcinogenic and mutagenic, it may become a hazard to public health. For this reason, it is urgently required to analyze this controversial dye in more detail. In our current research, the interaction between malachite green and hemoglobin under physiological conditions was investigated by the methods of molecular modeling, fluorescence spectroscopy, circular dichroism (CD) as well as hydrophobic ANS displacement experiments. From the molecular docking, the central cavity of hemoglobin was assigned to possess high-affinity for malachite green, this result was corroborated by time-resolved fluorescence and hydrophobic ANS probe results. The recognition mechanism was found to be of static type, or rather the hemoglobin-malachite green complex formation occurred via noncovalent interactions such as π-π interactions, hydrogen bonds and hydrophobic interactions with an association constant of 10(4) M(-1). Moreover, the results also show that the spatial structure of the biopolymer was changed in the presence of malachite green with a decrease of the α-helix and increase of the β-sheet, turn and random coil suggesting protein damage, as derived from far-UV CD and three-dimensional fluorescence. Results of this work will help to further comprehend the molecular recognition of malachite green by the receptor protein and the possible toxicological profiles of other compounds, which are the metabolites and ramifications of malachite green.

Development of a model for the rational design of molecular imprinted polymer: Computational approach for combined molecular dynamics/quantum mechanics calculations

International Nuclear Information System (INIS)

Dong Cunku; Li Xin; Guo Zechong; Qi Jingyao

2009-01-01

A new rational approach for the preparation of molecularly imprinted polymer (MIP) based on the combination of molecular dynamics (MD) simulations and quantum mechanics (QM) calculations is described in this work. Before performing molecular modeling, a virtual library of functional monomers was created containing forty frequently used monomers. The MD simulations were first conducted to screen the top three monomers from virtual library in each porogen-acetonitrile, chloroform and carbon tetrachloride. QM simulations were then performed with an aim to select the optimum monomer and progen solvent in which the QM simulations were carried out; the monomers giving the highest binding energies were chosen as the candidate to prepare MIP in its corresponding solvent. The acetochlor, a widely used herbicide, was chosen as the target analyte. According to the theoretical calculation results, the MIP with acetochlor as template was prepared by emulsion polymerization method using N,N-methylene bisacrylamide (MBAAM) as functional monomer and divinylbenzene (DVB) as cross-linker in chloroform. The synthesized MIP was then tested by equilibrium-adsorption method, and the MIP demonstrated high removal efficiency to the acetochlor. Mulliken charge distribution and 1 H NMR spectroscopy of the synthesized MIP provided insight on the nature of recognition during the imprinting process probing the governing interactions for selective binding site formation at a molecular level. We think the computer simulation method first proposed in this paper is a novel and reliable method for the design and synthesis of MIP.

Structural analysis and unique molecular recognition properties of a Bauhinia forficata lectin that inhibits cancer cell growth.

Science.gov (United States)

Lubkowski, Jacek; Durbin, Sarah V; Silva, Mariana C C; Farnsworth, David; Gildersleeve, Jeffrey C; Oliva, Maria Luiza V; Wlodawer, Alexander

2017-02-01

Lectins have been used at length for basic research and clinical applications. New insights into the molecular recognition properties enhance our basic understanding of carbohydrate-protein interactions and aid in the design/development of new lectins. In this study, we used a combination of cell-based assays, glycan microarrays, and X-ray crystallography to evaluate the structure and function of the recombinant Bauhinia forficata lectin (BfL). The lectin was shown to be cytostatic for several cancer cell lines included in the NCI-60 panel; in particular, it inhibited growth of melanoma cancer cells (LOX IMVI) by over 95%. BfL is dimeric in solution and highly specific for binding of oligosaccharides and glycopeptides with terminal N-acetylgalactosamine (GalNAc). BfL was found to have especially strong binding (apparent K d  = 0.5-1.0 nm) to the tumor-associated Tn antigen. High-resolution crystal structures were determined for the ligand-free lectin, as well as for its complexes with three Tn glycopeptides, globotetraose, and the blood group A antigen. Extensive analysis of the eight crystal structures and comparison to structures of related lectins revealed several unique features of GalNAc recognition. Of special note, the carboxylate group of Glu126, lining the glycan-binding pocket, forms H-bonds with both the N-acetyl of GalNAc and the peptide amido group of Tn antigens. Stabilization provided by Glu126 is described here for the first time for any GalNAc-specific lectin. Taken together, the results provide new insights into the molecular recognition of carbohydrates and provide a structural understanding that will enable rational engineering of BfL for a variety of applications. Structural data are available in the PDB under the accession numbers 5T50, 5T52, 5T55, 5T54, 5T5L, 5T5J, 5T5P, and 5T5O. © 2016 Federation of European Biochemical Societies.

Molecular Mechanisms of Odor Recognition

National Research Council Canada - National Science Library

Anholt, Robert

2000-01-01

.... We characterized the transduction pathway for the recognition of pheromones in the vomeronasal organ and also characterized subpopulations of olfactory neurons expressing different axonal G proteins...

Use of NMR spectroscopy in combination with pattern recognition techniques for elucidation of origin and adulteration of foodstuffs

Energy Technology Data Exchange (ETDEWEB)

Standal, Inger Beate

2009-07-01

Consumers and food authorities are, to an increasing extent, concerned about factors such as the origin of food, how it is produced, and if it is healthy and safe. There are methods for general quality control to map the safety and nutritional value; however there is a need for suitable analytical methods to verify information such as the production method (wild/farmed), geographical origin, species, and process history of foods. This thesis evaluates the applicability of using nuclear magnetic resonance (NMR) spectroscopy combined with pattern recognition techniques for authentication of foodstuffs. Fish and marine oils were chosen as materials. 13C NMR was applied to authenticate marine oils and muscle lipids of both fatty and lean fish, according to production method (wild/farmed), geographical origin, species, and process history. 1H NMR was applied on low molecular weight compounds extracted from cod muscle to authenticate fish according to species and processing conditions. 13C NMR combined with pattern recognition techniques enabled the differentiation of marine oils according to wild/farmed and geographical origin of the raw material. It is suggested that this was mainly due to the different diets of the fish from which the oil was produced. It was also possible to authenticate marine oils according to species, and to say something about the level of mixtures detectable. The Sn-2 position specificity of fatty acids in triacylglycerols was shown to be an important characteristic to separate oils of different species. Esterified fish oil (concentrates) could easily be differentiated from natural fish oil by their 13C NMR profile. (Author)

Robust Speaker Authentication Based on Combined Speech and Voiceprint Recognition

Science.gov (United States)

Malcangi, Mario

2009-08-01

Personal authentication is becoming increasingly important in many applications that have to protect proprietary data. Passwords and personal identification numbers (PINs) prove not to be robust enough to ensure that unauthorized people do not use them. Biometric authentication technology may offer a secure, convenient, accurate solution but sometimes fails due to its intrinsically fuzzy nature. This research aims to demonstrate that combining two basic speech processing methods, voiceprint identification and speech recognition, can provide a very high degree of robustness, especially if fuzzy decision logic is used.

Recognition of damage-associated, nucleic acid-related molecular patterns during inflammation and vaccination

Directory of Open Access Journals (Sweden)

Nao eJounai

2013-01-01

Full Text Available All mammalian cells are equipped with large numbers of sensors for protection from various sorts of invaders, who, in turn, are equipped with molecules containing pathogen-associated molecular patterns (PAMPs. Once these sensors recognize non-self antigens containing PAMPs, various physiological responses including inflammation are induced to eliminate the pathogens. However, the host sometimes suffers from chronic infection or continuous injuries, resulting in production of self-molecules containing damage-associated molecular patterns (DAMPs. DAMPs are also responsible for the elimination of pathogens, but promiscuous recognition of DAMPs through sensors against PAMPs has been reported. Accumulation of DAMPs leads to massive inflammation and continuous production of DAMPs; that is, a vicious circle leading to the development of autoimmune disease. From a vaccinological point of view, the accurate recognition of both PAMPs and DAMPs is important for vaccine immunogenicity, because vaccine adjuvants are composed of several PAMPs and/or DAMPs, which are also associated with severe adverse events after vaccination. Here, we review as the roles of PAMPs and DAMPs upon infection with pathogens or inflammation, and the sensors responsible for recognizing them, as well as their relationship with the development of autoimmune disease or the immunogenicity of vaccines.

Molecular recognition at methyl methacrylate/n-butyl acrylate (MMA/nBA) monomer unit boundaries of phospholipids at p-MMA/nBA copolymer surfaces.

Science.gov (United States)

Yu, Min; Urban, Marek W; Sheng, Yinghong; Leszczynski, Jerzy

2008-09-16

Lipid structural features and their interactions with proteins provide a useful vehicle for further advances in membrane proteins research. To mimic one of potential lipid-protein interactions we synthesized poly(methyl methacrylate/ n-butyl acrylate) (p-MMA/nBA) colloidal particles that were stabilized by phospholipid (PLs). Upon the particle coalescence, PL stratification resulted in the formation of surface localized ionic clusters (SLICs). These entities are capable of recognizing MMA/nBA monomer interfaces along the p-MMA/nBA copolymer backbone and form crystalline SLICs at the monomer interface. By utilizing attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy and selected area electron diffraction (SAD) combined with ab initio calculations, studies were conducted that identified the origin of SLICs as well as their structural features formed on the surface of p-MMA/nBA copolymer films stabilized by 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC) PL. Specific entities responsible for SLIC formation are selective noncovalent bonds of anionic phosphate and cationic quaternary ammonium segments of DLPC that interact with two neighboring carbonyl groups of nBA and MMA monomers of the p-MMA/nBA polymer backbone. To the best of our knowledge this is the first example of molecular recognition facilitated by coalescence of copolymer colloidal particles and the ability of PLs to form SLICs at the boundaries of the neighboring MMA and nBA monomer units of the p-MMA/nBA chain. The dominating noncovalent bonds responsible for the molecular recognition is a combination of H-bonding and electrostatic interactions.

Selecting Molecular Recognition. What Can Existing Aptamers Tell Us about Their Inherent Recognition Capabilities and Modes of Interaction?

Directory of Open Access Journals (Sweden)

Ralf Landgraf

2012-05-01

Full Text Available The use of nucleic acid derived aptamers has rapidly expanded since the introduction of SELEX in 1990. Nucleic acid aptamers have demonstrated their ability to target a broad range of molecules in ways that rival antibodies, but advances have been very uneven for different biochemical classes of targets, and clinical applications have been slow to emerge. What sets different aptamers apart from each other and from rivaling molecular recognition platforms, specifically proteins? What advantages do aptamers as a reagent class offer, and how do the chemical properties and selection procedures of aptamers influence their function? Do the building blocks of nucleic acid aptamers dictate inherent limitations in the nature of molecular targets, and do existing aptamers give us insight in how these challenges might be overcome? This review is written as an introduction for potential endusers of aptamer technology who are evaluating the advantages of aptamers as a versatile, affordable, yet highly expandable platform to target a broad range of biological processes or interactions.

Consequences of Morphology on Molecularly Imprinted Polymer-Ligand Recognition

Directory of Open Access Journals (Sweden)

Annika M. Rosengren

2013-01-01

Full Text Available The relationship between molecularly imprinted polymer (MIP morphology and template-rebinding over a series of warfarin-imprinted methacrylic acid co(ethylene dimethacrylate polymers has been explored. Detailed investigations of the nature of template recognition revealed that an optimal template binding was obtained with polymers possessing a narrow population of pores (~3–4 nm in the mesopore size range. Importantly, the warfarin-polymer rebinding analyses suggest strategies for regulating ligand binding capacity and specificity through variation of the degree of cross-linking, where polymers prepared with a lower degree of cross-linking afford higher capacity though non-specific in character. In contrast, the co-existence of specific and non-specific binding was found in conjunction with higher degrees of cross-linking and resultant meso- and macropore size distributions.

π-Cation Interactions in Molecular Recognition: Perspectives on Pharmaceuticals and Pesticides.

Science.gov (United States)

Liang, Zhibin; Li, Qing X

2018-04-04

The π-cation interaction that differs from the cation-π interaction is a valuable concept in molecular design of pharmaceuticals and pesticides. In this Perspective we present an up-to-date review (from 1995 to 2017) on bioactive molecules involving π-cation interactions with the recognition site, and categorize into systems of inhibitor-enzyme, ligand-receptor, ligand-transporter, and hapten-antibody. The concept of π-cation interactions offers use of π systems in a small molecule to enhance the binding affinity, specificity, selectivity, lipophilicity, bioavailability, and metabolic stability, which are physiochemical features desired for drugs and pesticides.

Combining Biometric Fractal Pattern and Particle Swarm Optimization-Based Classifier for Fingerprint Recognition

Directory of Open Access Journals (Sweden)

Chia-Hung Lin

2010-01-01

Full Text Available This paper proposes combining the biometric fractal pattern and particle swarm optimization (PSO-based classifier for fingerprint recognition. Fingerprints have arch, loop, whorl, and accidental morphologies, and embed singular points, resulting in the establishment of fingerprint individuality. An automatic fingerprint identification system consists of two stages: digital image processing (DIP and pattern recognition. DIP is used to convert to binary images, refine out noise, and locate the reference point. For binary images, Katz's algorithm is employed to estimate the fractal dimension (FD from a two-dimensional (2D image. Biometric features are extracted as fractal patterns using different FDs. Probabilistic neural network (PNN as a classifier performs to compare the fractal patterns among the small-scale database. A PSO algorithm is used to tune the optimal parameters and heighten the accuracy. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.

Investigating the binding behaviour of two avidin-based testosterone binders using molecular recognition force spectroscopy.

Science.gov (United States)

Rangl, Martina; Leitner, Michael; Riihimäki, Tiina; Lehtonen, Soili; Hytönen, Vesa P; Gruber, Hermann J; Kulomaa, Markku; Hinterdorfer, Peter; Ebner, Andreas

2014-02-01

Molecular recognition force spectroscopy, a biosensing atomic force microscopy technique allows to characterise the dissociation of ligand-receptor complexes at the molecular level. Here, we used molecular recognition force spectroscopy to study the binding capability of recently developed testosterone binders. The two avidin-based proteins called sbAvd-1 and sbAvd-2 are expected to bind both testosterone and biotin but differ in their binding behaviour towards these ligands. To explore the ligand binding and dissociation energy landscape of these proteins, we tethered biotin or testosterone to the atomic force microscopy probe while the testosterone-binding protein was immobilized on the surface. Repeated formation and rupture of the ligand-receptor complex at different pulling velocities allowed determination of the loading rate dependence of the complex-rupturing force. In this way, we obtained the molecular dissociation rate (k(off)) and energy landscape distances (x(β)) of the four possible complexes: sbAvd-1-biotin, sbAvd-1-testosterone, sbAvd-2-biotin and sbAvd-2-testosterone. It was found that the kinetic off-rates for both proteins and both ligands are similar. In contrast, the x(β) values, as well as the probability of complex formations, varied considerably. In addition, competitive binding experiments with biotin and testosterone in solution differ significantly for the two testosterone-binding proteins, implying a decreased cross-reactivity of sbAvd-2. Unravelling the binding behaviour of the investigated testosterone-binding proteins is expected to improve their usability for possible sensing applications. Copyright © 2014 John Wiley & Sons, Ltd.

Higher Desolvation Energy Reduces Molecular Recognition in Multi-Drug Resistant HIV-1 Protease

Directory of Open Access Journals (Sweden)

Ladislau C. Kovari

2012-05-01

Full Text Available Designing HIV-1 protease inhibitors that overcome drug-resistance is still a challenging task. In this study, four clinical isolates of multi-drug resistant HIV-1 proteases that exhibit resistance to all the US FDA-approved HIV-1 protease inhibitors and also reduce the substrate recognition ability were examined. A multi-drug resistant HIV-1 protease isolate, MDR 769, was co-crystallized with the p2/NC substrate and the mutated CA/p2 substrate, CA/p2 P1’F. Both substrates display different levels of molecular recognition by the wild-type and multi-drug resistant HIV-1 protease. From the crystal structures, only limited differences can be identified between the wild-type and multi-drug resistant protease. Therefore, a wild-type HIV-1 protease and four multi-drug resistant HIV-1 proteases in complex with the two peptides were modeled based on the crystal structures and examined during a 10 ns-molecular dynamics simulation. The simulation results reveal that the multi-drug resistant HIV-1 proteases require higher desolvation energy to form complexes with the peptides. This result suggests that the desolvation of the HIV-1 protease active site is an important step of protease-ligand complex formation as well as drug resistance. Therefore, desolvation energy could be considered as a parameter in the evaluation of future HIV-1 protease inhibitor candidates.

Selective Nitrate Recognition by a Halogen‐Bonding Four‐Station [3]Rotaxane Molecular Shuttle

Science.gov (United States)

Barendt, Timothy A.; Docker, Andrew; Marques, Igor; Félix, Vítor

2016-01-01

Abstract The synthesis of the first halogen bonding [3]rotaxane host system containing a bis‐iodo triazolium‐bis‐naphthalene diimide four station axle component is reported. Proton NMR anion binding titration experiments revealed the halogen bonding rotaxane is selective for nitrate over the more basic acetate, hydrogen carbonate and dihydrogen phosphate oxoanions and chloride, and exhibits enhanced recognition of anions relative to a hydrogen bonding analogue. This elaborate interlocked anion receptor functions via a novel dynamic pincer mechanism where upon nitrate anion binding, both macrocycles shuttle from the naphthalene diimide stations at the periphery of the axle to the central halogen bonding iodo‐triazolium station anion recognition sites to form a unique 1:1 stoichiometric nitrate anion–rotaxane sandwich complex. Molecular dynamics simulations carried out on the nitrate and chloride halogen bonding [3]rotaxane complexes corroborate the 1H NMR anion binding results. PMID:27436297

Protein recognition by a pattern-generating fluorescent molecular probe

Science.gov (United States)

Pode, Zohar; Peri-Naor, Ronny; Georgeson, Joseph M.; Ilani, Tal; Kiss, Vladimir; Unger, Tamar; Markus, Barak; Barr, Haim M.; Motiei, Leila; Margulies, David

2017-12-01

Fluorescent molecular probes have become valuable tools in protein research; however, the current methods for using these probes are less suitable for analysing specific populations of proteins in their native environment. In this study, we address this gap by developing a unimolecular fluorescent probe that combines the properties of small-molecule-based probes and cross-reactive sensor arrays (the so-called chemical 'noses/tongues'). On the one hand, the probe can detect different proteins by generating unique identification (ID) patterns, akin to cross-reactive arrays. On the other hand, its unimolecular scaffold and selective binding enable this ID-generating probe to identify combinations of specific protein families within complex mixtures and to discriminate among isoforms in living cells, where macroscopic arrays cannot access. The ability to recycle the molecular device and use it to track several binding interactions simultaneously further demonstrates how this approach could expand the fluorescent toolbox currently used to detect and image proteins.

Molecular imprinting-chemiluminescence determination of trimethoprim using trimethoprim-imprinted polymer as recognition material.

Science.gov (United States)

He, Yunhua; Lu, Jiuru; Liu, Mei; Du, Jianxiu

2005-07-01

A new molecular imprinting-chemiluminescence method for the determination of trimethoprim was developed, in which trimethoprim-imprinted polymer was used as the molecular recognition material and the CL reaction of trimethoprim with potassium permanganate in acidic medium was used as the detection system. The CL intensity responds linearly to the concentration of trimethoprim within the 5.0 x 10(-8)-5.0 x 10(-6) g mL(-1) range (r= 0.9983) with a detection limit of 2 x 10(-8) g mL(-1). The relative standard deviation for the determination of 1.0 x 10(-7) g mL(-1) trimethoprim solutions is 4.8% (n= 9). The method has been applied to the determination of trimethoprim in pharmaceutical preparations and body fluids, and satisfactory results were obtained.

Molecular recognition of nucleotides in micelles and the development and expansion of a chemistry outreach program

Science.gov (United States)

Schechinger, Linda Sue

I. To investigate the delivery of nucleotide-based drugs, we are studying molecular recognition of nucleotide derivatives in environments that are similar to cell membranes. The Nowick group previously discovered that membrane-like surfactant micelles tetradecyltrimethylammonium bromide (TTAB) micelle facilitate molecular of adenosine monophosphate (AMP) recognition. The micelles bind nucleotides by means of electrostatic interactions and hydrogen bonding. We observed binding by following 1H NMR chemical shift changes of unique hexylthymine protons upon addition of AMP. Cationic micelles are required for binding. In surfactant-free or sodium dodecylsulfate solutions, no hydrogen bonding is observed. These observations suggest that the cationic surfactant headgroups bind the nucleotide phosphate group, while the intramicellar base binds the nucleotide base. The micellar system was optimized to enhance binding and selectivity for adenosine nucleotides. The selectivity for adenosine and the number of phosphate groups attached to the adenosine were both investigated. Addition of cytidine, guanidine, or uridine monophosphates, results in no significant downfield shifting of the NH resonance. Selectivity for the phosphate is limited, since adenosine mono-, di-, and triphosphates all have similar binding constants. We successfully achieved molecular recognition of adenosine nucleotides in micellar environments. There is significant difference in the binding interactions between the adenosine nucleotides and three other natural nucleotides. II. The UCI Chemistry Outreach Program (UCICOP) addresses the declining interest of the nations youth for science. UCICOP brings fun and exciting chemistry experiments to local high schools, to remind students that science is fun and has many practical uses. Volunteer students and alumni of UCI perform the demonstrations using scripts and material provided by UCICOP. The preparation of scripts and materials is done by two coordinators

Chemical entity recognition in patents by combining dictionary-based and statistical approaches

Science.gov (United States)

Akhondi, Saber A.; Pons, Ewoud; Afzal, Zubair; van Haagen, Herman; Becker, Benedikt F.H.; Hettne, Kristina M.; van Mulligen, Erik M.; Kors, Jan A.

2016-01-01

We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Passage Detection (CPD) classification task. We addressed both tasks by an ensemble system that combines a dictionary-based approach with a statistical one. For this purpose the performance of several lexical resources was assessed using Peregrine, our open-source indexing engine. We combined our dictionary-based results on the patent corpus with the results of tmChem, a chemical recognizer using a conditional random field classifier. To improve the performance of tmChem, we utilized three additional features, viz. part-of-speech tags, lemmas and word-vector clusters. When evaluated on the training data, our final system obtained an F-score of 85.21% for the CEMP task, and an accuracy of 91.53% for the CPD task. On the test set, the best system ranked sixth among 21 teams for CEMP with an F-score of 86.82%, and second among nine teams for CPD with an accuracy of 94.23%. The differences in performance between the best ensemble system and the statistical system separately were small. Database URL: http://biosemantics.org/chemdner-patents PMID:27141091

Chemotherapy and molecular target therapy combined with radiation therapy

International Nuclear Information System (INIS)

Akimoto, Tetsuo

2012-01-01

Combined chemotherapy and radiation therapy has been established as standard treatment approach for locally advanced head and neck cancer, esophageal cancer and so on through randomized clinical trials. However, radiation-related morbidity such as acute toxicity also increased as treatment intensity has increased. In underlining mechanism for enhancement of normal tissue reaction in chemo-radiation therapy, chemotherapy enhanced radiosensitivity of normal tissues in addition to cancer cells. Molecular target-based drugs combined with radiation therapy have been expected as promising approach that makes it possible to achieve cancer-specific enhancement of radiosensitivity, and clinical trials using combined modalities have been performed to evaluate the feasibility and efficacy of this approach. In order to obtain maximum radiotherapeutic gain, a detailed understanding of the mechanism underlying the interaction between radiation and Molecular target-based drugs is indispensable. Among molecular target-based drugs, inhibitors targeting epidermal growth factor receptor (EGFR) and its signal transduction pathways have been vigorously investigated, and mechanisms regarding the radiosensitizing effect have been getting clear. In addition, the results of randomized clinical trials demonstrated that radiation therapy combined with cetuximab resulted in improvement of overall and disease-specific survival rate compared with radiation therapy in locally advanced head and neck cancer. In this review, clinical usefulness of chemo-radiation therapy and potential molecular targets for potentiation of radiation-induced cell killing are summarized. (author)

MOLECULAR CYTOGENETICS OF LYMPHOMA. WHERE DO WE STAND IN 2010?

OpenAIRE

2011-01-01

Abstract Since approximately 20 years most malignant lymphomas are classified by the recognition of clinico-pathologic entities, each with its own combination of clinical, morphologic, immunophenotypic and molecular genetic characteristics. Obviously, in many instances molecular cytogenetics is of great help for classification and in some lymphomas it is even a prerequisite. Molecular cytogenetic alterations can be detected by a large variety of techniques, ranging from conventiona...

Selective Nitrate Recognition by a Halogen-Bonding Four-Station [3]Rotaxane Molecular Shuttle.

Science.gov (United States)

Barendt, Timothy A; Docker, Andrew; Marques, Igor; Félix, Vítor; Beer, Paul D

2016-09-05

The synthesis of the first halogen bonding [3]rotaxane host system containing a bis-iodo triazolium-bis-naphthalene diimide four station axle component is reported. Proton NMR anion binding titration experiments revealed the halogen bonding rotaxane is selective for nitrate over the more basic acetate, hydrogen carbonate and dihydrogen phosphate oxoanions and chloride, and exhibits enhanced recognition of anions relative to a hydrogen bonding analogue. This elaborate interlocked anion receptor functions via a novel dynamic pincer mechanism where upon nitrate anion binding, both macrocycles shuttle from the naphthalene diimide stations at the periphery of the axle to the central halogen bonding iodo-triazolium station anion recognition sites to form a unique 1:1 stoichiometric nitrate anion-rotaxane sandwich complex. Molecular dynamics simulations carried out on the nitrate and chloride halogen bonding [3]rotaxane complexes corroborate the (1) H NMR anion binding results. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Metal oxide nanosensors using polymeric membranes, enzymes and antibody receptors as ion and molecular recognition elements.

Science.gov (United States)

Willander, Magnus; Khun, Kimleang; Ibupoto, Zafar Hussain

2014-05-16

The concept of recognition and biofunctionality has attracted increasing interest in the fields of chemistry and material sciences. Advances in the field of nanotechnology for the synthesis of desired metal oxide nanostructures have provided a solid platform for the integration of nanoelectronic devices. These nanoelectronics-based devices have the ability to recognize molecular species of living organisms, and they have created the possibility for advanced chemical sensing functionalities with low limits of detection in the nanomolar range. In this review, various metal oxides, such as ZnO-, CuO-, and NiO-based nanosensors, are described using different methods (receptors) of functionalization for molecular and ion recognition. These functionalized metal oxide surfaces with a specific receptor involve either a complex formation between the receptor and the analyte or an electrostatic interaction during the chemical sensing of analytes. Metal oxide nanostructures are considered revolutionary nanomaterials that have a specific surface for the immobilization of biomolecules with much needed orientation, good conformation and enhanced biological activity which further improve the sensing properties of nanosensors. Metal oxide nanostructures are associated with certain unique optical, electrical and molecular characteristics in addition to unique functionalities and surface charge features which shows attractive platforms for interfacing biorecognition elements with effective transducing properties for signal amplification. There is a great opportunity in the near future for metal oxide nanostructure-based miniaturization and the development of engineering sensor devices.

Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

Science.gov (United States)

Mrabet, Yassine; Kilicoglu, Halil; Roberts, Kirk; Demner-Fushman, Dina

2016-01-01

Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-domain knowledge bases. In the first step of our method, we recognize named entities in consumer health questions using an unsupervised method that relies on a biomedical knowledge base, UMLS, and an open-domain knowledge base, DBpedia. In the next step, we cast topic recognition as a binary classification problem of deciding whether a named entity is the question topic or not. We evaluated our approach on a dataset from the National Library of Medicine (NLM), introduced in this paper, and another from the Genetic and Rare Disease Information Center (GARD). The combination of knowledge bases outperformed the results obtained by individual knowledge bases by up to 16.5% F1 and achieved state-of-the-art performance. Our results demonstrate that combining open-domain knowledge bases with biomedical knowledge bases can lead to a substantial improvement in understanding user-generated health content.

Molecularly imprinted polymer based on MWCNT-QDs as fluorescent biomimetic sensor for specific recognition of target protein

Energy Technology Data Exchange (ETDEWEB)

Ding, Zhaoqiang [College of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai 201620 (China); Annie Bligh, S.W. [Department of Life Sciences, Faculty of Science and Technology, University of Westminster, 115 New Cavendish Street, London W1W 6UW (United Kingdom); Tao, Lei; Quan, Jing [College of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai 201620 (China); Nie, Huali, E-mail: niehuali@dhu.edu.cn [College of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai 201620 (China); Zhu, Limin, E-mail: lzhu@dhu.edu.cn [College of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai 201620 (China); Gong, Xiao [College of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai 201620 (China)

2015-03-01

A novel molecularly imprinted optosensing material based on multi-walled carbon nanotube-quantum dots (MWCNT-QDs) has been designed and synthesized for its high selectivity, sensitivity and specificity in the recognition of a target protein bovine serum albumin (BSA). Molecularly imprinted polymer coated MWCNT-QDs using BSA as the template (BMIP-coated MWCNT-QDs) exhibits a fast mass-transfer speed with a response time of 25 min. It is found that the BSA as a target protein can significantly quench the luminescence of BMIP-coated MWCNT-QDs in a concentration-dependent manner that is best described by a Stern–Volmer equation. The K{sub SV} for BSA is much higher than bovine hemoglobin and lysozyme, implying a highly selective recognition of the BMIP-coated MWCNT-QDs to BSA. Under optimal conditions, the relative fluorescence intensity of BMIP-coated MWCNT-QDs decreases linearly with the increasing target protein BSA in the concentration range of 5.0 × 10{sup −7}–35.0 × 10{sup −7} M with a detection limit of 80 nM. - Highlights: • A novel fluorescent biomimetic sensor based on MWCNT-QDs was designed. • The sensor exhibited a fast mass-transfer speed with a response time of 25 min. • The sensor possessed a highly selective recognition to BSA.

[Emotion recognition rehabilitation combined with cognitive stimulation for people with Alzheimer's disease. Efficacy for cognition and functional aspects].

Science.gov (United States)

Garcia-Casal, J A; Goni-Imizcoz, M; Perea-Bartolome, M V; Garcia-Moja, C; Calvo-Simal, S; Cardelle-Garcia, F; Franco-Martin, M

2017-08-01

The ability to recognize facial emotional expression is essential for social interactions and adapting to the environment. Emotion recognition is impaired in people with Alzheimer's disease (AD), thus rehabilitation of these skills has the potential to elicit significant benefits. To assess the efficacy of a combined treatment of rehabilitation of emotion recognition (RER) and cognitive stimulation (CS) for people with AD, due to its potential implications for more effective psychosocial interventions. 36 patients were assigned to one of three experimental conditions: an experimental group (EG) that received 20 sessions of RER and 20 sessions of CS; a control group (CG) that received 40 sessions of CS, and a treatment as usual group (TAU). 32 patients completed the treatment (77.53 ± 5.43 years). Significant differences were found in MMSE30 (F = 5.10; p = 0.013), MMSE35 (F = 4.16; p = 0.026), affect recognition (Z = -2.81; p = 0.005) and basic activities of daily living (Z = -2.27; p = 0.018) favouring the efficacy of the combined treatment. The TAU group showed a decline in depression (Z = -1.99; p = 0.048), apathy (Z = -2.30; p = 0.022) and anosognosia (Z = -2.19; p = 0.028). The combined treatment of RER + CS was more effective than TAU and CS alone for the treatment of patients with AD. This is the first study about the rehabilitation of affect recognition in AD.

Molecularly imprinted nanoparticles with recognition properties towards a laminin H-Tyr-Ile-Gly-Ser-Arg-OH sequence for tissue engineering applications

International Nuclear Information System (INIS)

Rosellini, Elisabetta; Barbani, Niccoletta; Giusti, Paolo; Ciardelli, Gianluca; Cristallini, Caterina

2010-01-01

Nanotechnology is an emerging field that promises to revolutionize medicine and is increasingly used in tissue engineering applications. Our research group proposed for the first time molecular imprinting as a new nanotechnology for the creation of advanced synthetic support structures for cell adhesion and proliferation. The aim of this work was the synthesis and characterization of molecularly imprinted polymers with recognition properties towards a laminin peptide sequence and their application as functionalization structures in the development of bioactive materials. Nanoparticles with an average diameter of 200 nm were synthesized by precipitation polymerization of methacrylic acid in the presence of the template molecule and trimethylpropane trimethacrylate as the cross-linking agent. The imprinted nanoparticles showed good performance in terms of recognition capacity and selectivity. The cytotoxicity tests showed normal vitality of C2C12 myoblasts cultured in the medium that was put in contact with the imprinted polymers. After the deposition on the polymeric film surface, the imprinted particles maintained their specific recognition and rebinding behaviour, showing an even higher quantitative binding than free nanoparticles. Preliminary in vitro cell culture tests demonstrated the ability of functionalized materials to promote cell adhesion, proliferation and differentiation, suggesting that molecular imprinting can be used as an innovative functionalization technique.

Engineering responsive polymer building blocks with host-guest molecular recognition for functional applications.

Science.gov (United States)

Hu, Jinming; Liu, Shiyong

2014-07-15

CONSPECTUS: All living organisms and soft matter are intrinsically responsive and adaptive to external stimuli. Inspired by this fact, tremendous effort aiming to emulate subtle responsive features exhibited by nature has spurred the invention of a diverse range of responsive polymeric materials. Conventional stimuli-responsive polymers are constructed via covalent bonds and can undergo reversible or irreversible changes in chemical structures, physicochemical properties, or both in response to a variety of external stimuli. They have been imparted with a variety of emerging applications including drug and gene delivery, optical sensing and imaging, diagnostics and therapies, smart coatings and textiles, and tissue engineering. On the other hand, in comparison with molecular chemistry held by covalent bonds, supramolecular chemistry built on weak and reversible noncovalent interactions has emerged as a powerful and versatile strategy for materials fabrication due to its facile accessibility, extraordinary reversibility and adaptivity, and potent applications in diverse fields. Typically involving more than one type of noncovalent interactions (e.g., hydrogen bonding, metal coordination, hydrophobic association, electrostatic interactions, van der Waals forces, and π-π stacking), host-guest recognition refers to the formation of supramolecular inclusion complexes between two or more entities connected together in a highly controlled and cooperative manner. The inherently reversible and adaptive nature of host-guest molecular recognition chemistry, stemming from multiple noncovalent interactions, has opened up a new platform to construct novel types of stimuli-responsive materials. The introduction of host-guest chemistry not only enriches the realm of responsive materials but also confers them with promising new applications. Most intriguingly, the integration of responsive polymer building blocks with host-guest recognition motifs will endow the former with

Chemical entity recognition in patents by combining dictionary-based and statistical approaches.

Science.gov (United States)

Akhondi, Saber A; Pons, Ewoud; Afzal, Zubair; van Haagen, Herman; Becker, Benedikt F H; Hettne, Kristina M; van Mulligen, Erik M; Kors, Jan A

2016-01-01

We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Passage Detection (CPD) classification task. We addressed both tasks by an ensemble system that combines a dictionary-based approach with a statistical one. For this purpose the performance of several lexical resources was assessed using Peregrine, our open-source indexing engine. We combined our dictionary-based results on the patent corpus with the results of tmChem, a chemical recognizer using a conditional random field classifier. To improve the performance of tmChem, we utilized three additional features, viz. part-of-speech tags, lemmas and word-vector clusters. When evaluated on the training data, our final system obtained an F-score of 85.21% for the CEMP task, and an accuracy of 91.53% for the CPD task. On the test set, the best system ranked sixth among 21 teams for CEMP with an F-score of 86.82%, and second among nine teams for CPD with an accuracy of 94.23%. The differences in performance between the best ensemble system and the statistical system separately were small.Database URL: http://biosemantics.org/chemdner-patents. © The Author(s) 2016. Published by Oxford University Press.

Metal Oxide Nanosensors Using Polymeric Membranes, Enzymes and Antibody Receptors as Ion and Molecular Recognition Elements

Directory of Open Access Journals (Sweden)

Magnus Willander

2014-05-01

Full Text Available The concept of recognition and biofunctionality has attracted increasing interest in the fields of chemistry and material sciences. Advances in the field of nanotechnology for the synthesis of desired metal oxide nanostructures have provided a solid platform for the integration of nanoelectronic devices. These nanoelectronics-based devices have the ability to recognize molecular species of living organisms, and they have created the possibility for advanced chemical sensing functionalities with low limits of detection in the nanomolar range. In this review, various metal oxides, such as ZnO-, CuO-, and NiO-based nanosensors, are described using different methods (receptors of functionalization for molecular and ion recognition. These functionalized metal oxide surfaces with a specific receptor involve either a complex formation between the receptor and the analyte or an electrostatic interaction during the chemical sensing of analytes. Metal oxide nanostructures are considered revolutionary nanomaterials that have a specific surface for the immobilization of biomolecules with much needed orientation, good conformation and enhanced biological activity which further improve the sensing properties of nanosensors. Metal oxide nanostructures are associated with certain unique optical, electrical and molecular characteristics in addition to unique functionalities and surface charge features which shows attractive platforms for interfacing biorecognition elements with effective transducing properties for signal amplification. There is a great opportunity in the near future for metal oxide nanostructure-based miniaturization and the development of engineering sensor devices.

Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

Science.gov (United States)

Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

A proposal for combining mapping, localization and target recognition

Science.gov (United States)

Grönwall, Christina; Hendeby, Gustaf; Sinivaara, Kristian

2015-10-01

Simultaneous localization and mapping (SLAM) is a well-known positioning approach in GPS-denied environments such as urban canyons and inside buildings. Autonomous/aided target detection and recognition (ATR) is commonly used in military application to detect threats and targets in outdoor environments. This papers present approaches to combine SLAM with ATR in ways that compensate for the drawbacks in each method. The methods use physical objects that are recognizable by ATR as unambiguous features in SLAM, while SLAM provides the ATR with better position estimates. Landmarks in the form of 3D point features based on normal aligned radial features (NARF) are used in conjunction with identified objects and 3D object models that replace landmarks when possible. This leads to a more compact map representation with fewer landmarks, which partly compensates for the introduced cost of the ATR. We analyze three approaches to combine SLAM and 3D-data; point-point matching ignoring NARF features, point-point matching using the set of points that are selected by NARF feature analysis, and matching of NARF features using nearest neighbor analysis. The first two approaches are is similar to the common iterative closest point (ICP). We propose an algorithm that combines EKF-SLAM and ATR based on rectangle estimation. The intended application is to improve the positioning of a first responder moving through an indoor environment, where the map offers localization and simultaneously helps locate people, furniture and potentially dangerous objects such as gas canisters.

Neuroanatomical Markers of Social Hierarchy Recognition in Humans: A Combined ERP/MRI Study.

Science.gov (United States)

Santamaría-García, Hernando; Burgaleta, Miguel; Sebastián-Gallés, Nuria

2015-07-29

Social hierarchy is an ubiquitous principle of social organization across animal species. Although some progress has been made in our understanding of how humans infer hierarchical identity, the neuroanatomical basis for perceiving key social dimensions of others remains unexplored. Here, we combined event-related potentials and structural MRI to reveal the neuroanatomical substrates of early status recognition. We designed a covertly simulated hierarchical setting in which participants performed a task either with a superior or with an inferior player. Participants showed higher amplitude in the N170 component when presented with a picture of a superior player compared with an inferior player. Crucially, the magnitude of this effect correlated with brain morphology of the posterior cingulate cortex, superior temporal gyrus, insula, fusiform gyrus, and caudate nucleus. We conclude that early recognition of social hierarchies relies on the structural properties of a network involved in the automatic recognition of social identity. Humans can perceive social hierarchies very rapidly, an ability that is key for social interactions. However, some individuals are more sensitive to hierarchical information than others. Currently, it is unknown how brain structure supports such fast-paced processes of social hierarchy perception and their individual differences. Here, we addressed this issue for the first time by combining the high temporal resolution of event-related potentials (ERPs) and the high spatial resolution of structural MRI. This methodological approach allowed us to unveil a novel association between ERP neuromarkers of social hierarchy perception and the morphology of several cortical and subcortical brain regions typically assumed to play a role in automatic processes of social cognition. Our results are a step forward in our understanding of the human social brain. Copyright © 2015 the authors 0270-6474/15/3510843-08$15.00/0.

Combined Molecular Dynamics Simulation-Molecular-Thermodynamic Theory Framework for Predicting Surface Tensions.

Science.gov (United States)

Sresht, Vishnu; Lewandowski, Eric P; Blankschtein, Daniel; Jusufi, Arben

2017-08-22

A molecular modeling approach is presented with a focus on quantitative predictions of the surface tension of aqueous surfactant solutions. The approach combines classical Molecular Dynamics (MD) simulations with a molecular-thermodynamic theory (MTT) [ Y. J. Nikas, S. Puvvada, D. Blankschtein, Langmuir 1992 , 8 , 2680 ]. The MD component is used to calculate thermodynamic and molecular parameters that are needed in the MTT model to determine the surface tension isotherm. The MD/MTT approach provides the important link between the surfactant bulk concentration, the experimental control parameter, and the surfactant surface concentration, the MD control parameter. We demonstrate the capability of the MD/MTT modeling approach on nonionic alkyl polyethylene glycol surfactants at the air-water interface and observe reasonable agreement of the predicted surface tensions and the experimental surface tension data over a wide range of surfactant concentrations below the critical micelle concentration. Our modeling approach can be extended to ionic surfactants and their mixtures with both ionic and nonionic surfactants at liquid-liquid interfaces.

Synergetic dual recognition and separation of the fungicide carbendazim by using magnetic nanoparticles carrying a molecularly imprinted polymer and immobilized β-cyclodextrin

International Nuclear Information System (INIS)

Li, Shuhuai; Wu, Xuejin; Zhang, Qun; Li, Pingping

2016-01-01

The authors describe a nanomaterial for solid-phase extraction of carbendazim. Magnetic molecularly imprinted polymer nanoparticles (mag-MIP-NPs) were obtained by immobilizing the MIP and a thiolated β-cyclodextrin on the surface of magnetite (Fe_3O_4) nanoparticles coated with gold nanoparticles. Both the recognition sites of the MIP and the hydrophobic cavities in the β-cyclodextrin contribute to the specific molecular recognition and extraction of carbendazim. The mag-MIP-NPs have an apparent adsorption capacity of 190 mg⋅g"-"1. Spiked vegetables were analyzed by using this material for extraction of carbendazim prior to its determination by ultra performance liquid chromatography (UHPLC). Recoveries range from 90.5 % to 109 %, and the detection limit is 3.0 pg⋅mL"-"1. (author)

Preparation of a magnetic molecularly imprinted polymer for selective recognition of rhodamine B

International Nuclear Information System (INIS)

Liu, Xiuying; Yu, Dan; Yu, Yingchao; Ji, Shujuan

2014-01-01

Graphical abstract: A novel material based on the use of magnetic Fe3O4 nanoparticles coated with MMIP for preconcentration and determination of RhB in real samples prior to fluorospectrophotometry was developed. - Highlights: • A novel rhodamine B magnetic molecularly imprinted polymer by using Fe 3 O 4 magnetite as the magnetically susceptible component was synthesized. • The MMIP had rapid adsorption and high selectivity towards rhodamine B. • Rhodamine B can be extracted selectively by MMIP from real samples. • The method provides the advantages of short analysis time and high sensitivity. - Abstract: A novel magnetic molecularly imprinted polymer (MMIP) was developed as an adsorbent to selectively remove rhodamine B from real samples. The polymer was characterized by scanning electron microscopy, Fourier-transform infrared spectroscopy, and thermo-gravimetric analysis. Static adsorption, kinetic adsorption, and selective recognition experiments were also performed to investigate the specific adsorption equilibrium, kinetics, and selective recognition ability of the MMIP. The MMIPs had outstanding thermal stability, large adsorption capacity, and high competitive selectivity. When they were used as dispersed solid-phase extraction adsorbents in real samples, rhodamine B recovery was 79.97–81.88% and 75.56–79.74% in intra-day and inter-day reproducibility experiments with relative standard deviations lower than 2.62% and 4.28%, respectively. Extraction was optimized for yield and efficiency. Precision, accuracy, and linear working range were determined under optimal experimental conditions. The limits of detection and quantification were 1.05 and 3.49 μg L −1 , respectively. These results suggest MMIPs may be used for determination of rhodamine B in real samples

HPLC fingerprint analysis combined with chemometrics for pattern recognition of ginger.

Science.gov (United States)

Feng, Xu; Kong, Weijun; Wei, Jianhe; Ou-Yang, Zhen; Yang, Meihua

2014-03-01

Ginger, the fresh rhizome of Zingiber officinale Rosc. (Zingiberaceae), has been used worldwide; however, for a long time, there has been no standard approbated internationally for its quality control. To establish an efficacious and combinational method and pattern recognition technique for quality control of ginger. A simple, accurate and reliable method based on high-performance liquid chromatography with photodiode array (HPLC-PDA) detection was developed for establishing the chemical fingerprints of 10 batches of ginger from different markets in China. The method was validated in terms of precision, reproducibility and stability; and the relative standard deviations were all less than 1.57%. On the basis of this method, the fingerprints of 10 batches of ginger samples were obtained, which showed 16 common peaks. Coupled with similarity evaluation software, the similarities between each fingerprint of the sample and the simulative mean chromatogram were in the range of 0.998-1.000. Then, the chemometric techniques, including similarity analysis, hierarchical clustering analysis and principal component analysis were applied to classify the ginger samples. Consistent results were obtained to show that ginger samples could be successfully classified into two groups. This study revealed that HPLC-PDA method was simple, sensitive and reliable for fingerprint analysis, and moreover, for pattern recognition and quality control of ginger.

Molecular Recognition of PTS-1 Cargo Proteins by Pex5p: Implications for Protein Mistargeting in Primary Hyperoxaluria

Directory of Open Access Journals (Sweden)

Noel Mesa-Torres

2015-02-01

Full Text Available Peroxisomal biogenesis and function critically depends on the import of cytosolic proteins carrying a PTS1 sequence into this organelle upon interaction with the peroxin Pex5p. Recent structural studies have provided important insights into the molecular recognition of cargo proteins by Pex5p. Peroxisomal import is a key feature in the pathogenesis of primary hyperoxaluria type 1 (PH1, where alanine:glyoxylate aminotransferase (AGT undergoes mitochondrial mistargeting in about a third of patients. Here, we study the molecular recognition of PTS1 cargo proteins by Pex5p using oligopeptides and AGT variants bearing different natural PTS1 sequences, and employing an array of biophysical, computational and cell biology techniques. Changes in affinity for Pex5p (spanning over 3–4 orders of magnitude reflect different thermodynamic signatures, but overall bury similar amounts of molecular surface. Structure/energetic analyses provide information on the contribution of ancillary regions and the conformational changes induced in Pex5p and the PTS1 cargo upon complex formation. Pex5p stability in vitro is enhanced upon cargo binding according to their binding affinities. Moreover, we provide evidence that the rational modulation of the AGT: Pex5p binding affinity might be useful tools to investigate mistargeting and misfolding in PH1 by pulling the folding equilibria towards the native and peroxisomal import competent state.

Design, preparation, surface recognition properties, and characteristics of icariin molecularly imprinted polymers

Directory of Open Access Journals (Sweden)

Xiaohe Jia

2015-12-01

Full Text Available Icariin molecularly imprinted polymers (MIPs were prepared by precipitation polymerization. Prior to the polymerization, computer simulation was performed to sketchily choose the suitable functional monomer and the corresponding polymerization solvent. The optimized synthesis parameters, including the functional monomer acrylamide, the mixture of methanol and acetonitrile (V:V = 3:1 as the polymerization solvent, and the reaction molar ratio (1:6:80 of template molecule, functional monomer and cross-linker, were respectively obtained by single factor analysis and orthogonal design methods. The results of the adsorption experiments showed that the resultant MIPs exhibited good adsorption and recognition abilities to icariin. Scatchard analysis illustrated that the homogeneous binding sites only for icariin molecules were formed in the prepared MIPs.

Electrospun Nanofibers from a Tricyanofuran-Based Molecular Switch for Colorimetric Recognition of Ammonia Gas.

Science.gov (United States)

Khattab, Tawfik A; Abdelmoez, Sherif; Klapötke, Thomas M

2016-03-14

A chromophore based on tricyanofuran (TCF) with a hydrazone (H) recognition moiety was developed. Its molecular-switching performance is reversible and has differential sensitivity towards aqueous ammonia at comparable concentrations. Nanofibers were fabricated from the TCF-H chromophore by electrospinning. The film fabricated from these nanofibers functions as a solid-state optical chemosensor for probing ammonia vapor. Recognition of ammonia vapor occurs by proton transfer from the hydrazone fragment of the chromophore to the ammonia nitrogen atom and is facilitated by the strongly electron withdrawing TCF fragment. The TCF-H chromophore was added to a solution of poly(acrylic acid), which was electrospun to obtain a nanofibrous sensor device. The morphology of the nanofibrous sensor was determined by SEM, which showed that nanofibers with a diameter range of 200-450 nm formed a nonwoven mat. The resultant nanofibrous sensor showed very good sensitivity in ammonia-vapor detection. Furthermore, very good reversibility and short response time were also observed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electrochemical sensor for catechol and dopamine based on a catalytic molecularly imprinted polymer-conducting polymer hybrid recognition element.

Science.gov (United States)

Lakshmi, Dhana; Bossi, Alessandra; Whitcombe, Michael J; Chianella, Iva; Fowler, Steven A; Subrahmanyam, Sreenath; Piletska, Elena V; Piletsky, Sergey A

2009-05-01

One of the difficulties with using molecularly imprinted polymers (MIPs) and other electrically insulating materials as the recognition element in electrochemical sensors is the lack of a direct path for the conduction of electrons from the active sites to the electrode. We have sought to address this problem through the preparation and characterization of novel hybrid materials combining a catalytic MIP, capable of oxidizing the template, catechol, with an electrically conducting polymer. In this way a network of "molecular wires" assists in the conduction of electrons from the active sites within the MIP to the electrode surface. This was made possible by the design of a new monomer that combines orthogonal polymerizable functionality; comprising an aniline group and a methacrylamide. Conducting films were prepared on the surface of electrodes (Au on glass) by electropolymerization of the aniline moiety. A layer of MIP was photochemically grafted over the polyaniline, via N,N'-diethyldithiocarbamic acid benzyl ester (iniferter) activation of the methacrylamide groups. Detection of catechol by the hybrid-MIP sensor was found to be specific, and catechol oxidation was detected by cyclic voltammetry at the optimized operating conditions: potential range -0.6 V to +0.8 V (vs Ag/AgCl), scan rate 50 mV/s, PBS pH 7.4. The calibration curve for catechol was found to be linear to 144 microM, with a limit of detection of 228 nM. Catechol and dopamine were detected by the sensor, whereas analogues and potentially interfering compounds, including phenol, resorcinol, hydroquinone, serotonin, and ascorbic acid, had minimal effect (< or = 3%) on the detection of either analyte. Non-imprinted hybrid electrodes and bare gold electrodes failed to give any response to catechol at concentrations below 0.5 mM. Finally, the catalytic properties of the sensor were characterized by chronoamperometry and were found to be consistent with Michaelis-Menten kinetics.

Entity recognition in the biomedical domain using a hybrid approach.

Science.gov (United States)

Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

2017-11-09

This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

Online 3D Ear Recognition by Combining Global and Local Features.

Science.gov (United States)

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%.

Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation.

Directory of Open Access Journals (Sweden)

Zheng-Yu Jiang

Full Text Available Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1, a substrate adaptor component of the Cullin3 (Cul3-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2 and IκB kinase β (IKKβ, which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI, the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling.

Molecular recognition of AT-DNA sequences by the induced CD pattern of dibenzotetraaza[14]annulene (DBTAA)-adenine derivatives.

Science.gov (United States)

Stojković, Marijana Radić; Skugor, Marko; Dudek, Lukasz; Grolik, Jarosław; Eilmes, Julita; Piantanida, Ivo

2014-01-01

An investigation of the interactions of two novel and several known DBTAA-adenine conjugates with double-stranded DNA and RNA has revealed the DNA/RNA groove as the dominant binding site, which is in contrast to the majority of previously studied DBTAA analogues (DNA/RNA intercalators). Only DBTAA-propyladenine conjugates revealed the molecular recognition of AT-DNA by an ICD band pattern > 300 nm, whereas significant ICD bands did not appear for other ds-DNA/RNA. A structure-activity relation for the studied series of compounds showed that the essential structural features for the ICD recognition are a) the presence of DNA-binding appendages (adenine side chain and positively charged side chain) on both DBTAA side chains, and b) the presence of a short propyl linker, which does not support intramolecular aromatic stacking between DBTAA and adenine. The observed AT-DNA-ICD pattern differs from previously reported ss-DNA (poly dT) ICD recognition by a strong negative ICD band at 350 nm, which allows for the dynamic differentiation between ss-DNA (poly dT) and coupled ds-AT-DNA.

In Vitro Selection of a Single-Stranded DNA Molecular Recognition Element Specific for Bromacil

Directory of Open Access Journals (Sweden)

Ryan M. Williams

2014-01-01

Full Text Available Bromacil is a widely used herbicide that is known to contaminate environmental systems. Due to the hazards it presents and inefficient detection methods, it is necessary to create a rapid and efficient sensing device. Towards this end, we have utilized a stringent in vitro selection method to identify single-stranded DNA molecular recognition elements (MRE specific for bromacil. We have identified one MRE with high affinity (Kd=9.6 nM and specificity for bromacil compared to negative targets of selection and other pesticides. The selected ssDNA MRE will be useful as the sensing element in a field-deployable bromacil detection device.

RECOGNITION DYNAMICS OF ESCHERICHIA COLI THIOREDOXIN PROBED USING MOLECULAR DYNAMICS AND BINDING FREE ENERGY CALCULATIONS

Directory of Open Access Journals (Sweden)

M. S. Shahul Hameed

2016-03-01

Full Text Available E. coli thioredoxin has been regarded as a hub protein as it interacts with, and regulates, numerous target proteins involved in a wide variety of cellular processes. Thioredoxin can form complexes with a variety of target proteins with a wide range of affinity, using a consensus binding surface. In this study an attempt to deduce the molecular basis for the observed multispecificity of E. coli thioredoxin has been made. In this manuscript it has been shown that structural plasticity, adaptable and exposed hydrophobic binding surface, surface electrostatics, closely clustered multiple hot spot residues and conformational changes brought about by the redox status of the protein have been shown to account for the observed multispecificity and molecular recognition of thioredoxin. Dynamical differences between the two redox forms of the enzyme have also been studied to account for their differing interactions with some target proteins.

Molecular recognition of H3/H4 histone tails by the tudor domains of JMJD2A: a comparative molecular dynamics simulations study.

Directory of Open Access Journals (Sweden)

Musa Ozboyaci

Full Text Available BACKGROUND: Histone demethylase, JMJD2A, specifically recognizes and binds to methylated lysine residues at histone H3 and H4 tails (especially trimethylated H3K4 (H3K4me3, trimethylated H3K9 (H3K9me3 and di,trimethylated H4K20 (H4K20me2, H4K20me3 via its tandem tudor domains. Crystal structures of JMJD2A-tudor binding to H3K4me3 and H4K20me3 peptides are available whereas the others are not. Complete picture of the recognition of the four histone peptides by the tandem tudor domains yet remains to be clarified. METHODOLOGY/PRINCIPAL FINDINGS: We report a detailed molecular dynamics simulation and binding energy analysis of the recognition of JMJD2A-tudor with four different histone tails. 25 ns fully unrestrained molecular dynamics simulations are carried out for each of the bound and free structures. We investigate the important hydrogen bonds and electrostatic interactions between the tudor domains and the peptide molecules and identify the critical residues that stabilize the complexes. Our binding free energy calculations show that H4K20me2 and H3K9me3 peptides have the highest and lowest affinity to JMJD2A-tudor, respectively. We also show that H4K20me2 peptide adopts the same binding mode with H4K20me3 peptide, and H3K9me3 peptide adopts the same binding mode with H3K4me3 peptide. Decomposition of the enthalpic and the entropic contributions to the binding free energies indicate that the recognition of the histone peptides is mainly driven by favourable van der Waals interactions. Residue decomposition of the binding free energies with backbone and side chain contributions as well as their energetic constituents identify the hotspots in the binding interface of the structures. CONCLUSION: Energetic investigations of the four complexes suggest that many of the residues involved in the interactions are common. However, we found two receptor residues that were related to selective binding of the H3 and H4 ligands. Modifications or mutations

Combined-modality treatment of solid tumors using radiotherapy and molecular targeted agents.

Science.gov (United States)

Ma, Brigette B Y; Bristow, Robert G; Kim, John; Siu, Lillian L

2003-07-15

Molecular targeted agents have been combined with radiotherapy (RT) in recent clinical trials in an effort to optimize the therapeutic index of RT. The appeal of this strategy lies in their potential target specificity and clinically acceptable toxicity. This article integrates the salient, published research findings into the underlying molecular mechanisms, preclinical efficacy, and clinical applicability of combining RT with molecular targeted agents. These agents include inhibitors of intracellular signal transduction molecules, modulators of apoptosis, inhibitors of cell cycle checkpoints control, antiangiogenic agents, and cyclo-oxygenase-2 inhibitors. Molecular targeted agents can have direct effects on the cytoprotective and cytotoxic pathways implicated in the cellular response to ionizing radiation (IR). These pathways involve cellular proliferation, DNA repair, cell cycle progression, nuclear transcription, tumor angiogenesis, and prostanoid-associated inflammation. These pathways can also converge to alter RT-induced apoptosis, terminal growth arrest, and reproductive cell death. Pharmacologic modulation of these pathways may potentially enhance tumor response to RT though inhibition of tumor repopulation, improvement of tumor oxygenation, redistribution during the cell cycle, and alteration of intrinsic tumor radiosensitivity. Combining RT and molecular targeted agents is a rational approach in the treatment of solid tumors. Translation of this approach from promising preclinical data to clinical trials is actively underway.

Preparation of molecularly imprinted nanoparticles with superparamagnetic susceptibility through atom transfer radical emulsion polymerization for the selective recognition of tetracycline from aqueous medium

International Nuclear Information System (INIS)

Dai, Jiangdong; Pan, Jianming; Xu, Longcheng; Li, Xiuxiu; Zhou, Zhiping; Zhang, Rongxian; Yan, Yongsheng

2012-01-01

Highlights: ► Atom transfer radical emulsion polymerization is a “living” and green technique. ► Nanoparticles can overcome mass transfer limitations and improve accessibility. ► Molecular imprinted nanoparticles with magnetic property for fast separation. ► The performance of imprinted nanoparticles was investigated in detail. ► Nanoparticles were used to selective recognize Tetracycline from water medium. - Abstract: In the work, we reported an effective method for the preparation of molecularly imprinted nanoparticles with superparamagnetic susceptibility through atom transfer radical emulsion polymerization (ATREP), and then as-prepared magnetic molecularly imprinted nanoparticles (MMINs) were evaluated as adsorbents for selective recognition of tetracycline (TC) molecules from aqueous medium. The resulting nanoparticles were characterized by FT-IR, TGA, VSM, SEM and TEM. The results demonstrated MMINs with a narrow diameter distribution were cross-linked with modified Fe 3 O 4 particles, composed of imprinted layer and exhibited good magnetic sensitivity, magnetic and thermal stability. Batch rebinding studies were carried out to determine the specific adsorption equilibrium, kinetics, and selective recognition. The estimated adsorption capacity of MMINs towards TC by the Langmuir isotherm model was 12.10 mg g −1 at 298 K, which was 6.33 times higher than that of magnetic non-molecularly imprinted nanoparticles (MNINs). The kinetic property of MMINs was well-described by the pseudo-second-order rate equation. The results of selective recognition experiments demonstrated outstanding affinity and selectivity towards TC over competitive antibiotics. The reusability of MMINs showed no obviously deterioration at least five repeated cycles in performance. In addition, the MMINs prepared were successfully applied to the extraction of TC from the spiked pork sample.

Assembling of G-strands into novel tetra-molecular parallel G4-DNA nanostructures using avidin-biotin recognition.

Science.gov (United States)

Borovok, Natalia; Iram, Natalie; Zikich, Dragoslav; Ghabboun, Jamal; Livshits, Gideon I; Porath, Danny; Kotlyar, Alexander B

2008-09-01

We describe a method for the preparation of novel long (hundreds of nanometers), uniform, inter-molecular G4-DNA molecules composed of four parallel G-strands. The only long continuous G4-DNA reported so far are intra-molecular structures made of a single G-strand. To enable a tetra-molecular assembly of the G-strands we developed a novel approach based on avidin-biotin biological recognition. The steps of the G4-DNA production include: (i) Enzymatic synthesis of long poly(dG)-poly(dC) molecules with biotinylated poly(dG)-strand; (ii) Formation of a complex between avidin-tetramer and four biotinylated poly(dG)-poly(dC) molecules; (iii) Separation of the poly(dC) strands from the poly(dG)-strands, which are connected to the avidin; (iv) Assembly of the four G-strands attached to the avidin into tetra-molecular G4-DNA. The average contour length of the formed structures, as measured by AFM, is equal to that of the initial poly(dG)-poly(dC) molecules, suggesting a tetra-molecular mechanism of the G-strands assembly. The height of tetra-molecular G4-nanostructures is larger than that of mono-molecular G4-DNA molecules having similar contour length. The CD spectra of the tetra- and mono-molecular G4-DNA are markedly different, suggesting different structural organization of these two types of molecules. The tetra-molecular G4-DNA nanostructures showed clear electrical polarizability. This suggests that they may be useful for molecular electronics.

Online 3D Ear Recognition by Combining Global and Local Features.

Directory of Open Access Journals (Sweden)

Yahui Liu

Full Text Available The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles and local feature class (points, lines, and areas. These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%.

Molecularly Imprinted Sol-Gel-Based QCM Sensor Arrays for the Detection and Recognition of Volatile Aldehydes

Directory of Open Access Journals (Sweden)

Chuanjun Liu

2017-02-01

Full Text Available The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers; are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM sensor arrays based on molecularly imprinted sol-gel (MISG materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL; nonanal (NAL and bezaldehyde (BAL. The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS and tetrabutoxytitanium (TBOT. Aminopropyltriethoxysilane (APT; diethylaminopropyltrimethoxysilane (EAP and trimethoxy-phenylsilane (TMP were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA; nonanoic acid (NA and benzoic acid (BA were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors; functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA; multivariate analysis of covariance (MANCOVA and hierarchical cluster analysis (HCA. The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors; which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP effect and the matrix

Online handwritten mathematical expression recognition

Science.gov (United States)

Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

2007-01-01

We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

The role of the molecular chaperone heat shock protein A2 (HSPA2 in regulating human sperm-egg recognition

Directory of Open Access Journals (Sweden)

Brett Nixon

2015-01-01

Full Text Available One of the most common lesions present in the spermatozoa of human infertility patients is an idiopathic failure of sperm-egg recognition. Although this unique cellular interaction can now be readily by-passed by assisted reproductive strategies such as intracytoplasmic sperm injection (ICSI, recent large-scale epidemiological studies have encouraged the cautious use of this technology and highlighted the need for further research into the mechanisms responsible for defective sperm-egg recognition. Previous work in this field has established that the sperm domains responsible for oocyte interaction are formed during spermatogenesis prior to being dynamically modified during epididymal maturation and capacitation in female reproductive tract. While the factors responsible for the regulation of these sequential maturational events are undoubtedly complex, emerging research has identified the molecular chaperone, heat shock protein A2 (HSPA2, as a key regulator of these events in human spermatozoa. HSPA2 is a testis-enriched member of the 70 kDa heat shock protein family that promotes the folding, transport, and assembly of protein complexes and has been positively correlated with in vitro fertilization (IVF success. Furthermore, reduced expression of HSPA2 from the human sperm proteome leads to an impaired capacity for cumulus matrix dispersal, sperm-egg recognition and fertilization following both IVF and ICSI. In this review, we consider the evidence supporting the role of HSPA2 in sperm function and explore the potential mechanisms by which it is depleted in the spermatozoa of infertile patients. Such information offers novel insights into the molecular mechanisms governing sperm function.

Molecular profiling of childhood cancer: Biomarkers and novel therapies.

Science.gov (United States)

Saletta, Federica; Wadham, Carol; Ziegler, David S; Marshall, Glenn M; Haber, Michelle; McCowage, Geoffrey; Norris, Murray D; Byrne, Jennifer A

2014-06-01

Technological advances including high-throughput sequencing have identified numerous tumor-specific genetic changes in pediatric and adolescent cancers that can be exploited as targets for novel therapies. This review provides a detailed overview of recent advances in the application of target-specific therapies for childhood cancers, either as single agents or in combination with other therapies. The review summarizes preclinical evidence on which clinical trials are based, early phase clinical trial results, and the incorporation of predictive biomarkers into clinical practice, according to cancer type. There is growing evidence that molecularly targeted therapies can valuably add to the arsenal available for treating childhood cancers, particularly when used in combination with other therapies. Nonetheless the introduction of molecularly targeted agents into practice remains challenging, due to the use of unselected populations in some clinical trials, inadequate methods to evaluate efficacy, and the need for improved preclinical models to both evaluate dosing and safety of combination therapies. The increasing recognition of the heterogeneity of molecular causes of cancer favors the continued development of molecularly targeted agents, and their transfer to pediatric and adolescent populations.

Optimized molecular reconstruction procedure combining hybrid reverse Monte Carlo and molecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Bousige, Colin; Boţan, Alexandru; Coasne, Benoît, E-mail: coasne@mit.edu [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); UMI 3466 CNRS-MIT, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Ulm, Franz-Josef [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Pellenq, Roland J.-M. [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); UMI 3466 CNRS-MIT, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); CINaM, CNRS/Aix Marseille Université, Campus de Luminy, 13288 Marseille Cedex 09 (France)

2015-03-21

We report an efficient atom-scale reconstruction method that consists of combining the Hybrid Reverse Monte Carlo algorithm (HRMC) with Molecular Dynamics (MD) in the framework of a simulated annealing technique. In the spirit of the experimentally constrained molecular relaxation technique [Biswas et al., Phys. Rev. B 69, 195207 (2004)], this modified procedure offers a refined strategy in the field of reconstruction techniques, with special interest for heterogeneous and disordered solids such as amorphous porous materials. While the HRMC method generates physical structures, thanks to the use of energy penalties, the combination with MD makes the method at least one order of magnitude faster than HRMC simulations to obtain structures of similar quality. Furthermore, in order to ensure the transferability of this technique, we provide rational arguments to select the various input parameters such as the relative weight ω of the energy penalty with respect to the structure optimization. By applying the method to disordered porous carbons, we show that adsorption properties provide data to test the global texture of the reconstructed sample but are only weakly sensitive to the presence of defects. In contrast, the vibrational properties such as the phonon density of states are found to be very sensitive to the local structure of the sample.

Accessing Specific Peptide Recognition by Combinatorial Chemistry

DEFF Research Database (Denmark)

Li, Ming

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

Molecular recognition of AT-DNA sequences by the induced CD pattern of dibenzotetraaza[14]annulene (DBTAA)–adenine derivatives

Science.gov (United States)

Stojković, Marijana Radić; Škugor, Marko; Dudek, Łukasz; Grolik, Jarosław; Eilmes, Julita

2014-01-01

Summary An investigation of the interactions of two novel and several known DBTAA–adenine conjugates with double-stranded DNA and RNA has revealed the DNA/RNA groove as the dominant binding site, which is in contrast to the majority of previously studied DBTAA analogues (DNA/RNA intercalators). Only DBTAA–propyladenine conjugates revealed the molecular recognition of AT-DNA by an ICD band pattern > 300 nm, whereas significant ICD bands did not appear for other ds-DNA/RNA. A structure–activity relation for the studied series of compounds showed that the essential structural features for the ICD recognition are a) the presence of DNA-binding appendages (adenine side chain and positively charged side chain) on both DBTAA side chains, and b) the presence of a short propyl linker, which does not support intramolecular aromatic stacking between DBTAA and adenine. The observed AT-DNA-ICD pattern differs from previously reported ss-DNA (poly dT) ICD recognition by a strong negative ICD band at 350 nm, which allows for the dynamic differentiation between ss-DNA (poly dT) and coupled ds-AT-DNA. PMID:25246976

Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System.

Science.gov (United States)

Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

2015-01-01

The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

Preparation of molecularly imprinted nanoparticles with superparamagnetic susceptibility through atom transfer radical emulsion polymerization for the selective recognition of tetracycline from aqueous medium

Energy Technology Data Exchange (ETDEWEB)

Dai, Jiangdong; Pan, Jianming; Xu, Longcheng; Li, Xiuxiu [School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013 (China); Zhou, Zhiping [School of Material Science and Engineering, Jiangsu University, Zhenjiang 212013 (China); Zhang, Rongxian [School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013 (China); Yan, Yongsheng, E-mail: djdxxx123@163.com [School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013 (China); State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing, 100191 (China)

2012-02-29

Highlights: Black-Right-Pointing-Pointer Atom transfer radical emulsion polymerization is a 'living' and green technique. Black-Right-Pointing-Pointer Nanoparticles can overcome mass transfer limitations and improve accessibility. Black-Right-Pointing-Pointer Molecular imprinted nanoparticles with magnetic property for fast separation. Black-Right-Pointing-Pointer The performance of imprinted nanoparticles was investigated in detail. Black-Right-Pointing-Pointer Nanoparticles were used to selective recognize Tetracycline from water medium. - Abstract: In the work, we reported an effective method for the preparation of molecularly imprinted nanoparticles with superparamagnetic susceptibility through atom transfer radical emulsion polymerization (ATREP), and then as-prepared magnetic molecularly imprinted nanoparticles (MMINs) were evaluated as adsorbents for selective recognition of tetracycline (TC) molecules from aqueous medium. The resulting nanoparticles were characterized by FT-IR, TGA, VSM, SEM and TEM. The results demonstrated MMINs with a narrow diameter distribution were cross-linked with modified Fe{sub 3}O{sub 4} particles, composed of imprinted layer and exhibited good magnetic sensitivity, magnetic and thermal stability. Batch rebinding studies were carried out to determine the specific adsorption equilibrium, kinetics, and selective recognition. The estimated adsorption capacity of MMINs towards TC by the Langmuir isotherm model was 12.10 mg g{sup -1} at 298 K, which was 6.33 times higher than that of magnetic non-molecularly imprinted nanoparticles (MNINs). The kinetic property of MMINs was well-described by the pseudo-second-order rate equation. The results of selective recognition experiments demonstrated outstanding affinity and selectivity towards TC over competitive antibiotics. The reusability of MMINs showed no obviously deterioration at least five repeated cycles in performance. In addition, the MMINs prepared were successfully

Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

Science.gov (United States)

Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

2017-05-01

For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high

Clinical effects of low-molecular-weight heparin combined with ...

African Journals Online (AJOL)

Purpose: To explore the clinical effects of low-molecular-weight heparin (LMWH) combined with ulinastatin (UTI) in children with acute pancreatitis. Methods: In total, 560 patients with severe acute pancreatitis treated at Binzhou People's Hospital, Shandong, China, from April 2012 to June 2014 were enrolled in this study.

Preparation and recognition of surface molecularly imprinted core-shell microbeads for protein in aqueous solutions

International Nuclear Information System (INIS)

Lu Yan; Yan Changling; Gao Shuyan

2009-01-01

In this paper, a surface molecular imprinting technique was reported for preparing core-shell microbeads of protein imprinting, and bovine hemoglobin or bovine serum albumin were used as model proteins for studying the imprinted core-shell microbeads. 3-Aminophenylboronic acid (APBA) was polymerized onto the surface of polystyrene microbead in the presence of the protein templates to create protein-imprinted core-shell microbeads. The various samples were characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS) and Brunauer-Emmett-Teller (BET) methods. The effect of pH on rebinding of the template hemoglobin, the specific binding and selective recognition were studied for the imprinted microbeads. The results show that the bovine hemoglobin-imprinted core-shell microbeads were successfully created. The shell was a sort of imprinted thin films with porous structure and larger surface areas. The imprinted microbeads have good selectivity for templates and high stability. Due to the recognition sites locating at or closing to the surface, these imprinted microbeads have good property of mass-transport. Unfortunately, the imprint technology was not successfully applied to imprinting bovine serum albumin (BSA).

Preparation and recognition of surface molecularly imprinted core-shell microbeads for protein in aqueous solutions

Energy Technology Data Exchange (ETDEWEB)

Lu Yan, E-mail: yanlu2001@sohu.com [College of Chemistry and Environmental Science, Henan Normal University, 46 Jlanshe Road, Xinxiang 453007 (China); Yan Changling; Gao Shuyan [College of Chemistry and Environmental Science, Henan Normal University, 46 Jlanshe Road, Xinxiang 453007 (China)

2009-04-01

In this paper, a surface molecular imprinting technique was reported for preparing core-shell microbeads of protein imprinting, and bovine hemoglobin or bovine serum albumin were used as model proteins for studying the imprinted core-shell microbeads. 3-Aminophenylboronic acid (APBA) was polymerized onto the surface of polystyrene microbead in the presence of the protein templates to create protein-imprinted core-shell microbeads. The various samples were characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS) and Brunauer-Emmett-Teller (BET) methods. The effect of pH on rebinding of the template hemoglobin, the specific binding and selective recognition were studied for the imprinted microbeads. The results show that the bovine hemoglobin-imprinted core-shell microbeads were successfully created. The shell was a sort of imprinted thin films with porous structure and larger surface areas. The imprinted microbeads have good selectivity for templates and high stability. Due to the recognition sites locating at or closing to the surface, these imprinted microbeads have good property of mass-transport. Unfortunately, the imprint technology was not successfully applied to imprinting bovine serum albumin (BSA).

Production of Medium Chain Fatty Acids by Yarrowia lipolytica: Combining Molecular Design and TALEN to Engineer the Fatty Acid Synthase.

Science.gov (United States)

Rigouin, Coraline; Gueroult, Marc; Croux, Christian; Dubois, Gwendoline; Borsenberger, Vinciane; Barbe, Sophie; Marty, Alain; Daboussi, Fayza; André, Isabelle; Bordes, Florence

2017-10-20

Yarrowia lipolytica is a promising organism for the production of lipids of biotechnological interest and particularly for biofuel. In this study, we engineered the key enzyme involved in lipid biosynthesis, the giant multifunctional fatty acid synthase (FAS), to shorten chain length of the synthesized fatty acids. Taking as starting point that the ketoacyl synthase (KS) domain of Yarrowia lipolytica FAS is directly involved in chain length specificity, we used molecular modeling to investigate molecular recognition of palmitic acid (C16 fatty acid) by the KS. This enabled to point out the key role of an isoleucine residue, I1220, from the fatty acid binding site, which could be targeted by mutagenesis. To address this challenge, TALEN (transcription activator-like effector nucleases)-based genome editing technology was applied for the first time to Yarrowia lipolytica and proved to be very efficient for inducing targeted genome modifications. Among the generated FAS mutants, those having a bulky aromatic amino acid residue in place of the native isoleucine at position 1220 led to a significant increase of myristic acid (C14) production compared to parental wild-type KS. Particularly, the best performing mutant, I1220W, accumulates C14 at a level of 11.6% total fatty acids. Overall, this work illustrates how a combination of molecular modeling and genome-editing technology can offer novel opportunities to rationally engineer complex systems for synthetic biology.

Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

Directory of Open Access Journals (Sweden)

Pavol Partila

2015-01-01

Full Text Available The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

Combining Illumination Normalization Methods for Better Face Recognition

NARCIS (Netherlands)

Boom, B.J.; Tao, Q.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

2009-01-01

Face Recognition under uncontrolled illumination conditions is partly an unsolved problem. There are two categories of illumination normalization methods. The first category performs a local preprocessing, where they correct a pixel value based on a local neighborhood in the images. The second

Study on the mechanism of chiral recognition with molecularly imprinted polymers

International Nuclear Information System (INIS)

Lu Yan; Li Chenxi; Zhang Hesheng; Liu Xiaohang

2003-01-01

This study aimed at elucidating the chiral recognition mechanism with molecularly imprinted polymers (MIPs) in aqueous environment. The system used ethylene glycol dimethacrylate (EGDMA), methacrylic acid (MAA), and 4-L-phenylalanylamino-pyridine (4-L-PheNHPy) as the cross-linking monomer, functional monomer and template, respectively, to assemble the imprinted polymer. A self-assembly mechanism, which includes the pre-organizing functional monomers around template before polymerization process, was proposed. This mechanism was supported by 1 H NMR titration test. Interactions between functional monomer and template were observed using UV-Vis spectroscopy of solutions of these components as well. These studies indicated a 1:2 molecular complex dominantly formed between 4-L-PheNHPy and MAA. Association constant was estimated to be 97,000 M -2 . Based on these results, a model mainly involving two-spot interaction was proposed evolving from our reported concept of exact placement of functional group. Ionic interaction between the primary amino group of 4-L-PheNHPy and carboxylic acid group inside the microcavity on MIPs was believed to play a predominate role in the enantioselectivity as supported by the observation of the relationship between the retention factor of 4-L-PheNHPy and the pH of mobile phase. While thermodynamic study at different pH revealed that, the interaction between the pyridyl group of 4-L-PheNHPy and the carboxylic acid group on the MIPs is also strong, implying that it also plays a profound role in determining the highly chiral selectivity of MIPs

Leukemia-Associated Mutations in Nucleophosmin Alter Recognition by CRM1: Molecular Basis of Aberrant Transport.

Directory of Open Access Journals (Sweden)

Igor Arregi

Full Text Available Nucleophosmin (NPM is a nucleocytoplasmic shuttling protein, normally enriched in nucleoli, that performs several activities related to cell growth. NPM mutations are characteristic of a subtype of acute myeloid leukemia (AML, where mutant NPM seems to play an oncogenic role. AML-associated NPM mutants exhibit altered subcellular traffic, being aberrantly located in the cytoplasm of leukoblasts. Exacerbated export of AML variants of NPM is mediated by the nuclear export receptor CRM1, and due, in part, to a mutationally acquired novel nuclear export signal (NES. To gain insight on the molecular basis of NPM transport in physiological and pathological conditions, we have evaluated the export efficiency of NPM in cells, and present new data indicating that, in normal conditions, wild type NPM is weakly exported by CRM1. On the other hand, we have found that AML-associated NPM mutants efficiently form complexes with CRM1HA (a mutant CRM1 with higher affinity for NESs, and we have quantitatively analyzed CRM1HA interaction with the NES motifs of these mutants, using fluorescence anisotropy and isothermal titration calorimetry. We have observed that the affinity of CRM1HA for these NESs is similar, which may help to explain the transport properties of the mutants. We also describe NPM recognition by the import machinery. Our combined cellular and biophysical studies shed further light on the determinants of NPM traffic, and how it is dramatically altered by AML-related mutations.

The Improvement of Behavior Recognition Accuracy of Micro Inertial Accelerometer by Secondary Recognition Algorithm

Directory of Open Access Journals (Sweden)

Yu Liu

2014-05-01

Full Text Available Behaviors of “still”, “walking”, “running”, “jumping”, “upstairs” and “downstairs” can be recognized by micro inertial accelerometer of low cost. By using the features as inputs to the well-trained BP artificial neural network which is selected as classifier, those behaviors can be recognized. But the experimental results show that the recognition accuracy is not satisfactory. This paper presents secondary recognition algorithm and combine it with BP artificial neural network to improving the recognition accuracy. The Algorithm is verified by the Android mobile platform, and the recognition accuracy can be improved more than 8 %. Through extensive testing statistic analysis, the recognition accuracy can reach 95 % through BP artificial neural network and the secondary recognition, which is a reasonable good result from practical point of view.

Perspective: Watching low-frequency vibrations of water in biomolecular recognition by THz spectroscopy

Science.gov (United States)

Xu, Yao; Havenith, Martina

2015-11-01

Terahertz (THz) spectroscopy has turned out to be a powerful tool which is able to shed new light on the role of water in biomolecular processes. The low frequency spectrum of the solvated biomolecule in combination with MD simulations provides deep insights into the collective hydrogen bond dynamics on the sub-ps time scale. The absorption spectrum between 1 THz and 10 THz of solvated biomolecules is sensitive to changes in the fast fluctuations of the water network. Systematic studies on mutants of antifreeze proteins indicate a direct correlation between biological activity and a retardation of the (sub)-ps hydration dynamics at the protein binding site, i.e., a "hydration funnel." Kinetic THz absorption studies probe the temporal changes of THz absorption during a biological process, and give access to the kinetics of the coupled protein-hydration dynamics. When combined with simulations, the observed results can be explained in terms of a two-tier model involving a local binding and a long range influence on the hydration bond dynamics of the water around the binding site that highlights the significance of the changes in the hydration dynamics at recognition site for biomolecular recognition. Water is shown to assist molecular recognition processes.

Site-discrimination by molecular imposters at dissymmetric molecular crystal surfaces

Science.gov (United States)

Poloni, Laura N.

The organization of atoms and molecules into crystalline forms is ubiquitous in nature and has been critical to the development of many technologies on which modern society relies. Classical crystal growth theory can describe atomic crystal growth, however, a description of molecular crystal growth is lacking. Molecular crystals are often characterized by anisotropic intermolecular interactions and dissymmetric crystal surfaces with anisotropic growth rates along different crystallographic directions. This thesis describes combination of experimental and computational techniques to relate crystal structure to surface structure and observed growth rates. Molecular imposters, also known as tailor-made impurities, can be used to control crystal growth for practical applications such as inhibition of pathological crystals, but can also be used to understand site specificity at crystal growth surfaces. The first part of this thesis builds on previous real-time in situ atomic force microscopy (AFM) observations of dislocation-actuated growth on the morphologically significant face of hexagonal L-cystine crystals, which aggregate in vivo to form kidney stones in patients suffering from cystinuria. The inhibitory effect of various L-cystine structural mimics (a.k.a. molecular imposters) was investigated through experimental and computational methods to identify the key structural factors responsible for molecular recognition between molecular imposters and L-cystine crystal surface sites. The investigation of L-cystine crystal growth in the presence of molecular imposters through a combination of kinetic analysis using in situ AFM, morphology analysis and birefringence measurements of bulk crystals, and molecular modeling of imposter binding to energetically inequivalent surface sites revealed that different molecular imposters inhibited crystal growth by a Cabrera-Vermilyea pinning mechanism and that imposters bind to a single binding site on the dissymmetric {1000} L

Low molecular weight salts combined with fluorinated solvents for electrolytes

Science.gov (United States)

Tikhonov, Konstantin; Yip, Ka Ki; Lin, Tzu-Yuan; Lei, Norman; Guerrero-Zavala, Guillermo; Kwong, Kristie W.

2015-11-10

Provided are electrochemical cells and electrolytes used to build such cells. An electrolyte includes at least one salt having a molecular weight less than about 250. Such salts allow forming electrolytes with higher salt concentrations and ensure high conductivity and ion transport in these electrolytes. The low molecular weight salt may have a concentration of at least about 0.5M and may be combined with one or more other salts, such as linear and cyclic imide salts and/or methide salts. The concentration of these additional salts may be less than that of the low molecular weight salt, in some embodiments, twice less. The additional salts may have a molecular weight greater than about 250. The electrolyte may also include one or more fluorinated solvents and may be capable of maintaining single phase solutions at between about -30.degree. C. to about 80.degree. C.

Molecularly imprinted polymer based on chemiluminescence imaging for the chiral recognition of dansyl-phenylalanine.

Science.gov (United States)

Wang, Li; Zhang, Zhujun; Huang, Lianggao

2008-03-01

A new molecularly imprinted polymer (MIP)-chemiluminescence (CL) imaging detection approach towards chiral recognition of dansyl-phenylalanine (Phe) is presented. The polymer microspheres were synthesized using precipitation polymerization with dansyl-L-Phe as template. Polymer microspheres were immobilized in microtiter plates (96 wells) using poly(vinyl alcohol) (PVA) as glue. The analyte was selectively adsorbed on the MIP microspheres. After washing, the bound fraction was quantified based on peroxyoxalate chemiluminescence (PO-CL) analysis. In the presence of dansyl-Phe, bis(2,4,6-trichlorophenyl)oxalate (TCPO) reacted with hydrogen peroxide (H2O2) to emit chemiluminescence. The signal was detected and quantified with a highly sensitive cooled charge-coupled device (CCD). Influencing factors were investigated and optimized in detail. Control experiments using capillary electrophoresis showed that there was no significant difference between the proposed method and the control method at a confidence level of 95%. The method can perform 96 independent measurements simultaneously in 30 min and the limits of detection (LODs) for dansyl-L-Phe and dansyl-D-Phe were 0.025 micromol L(-1) and 0.075 micromol L(-1) (3sigma), respectively. The relative standard deviation (RSD) for 11 parallel measurements of dansyl-L-Phe (0.78 micromol L(-1)) was 8%. The results show that MIP-based CL imaging can become a useful analytical technology for quick chiral recognition.

Authentication of Whey Protein Powders by Portable Mid-Infrared Spectrometers Combined with Pattern Recognition Analysis.

Science.gov (United States)

Wang, Ting; Tan, Siow Ying; Mutilangi, William; Aykas, Didem P; Rodriguez-Saona, Luis E

2015-10-01

The objective of this study was to develop a simple and rapid method to differentiate whey protein types (WPC, WPI, and WPH) used for beverage manufacturing by combining the spectral signature collected from portable mid-infrared spectrometers and pattern recognition analysis. Whey protein powders from different suppliers are produced using a large number of processing and compositional variables, resulting in variation in composition, concentration, protein structure, and thus functionality. Whey protein powders including whey protein isolates, whey protein concentrates and whey protein hydrolysates were obtained from different suppliers and their spectra collected using portable mid-infrared spectrometers (single and triple reflection) by pressing the powder onto an Attenuated Total Reflectance (ATR) diamond crystal with a pressure clamp. Spectra were analyzed by soft independent modeling of class analogy (SIMCA) generating a classification model showing the ability to differentiate whey protein types by forming tight clusters with interclass distance values of >3, considered to be significantly different from each other. The major bands centered at 1640 and 1580 cm(-1) were responsible for separation and were associated with differences in amide I and amide II vibrations of proteins, respectively. Another important band in whey protein clustering was associated with carboxylate vibrations of acidic amino acids (∼1570 cm(-1)). The use of a portable mid-IR spectrometer combined with pattern recognition analysis showed potential for discriminating whey protein ingredients that can help to streamline the analytical procedure so that it is more applicable for field-based screening of ingredients. A rapid, simple and accurate method was developed to authenticate commercial whey protein products by using portable mid-infrared spectrometers combined with chemometrics, which could help ensure the functionality of whey protein ingredients in food applications. © 2015

Interconnectivity of macroporous molecularly imprinted polymers fabricated by hydroxyapatite-stabilized Pickering high internal phase emulsions-hydrogels for the selective recognition of protein.

Science.gov (United States)

Sun, Yanhua; Li, Yuqing; Xu, Jiangfeng; Huang, Ling; Qiu, Tianyun; Zhong, Shian

2017-07-01

Hydroxyapatite hybridized molecularly imprinted polydopamine polymers with selective recognition of bovine hemoglobin (BHb) were successfully prepared via Pickering oil-in-water high internal phase emulsions-hydrogels and molecularly imprinting technique. The emulsions were stabilized by hydroxyapatite of which the wettability was modified by 3-methacryloxypropyltrimethoxysilane. The materials were characterized by SEM, IR and TGA. The results showed that the BHb imprinted polymers based on Pickering hydrogels (Hydro-MIPs) possess macropores ranging from 20μm to 50μm, and their large numbers of amino groups and hydroxyl groups result in a favorable adsorption capacity for BHb. The maximum adsorption capacity of Hydro-MIPs for BHb was 438mg/g, 3.27 times more than that of the non-imprinted polymers (Hydro-NIPs). The results indicated that Hydro-MIPs possessing well-defined hierarchical porous structures exhibited outstanding recognition behavior towards the target protein molecules. This work provided a promising alternative method for the fabrication of polymer materials with tunable and interconnected pores structures for the separation and purification of protein in vitro. Copyright © 2017. Published by Elsevier B.V.

iBodies: modular synthetic antibody mimetics based on hydrophilic polymers decorated with functional moieties as tools for molecular recognition, imaging and specific drug delivery

Czech Academy of Sciences Publication Activity Database

Šácha, Pavel; Dvořáková, Petra; Knedlík, Tomáš; Schimer, Jiří; Šubr, Vladimír; Ulbrich, Karel; Bušek, P.; Navrátil, Václav; Sedlák, František; Majer, Pavel; Šedo, A.; Konvalinka, Jan

2017-01-01

Roč. 284, Suppl 1 (2017), s. 340 ISSN 1742-464X. [FEBS Congress /42./ From Molecules to Cells and Back. 10.09.2017-14.09.2017, Jerusalem] Institutional support: RVO:61388963 ; RVO:61389013 Keywords : antibody mimetics * molecular recognition * polymer conjugates Subject RIV: CE - Biochemistry

Facial expression recognition based on improved deep belief networks

Science.gov (United States)

Wu, Yao; Qiu, Weigen

2017-08-01

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

Enhanced host–guest electrochemical recognition of herbicide MCPA using a b-cyclodextrin carbon nanotube sensor

OpenAIRE

Rahemi, V.; Vandamme, J.J.; Garrido, J.M.P.J.; Borges, F.; Brett, C.M.A.; Garrido, E.M.P.J.

2012-01-01

An electrochemical sensor for the determination of the chlorophenoxy herbicide MCPA has been developed, based on a combination of multi-walled carbon nanotubes with incorporated b-cyclodextrin and a polyaniline film modified glassy carbon electrode. The proposed molecular host–guest recogni-tion based sensor has a high electrochemical sensitivity for the determination of MCPA. The electrochemical behaviour of MCPA at the chemically modified electrode was investigated in detail by cyclic volta...

Molecular basis for the wide range of affinity found in Csr/Rsm protein-RNA recognition.

Science.gov (United States)

Duss, Olivier; Michel, Erich; Diarra dit Konté, Nana; Schubert, Mario; Allain, Frédéric H-T

2014-04-01

The carbon storage regulator/regulator of secondary metabolism (Csr/Rsm) type of small non-coding RNAs (sRNAs) is widespread throughout bacteria and acts by sequestering the global translation repressor protein CsrA/RsmE from the ribosome binding site of a subset of mRNAs. Although we have previously described the molecular basis of a high affinity RNA target bound to RsmE, it remains unknown how other lower affinity targets are recognized by the same protein. Here, we have determined the nuclear magnetic resonance solution structures of five separate GGA binding motifs of the sRNA RsmZ of Pseudomonas fluorescens in complex with RsmE. The structures explain how the variation of sequence and structural context of the GGA binding motifs modulate the binding affinity for RsmE by five orders of magnitude (∼10 nM to ∼3 mM, Kd). Furthermore, we see that conformational adaptation of protein side-chains and RNA enable recognition of different RNA sequences by the same protein contributing to binding affinity without conferring specificity. Overall, our findings illustrate how the variability in the Csr/Rsm protein-RNA recognition allows a fine-tuning of the competition between mRNAs and sRNAs for the CsrA/RsmE protein.

Molecular mechanism of ligand recognition by membrane transport protein, Mhp1

Science.gov (United States)

Simmons, Katie J; Jackson, Scott M; Brueckner, Florian; Patching, Simon G; Beckstein, Oliver; Ivanova, Ekaterina; Geng, Tian; Weyand, Simone; Drew, David; Lanigan, Joseph; Sharples, David J; Sansom, Mark SP; Iwata, So; Fishwick, Colin WG; Johnson, A Peter; Cameron, Alexander D; Henderson, Peter JF

2014-01-01

The hydantoin transporter Mhp1 is a sodium-coupled secondary active transport protein of the nucleobase-cation-symport family and a member of the widespread 5-helix inverted repeat superfamily of transporters. The structure of Mhp1 was previously solved in three different conformations providing insight into the molecular basis of the alternating access mechanism. Here, we elucidate detailed events of substrate binding, through a combination of crystallography, molecular dynamics, site-directed mutagenesis, biochemical/biophysical assays, and the design and synthesis of novel ligands. We show precisely where 5-substituted hydantoin substrates bind in an extended configuration at the interface of the bundle and hash domains. They are recognised through hydrogen bonds to the hydantoin moiety and the complementarity of the 5-substituent for a hydrophobic pocket in the protein. Furthermore, we describe a novel structure of an intermediate state of the protein with the external thin gate locked open by an inhibitor, 5-(2-naphthylmethyl)-L-hydantoin, which becomes a substrate when leucine 363 is changed to an alanine. We deduce the molecular events that underlie acquisition and transport of a ligand by Mhp1. PMID:24952894

Fluorescence and room temperature phosphorescence of 6-bromo-2-naphthol in {beta}-cyclodextrin solution and its selective molecular recognition for cyclohexane

Energy Technology Data Exchange (ETDEWEB)

Zhai Yanqiang; Zhang Shuzhen; Xie Jianwei; Liu Changsong

2003-10-08

The room temperature phosphorescence (RTP) and fluorescence behavior of 6-bromo-2-naphthol (BN) in water and {beta}-cyclodextrin ({beta}-CD) aerated aqueous solution was investigated. The study of fluorescence behavior at different pH values indicated that three kinds of species of BN (protonated, uncharged and anionic species) formed 1:1 inclusion complexes with {beta}-CD, and RTP and fluorescence emission depended on the pH of the solution. The inclusion complex constants were 430{+-}25 l mol{sup -1} (pH 1.80), 840{+-}25 l mol{sup -1} (pH 5.80), 1850{+-}75 l mol{sup -1} (pH 11.50), respectively. Experimental results elucidated that RTP of the BN/{beta}-CD/cyclohexane solution came from the protonated and uncharged species of BN, but not from the anionic species, though the inclusion constant of the anionic species of BN with {beta}-CD was larger than that of the other two species of BN Selective molecular recognition of BN/{beta}-CD as an RTP sensor for 28 small organic molecules was studied, it was shown that BN/{beta}-CD could be develop as a new RTP sensor with high selectivity molecular recognition ability for cyclohexane.

Fluorescence and room temperature phosphorescence of 6-bromo-2-naphthol in β-cyclodextrin solution and its selective molecular recognition for cyclohexane

International Nuclear Information System (INIS)

Zhai Yanqiang; Zhang Shuzhen; Xie Jianwei; Liu Changsong

2003-01-01

The room temperature phosphorescence (RTP) and fluorescence behavior of 6-bromo-2-naphthol (BN) in water and β-cyclodextrin (β-CD) aerated aqueous solution was investigated. The study of fluorescence behavior at different pH values indicated that three kinds of species of BN (protonated, uncharged and anionic species) formed 1:1 inclusion complexes with β-CD, and RTP and fluorescence emission depended on the pH of the solution. The inclusion complex constants were 430±25 l mol -1 (pH 1.80), 840±25 l mol -1 (pH 5.80), 1850±75 l mol -1 (pH 11.50), respectively. Experimental results elucidated that RTP of the BN/β-CD/cyclohexane solution came from the protonated and uncharged species of BN, but not from the anionic species, though the inclusion constant of the anionic species of BN with β-CD was larger than that of the other two species of BN Selective molecular recognition of BN/β-CD as an RTP sensor for 28 small organic molecules was studied, it was shown that BN/β-CD could be develop as a new RTP sensor with high selectivity molecular recognition ability for cyclohexane

Tragacanth gum-based nanogel as a superparamagnetic molecularly imprinted polymer for quercetin recognition and controlled release.

Science.gov (United States)

Hemmati, Khadijeh; Masoumi, Arameh; Ghaemy, Mousa

2016-01-20

A highly selective magnetic molecularly imprinted polymer (MMIP) with core-shell structure has been synthesized by a sol-gel process composed of Tragacanth Gum (TG) crosslinker, Fe3O4/SiO2 nanoparticles, and N-vinyl imidazole(VI) functional monomer in the presence of template Quercetin (QC). Different techniques including scanning electron microscopy (SEM), SEM-energy dispersive spectroscopy (SEM-EDS), vibrating sample magnetometer (VSM), and transmission electron microscopy (TEM) were used to verify the successful synthesis of MIP on the surface of Fe3O4/SiO2 nanoparticles. The swelling behavior of MMIP, its recognition and selectivity for QC and structural analog, Catechin (CT), were tested and compared with magnetic non imprinted polymer (MNIP). MMIP adsorbs the template drug quickly and equilibrium could be reached in 2h. The mechanism for adsorption was found to follow the Langmuir model with the maximum capacity of 175.43 mg g(-1). The MMIP indicated excellent recognition and binding affinity toward QC, selectivity factor (ɛ) relative to CT was 2.16. Finally, the MMIP was evaluated as a drug delivery device by performing in vitro release studies in PBS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural activity during emotion recognition after combined cognitive plus social-cognitive training in schizophrenia

Science.gov (United States)

Hooker, Christine I.; Bruce, Lori; Fisher, Melissa; Verosky, Sara C.; Miyakawa, Asako; Vinogradov, Sophia

2012-01-01

Cognitive remediation training has been shown to improve both cognitive and social-cognitive deficits in people with schizophrenia, but the mechanisms that support this behavioral improvement are largely unknown. One hypothesis is that intensive behavioral training in cognition and/or social-cognition restores the underlying neural mechanisms that support targeted skills. However, there is little research on the neural effects of cognitive remediation training. This study investigated whether a 50 hour (10-week) remediation intervention which included both cognitive and social-cognitive training would influence neural function in regions that support social-cognition. Twenty-two stable, outpatient schizophrenia participants were randomized to a treatment condition consisting of auditory-based cognitive training (AT) [Brain Fitness Program/auditory module ~60 minutes/day] plus social-cognition training (SCT) which was focused on emotion recognition [~5–15 minutes per day] or a placebo condition of non-specific computer games (CG) for an equal amount of time. Pre and post intervention assessments included an fMRI task of positive and negative facial emotion recognition, and standard behavioral assessments of cognition, emotion processing, and functional outcome. There were no significant intervention-related improvements in general cognition or functional outcome. FMRI results showed the predicted group-by-time interaction. Specifically, in comparison to CG, AT+SCT participants had a greater pre-to-post intervention increase in postcentral gyrus activity during emotion recognition of both positive and negative emotions. Furthermore, among all participants, the increase in postcentral gyrus activity predicted behavioral improvement on a standardized test of emotion processing (MSCEIT: Perceiving Emotions). Results indicate that combined cognition and social-cognition training impacts neural mechanisms that support social-cognition skills. PMID:22695257

Nanosilica-based molecularly imprinted polymer nanoshell for specific recognition and determination of rhodamine B in red wine and beverages.

Science.gov (United States)

Long, Zerong; Xu, Weiwei; Lu, Yi; Qiu, Hongdeng

2016-09-01

A new and facile rhodamine B (RhB)-imprinted polymer nanoshell coating for SiO2 nanoparticles was readily prepared by a combination of silica gel modification and molecular surface imprinting. The RhB-imprinted polymers (RhB-MIPs) were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and UV-vis spectroscopy; the binding properties and selectivity of these MIPs were investigated in detail. The uniformly imprinted nanoparticles displayed a rather thin shell thickness (23nm) with highly effective recognition sites, showing homogenous distribution and monolayer adsorption. The maximum MIP adsorption capacity (Qm) was as high as 45.2mgg(-1), with an adsorption equilibrium time of about 15min at ambient temperature. Dynamic rebinding experiments showed that chemical adsorption is crucial for RhB binding to RhB-MIPs. The adsorption isotherm for RhB-MIPs binding could also be described by the Langmuir equation at different temperatures and pH values. Increasing temperature led to an enhanced Qm, a decreased dissociation constant (K'd), and a more negative free energy (ΔG), indicating that adsorption is favored at higher temperatures. Moreover, the adsorption capacity of RhB was remarkably affected by pH. At pH>7, the adsorption of RhB was driven by hydrogen bonding interactions, while at pH<7 electrostatic forces were dominant. Additionally, the MIPs also showed specific recognition of RhB from the standard mixture solution containing five structurally analogs. This method was also successfully employed to determine RhB content in red wine and beverages using three levels of spiking, with recoveries in the range of 91.6-93.1% and relative standard deviations lower than 4.1%. Copyright © 2016 Elsevier B.V. All rights reserved.

Machine learning and pattern recognition from surface molecular architectures.

Science.gov (United States)

Maksov, Artem; Ziatdinov, Maxim; Fujii, Shintaro; Sumpter, Bobby; Kalinin, Sergei

The ability to utilize molecular assemblies as data storage devices requires capability to identify individual molecular states on a scale of thousands of molecules. We present a novel method of applying machine learning techniques for extraction of positional and rotational information from ultra-high vacuum scanning tunneling microscopy (STM) images and apply it to self-assembled monolayer of π-bowl sumanene molecules on gold. From density functional theory (DFT) simulations, we assume existence of distinct polar and multiple azimuthal rotational states. We use DFT-generated templates in conjunction with Markov Chain Monte Carlo (MCMC) sampler and noise modeling to create synthetic images representative of our model. We extract positional information of each molecule and use nearest neighbor criteria to construct a graph input to Markov Random Field (MRF) model to identify polar rotational states. We train a convolutional Neural Network (cNN) on a synthetic dataset and combine it with MRF model to classify molecules based on their azimuthal rotational state. We demonstrate effectiveness of such approach compared to other methods. Finally, we apply our approach to experimental images and achieve complete rotational class information extraction. This research was sponsored by the Division of Materials Sciences and Engineering, Office of Science, Basic Energy Sciences, US DOE.

Combining Radiation Epidemiology With Molecular Biology-Changing From Health Risk Estimates to Therapeutic Intervention.

Science.gov (United States)

Abend, Michael; Port, Matthias

2016-08-01

The authors herein summarize six presentations dedicated to the key session "molecular radiation epidemiology" of the ConRad meeting 2015. These presentations were chosen in order to highlight the promise when combining conventional radiation epidemiology with molecular biology. Conventional radiation epidemiology uses dose estimates for risk predictions on health. However, combined with molecular biology, dose-dependent bioindicators of effect hold the promise to improve clinical diagnostics and to provide target molecules for potential therapeutic intervention. One out of the six presentations exemplified the use of radiation-induced molecular changes as biomarkers of exposure by measuring stabile chromosomal translocations. The remaining five presentations focused on molecular changes used as bioindicators of the effect. These bioindicators of the effect could be used for diagnostic purposes on colon cancers (genomic instability), thyroid cancer (CLIP2), or head and neck squamous cell cancers. Therapeutic implications of gene expression changes were examined in Chernobyl thyroid cancer victims and Mayak workers.

Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN

Science.gov (United States)

Zhu, Lianzhang; Chen, Leiming; Zhao, Dehai

2017-01-01

Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emotion classification methods. Five types of features are extracted from a speech sample: mel frequency cepstrum coefficient (MFCC), pitch, formant, short-term zero-crossing rate and short-term energy. By comparing statistical features with deep features extracted by a Deep Belief Network (DBN), we attempt to find the best features to identify the emotion status for speech. We propose a novel classification method that combines DBN and SVM (support vector machine) instead of using only one of them. In addition, a conjugate gradient method is applied to train DBN in order to speed up the training process. Gender-dependent experiments are conducted using an emotional speech database created by the Chinese Academy of Sciences. The results show that DBN features can reflect emotion status better than artificial features, and our new classification approach achieves an accuracy of 95.8%, which is higher than using either DBN or SVM separately. Results also show that DBN can work very well for small training databases if it is properly designed. PMID:28737705

Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN.

Science.gov (United States)

Zhu, Lianzhang; Chen, Leiming; Zhao, Dehai; Zhou, Jiehan; Zhang, Weishan

2017-07-24

Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emotion classification methods. Five types of features are extracted from a speech sample: mel frequency cepstrum coefficient (MFCC), pitch, formant, short-term zero-crossing rate and short-term energy. By comparing statistical features with deep features extracted by a Deep Belief Network (DBN), we attempt to find the best features to identify the emotion status for speech. We propose a novel classification method that combines DBN and SVM (support vector machine) instead of using only one of them. In addition, a conjugate gradient method is applied to train DBN in order to speed up the training process. Gender-dependent experiments are conducted using an emotional speech database created by the Chinese Academy of Sciences. The results show that DBN features can reflect emotion status better than artificial features, and our new classification approach achieves an accuracy of 95.8%, which is higher than using either DBN or SVM separately. Results also show that DBN can work very well for small training databases if it is properly designed.

Dereplication of depsides from the lichen Pseudevernia furfuracea by centrifugal partition chromatography combined to 13C nuclear magnetic resonance pattern recognition

International Nuclear Information System (INIS)

Oettl, Sarah K.; Hubert, Jane; Nuzillard, Jean-Marc; Stuppner, Hermann; Renault, Jean-Hugues; Rollinger, Judith M.

2014-01-01

Highlights: • The major depsides of a lichen extract were directly identified within mixtures. • The initial extract was rapidly fractionated by CPC in the pH-zone refining mode. • Hierarchical clustering of 13 C NMR signals resulted in the identification of depside molecular skeletons. • 13 C chemical shift clusters were assigned to structures using a 13 C NMR database. • Six depsides were unambiguously identified by this approach. - Abstract: Lichens produce a diversity of secondary metabolites, among them depsides comprised of two or more hydroxybenzoic acid units linked by ester, ether, or C-C-bonds. During classic solid support-based purification processes, depsides are often hydrolyzed and in many cases time, consuming procedures result only in the isolation of decomposition products. In an attempt to avoid extensive purification steps while maintaining metabolite structure integrity, we propose an alternative method to identify the major depsides of a lichen crude extract (Pseudevernia furfuracea var. ceratea (Ach.) D. Hawksw., Parmeliaceae) directly within mixtures. Exploiting the acidic character of depsides and differences in polarity, the extract was fractionated by centrifugal partition chromatography in the pH-zone refining mode resulting in twelve simplified mixtures of depsides. After 13 C nuclear magnetic resonance analysis of the produced fractions, the major molecular structures were directly identified within the fraction series by using a recently developed pattern recognition method, which combines spectral data alignment and hierarchical clustering analysis. The obtained clusters of 13 C chemical shifts were assigned to their corresponding molecular structures with the help of an in-house 13 C NMR chemical shift database, resulting in six unambiguously identified compounds, namely methyl β-orcinolcarboxylate (1), atranorin (2), 5-chloroatranorin (3), olivetol carboxylic acid (4), olivetoric acid (5), and olivetonide (6)

Molecular recognition of AT-DNA sequences by the induced CD pattern of dibenzotetraaza[14]annulene (DBTAA)–adenine derivatives

OpenAIRE

Stojković, Marijana Radić; Škugor, Marko; Dudek, Łukasz; Grolik, Jarosław; Eilmes, Julita; Piantanida, Ivo

2014-01-01

Summary An investigation of the interactions of two novel and several known DBTAA–adenine conjugates with double-stranded DNA and RNA has revealed the DNA/RNA groove as the dominant binding site, which is in contrast to the majority of previously studied DBTAA analogues (DNA/RNA intercalators). Only DBTAA–propyladenine conjugates revealed the molecular recognition of AT-DNA by an ICD band pattern > 300 nm, whereas significant ICD bands did not appear for other ds-DNA/RNA. A structure–activity...

Comparison of extraction chromatography and a procedure based on the molecular recognition method as separation methods in the determination of neptunium and plutonium radionuclides

International Nuclear Information System (INIS)

Strisovska, Jana; Galanda, Dusan; Drabova, Veronika; Kuruc, Jozef

2012-01-01

The potential of various types of sorbents for separation of radionuclides of plutonium and neptunium were examined. Extraction chromatography and a procedure based on the molecular recognition method were used for the separation. The suitability of the various sorbent types and brands for this purpose was determined. (orig.)

A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection.

NARCIS (Netherlands)

Luts, J.; Heerschap, A.; Suykens, J.A.; Huffel, S. van

2007-01-01

OBJECTIVE: This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brain tumours. Recently, the combined use of magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging

Computational modeling on the recognition of the HRE motif by HIF-1: molecular docking and molecular dynamics studies.

Science.gov (United States)

Sokkar, Pandian; Sathis, Vani; Ramachandran, Murugesan

2012-05-01

Hypoxia inducible factor-1 (HIF-1) is a bHLH-family transcription factor that controls genes involved in glycolysis, angiogenesis, migration, as well as invasion factors that are important for tumor progression and metastasis. HIF-1, a heterodimer of HIF-1α and HIF-1β, binds to the hypoxia responsive element (HRE) present in the promoter regions of hypoxia responsive genes, such as vascular endothelial growth factor (VEGF). Neither the structure of free HIF-1 nor that of its complex with HRE is available. Computational modeling of the transcription factor-DNA complex has always been challenging due to their inherent flexibility and large conformational space. The present study aims to model the interaction between the DNA-binding domain of HIF-1 and HRE. Experiments showed that rigid macromolecular docking programs (HEX and GRAMM-X) failed to predict the optimal dimerization of individually modeled HIF-1 subunits. Hence, the HIF-1 heterodimer was modeled based on the phosphate system positive regulatory protein (PHO4) homodimer. The duplex VEGF-DNA segment containing HRE with flanking nucleotides was modeled in the B form and equilibrated via molecular dynamics (MD) simulation. A rigid docking approach was used to predict the crude binding mode of HIF-1 dimer with HRE, in which the putative contacts were found to be present. An MD simulation (5 ns) of the HIF-1-HRE complex in explicit water was performed to account for its flexibility and to optimize its interactions. All of the conserved amino acid residues were found to play roles in the recognition of HRE. The present work, which sheds light on the recognition of HRE by HIF-1, could be beneficial in the design of peptide or small molecule therapeutics that can mimic HIF-1 and bind with the HRE sequence.

Human Gait Recognition Based on Multiview Gait Sequences

Directory of Open Access Journals (Sweden)

Xiaxi Huang

2008-05-01

Full Text Available Most of the existing gait recognition methods rely on a single view, usually the side view, of the walking person. This paper investigates the case in which several views are available for gait recognition. It is shown that each view has unequal discrimination power and, therefore, should have unequal contribution in the recognition process. In order to exploit the availability of multiple views, several methods for the combination of the results that are obtained from the individual views are tested and evaluated. A novel approach for the combination of the results from several views is also proposed based on the relative importance of each view. The proposed approach generates superior results, compared to those obtained by using individual views or by using multiple views that are combined using other combination methods.

Cognitive object recognition system (CORS)

Science.gov (United States)

Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

2010-04-01

We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

Container-code recognition system based on computer vision and deep neural networks

Science.gov (United States)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Medicinal plant phytochemicals and their inhibitory activities against pancreatic lipase: molecular docking combined with molecular dynamics simulation approach

OpenAIRE

Ahmed, Bilal; Ali Ashfaq, Usman; Mirza, Muhammad Usman

2017-01-01

Obesity is the worst health risk worldwide, which is linked to a number of diseases. Pancreatic lipase is considered as an affective cause of obesity and can be a major target for controlling the obesity. The present study was designed to find out best phytochemicals against pancreatic lipase through molecular docking combined with molecular dynamics (MD) simulation. For this purpose, a total of 3770 phytochemicals were docked against pancreatic lipase and ranked them on the basis of binding ...

A unified classifier for robust face recognition based on combining multiple subspace algorithms

Science.gov (United States)

Ijaz Bajwa, Usama; Ahmad Taj, Imtiaz; Waqas Anwar, Muhammad

2012-10-01

Face recognition being the fastest growing biometric technology has expanded manifold in the last few years. Various new algorithms and commercial systems have been proposed and developed. However, none of the proposed or developed algorithm is a complete solution because it may work very well on one set of images with say illumination changes but may not work properly on another set of image variations like expression variations. This study is motivated by the fact that any single classifier cannot claim to show generally better performance against all facial image variations. To overcome this shortcoming and achieve generality, combining several classifiers using various strategies has been studied extensively also incorporating the question of suitability of any classifier for this task. The study is based on the outcome of a comprehensive comparative analysis conducted on a combination of six subspace extraction algorithms and four distance metrics on three facial databases. The analysis leads to the selection of the most suitable classifiers which performs better on one task or the other. These classifiers are then combined together onto an ensemble classifier by two different strategies of weighted sum and re-ranking. The results of the ensemble classifier show that these strategies can be effectively used to construct a single classifier that can successfully handle varying facial image conditions of illumination, aging and facial expressions.

Neural activity during emotion recognition after combined cognitive plus social cognitive training in schizophrenia.

Science.gov (United States)

Hooker, Christine I; Bruce, Lori; Fisher, Melissa; Verosky, Sara C; Miyakawa, Asako; Vinogradov, Sophia

2012-08-01

Cognitive remediation training has been shown to improve both cognitive and social cognitive deficits in people with schizophrenia, but the mechanisms that support this behavioral improvement are largely unknown. One hypothesis is that intensive behavioral training in cognition and/or social cognition restores the underlying neural mechanisms that support targeted skills. However, there is little research on the neural effects of cognitive remediation training. This study investigated whether a 50 h (10-week) remediation intervention which included both cognitive and social cognitive training would influence neural function in regions that support social cognition. Twenty-two stable, outpatient schizophrenia participants were randomized to a treatment condition consisting of auditory-based cognitive training (AT) [Brain Fitness Program/auditory module ~60 min/day] plus social cognition training (SCT) which was focused on emotion recognition [~5-15 min per day] or a placebo condition of non-specific computer games (CG) for an equal amount of time. Pre and post intervention assessments included an fMRI task of positive and negative facial emotion recognition, and standard behavioral assessments of cognition, emotion processing, and functional outcome. There were no significant intervention-related improvements in general cognition or functional outcome. fMRI results showed the predicted group-by-time interaction. Specifically, in comparison to CG, AT+SCT participants had a greater pre-to-post intervention increase in postcentral gyrus activity during emotion recognition of both positive and negative emotions. Furthermore, among all participants, the increase in postcentral gyrus activity predicted behavioral improvement on a standardized test of emotion processing (MSCEIT: Perceiving Emotions). Results indicate that combined cognition and social cognition training impacts neural mechanisms that support social cognition skills. Copyright © 2012 Elsevier B.V. All

A Bayesian classifier for symbol recognition

OpenAIRE

Barrat , Sabine; Tabbone , Salvatore; Nourrissier , Patrick

2007-01-01

URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...

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

Science.gov (United States)

Štambuk, Nikola

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

Molecular insights into the specific recognition between the RNA binding domain qRRM2 of hnRNP F and G-tract RNA: A molecular dynamics study.

Science.gov (United States)

Wang, Lingyun; Yan, Feng

2017-12-09

Heterogeneous nuclear ribonucleoprotein F (hnRNP F) controls the expression of various genes through regulating the alternative splicing of pre-mRNAs in the nucleus. It uses three quasi-RNA recognition motifs (qRRMs) to recognize G-tract RNA which contains at least three consecutive guanines. The structures containing qRRMs of hnRNP F in complex with G-tract RNA have been determined by nuclear magnetic resonance (NMR) spectroscopy, shedding light on the recognition mechanism of qRRMs with G-tract RNA. However, knowledge of the recognition details is still lacking. To investigate how qRRMs specifically bind with G-tract RNA and how the mutations of any guanine to an adenine in the G-tract affect the binding, molecular dynamics simulations with binding free energy analysis were performed based on the NMR structure of qRRM2 in complex with G-tract RNA. Simulation results demonstrate that qRRM2 binds strongly with G-tract RNA, but any mutation of the G-tract leads to a drastic reduction of the binding free energy. Further comparisons of the energetic components reveal that van der Waals and non-polar interactions play essential roles in the binding between qRRM2 and G-tract RNA, but the interactions are weakened by the effect of RNA mutations. Structural and dynamical analyses indicate that when qRRM2 binds with G-tract RNA, both qRRM2 and G-tract maintain stabilized structures and dynamics; however, the stability is disrupted by the mutations of the G-tract. These results provide novel insights into the recognition mechanism of qRRM2 with G-tract RNA that are not elucidated by the NMR technique. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification and characterization of tebuconazole transformation products in soil by combining suspect screening and molecular typology

International Nuclear Information System (INIS)

Storck, Veronika; Lucini, Luigi; Mamy, Laure; Ferrari, Federico; Papadopoulou, Evangelia S.; Nikolaki, Sofia; Karas, Panagiotis A.; Servien, Remi; Karpouzas, Dimitrios G.; Trevisan, Marco; Benoit, Pierre; Martin-Laurent, Fabrice

2016-01-01

Pesticides generate transformation products (TPs) when they are released into the environment. These TPs may be of ecotoxicological importance. Past studies have demonstrated how difficult it is to predict the occurrence of pesticide TPs and their environmental risk. The monitoring approaches mostly used in current regulatory frameworks target only known ecotoxicologically relevant TPs. Here, we present a novel combined approach which identifies and categorizes known and unknown pesticide TPs in soil by combining suspect screening time-of-flight mass spectrometry with in silico molecular typology. We used an empirical and theoretical pesticide TP library for compound identification by both non-target and target time-of-flight (tandem) mass spectrometry, followed by structural proposition through a molecular structure correlation program. In silico molecular typology was then used to group TPs according to common molecular descriptors and to indirectly elucidate their environmental parameters by analogy to known pesticide compounds with similar molecular descriptors. This approach was evaluated via the identification of TPs of the triazole fungicide tebuconazole occurring in soil during a field dissipation study. Overall, 22 empirical and 12 yet unknown TPs were detected, and categorized into three groups with defined environmental properties. This approach combining suspect screening time-of-flight mass spectrometry with molecular typology could be extended to other organic pollutants and used to rationalize the choice of TPs to be investigated towards a more comprehensive environmental risk assessment scheme. - Highlights: • Combined method to detect and categorize pesticide transformation products in soil. • Detection by QTOF-MS of new tebuconazole transformation products without standards. • Estimation by in silico molecular typology of their environmental parameters. • Method to rationally choose relevant transformation products to be studied. • The

Voice Recognition in Face-Blind Patients

Science.gov (United States)

Liu, Ran R.; Pancaroglu, Raika; Hills, Charlotte S.; Duchaine, Brad; Barton, Jason J. S.

2016-01-01

Right or bilateral anterior temporal damage can impair face recognition, but whether this is an associative variant of prosopagnosia or part of a multimodal disorder of person recognition is an unsettled question, with implications for cognitive and neuroanatomic models of person recognition. We assessed voice perception and short-term recognition of recently heard voices in 10 subjects with impaired face recognition acquired after cerebral lesions. All 4 subjects with apperceptive prosopagnosia due to lesions limited to fusiform cortex had intact voice discrimination and recognition. One subject with bilateral fusiform and anterior temporal lesions had a combined apperceptive prosopagnosia and apperceptive phonagnosia, the first such described case. Deficits indicating a multimodal syndrome of person recognition were found only in 2 subjects with bilateral anterior temporal lesions. All 3 subjects with right anterior temporal lesions had normal voice perception and recognition, 2 of whom performed normally on perceptual discrimination of faces. This confirms that such lesions can cause a modality-specific associative prosopagnosia. PMID:25349193

Forensic speaker recognition

NARCIS (Netherlands)

Meuwly, Didier

2013-01-01

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

Dereplication of depsides from the lichen Pseudevernia furfuracea by centrifugal partition chromatography combined to {sup 13}C nuclear magnetic resonance pattern recognition

Energy Technology Data Exchange (ETDEWEB)

Oettl, Sarah K. [Institute of Pharmacy/Pharmacognosy, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innrain 80–82, 6020 Innsbruck (Austria); Hubert, Jane, E-mail: jane.hubert@univ-reims.fr [Institut de Chimie Moléculaire de Reims (UMR CNRS 7312), SFR CAP' sANTE, UFR de Pharmacie, Université de Reims Champagne-Ardenne, BP 1039, 51687 Reims Cedex 2 (France); Nuzillard, Jean-Marc [Institut de Chimie Moléculaire de Reims (UMR CNRS 7312), SFR CAP' sANTE, UFR de Pharmacie, Université de Reims Champagne-Ardenne, BP 1039, 51687 Reims Cedex 2 (France); Stuppner, Hermann [Institute of Pharmacy/Pharmacognosy, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innrain 80–82, 6020 Innsbruck (Austria); Renault, Jean-Hugues [Institut de Chimie Moléculaire de Reims (UMR CNRS 7312), SFR CAP' sANTE, UFR de Pharmacie, Université de Reims Champagne-Ardenne, BP 1039, 51687 Reims Cedex 2 (France); Rollinger, Judith M. [Institute of Pharmacy/Pharmacognosy, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innrain 80–82, 6020 Innsbruck (Austria)

2014-10-10

Highlights: • The major depsides of a lichen extract were directly identified within mixtures. • The initial extract was rapidly fractionated by CPC in the pH-zone refining mode. • Hierarchical clustering of {sup 13}C NMR signals resulted in the identification of depside molecular skeletons. • {sup 13}C chemical shift clusters were assigned to structures using a {sup 13}C NMR database. • Six depsides were unambiguously identified by this approach. - Abstract: Lichens produce a diversity of secondary metabolites, among them depsides comprised of two or more hydroxybenzoic acid units linked by ester, ether, or C-C-bonds. During classic solid support-based purification processes, depsides are often hydrolyzed and in many cases time, consuming procedures result only in the isolation of decomposition products. In an attempt to avoid extensive purification steps while maintaining metabolite structure integrity, we propose an alternative method to identify the major depsides of a lichen crude extract (Pseudevernia furfuracea var. ceratea (Ach.) D. Hawksw., Parmeliaceae) directly within mixtures. Exploiting the acidic character of depsides and differences in polarity, the extract was fractionated by centrifugal partition chromatography in the pH-zone refining mode resulting in twelve simplified mixtures of depsides. After {sup 13}C nuclear magnetic resonance analysis of the produced fractions, the major molecular structures were directly identified within the fraction series by using a recently developed pattern recognition method, which combines spectral data alignment and hierarchical clustering analysis. The obtained clusters of {sup 13}C chemical shifts were assigned to their corresponding molecular structures with the help of an in-house {sup 13}C NMR chemical shift database, resulting in six unambiguously identified compounds, namely methyl β-orcinolcarboxylate (1), atranorin (2), 5-chloroatranorin (3), olivetol carboxylic acid (4), olivetoric acid (5

Effective Use of Molecular Recognition in Gas Sensing: Results from Acoustic Wave and In-Situ FTIR Measurements

Energy Technology Data Exchange (ETDEWEB)

Bodenhofer, K,; Gopel, W.; Hierlemann, A.; Ricco, A.J.

1998-12-09

To probe directly the analyte/film interactions that characterize molecular recognition in gas sensors, we recorded changes to the in-situ surface vibrational spectra of specifically fictionalized surface acoustic wave (SAW) devices concurrently with analyte exposure and SAW measurement of the extent of sorption. Fourier-lmnsform infrared external- reflectance spectra (FTIR-ERS) were collected from operating 97-MH2 SAW delay lines during exposure to a range of analytes as they interacted with thin-film coatings previously shown to be selective: cyclodextrins for chiral recognition, Ni-camphorates for Lewis bases such as pyridine and organophosphonates, and phthalocyanines for aromatic compounds. In most cases where specific chemical interactions-metal coordination, "cage" compound inclusion, or z stacking-were expected, analyte dosing caused distinctive changes in the IR spectr~ together with anomalously large SAW sensor responses. In contrast, control experiments involving the physisorption of the same analytes by conventional organic polymers did not cause similar changes in the IR spectra, and the SAW responses were smaller. For a given conventional polymer, the partition coefficients (or SAW sensor signals) roughly followed the analyte fraction of saturation vapor pressure. These SAW/FTIR results support earlier conclusions derived from thickness-shear mode resonator data.

Rapid determination of 239Pu in urine samples using molecular recognition technology product AnaLigRPu-02 gel

International Nuclear Information System (INIS)

Silvia Dulanska; Boris Remenec; Jan Bilohuscin; Miroslav Labaska; Bianka Horvathova; Andrej Matel

2013-01-01

This paper describes the use of IBC's AnaLig R Pu-02 molecular recognition technology product to effectively and selectively pre-concentrate, separate and recover plutonium from urine samples. This method uses two-stage column separations consisting of two different commercial products, Eichrom's Pre-filter Material and AnaLig R Pu-02 resin from IBC Advanced Technologies. By eliminating the co-precipitation techniques and the ashing steps to remove residual organics, the analysis time was reduced significantly. The method was successfully tested by adding known activities of reference solutions of 242 Pu and 239 Pu to urine samples. (author)

Self-oriented nanoparticles for site-selective immunoglobulin G recognition via epitope imprinting approach.

Science.gov (United States)

Çorman, Mehmet Emin; Armutcu, Canan; Uzun, Lokman; Say, Rıdvan; Denizli, Adil

2014-11-01

Molecular imprinting is a polymerization technique that provides synthetic analogs for template molecules. Molecularly imprinted polymers (MIPs) have gained much attention due to their unique properties such as selectivity and specificity for target molecules. In this study, we focused on the development of polymeric materials with molecular recognition ability, so molecular imprinting was combined with miniemulsion polymerization to synthesize self-orienting nanoparticles through the use of an epitope imprinting approach. Thus, L-lysine imprinted nanoparticles (LMIP) were synthesized via miniemulsion polymerization technique. Immunoglobulin G (IgG) was then bound to the cavities that specifically formed for L-lysine molecules that are typically found at the C-terminus of the Fc region of antibody molecules. The resulting nanoparticles makes it possible to minimize the nonspecific interaction between monomer and template molecules. In addition, the orientation of the entire IgG molecule was controlled, and random imprinting of the IgG was prevented. The optimum conditions were determined for IgG recognition using the imprinted nanoparticles. The selectivity of the nanoparticles against IgG molecules was also evaluated using albumin and hemoglobin as competitor molecules. In order to show the self-orientation capability of imprinted nanoparticles, human serum albumin (HSA) adsorption onto both the plain nanoparticles and immobilized nanoparticles by anti-human serum albumin antibody (anti-HSA antibody) was also carried out. Due to anti-HSA antibody immobilization on the imprinted nanoparticles, the adsorption capability of nanoparticles against HSA molecules vigorously enhanced. It is proved that the oriented immobilization of antibodies was appropriately succeeded. Copyright © 2014 Elsevier B.V. All rights reserved.

Magnetic nanoparticles in fluid environment: combining molecular dynamics and Lattice-Boltzmann

Energy Technology Data Exchange (ETDEWEB)

Melenev, Petr, E-mail: melenev@icmm.ru [Ural Federal University, 4, Turgeneva str., 620000 Ekaterinburg (Russian Federation); Institute of Continuous Media Mechanics, 1, Koroleva str., 614013 Perm (Russian Federation)

2017-06-01

Hydrodynamic interactions between magnetic nanoparticles suspended in the Newtonian liquid are accounted for using a combination of the lattice Boltzmann method and molecular dynamics simulations. Nanoparticle is modelled by the system of molecular dynamics material points (which form structure resembles raspberry) coupled to the lattice Boltzmann fluid. The hydrodynamic coupling between the colloids is studied by simulations of the thermo-induced rotational diffusion of two raspberry objects. It was found that for the considered range of model parameters the approaching of the raspberries leads to slight retard of the relaxation process. The presence of the weak magnetic dipolar interaction between the objects leads to modest decrease of the relaxation time and the extent of the acceleration of the diffusion is intensified along with magnetic forces. - Highlights: • The combination of molecular dynamics and lattice Boltzmann method is utilized for the reveal of the role of hydrodynamic interaction in rotational dynamics of colloid particles. • The verification of the model parameters is done based on the comparison with the results of Langevin dynamics. • For the task of free rotational diffusion of the pair of colloid particles the influence of the hydrodynamic interactions on the relaxation time is examined in the case of nonmagnetic particles and at the presence of weak dipolar interaction.

Improved RGB-D-T based Face Recognition

DEFF Research Database (Denmark)

Oliu Simon, Marc; Corneanu, Ciprian; Nasrollahi, Kamal

2016-01-01

years. At the same time a multimodal facial recognition is a promising approach. This paper combines the latest successes in both directions by applying deep learning Convolutional Neural Networks (CNN) to the multimodal RGB-D-T based facial recognition problem outperforming previously published results......Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent...

Molecular recognition of DNA-protein complexes: A straightforward method combining scanning force and fluorescence microscopy

NARCIS (Netherlands)

H. Sanchez (Humberto); R. Kanaar (Roland); C. Wyman (Claire)

2010-01-01

textabstractCombining scanning force and fluorescent microscopy allows simultaneous identification of labeled biomolecules and analysis of their nanometer level architectural arrangement. Fluorescent polystyrene nano-spheres were used as reliable objects for alignment of optical and topographic

Creating molecular macrocycles for anion recognition

Directory of Open Access Journals (Sweden)

Amar H. Flood

2016-03-01

Full Text Available The creation and functionality of new classes of macrocycles that are shape persistent and can bind anions is described. The genesis of triazolophane macrocycles emerges out of activity surrounding 1,2,3-triazoles made using click chemistry; and the same triazoles are responsible for anion capture. Mistakes made and lessons learnt in anion recognition provide deeper understanding that, together with theory, now provides for computer-aided receptor design. The lessons are acted upon in the creation of two new macrocycles. First, cyanostars are larger and like to capture large anions. Second is tricarb, which also favors large anions but shows a propensity to self-assemble in an orderly and stable manner, laying a foundation for future designs of hierarchical nanostructures.

A new method for incoherent combining of far-field laser beams based on multiple faculae recognition

Science.gov (United States)

Ye, Demao; Li, Sichao; Yan, Zhihui; Zhang, Zenan; Liu, Yuan

2018-03-01

Compared to coherent beam combining, incoherent beam combining can complete the output of high power laser beam with high efficiency, simple structure, low cost and high thermal damage resistance, and it is easy to realize in engineering. Higher target power is achieved by incoherent beam combination which using technology of multi-channel optical path correction. However, each channel forms a spot in the far field respectively, which cannot form higher laser power density with low overlap ratio of faculae. In order to improve the combat effectiveness of the system, it is necessary to overlap different faculae that improve the target energy density. Hence, a novel method for incoherent combining of far-field laser beams is present. The method compromises piezoelectric ceramic technology and evaluation algorithm of faculae coincidence degree which based on high precision multi-channel optical path correction. The results show that the faculae recognition algorithm is low-latency(less than 10ms), which can meet the needs of practical engineering. Furthermore, the real time focusing ability of far field faculae is improved which was beneficial to the engineering of high-energy laser weapon or other laser jamming systems.

The processing of auditory and visual recognition of self-stimuli.

Science.gov (United States)

Hughes, Susan M; Nicholson, Shevon E

2010-12-01

This study examined self-recognition processing in both the auditory and visual modalities by determining how comparable hearing a recording of one's own voice was to seeing photograph of one's own face. We also investigated whether the simultaneous presentation of auditory and visual self-stimuli would either facilitate or inhibit self-identification. Ninety-one participants completed reaction-time tasks of self-recognition when presented with their own faces, own voices, and combinations of the two. Reaction time and errors made when responding with both the right and left hand were recorded to determine if there were lateralization effects on these tasks. Our findings showed that visual self-recognition for facial photographs appears to be superior to auditory self-recognition for voice recordings. Furthermore, a combined presentation of one's own face and voice appeared to inhibit rather than facilitate self-recognition and there was a left-hand advantage for reaction time on the combined-presentation tasks. Copyright © 2010 Elsevier Inc. All rights reserved.

Structure of the mouse galectin-4 N-terminal carbohydrate-recognition domain reveals the mechanism of oligosaccharide recognition

Czech Academy of Sciences Publication Activity Database

Krejčiříková, Veronika; Pachl, Petr; Fábry, Milan; Malý, Petr; Řezáčová, Pavlína; Brynda, Jiří

2011-01-01

Roč. 67, Pt3 (2011), 204-211 ISSN 0907-4449 R&D Projects: GA ČR GA203/09/0820; GA ČR GA304/03/0090; GA ČR GA301/07/0600 Institutional research plan: CEZ:AV0Z50520514; CEZ:AV0Z50520701; CEZ:AV0Z40550506 Keywords : S-type lectins * carbohydrate binding * molecular recognition Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 12.619, year: 2011

Nanomedicine-based combination anticancer therapy between nucleic acids and small-molecular drugs.

Science.gov (United States)

Huang, Wei; Chen, Liqing; Kang, Lin; Jin, Mingji; Sun, Ping; Xin, Xin; Gao, Zhonggao; Bae, You Han

2017-06-01

Anticancer therapy has always been a vital challenge for the development of nanomedicine. Repeated single therapeutic agent may lead to undesirable and severe side effects, unbearable toxicity and multidrug resistance due to complex nature of tumor. Nanomedicine-based combination anticancer therapy can synergistically improve antitumor outcomes through multiple-target therapy, decreasing the dose of each therapeutic agent and reducing side effects. There are versatile combinational anticancer strategies such as chemotherapeutic combination, nucleic acid-based co-delivery, intrinsic sensitive and extrinsic stimulus combinational patterns. Based on these combination strategies, various nanocarriers and drug delivery systems were engineered to carry out the efficient co-delivery of combined therapeutic agents for combination anticancer therapy. This review focused on illustrating nanomedicine-based combination anticancer therapy between nucleic acids and small-molecular drugs for synergistically improving anticancer efficacy. Copyright © 2017 Elsevier B.V. All rights reserved.

Engineering of an Extremely Thermostable Alpha/Beta Barrel Scaffold to Serve as a High Affinity Molecular Recognition Element for Use in Sensor Applications

Science.gov (United States)

2015-12-23

Molecular Recognition Element For Use in Sensor Applications Report Title The overall goal of the project was to evolve a highly thermostable enzyme ( alcohol ...SECURITY CLASSIFICATION OF: The overall goal of the project was to evolve a highly thermostable enzyme ( alcohol dehydrogenase D (AdhD) from Pyrococcus...furiosus) to bind an explosive molecule, RDX. The enzyme naturally catalyzes the nicotinamide cofactor-dependent oxidation or reduction of alcohols

Application of Machine Learning tools to recognition of molecular patterns in STM images

Science.gov (United States)

Maksov, Artem; Ziatdinov, Maxim; Fujii, Shintaro; Kiguchi, Manabu; Higashibayashi, Shuhei; Sakurai, Hidehiro; Kalinin, Sergei; Sumpter, Bobby

The ability to utilize individual molecules and molecular assemblies as data storage elements has motivated scientist for years, concurrent with the continuous effort to shrink a size of data storage devices in microelectronics industry. One of the critical issues in this effort lies in being able to identify individual molecular assembly units (patterns), on a large scale in an automated fashion of complete information extraction. Here we present a novel method of applying machine learning techniques for extraction of positional and rotational information from scanning tunneling microscopy (STM) images of π-bowl sumanene molecules on gold. We use Markov Random Field (MRF) model to decode the polar rotational states for each molecule in a large scale STM image of molecular film. We further develop an algorithm that uses a convolutional Neural Network combined with MRF and input from density functional theory to classify molecules into different azimuthal rotational classes. Our results demonstrate that a molecular film is partitioned into distinctive azimuthal rotational domains consisting typically of 20-30 molecules. In each domain, the ``bowl-down'' molecules are generally surrounded by six nearest neighbor molecules in ``bowl-up'' configuration, and the resultant overall structure form a periodic lattice of rotational and polar states within each domain. Research was supported by the US Department of Energy.

Exploring the molecular basis of dsRNA recognition by NS1 protein of influenza A virus using molecular dynamics simulation and free energy calculation.

Science.gov (United States)

Pan, Dabo; Sun, Huijun; Shen, Yulin; Liu, Huanxiang; Yao, Xiaojun

2011-12-01

The frequent outbreak of influenza pandemic and the limited available anti-influenza drugs highlight the urgent need for the development of new antiviral drugs. The dsRNA-binding surface of nonstructural protein 1 of influenza A virus (NS1A) is a promising target. The detailed understanding of NS1A-dsRNA interaction will be valuable for structure-based anti-influenza drug discovery. To characterize and explore the key interaction features between dsRNA and NS1A, molecular dynamics simulation combined with MM-GBSA calculations were performed. Based on the MM-GBSA calculations, we find that the intermolecular van der Waals interaction and the nonpolar solvation term provide the main driving force for the binding process. Meanwhile, 17 key residues from NS1A were identified to be responsible for the dsRNA binding. Compared with the wild type NS1A, all the studied mutants S42A, T49A, R38A, R35AR46A have obvious reduced binding free energies with dsRNA reflecting in the reduction of the polar and/or nonpolar interactions. In addition, the structural and energy analysis indicate the mutations have a small effect to the backbone structures but the loss of side chain interactions is responsible for the decrease of the binding affinity. The uncovering of NS1A-dsRNA recognition mechanism will provide some useful insights and new chances for the development of anti-influenza drugs. Copyright © 2011 Elsevier B.V. All rights reserved.

Label-Free Bioanalyte Detection from Nanometer to Micrometer Dimensions—Molecular Imprinting and QCMs †

Directory of Open Access Journals (Sweden)

Adnan Mujahid

2018-06-01

Full Text Available Modern diagnostic tools and immunoassay protocols urges direct analyte recognition based on its intrinsic behavior without using any labeling indicator. This not only improves the detection reliability, but also reduces sample preparation time and complexity involved during labeling step. Label-free biosensor devices are capable of monitoring analyte physiochemical properties such as binding sensitivity and selectivity, affinity constants and other dynamics of molecular recognition. The interface of a typical biosensor could range from natural antibodies to synthetic receptors for example molecular imprinted polymers (MIPs. The foremost advantages of using MIPs are their high binding selectivity comparable to natural antibodies, straightforward synthesis in short time, high thermal/chemical stability and compatibility with different transducers. Quartz crystal microbalance (QCM resonators are leading acoustic devices that are extensively used for mass-sensitive measurements. Highlight features of QCM devices include low cost fabrication, room temperature operation, and most importantly ability to monitor extremely low mass shifts, thus potentially a universal transducer. The combination of MIPs with quartz QCM has turned out as a prominent sensing system for label-free recognition of diverse bioanalytes. In this article, we shall encompass the potential applications of MIP-QCM sensors exclusively label-free recognition of bacteria and virus species as representative micro and nanosized bioanalytes.

Helicase Dependent Isothermal Amplification of DNA and RNA using Self-Avoiding Molecular Recognition Systems

Science.gov (United States)

Yang, Zunyi; McLendon, Chris; Hutter, Daniel; Bradley, Kevin M.; Hoshika, Shuichi; Frye, Carole; Benner, Steven A.

2015-01-01

Assays that target DNA or RNA (xNA) are highly sensitive, as small amounts of xNA can be amplified by PCR. Unfortunately, PCR is inconvenient in low resource environments, requiring equipment and power that may not be available in these environments. However, isothermal procedures that avoid thermal cycling are often confounded by primer dimers, off-target priming, and other artifacts. Here, we show how a “self avoiding molecular recognition system” (SAMRS) eliminates these artifacts to give clean amplicons in a helicase-dependent isothermal amplification (SAMRS-HDA). We also show that incorporating SAMRS into the 3′-ends of primers facilitates the design and screening of primers for HDA assays. Finally, we show that SAMRS-HDA can be twofold multiplexed, something difficult to achieve with HDA using standard primers. This shows that SAMRS-HDA is a more versatile approach than standard HDA with a broader applicability for xNA-targeted diagnostics and research. PMID:25953623

Molecularly Imprinted Polymers: Present and Future Prospective

Directory of Open Access Journals (Sweden)

Giuseppe Vasapollo

2011-09-01

Full Text Available Molecular Imprinting Technology (MIT is a technique to design artificial receptors with a predetermined selectivity and specificity for a given analyte, which can be used as ideal materials in various application fields. Molecularly Imprinted Polymers (MIPs, the polymeric matrices obtained using the imprinting technology, are robust molecular recognition elements able to mimic natural recognition entities, such as antibodies and biological receptors, useful to separate and analyze complicated samples such as biological fluids and environmental samples. The scope of this review is to provide a general overview on MIPs field discussing first general aspects in MIP preparation and then dealing with various application aspects. This review aims to outline the molecularly imprinted process and present a summary of principal application fields of molecularly imprinted polymers, focusing on chemical sensing, separation science, drug delivery and catalysis. Some significant aspects about preparation and application of the molecular imprinting polymers with examples taken from the recent literature will be discussed. Theoretical and experimental parameters for MIPs design in terms of the interaction between template and polymer functionalities will be considered and synthesis methods for the improvement of MIP recognition properties will also be presented.

Combining Near-Infrared Spectroscopy and Chemometrics for Rapid Recognition of an Hg-Contaminated Plant

Directory of Open Access Journals (Sweden)

Bang-Cheng Tang

2016-01-01

Full Text Available The feasibility of rapid recognition of an Hg-contaminated plant as a soil pollution indicator was investigated using near-infrared spectroscopy (NIRS and chemometrics. The stem and leave of a native plant, Miscanthus floridulus (Labill. Warb. (MFLW, were collected from Hg-contaminated areas (n1=125 as well as from regular areas (n2=116. The samples were dried and crushed and the powders were sieved through an 80-mesh sieve. Reference analysis of Hg levels was performed using inductively coupled plasma-atomic emission spectrometry (ICP-AES. The actual Hg contents of contaminated and normal samples were 16.2–30.5 and 0.0–0.1 mg/Kg, respectively. The NIRS measurements of impacted sample powders were collected in the mode of reflectance. The DUPLEX algorithm was utilized to split the NIRS data into representative training and test sets. Different spectral preprocessing methods were performed to remove the unwanted and noncomposition-correlated spectral variations. Classification models were developed using partial least squares discrimination analysis (PLSDA based on the raw, smoothed, second-order derivative (D2, and standard normal variate (SNV data, respectively. The prediction accuracy obtained by PLSDA with each data preprocessing option was 100%, indicating pattern recognition of Hg-contaminated MFLW samples using NIRS data was in perfect consistence with the ICP-AES results. NIRS combined with chemometrics will provide a tool to screen the Hg-contaminated MFLW, which can be potentially used as an indicator of soil pollution.

Interdependence of Inhibitor Recognition in HIV-1 Protease.

Science.gov (United States)

Paulsen, Janet L; Leidner, Florian; Ragland, Debra A; Kurt Yilmaz, Nese; Schiffer, Celia A

2017-05-09

Molecular recognition is a highly interdependent process. Subsite couplings within the active site of proteases are most often revealed through conditional amino acid preferences in substrate recognition. However, the potential effect of these couplings on inhibition and thus inhibitor design is largely unexplored. The present study examines the interdependency of subsites in HIV-1 protease using a focused library of protease inhibitors, to aid in future inhibitor design. Previously a series of darunavir (DRV) analogs was designed to systematically probe the S1' and S2' subsites. Co-crystal structures of these analogs with HIV-1 protease provide the ideal opportunity to probe subsite interdependency. All-atom molecular dynamics simulations starting from these structures were performed and systematically analyzed in terms of atomic fluctuations, intermolecular interactions, and water structure. These analyses reveal that the S1' subsite highly influences other subsites: the extension of the hydrophobic P1' moiety results in 1) reduced van der Waals contacts in the P2' subsite, 2) more variability in the hydrogen bond frequencies with catalytic residues and the flap water, and 3) changes in the occupancy of conserved water sites both proximal and distal to the active site. In addition, one of the monomers in this homodimeric enzyme has atomic fluctuations more highly correlated with DRV than the other monomer. These relationships intricately link the HIV-1 protease subsites and are critical to understanding molecular recognition and inhibitor binding. More broadly, the interdependency of subsite recognition within an active site requires consideration in the selection of chemical moieties in drug design; this strategy is in contrast to what is traditionally done with independent optimization of chemical moieties of an inhibitor.

Bio-Mimetic Sensors Based on Molecularly Imprinted Membranes

Directory of Open Access Journals (Sweden)

Catia Algieri

2014-07-01

Full Text Available An important challenge for scientific research is the production of artificial systems able to mimic the recognition mechanisms occurring at the molecular level in living systems. A valid contribution in this direction resulted from the development of molecular imprinting. By means of this technology, selective molecular recognition sites are introduced in a polymer, thus conferring it bio-mimetic properties. The potential applications of these systems include affinity separations, medical diagnostics, drug delivery, catalysis, etc. Recently, bio-sensing systems using molecularly imprinted membranes, a special form of imprinted polymers, have received the attention of scientists in various fields. In these systems imprinted membranes are used as bio-mimetic recognition elements which are integrated with a transducer component. The direct and rapid determination of an interaction between the recognition element and the target analyte (template was an encouraging factor for the development of such systems as alternatives to traditional bio-assay methods. Due to their high stability, sensitivity and specificity, bio-mimetic sensors-based membranes are used for environmental, food, and clinical uses. This review deals with the development of molecularly imprinted polymers and their different preparation methods. Referring to the last decades, the application of these membranes as bio-mimetic sensor devices will be also reported.

Bio-Mimetic Sensors Based on Molecularly Imprinted Membranes

Science.gov (United States)

Algieri, Catia; Drioli, Enrico; Guzzo, Laura; Donato, Laura

2014-01-01

An important challenge for scientific research is the production of artificial systems able to mimic the recognition mechanisms occurring at the molecular level in living systems. A valid contribution in this direction resulted from the development of molecular imprinting. By means of this technology, selective molecular recognition sites are introduced in a polymer, thus conferring it bio-mimetic properties. The potential applications of these systems include affinity separations, medical diagnostics, drug delivery, catalysis, etc. Recently, bio-sensing systems using molecularly imprinted membranes, a special form of imprinted polymers, have received the attention of scientists in various fields. In these systems imprinted membranes are used as bio-mimetic recognition elements which are integrated with a transducer component. The direct and rapid determination of an interaction between the recognition element and the target analyte (template) was an encouraging factor for the development of such systems as alternatives to traditional bio-assay methods. Due to their high stability, sensitivity and specificity, bio-mimetic sensors-based membranes are used for environmental, food, and clinical uses. This review deals with the development of molecularly imprinted polymers and their different preparation methods. Referring to the last decades, the application of these membranes as bio-mimetic sensor devices will be also reported. PMID:25196110

Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

Directory of Open Access Journals (Sweden)

Dat Tien Nguyen

2018-02-01

Full Text Available Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples. Therefore, a presentation attack detection (PAD method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP, local ternary pattern (LTP, and histogram of oriented gradients (HOG. As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN method to extract deep image features and the multi-level local binary pattern (MLBP method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.

Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors.

Science.gov (United States)

Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

2018-02-26

Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.

Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

Science.gov (United States)

Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

2018-01-01

Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases. PMID:29495417

Molecular Evolution of the CYP2D Subfamily in Primates: Purifying Selection on Substrate Recognition Sites without the Frequent or Long-Tract Gene Conversion

Science.gov (United States)

Yasukochi, Yoshiki; Satta, Yoko

2015-01-01

The human cytochrome P450 (CYP) 2D6 gene is a member of the CYP2D gene subfamily, along with the CYP2D7P and CYP2D8P pseudogenes. Although the CYP2D6 enzyme has been studied extensively because of its clinical importance, the evolution of the CYP2D subfamily has not yet been fully understood. Therefore, the goal of this study was to reveal the evolutionary process of the human drug metabolic system. Here, we investigate molecular evolution of the CYP2D subfamily in primates by comparing 14 CYP2D sequences from humans to New World monkey genomes. Window analysis and statistical tests revealed that entire genomic sequences of paralogous genes were extensively homogenized by gene conversion during molecular evolution of CYP2D genes in primates. A neighbor-joining tree based on genomic sequences at the nonsubstrate recognition sites showed that CYP2D6 and CYP2D8 genes were clustered together due to gene conversion. In contrast, a phylogenetic tree using amino acid sequences at substrate recognition sites did not cluster the CYP2D6 and CYP2D8 genes, suggesting that the functional constraint on substrate specificity is one of the causes for purifying selection at the substrate recognition sites. Our results suggest that the CYP2D gene subfamily in primates has evolved to maintain the regioselectivity for a substrate hydroxylation activity between individual enzymes, even though extensive gene conversion has occurred across CYP2D coding sequences. PMID:25808902

Graphene oxide-sensitized molecularly imprinted opto-polymers for charge-transfer fluorescent sensing of cyanoguanidine.

Science.gov (United States)

Liu, Huilin; Zhou, Kaiwen; Chen, Xiaomo; Wang, Jing; Wang, Shuo; Sun, Baoguo

2017-11-15

The hierarchical structuring of materials offers exciting opportunities to construct functional sensors. Multiple processes were combined to create complex materials for the selective detection of cyanoguanidine (CYA) using graphene oxide-sensitized molecularly imprinted opto-polymers (MIOP). Molecular imprinting was used to construct molecular-scale analyte-selective cavities, graphene oxide was introduced to provide a platform for the polymerization, and increase the stability and binding kinetic properties, and 3-methacryloxy propyl trimethoxy silane-modified quantum dots were combined with a functional monomer to increase the fluorescence quantum yield. Polymer cross-linking and fluorescence intensity were optimized for molecular recognition and opto-sensing detection. Selective and sensitive, fluorescence sensing of CYA was possible at concentrations as low as to 1.6μM. It could be applied to the rapid and cost-effective monitoring of CYA in infant formula. The approach is generic and applicable to many molecules and conventional opto-sensors, based on molecularly imprinted polymer formulations, individually or in multiplexed arrays. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unique molecular landscapes in cancer: implications for individualized, curated drug combinations.

Science.gov (United States)

Wheler, Jennifer; Lee, J Jack; Kurzrock, Razelle

2014-12-15

With increasingly sophisticated technologies in molecular biology and "omic" platforms to analyze patients' tumors, more molecular diversity and complexity in cancer are being observed. Recently, we noted unique genomic profiles in a group of patients with metastatic breast cancer based on an analysis with next-generation sequencing. Among 57 consecutive patients, no two had the same molecular portfolio. Applied genomics therefore appears to represent a disruptive innovation in that it unveils a heterogeneity to metastatic cancer that may be ill-suited to canonical clinical trials and practice paradigms. Upon recognizing that patients have unique tumor landscapes, it is possible that there may be a "mismatch" between our traditional clinical trials system that selects patients based on common characteristics to evaluate a drug (drug-centric approach) and optimal treatment based on curated, individualized drug combinations for each patient (patient-centric approach). ©2014 American Association for Cancer Research.

Towards structural models of molecular recognition in olfactory receptors.

Science.gov (United States)

Afshar, M; Hubbard, R E; Demaille, J

1998-02-01

The G protein coupled receptors (GPCR) are an important class of proteins that act as signal transducers through the cytoplasmic membrane. Understanding the structure and activation mechanism of these proteins is crucial for understanding many different aspects of cellular signalling. The olfactory receptors correspond to the largest family of GPCRs. Very little is known about how the structures of the receptors govern the specificity of interaction which enables identification of particular odorant molecules. In this paper, we review recent developments in two areas of molecular modelling: methods for modelling the configuration of trans-membrane helices and methods for automatic docking of ligands into receptor structures. We then show how a subset of these methods can be combined to construct a model of a rat odorant receptor interacting with lyral for which experimental data are available. This modelling can help us make progress towards elucidating the specificity of interactions between receptors and odorant molecules.

Combining phylogenomics and fossils in higher-level squamate reptile phylogeny: molecular data change the placement of fossil taxa.

Science.gov (United States)

Wiens, John J; Kuczynski, Caitlin A; Townsend, Ted; Reeder, Tod W; Mulcahy, Daniel G; Sites, Jack W

2010-12-01

Molecular data offer great potential to resolve the phylogeny of living taxa but can molecular data improve our understanding of relationships of fossil taxa? Simulations suggest that this is possible, but few empirical examples have demonstrated the ability of molecular data to change the placement of fossil taxa. We offer such an example here. We analyze the placement of snakes among squamate reptiles, combining published morphological data (363 characters) and new DNA sequence data (15,794 characters, 22 nuclear loci) for 45 living and 19 fossil taxa. We find several intriguing results. First, some fossil taxa undergo major changes in their phylogenetic position when molecular data are added. Second, most fossil taxa are placed with strong support in the expected clades by the combined data Bayesian analyses, despite each having >98% missing cells and despite recent suggestions that extensive missing data are problematic for Bayesian phylogenetics. Third, morphological data can change the placement of living taxa in combined analyses, even when there is an overwhelming majority of molecular characters. Finally, we find strong but apparently misleading signal in the morphological data, seemingly associated with a burrowing lifestyle in snakes, amphisbaenians, and dibamids. Overall, our results suggest promise for an integrated and comprehensive Tree of Life by combining molecular and morphological data for living and fossil taxa.

Investigating biomolecular recognition at the cell surface using atomic force microscopy.

Science.gov (United States)

Wang, Congzhou; Yadavalli, Vamsi K

2014-05-01

Probing the interaction forces that drive biomolecular recognition on cell surfaces is essential for understanding diverse biological processes. Force spectroscopy has been a widely used dynamic analytical technique, allowing measurement of such interactions at the molecular and cellular level. The capabilities of working under near physiological environments, combined with excellent force and lateral resolution make atomic force microscopy (AFM)-based force spectroscopy a powerful approach to measure biomolecular interaction forces not only on non-biological substrates, but also on soft, dynamic cell surfaces. Over the last few years, AFM-based force spectroscopy has provided biophysical insight into how biomolecules on cell surfaces interact with each other and induce relevant biological processes. In this review, we focus on describing the technique of force spectroscopy using the AFM, specifically in the context of probing cell surfaces. We summarize recent progress in understanding the recognition and interactions between macromolecules that may be found at cell surfaces from a force spectroscopy perspective. We further discuss the challenges and future prospects of the application of this versatile technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

DNA recognition by synthetic constructs.

Science.gov (United States)

Pazos, Elena; Mosquera, Jesús; Vázquez, M Eugenio; Mascareñas, José L

2011-09-05

The interaction of transcription factors with specific DNA sites is key for the regulation of gene expression. Despite the availability of a large body of structural data on protein-DNA complexes, we are still far from fully understanding the molecular and biophysical bases underlying such interactions. Therefore, the development of non-natural agents that can reproduce the DNA-recognition properties of natural transcription factors remains a major and challenging goal in chemical biology. In this review we summarize the basics of double-stranded DNA recognition by transcription factors, and describe recent developments in the design and preparation of synthetic DNA binders. We mainly focus on synthetic peptides that have been designed by following the DNA interaction of natural proteins, and we discuss how the tools of organic synthesis can be used to make artificial constructs equipped with functionalities that introduce additional properties to the recognition process, such as sensing and controllability. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of biomolecular recognition via magnetic nanoparticle in nanobiotechnology

Science.gov (United States)

Shen, Wei-Zheng; Cetinel, Sibel; Montemagno, Carlo

2018-05-01

The marriage of biomolecular recognition and magnetic nanoparticle creates tremendous opportunities in the development of advanced technology both in academic research and in industrial sectors. In this paper, we review current progress on the magnetic nanoparticle-biomolecule hybrid systems, particularly employing the recognition pairs of DNA-DNA, DNA-protein, protein-protein, and protein-inorganics in several nanobiotechnology application areas, including molecular biology, diagnostics, medical treatment, industrial biocatalysts, and environmental separations.

Target recognition of log-polar ladar range images using moment invariants

Science.gov (United States)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

Molecular recognition of the environment and mechanisms of the origin of species in quantum-like modeling of evolution.

Science.gov (United States)

Melkikh, Alexey V; Khrennikov, Andrei

2017-11-01

A review of the mechanisms of speciation is performed. The mechanisms of the evolution of species, taking into account the feedback of the state of the environment and mechanisms of the emergence of complexity, are considered. It is shown that these mechanisms, at the molecular level, cannot work steadily in terms of classical mechanics. Quantum mechanisms of changes in the genome, based on the long-range interaction potential between biologically important molecules, are proposed as one of possible explanation. Different variants of interactions of the organism and environment based on molecular recognition and leading to new species origins are considered. Experiments to verify the model are proposed. This bio-physical study is completed by the general operational model of based on quantum information theory. The latter is applied to model of epigenetic evolution. We briefly present the basics of the quantum-like approach to modeling of bio-informational processes. This approach is illustrated by the quantum-like model of epigenetic evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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.

The A2iA French handwriting recognition system at the Rimes-ICDAR2011 competition

Science.gov (United States)

Menasri, Farès; Louradour, Jérôme; Bianne-Bernard, Anne-Laure; Kermorvant, Christopher

2012-01-01

This paper describes the system for the recognition of French handwriting submitted by A2iA to the competition organized at ICDAR2011 using the Rimes database. This system is composed of several recognizers based on three different recognition technologies, combined using a novel combination method. A framework multi-word recognition based on weighted finite state transducers is presented, using an explicit word segmentation, a combination of isolated word recognizers and a language model. The system was tested both for isolated word recognition and for multi-word line recognition and submitted to the RIMES-ICDAR2011 competition. This system outperformed all previously proposed systems on these tasks.

A universal entropy-driven mechanism for thioredoxin–target recognition

Science.gov (United States)

Palde, Prakash B.; Carroll, Kate S.

2015-01-01

Cysteine residues in cytosolic proteins are maintained in their reduced state, but can undergo oxidation owing to posttranslational modification during redox signaling or under conditions of oxidative stress. In large part, the reduction of oxidized protein cysteines is mediated by a small 12-kDa thiol oxidoreductase, thioredoxin (Trx). Trx provides reducing equivalents for central metabolic enzymes and is implicated in redox regulation of a wide number of target proteins, including transcription factors. Despite its importance in cellular redox homeostasis, the precise mechanism by which Trx recognizes target proteins, especially in the absence of any apparent signature binding sequence or motif, remains unknown. Knowledge of the forces associated with the molecular recognition that governs Trx–protein interactions is fundamental to our understanding of target specificity. To gain insight into Trx–target recognition, we have thermodynamically characterized the noncovalent interactions between Trx and target proteins before S-S reduction using isothermal titration calorimetry (ITC). Our findings indicate that Trx recognizes the oxidized form of its target proteins with exquisite selectivity, compared with their reduced counterparts. Furthermore, we show that recognition is dependent on the conformational restriction inherent to oxidized targets. Significantly, the thermodynamic signatures for multiple Trx targets reveal favorable entropic contributions as the major recognition force dictating these protein–protein interactions. Taken together, our data afford significant new insight into the molecular forces responsible for Trx–target recognition and should aid the design of new strategies for thiol oxidoreductase inhibition. PMID:26080424

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

Science.gov (United States)

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

2017-01-01

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

Molecular Imprinting of Macromolecules for Sensor Applications.

Science.gov (United States)

Saylan, Yeşeren; Yilmaz, Fatma; Özgür, Erdoğan; Derazshamshir, Ali; Yavuz, Handan; Denizli, Adil

2017-04-19

Molecular recognition has an important role in numerous living systems. One of the most important molecular recognition methods is molecular imprinting, which allows host compounds to recognize and detect several molecules rapidly, sensitively and selectively. Compared to natural systems, molecular imprinting methods have some important features such as low cost, robustness, high recognition ability and long term durability which allows molecularly imprinted polymers to be used in various biotechnological applications, such as chromatography, drug delivery, nanotechnology, and sensor technology. Sensors are important tools because of their ability to figure out a potentially large number of analytical difficulties in various areas with different macromolecular targets. Proteins, enzymes, nucleic acids, antibodies, viruses and cells are defined as macromolecules that have wide range of functions are very important. Thus, macromolecules detection has gained great attention in concerning the improvement in most of the studies. The applications of macromolecule imprinted sensors will have a spacious exploration according to the low cost, high specificity and stability. In this review, macromolecules for molecularly imprinted sensor applications are structured according to the definition of molecular imprinting methods, developments in macromolecular imprinting methods, macromolecular imprinted sensors, and conclusions and future perspectives. This chapter follows the latter strategies and focuses on the applications of macromolecular imprinted sensors. This allows discussion on how sensor strategy is brought to solve the macromolecules imprinting.

Bio-recognitive photonics of a DNA-guided organic semiconductor

Science.gov (United States)

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an `inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Bio-recognitive photonics of a DNA-guided organic semiconductor.

Science.gov (United States)

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-04

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an 'inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Design of molecular imprinted polymers compatible with aqueous environment.

Science.gov (United States)

Piletska, Elena V; Guerreiro, Antonio R; Romero-Guerra, Maria; Chianella, Iva; Turner, Anthony P F; Piletsky, Sergey A

2008-01-21

The main problem of poor water compatibility of molecularly imprinted polymers (MIPs) was addressed in examples describing design of synthetic receptors with high affinity for drugs of abuse. An extensive potentiometric titration of 10 popular functional monomers and corresponding imprinted and blank polymers was conducted in order to evaluate the subtleties of functional groups ionisation under aqueous conditions. It was found that polymers prepared using 2-trifluoromethacrylic acid (TFMAA) in combination with toluene as porogen possess superior properties which make them suitable for effective template recognition in water. The potential impact of phase separation during polymerisation on formation of high quality imprints has been discussed. Three drugs of abuse such as cocaine, deoxyephedrine and methadone were used as template models in polymer preparation for the practical validation of obtained results. The polymer testing showed that synthesized molecularly imprinted polymers have high affinity and selectivity for corresponding templates in aqueous environment, with imprinting factors of 2.6 for cocaine and 1.4 for methadone and deoxyephedrine. Corresponding blank polymers were unable to differentiate between analytes, suggesting that imprinting phenomenon was responsible for the recognition properties.

Helicase-Dependent Isothermal Amplification of DNA and RNA by Using Self-Avoiding Molecular Recognition Systems.

Science.gov (United States)

Yang, Zunyi; McLendon, Chris; Hutter, Daniel; Bradley, Kevin M; Hoshika, Shuichi; Frye, Carole B; Benner, Steven A

2015-06-15

Assays that detect DNA or RNA (xNA) are highly sensitive, as small amounts of xNA can be amplified by PCR. Unfortunately, PCR is inconvenient in low-resource environments, and requires equipment and power that might not be available in these environments. Isothermal procedures, which avoid thermal cycling, are often confounded by primer dimers, off-target priming, and other artifacts. Here, we show how a "self avoiding molecular recognition system" (SAMRS) eliminates these artifacts and gives clean amplicons in a helicase-dependent isothermal amplification (SAMRS-HDA). We also show that incorporating SAMRS into the 3'-ends of primers facilitates the design and screening of primers for HDA assays. Finally, we show that SAMRS-HDA can be twofold multiplexed, difficult to achieve with HDA using standard primers. Thus, SAMRS-HDA is a more versatile approach than standard HDA, with a broader applicability for xNA-targeted diagnostics and research. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Writing and Speech Recognition : Observing Error Correction Strategies of Professional Writers

NARCIS (Netherlands)

Leijten, M.A.J.C.

2007-01-01

In this thesis we describe the organization of speech recognition based writing processes. Writing can be seen as a visual representation of spoken language: a combination that speech recognition takes full advantage of. In the field of writing research, speech recognition is a new writing

Collectin CL-LK Is a Novel Soluble Pattern Recognition Receptor for Mycobacterium tuberculosis

DEFF Research Database (Denmark)

Troegeler, Anthony; Lugo-Villarino, Geanncarlo; Hansen, Søren

2015-01-01

Understanding the molecular components of immune recognition of the tuberculosis (TB) bacillus, Mycobacterium tuberculosis, can help designing novel strategies to combat TB. Here, we identify collectin CL-LK as a novel soluble C-type lectin able to bind M. tuberculosis, and characterize mycobacte......Understanding the molecular components of immune recognition of the tuberculosis (TB) bacillus, Mycobacterium tuberculosis, can help designing novel strategies to combat TB. Here, we identify collectin CL-LK as a novel soluble C-type lectin able to bind M. tuberculosis, and characterize...

Effective Brownian ratchet separation by a combination of molecular filtering and a self-spreading lipid bilayer system.

Science.gov (United States)

Motegi, Toshinori; Nabika, Hideki; Fu, Yingqiang; Chen, Lili; Sun, Yinlu; Zhao, Jianwei; Murakoshi, Kei

2014-07-01

A new molecular manipulation method in the self-spreading lipid bilayer membrane by combining Brownian ratchet and molecular filtering effects is reported. The newly designed ratchet obstacle was developed to effectively separate dye-lipid molecules. The self-spreading lipid bilayer acted as both a molecular transport system and a manipulation medium. By controlling the size and shape of ratchet obstacles, we achieved a significant increase in the separation angle for dye-lipid molecules compared to that with the previous ratchet obstacle. A clear difference was observed between the experimental results and the simple random walk simulation that takes into consideration only the geometrical effect of the ratchet obstacles. This difference was explained by considering an obstacle-dependent local decrease in molecular diffusivity near the obstacles, known as the molecular filtering effect at nanospace. Our experimental findings open up a novel controlling factor in the Brownian ratchet manipulation that allow the efficient separation of molecules in the lipid bilayer based on the combination of Brownian ratchet and molecular filtering effects.

Gender recognition from unconstrained and articulated human body.

Science.gov (United States)

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.

Gender Recognition from Unconstrained and Articulated Human Body

Science.gov (United States)

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition. PMID:24977203

Mapping molecular adhesion sites inside SMIL coated capillaries using atomic force microscopy recognition imaging

Energy Technology Data Exchange (ETDEWEB)

Leitner, Michael [Institute of Biophysics, Johannes Kepler University Linz, Gruberstrasse 40, 4020 Linz (Austria); Stock, Lorenz G. [Division of Chemistry and Bioanalytics, Department of Molecular Biology, University Salzburg, Hellbrunnerstrasse 34, 5020 Salzburg (Austria); Christian Doppler Laboratory for Innovative Tools for the Characterization of Biosimilars, University Salzburg, Hellbrunnerstrasse 34, 5020 Salzburg (Austria); Traxler, Lukas [Institute of Biophysics, Johannes Kepler University Linz, Gruberstrasse 40, 4020 Linz (Austria); Leclercq, Laurent [Institut des Biomolécules Max Mousseron (IBMM, UMR 5247, CNRS, Université de Montpellier, Ecole Nationale Supérieure de Chimie de Montpellier), Place Eugène Bataillon, CC 1706, 34095 Montpellier (France); Bonazza, Klaus; Friedbacher, Gernot [Institute of Chemical Technologies and Analytics, Vienna University of Technology, Getreidemarkt 9/164, 1060 Vienna (Austria); Cottet, Hervé [Institut des Biomolécules Max Mousseron (IBMM, UMR 5247, CNRS, Université de Montpellier, Ecole Nationale Supérieure de Chimie de Montpellier), Place Eugène Bataillon, CC 1706, 34095 Montpellier (France); Stutz, Hanno [Division of Chemistry and Bioanalytics, Department of Molecular Biology, University Salzburg, Hellbrunnerstrasse 34, 5020 Salzburg (Austria); Christian Doppler Laboratory for Innovative Tools for the Characterization of Biosimilars, University Salzburg, Hellbrunnerstrasse 34, 5020 Salzburg (Austria); Ebner, Andreas, E-mail: andreas.ebner@jku.at [Institute of Biophysics, Johannes Kepler University Linz, Gruberstrasse 40, 4020 Linz (Austria)

2016-08-03

Capillary zone electrophoresis (CZE) is a powerful analytical technique for fast and efficient separation of different analytes ranging from small inorganic ions to large proteins. However electrophoretic resolution significantly depends on the coating of the inner capillary surface. High technical efforts like Successive Multiple Ionic Polymer Layer (SMIL) generation have been taken to develop stable coatings with switchable surface charges fulfilling the requirements needed for optimal separation. Although the performance can be easily proven in normalized test runs, characterization of the coating itself remains challenging. Atomic force microscopy (AFM) allows for topographical investigation of biological and analytical relevant surfaces with nanometer resolution and yields information about the surface roughness and homogeneity. Upgrading the scanning tip to a molecular biosensor by adhesive molecules (like partly inverted charged molecules) allows for performing topography and recognition imaging (TREC). As a result, simultaneously acquired sample topography and adhesion maps can be recorded. We optimized this technique for electrophoresis capillaries and investigated the charge distribution of differently composed and treated SMIL coatings. By using the positively charged protein avidin as a single molecule sensor, we compared these SMIL coatings with respect to negative charges, resulting in adhesion maps with nanometer resolution. The capability of TREC as a functional investigation technique at the nanoscale was successfully demonstrated. - Highlights: • SMIL coating allows generation of homogeneous ultra-flat surfaces. • Molecular electrostatic adhesion forces can be determined in the inner wall of CZE capillary with picoNewton accuracy. • Topographical images and simultaneously acquired adhesion maps yield morphological and chemical information at the nanoscale.

Gelation or molecular recognition; is the bis-(α,β-dihydroxy esters motif an omnigelator?

Directory of Open Access Journals (Sweden)

Peter C. Griffiths

2010-11-01

Full Text Available Understanding the gelation of liquids by low molecular weight solutes at low concentrations gives an insight into many molecular recognition phenomena and also offers a simple route to modifying the physical properties of the liquid. Bis-(α,β-dihydroxy esters are shown here to gel thermoreversibly a wide range of solvents, raising interesting questions as to the mechanism of gelation. At gelator concentrations of 5–50 mg ml−1, gels were successfully formed in acetone, ethanol/water mixtures, toluene, cyclohexane and chloroform (the latter, albeit at a higher gelator concentration. A range of neutron techniques – in particular small-angle neutron scattering (SANS – have been employed to probe the structure of a selection of these gels. The universality of gelation in a range of solvent types suggests the gelation mechanism is a feature of the bis-(α,β-dihydroxy ester motif, with SANS demonstrating the presence of regular structures in the 30–40 Å range. A correlation between the apparent rodlike character of the structures formed and the polarity of the solvent is evident. Preliminary spin-echo neutron scattering studies (SESANS indicated the absence of any larger scale structures. Inelastic neutron spectroscopy (INS studies demonstrated that the solvent is largely unaffected by gelation, but does reveal insights into the thermal history of the samples. Further neutron studies of this kind (particularly SESANS and INS are warranted, and it is hoped that this work will stimulate others to pursue this line of research.

Molecular Imprinting Technology in Quartz Crystal Microbalance (QCM) Sensors

Science.gov (United States)

Emir Diltemiz, Sibel; Keçili, Rüstem; Ersöz, Arzu; Say, Rıdvan

2017-01-01

Molecularly imprinted polymers (MIPs) as artificial antibodies have received considerable scientific attention in the past years in the field of (bio)sensors since they have unique features that distinguish them from natural antibodies such as robustness, multiple binding sites, low cost, facile preparation and high stability under extreme operation conditions (higher pH and temperature values, etc.). On the other hand, the Quartz Crystal Microbalance (QCM) is an analytical tool based on the measurement of small mass changes on the sensor surface. QCM sensors are practical and convenient monitoring tools because of their specificity, sensitivity, high accuracy, stability and reproducibility. QCM devices are highly suitable for converting the recognition process achieved using MIP-based memories into a sensor signal. Therefore, the combination of a QCM and MIPs as synthetic receptors enhances the sensitivity through MIP process-based multiplexed binding sites using size, 3D-shape and chemical function having molecular memories of the prepared sensor system toward the target compound to be detected. This review aims to highlight and summarize the recent progress and studies in the field of (bio)sensor systems based on QCMs combined with molecular imprinting technology. PMID:28245588

Molecular Imprinting Technology in Quartz Crystal Microbalance (QCM Sensors

Directory of Open Access Journals (Sweden)

Sibel Emir Diltemiz

2017-02-01

Full Text Available Molecularly imprinted polymers (MIPs as artificial antibodies have received considerable scientific attention in the past years in the field of (biosensors since they have unique features that distinguish them from natural antibodies such as robustness, multiple binding sites, low cost, facile preparation and high stability under extreme operation conditions (higher pH and temperature values, etc.. On the other hand, the Quartz Crystal Microbalance (QCM is an analytical tool based on the measurement of small mass changes on the sensor surface. QCM sensors are practical and convenient monitoring tools because of their specificity, sensitivity, high accuracy, stability and reproducibility. QCM devices are highly suitable for converting the recognition process achieved using MIP-based memories into a sensor signal. Therefore, the combination of a QCM and MIPs as synthetic receptors enhances the sensitivity through MIP process-based multiplexed binding sites using size, 3D-shape and chemical function having molecular memories of the prepared sensor system toward the target compound to be detected. This review aims to highlight and summarize the recent progress and studies in the field of (biosensor systems based on QCMs combined with molecular imprinting technology.

Supramolecular chemistry-general principles and selected examples from anion recognition and metallosupramolecular chemistry.

Science.gov (United States)

Albrecht, Markus

2007-12-01

This review gives an introduction into supramolecular chemistry describing in the first part general principles, focusing on terms like noncovalent interaction, molecular recognition, self-assembly, and supramolecular function. In the second part those will be illustrated by simple examples from our laboratories. Supramolecular chemistry is the science that bridges the gap between the world of molecules and nanotechnology. In supramolecular chemistry noncovalent interactions occur between molecular building blocks, which by molecular recognition and self-assembly form (functional) supramolecular entities. It is also termed the "chemistry of the noncovalent bond." Molecular recognition is based on geometrical complementarity based on the "key-and-lock" principle with nonshape-dependent effects, e.g., solvatization, being also highly influential. Self-assembly leads to the formation of well-defined aggregates. Hereby the overall structure of the target ensemble is controlled by the symmetry features of the certain building blocks. Finally, the aggregates can possess special properties or supramolecular functions, which are only found in the ensemble but not in the participating molecules. This review gives an introduction on supramolecular chemistry and illustrates the fundamental principles by recent examples from our group.

Structural insights into the recognition of phosphopeptide by the FHA domain of kanadaptin

DEFF Research Database (Denmark)

Xu, Qingping; Deller, Marc C; Nielsen, Tine K

2014-01-01

with a phosphopeptide mimic derived from a peptide segment from the N-terminus of a symmetry-related molecule as well as a sulfate bound to the structurally conserved phosphothreonine recognition cleft. This structure provides insights into the molecular recognition features utilized by this family of proteins...

MOLECULARLY IMPRINTED POLYMER TECHNOLOGY: A ...

African Journals Online (AJOL)

dell

Cross-linking ensures polymer rigidity that “freezes” the 3-D molecular architecture of the binding cavity when the ... molecular technology applications whose potential is still .... recognition element is responsible for the selective ... organic treatments, making them superior ... efficiency with which such materials may be.

On the combination of molecular replacement and single-wavelength anomalous diffraction phasing for automated structure determination

International Nuclear Information System (INIS)

Panjikar, Santosh; Parthasarathy, Venkataraman; Lamzin, Victor S.; Weiss, Manfred S.; Tucker, Paul A.

2009-01-01

The combination of molecular replacement and single-wavelength anomalous diffraction improves the performance of automated structure determination with Auto-Rickshaw. A combination of molecular replacement and single-wavelength anomalous diffraction phasing has been incorporated into the automated structure-determination platform Auto-Rickshaw. The complete MRSAD procedure includes molecular replacement, model refinement, experimental phasing, phase improvement and automated model building. The improvement over the standard SAD or MR approaches is illustrated by ten test cases taken from the JCSG diffraction data-set database. Poor MR or SAD phases with phase errors larger than 70° can be improved using the described procedure and a large fraction of the model can be determined in a purely automatic manner from X-ray data extending to better than 2.6 Å resolution

Imprinting of molecular recognition sites combined with π-donor-acceptor interactions using bis-aniline-crosslinked Au-CdSe/ZnS nanoparticles array on electrodes: Development of electrochemiluminescence sensor for the ultrasensitive and selective detection of 2-methyl-4-chlorophenoxyacetic acid.

Science.gov (United States)

Yang, Yukun; Fang, Guozhen; Wang, Xiaomin; Liu, Guiyang; Wang, Shuo

2016-03-15

A novel strategy is reported for the fabrication of bis-aniline-crosslinked Au nanoparticles (NPs)-CdSe/ZnS quantum dots (QDs) array composite by facil one-step co-electropolymerization of thioaniline-functionalized AuNPs and thioaniline-functionalized CdSe/ZnS QDs onto thioaniline-functionalized Au elctrodes (AuE). Stable and enhanced cathodic electrochemiluminescence (ECL) of CdSe/ZnS QDs is observed on the modified electrode in neutral solution, suggesting promising applications in ECL sensing. An advanced ECL sensor is explored for detection of 2-methyl-4-chlorophenoxyacetic acid (MCPA) which quenches the ECL signal through electron-transfer pathway. The sensitive determination of MCPA with limit of detection (LOD) of 2.2 nmolL(-1) (S/N=3) is achieved by π-donor-acceptor interactions between MCPA and the bis-aniline bridging units. Impressively, the imprinting of molecular recognition sites into the bis-aniline-crosslinked AuNPs-CdSe/ZnS QDs array yields a functionalized electrode with an extremely sensitive response to MCPA in a linear range of 10 pmolL(-1)-50 μmolL(-1) with a LOD of 4.3 pmolL(-1 ()S/N=3). The proposed ECL sensor with high sensitivity, good selectivity, reproducibility and stability has been successfully applied for the determination of MCPA in real samples with satisfactory recoveries. In this study, ECL sensor combined the merits of QDs-ECL and molecularly imprinting technology is reported for the first time. The developed ECL sensor holds great promise for the fabrication of QDs-based ECL sensors with improved sensitivity and furthermore opens the door to wide applications of QDs-based ECL in food safety and environmental monitoring. Copyright © 2015 Elsevier B.V. All rights reserved.

Nanostructured materials for selective recognition and targeted drug delivery

International Nuclear Information System (INIS)

Kotrotsiou, O; Kotti, K; Dini, E; Kammona, O; Kiparissides, C

2005-01-01

Selective recognition requires the introduction of a molecular memory into a polymer matrix in order to make it capable of rebinding an analyte with a very high specificity. In addition, targeted drug delivery requires drug-loaded vesicles which preferentially localize to the sites of injury and avoid uptake into uninvolved tissues. The rapid evolution of nanotechnology is aiming to fulfill the goal of selective recognition and optimal drug delivery through the development of molecularly imprinted polymeric (MIP) nanoparticles, tailor-made for a diverse range of analytes (e.g., pharmaceuticals, pesticides, amino acids, etc.) and of nanostructured targeted drug carriers (e.g., liposomes and micelles) with increased circulation lifetimes. In the present study, PLGA microparticles containing multilamellar vesicles (MLVs), and MIP nanoparticles were synthesized to be employed as drug carriers and synthetic receptors respectively

A combination of molecular markers and clinical features improve the classification of pancreatic cysts.

Science.gov (United States)

Springer, Simeon; Wang, Yuxuan; Dal Molin, Marco; Masica, David L; Jiao, Yuchen; Kinde, Isaac; Blackford, Amanda; Raman, Siva P; Wolfgang, Christopher L; Tomita, Tyler; Niknafs, Noushin; Douville, Christopher; Ptak, Janine; Dobbyn, Lisa; Allen, Peter J; Klimstra, David S; Schattner, Mark A; Schmidt, C Max; Yip-Schneider, Michele; Cummings, Oscar W; Brand, Randall E; Zeh, Herbert J; Singhi, Aatur D; Scarpa, Aldo; Salvia, Roberto; Malleo, Giuseppe; Zamboni, Giuseppe; Falconi, Massimo; Jang, Jin-Young; Kim, Sun-Whe; Kwon, Wooil; Hong, Seung-Mo; Song, Ki-Byung; Kim, Song Cheol; Swan, Niall; Murphy, Jean; Geoghegan, Justin; Brugge, William; Fernandez-Del Castillo, Carlos; Mino-Kenudson, Mari; Schulick, Richard; Edil, Barish H; Adsay, Volkan; Paulino, Jorge; van Hooft, Jeanin; Yachida, Shinichi; Nara, Satoshi; Hiraoka, Nobuyoshi; Yamao, Kenji; Hijioka, Susuma; van der Merwe, Schalk; Goggins, Michael; Canto, Marcia Irene; Ahuja, Nita; Hirose, Kenzo; Makary, Martin; Weiss, Matthew J; Cameron, John; Pittman, Meredith; Eshleman, James R; Diaz, Luis A; Papadopoulos, Nickolas; Kinzler, Kenneth W; Karchin, Rachel; Hruban, Ralph H; Vogelstein, Bert; Lennon, Anne Marie

2015-11-01

The management of pancreatic cysts poses challenges to both patients and their physicians. We investigated whether a combination of molecular markers and clinical information could improve the classification of pancreatic cysts and management of patients. We performed a multi-center, retrospective study of 130 patients with resected pancreatic cystic neoplasms (12 serous cystadenomas, 10 solid pseudopapillary neoplasms, 12 mucinous cystic neoplasms, and 96 intraductal papillary mucinous neoplasms). Cyst fluid was analyzed to identify subtle mutations in genes known to be mutated in pancreatic cysts (BRAF, CDKN2A, CTNNB1, GNAS, KRAS, NRAS, PIK3CA, RNF43, SMAD4, TP53, and VHL); to identify loss of heterozygozity at CDKN2A, RNF43, SMAD4, TP53, and VHL tumor suppressor loci; and to identify aneuploidy. The analyses were performed using specialized technologies for implementing and interpreting massively parallel sequencing data acquisition. An algorithm was used to select markers that could classify cyst type and grade. The accuracy of the molecular markers was compared with that of clinical markers and a combination of molecular and clinical markers. We identified molecular markers and clinical features that classified cyst type with 90%-100% sensitivity and 92%-98% specificity. The molecular marker panel correctly identified 67 of the 74 patients who did not require surgery and could, therefore, reduce the number of unnecessary operations by 91%. We identified a panel of molecular markers and clinical features that show promise for the accurate classification of cystic neoplasms of the pancreas and identification of cysts that require surgery. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.

Deep kernel learning method for SAR image target recognition

Science.gov (United States)

Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

2017-10-01

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

Probabilistic Open Set Recognition

Science.gov (United States)

Jain, Lalit Prithviraj

Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

A combined reaction class approach with integrated molecular orbital+molecular orbital (IMOMO) methodology: A practical tool for kinetic modeling

International Nuclear Information System (INIS)

Truong, Thanh N.; Maity, Dilip K.; Truong, Thanh-Thai T.

2000-01-01

We present a new practical computational methodology for predicting thermal rate constants of reactions involving large molecules or a large number of elementary reactions in the same class. This methodology combines the integrated molecular orbital+molecular orbital (IMOMO) approach with our recently proposed reaction class models for tunneling. With the new methodology, we show that it is possible to significantly reduce the computational cost by several orders of magnitude while compromising the accuracy in the predicted rate constants by less than 40% over a wide range of temperatures. Another important result is that the computational cost increases only slightly as the system size increases. (c) 2000 American Institute of Physics

Improved hemicryptophane hosts for the stereoselective recognition of glucopyranosides

Czech Academy of Sciences Publication Activity Database

Schmitt, A.; Perraud, O.; Payet, E.; Chatelet, B.; Bousquet, B.; Valls, M.; Padula, Daniele; Di Bari, L.; Dutasta, J. P.; Martinez, A.

2014-01-01

Roč. 12, č. 24 (2014), s. 4211-4217 ISSN 1477-0520 Institutional support: RVO:61388963 Keywords : hydrogen-bonding receptors * molecular recognition * artificial receptors Subject RIV: CC - Organic Chemistry Impact factor: 3.562, year: 2014

Computer aided molecular design with combined molecular modeling and group contribution

DEFF Research Database (Denmark)

Harper, Peter Mathias; Gani, Rafiqul; Kolar, Petr

1999-01-01

Computer-aided molecular design (CAMD) provides a means for determining molecules or mixtures of molecules (CAMMD) having a desirable set of physicochemical properties. The application range of CAMD is restricted due to limitations on the complexity of the generated molecular structures and on th......Computer-aided molecular design (CAMD) provides a means for determining molecules or mixtures of molecules (CAMMD) having a desirable set of physicochemical properties. The application range of CAMD is restricted due to limitations on the complexity of the generated molecular structures...

The Role of Binocular Disparity in Rapid Scene and Pattern Recognition

Directory of Open Access Journals (Sweden)

Matteo Valsecchi

2013-04-01

Full Text Available We investigated the contribution of binocular disparity to the rapid recognition of scenes and simpler spatial patterns using a paradigm combining backward masked stimulus presentation and short-term match-to-sample recognition. First, we showed that binocular disparity did not contribute significantly to the recognition of briefly presented natural and artificial scenes, even when the availability of monocular cues was reduced. Subsequently, using dense random dot stereograms as stimuli, we showed that observers were in principle able to extract spatial patterns defined only by disparity under brief, masked presentations. Comparing our results with the predictions from a cue-summation model, we showed that combining disparity with luminance did not per se disrupt the processing of disparity. Our results suggest that the rapid recognition of scenes is mediated mostly by a monocular comparison of the images, although we can rely on stereo in fast pattern recognition.

Zipper-like magnetic molecularly imprinted microspheres for on/off-switchable recognition and extraction of 17β-estradiol from food samples.

Science.gov (United States)

Zhu, Wenting; Peng, Hailong; Luo, Mei; Yu, Ningxiang; Xiong, Hua; Wang, Ronghui; Li, Yanbin

2018-09-30

Zipper-like on/off-switchable and magnetic molecularly imprinted microspheres (SM-MIMs) were constructed using acrylamide (AAm) and 2-acrylamide-2-methyl propanesulfonic acid (AMPS) as functional monomers for 17β-estradiol (17β-E 2 ) recognition and extraction. The imprinted polymer interactions between poly(AAm) (PAAm) and poly(AMPS) (PAMPS) with on/off-switchable property to temperature, exhibited dissociation at relatively higher temperatures (such as 30 °C) and helped 17β-E 2 enter into imprinted sites, leading to higher binding capability. Conversely, the interpolymer complexes between PAAm and PAMPS formed and blocked 17β-E 2 access to imprinted sites at lower temperature (such as 20 °C). SM-MIMs were used as dispersive solid phase extraction (SPE) adsorbent with HPLC for 17β-E 2 pretreatment and detection in food samples, and low limit detection (2.52 µg L -1 ) and quantification (10.76 µg L -1 ) with higher recovery were obtained. Therefore, SM-MIMs may be a promising adsorbent for 17β-E 2 pretreatment in food samples owing to its advantages of on/off-switchable recognition, eco-friendly elution, and efficient separation. Copyright © 2018. Published by Elsevier Ltd.

Representing Objects using Global 3D Relational Features for Recognition Tasks

DEFF Research Database (Denmark)

Mustafa, Wail

2015-01-01

representations. For representing objects, we derive global descriptors encoding shape using viewpoint-invariant features obtained from multiple sensors observing the scene. Objects are also described using color independently. This allows for combining color and shape when it is required for the task. For more...... robust color description, color calibration is performed. The framework was used in three recognition tasks: object instance recognition, object category recognition, and object spatial relationship recognition. For the object instance recognition task, we present a system that utilizes color and scale...

Type-2 fuzzy graphical models for pattern recognition

CERN Document Server

Zeng, Jia

2015-01-01

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

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

Science.gov (United States)

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.

The Complete Gabor-Fisher Classifier for Robust Face Recognition

Directory of Open Access Journals (Sweden)

Štruc Vitomir

2010-01-01

Full Text Available Abstract This paper develops a novel face recognition technique called Complete Gabor Fisher Classifier (CGFC. Different from existing techniques that use Gabor filters for deriving the Gabor face representation, the proposed approach does not rely solely on Gabor magnitude information but effectively uses features computed based on Gabor phase information as well. It represents one of the few successful attempts found in the literature of combining Gabor magnitude and phase information for robust face recognition. The novelty of the proposed CGFC technique comes from (1 the introduction of a Gabor phase-based face representation and (2 the combination of the recognition technique using the proposed representation with classical Gabor magnitude-based methods into a unified framework. The proposed face recognition framework is assessed in a series of face verification and identification experiments performed on the XM2VTS, Extended YaleB, FERET, and AR databases. The results of the assessment suggest that the proposed technique clearly outperforms state-of-the-art face recognition techniques from the literature and that its performance is almost unaffected by the presence of partial occlusions of the facial area, changes in facial expression, or severe illumination changes.

Selective extraction of dimethoate from cucumber samples by use of molecularly imprinted microspheres

Directory of Open Access Journals (Sweden)

Jiao-Jiao Du

2015-06-01

Full Text Available Molecularly imprinted polymers for dimethoate recognition were synthesized by the precipitation polymerization technique using methyl methacrylate (MMA as the functional monomer and ethylene glycol dimethacrylate (EGDMA as the cross-linker. The morphology, adsorption and recognition properties were investigated by scanning electron microscopy (SEM, static adsorption test, and competitive adsorption test. To obtain the best selectivity and binding performance, the synthesis and adsorption conditions of MIPs were optimized through single factor experiments. Under the optimized conditions, the resultant polymers exhibited uniform size, satisfactory binding capacity and significant selectivity. Furthermore, the imprinted polymers were successfully applied as a specific solid-phase extractants combined with high performance liquid chromatography (HPLC for determination of dimethoate residues in the cucumber samples. The average recoveries of three spiked samples ranged from 78.5% to 87.9% with the relative standard deviations (RSDs less than 4.4% and the limit of detection (LOD obtained for dimethoate as low as 2.3 μg/mL. Keywords: Molecularly imprinted polymer, Precipitation polymerization, Dimethoate, Cucumber, HPLC

Gender Recognition from Unconstrained and Articulated Human Body

Directory of Open Access Journals (Sweden)

Qin Wu

2014-01-01

human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.

Hybrid Speaker Recognition Using Universal Acoustic Model

Science.gov (United States)

Nishimura, Jun; Kuroda, Tadahiro

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

Three-dimensional object recognition using similar triangles and decision trees

Science.gov (United States)

Spirkovska, Lilly

1993-01-01

A system, TRIDEC, that is capable of distinguishing between a set of objects despite changes in the objects' positions in the input field, their size, or their rotational orientation in 3D space is described. TRIDEC combines very simple yet effective features with the classification capabilities of inductive decision tree methods. The feature vector is a list of all similar triangles defined by connecting all combinations of three pixels in a coarse coded 127 x 127 pixel input field. The classification is accomplished by building a decision tree using the information provided from a limited number of translated, scaled, and rotated samples. Simulation results are presented which show that TRIDEC achieves 94 percent recognition accuracy in the 2D invariant object recognition domain and 98 percent recognition accuracy in the 3D invariant object recognition domain after training on only a small sample of transformed views of the objects.

Application of molecular imaging combined with genetic screening in diagnosing MELAS, diabetes and recurrent pancreatitis.

Science.gov (United States)

Zhiping, W; Quwen, L; Hai, Z; Jian, Z; Peiyi, G

2016-01-01

We report molecular imaging combined with gene diagnosis in a family with 7 members who carried an A3243G mutation in mitochondrial tRNA and p.Thr 137 Met in cationic trypsinogen (PRSS1) gene presented with mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS), diabetes, and recurrent pancreatitis. DNA sequencing was used to detect and validate mitochondrial DNA and PRSS1. We also verified that mitochondrial heterozygous mutations and c.410 C>T mutation causing p.Thr 137 Met could be detected in oral epithelial cells or in urine sediment cells. In addition, molecular imaging was carried out in the affected family members. In this pedigree, MELAS syndrome accompanied by pancreatitis was an important clinical feature, followed by diabetes. Heteroplasmy of the mtDNA A3243G and c.410 C>T mutation of PRSS1 was found in all tissue samples of these patients, but no mutations were found in 520 normal control and normal individuals of the family. However, based on molecular imaging observations, patients with relatively higher lactate/pyruvate levels had more typical and more severe symptoms, particularly those of pancreatic disease (diabetes or pancreatitis). MELAS syndrome may be associated with pancreatitis. For the diagnosis, it is more reasonable to perform molecular imaging combined with gene diagnosis.

Improved pattern recognition systems by hybrid methods

International Nuclear Information System (INIS)

Duerr, B.; Haettich, W.; Tropf, H.; Winkler, G.; Fraunhofer-Gesellschaft zur Foerderung der Angewandten Forschung e.V., Karlsruhe

1978-12-01

This report describes a combination of statistical and syntactical pattern recongition methods. The hierarchically structured recognition system consists of a conventional statistical classifier, a structural classifier analysing the topological composition of the patterns, a stage reducing the number of hypotheses made by the first two stages, and a mixed stage based on a search for maximum similarity between syntactically generated prototypes and patterns. The stages work on different principles to avoid mistakes made in one stage in the other stages. This concept is applied to the recognition of numerals written without constraints. If no samples are rejected, a recognition rate of 99,5% is obtained. (orig.) [de

Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

Directory of Open Access Journals (Sweden)

Bin Li

2012-02-01

Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and cost-sensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method; candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal

Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

Directory of Open Access Journals (Sweden)

Bin Li

2011-10-01

Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and costsensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method;candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal parameters

Research on improving image recognition robustness by combining multiple features with associative memory

Science.gov (United States)

Guo, Dongwei; Wang, Zhe

2018-05-01

Convolutional neural networks (CNN) achieve great success in computer vision, it can learn hierarchical representation from raw pixels and has outstanding performance in various image recognition tasks [1]. However, CNN is easy to be fraudulent in terms of it is possible to produce images totally unrecognizable to human eyes that CNNs believe with near certainty are familiar objects. [2]. In this paper, an associative memory model based on multiple features is proposed. Within this model, feature extraction and classification are carried out by CNN, T-SNE and exponential bidirectional associative memory neural network (EBAM). The geometric features extracted from CNN and the digital features extracted from T-SNE are associated by EBAM. Thus we ensure the recognition of robustness by a comprehensive assessment of the two features. In our model, we can get only 8% error rate with fraudulent data. In systems that require a high safety factor or some key areas, strong robustness is extremely important, if we can ensure the image recognition robustness, network security will be greatly improved and the social production efficiency will be extremely enhanced.

A New Fuzzy Cognitive Map Learning Algorithm for Speech Emotion Recognition

Directory of Open Access Journals (Sweden)

Wei Zhang

2017-01-01

Full Text Available Selecting an appropriate recognition method is crucial in speech emotion recognition applications. However, the current methods do not consider the relationship between emotions. Thus, in this study, a speech emotion recognition system based on the fuzzy cognitive map (FCM approach is constructed. Moreover, a new FCM learning algorithm for speech emotion recognition is proposed. This algorithm includes the use of the pleasure-arousal-dominance emotion scale to calculate the weights between emotions and certain mathematical derivations to determine the network structure. The proposed algorithm can handle a large number of concepts, whereas a typical FCM can handle only relatively simple networks (maps. Different acoustic features, including fundamental speech features and a new spectral feature, are extracted to evaluate the performance of the proposed method. Three experiments are conducted in this paper, namely, single feature experiment, feature combination experiment, and comparison between the proposed algorithm and typical networks. All experiments are performed on TYUT2.0 and EMO-DB databases. Results of the feature combination experiments show that the recognition rates of the combination features are 10%–20% better than those of single features. The proposed FCM learning algorithm generates 5%–20% performance improvement compared with traditional classification networks.

Is emotion recognition the only problem in ADHD? effects of pharmacotherapy on face and emotion recognition in children with ADHD.

Science.gov (United States)

Demirci, Esra; Erdogan, Ayten

2016-12-01

The objectives of this study were to evaluate both face and emotion recognition, to detect differences among attention deficit and hyperactivity disorder (ADHD) subgroups, to identify effects of the gender and to assess the effects of methylphenidate and atomoxetine treatment on both face and emotion recognition in patients with ADHD. The study sample consisted of 41 male, 29 female patients, 8-15 years of age, who were diagnosed as having combined type ADHD (N = 26), hyperactive/impulsive type ADHD (N = 21) or inattentive type ADHD (N = 23) but had not previously used any medication for ADHD and 35 male, 25 female healthy individuals. Long-acting methylphenidate (OROS-MPH) was prescribed to 38 patients, whereas atomoxetine was prescribed to 32 patients. The reading the mind in the eyes test (RMET) and Benton face recognition test (BFRT) were applied to all participants before and after treatment. The patients with ADHD had a significantly lower number of correct answers in child and adolescent RMET and in BFRT than the healthy controls. Among the ADHD subtypes, the hyperactive/impulsive subtype had a lower number of correct answers in the RMET than the inattentive subtypes, and the hyperactive/impulsive subtype had a lower number of correct answers in short and long form of BFRT than the combined and inattentive subtypes. Male and female patients with ADHD did not differ significantly with respect to the number of correct answers on the RMET and BFRT. The patients showed significant improvement in RMET and BFRT after treatment with OROS-MPH or atomoxetine. Patients with ADHD have difficulties in face recognition as well as emotion recognition. Both OROS-MPH and atomoxetine affect emotion recognition. However, further studies on the face and emotion recognition are needed in ADHD.

Supramolecular Nanoparticles for Molecular Diagnostics and Therapeutics

Science.gov (United States)

Chen, Kuan-Ju

Over the past decades, significant efforts have been devoted to explore the use of various nanoparticle-based systems in the field of nanomedicine, including molecular imaging and therapy. Supramolecular synthetic approaches have attracted lots of attention due to their flexibility, convenience, and modularity for producing nanoparticles. In this dissertation, the developmental story of our size-controllable supramolecular nanoparticles (SNPs) will be discussed, as well as their use in specific biomedical applications. To achieve the self-assembly of SNPs, the well-characterized molecular recognition system (i.e., cyclodextrin/adamantane recognition) was employed. The resulting SNPs, which were assembled from three molecular building blocks, possess incredible stability in various physiological conditions, reversible size-controllability and dynamic disassembly that were exploited for various in vitro and in vivo applications. An advantage of using the supramolecular approach is that it enables the convenient incorporation of functional ligands onto SNP surface that confers functionality ( e.g., targeting, cell penetration) to SNPs. We utilized SNPs for molecular imaging such as magnetic resonance imaging (MRI) and positron emission tomography (PET) by introducing reporter systems (i.e., radio-isotopes, MR contrast agents, and fluorophores) into SNPs. On the other hand, the incorporation of various payloads, including drugs, genes and proteins, into SNPs showed improved delivery performance and enhanced therapeutic efficacy for these therapeutic agents. Leveraging the powers of (i) a combinatorial synthetic approach based on supramolecular assembly and (ii) a digital microreactor, a rapid developmental pathway was developed that is capable of screening SNP candidates for the ideal structural and functional properties that deliver optimal performance. Moreover, SNP-based theranostic delivery systems that combine reporter systems and therapeutic payloads into a

Molecular requirements for the combined effects of TRAIL and ionising radiation

International Nuclear Information System (INIS)

Marini, Patrizia; Jendrossek, Verena; Durand, Elise; Gruber, Charlotte; Budach, Wilfried; Belka, Claus

2003-01-01

Background and purpose: Previously it was shown that combination of death ligand TRAIL and irradiation strongly increases cell kill in several human tumour cell lines. Since Bcl-2 overexpression did not strongly interfere with the efficacy, components of the mitochondrial death pathway are not required for an effective combined treatment. In the present study the minimal molecular prerequisites for the efficacy of a combined treatment were determined. Materials and methods: Apoptosis induction in control, caspase-8 and FADD negative Jurkat cells, BJAB control and FADD-DN cells was analysed by FACS. Activation of caspase-8, -10 and -3 and cleavage of PARP was determined by immunoblotting. TRAIL receptors were activated using recombinant human TRAIL. Surface expression of TRAIL receptors DR4 and DR5 was analysed by FACS. Results: Jurkat T-cells express the agonistic DR5 receptor but not DR4. Presence of FADD was found to be essential for TRAIL induced apoptosis. Caspase-8 negative cells show very low rates of apoptosis after prolonged stimulation with TRAIL. No combined effects of TRAIL with irradiation could be found in FADD-DN over expressing and FADD deficient cells. However, the combination of TRAIL and irradiation clearly lead to a combined effect in caspase-8 negative Jurkat cells, albeit with reduced death rates. In these cells activation of the alternative initiator caspase-10 could be detected after combined treatment. Conclusion: Our data show that a combined therapy with TRAIL and irradiation will only be effective in cells expressing at least one agonistic TRAIL receptor, FADD and caspase-8 or caspase-10

Genes Regulating Maternal Recognition of Pregnancy in Domestic Animals: an Update

Directory of Open Access Journals (Sweden)

Avantika Mor

2015-12-01

Full Text Available ABSTRACT Early embryonic mortality is one of the main sources of reproductive wastages and major constraints for full exploitation of the production potential of livestock. The survivality of embryo during early embryonic life is mostly dependent on the efficiency with which the maternal recognition of pregnancy (MRP is established. Maternal recognition of pregnancy involves molecular dialogue between the trophoblast of conceptus and uterine endometrium. Embryonic development to the blastocyst stage and uterine differentiation to the receptive environment are crucial for successful establishment of the embryo-uterine cross-talk that leads to the initiation and progression of successful implantation. Unravelling the complex intricate molecular and cellular dialogues between the conceptus and uterine environment will facilitate development of strategies to augment early embryo survivality.

Molecular profiling of childhood cancer: Biomarkers and novel therapies

Directory of Open Access Journals (Sweden)

Federica Saletta

2014-06-01

General significance: The increasing recognition of the heterogeneity of molecular causes of cancer favors the continued development of molecularly targeted agents, and their transfer to pediatric and adolescent populations.

Facial expression recognition in the wild based on multimodal texture features

Science.gov (United States)

Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

2016-11-01

Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

Two dimensional molecular electronics spectroscopy for molecular fingerprinting, DNA sequencing, and cancerous DNA recognition.

Science.gov (United States)

Rajan, Arunkumar Chitteth; Rezapour, Mohammad Reza; Yun, Jeonghun; Cho, Yeonchoo; Cho, Woo Jong; Min, Seung Kyu; Lee, Geunsik; Kim, Kwang S

2014-02-25

Laser-driven molecular spectroscopy of low spatial resolution is widely used, while electronic current-driven molecular spectroscopy of atomic scale resolution has been limited because currents provide only minimal information. However, electron transmission of a graphene nanoribbon on which a molecule is adsorbed shows molecular fingerprints of Fano resonances, i.e., characteristic features of frontier orbitals and conformations of physisorbed molecules. Utilizing these resonance profiles, here we demonstrate two-dimensional molecular electronics spectroscopy (2D MES). The differential conductance with respect to bias and gate voltages not only distinguishes different types of nucleobases for DNA sequencing but also recognizes methylated nucleobases which could be related to cancerous cell growth. This 2D MES could open an exciting field to recognize single molecule signatures at atomic resolution. The advantages of the 2D MES over the one-dimensional (1D) current analysis can be comparable to those of 2D NMR over 1D NMR analysis.

Gliding and Saccadic Gaze Gesture Recognition in Real Time

DEFF Research Database (Denmark)

Rozado, David; San Agustin, Javier; Rodriguez, Francisco

2012-01-01

, and their corresponding real-time recognition algorithms, Hierarchical Temporal Memory networks and the Needleman-Wunsch algorithm for sequence alignment. Our results show how a specific combination of gaze gesture modality, namely saccadic gaze gestures, and recognition algorithm, Needleman-Wunsch, allows for reliable...... usage of intentional gaze gestures to interact with a computer with accuracy rates of up to 98% and acceptable completion speed. Furthermore, the gesture recognition engine does not interfere with otherwise standard human-machine gaze interaction generating therefore, very low false positive rates...

Molecularly Imprinted Membranes

Science.gov (United States)

Trotta, Francesco; Biasizzo, Miriam; Caldera, Fabrizio

2012-01-01

Although the roots of molecularly imprinted polymers lie in the beginning of 1930s in the past century, they have had an exponential growth only 40–50 years later by the works of Wulff and especially by Mosbach. More recently, it was also proved that molecular imprinted membranes (i.e., polymer thin films) that show recognition properties at molecular level of the template molecule are used in their formation. Different procedures and potential application in separation processes and catalysis are reported. The influences of different parameters on the discrimination abilities are also discussed. PMID:24958291

A Knowledge-driven Approach to Composite Activity Recognition in Smart Environments

OpenAIRE

Chen, Liming; Wang, H.; Sterritt, Roy; Okeyo, George

2012-01-01

Knowledge-driven activity recognition has recently attracted increasing attention but mainly focused on simple activities. This paper extends previous work to introduce a knowledge-driven approach to recognition of composite activities such as interleaved and concurrent activities. The approach combines ontological and temporal knowledge modelling formalisms for composite activity modelling. It exploits ontological reasoning for simple activity recognition and rule-based temporal inference to...

Biopolymeric receptor for peptide recognition by molecular imprinting approach—Synthesis, characterization and application

International Nuclear Information System (INIS)

Singh, Lav Kumar; Singh, Monika; Singh, Meenakshi

2014-01-01

The present work is focused on the development of a biocompatible zwitterionic hydrogel for various applications in analytical chemistry. Biopolymer chitosan was derivatized to obtain a series of zwitterionic hydrogel samples. Free amino groups hanging on the biopolymeric chain were reacted with γ-butyrolactone to quaternize the N-centers of polymeric chain. N,N-methylene-bis-acrylamide acts as a crosslinker via Michael-type addition in the subsequent step and facilitated gelation of betainized chitosan. These biopolymeric hydrogel samples were fully characterized by FTIR, 1 H NMR, 13 C NMR spectra, SEM and XRD. Hydrogels were further characterized for their swelling behavior at varying parameters. The extent of swelling was perceived to be dictated by solvent composition such as pH, ionic strength and temperature. This valuable polymeric format is herein chosen to design an artificial receptor for dipeptide ‘carnosine’, which has adequate societal significance to be analytically determined, by molecular imprinting. Electrostatic interactions along with complementary H-bonding and other hydrophobic interactions inducing additional synergetic effect between the template (carnosine) and the imprinted polymer led to the formation of imprinted sites. The MIP was able to selectively and specifically take up carnosine from aqueous solution quantitatively. Thus prepared MIPs were characterized by FTIR spectroscopy, SEM providing evidence for the quality and quantity of imprinted gels. The binding studies showed that the MIP illustrated good recognition for carnosine as compared to non-imprinted polymers (NIPs). Detection limit was estimated as 3.3 μg mL −1 . Meanwhile, selectivity experiments demonstrated that imprinted gel had a high affinity to carnosine in the presence of close structural analogues (interferrants). - Highlights: • Development of a biocompatible zwitterionic hydrogel • A series of chitosan-derived zwitterionic hydrogel samples • Polymeric

Page Recognition: Quantum Leap In Recognition Technology

Science.gov (United States)

Miller, Larry

1989-07-01

No milestone has proven as elusive as the always-approaching "year of the LAN," but the "year of the scanner" might claim the silver medal. Desktop scanners have been around almost as long as personal computers. And everyone thinks they are used for obvious desktop-publishing and business tasks like scanning business documents, magazine articles and other pages, and translating those words into files your computer understands. But, until now, the reality fell far short of the promise. Because it's true that scanners deliver an accurate image of the page to your computer, but the software to recognize this text has been woefully disappointing. Old optical-character recognition (OCR) software recognized such a limited range of pages as to be virtually useless to real users. (For example, one OCR vendor specified 12-point Courier font from an IBM Selectric typewriter: the same font in 10-point, or from a Diablo printer, was unrecognizable!) Computer dealers have told me the chasm between OCR expectations and reality is so broad and deep that nine out of ten prospects leave their stores in disgust when they learn the limitations. And this is a very important, very unfortunate gap. Because the promise of recognition -- what people want it to do -- carries with it tremendous improvements in our productivity and ability to get tons of written documents into our computers where we can do real work with it. The good news is that a revolutionary new development effort has led to the new technology of "page recognition," which actually does deliver the promise we've always wanted from OCR. I'm sure every reader appreciates the breakthrough represented by the laser printer and page-makeup software, a combination so powerful it created new reasons for buying a computer. A similar breakthrough is happening right now in page recognition: the Macintosh (and, I must admit, other personal computers) equipped with a moderately priced scanner and OmniPage software (from Caere

Tunneling of electrons via rotor–stator molecular interfaces: Combined ab initio and model study

Energy Technology Data Exchange (ETDEWEB)

Petreska, Irina, E-mail: irina.petreska@pmf.ukim.mk [Institute of Physics, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University, PO Box 162, 1000 Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of); Ohanesjan, Vladimir [Institute of Physics, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University, PO Box 162, 1000 Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of); Pejov, Ljupčo [Institute of Chemistry, Department of Physical Chemistry, Ss. Cyril and Methodius University, Arhimedova 5, P.O. Box 162, 1000 Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of); Kocarev, Ljupčo [Macedonian Academy of Sciences and Arts, Krste Misirkov 2, PO Box 428, 1000 Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of); Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of)

2016-07-01

Tunneling of electrons through rotor–stator anthracene aldehyde molecular interfaces is studied with a combined ab initio and model approach. Molecular electronic structure calculated from first principles is utilized to model different shapes of tunneling barriers. Together with a rectangular barrier, we also consider a sinusoidal shape that captures the effects of the molecular internal structure more realistically. Quasiclassical approach with the Simmons’ formula for current density is implemented. Special attention is paid on conformational dependence of the tunneling current. Our results confirm that the presence of the side aldehyde group enhances the interesting electronic properties of the pure anthracene molecule, making it a bistable system with geometry dependent transport properties. We also investigate the transition voltage and we show that conformation-dependent field emission could be observed in these molecular interfaces at realistically low voltages. The present study accompanies our previous work where we investigated the coherent transport via strongly coupled delocalized orbital by application of Non-equilibrium Green’s Function Formalism.

Object recognition with hierarchical discriminant saliency networks.

Science.gov (United States)

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

ICT-Isomerization-Induced Turn-On Fluorescence Probe with a Large Emission Shift for Mercury Ion: Application in Combinational Molecular Logic.

Science.gov (United States)

Bhatta, Sushil Ranjan; Mondal, Bijan; Vijaykumar, Gonela; Thakur, Arunabha

2017-10-02

A unique turn-on fluorescent device based on a ferrocene-aminonaphtholate derivative specific for Hg 2+ cation was developed. Upon binding with Hg 2+ ion, the probe shows a dramatic fluorescence enhancement (the fluorescence quantum yield increases 58-fold) along with a large red shift of 68 nm in the emission spectrum. The fluorescence enhancement with a red shift may be ascribed to the combinational effect of C═N isomerization and an extended intramolecular charge transfer (ICT) mechanism. The response was instantaneous with a detection limit of 2.7 × 10 -9 M. Upon Hg 2+ recognition, the ferrocene/ferrocenium redox peak was anodically shifted by ΔE 1/2 = 72 mV along with a "naked eye" color change from faint yellow to pale orange for this metal cation. Further, upon protonation of the imine nitrogen, the present probe displays a high fluorescence output due to suppression of the C═N isomerization process. Upon deprotonation using strong base, the fluorescence steadily decreases, which indicates that H + and OH - can be used to regulate the off-on-off fluorescence switching of the present probe. Density functional theory studies revealed that the addition of acid leads to protonation of the imine N (according to natural bond orbital analysis), and the resulting iminium proton forms a strong H-bond (2.307 Å) with one of the triazole N atoms to form a five-membered ring, which makes the molecule rigid; hence, enhancement of the ICT process takes place, thereby leading to a fluorescence enhancement with a red shift. The unprecedented combination of H + , OH - , and Hg 2+ ions has been used to generate a molecular system exhibiting the INHIBIT-OR combinational logic operation.

Fast screening of ketamine in biological samples based on molecularly imprinted photonic hydrogels

International Nuclear Information System (INIS)

Meng, Liang; Meng, Pinjia; Zhang, Qingqing; Wang, Yanji

2013-01-01

Graphical abstract: A novel label-free colorimetric chemosensor: with the increase in the concentration of ketamine, the Bragg diffraction peak of MIPHs gradually shifted to the longer wavelength region. Accompanying the peak shift, the color change of MIPHs was also observed obviously: from green to red. Highlights: ► We developed the label-free colorimetric MIPHs for handy and fast screening of ketamine. ► The obvious color change of MIPHs was observed upon ketamine. ► The MIPHs exhibited good sensing abilities in an aqueous environment. ► The sensing mechanisms of the water-compatible MIPHs were investigated. ► The MIPHs were employed to screening ketamine in real biological samples. -- Abstract: A novel label-free colorimetric chemosensor was developed for handy and fast screening of ketamine with high sensitivity and specificity based on molecularly imprinted photonic hydrogels (MIPHs) that combined the colloidal-crystal with molecular imprinting technique. The unique inverse opal arrays with a thin polymer wall in which the imprinted nanocavities of ketamine moleculars distributed allowed high sensitive, quick responsive, specific detection of the target analyte, and good regenerating ability in an aqueous environment. Due to the hierarchical inverse opal structural characteristics, the specific ketamine molecular recognition process can induce obvious swelling of the MIPHs to be directly transferred into visually perceptible optical signal (change in color) which can be detected by the naked eye through Bragg diffractive shifts of ordered macroporous arrays. In order to enhance the recognition ability in aqueous environments, the MIPHs were designed as water-compatible and synthesized in a water–methanol system. The molecular recognition mechanisms were investigated. The proposed MIPHs were successfully employed to screen trace level ketamine in human urine and saliva samples, exhibiting high sensitivity, rapid response, and specificity in the

Fast screening of ketamine in biological samples based on molecularly imprinted photonic hydrogels

Energy Technology Data Exchange (ETDEWEB)

Meng, Liang [Department of Forensic Science, People' s Public Security University of China, Beijing (China); Meng, Pinjia, E-mail: mengpinjia@163.com [Department of Forensic Science, People' s Public Security University of China, Beijing (China); Zhang, Qingqing; Wang, Yanji [Department of Forensic Science, People' s Public Security University of China, Beijing (China)

2013-04-10

Graphical abstract: A novel label-free colorimetric chemosensor: with the increase in the concentration of ketamine, the Bragg diffraction peak of MIPHs gradually shifted to the longer wavelength region. Accompanying the peak shift, the color change of MIPHs was also observed obviously: from green to red. Highlights: ► We developed the label-free colorimetric MIPHs for handy and fast screening of ketamine. ► The obvious color change of MIPHs was observed upon ketamine. ► The MIPHs exhibited good sensing abilities in an aqueous environment. ► The sensing mechanisms of the water-compatible MIPHs were investigated. ► The MIPHs were employed to screening ketamine in real biological samples. -- Abstract: A novel label-free colorimetric chemosensor was developed for handy and fast screening of ketamine with high sensitivity and specificity based on molecularly imprinted photonic hydrogels (MIPHs) that combined the colloidal-crystal with molecular imprinting technique. The unique inverse opal arrays with a thin polymer wall in which the imprinted nanocavities of ketamine moleculars distributed allowed high sensitive, quick responsive, specific detection of the target analyte, and good regenerating ability in an aqueous environment. Due to the hierarchical inverse opal structural characteristics, the specific ketamine molecular recognition process can induce obvious swelling of the MIPHs to be directly transferred into visually perceptible optical signal (change in color) which can be detected by the naked eye through Bragg diffractive shifts of ordered macroporous arrays. In order to enhance the recognition ability in aqueous environments, the MIPHs were designed as water-compatible and synthesized in a water–methanol system. The molecular recognition mechanisms were investigated. The proposed MIPHs were successfully employed to screen trace level ketamine in human urine and saliva samples, exhibiting high sensitivity, rapid response, and specificity in the

Fast cat-eye effect target recognition based on saliency extraction

Science.gov (United States)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

Background complexity is a main reason that results in false detection in cat-eye target recognition. Human vision has selective attention property which can help search the salient target from complex unknown scenes quickly and precisely. In the paper, we propose a novel cat-eye effect target recognition method named Multi-channel Saliency Processing before Fusion (MSPF). This method combines traditional cat-eye target recognition with the selective characters of visual attention. Furthermore, parallel processing enables it to achieve fast recognition. Experimental results show that the proposed method performs better in accuracy, robustness and speed compared to other methods.

Chinese License Plates Recognition Method Based on A Robust and Efficient Feature Extraction and BPNN Algorithm

Science.gov (United States)

Zhang, Ming; Xie, Fei; Zhao, Jing; Sun, Rui; Zhang, Lei; Zhang, Yue

2018-04-01

The prosperity of license plate recognition technology has made great contribution to the development of Intelligent Transport System (ITS). In this paper, a robust and efficient license plate recognition method is proposed which is based on a combined feature extraction model and BPNN (Back Propagation Neural Network) algorithm. Firstly, the candidate region of the license plate detection and segmentation method is developed. Secondly, a new feature extraction model is designed considering three sets of features combination. Thirdly, the license plates classification and recognition method using the combined feature model and BPNN algorithm is presented. Finally, the experimental results indicate that the license plate segmentation and recognition both can be achieved effectively by the proposed algorithm. Compared with three traditional methods, the recognition accuracy of the proposed method has increased to 95.7% and the consuming time has decreased to 51.4ms.

Molecularly Imprinted Nanomaterials for Sensor Applications

Science.gov (United States)

Irshad, Muhammad; Iqbal, Naseer; Mujahid, Adnan; Afzal, Adeel; Hussain, Tajamal; Sharif, Ahsan; Ahmad, Ejaz; Athar, Muhammad Makshoof

2013-01-01

Molecular imprinting is a well-established technology to mimic antibody-antigen interaction in a synthetic platform. Molecularly imprinted polymers and nanomaterials usually possess outstanding recognition capabilities. Imprinted nanostructured materials are characterized by their small sizes, large reactive surface area and, most importantly, with rapid and specific analysis of analytes due to the formation of template driven recognition cavities within the matrix. The excellent recognition and selectivity offered by this class of materials towards a target analyte have found applications in many areas, such as separation science, analysis of organic pollutants in water, environmental analysis of trace gases, chemical or biological sensors, biochemical assays, fabricating artificial receptors, nanotechnology, etc. We present here a concise overview and recent developments in nanostructured imprinted materials with respect to various sensor systems, e.g., electrochemical, optical and mass sensitive, etc. Finally, in light of recent studies, we conclude the article with future perspectives and foreseen applications of imprinted nanomaterials in chemical sensors. PMID:28348356

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

Science.gov (United States)

2010-01-01

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

Object recognition memory: neurobiological mechanisms of encoding, consolidation and retrieval.

Science.gov (United States)

Winters, Boyer D; Saksida, Lisa M; Bussey, Timothy J

2008-07-01

Tests of object recognition memory, or the judgment of the prior occurrence of an object, have made substantial contributions to our understanding of the nature and neurobiological underpinnings of mammalian memory. Only in recent years, however, have researchers begun to elucidate the specific brain areas and neural processes involved in object recognition memory. The present review considers some of this recent research, with an emphasis on studies addressing the neural bases of perirhinal cortex-dependent object recognition memory processes. We first briefly discuss operational definitions of object recognition and the common behavioural tests used to measure it in non-human primates and rodents. We then consider research from the non-human primate and rat literature examining the anatomical basis of object recognition memory in the delayed nonmatching-to-sample (DNMS) and spontaneous object recognition (SOR) tasks, respectively. The results of these studies overwhelmingly favor the view that perirhinal cortex (PRh) is a critical region for object recognition memory. We then discuss the involvement of PRh in the different stages--encoding, consolidation, and retrieval--of object recognition memory. Specifically, recent work in rats has indicated that neural activity in PRh contributes to object memory encoding, consolidation, and retrieval processes. Finally, we consider the pharmacological, cellular, and molecular factors that might play a part in PRh-mediated object recognition memory. Recent studies in rodents have begun to indicate the remarkable complexity of the neural substrates underlying this seemingly simple aspect of declarative memory.

Threshold models of recognition and the recognition heuristic

Directory of Open Access Journals (Sweden)

Edgar Erdfelder

2011-02-01

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

Formation of target-specific binding sites in enzymes: solid-phase molecular imprinting of HRP

Science.gov (United States)

Czulak, J.; Guerreiro, A.; Metran, K.; Canfarotta, F.; Goddard, A.; Cowan, R. H.; Trochimczuk, A. W.; Piletsky, S.

2016-05-01

Here we introduce a new concept for synthesising molecularly imprinted nanoparticles by using proteins as macro-functional monomers. For a proof-of-concept, a model enzyme (HRP) was cross-linked using glutaraldehyde in the presence of glass beads (solid-phase) bearing immobilized templates such as vancomycin and ampicillin. The cross-linking process links together proteins and protein chains, which in the presence of templates leads to the formation of permanent target-specific recognition sites without adverse effects on the enzymatic activity. Unlike complex protein engineering approaches commonly employed to generate affinity proteins, the method proposed can be used to produce protein-based ligands in a short time period using native protein molecules. These affinity materials are potentially useful tools especially for assays since they combine the catalytic properties of enzymes (for signaling) and molecular recognition properties of antibodies. We demonstrate this concept in an ELISA-format assay where HRP imprinted with vancomycin and ampicillin replaced traditional enzyme-antibody conjugates for selective detection of templates at micromolar concentrations. This approach can potentially provide a fast alternative to raising antibodies for targets that do not require high assay sensitivities; it can also find uses as a biochemical research tool, as a possible replacement for immunoperoxidase-conjugates.Here we introduce a new concept for synthesising molecularly imprinted nanoparticles by using proteins as macro-functional monomers. For a proof-of-concept, a model enzyme (HRP) was cross-linked using glutaraldehyde in the presence of glass beads (solid-phase) bearing immobilized templates such as vancomycin and ampicillin. The cross-linking process links together proteins and protein chains, which in the presence of templates leads to the formation of permanent target-specific recognition sites without adverse effects on the enzymatic activity. Unlike

Medicinal plant phytochemicals and their inhibitory activities against pancreatic lipase: molecular docking combined with molecular dynamics simulation approach.

Science.gov (United States)

Ahmed, Bilal; Ali Ashfaq, Usman; Usman Mirza, Muhammad

2018-05-01

Obesity is the worst health risk worldwide, which is linked to a number of diseases. Pancreatic lipase is considered as an affective cause of obesity and can be a major target for controlling the obesity. The present study was designed to find out best phytochemicals against pancreatic lipase through molecular docking combined with molecular dynamics (MD) simulation. For this purpose, a total of 3770 phytochemicals were docked against pancreatic lipase and ranked them on the basis of binding affinity. Finally, 10 molecules (Kushenol K, Rosmarinic acid, Reserpic acid, Munjistin, Leachianone G, Cephamycin C, Arctigenin, 3-O-acetylpadmatin, Geniposide and Obtusin) were selected that showed strong bonding with the pancreatic lipase. MD simulations were performed on top five compounds using AMBER16. The simulated complexes revealed stability and ligands remained inside the binding pocket. This study concluded that these finalised molecules can be used as drug candidate to control obesity.

Utterance independent bimodal emotion recognition in spontaneous communication

Science.gov (United States)

Tao, Jianhua; Pan, Shifeng; Yang, Minghao; Li, Ya; Mu, Kaihui; Che, Jianfeng

2011-12-01

Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition. This article introduces the methods of reducing the utterance influences in visual parameters for the audio-visual-based emotion recognition. The audio and visual channels are first combined under a Multistream Hidden Markov Model (MHMM). Then, the utterance reduction is finished by finding the residual between the real visual parameters and the outputs of the utterance related visual parameters. This article introduces the Fused Hidden Markov Model Inversion method which is trained in the neutral expressed audio-visual corpus to solve the problem. To reduce the computing complexity the inversion model is further simplified to a Gaussian Mixture Model (GMM) mapping. Compared with traditional bimodal emotion recognition methods (e.g., SVM, CART, Boosting), the utterance reduction method can give better results of emotion recognition. The experiments also show the effectiveness of our emotion recognition system when it was used in a live environment.

Fingerprint recognition system by use of graph matching

Science.gov (United States)

Shen, Wei; Shen, Jun; Zheng, Huicheng

2001-09-01

Fingerprint recognition is an important subject in biometrics to identify or verify persons by physiological characteristics, and has found wide applications in different domains. In the present paper, we present a finger recognition system that combines singular points and structures. The principal steps of processing in our system are: preprocessing and ridge segmentation, singular point extraction and selection, graph representation, and finger recognition by graphs matching. Our fingerprint recognition system is implemented and tested for many fingerprint images and the experimental result are satisfactory. Different techniques are used in our system, such as fast calculation of orientation field, local fuzzy dynamical thresholding, algebraic analysis of connections and fingerprints representation and matching by graphs. Wed find that for fingerprint database that is not very large, the recognition rate is very high even without using a prior coarse category classification. This system works well for both one-to-few and one-to-many problems.

PKC-epsilon activation is required for recognition memory in the rat.

Science.gov (United States)

Zisopoulou, Styliani; Asimaki, Olga; Leondaritis, George; Vasilaki, Anna; Sakellaridis, Nikos; Pitsikas, Nikolaos; Mangoura, Dimitra

2013-09-15

Activation of PKCɛ, an abundant and developmentally regulated PKC isoform in the brain, has been implicated in memory throughout life and across species. Yet, direct evidence for a mechanistic role for PKCɛ in memory is still lacking. Hence, we sought to evaluate this in rats, using short-term treatments with two PKCɛ-selective peptides, the inhibitory ɛV1-2 and the activating ψɛRACK, and the novel object recognition task (NORT). Our results show that the PKCɛ-selective activator ψɛRACK, did not have a significant effect on recognition memory. In the short time frames used, however, inhibition of PKCɛ activation with the peptide inhibitor ɛV1-2 significantly impaired recognition memory. Moreover, when we addressed at the molecular level the immediate proximal signalling events of PKCɛ activation in acutely dissected rat hippocampi, we found that ψɛRACK increased in a time-dependent manner phosphorylation of MARCKS and activation of Src, Raf, and finally ERK1/2, whereas ɛV1-2 inhibited all basal activity of this pathway. Taken together, these findings present the first direct evidence that PKCɛ activation is an essential molecular component of recognition memory and point toward the use of systemically administered PKCɛ-regulating peptides as memory study tools and putative therapeutic agents. Copyright © 2013 Elsevier B.V. All rights reserved.

Recognition of social identity in ants

Directory of Open Access Journals (Sweden)

Nick eBos

2012-03-01

Full Text Available Recognizing the identity of others, from the individual to the group level, is a hallmark of society. Ants, and other social insects, have evolved advanced societies characterized by efficient social recognition systems. Colony identity is mediated by colony specific signature mixtures, a blend of hydrocarbons present on the cuticle of every individual (the label. Recognition occurs when an ant encounters another individual, and compares the label it perceives to an internal representation of its own colony odor (the template. A mismatch between label and template leads to rejection of the encountered individual. Although advances have been made in our understanding of how the label is produced and acquired, contradictory evidence exists about information processing of recognition cues. Here, we review the literature on template acquisition in ants and address how and when the template is formed, where in the nervous system it is localized, and the possible role of learning. We combine seemingly contradictory evidence in to a novel, parsimonious theory for the information processing of nestmate recognition cues.

Episodic Short-Term Recognition Requires Encoding into Visual Working Memory: Evidence from Probe Recognition after Letter Report.

Science.gov (United States)

Poth, Christian H; Schneider, Werner X

2016-01-01

Human vision is organized in discrete processing episodes (e.g., eye fixations or task-steps). Object information must be transmitted across episodes to enable episodic short-term recognition: recognizing whether a current object has been seen in a previous episode. We ask whether episodic short-term recognition presupposes that objects have been encoded into capacity-limited visual working memory (VWM), which retains visual information for report. Alternatively, it could rely on the activation of visual features or categories that occurs before encoding into VWM. We assessed the dependence of episodic short-term recognition on VWM by a new paradigm combining letter report and probe recognition. Participants viewed displays of 10 letters and reported as many as possible after a retention interval (whole report). Next, participants viewed a probe letter and indicated whether it had been one of the 10 letters (probe recognition). In Experiment 1, probe recognition was more accurate for letters that had been encoded into VWM (reported letters) compared with non-encoded letters (non-reported letters). Interestingly, those letters that participants reported in their whole report had been near to one another within the letter displays. This suggests that the encoding into VWM proceeded in a spatially clustered manner. In Experiment 2, participants reported only one of 10 letters (partial report) and probes either referred to this letter, to letters that had been near to it, or far from it. Probe recognition was more accurate for near than for far letters, although none of these letters had to be reported. These findings indicate that episodic short-term recognition is constrained to a small number of simultaneously presented objects that have been encoded into VWM.

Episodic Short-Term Recognition Requires Encoding into Visual Working Memory: Evidence from Probe Recognition after Letter Report

Directory of Open Access Journals (Sweden)

Christian H. Poth

2016-09-01

Full Text Available Human vision is organized in discrete processing episodes (e.g. eye fixations or task-steps. Object information must be transmitted across episodes to enable episodic short-term recognition: recognizing whether a current object has been seen in a previous episode. We ask whether episodic short-term recognition presupposes that objects have been encoded into capacity-limited visual working memory (VWM, which retains visual information for report. Alternatively, it could rely on the activation of visual features or categories that occurs before encoding into VWM. We assessed the dependence of episodic short-term recognition on VWM by a new paradigm combining letter report and probe recognition. Participants viewed displays of ten letters and reported as many as possible after a retention interval (whole report. Next, participants viewed a probe letter and indicated whether it had been one of the ten letters (probe recognition. In Experiment 1, probe recognition was more accurate for letters that had been encoded into VWM (reported letters compared with non-encoded letters (non-reported letters. Interestingly, those letters that participants reported in their whole report had been near to one another within the letter displays. This suggests that the encoding into VWM proceeded in a spatially clustered manner. In Experiment 2 participants reported only one of ten letters (partial report and probes either referred to this letter, to letters that had been near to it, or far from it. Probe recognition was more accurate for near than for far letters, although none of these letters had to be reported. These findings indicate that episodic short-term recognition is constrained to a small number of simultaneously presented objects that have been encoded into VWM.

The combination of novel targeted molecular agents and radiation in the treatment of pediatric gliomas

Directory of Open Access Journals (Sweden)

Tina eDasgupta

2013-05-01

Full Text Available Brain tumors are the most common solid pediatric malignancy. For high-grade, recurrent or refractory pediatric brain tumors, radiation therapy (XRT is an integral treatment modality. In the era of personalized cancer therapy, molecularly targeted agents have been designed to inhibit pathways critical to tumorigenesis. Our evolving knowledge of genetic aberrations in low-grade gliomas is being exploited with targeted inhibitors. These agents are also being combined with XRT to increase their efficacy. In this review, we discuss novel agents targeting three different pathways in low-grade gliomas, and their potential combination with XRT. B-Raf is a kinase in the Ras/Raf/MAPK kinase pathway, which is integral to cellular division, survival and metabolism. In low-grade pediatric gliomas, point mutations in BRAF (BRAF V600E or a BRAF fusion mutation (KIAA1549:BRAF causes overactivation of the MEK/MAPK pathway. Pre-clinical data shows cooperation between XRT and tagrgeted inhibitors of BRAF V600E, and MEK and mTOR inhibitors in the gliomas with the BRAF fusion. A second important signaling cascade in pediatric glioma pathogenesis is the PI3 kinase (PI3K/mTOR pathway. Dual PI3K/mTOR inhibitors are poised to enter studies of pediatric tumors. Finally, many brain tumors express potent stimulators of angiogenesis. Several inhibitors of immunomodulators are currently being evaluated in in clinical trials for the treatment of recurrent or refractory pediatric central nervous system (CNS tumors. In summary, combinations of these targeted inhibitors with radiation are currently under investigation in both translational bench research and early clinical trials. We summarize the molecular rationale for, and the pre-clinical data supporting the combinations of these targeted agents with other anti-cancer agents and XRT in pediatric gliomas. Parallels are drawn to adult gliomas, and the molecular mechanisms underlying the efficacy of these agents is discussed

A Unified Approach to the Recognition of Complex Actions from Sequences of Zone-Crossings

NARCIS (Netherlands)

Sanromà, G.; Patino, L.; Burghouts, G.J.; Schutte, K.; Ferryman, J.

2014-01-01

We present a method for the recognition of complex actions. Our method combines automatic learning of simple actions and manual definition of complex actions in a single grammar. Contrary to the general trend in complex action recognition, that consists in dividing recognition into two stages, our

Charged hydrogels for post-loading, release, and molecular imprinting of proteins

NARCIS (Netherlands)

Schillemans, J.P.|info:eu-repo/dai/nl/304835137

2010-01-01

Molecular imprinting is a technique to create template-shaped cavities in polymer matrices with memory of the template molecules, to be used in molecular recognition. Molecular imprinting of low molecular weight compounds is a well established technique used to create high affinity materials. On the

Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

2018-01-01

Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However, this method has not been widely explored...... in combination with deep convolutional neural network based RGB-D object recognition models. Hence, in this paper, we form different ensembles of complementary deep convolutional neural network models, and show that this can be used to increase the recognition performance beyond existing limits. Experiments...

Imprinted electrochemical sensor for dopamine recognition and determination based on a carbon nanotube/polypyrrole film

International Nuclear Information System (INIS)

Kan Xianwen; Zhou Hong; Li Chen; Zhu Anhong; Xing Zonglan; Zhao Zhe

2012-01-01

An electrochemical sensor combining a molecular imprinted technique and an electropolymerization method was developed in this work. A molecular imprinted polymer (MIP) film was fabricated by electropolymerizing pyrrole in the presence of dopamine (DA) after electrodepositing carboxyl-functionalized multi-walled carbon nanotubes (MWNTs-COOH) onto a glassy carbon electrode (GCE) surface. Scanning electron microscopy (SEM), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS) were employed to characterize the constructed sensor. The effects of pH, the monomer concentration, the number of cycles for the electropolymerization, and the scan rate for the sensor preparation were optimized. The MIP-based sensor displayed an excellent recognition capacity toward DA compared with other structurally similar molecules. Additionally, the DPV peak current was linear to the DA concentration in the range from 6.25 × 10 −7 to 1 × 10 −4 mol/L, with a detection limit of 6 × 10 −8 mol/L. The prepared sensor also showed stable reproducibility and regeneration capacity.

A bacterial tyrosine phosphatase inhibits plant pattern recognition receptor activation

Science.gov (United States)

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...

Stigma-pollen recognition: a new look

Directory of Open Access Journals (Sweden)

C. Dumas

2014-01-01

Full Text Available During the last two decades, there have been several conceptual developments in our understanding of pollen-stigma recognition and molecular mechanisms involved. The main models proposed are compared. Based on additional data a hypothesis to complete these models especially for pollen hydration and adhesion is proposed. After attachment of the pollen to the stigma surface a close interaction exists involving lipoproteic membrane-like compounds (pollenkitt and stigma pellicle and pollen agglutinating ability.

Computational Design of Molecularly Imprinted Polymers

Science.gov (United States)

Subrahmanyam, Sreenath; Piletsky, Sergey A.

Artificial receptors have been in use for several decades as sensor elements, in affinity separation, and as models for investigation of molecular recognition. Although there have been numerous publications on the use of molecular modeling in characterization of their affinity and selectivity, very few attempts have been made on the application of molecular modeling in computational design of synthetic receptors. This chapter discusses recent successes in the use of computational design for the development of one particular branch of synthetic receptors - molecularly imprinted polymers.

Three-dimensional fingerprint recognition by using convolution neural network

Science.gov (United States)

Tian, Qianyu; Gao, Nan; Zhang, Zonghua

2018-01-01

With the development of science and technology and the improvement of social information, fingerprint recognition technology has become a hot research direction and been widely applied in many actual fields because of its feasibility and reliability. The traditional two-dimensional (2D) fingerprint recognition method relies on matching feature points. This method is not only time-consuming, but also lost three-dimensional (3D) information of fingerprint, with the fingerprint rotation, scaling, damage and other issues, a serious decline in robustness. To solve these problems, 3D fingerprint has been used to recognize human being. Because it is a new research field, there are still lots of challenging problems in 3D fingerprint recognition. This paper presents a new 3D fingerprint recognition method by using a convolution neural network (CNN). By combining 2D fingerprint and fingerprint depth map into CNN, and then through another CNN feature fusion, the characteristics of the fusion complete 3D fingerprint recognition after classification. This method not only can preserve 3D information of fingerprints, but also solves the problem of CNN input. Moreover, the recognition process is simpler than traditional feature point matching algorithm. 3D fingerprint recognition rate by using CNN is compared with other fingerprint recognition algorithms. The experimental results show that the proposed 3D fingerprint recognition method has good recognition rate and robustness.

Printed Persian Subword Recognition Using Wavelet Packet Descriptors

Directory of Open Access Journals (Sweden)

Samira Nasrollahi

2013-01-01

Full Text Available In this paper, we present a new approach to offline OCR (optical character recognition for printed Persian subwords using wavelet packet transform. The proposed algorithm is used to extract font invariant and size invariant features from 87804 subwords of 4 fonts and 3 sizes. The feature vectors are compressed using PCA. The obtained feature vectors yield a pictorial dictionary for which an entry is the mean of each group that consists of the same subword with 4 fonts in 3 sizes. The sets of these features are congregated by combining them with the dot features for the recognition of printed Persian subwords. To evaluate the feature extraction results, this algorithm was tested on a set of 2000 subwords in printed Persian text documents. An encouraging recognition rate of 97.9% is got at subword level recognition.

Chemical Entity Recognition and Resolution to ChEBI

Science.gov (United States)

Grego, Tiago; Pesquita, Catia; Bastos, Hugo P.; Couto, Francisco M.

2012-01-01

Chemical entities are ubiquitous through the biomedical literature and the development of text-mining systems that can efficiently identify those entities are required. Due to the lack of available corpora and data resources, the community has focused its efforts in the development of gene and protein named entity recognition systems, but with the release of ChEBI and the availability of an annotated corpus, this task can be addressed. We developed a machine-learning-based method for chemical entity recognition and a lexical-similarity-based method for chemical entity resolution and compared them with Whatizit, a popular-dictionary-based method. Our methods outperformed the dictionary-based method in all tasks, yielding an improvement in F-measure of 20% for the entity recognition task, 2–5% for the entity-resolution task, and 15% for combined entity recognition and resolution tasks. PMID:25937941

Selective separation of hydroxy polychlorinated biphenyls (HO-PCBs) by the structural recognition on the molecularly imprinted polymers: Direct separation of the thyroid hormone active analogues from mixtures

International Nuclear Information System (INIS)

Kubo, Takuya; Matsumoto, Hideyuki; Shiraishi, Fujio; Nomachi, Makoto; Nemoto, Koji; Hosoya, Ken; Kaya, Kunimitsu

2007-01-01

We developed novel separation media for hydroxy polychlorinated biphenyls (HO-PCBs) using the molecular imprinting techniques. The results of evaluation for the molecularly imprinted polymers (MIPs) by the liquid chromatography (LC) suggested that MIPs had selective separation ability for certain HO-PCB analogues. The results of the LC evaluations and molecular modeling indicated that the molecular volumes and pK a values of template molecules were related with the retention factor of HO-PCBs. Additionally, according to the detail evaluation toward the selective separation behaviors of MIPs, these HO-PCB analogues have low pK a values dependent on their chemical structures. In other words, the prepared MIPs had selective recognition ability against the analogues, which have an OH group on a phenyl carbon and two chlorine atoms on the both neighboring carbons of the carbon attached with the OH group. Moreover, these analogues may have a potential for thyroid hormone activities so that we attempted to separate these analogues directly from mixtures of HO-PCBs using a prepared MIP

Ficolins and FIBCD1: Soluble and membrane bound pattern recognition molecules with acetyl group selectivity

DEFF Research Database (Denmark)

Thomsen, Theresa; Schlosser, Anders; Holmskov, Uffe

2011-01-01

as pattern recognition molecules. Ficolins are soluble oligomeric proteins composed of trimeric collagen-like regions linked to fibrinogen-related domains (FReDs) that have the ability to sense molecular patterns on both pathogens and apoptotic cell surfaces and activate the complement system. The ficolins......D-containing molecules, and discusses structural resemblance but also diversity in recognition of acetylated ligands....

78 FR 21128 - Molecular Diagnostic Instruments With Combined Functions; Draft Guidance for Industry and Food...

Science.gov (United States)

2013-04-09

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2013-D-0258] Molecular Diagnostic Instruments With Combined Functions; Draft Guidance for Industry and Food and Drug Administration Staff; Availability AGENCY: Food and Drug Administration, HHS. ACTION: Notice. SUMMARY: The Food...

Mapping correspondence between facial mimicry and emotion recognition in healthy subjects.

Science.gov (United States)

Ponari, Marta; Conson, Massimiliano; D'Amico, Nunzia Pina; Grossi, Dario; Trojano, Luigi

2012-12-01

We aimed at verifying the hypothesis that facial mimicry is causally and selectively involved in emotion recognition. For this purpose, in Experiment 1, we explored the effect of tonic contraction of muscles in upper or lower half of participants' face on their ability to recognize emotional facial expressions. We found that the "lower" manipulation specifically impaired recognition of happiness and disgust, the "upper" manipulation impaired recognition of anger, while both manipulations affected recognition of fear; recognition of surprise and sadness were not affected by either blocking manipulations. In Experiment 2, we verified whether emotion recognition is hampered by stimuli in which an upper or lower half-face showing an emotional expression is combined with a neutral half-face. We found that the neutral lower half-face interfered with recognition of happiness and disgust, whereas the neutral upper half impaired recognition of anger; recognition of fear and sadness was impaired by both manipulations, whereas recognition of surprise was not affected by either manipulation. Taken together, the present findings support simulation models of emotion recognition and provide insight into the role of mimicry in comprehension of others' emotional facial expressions. PsycINFO Database Record (c) 2012 APA, all rights reserved.

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

Science.gov (United States)

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

2017-11-01

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

Molecularly imprinted polymers--potential and challenges in analytical chemistry

Energy Technology Data Exchange (ETDEWEB)

Mahony, J.O. [Dublin City University, School of Chemical Sciences, Glasnevin, Dublin 9 (Ireland); Nolan, K. [Dublin City University, School of Chemical Sciences, Glasnevin, Dublin 9 (Ireland); Smyth, M.R. [Dublin City University, School of Chemical Sciences, Glasnevin, Dublin 9 (Ireland); Mizaikoff, B. [Georgia Institute of Technology, School of Chemistry and Biochemistry, 770 State Street, Boggs Building, Atlanta, GA 30332-0400 (United States)]. E-mail: boris.mizaikoff@chemistry.gatech.edu

2005-04-04

Among the variety of biomimetic recognition schemes utilizing supramolecular approaches molecularly imprinted polymers (MIPs) have proven their potential as synthetic receptors in numerous applications ranging from liquid chromatography to assays and sensor technology. Their inherent advantages compared to biochemical/biological recognition systems include robustness, storage endurance and lower costs. However, until recently only few contributions throughout the relevant literature describe quantitative analytical applications of MIPs for practically relevant analyte molecules and real-world samples. Increased motivation to thoroughly evaluate the true potential of MIP technology is clearly attributed to the demands of modern analytical chemistry, which include enhanced sensitivity, selectivity and applicability of molecular recognition building blocks at decreasing costs. In particular, the areas of environmental monitoring, food and beverage analysis and industrial process surveillance require analytical tools capable of discriminating chemicals with high molecular specificity considering increasing numbers of complex environmental contaminants, pollution of raw products and rigorous quality control requested by legislation and consumer protection. Furthermore, efficient product improvement and development of new products requires precise qualitative and quantitative analytical methods. Finally, environmental, food and process safety control issues favor the application of on-line in situ analytical methods with high molecular selectivity. While biorecognition schemes frequently suffer from degrading bioactivity and long-term stability when applied in real-world sample environments, MIPs serving as synthetic antibodies have successfully been applied as stationary phase separation matrix (e.g. HPLC and SPE), recognition component in bioassays (e.g. ELISA) or biomimetic recognition layer in chemical sensor systems. Examples such as MIP-based selective analysis of

Molecularly imprinted polymers--potential and challenges in analytical chemistry

International Nuclear Information System (INIS)

Mahony, J.O.; Nolan, K.; Smyth, M.R.; Mizaikoff, B.

2005-01-01

Among the variety of biomimetic recognition schemes utilizing supramolecular approaches molecularly imprinted polymers (MIPs) have proven their potential as synthetic receptors in numerous applications ranging from liquid chromatography to assays and sensor technology. Their inherent advantages compared to biochemical/biological recognition systems include robustness, storage endurance and lower costs. However, until recently only few contributions throughout the relevant literature describe quantitative analytical applications of MIPs for practically relevant analyte molecules and real-world samples. Increased motivation to thoroughly evaluate the true potential of MIP technology is clearly attributed to the demands of modern analytical chemistry, which include enhanced sensitivity, selectivity and applicability of molecular recognition building blocks at decreasing costs. In particular, the areas of environmental monitoring, food and beverage analysis and industrial process surveillance require analytical tools capable of discriminating chemicals with high molecular specificity considering increasing numbers of complex environmental contaminants, pollution of raw products and rigorous quality control requested by legislation and consumer protection. Furthermore, efficient product improvement and development of new products requires precise qualitative and quantitative analytical methods. Finally, environmental, food and process safety control issues favor the application of on-line in situ analytical methods with high molecular selectivity. While biorecognition schemes frequently suffer from degrading bioactivity and long-term stability when applied in real-world sample environments, MIPs serving as synthetic antibodies have successfully been applied as stationary phase separation matrix (e.g. HPLC and SPE), recognition component in bioassays (e.g. ELISA) or biomimetic recognition layer in chemical sensor systems. Examples such as MIP-based selective analysis of

Static facial expression recognition with convolution neural networks

Science.gov (United States)

Zhang, Feng; Chen, Zhong; Ouyang, Chao; Zhang, Yifei

2018-03-01

Facial expression recognition is a currently active research topic in the fields of computer vision, pattern recognition and artificial intelligence. In this paper, we have developed a convolutional neural networks (CNN) for classifying human emotions from static facial expression into one of the seven facial emotion categories. We pre-train our CNN model on the combined FER2013 dataset formed by train, validation and test set and fine-tune on the extended Cohn-Kanade database. In order to reduce the overfitting of the models, we utilized different techniques including dropout and batch normalization in addition to data augmentation. According to the experimental result, our CNN model has excellent classification performance and robustness for facial expression recognition.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH; Yong-Wan; KIM; Dong-Ju; LEE; Woo-Seok; HONG; Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech.The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform(FFT) spectral entropy,delta FFT spectral entropy,Mel-frequency filter bank(MFB) spectral entropy,and Delta MFB spectral entropy.Spectral-based entropy features are simple.They reflect frequency characteristic and changing characteristic in frequency of speech.We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance.Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results,respectively.These scores are first obtained from a pattern recognition procedure.The pattern recognition phase uses the Gaussian mixture model(GMM).We classify the four emotional states as anger,sadness,happiness and neutrality.The proposed method is evaluated using 45 sentences in each emotion for 30 subjects,15 males and 15 females.Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy,Zero Crossing Rate(ZCR),linear prediction coefficient(LPC),and pitch parameters.We demonstrate the effectiveness of the proposed approach.One of the proposed features,combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods.We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech. The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform (FFT) spectral entropy, delta FFT spectral entropy, Mel-frequency filter bank (MFB)spectral entropy, and Delta MFB spectral entropy. Spectral-based entropy features are simple. They reflect frequency characteristic and changing characteristic in frequency of speech. We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance. Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results, respectively.These scores are first obtained from a pattern recognition procedure. The pattern recognition phase uses the Gaussian mixture model (GMM). We classify the four emotional states as anger, sadness,happiness and neutrality. The proposed method is evaluated using 45 sentences in each emotion for 30 subjects, 15 males and 15 females. Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy, Zero Crossing Rate (ZCR),linear prediction coefficient (LPC), and pitch parameters. We demonstrate the effectiveness of the proposed approach. One of the proposed features, combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods. We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Chiral Recognition in Molecular and Macromolecular Pairs of(S)- and (R)- 1-Cyano-2-Methylpropyl 4’((4-(8-Vinyloxyoctyloxy)Benzoyl) Biphenyl-4-Carboxylate Enantiomers

Science.gov (United States)

1994-06-30

above please provide a graphical abstract of the paper ar, return it to the Editorial Office as soon as possible. 4oeg0 o F-99S or TS A& I DTI•’ I J. u1...TCLSICAON 2.LIMITATION OF ABSTRAC •F oFPORT OF THIS PAGE OF ABSTRACT . unclass ified Graphical Abstracts for Perkin Txans. 1 Example TITLE GRAPHICAL ... ABSTRACT AUTHORS’ N AMES Template (S)-II Chiral recognition in molecular and . -- macromolecular pairs of (S)- and -- (R)-i-cyano-2-methyipropyl 4’-{[4

Pattern recognition

CERN Document Server

Theodoridis, Sergios

2003-01-01

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

A sensor and video based ontology for activity recognition in smart environments.

Science.gov (United States)

Mitchell, D; Morrow, Philip J; Nugent, Chris D

2014-01-01

Activity recognition is used in a wide range of applications including healthcare and security. In a smart environment activity recognition can be used to monitor and support the activities of a user. There have been a range of methods used in activity recognition including sensor-based approaches, vision-based approaches and ontological approaches. This paper presents a novel approach to activity recognition in a smart home environment which combines sensor and video data through an ontological framework. The ontology describes the relationships and interactions between activities, the user, objects, sensors and video data.

Combined, solid-state molecular property and gamma spectrometers for CBRNE detection

Science.gov (United States)

Rogers, Ben; Grate, Jay; Pearson, Brett; Gallagher, Neal; Wise, Barry; Whitten, Ralph; Adams, Jesse

2013-05-01

Nevada Nanotech Systems, Inc. (Nevada Nano) has developed a multi-sensor solution to Chemical, Biological, Radiological, Nuclear and Explosives (CBRNE) detection that combines the Molecular Property Spectrometer™ (MPS™)—a micro-electro-mechanical chip-based technology capable of measuring a variety of thermodynamic and electrostatic molecular properties of sampled vapors and particles—and a compact, high-resolution, solid-state gamma spectrometer module for identifying radioactive materials, including isotopes used in dirty bombs and nuclear weapons. By conducting multiple measurements, the system can provide a more complete characterization of an unknown sample, leading to a more accurate identification. Positive identifications of threats are communicated using an integrated wireless module. Currently, system development is focused on detection of commercial, military and improvised explosives, radioactive materials, and chemical threats. The system can be configured for a variety of CBRNE applications, including handheld wands and swab-type threat detectors requiring short sample times, and ultra-high sensitivity detectors in which longer sampling times are used. Here we provide an overview of the system design and operation and present results from preliminary testing.

Use of UV-vis-NIR spectroscopy to monitor label-free interaction between molecular recognition elements and erythropoietin on a gold-coated polycarbonate platform.

Science.gov (United States)

Citartan, Marimuthu; Gopinath, Subash C B; Tominaga, Junji; Chen, Yeng; Tang, Thean-Hock

2014-08-01

Label-free-based detection is pivotal for real-time monitoring of biomolecular interactions and to eliminate the need for labeling with tags that can occupy important binding sites of biomolecules. One simplest form of label-free-based detection is ultraviolet-visible-near-infrared (UV-vis-NIR) spectroscopy, which measure changes in reflectivity as a means to monitor immobilization and interaction of biomolecules with their corresponding partners. In biosensor development, the platform used for the biomolecular interaction should be suitable for different molecular recognition elements. In this study, gold (Au)-coated polycarbonate was used as a platform and as a proof-of-concept, erythropoietin (EPO), a doping substance widely abused by the athletes was used as the target. The interaction of EPO with its corresponding molecular recognition elements (anti-EPO monoclonal antibody and anti-EPO DNA aptamer) is monitored by UV-vis-NIR spectroscopy. Prior to this, to show that UV-vis-NIR spectroscopy is a suitable method for measuring biomolecular interaction, the interaction between biotin and streptavidin was demonstrated via this strategy and reflectivity of this interaction decreased by 25%. Subsequent to this, interaction of the EPO with anti-EPO monoclonal antibody and anti-EPO DNA aptamer resulted in the decrease of reflectivity by 5% and 10%, respectively. The results indicated that Au-coated polycarbonate could be an ideal biosensor platform for monitoring biomolecular interactions using UV-vis-NIR spectroscopy. A smaller version of the Au-coated polycarbonate substrates can be derived from the recent set-up, to be applied towards detecting EPO abuse among atheletes. Copyright © 2014 Elsevier B.V. All rights reserved.

Color constancy in 3D-2D face recognition

Science.gov (United States)

Meyer, Manuel; Riess, Christian; Angelopoulou, Elli; Evangelopoulos, Georgios; Kakadiaris, Ioannis A.

2013-05-01

Face is one of the most popular biometric modalities. However, up to now, color is rarely actively used in face recognition. Yet, it is well-known that when a person recognizes a face, color cues can become as important as shape, especially when combined with the ability of people to identify the color of objects independent of illuminant color variations. In this paper, we examine the feasibility and effect of explicitly embedding illuminant color information in face recognition systems. We empirically examine the theoretical maximum gain of including known illuminant color to a 3D-2D face recognition system. We also investigate the impact of using computational color constancy methods for estimating the illuminant color, which is then incorporated into the face recognition framework. Our experiments show that under close-to-ideal illumination estimates, one can improve face recognition rates by 16%. When the illuminant color is algorithmically estimated, the improvement is approximately 5%. These results suggest that color constancy has a positive impact on face recognition, but the accuracy of the illuminant color estimate has a considerable effect on its benefits.

A Robust Multimodal Bio metric Authentication Scheme with Voice and Face Recognition

International Nuclear Information System (INIS)

Kasban, H.

2017-01-01

This paper proposes a multimodal biometric scheme for human authentication based on fusion of voice and face recognition. For voice recognition, three categories of features (statistical coefficients, cepstral coefficients and voice timbre) are used and compared. The voice identification modality is carried out using Gaussian Mixture Model (GMM). For face recognition, three recognition methods (Eigenface, Linear Discriminate Analysis (LDA), and Gabor filter) are used and compared. The combination of voice and face biometrics systems into a single multimodal biometrics system is performed using features fusion and scores fusion. This study shows that the best results are obtained using all the features (cepstral coefficients, statistical coefficients and voice timbre features) for voice recognition, LDA face recognition method and scores fusion for the multimodal biometrics system

Facial Emotion Recognition Using Context Based Multimodal Approach

Directory of Open Access Journals (Sweden)

Priya Metri

2011-12-01

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

Action Recognition by Joint Spatial-Temporal Motion Feature

Directory of Open Access Journals (Sweden)

Weihua Zhang

2013-01-01

Full Text Available This paper introduces a method for human action recognition based on optical flow motion features extraction. Automatic spatial and temporal alignments are combined together in order to encourage the temporal consistence on each action by an enhanced dynamic time warping (DTW algorithm. At the same time, a fast method based on coarse-to-fine DTW constraint to improve computational performance without reducing accuracy is induced. The main contributions of this study include (1 a joint spatial-temporal multiresolution optical flow computation method which can keep encoding more informative motion information than recent proposed methods, (2 an enhanced DTW method to improve temporal consistence of motion in action recognition, and (3 coarse-to-fine DTW constraint on motion features pyramids to speed up recognition performance. Using this method, high recognition accuracy is achieved on different action databases like Weizmann database and KTH database.

Integrating Molecular Computation and Material Production in an Artificial Subcellular Matrix

DEFF Research Database (Denmark)

Fellermann, Harold; Hadorn, Maik; Bönzli, Eva

Living systems are unique in that they integrate molecular recognition and information processing with material production on the molecular scale. Pre- dominant locus of this integration is the cellular matrix, where a multitude of biochemical reactions proceed simultaneously in highly compartmen......Living systems are unique in that they integrate molecular recognition and information processing with material production on the molecular scale. Pre- dominant locus of this integration is the cellular matrix, where a multitude of biochemical reactions proceed simultaneously in highly...... compartmentalized re- action compartments that interact and get delivered through vesicle trafficking. The European Commission funded project MatchIT (Matrix for Chemical IT) aims at creating an artificial cellular matrix that seamlessly integrates infor- mation processing and material production in much the same...

The molecular mechanism of Zinc acquisition by the neisserial outer-membrane transporter ZnuD

Science.gov (United States)

Calmettes, Charles; Ing, Christopher; Buckwalter, Carolyn M.; El Bakkouri, Majida; Chieh-Lin Lai, Christine; Pogoutse, Anastassia; Gray-Owen, Scott D.; Pomès, Régis; Moraes, Trevor F.

2015-01-01

Invading bacteria from the Neisseriaceae, Acinetobacteriaceae, Bordetellaceae and Moraxellaceae families express the conserved outer-membrane zinc transporter zinc-uptake component D (ZnuD) to overcome nutritional restriction imposed by the host organism during infection. Here we demonstrate that ZnuD is required for efficient systemic infections by the causative agent of bacterial meningitis, Neisseria meningitidis, in a mouse model. We also combine X-ray crystallography and molecular dynamics simulations to gain insight into the mechanism of zinc recognition and transport across the bacterial outer-membrane by ZnuD. Because ZnuD is also considered a promising vaccine candidate against N. meningitidis, we use several ZnuD structural intermediates to map potential antigenic epitopes, and propose a mechanism by which ZnuD can maintain high sequence conservation yet avoid immune recognition by altering the conformation of surface-exposed loops. PMID:26282243

Robust Face Recognition by Computing Distances from Multiple Histograms of Oriented Gradients

NARCIS (Netherlands)

Karaaba, Mahir; Surinta, Olarik; Schomaker, Lambertus; Wiering, Marco

2015-01-01

The Single Sample per Person Problem is a challenging problem for face recognition algorithms. Patch-based methods have obtained some promising results for this problem. In this paper, we propose a new face recognition algorithm that is based on a combination of different histograms of oriented

Homeostasis-altering molecular processes as mechanisms of inflammasome activation.

Science.gov (United States)

Liston, Adrian; Masters, Seth L

2017-03-01

The innate immune system uses a distinct set of germline-encoded pattern recognition receptors (PRRs) to initiate downstream inflammatory cascades. This recognition system is in stark contrast to the adaptive immune system, which relies on highly variable, randomly generated antigen receptors. A key limitation of the innate immune system's reliance on fixed PRRs is its inflexibility in responding to rapidly evolving pathogens. Recent advances in our understanding of inflammasome activation suggest that the innate immune system also has sophisticated mechanisms for responding to pathogens for which there is no fixed PRR. This includes the recognition of debris from dying cells, known as danger-associated molecular patterns (DAMPs), which can directly activate PRRs in a similar manner to pathogen-associated molecular patterns (PAMPs). Distinct from this, emerging data for the inflammasome components NLRP3 (NOD-, LRR- and pyrin domain-containing 3) and pyrin suggest that they do not directly detect molecular patterns, but instead act as signal integrators that are capable of detecting perturbations in cytoplasmic homeostasis, for example, as initiated by infection. Monitoring these perturbations, which we term 'homeostasis-altering molecular processes' (HAMPs), provides potent flexibility in the capacity of the innate immune system to detect evolutionarily novel infections; however, HAMP sensing may also underlie the sterile inflammation that drives chronic inflammatory diseases.

Molecular basis for H3K36me3 recognition by the Tudor domain of PHF1

Science.gov (United States)

Musselman, Catherine A.; Avvakumov, Nikita; Watanabe, Reiko; Abraham, Christopher G.; Lalonde, Marie-Eve; Hong, Zehui; Allen, Christopher; Roy, Siddhartha; Nuñez, James K.; Nickoloff, Jac; Kulesza, Caroline A.; Yasui, Akira; Côté, Jacques; Kutateladze, Tatiana G.

2013-01-01

The PHD finger protein 1 (PHF1) is essential in epigenetic regulation and genome maintenance. Here, we demonstrate that the Tudor domain of human PHF1 binds to histone H3 trimethylated at Lys36 (H3K36me3). We report a 1.9 Å resolution crystal structure of the Tudor domain in complex with H3K36me3 and describe the molecular mechanism of H3K36me3 recognition using NMR analysis. Binding of PHF1 to H3K36me3 inhibits the ability of the Polycomb PRC2 complex to methylate H3K27 in vitro and in vivo. Laser micro-irradiation data reveal that PHF1 is transiently recruited to DNA double-strand breaks (DSBs), and PHF1 mutants impaired in the H3K36me3 interaction exhibit reduced retention at DSB sites. Together, our findings suggest that PHF1 can mediate deposition of the repressive H3K27me3 mark and acts as an early DNA damage response cofactor. PMID:23142980

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

Science.gov (United States)

2010-01-01

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

Artificial receptor-functionalized nanoshell: facile preparation, fast separation and specific protein recognition

Science.gov (United States)

Ouyang, Ruizhuo; Lei, Jianping; Ju, Huangxian

2010-05-01

This work combined molecular imprinting technology with superparamagnetic nanospheres as the core to prepare artificial receptor-functionalized magnetic nanoparticles for separation of homologous proteins. Using dopamine as a functional monomer, novel surface protein-imprinted superparamagnetic polydopamine (PDA) core-shell nanoparticles were successfully prepared in physiological conditions, which could maintain the natural structure of a protein template and achieved the development of molecularly imprinted polymers (MIPs) from one dimension to zero dimension for efficient recognition towards large biomolecules. The resultant nanoparticles could be used for convenient magnetic separation of homologous proteins with high specificity. The nanoparticles possessed good monodispersibility, uniform surface morphology and high saturation magnetization value. The bound amounts of template proteins measured by both indirect and direct methods were in good agreement. The maximum number of imprinted cavities on the surface of the bovine hemoglobin (Hb)-imprinted nanoshell was 2.21 × 1018 g - 1, which well matched their maximum binding capacity toward bovine Hb. Both the simple method for preparation of MIPs and the magnetic nanospheres showed good application potential in fast separation, effective concentration and selective biosensing of large protein molecules.

Artificial receptor-functionalized nanoshell: facile preparation, fast separation and specific protein recognition

Energy Technology Data Exchange (ETDEWEB)

Ouyang, Ruizhuo; Lei Jianping; Ju Huangxian, E-mail: jpl@nju.edu.cn, E-mail: hxju@nju.edu.cn [Key Laboratory of Analytical Chemistry for Life Science (Education Ministry of China), Department of Chemistry, Nanjing University, Nanjing 210093 (China)

2010-05-07

This work combined molecular imprinting technology with superparamagnetic nanospheres as the core to prepare artificial receptor-functionalized magnetic nanoparticles for separation of homologous proteins. Using dopamine as a functional monomer, novel surface protein-imprinted superparamagnetic polydopamine (PDA) core-shell nanoparticles were successfully prepared in physiological conditions, which could maintain the natural structure of a protein template and achieved the development of molecularly imprinted polymers (MIPs) from one dimension to zero dimension for efficient recognition towards large biomolecules. The resultant nanoparticles could be used for convenient magnetic separation of homologous proteins with high specificity. The nanoparticles possessed good monodispersibility, uniform surface morphology and high saturation magnetization value. The bound amounts of template proteins measured by both indirect and direct methods were in good agreement. The maximum number of imprinted cavities on the surface of the bovine hemoglobin (Hb)-imprinted nanoshell was 2.21 x 10{sup 18} g{sup -1}, which well matched their maximum binding capacity toward bovine Hb. Both the simple method for preparation of MIPs and the magnetic nanospheres showed good application potential in fast separation, effective concentration and selective biosensing of large protein molecules.

Molecular Imprinting Applications in Forensic Science.

Science.gov (United States)

Yılmaz, Erkut; Garipcan, Bora; Patra, Hirak K; Uzun, Lokman

2017-03-28

Producing molecular imprinting-based materials has received increasing attention due to recognition selectivity, stability, cast effectiveness, and ease of production in various forms for a wide range of applications. The molecular imprinting technique has a variety of applications in the areas of the food industry, environmental monitoring, and medicine for diverse purposes like sample pretreatment, sensing, and separation/purification. A versatile usage, stability and recognition capabilities also make them perfect candidates for use in forensic sciences. Forensic science is a demanding area and there is a growing interest in molecularly imprinted polymers (MIPs) in this field. In this review, recent molecular imprinting applications in the related areas of forensic sciences are discussed while considering the literature of last two decades. Not only direct forensic applications but also studies of possible forensic value were taken into account like illicit drugs, banned sport drugs, effective toxins and chemical warfare agents in a review of over 100 articles. The literature was classified according to targets, material shapes, production strategies, detection method, and instrumentation. We aimed to summarize the current applications of MIPs in forensic science and put forth a projection of their potential uses as promising alternatives for benchmark competitors.

Driving Forces Controlling Host-Guest Recognition in Supercritical Carbon Dioxide Solvent.

Science.gov (United States)

Ingrosso, Francesca; Altarsha, Muhannad; Dumarçay, Florence; Kevern, Gwendal; Barth, Danielle; Marsura, Alain; Ruiz-López, Manuel F

2016-02-24

The formation of supramolecular host-guest complexes is a very useful and widely employed tool in chemistry. However, supramolecular chemistry in non-conventional solvents such as supercritical carbon dioxide (scCO2 ), one of the most promising sustainable solvents, is still in its infancy. In this work, we explored a successful route to the development of green processes in supercritical CO2 by combining a theoretical approach with experiments. We were able to synthesize and characterize an inclusion complex between a polar aromatic molecule (benzoic acid) and peracetylated-β-cyclodextrin, which is soluble in the supercritical medium. This finding opens the way to wide, environmental friendly, applications of scCO2 in many areas of chemistry, including supramolecular synthesis, reactivity and catalysis, micro and nano-particle formation, molecular recognition, as well as enhanced extraction processes with increased selectivity. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining experimental and simulation data of molecular processes via augmented Markov models.

Science.gov (United States)

Olsson, Simon; Wu, Hao; Paul, Fabian; Clementi, Cecilia; Noé, Frank

2017-08-01

Accurate mechanistic description of structural changes in biomolecules is an increasingly important topic in structural and chemical biology. Markov models have emerged as a powerful way to approximate the molecular kinetics of large biomolecules while keeping full structural resolution in a divide-and-conquer fashion. However, the accuracy of these models is limited by that of the force fields used to generate the underlying molecular dynamics (MD) simulation data. Whereas the quality of classical MD force fields has improved significantly in recent years, remaining errors in the Boltzmann weights are still on the order of a few [Formula: see text], which may lead to significant discrepancies when comparing to experimentally measured rates or state populations. Here we take the view that simulations using a sufficiently good force-field sample conformations that are valid but have inaccurate weights, yet these weights may be made accurate by incorporating experimental data a posteriori. To do so, we propose augmented Markov models (AMMs), an approach that combines concepts from probability theory and information theory to consistently treat systematic force-field error and statistical errors in simulation and experiment. Our results demonstrate that AMMs can reconcile conflicting results for protein mechanisms obtained by different force fields and correct for a wide range of stationary and dynamical observables even when only equilibrium measurements are incorporated into the estimation process. This approach constitutes a unique avenue to combine experiment and computation into integrative models of biomolecular structure and dynamics.

Evolution of Soybean mosaic virus-G7 molecularly cloned genome in Rsv1-genotype soybean results in emergence of a mutant capable of evading Rsv1-mediated recognition

International Nuclear Information System (INIS)

Hajimorad, M.R.; Eggenberger, A.L.; Hill, J.H.

2003-01-01

Plant resistance (R) genes direct recognition of pathogens harboring matching avirluent signals leading to activation of defense responses. It has long been hypothesized that under selection pressure the infidelity of RNA virus replication together with large population size and short generation times results in emergence of mutants capable of evading R-mediated recognition. In this study, the Rsv1/Soybean mosaic virus (SMV) pathosystem was used to investigate this hypothesis. In soybean line PI 96983 (Rsv1), the progeny of molecularly cloned SMV strain G7 (pSMV-G7) provokes a lethal systemic hypersensitive response (LSHR) with up regulation of a defense-associated gene transcript (PR-1). Serial passages of a large population of the progeny in PI 96983 resulted in emergence of a mutant population (vSMV-G7d), incapable of provoking either Rsv1-mediated LSHR or PR-1 protein gene transcript up regulation. An infectious clone of the mutant (pSMV-G7d) was synthesized whose sequences were very similar but not identical to the vSMV-G7d population; however, it displayed a similar phenotype. The genome of pSMV-G7d differs from parental pSMV-G7 by 17 substitutions, of which 10 are translationally silent. The seven amino acid substitutions in deduced sequences of pSMV-G7d differ from that of pSMV-G7 by one each in P1 proteinase, helper component-proteinase, and coat protein, respectively, and by four in P3. To the best of our knowledge, this is the first demonstration in which experimental evolution of a molecularly cloned plant RNA virus resulted in emergence of a mutant capable of evading an R-mediated recognition

Preparation of a molecularly imprinted sensor based on quartz crystal microbalance for specific recognition of sialic acid in human urine.

Science.gov (United States)

Qiu, Xiuzhen; Xu, Xian-Yan; Chen, Xuncai; Wu, Yiyong; Guo, Huishi

2018-05-08

A novel molecularly imprinted quartz crystal microbalance (QCM) sensor was successfully prepared for selective determination of sialic acid (SA) in human urine samples. To obtain the QCM sensor, we first modified the gold surface of the QCM chip by self-assembling of allylmercaptane to introduce polymerizable double bonds on the chip surface. Then, SA molecularly imprinted polymer (MIP) nanofilm was attached to the modified QCM chip surface. For comparison, we have also characterized the nonmodified and improved surfaces of the QCM sensor by using atomic force microscopy (AFM) and Fourier transform infrared (FTIR) spectroscopy. We then tested the selectivity and detection limit of the imprinted QCM sensor via a series of adsorption experiments. The results show a linear response in the range of 0.025-0.50 μmol L -1 for sialic acid. Moreover, the limit of detection (LOD) of the prepared imprinted QCM sensor was found to be 1.0 nmol L -1 for sialic acid, and high recovery values range from 87.6 to 108.5% with RSD sensor was developed and used to detect sialic acid in human urine samples. Graphical abstract Specific recognition of sialic acid by the MIP-QCM sensor system.

A structural and mutagenic blueprint for molecular recognition of strychnine and d-tubocurarine by different cys-loop receptors.

Directory of Open Access Journals (Sweden)

Marijke Brams

2011-03-01

Full Text Available Cys-loop receptors (CLR are pentameric ligand-gated ion channels that mediate fast excitatory or inhibitory transmission in the nervous system. Strychnine and d-tubocurarine (d-TC are neurotoxins that have been highly instrumental in decades of research on glycine receptors (GlyR and nicotinic acetylcholine receptors (nAChR, respectively. In this study we addressed the question how the molecular recognition of strychnine and d-TC occurs with high affinity and yet low specificity towards diverse CLR family members. X-ray crystal structures of the complexes with AChBP, a well-described structural homolog of the extracellular domain of the nAChRs, revealed that strychnine and d-TC adopt multiple occupancies and different ligand orientations, stabilizing the homopentameric protein in an asymmetric state. This introduces a new level of structural diversity in CLRs. Unlike protein and peptide neurotoxins, strychnine and d-TC form a limited number of contacts in the binding pocket of AChBP, offering an explanation for their low selectivity. Based on the ligand interactions observed in strychnine- and d-TC-AChBP complexes we performed alanine-scanning mutagenesis in the binding pocket of the human α1 GlyR and α7 nAChR and showed the functional relevance of these residues in conferring high potency of strychnine and d-TC, respectively. Our results demonstrate that a limited number of ligand interactions in the binding pocket together with an energetic stabilization of the extracellular domain are key to the poor selective recognition of strychnine and d-TC by CLRs as diverse as the GlyR, nAChR, and 5-HT(3R.

Handwritten Word Recognition Using Multi-view Analysis

Science.gov (United States)

de Oliveira, J. J.; de A. Freitas, C. O.; de Carvalho, J. M.; Sabourin, R.

This paper brings a contribution to the problem of efficiently recognizing handwritten words from a limited size lexicon. For that, a multiple classifier system has been developed that analyzes the words from three different approximation levels, in order to get a computational approach inspired on the human reading process. For each approximation level a three-module architecture composed of a zoning mechanism (pseudo-segmenter), a feature extractor and a classifier is defined. The proposed application is the recognition of the Portuguese handwritten names of the months, for which a best recognition rate of 97.7% was obtained, using classifier combination.

Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model

Science.gov (United States)

Jin, Jing; Wang, Yuanqing; Xu, Liujing; Cao, Liqun; Han, Lei; Zhou, Biye; Li, Minggao

2014-11-01

A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user's hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television

Study on recognition algorithm for paper currency numbers based on neural network

Science.gov (United States)

Li, Xiuyan; Liu, Tiegen; Li, Yuanyao; Zhang, Zhongchuan; Deng, Shichao

2008-12-01

Based on the unique characteristic, the paper currency numbers can be put into record and the automatic identification equipment for paper currency numbers is supplied to currency circulation market in order to provide convenience for financial sectors to trace the fiduciary circulation socially and provide effective supervision on paper currency. Simultaneously it is favorable for identifying forged notes, blacklisting the forged notes numbers and solving the major social problems, such as armor cash carrier robbery, money laundering. For the purpose of recognizing the paper currency numbers, a recognition algorithm based on neural network is presented in the paper. Number lines in original paper currency images can be draw out through image processing, such as image de-noising, skew correction, segmentation, and image normalization. According to the different characteristics between digits and letters in serial number, two kinds of classifiers are designed. With the characteristics of associative memory, optimization-compute and rapid convergence, the Discrete Hopfield Neural Network (DHNN) is utilized to recognize the letters; with the characteristics of simple structure, quick learning and global optimum, the Radial-Basis Function Neural Network (RBFNN) is adopted to identify the digits. Then the final recognition results are obtained by combining the two kinds of recognition results in regular sequence. Through the simulation tests, it is confirmed by simulation results that the recognition algorithm of combination of two kinds of recognition methods has such advantages as high recognition rate and faster recognition simultaneously, which is worthy of broad application prospect.

The influence of combined cognitive plus social-cognitive training on amygdala response during face emotion recognition in schizophrenia.

Science.gov (United States)

Hooker, Christine I; Bruce, Lori; Fisher, Melissa; Verosky, Sara C; Miyakawa, Asako; D'Esposito, Mark; Vinogradov, Sophia

2013-08-30

Both cognitive and social-cognitive deficits impact functional outcome in schizophrenia. Cognitive remediation studies indicate that targeted cognitive and/or social-cognitive training improves behavioral performance on trained skills. However, the neural effects of training in schizophrenia and their relation to behavioral gains are largely unknown. This study tested whether a 50-h intervention which included both cognitive and social-cognitive training would influence neural mechanisms that support social ccognition. Schizophrenia participants completed a computer-based intervention of either auditory-based cognitive training (AT) plus social-cognition training (SCT) (N=11) or non-specific computer games (CG) (N=11). Assessments included a functional magnetic resonance imaging (fMRI) task of facial emotion recognition, and behavioral measures of cognition, social cognition, and functional outcome. The fMRI results showed the predicted group-by-time interaction. Results were strongest for emotion recognition of happy, surprise and fear: relative to CG participants, AT+SCT participants showed a neural activity increase in bilateral amygdala, right putamen and right medial prefrontal cortex. Across all participants, pre-to-post intervention neural activity increase in these regions predicted behavioral improvement on an independent emotion perception measure (MSCEIT: Perceiving Emotions). Among AT+SCT participants alone, neural activity increase in right amygdala predicted behavioral improvement in emotion perception. The findings indicate that combined cognition and social-cognition training improves neural systems that support social-cognition skills. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Multi-font printed Mongolian document recognition system

Science.gov (United States)

Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

2009-01-01

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

Object Recognition and Localization: The Role of Tactile Sensors

Directory of Open Access Journals (Sweden)

Achint Aggarwal

2014-02-01

Full Text Available Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments.

Molecular recognition of halogen-tagged aromatic VOCs at the air-silicon interface.

Science.gov (United States)

Condorelli, Guglielmo G; Motta, Alessandro; Favazza, Maria; Gurrieri, Ettore; Betti, Paolo; Dalcanale, Enrico

2010-01-14

Selective and reversible complexation of halogen-tagged aromatic VOCs by a quinoxaline cavitand-decorated Si surface is demonstrated. The specific host-guest interactions of the Si-bonded receptors are proved to be responsible of the surface recognition properties, while extracavity non specific adsorptions are totally suppressed compared to the bulk material.

Artificial intelligence tools for pattern recognition

Science.gov (United States)

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

2017-06-01

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

A Neural Model Combining Attentional Orienting to Object Recognition: Preliminary Explorations on the Interplay Between Where and What

National Research Council Canada - National Science Library

Miau, Florence

2001-01-01

... ("where") pathway and an object recognition ("what") pathway. The fast visual attention front-end rapidly selects the few most conspicuous image locations, and the slower object recognition back-end identifies objects at the selected locations...

Extraction and fusion of spectral parameters for face recognition

Science.gov (United States)

Boisier, B.; Billiot, B.; Abdessalem, Z.; Gouton, P.; Hardeberg, J. Y.

2011-03-01

Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately in order to extract the most appropriate information for face recognition. We also verify the consistency of several keypoints extraction techniques in the Near Infrared (NIR) and in the Visible Spectrum.

IMAGE TYPE WATER METER CHARACTER RECOGNITION BASED ON EMBEDDED DSP

OpenAIRE

LIU Ying; HAN Yan-bin; ZHANG Yu-lin

2015-01-01

In the paper, we combined DSP processor with image processing algorithm and studied the method of water meter character recognition. We collected water meter image through camera at a fixed angle, and the projection method is used to recognize those digital images. The experiment results show that the method can recognize the meter characters accurately and artificial meter reading is replaced by automatic digital recognition, which improves working efficiency.

Molecularly Imprinted Polymer Technology: A Powerful, Generic ...

African Journals Online (AJOL)

Molecularly Imprinted Polymer Technology: A Powerful, Generic, Facile and Cost Effective Alternative for Enantio-recognition and Separation: A Glance at Advances and Applications. ... Tanzania Journal of Science. Journal Home · ABOUT ...

Implementation of CT and IHT Processors for Invariant Object Recognition System

Directory of Open Access Journals (Sweden)

J. Turan jr.

2004-12-01

Full Text Available This paper presents PDL or ASIC implementation of key modules ofinvariant object recognition system based on the combination of theIncremental Hough transform (IHT, correlation and rapid transform(RT. The invariant object recognition system was represented partiallyin C++ language for general-purpose processor on personal computer andpartially described in VHDL code for implementation in PLD or ASIC.

Speech recognition using articulatory and excitation source features

CERN Document Server

Rao, K Sreenivasa

2017-01-01

This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.

Genetic determinants of mate recognition in Brachionus manjavacas (Rotifera).

Science.gov (United States)

Snell, Terry W; Shearer, Tonya L; Smith, Hilary A; Kubanek, Julia; Gribble, Kristin E; Welch, David B Mark

2009-09-09

Mate choice is of central importance to most animals, influencing population structure, speciation, and ultimately the survival of a species. Mating behavior of male brachionid rotifers is triggered by the product of a chemosensory gene, a glycoprotein on the body surface of females called the mate recognition pheromone. The mate recognition pheromone has been biochemically characterized, but little was known about the gene(s). We describe the isolation and characterization of the mate recognition pheromone gene through protein purification, N-terminal amino acid sequence determination, identification of the mate recognition pheromone gene from a cDNA library, sequencing, and RNAi knockdown to confirm the functional role of the mate recognition pheromone gene in rotifer mating. A 29 kD protein capable of eliciting rotifer male circling was isolated by high-performance liquid chromatography. Two transcript types containing the N-terminal sequence were identified in a cDNA library; further characterization by screening a genomic library and by polymerase chain reaction revealed two genes belonging to each type. Each gene begins with a signal peptide region followed by nearly perfect repeats of an 87 to 92 codon motif with no codons between repeats and the final motif prematurely terminated by the stop codon. The two Type A genes contain four and seven repeats and the two Type B genes contain three and five repeats, respectively. Only the Type B gene with three repeats encodes a peptide with a molecular weight of 29 kD. Each repeat of the Type B gene products contains three asparagines as potential sites for N-glycosylation; there are no asparagines in the Type A genes. RNAi with Type A double-stranded RNA did not result in less circling than in the phosphate-buffered saline control, but transfection with Type B double-stranded RNA significantly reduced male circling by 17%. The very low divergence between repeat units, even at synonymous positions, suggests that the

Molecular Recognition in the Oxidation of Catechols by Dicobalt-BISDIEN Dioxygen Complexes

Science.gov (United States)

1992-01-30

Recognition in the Oxidation of Catechols by Dicobalt-RISDIEN Dioxygen Complexes Lizete F S Cezar and Bruno Szpoganicz Departamento de Quimica ...bridged bi- nuclear Co(II)-BISDIEN dioxygen complexes; Co20 2 LCat2 + is the bivalent form, and Co20 2 (OH)LCat + and Co 20 2 (OH)2 Cat° are hydroxo

Molecular Recognition of Corticotropin releasing Factor by Its G protein-coupled Receptor CRFR1

Energy Technology Data Exchange (ETDEWEB)

Pioszak, Augen A.; Parker, Naomi R.; Suino-Powell, Kelly; Xu, H. Eric (Van Andel)

2009-01-15

The bimolecular interaction between corticotropin-releasing factor (CRF), a neuropeptide, and its type 1 receptor (CRFR1), a class B G-protein-coupled receptor (GPCR), is crucial for activation of the hypothalamic-pituitary-adrenal axis in response to stress, and has been a target of intense drug design for the treatment of anxiety, depression, and related disorders. As a class B GPCR, CRFR1 contains an N-terminal extracellular domain (ECD) that provides the primary ligand binding determinants. Here we present three crystal structures of the human CRFR1 ECD, one in a ligand-free form and two in distinct CRF-bound states. The CRFR1 ECD adopts the alpha-beta-betaalpha fold observed for other class B GPCR ECDs, but the N-terminal alpha-helix is significantly shorter and does not contact CRF. CRF adopts a continuous alpha-helix that docks in a hydrophobic surface of the ECD that is distinct from the peptide-binding site of other class B GPCRs, thereby providing a basis for the specificity of ligand recognition between CRFR1 and other class B GPCRs. The binding of CRF is accompanied by clamp-like conformational changes of two loops of the receptor that anchor the CRF C terminus, including the C-terminal amide group. These structural studies provide a molecular framework for understanding peptide binding and specificity by the CRF receptors as well as a template for designing potent and selective CRFR1 antagonists for therapeutic applications.

Perfect-absorption graphene metamaterials for surface-enhanced molecular fingerprint spectroscopy

Science.gov (United States)

Guo, Xiangdong; Hu, Hai; Liao, Baoxin; Zhu, Xing; Yang, Xiaoxia; Dai, Qing

2018-05-01

Graphene plasmon with extremely strong light confinement and tunable resonance frequency represents a promising surface-enhanced infrared absorption (SEIRA) sensing platform. However, plasmonic absorption is relatively weak (approximately 1%-9%) in monolayer graphene nanostructures, which would limit its sensitivity. Here, we theoretically propose a hybrid plasmon-metamaterial structure that can realize perfect absorption in graphene with a low carrier mobility of 1000 cm2 V-1 s-1. This structure combines a gold reflector and a gold grating to the graphene plasmon structures, which introduce interference effect and the lightning-rod effect, respectively, and largely enhance the coupling of light to graphene. The vibration signal of trace molecules can be enhanced up to 2000-fold at the hotspot of the perfect-absorption structure, enabling the SEIRA sensing to reach the molecular level. This hybrid metal-graphene structure provides a novel path to generate high sensitivity in nanoscale molecular recognition for numerous applications.

Combining fossil and molecular data to date the diversification of New World Primates.

Science.gov (United States)

Schrago, C G; Mello, B; Soares, A E R

2013-11-01

Recent methodological advances in molecular dating associated with the growing availability of sequence data have prompted the study of the evolution of New World Anthropoidea in recent years. Motivated by questions regarding historical biogeography or the mode of evolution, these works aimed to obtain a clearer scenario of Platyrrhini origins and diversification. Although some consensus was found, disputed issues, especially those relating to the evolutionary affinities of fossil taxa, remain. The use of fossil taxa for divergence time analysis is traditionally restricted to the provision of calibration priors. However, new analytical approaches have been developed that incorporate fossils as terminals and, thus, directly assign ages to the fossil tips. In this study, we conducted a combined analysis of molecular and morphological data, including fossils, to derive the timescale of New World anthropoids. Differently from previous studies that conducted total-evidence analysis of molecules and morphology, our approach investigated the morphological clock alone. Our results corroborate the hypothesis that living platyrrhines diversified in the last 20 Ma and that Miocene Patagonian fossils compose an independent evolutionary radiation that diversified in the late Oligocene. When compared to the node ages inferred from the molecular timescale, the inclusion of fossils augmented the precision of the estimates for nodes constrained by the fossil tips. We show that morphological data can be analysed using the same methodological framework applied in relaxed molecular clock studies. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Molecularly imprinted electrochemical sensing interface based on in-situ-polymerization of amino-functionalized ionic liquid for specific recognition of bovine serum albumin.

Science.gov (United States)

Wang, Yanying; Han, Miao; Liu, Guishen; Hou, Xiaodong; Huang, Yina; Wu, Kangbing; Li, Chunya

2015-12-15

A molecularly imprinted polymer film was in situ polymerized on a carboxyl functionalized multi-walled carbon nanotubes modified glassy carbon electrode surface under room temperature. This technique provides a promising imprinting approach for protein in an aqueous solution using 3-(3-aminopropyl)-1-vinylimidazolium tetrafluoroborate ionic liquid as functional monomer, N, N'-methylenebisacrylamide as crossing linker, ammonium persulfate and N,N,N',N'-tetramethylethylenediamine as initiator, and bovine serum albumin (BSA) as template. The molecularly imprinted polymerized ionic liquid film shows enhanced accessibility, high specificity and sensitivity towards BSA. Electrochemical sensing performance of the imprinted sensor was thoroughly investigated using K3Fe[CN]6/K4Fe[CN]6 as electroactive probes. Under optimal conditions, the current difference before and after specific recognition of BSA was found linearly related to its concentration in the range from 1.50×10(-9) to 1.50×10(-6) mol L(-1). The detection limit was calculated to be 3.91×10(-10) mol L(-1) (S/N=3). The practical application of the imprinted sensor was demonstrated by determining BSA in liquid milk samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Subject independent facial expression recognition with robust face detection using a convolutional neural network.

Science.gov (United States)

Matsugu, Masakazu; Mori, Katsuhiko; Mitari, Yusuke; Kaneda, Yuji

2003-01-01

Reliable detection of ordinary facial expressions (e.g. smile) despite the variability among individuals as well as face appearance is an important step toward the realization of perceptual user interface with autonomous perception of persons. We describe a rule-based algorithm for robust facial expression recognition combined with robust face detection using a convolutional neural network. In this study, we address the problem of subject independence as well as translation, rotation, and scale invariance in the recognition of facial expression. The result shows reliable detection of smiles with recognition rate of 97.6% for 5600 still images of more than 10 subjects. The proposed algorithm demonstrated the ability to discriminate smiling from talking based on the saliency score obtained from voting visual cues. To the best of our knowledge, it is the first facial expression recognition model with the property of subject independence combined with robustness to variability in facial appearance.

Chirality in molecular collision dynamics

Science.gov (United States)

Lombardi, Andrea; Palazzetti, Federico

2018-02-01

Chirality is a phenomenon that permeates the natural world, with implications for atomic and molecular physics, for fundamental forces and for the mechanisms at the origin of the early evolution of life and biomolecular homochirality. The manifestations of chirality in chemistry and biochemistry are numerous, the striking ones being chiral recognition and asymmetric synthesis with important applications in molecular sciences and in industrial and pharmaceutical chemistry. Chiral discrimination phenomena, due to the existence of two enantiomeric forms, very well known in the case of interaction with light, but still nearly disregarded in molecular collision studies. Here we review some ideas and recent advances about the role of chirality in molecular collisions, designing and illustrating molecular beam experiments for the demonstration of chiral effects and suggesting a scenario for a stereo-directional origin of chiral selection.

Theragnosis-based combined cancer therapy using doxorubicin-conjugated microRNA-221 molecular beacon.

Science.gov (United States)

Lee, Jonghwan; Choi, Kyung-Ju; Moon, Sung Ung; Kim, Soonhag

2016-01-01

Recently, microRNA (miRNA or miR) has emerged as a new cancer biomarker because of its high expression level in various cancer types and its role in the control of tumor suppressor genes. In cancer studies, molecular imaging and treatment based on target cancer markers have been combined to facilitate simultaneous cancer diagnosis and therapy. In this study, for combined therapy with diagnosis of cancer, we developed a doxorubicin-conjugated miR-221 molecular beacon (miR-221 DOXO MB) in a single platform composed of three different nucleotides: miR-221 binding sequence, black hole quencher 1 (BHQ1), and doxorubicin binding site. Imaging of endogenous miR-221 was achieved by specific hybridization between miR-221 and the miR-221 binding site in miR-221 DOXO MB. The presence of miR-221 triggered detachment of the quencher oligo and subsequent activation of a fluorescent signal of miR-221 DOXO MB. Simultaneous cancer therapy in C6 astrocytoma cells and nude mice was achieved by inhibition of miRNA-221 function that downregulates tumor suppressor genes. The detection of miR-221 expression and inhibition of miR-221 function by miR-221 DOXO MB provide the feasibility as a cancer theragnostic probe. Furthermore, a cytotoxic effect was induced by unloading of doxorubicin intercalated into miR-221 DOXO MB inside cells. Loss of miR-221 function and cytotoxicity induced by the miR-221 DOXO MB provides combined therapeutic efficacy against cancers. This method could be used as a new theragnostic probe with enhanced therapy to detect and inhibit many cancer-related miRNAs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Primitive Based Action Representation and recognition

DEFF Research Database (Denmark)

Baby, Sanmohan

The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human-machine i......The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human......-machine interface, entertainment, biomechanics etc. Recent developments in neuroscience suggest that all actions are a compositions of smaller units called primitives. Current works based on primitives for action recognition uses a supervised framework for specifying the primitives. We propose a method to extract...... primitives automatically. These primitives are to be used to generate actions based on certain rules for combining. These rules are expressed as a stochastic context free grammar. A model merging approach is adopted to learn a Hidden Markov Model to t the observed data sequences. The states of the HMM...

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

NARCIS (Netherlands)

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

2010-01-01

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

Pyrrole-phenylboronic acid: a novel monomer for dopamine recognition and detection based on imprinted electrochemical sensor.

Science.gov (United States)

Zhong, Min; Teng, Ying; Pang, Shufen; Yan, Liqin; Kan, Xianwen

2015-02-15

A molecular imprinting polymer (MIP) based electrochemical sensor was successfully prepared for dopamine (DA) recognition and detection using pyrrole-phenylboronic acid (py-PBA) as a novel electropolymerized monomer. py-PBA could form cyclic boronic ester bond with DA, thus endowing a double recognition capacity of the sensor to DA in the combination of the imprinted effect of MIP. Compared with the sensor prepared using pyrrole or phenylboronic acid as electropolymerized monomer, the present sensor exhibited a remarkable high imprinted factor to DA. The influence factors including pH value, the mole ratio between monomer and template molecule, electropolymerization scan rate, and scan cycles of electropolymerization process were investigated and optimized. Under the optimal conditions, the sensor could recognize DA from its analogs and monosaccharides. A linear ranging from 5.0 × 10(-8) to 1.0 × 10(-5) mol/L for the detection of DA was obtained with a detection limit of 3.3 × 10(-8) mol/L (S/N = 3). The sensor has been applied to analyze DA in injection samples with satisfactory results. Copyright © 2014 Elsevier B.V. All rights reserved.

Face recognition algorithm using extended vector quantization histogram features.

Science.gov (United States)

Yan, Yan; Lee, Feifei; Wu, Xueqian; Chen, Qiu

2018-01-01

In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.

Recognition of microbial glycolipids by Natural Killer T cells

Directory of Open Access Journals (Sweden)

Dirk Michael Zajonc

2015-08-01

Full Text Available T cells can recognize microbial antigens when presented by dedicated antigen-presenting molecules. While peptides are presented by classical members of the Major Histocompatibility (MHC family (MHC I and II, lipids, glycolipids and lipopeptides can be presented by the non-classical MHC member CD1. The best studied subset of lipid-reactive T cells are Type I Natural killer T (iNKT cells that recognize a variety of different antigens when presented by the non-classical MHCI homolog CD1d. iNKT cells have been shown to be important for the protection against various microbial pathogens, including B. burgdorferi the causative agents of Lyme disease and S. pneumoniae, which causes pneumococcal meningitis and community-acquired pneumonia. Both pathogens carry microbial glycolipids that can trigger the T cell antigen receptor (TCR, leading to iNKT cell activation. iNKT cells have an evolutionary conserved TCR alpha chain, yet retain the ability to recognize structurally diverse glycolipids. They do so using a conserved recognition mode, in which the TCR enforces a conserved binding orientation on CD1d. TCR binding is accompanied by structural changes within the TCR binding site of CD1d, as well as the glycolipid antigen itself. In addition to direct recognition of microbial antigens, iNKT cells can also be activated by a combination of cytokines (IL-12/IL-18 and TCR stimulation. Many microbes carry TLR antigens and microbial infections can lead to TLR activation. The subsequent cytokine response in turn lower the threshold of TCR mediated iNKT cell activation, especially when weak microbial or even self-antigens are presented during the cause of the infection. In summary, iNKT cells can be directly activated through TCR triggering of strong antigens, while cytokines produced by the innate immune response may be necessary for TCR triggering and iNKT cell activation in the presence of weak antigens. Here we will review the molecular basis of iNKT cell

Environmental Sound Recognition Using Time-Frequency Intersection Patterns

Directory of Open Access Journals (Sweden)

Xuan Guo

2012-01-01

Full Text Available Environmental sound recognition is an important function of robots and intelligent computer systems. In this research, we use a multistage perceptron neural network system for environmental sound recognition. The input data is a combination of time-variance pattern of instantaneous powers and frequency-variance pattern with instantaneous spectrum at the power peak, referred to as a time-frequency intersection pattern. Spectra of many environmental sounds change more slowly than those of speech or voice, so the intersectional time-frequency pattern will preserve the major features of environmental sounds but with drastically reduced data requirements. Two experiments were conducted using an original database and an open database created by the RWCP project. The recognition rate for 20 kinds of environmental sounds was 92%. The recognition rate of the new method was about 12% higher than methods using only an instantaneous spectrum. The results are also comparable with HMM-based methods, although those methods need to treat the time variance of an input vector series with more complicated computations.

Constraints in distortion-invariant target recognition system simulation

Science.gov (United States)

Iftekharuddin, Khan M.; Razzaque, Md A.

2000-11-01

Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

Face recognition using slow feature analysis and contourlet transform

Science.gov (United States)

Wang, Yuehao; Peng, Lingling; Zhe, Fuchuan

2018-04-01

In this paper we propose a novel face recognition approach based on slow feature analysis (SFA) in contourlet transform domain. This method firstly use contourlet transform to decompose the face image into low frequency and high frequency part, and then takes technological advantages of slow feature analysis for facial feature extraction. We named the new method combining the slow feature analysis and contourlet transform as CT-SFA. The experimental results on international standard face database demonstrate that the new face recognition method is effective and competitive.

An Exploration of Molecular Correlates Relevant to Radiation Combined Skin-Burn Trauma.

Directory of Open Access Journals (Sweden)

Aminul Islam

Full Text Available Exposure to high dose radiation in combination with physical injuries such as burn or wound trauma can produce a more harmful set of medical complications requiring specialist interventions. Currently these interventions are unavailable as are the precise biomarkers needed to help both accurately assess and treat such conditions. In the present study, we tried to identify and explore the possible role of serum exosome microRNA (miRNA signatures as potential biomarkers for radiation combined burn injury (RCBI.Female B6D2F1/J mice were assigned to four experimental groups (n = 6: sham control (SHAM, burn injury (BURN, radiation injury (RI and combined radiation skin burn injury (CI. We performed serum multiplex cytokine analysis and serum exosome miRNA expression profiling to determine novel miRNA signatures and important biological pathways associated with radiation combined skin-burn trauma.Serum cytokines, IL-5 and MCP-1, were significantly induced only in CI mice (p<0.05. From 890 differentially expressed miRNAs identified, microarray analysis showed 47 distinct miRNA seed sequences significantly associated with CI mice compared to SHAM control mice (fold change ≥ 1.2, p<0.05. Furthermore, only two major miRNA seed sequences (miR-690 and miR-223 were validated to be differentially expressed for CI mice specifically (fold change ≥ 1.5, p<0.05.Serum exosome miRNA signature data of adult mice, following RCBI, provides new insights into the molecular and biochemical pathways associated with radiation combined skin-burn trauma in vivo.

Emotion recognition abilities across stimulus modalities in schizophrenia and the role of visual attention.

Science.gov (United States)

Simpson, Claire; Pinkham, Amy E; Kelsven, Skylar; Sasson, Noah J

2013-12-01

Emotion can be expressed by both the voice and face, and previous work suggests that presentation modality may impact emotion recognition performance in individuals with schizophrenia. We investigated the effect of stimulus modality on emotion recognition accuracy and the potential role of visual attention to faces in emotion recognition abilities. Thirty-one patients who met DSM-IV criteria for schizophrenia (n=8) or schizoaffective disorder (n=23) and 30 non-clinical control individuals participated. Both groups identified emotional expressions in three different conditions: audio only, visual only, combined audiovisual. In the visual only and combined conditions, time spent visually fixating salient features of the face were recorded. Patients were significantly less accurate than controls in emotion recognition during both the audio and visual only conditions but did not differ from controls on the combined condition. Analysis of visual scanning behaviors demonstrated that patients attended less than healthy individuals to the mouth in the visual condition but did not differ in visual attention to salient facial features in the combined condition, which may in part explain the absence of a deficit for patients in this condition. Collectively, these findings demonstrate that patients benefit from multimodal stimulus presentations of emotion and support hypotheses that visual attention to salient facial features may serve as a mechanism for accurate emotion identification. © 2013.

Optical Pattern Recognition

Science.gov (United States)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Taste and odor recognition memory: the emotional flavor of life.

Science.gov (United States)

Miranda, Maria Isabel

2012-01-01

In recent years, our knowledge of the neurobiology of taste and smell has greatly increased; by using several learning models, we now have a better understanding of the behavioral and neurochemical basis of memory recognition. Studies have provided new evidence of some processes that depend on prior experience with the specific combination of sensory stimuli. This review contains recent research related to taste and odor recognition memory, and the goal is to highlight the role of two prominent brain structures, the insular cortex and the amygdala. These structures have an important function during learning and memory and have been associated with the differences in learning induced by the diverse degrees of emotion during taste/odor memory formation, either aversive or appetitive or when taste and odor are combined and/or potentiated.Therefore, this review includes information about certain neurochemical transmitters and their interactions during appetitive or aversive taste memory formation,taste-potentiated odor aversion memory, and conditioned odor aversion, which might be able to maintain the complex processes necessary for flavor recognition memory.

Protein fold recognition using geometric kernel data fusion.

Science.gov (United States)

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

A new selective developmental deficit: Impaired object recognition with normal face recognition.

Science.gov (United States)

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

Fusing Eye-gaze and Speech Recognition for Tracking in an Automatic Reading Tutor

DEFF Research Database (Denmark)

Rasmussen, Morten Højfeldt; Tan, Zheng-Hua

2013-01-01

In this paper we present a novel approach for automatically tracking the reading progress using a combination of eye-gaze tracking and speech recognition. The two are fused by first generating word probabilities based on eye-gaze information and then using these probabilities to augment the langu......In this paper we present a novel approach for automatically tracking the reading progress using a combination of eye-gaze tracking and speech recognition. The two are fused by first generating word probabilities based on eye-gaze information and then using these probabilities to augment...

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

Science.gov (United States)

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

2018-02-22

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

Combined quantum mechanical and molecular mechanical reaction pathway calculation for aromatic hydroxylation by p-hydroxybenzoate-3-hydroxylase

NARCIS (Netherlands)

Ridder, L.; Mulholland, A.; Rietjens, I.M.C.M.; Vervoort, J.

1999-01-01

The reaction pathway for the aromatic 3-hydroxylation of p-hydroxybenzoate by the reactive C4a-hydroperoxyflavin cofactor intermediate in p-hydroxybenzoate hydroxylase (PHBH) has been investigated by a combined quantum mechanical and molecular mechanical (QM/MM) method. A structural model for the

A Method to Integrate GMM, SVM and DTW for Speaker Recognition

Directory of Open Access Journals (Sweden)

Ing-Jr Ding

2014-01-01

Full Text Available This paper develops an effective and efficient scheme to integrate Gaussian mixture model (GMM, support vector machine (SVM, and dynamic time wrapping (DTW for automatic speaker recognition. GMM and SVM are two popular classifiers for speaker recognition applications. DTW is a fast and simple template matching method, and it is frequently seen in applications of speech recognition. In this work, DTW does not play a role to perform speech recognition, and it will be employed to be a verifier for verification of valid speakers. The proposed combination scheme of GMM, SVM and DTW, called SVMGMM-DTW, for speaker recognition in this study is a two-phase verification process task including GMM-SVM verification of the first phase and DTW verification of the second phase. By providing a double check to verify the identity of a speaker, it will be difficult for imposters to try to pass the security protection; therefore, the safety degree of speaker recognition systems will be largely increased. A series of experiments designed on door access control applications demonstrated that the superiority of the developed SVMGMM-DTW on speaker recognition accuracy.

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

Science.gov (United States)

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

2006-11-01

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

Recognition properties of receptors consisting of imidazole and indole recognition units towards carbohydrates

Directory of Open Access Journals (Sweden)

Monika Mazik

2010-02-01

Full Text Available Compounds 4 and 5, including both 4(5-substituted imidazole or 3-substituted indole units as the entities used in nature, and 2-aminopyridine group as a heterocyclic analogue of the asparagine/glutamine primary amide side chain, were prepared and their binding properties towards carbohydrates were studied. The design of these receptors was inspired by the binding motifs observed in the crystal structures of protein–carbohydrate complexes. 1H NMR spectroscopic titrations in competitive and non-competitive media as well as binding studies in two-phase systems, such as dissolution of solid carbohydrates in apolar media, revealed both highly effective recognition of neutral carbohydrates and interesting binding preferences of these acyclic compounds. Compared to the previously described acyclic receptors, compounds 4 and 5 showed significantly increased binding affinity towards β-galactoside. Both receptors display high β- vs. α-anomer binding preferences in the recognition of glycosides. It has been shown that both hydrogen bonding and interactions of the carbohydrate CH units with the aromatic rings of the receptors contribute to the stabilization of the receptor–carbohydrate complexes. The molecular modeling calculations, synthesis and binding properties of 4 and 5 towards selected carbohydrates are described and compared with those of the previously described receptors.

COGNITIVE STYLE OF A PERSON AS A FACTOR OF EFFECTIVE EMOTION RECOGNITION

Directory of Open Access Journals (Sweden)

E V Belovol

2015-12-01

Full Text Available Facial expression is one of the most informative sources of non-verbal information. Early studies on the ability to recognize emotions over the face, pointed to the universality of emotion expression and recognition. More recent studies have shown a combination of universal mechanisms and cultural-specific patterns. The process of emotion recognition is based on face perception that’s why the in-group effect should be taken under consideration. The in-group advantage hypothesis posits that observers are more accurate at recognizing facial expressions displayed by the same culture compared to other culture members. On the other hand, the process of emotion recognition is determined by such cognitive features as a cognitive style. This article describes the approaches to emotion expression and recognition, culture-specific features to basic emotion expression. It also describes factors related to recognition of basic emotions by people from different cultures. It was discovered that field-independent people are more accurate in emotion recognition than field- dependent people because they are able to distinguish markers of emotions. There was found no correlation between successful emotion recognition and the observers’ gender, no correlation between successful emotion recognition and the observers’ race

Aptamer-Based Molecular Recognition of Lysergamine, Metergoline and Small Ergot Alkaloids

Directory of Open Access Journals (Sweden)

Johan Robbens

2012-12-01

Full Text Available Ergot alkaloids are mycotoxins produced by fungi of the genus Claviceps, which infect cereal crops and grasses. The uptake of ergot alkaloid contaminated cereal products can be lethal to humans and animals. For food safety assessment, analytical techniques are currently used to determine the presence of ergot alkaloids in food and feed samples. However, the number of samples which can be analyzed is limited, due to the cost of the equipment and the need for skilled personnel. In order to compensate for the lack of rapid tests for the detection of ergot alkaloids, the aim of this study was to develop a specific recognition element for ergot alkaloids, which could be further applied to produce a colorimetric reaction in the presence of these toxins. As recognition elements, single-stranded DNA ligands were selected by using an iterative selection procedure named SELEX, i.e., Systematic Evolution of Ligands by EXponential enrichment. After several selection cycles, the resulting aptamers were cloned and sequenced. A surface plasmon resonance analysis enabled determination of the dissociation constants of the complexes of aptamers and lysergamine. Dissociation constants in the nanomolar range were obtained with three selected aptamers. One of the selected aptamers, having a dissociation constant of 44 nM, was linked to gold nanoparticles and it was possible to produce a colorimetric reaction in the presence of lysergamine. This system could also be applied to small ergot alkaloids in an ergot contaminated flour sample.

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

Directory of Open Access Journals (Sweden)

Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Syntactic error modeling and scoring normalization in speech recognition: Error modeling and scoring normalization in the speech recognition task for adult literacy training

Science.gov (United States)

Olorenshaw, Lex; Trawick, David

1991-01-01

The purpose was to develop a speech recognition system to be able to detect speech which is pronounced incorrectly, given that the text of the spoken speech is known to the recognizer. Better mechanisms are provided for using speech recognition in a literacy tutor application. Using a combination of scoring normalization techniques and cheater-mode decoding, a reasonable acceptance/rejection threshold was provided. In continuous speech, the system was tested to be able to provide above 80 pct. correct acceptance of words, while correctly rejecting over 80 pct. of incorrectly pronounced words.

Genetic determinants of mate recognition in Brachionus manjavacas (Rotifera

Directory of Open Access Journals (Sweden)

Kubanek Julia

2009-09-01

Full Text Available Abstract Background Mate choice is of central importance to most animals, influencing population structure, speciation, and ultimately the survival of a species. Mating behavior of male brachionid rotifers is triggered by the product of a chemosensory gene, a glycoprotein on the body surface of females called the mate recognition pheromone. The mate recognition pheromone has been biochemically characterized, but little was known about the gene(s. We describe the isolation and characterization of the mate recognition pheromone gene through protein purification, N-terminal amino acid sequence determination, identification of the mate recognition pheromone gene from a cDNA library, sequencing, and RNAi knockdown to confirm the functional role of the mate recognition pheromone gene in rotifer mating. Results A 29 kD protein capable of eliciting rotifer male circling was isolated by high-performance liquid chromatography. Two transcript types containing the N-terminal sequence were identified in a cDNA library; further characterization by screening a genomic library and by polymerase chain reaction revealed two genes belonging to each type. Each gene begins with a signal peptide region followed by nearly perfect repeats of an 87 to 92 codon motif with no codons between repeats and the final motif prematurely terminated by the stop codon. The two Type A genes contain four and seven repeats and the two Type B genes contain three and five repeats, respectively. Only the Type B gene with three repeats encodes a peptide with a molecular weight of 29 kD. Each repeat of the Type B gene products contains three asparagines as potential sites for N-glycosylation; there are no asparagines in the Type A genes. RNAi with Type A double-stranded RNA did not result in less circling than in the phosphate-buffered saline control, but transfection with Type B double-stranded RNA significantly reduced male circling by 17%. The very low divergence between repeat units

Recognition and determination of bovine hemoglobin using a gold electrode modified with gold nanoparticles and molecularly imprinted self-polymerized dopamine

International Nuclear Information System (INIS)

Li, Lu; Fan, Limei; Dai, Yunlong; Kan, Xianwen

2015-01-01

A molecularly imprinted polymer (MIP) was prepared by self-polymerization of dopamine in the presence of bovine hemoglobin (BHb) and then deposited on the surface of an electrode modified with gold nanoparticles (AuNPs). Scanning electron microscopy, cyclic voltammetry, and differential pulse voltammetry were employed to characterize the modified electrode using the hexacyanoferrate redox system as an electroactive probe. The effects of BHb concentration, dopamine concentration, and polymerization time were optimized. Under optimized conditions, the modified electrode selectively recognizes BHb even in the presence of other proteins. The peak current for hexacyanoferrate, typically measured at + 0.17 V (vs. SCE), depends on the concentration of BHb in the 1.0 × 10 −11 to 1.0 × 10 −2 mg mL −1 range. Due to the ease of preparation and tight adherence of polydopamine to various support materials, the present strategy conceivably also provides a platform for the recognition and detection of other proteins. (author)

Combined therapeutic effect and molecular mechanisms of metformin and cisplatin in human lung cancer xenografts in nude mice

OpenAIRE

Yu-Qin Chen; Gang Chen

2015-01-01

Objective: This work was aimed at studying the inhibitory activity of metformin combined with the commonly used chemotherapy drug cisplatin in human lung cancer xenografts in nude mice. We also examined the combined effects of these drugs on the molecular expression of survivin, matrix metalloproteinase-2 (MMP-2), vascular endothelial growth factor-C (VEGF-C), and vascular endothelial growth factorreceptor-3 (VEGFR-3) to determine the mechanism of action and to explore the potential applicati...

Speech Recognition

Directory of Open Access Journals (Sweden)

Adrian Morariu

2009-01-01

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

Introducing MINA--The Molecularly Imprinted Nanoparticle Assay.

Science.gov (United States)

Shutov, Roman V; Guerreiro, Antonio; Moczko, Ewa; de Vargas-Sansalvador, Isabel Perez; Chianella, Iva; Whitcombe, Michael J; Piletsky, Sergey A

2014-03-26

A new ELISA- (enzyme-linked immunosorbent assay)-like assay is demonstrated in which no elements of biological origin are used for molecular recognition or signaling. Composite imprinted nanoparticles that contain a catalytic core and which are synthesized by using a solid-phase approach can simultaneously act as recognition/signaling elements, and be used with minimal modifications to standard assay protocols. This assay provides a new route towards replacement of unstable biomolecules in immunoassays. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Near infrared face recognition by combining Zernike moments and undecimated discrete wavelet transform

Czech Academy of Sciences Publication Activity Database

Farokhi, Sajad; Shamsuddin, S.M.; Sheikh, U.U.; Flusser, Jan; Khansari, M.; Jafari-Khouzani, K.

2014-01-01

Roč. 31, č. 1 (2014), s. 13-27 ISSN 1051-2004 R&D Projects: GA ČR GAP103/11/1552 Institutional support: RVO:67985556 Keywords : Zernike moments * Undecimated discrete wavelet transform * Decision fusion * Near infrared * Face recognition Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.256, year: 2014 http://library.utia.cas.cz/separaty/2014/ZOI/flusser-0428536.pdf

Optical character recognition of handwritten Arabic using hidden Markov models

Science.gov (United States)

Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.

2011-04-01

The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

Recognition and Toleration

DEFF Research Database (Denmark)

Lægaard, Sune

2010-01-01

Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms...... or interpretations of recognition and toleration are considered, confusing and problematic uses of the terms are noted, and the compatibility of toleration and recognition is discussed. The article argues that there is a range of legitimate and importantly different conceptions of both toleration and recognition...

Pattern recognition applied to uranium prospecting

Energy Technology Data Exchange (ETDEWEB)

Briggs, P L; Press, F [Massachusetts Inst. of Tech., Cambridge (USA). Dept. of Earth and Planetary Sciences

1977-07-14

It is stated that pattern recognition techniques provide one way of combining quantitative and descriptive geological data for mineral prospecting. A quantified decision process using computer-selected patterns of geological data has the potential for selecting areas with undiscovered deposits of uranium or other minerals. When a natural resource is mined more rapidly than it is discovered, its continued production becomes increasingly difficult, and it has been noted that, although a considerable uranium reserve may remain in the U.S.A., the discovery rate for uranium is decreasing exponentially with cumulative exploration footage drilled. Pattern recognition methods of organising geological information for prospecting may provide new predictive power, as well as insight into the occurrence of uranium ore deposits. Often the task of prospecting consists of three stages of information processing: (1) collection of data on known ore deposits; (2) noting any regularities common to the known examples of an ore; (3) selection of new exploration targets based on the results of the second stage. A logical pattern recognition algorithm is here described that implements this geological procedure to demonstrate the possibility of building a quantified uranium prospecting guide from diverse geologic data.

Continuous Chinese sign language recognition with CNN-LSTM

Science.gov (United States)

Yang, Su; Zhu, Qing

2017-07-01

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

Adaptive pattern recognition in real-time video-based soccer analysis

DEFF Research Database (Denmark)

Schlipsing, Marc; Salmen, Jan; Tschentscher, Marc

2017-01-01

are taken into account. Our contribution is twofold: (1) the deliberate use of machine learning and pattern recognition techniques allows us to achieve high classification accuracy in varying environments. We systematically evaluate combinations of image features and learning machines in the given online......Computer-aided sports analysis is demanded by coaches and the media. Image processing and machine learning techniques that allow for "live" recognition and tracking of players exist. But these methods are far from collecting and analyzing event data fully autonomously. To generate accurate results......, human interaction is required at different stages including system setup, calibration, supervision of classifier training, and resolution of tracking conflicts. Furthermore, the real-time constraints are challenging: in contrast to other object recognition and tracking applications, we cannot treat data...

The antibacterial protein lysozyme identified as the termite egg recognition pheromone.

Directory of Open Access Journals (Sweden)

Kenji Matsuura

Full Text Available Social insects rely heavily on pheromone communication to maintain their sociality. Egg protection is one of the most fundamental social behaviours in social insects. The recent discovery of the termite-egg mimicking fungus 'termite-ball' and subsequent studies on termite egg protection behaviour have shown that termites can be manipulated by using the termite egg recognition pheromone (TERP, which strongly evokes the egg-carrying and -grooming behaviours of workers. Despite the great scientific and economic importance, TERP has not been identified because of practical difficulties. Herein we identified the antibacterial protein lysozyme as the TERP. We isolated the target protein using ion-exchange and hydrophobic interaction chromatography, and the MALDI-TOF MS analysis showed a molecular size of 14.5 kDa. We found that the TERP provided antibacterial activity against a gram-positive bacterium. Among the currently known antimicrobial proteins, the molecular size of 14.5 kDa limits the target to lysozyme. Termite lysozymes obtained from eggs and salivary glands, and even hen egg lysozyme, showed a strong termite egg recognition activity. Besides eggs themselves, workers also supply lysozyme to eggs through frequent egg-grooming, by which egg surfaces are coated with saliva containing lysozyme. Reverse transcript PCR analysis showed that mRNA of termite lysozyme was expressed in both salivary glands and eggs. Western blot analysis confirmed that lysozyme production begins in immature eggs in queen ovaries. This is the first identification of proteinaceous pheromone in social insects. Researchers have focused almost exclusively on hydrocarbons when searching for recognition pheromones in social insects. The present finding of a proteinaceous pheromone represents a major step forward in, and result in the broadening of, the search for recognition pheromones. This novel function of lysozyme as a termite pheromone illuminates the profound influence

Deep Multimodal Pain Recognition: A Database and Comparison of Spatio-Temporal Visual Modalities

DEFF Research Database (Denmark)

Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.

2018-01-01

, exploiting both spatial and temporal information of the face to assess pain level, and second, incorporating multiple visual modalities to capture complementary face information related to pain. Most works in the literature focus on merely exploiting spatial information on chromatic (RGB) video data......PAIN)' database, for RGBDT pain level recognition in sequences. We provide a first baseline results including 5 pain levels recognition by analyzing independent visual modalities and their fusion with CNN and LSTM models. From the experimental evaluation we observe that fusion of modalities helps to enhance...... recognition performance of pain levels in comparison to isolated ones. In particular, the combination of RGB, D, and T in an early fusion fashion achieved the best recognition rate....

Embedded Face Detection and Recognition

Directory of Open Access Journals (Sweden)

Göksel Günlü

2012-10-01

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

Adaptive frozen orbital treatment for the fragment molecular orbital method combined with density-functional tight-binding

Science.gov (United States)

Nishimoto, Yoshio; Fedorov, Dmitri G.

2018-02-01

The exactly analytic gradient is derived and implemented for the fragment molecular orbital (FMO) method combined with density-functional tight-binding (DFTB) using adaptive frozen orbitals. The response contributions which arise from freezing detached molecular orbitals on the border between fragments are computed by solving Z-vector equations. The accuracy of the energy, its gradient, and optimized structures is verified on a set of representative inorganic materials and polypeptides. FMO-DFTB is applied to optimize the structure of a silicon nano-wire, and the results are compared to those of density functional theory and experiment. FMO accelerates the DFTB calculation of a boron nitride nano-ring with 7872 atoms by a factor of 406. Molecular dynamics simulations using FMO-DFTB applied to a 10.7 μm chain of boron nitride nano-rings, consisting of about 1.2 × 106 atoms, reveal the rippling and twisting of nano-rings at room temperature.

Identification of anti-filarial leads against aspartate semialdehyde dehydrogenase of Wolbachia endosymbiont of Brugia malayi: combined molecular docking and molecular dynamics approaches.

Science.gov (United States)

Amala, Mathimaran; Rajamanikandan, Sundaraj; Prabhu, Dhamodharan; Surekha, Kanagarajan; Jeyakanthan, Jeyaraman

2018-02-06

Lymphatic filariasis is a debilitating vector borne parasitic disease that infects human lymphatic system by nematode Brugia malayi. Currently available anti-filarial drugs are effective only on the larval stages of parasite. So far, no effective drugs are available for humans to treat filarial infections. In this regard, aspartate semialdehyde dehydrogenase (ASDase) in lysine biosynthetic pathway from Wolbachia endosymbiont Brugia malayi represents an attractive therapeutic target for the development of novel anti-filarial agents. In this present study, molecular modeling combined with molecular dynamics simulations and structure-based virtual screening were performed to identify potent lead molecules against ASDase. Based on Glide score, toxicity profile, binding affinity and mode of interactions with the ASDase, five potent lead molecules were selected. The molecular docking and dynamics results revealed that the amino acid residues Arg103, Asn133, Cys134, Gln161, Ser164, Lys218, Arg239, His246, and Asn321 plays a crucial role in effective binding of Top leads into the active site of ASDase. The stability of the ASDase-lead complexes was confirmed by running the 30 ns molecular dynamics simulations. The pharmacokinetic properties of the identified lead molecules are in the acceptable range. Furthermore, density functional theory and binding free energy calculations were performed to rank the lead molecules. Thus, the identified lead molecules can be used for the development of anti-filarial agents to combat the pathogenecity of Brugia malayi.

[Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

Science.gov (United States)

Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

2012-07-01

In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

Tracking and recognition face in videos with incremental local sparse representation model

Science.gov (United States)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

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

Science.gov (United States)

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.

Episodic Reasoning for Vision-Based Human Action Recognition

Directory of Open Access Journals (Sweden)

Maria J. Santofimia

2014-01-01

Full Text Available Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.

СHIRAL RECOGNITION OF CYSTEINE MOLECULES BY CHIRAL CdSe AND CdS QUANTUM DOTS

Directory of Open Access Journals (Sweden)

M. V. Mukhina

2015-11-01

Full Text Available Here, we report the investigation of mechanism of chiral molecular recognition of cysteine biomolecules by chiral CdSe and CdS semiconductor nanocrystals. To observe chiral recognition process, we prepared enantioenriched ensembles of the nanocrystals capped with achiral ligand. The enantioenriched samples of intrinsically chiral CdSe quantum dots were prepared by separation of initial racemic mixture of the nanocrystals using chiral phase transfer from chloroform to water driven by L- and D-cysteine. Chiral molecules of cysteine and penicillamine were substituted for achiral molecules of dodecanethiol on the surfaces of CdSe and CdS samples, respectively, via reverse phase transfer from water to chloroform. We estimated an efficiency of the hetero- (d-L or l-D and homocomplexes (l-L formation by comparing the extents of corresponding complexing reactions. Using circular dichroism spectroscopy data we show an ability of nanocrystals enantiomers to discriminate between left-handed and right-handed enantiomers of biomolecules via preferential formation of heterocomplexes. Development of approaches for obtaining chiral nanocrystals via chiral phase transfer offers opportunities for investigation of molecular recognition at the nano/bio interfaces.

Chinese handwriting recognition an algorithmic perspective

CERN Document Server

Su, Tonghua

2013-01-01

This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focused on. Baseline systems are initially presented for these strategies and are subsequently expanded on and incrementally improved. The sophisticated algorithms covered include: 1) string sample expansion algorithms which synthesize string samples from isolated characters or distort realistic string samples; 2) enhanced feature representation algorithms, e.g. enhanced four-plane features and Delta features; 3) novel learning algorithms, such as Perceptron learning with dynamic margin, MPE training and distributed training; and lastly 4) ensemble algorithms, that is, combining the two strategies using both parallel structure and serial structure. All the while, the book moves from basic to advanced algorithms, helping ...

Re-thinking employee recognition: understanding employee experiences of recognition

OpenAIRE

Smith, Charlotte

2013-01-01

Despite widespread acceptance of the importance of employee recognition for both individuals and organisations and evidence of its increasing use in organisations, employee recognition has received relatively little focused attention from academic researchers. Particularly lacking is research exploring the lived experience of employee recognition and the interpretations and meanings which individuals give to these experiences. Drawing on qualitative interviews conducted as part of my PhD rese...

Synthesis of a pH-Sensitive Hetero[4]Rotaxane Molecular Machine that Combines [c2]Daisy and [2]Rotaxane Arrangements.

Science.gov (United States)

Waelès, Philip; Riss-Yaw, Benjamin; Coutrot, Frédéric

2016-05-10

The synthesis of a novel pH-sensitive hetero[4]rotaxane molecular machine through a self-sorting strategy is reported. The original tetra-interlocked molecular architecture combines a [c2]daisy chain scaffold linked to two [2]rotaxane units. Actuation of the system through pH variation is possible thanks to the specific interactions of the dibenzo-24-crown-8 (DB24C8) macrocycles for ammonium, anilinium, and triazolium molecular stations. Selective deprotonation of the anilinium moieties triggers shuttling of the unsubstituted DB24C8 along the [2]rotaxane units. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proposed biomimetic molecular sensor array for astrobiology applications

Science.gov (United States)

Cullen, D. C.; Grant, W. D.; Piletsky, S.; Sims, M. R.

2001-08-01

A key objective of future astrobiology lander missions, e.g. to Mars and Europa, is the detection of biomarkers - molecules whose presence indicates the existence of either current or extinct life. To address limitations of current analytical methods for biomarker detection, we describe the methodology of a new project for demonstration of a robust molecular-recognition sensor array for astrobiology biomarkers. The sensor array will be realised by assembling components that have been demonstrated individually in previous or current research projects. The major components are (1) robust artificial molecular receptors comprised of molecular imprinted polymer (MIP) recognition systems and (2) a sensor array comprised of both optical and electrochemical sensor elements. These components will be integrated together using ink-jet printing technology coupled with in situ photo-polymerisation of MIPs. For demonstration, four model biomarkers are chosen as targets and represent various classes of potential biomarkers. Objectives of the proposed work include (1) demonstration of practical proof-of-concept, (2) identify areas for further development and (3) provide performance and design data for follow-up projects leading to astrobiology missions.

People's Risk Recognition Preceding Evacuation and Its Role in Demand Modeling and Planning.

Science.gov (United States)

Urata, Junji; Pel, Adam J

2018-05-01

Evacuation planning and management involves estimating the travel demand in the event that such action is required. This is usually done as a function of people's decision to evacuate, which we show is strongly linked to their risk awareness. We use an empirical data set, which shows tsunami evacuation behavior, to demonstrate that risk recognition is not synonymous with objective risk, but is instead determined by a combination of factors including risk education, information, and sociodemographics, and that it changes dynamically over time. Based on these findings, we formulate an ordered logit model to describe risk recognition combined with a latent class model to describe evacuation choices. Our proposed evacuation choice model along with a risk recognition class can evaluate quantitatively the influence of disaster mitigation measures, risk education, and risk information. The results obtained from the risk recognition model show that risk information has a greater impact in the sense that people recognize their high risk. The results of the evacuation choice model show that people who are unaware of their risk take a longer time to evacuate. © 2017 Society for Risk Analysis.

A General Polygon-based Deformable Model for Object Recognition

DEFF Research Database (Denmark)

Jensen, Rune Fisker; Carstensen, Jens Michael

1999-01-01

We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic distr...

Cross-recognition of a pit viper (Crotalinae) polyspecific antivenom explored through high-density peptide microarray epitope mapping

DEFF Research Database (Denmark)

Engmark, Mikael; Lomonte, Bruno; Gutiérrez, José María

2017-01-01

Snakebite antivenom is a 120 years old invention based on polyclonal mixtures of antibodies purified from the blood of hyper-immunized animals. Knowledge on antibody recognition sites (epitopes) on snake venom proteins is limited, but may be used to provide molecular level explanations...... for antivenom cross-reactivity. In turn, this may help guide antivenom development by elucidating immunological biases in existing antivenoms. In this study, we have identified and characterized linear elements of B-cell epitopes from 870 pit viper venom protein sequences by employing a high......-throughput methodology based on custom designed high-density peptide microarrays. By combining data on antibody-peptide interactions with multiple sequence alignments of homologous toxin sequences and protein modelling, we have determined linear elements of antibody binding sites for snake venom metalloproteases (SVMPs...

Two-step calibration method for multi-algorithm score-based face recognition systems by minimizing discrimination loss

NARCIS (Netherlands)

Susyanto, N.; Veldhuis, R.N.J.; Spreeuwers, L.J.; Klaassen, C.A.J.; Fierrez, J.; Li, S.Z.; Ross, A.; Veldhuis, R.; Alonso-Fernandez, F.; Bigun, J.

2016-01-01

We propose a new method for combining multi-algorithm score-based face recognition systems, which we call the two-step calibration method. Typically, algorithms for face recognition systems produce dependent scores. The two-step method is based on parametric copulas to handle this dependence. Its

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

Science.gov (United States)

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

Combination of cross-sectional and molecular imaging studies in the localization of gastroenteropancreatic neuroendocrine tumors.

Science.gov (United States)

Toumpanakis, Christos; Kim, Michelle K; Rinke, Anja; Bergestuen, Deidi S; Thirlwell, Christina; Khan, Mohid S; Salazar, Ramon; Oberg, Kjell

2014-01-01

aggressive disease course. When a secondary malignancy has already been established or is strongly suspected, combining molecular imaging techniques (e.g. (18)F-FDG PET and (68)Ga-DOTA PET) takes advantage of the diverse avidities of different tumor types to differentiate lesions of different origins. All the above-mentioned molecular imaging studies should always be reviewed and interpreted in a multidisciplinary (tumor board) meeting in combination with the conventional cross-sectional imaging, as the latter remains the imaging of choice for the evaluation of treatment response and disease follow-up. © 2014 S. Karger AG, Basel

Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates

Directory of Open Access Journals (Sweden)

Melisa Edith Gantner

2013-01-01

Full Text Available ABC efflux transporters are polyspecific members of the ABC superfamily that, acting as drug and metabolite carriers, provide a biochemical barrier against drug penetration and contribute to detoxification. Their overexpression is linked to multidrug resistance issues in a diversity of diseases. Breast cancer resistance protein (BCRP is the most expressed ABC efflux transporter throughout the intestine and the blood-brain barrier, limiting oral absorption and brain bioavailability of its substrates. Early recognition of BCRP substrates is thus essential to optimize oral drug absorption, design of novel therapeutics for central nervous system conditions, and overcome BCRP-mediated cross-resistance issues. We present the development of an ensemble of ligand-based machine learning algorithms for the early recognition of BCRP substrates, from a database of 262 substrates and nonsubstrates compiled from the literature. Such dataset was rationally partitioned into training and test sets by application of a 2-step clustering procedure. The models were developed through application of linear discriminant analysis to random subsamples of Dragon molecular descriptors. Simple data fusion and statistical comparison of partial areas under the curve of ROC curves were applied to obtain the best 2-model combination, which presented 82% and 74.5% of overall accuracy in the training and test set, respectively.

Graphical symbol recognition

OpenAIRE

K.C. , Santosh; Wendling , Laurent

2015-01-01

International audience; The chapter focuses on one of the key issues in document image processing i.e., graphical symbol recognition. Graphical symbol recognition is a sub-field of a larger research domain: pattern recognition. The chapter covers several approaches (i.e., statistical, structural and syntactic) and specially designed symbol recognition techniques inspired by real-world industrial problems. It, in general, contains research problems, state-of-the-art methods that convey basic s...

Impact of noise and other factors on speech recognition in anaesthesia

DEFF Research Database (Denmark)

Alapetite, Alexandre

2008-01-01

of training. Methods: Eight volunteers read aloud a total of about 3 600 typical short anaesthesia comments to be transcribed by a continuous speech recognition system. Background noises were collected in an operating room and reproduced. A regression analysis and descriptive statistics were done to evaluate...... operations. Objective: The aim of the experiment is to evaluate the relative impact of several factors affecting speech recognition when used in operating rooms, such as the type or loudness of background noises, type of microphone, type of recognition mode (free speech versus command mode), and type...... the relative effect of various factors. Results: Some factors have a major impact, such as the words to be recognised, the type of recognition, and participants. The type of microphone is especially significant when combined with the type of noise. While loud noises in the operating room can have a predominant...

Phytosterol Recognition via Rationally Designed Molecularly Imprinted Polymers

Directory of Open Access Journals (Sweden)

Lachlan J. Schwarz

2018-02-01

Full Text Available Molecularly imprinted polymers (MIPs prepared via a semi-covalent imprinting strategy using stigmasteryl methacrylate as a polymerisable template have been evaluated by static binding methods for their ability to selectively capture other valuable phytosterol targets, including campesterol and brassicasterol. Design criteria based on molecular modelling procedures and interaction energy calculations were employed to aid the selection of the co-monomer type, as well as the choice of co-monomer:template ratios for the formation of the pre-polymerisation complex. These novel hybrid semi-covalently imprinted polymers employed N,N′-dimethylacryl-amide (N,N′-DMAAM as the functional co-monomer and displayed specific binding capacities in the range 5.2–5.9 mg sterol/g MIP resin. Their binding attributes and selectivities towards phytosterol compounds were significantly different to the corresponding MIPs prepared via non-covalent procedures or when compared to non-imprinted polymers. Cross-reactivity studies using stigmasterol, ergosterol, cholesterol, campesterol, and brassicasterol as single analytes revealed the importance of the A-ring C-3-β-hydroxyl group and the orientational preferences of the D-ring alkyl chain structures in their interaction in the templated cavity with the N,N′-dimethylamide functional groups of the MIP. Finally, to obtain useful quantities of both campersterol and brassicasterol for these investigations, improved synthetic routes have been developed to permit the conversion of the more abundant, lower cost stigmasterol via a reactive aldehyde intermediate to these other sterols.

Insight into the binding interactions of CYP450 aromatase inhibitors with their target enzyme: a combined molecular docking and molecular dynamics study.

Science.gov (United States)

Galeazzi, Roberta; Massaccesi, Luca

2012-03-01

CYP450 aromatase catalyzes the terminal and rate-determining step in estrogen synthesis, the aromatization of androgens, and its inhibition is an efficient approach to treating estrogen-dependent breast cancer. Insight into the molecular basis of the interaction at the catalytic site between CYP450 aromatase inhibitors and the enzyme itself is required in order to design new and more active compounds. Hence, a combined molecular docking-molecular dynamics study was carried out to obtain the structure of the lowest energy association complexes of aromatase with some third-generation aromatase inhibitors (AIs) and with other novel synthesized letrozole-derived compounds which showed high in vitro activity. The results obtained clearly demonstrate the role of the pharmacophore groups present in the azaheterocyclic inhibitors (NSAIs)-namely the triazolic ring and highly functionalized aromatic moieties carrying H-bond donor or acceptor groups. In particular, it was pointed out that all of them can contribute to inhibition activity by interacting with residues of the catalytic cleft, but the amino acids involved are different for each compound, even if they belong to the same class. Furthermore, the azaheterocyclic group strongly coordinates with the Fe(II) of heme cysteinate in the most active NSAI complexes, while it prefers to adopt another orientation in less active ones.

Differential Recognition of Old World and New World Arenavirus Envelope Glycoproteins by Subtilisin Kexin Isozyme 1 (SKI-1)/Site 1 Protease (S1P)

Science.gov (United States)

Burri, Dominique J.; Ramos da Palma, Joel; Seidah, Nabil G.; Zanotti, Giuseppe; Cendron, Laura

2013-01-01

The arenaviruses are an important family of emerging viruses that includes several causative agents of severe hemorrhagic fevers in humans that represent serious public health problems. A crucial step of the arenavirus life cycle is maturation of the envelope glycoprotein precursor (GPC) by the cellular subtilisin kexin isozyme 1 (SKI-1)/site 1 protease (S1P). Comparison of the currently known sequences of arenavirus GPCs revealed the presence of a highly conserved aromatic residue at position P7 relative to the SKI-1/S1P cleavage side in Old World and clade C New World arenaviruses but not in New World viruses of clades A and B or cellular substrates of SKI-1/S1P. Using a combination of molecular modeling and structure-function analysis, we found that residueY285 of SKI-1/S1P, distal from the catalytic triad, is implicated in the molecular recognition of the aromatic “signature residue” at P7 in the GPC of Old World Lassa virus. Using a quantitative biochemical approach, we show that Y285 of SKI-1/S1P is crucial for the efficient processing of peptides derived from Old World and clade C New World arenavirus GPCs but not of those from clade A and B New World arenavirus GPCs. The data suggest that during coevolution with their mammalian hosts, GPCs of Old World and clade C New World viruses expanded the molecular contacts with SKI-1/S1P beyond the classical four-amino-acid recognition sequences and currently occupy an extended binding pocket. PMID:23536681

Toward noncooperative iris recognition: a classification approach using multiple signatures.

Science.gov (United States)

Proença, Hugo; Alexandre, Luís A

2007-04-01

This paper focuses on noncooperative iris recognition, i.e., the capture of iris images at large distances, under less controlled lighting conditions, and without active participation of the subjects. This increases the probability of capturing very heterogeneous images (regarding focus, contrast, or brightness) and with several noise factors (iris obstructions and reflections). Current iris recognition systems are unable to deal with noisy data and substantially increase their error rates, especially the false rejections, in these conditions. We propose an iris classification method that divides the segmented and normalized iris image into six regions, makes an independent feature extraction and comparison for each region, and combines each of the dissimilarity values through a classification rule. Experiments show a substantial decrease, higher than 40 percent, of the false rejection rates in the recognition of noisy iris images.

Perceptual Confusions Among Consonants, Revisited: Cross-Spectral Integration of Phonetic-Feature Information and Consonant Recognition

DEFF Research Database (Denmark)

Christiansen, Thomas Ulrich; Greenberg, Steven

2012-01-01

The perceptual basis of consonant recognition was experimentally investigated through a study of how information associated with phonetic features (Voicing, Manner, and Place of Articulation) combines across the acoustic-frequency spectrum. The speech signals, 11 Danish consonants embedded...... in Consonant + Vowel + Liquid syllables, were partitioned into 3/4-octave bands (“slits”) centered at 750 Hz, 1500 Hz, and 3000 Hz, and presented individually and in two- or three-slit combinations. The amount of information transmitted (IT) was calculated from consonant- confusion matrices for each feature...... the bands are essentially independent in terms of decoding this feature. Because consonant recognition and Place decoding are highly correlated (correlation coefficient r2 = 0.99), these results imply that the auditory processes underlying consonant recognition are not strictly linear. This may account...

An Edge-Based Macao License Plate Recognition System

Directory of Open Access Journals (Sweden)

Chi-Man Pun

2011-04-01

Full Text Available This paper presents a system to recognize Macao license plates. Sobel edge detector is employed to extract the vertical edges, and an edge composition algorithm is proposed to combine the edges into candidate plate regions. They are further examined on the existence of the character qMq by a verification algorithm. A row separation algorithm is also proposed to cater both one-row and two-row types of plates. Projection analysis and template matching methods are exploited to segment and recognize the characters. Various pre and post processing steps are proposed other than traditional implementation so as to improve the recognition accuracy. This work achieves a high recognition rate of 95%.

Atomistic insight into the catalytic mechanism of glycosyltransferases by combined quantum mechanics/molecular mechanics (QM/MM) methods.

Science.gov (United States)

Tvaroška, Igor

2015-02-11

Glycosyltransferases catalyze the formation of glycosidic bonds by assisting the transfer of a sugar residue from donors to specific acceptor molecules. Although structural and kinetic data have provided insight into mechanistic strategies employed by these enzymes, molecular modeling studies are essential for the understanding of glycosyltransferase catalyzed reactions at the atomistic level. For such modeling, combined quantum mechanics/molecular mechanics (QM/MM) methods have emerged as crucial. These methods allow the modeling of enzymatic reactions by using quantum mechanical methods for the calculation of the electronic structure of the active site models and treating the remaining enzyme environment by faster molecular mechanics methods. Herein, the application of QM/MM methods to glycosyltransferase catalyzed reactions is reviewed, and the insight from modeling of glycosyl transfer into the mechanisms and transition states structures of both inverting and retaining glycosyltransferases are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Research on Attribute Reduction in Hoisting Motor State Recognition of Quayside Container Crane

Science.gov (United States)

Li, F.; Tang, G.; Hu, X.

2017-07-01

In view of too many attributes in hoisting motor state recognition of quayside container crane. Attribute reduction method based on discernibility matrix is introduced to attribute reduction of lifting motor state information table. A method of attribute reduction based on the combination of rough set and genetic algorithm is proposed to deal with the hoisting motor state decision table. Under the condition that the information system's decision-making ability is unchanged, the redundant attribute is deleted. Which reduces the complexity and computation of the recognition process of the hoisting motor. It is possible to realize the fast state recognition.

Investigations into the origin of the molecular recognition of several adenosine deaminase inhibitors.

Science.gov (United States)

Gillerman, Irina; Fischer, Bilha

2011-01-13

Inhibitors of adenosine deaminase (ADA, EC 3.5.4.4) are potential therapeutic agents for the treatment of various health disorders. Several highly potent inhibitors were previously identified, yet they exhibit unacceptable toxicities. We performed a SAR study involving a series of C2 or C8 substituted purine-riboside analogues with a view to discover less potent inhibitors with a lesser toxicity. We found that any substitution at C8 position of nebularine resulted in total loss of activity toward calf intestinal ADA. However, several 2-substituted-adenosine, 8-aza-adenosine, and nebularine analogues exhibited inhibitory activity. Specifically, 2-Cl-purine riboside, 8-aza-2-thiohexyl adenosine, 2-thiohexyl adenosine, and 2-MeS-purine riboside were found to be competitive inhibitors of ADA with K(i) values of 25, 22, 6, and 3 μM, respectively. We concluded that electronic parameters are not major recognition determinants of ADA but rather steric parameters. A C2 substituent which fits ADA hydrophobic pocket and improves H-bonding with the enzyme makes a good inhibitor. In addition, a gg rotamer about C4'-C5' bond is apparently an important recognition determinant.

Appearance-based human gesture recognition using multimodal features for human computer interaction

Science.gov (United States)

Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

2011-03-01

The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

Prefixes versus suffixes: a search for a word-beginning superiority effect in word recognition from degraded speech

NARCIS (Netherlands)

Nooteboom, S.G.; Vlugt, van der M.J.

1985-01-01

This paper reports on a word recognition experiment in search of evidence for a word- beginning superiority effect in recognition from low-quality speech . In the experiment, lexical redundancy was controlled by combining monosyllable word stems with strongly constraining or weakly constraining

Synthesis of a specific monolithic column with artificial recognition sites for L-glutamic acid via cryo-crosslinking of imprinted nanoparticles.

Science.gov (United States)

Göktürk, Ilgım; Üzek, Recep; Uzun, Lokman; Denizli, Adil

2016-06-01

In this study, a new molecular imprinting (MIP)-based monolithic cryogel column was prepared using chemically crosslinked molecularly imprinted nanoparticles, to achieve a simplified chromatographic separation (SPE) for a model compound, L-glutamic acid (L-Glu). Cryogelation through crosslinking of imprinted nanoparticles forms stable monolithic cryogel columns. This technique reduces the leakage of nanoparticles and increases the surface area, while protecting the structural features of the cryogel for stable and efficient recognition of the template molecule. A non-imprinted monolithic cryogel column (NIP) was also prepared, using non-imprinted nanoparticles produced without the addition of L-Glu during polymerization. The molecularly imprinted monolithic cryogel column (MIP) indicates apparent recognition selectivity and a good adsorption capacity compared to the NIP. Also, we have achieved a significant increase in the adsorption capacity, using the advantage of high surface area of the nanoparticles.

Integrating Automatic Speech Recognition and Machine Translation for Better Translation Outputs

DEFF Research Database (Denmark)

Liyanapathirana, Jeevanthi

translations, combining machine translation with computer assisted translation has drawn attention in current research. This combines two prospects: the opportunity of ensuring high quality translation along with a significant performance gain. Automatic Speech Recognition (ASR) is another important area......, which caters important functionalities in language processing and natural language understanding tasks. In this work we integrate automatic speech recognition and machine translation in parallel. We aim to avoid manual typing of possible translations as dictating the translation would take less time...... to the n-best list rescoring, we also use word graphs with the expectation of arriving at a tighter integration of ASR and MT models. Integration methods include constraining ASR models using language and translation models of MT, and vice versa. We currently develop and experiment different methods...

Metal cofactor modulated folding and target recognition of HIV-1 NCp7.

Science.gov (United States)

Ren, Weitong; Ji, Dongqing; Xu, Xiulian

2018-01-01

The HIV-1 nucleocapsid 7 (NCp7) plays crucial roles in multiple stages of HIV-1 life cycle, and its biological functions rely on the binding of zinc ions. Understanding the molecular mechanism of how the zinc ions modulate the conformational dynamics and functions of the NCp7 is essential for the drug development and HIV-1 treatment. In this work, using a structure-based coarse-grained model, we studied the effects of zinc cofactors on the folding and target RNA(SL3) recognition of the NCp7 by molecular dynamics simulations. After reproducing some key properties of the zinc binding and folding of the NCp7 observed in previous experiments, our simulations revealed several interesting features in the metal ion modulated folding and target recognition. Firstly, we showed that the zinc binding makes the folding transition states of the two zinc fingers less structured, which is in line with the Hammond effect observed typically in mutation, temperature or denaturant induced perturbations to protein structure and stability. Secondly, We showed that there exists mutual interplay between the zinc ion binding and NCp7-target recognition. Binding of zinc ions enhances the affinity between the NCp7 and the target RNA, whereas the formation of the NCp7-RNA complex reshapes the intrinsic energy landscape of the NCp7 and increases the stability and zinc affinity of the two zinc fingers. Thirdly, by characterizing the effects of salt concentrations on the target RNA recognition, we showed that the NCp7 achieves optimal balance between the affinity and binding kinetics near the physiologically relevant salt concentrations. In addition, the effects of zinc binding on the inter-domain conformational flexibility and folding cooperativity of the NCp7 were also discussed.

Metal cofactor modulated folding and target recognition of HIV-1 NCp7.

Directory of Open Access Journals (Sweden)

Weitong Ren

Full Text Available The HIV-1 nucleocapsid 7 (NCp7 plays crucial roles in multiple stages of HIV-1 life cycle, and its biological functions rely on the binding of zinc ions. Understanding the molecular mechanism of how the zinc ions modulate the conformational dynamics and functions of the NCp7 is essential for the drug development and HIV-1 treatment. In this work, using a structure-based coarse-grained model, we studied the effects of zinc cofactors on the folding and target RNA(SL3 recognition of the NCp7 by molecular dynamics simulations. After reproducing some key properties of the zinc binding and folding of the NCp7 observed in previous experiments, our simulations revealed several interesting features in the metal ion modulated folding and target recognition. Firstly, we showed that the zinc binding makes the folding transition states of the two zinc fingers less structured, which is in line with the Hammond effect observed typically in mutation, temperature or denaturant induced perturbations to protein structure and stability. Secondly, We showed that there exists mutual interplay between the zinc ion binding and NCp7-target recognition. Binding of zinc ions enhances the affinity between the NCp7 and the target RNA, whereas the formation of the NCp7-RNA complex reshapes the intrinsic energy landscape of the NCp7 and increases the stability and zinc affinity of the two zinc fingers. Thirdly, by characterizing the effects of salt concentrations on the target RNA recognition, we showed that the NCp7 achieves optimal balance between the affinity and binding kinetics near the physiologically relevant salt concentrations. In addition, the effects of zinc binding on the inter-domain conformational flexibility and folding cooperativity of the NCp7 were also discussed.

Vehicle license plate recognition based on geometry restraints and multi-feature decision

Science.gov (United States)

Wu, Jianwei; Wang, Zongyue

2005-10-01

Vehicle license plate (VLP) recognition is of great importance to many traffic applications. Though researchers have paid much attention to VLP recognition there has not been a fully operational VLP recognition system yet for many reasons. This paper discusses a valid and practical method for vehicle license plate recognition based on geometry restraints and multi-feature decision including statistical and structural features. In general, the VLP recognition includes the following steps: the location of VLP, character segmentation, and character recognition. This paper discusses the three steps in detail. The characters of VLP are always declining caused by many factors, which makes it more difficult to recognize the characters of VLP, therefore geometry restraints such as the general ratio of length and width, the adjacent edges being perpendicular are used for incline correction. Image Moment has been proved to be invariant to translation, rotation and scaling therefore image moment is used as one feature for character recognition. Stroke is the basic element for writing and hence taking it as a feature is helpful to character recognition. Finally we take the image moment, the strokes and the numbers of each stroke for each character image and some other structural features and statistical features as the multi-feature to match each character image with sample character images so that each character image can be recognized by BP neural net. The proposed method combines statistical and structural features for VLP recognition, and the result shows its validity and efficiency.

Target recognition of ladar range images using even-order Zernike moments.

Science.gov (United States)

Liu, Zheng-Jun; Li, Qi; Xia, Zhi-Wei; Wang, Qi

2012-11-01

Ladar range images have attracted considerable attention in automatic target recognition fields. In this paper, Zernike moments (ZMs) are applied to classify the target of the range image from an arbitrary azimuth angle. However, ZMs suffer from high computational costs. To improve the performance of target recognition based on small samples, even-order ZMs with serial-parallel backpropagation neural networks (BPNNs) are applied to recognize the target of the range image. It is found that the rotation invariance and classified performance of the even-order ZMs are both better than for odd-order moments and for moments compressed by principal component analysis. The experimental results demonstrate that combining the even-order ZMs with serial-parallel BPNNs can significantly improve the recognition rate for small samples.

Recall and recognition of verbal paired associates in early Alzheimer's disease.

Science.gov (United States)

Lowndes, G J; Saling, M M; Ames, D; Chiu, E; Gonzalez, L M; Savage, G R

2008-07-01

The primary impairment in early Alzheimer's disease (AD) is encoding/consolidation, resulting from medial temporal lobe (MTL) pathology. AD patients perform poorly on cued-recall paired associate learning (PAL) tasks, which assess the ability of the MTLs to encode relational memory. Since encoding and retrieval processes are confounded within performance indexes on cued-recall PAL, its specificity for AD is limited. Recognition paradigms tend to show good specificity for AD, and are well tolerated, but are typically less sensitive than recall tasks. Associate-recognition is a novel PAL task requiring a combination of recall and recognition processes. We administered a verbal associate-recognition test and cued-recall analogue to 22 early AD patients and 55 elderly controls to compare their ability to discriminate these groups. Both paradigms used eight arbitrarily related word pairs (e.g., pool-teeth) with varying degrees of imageability. Associate-recognition was equally effective as the cued-recall analogue in discriminating the groups, and logistic regression demonstrated classification rates by both tasks were equivalent. These preliminary findings provide support for the clinical value of this recognition tool. Conceptually it has potential for greater specificity in informing neuropsychological diagnosis of AD in clinical samples but this requires further empirical support.

A multi-view face recognition system based on cascade face detector and improved Dlib

Science.gov (United States)

Zhou, Hongjun; Chen, Pei; Shen, Wei

2018-03-01

In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

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

Science.gov (United States)

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

2015-01-01

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

Statistical Pattern Recognition

CERN Document Server

Webb, Andrew R

2011-01-01

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

Recent Advances in Multinuclear NMR Spectroscopy for Chiral Recognition of Organic Compounds

Directory of Open Access Journals (Sweden)

Márcio S. Silva

2017-02-01

Full Text Available Nuclear magnetic resonance (NMR is a powerful tool for the elucidation of chemical structure and chiral recognition. In the last decade, the number of probes, media, and experiments to analyze chiral environments has rapidly increased. The evaluation of chiral molecules and systems has become a routine task in almost all NMR laboratories, allowing for the determination of molecular connectivities and the construction of spatial relationships. Among the features that improve the chiral recognition abilities by NMR is the application of different nuclei. The simplicity of the multinuclear NMR spectra relative to 1H, the minimal influence of the experimental conditions, and the larger shift dispersion make these nuclei especially suitable for NMR analysis. Herein, the recent advances in multinuclear (19F, 31P, 13C, and 77Se NMR spectroscopy for chiral recognition of organic compounds are presented. The review describes new chiral derivatizing agents and chiral solvating agents used for stereodiscrimination and the assignment of the absolute configuration of small organic compounds.

Robust Pedestrian Tracking and Recognition from FLIR Video: A Unified Approach via Sparse Coding

Directory of Open Access Journals (Sweden)

Xin Li

2014-06-01

Full Text Available Sparse coding is an emerging method that has been successfully applied to both robust object tracking and recognition in the vision literature. In this paper, we propose to explore a sparse coding-based approach toward joint object tracking-and-recognition and explore its potential in the analysis of forward-looking infrared (FLIR video to support nighttime machine vision systems. A key technical contribution of this work is to unify existing sparse coding-based approaches toward tracking and recognition under the same framework, so that they can benefit from each other in a closed-loop. On the one hand, tracking the same object through temporal frames allows us to achieve improved recognition performance through dynamical updating of template/dictionary and combining multiple recognition results; on the other hand, the recognition of individual objects facilitates the tracking of multiple objects (i.e., walking pedestrians, especially in the presence of occlusion within a crowded environment. We report experimental results on both the CASIAPedestrian Database and our own collected FLIR video database to demonstrate the effectiveness of the proposed joint tracking-and-recognition approach.

Dynamic combinatorial libraries: from exploring molecular recognition to systems chemistry.

Science.gov (United States)

Li, Jianwei; Nowak, Piotr; Otto, Sijbren

2013-06-26

Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines.

Emotion recognition based on multiple order features using fractional Fourier transform