Kruskal-Wallis-based computationally efficient feature selection for face recognition.

PubMed

Ali Khan, Sajid; Hussain, Ayyaz; Basit, Abdul; Akram, Sheeraz

2014-01-01

Face recognition in today's technological world, and face recognition applications attain much more importance. Most of the existing work used frontal face images to classify face image. However these techniques fail when applied on real world face images. The proposed technique effectively extracts the prominent facial features. Most of the features are redundant and do not contribute to representing face. In order to eliminate those redundant features, computationally efficient algorithm is used to select the more discriminative face features. Extracted features are then passed to classification step. In the classification step, different classifiers are ensemble to enhance the recognition accuracy rate as single classifier is unable to achieve the high accuracy. Experiments are performed on standard face database images and results are compared with existing techniques.

Wavelet Packet Feature Assessment for High-Density Myoelectric Pattern Recognition and Channel Selection toward Stroke Rehabilitation.

PubMed

Wang, Dongqing; Zhang, Xu; Gao, Xiaoping; Chen, Xiang; Zhou, Ping

2016-01-01

This study presents wavelet packet feature assessment of neural control information in paretic upper limb muscles of stroke survivors for myoelectric pattern recognition, taking advantage of high-resolution time-frequency representations of surface electromyogram (EMG) signals. On this basis, a novel channel selection method was developed by combining the Fisher's class separability index and the sequential feedforward selection analyses, in order to determine a small number of appropriate EMG channels from original high-density EMG electrode array. The advantages of the wavelet packet features and the channel selection analyses were further illustrated by comparing with previous conventional approaches, in terms of classification performance when identifying 20 functional arm/hand movements implemented by 12 stroke survivors. This study offers a practical approach including paretic EMG feature extraction and channel selection that enables active myoelectric control of multiple degrees of freedom with paretic muscles. All these efforts will facilitate upper limb dexterity restoration and improved stroke rehabilitation.

New Approaches Towards Recognition of Nucleic Acid Triple Helices

PubMed Central

Arya, Dev P.

2012-01-01

We show that groove recognition of nucleic acid triple helices can be achieved with aminosugars. Among these aminosugars, neomycin is the most effective aminoglycoside (groove binder) for stabilizing a DNA triple helix. It stabilizes both the T·A·T triplex and mixed-base DNA triplexes better than known DNA minor groove binders (which usually destabilize the triplex) and polyamines. Neomycin selectively stabilizes the triplex (T·A·T and mixed base) without any effect on the DNA duplex. The selectivity of neomycin likely originates from its potential and shape complementarity to the triplex Watson–Hoogsteen groove, making it the first molecule that selectively recognizes a triplex groove over a duplex groove. The groove recognition of aminoglycosides is not limited to DNA triplexes, but also extends to RNA and hybrid triple helical structures. Intercalator–neomycin conjugates are shown to simultaneously probe the base stacking and groove surface in the DNA triplex. Calorimetric and spectrosocopic studies allow the quantification of the effect of surface area of the intercalating moiety on binding to the triplex. These studies outline a novel approach to the recognition of DNA triplexes that incorporates the use of non-competing binding sites. These principles of dual recognition should be applicable to the design of ligands that can bind any given nucleic acid target with nanomolar affinities and with high selectivity. PMID:21073199

Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis

DOE PAGES

Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco; ...

2015-12-24

Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsinmore » kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Lastly, protein dynamics in free recoverin limits the overall rate of binding.« less

Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis

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

Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco

Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsinmore » kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Lastly, protein dynamics in free recoverin limits the overall rate of binding.« less

Shape recognition of microbial cells by colloidal cell imprints

NASA Astrophysics Data System (ADS)

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

2013-08-01

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

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

PubMed

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

Self-recognition, color signals, and cycles of greenbeard mutualism and altruism

PubMed Central

Sinervo, Barry; Chaine, Alexis; Clobert, Jean; Calsbeek, Ryan; Hazard, Lisa; Lancaster, Lesley; McAdam, Andrew G.; Alonzo, Suzanne; Corrigan, Gwynne; Hochberg, Michael E.

2006-01-01

Altruism presents a challenge to evolutionary theory because selection should favor selfish over caring strategies. Greenbeard altruism resolves this paradox by allowing cooperators to identify individuals carrying similar alleles producing a form of genic selection. In side-blotched lizards, genetically similar but unrelated blue male morphs settle on adjacent territories and cooperate. Here we show that payoffs of cooperation depend on asymmetric costs of orange neighbors. One blue male experiences low fitness and buffers his unrelated partner from aggressive orange males despite the potential benefits of defection. We show that recognition behavior is highly heritable in nature, and we map genetic factors underlying color and self-recognition behavior of genetic similarity in both sexes. Recognition and cooperation arise from genome-wide factors based on our mapping study of the location of genes responsible for self-recognition behavior, recognition of blue color, and the color locus. Our results provide an example of greenbeard interactions in a vertebrate that are typified by cycles of greenbeard mutualism interspersed with phases of transient true altruism. Such cycles provide a mechanism encouraging the origin and stability of true altruism. PMID:16651531

The salen based chemosensors for highly selective recognition of Zn2+ ion.

PubMed

Zhu, Wenkai; Du, LongChao; Li, Wensheng; Zuo, Jinyan; Shan, Jingrui

2018-06-03

Two novel salen based chemosensors have been successfully synthesized. UV-vis absorption, fluorescence emission spectroscopy and cyclic voltammetry (CV) were exploited to investigate their recognition toward various metal ions, including Na + , K + , Mg 2+ , Al 3+ , Zn 2+ , Ag + , Pb 2+ , Co 2+ , Li + , Ba 2+ , Ca 2+ , Cd 2+ , La 3+ , Cu 2+ and Mn 2+ ions. The results indicated that the sensor L1 and L2 exhibited highly selective and sensitive recognition for Zn 2+ ions. The binding stoichiometry ratio of L1-Zn 2+ /L2-Zn 2+ were recognized as 4:1 by the method of Job's plot. Meanwhile, this investigation is confirmed by 1 H NMR. These results indicated that L1 and L2 can be applied as chemosensor for the detection of Zn 2+ ion. Copyright © 2018 Elsevier B.V. All rights reserved.

Developments in Molecular Recognition and Sensing at Interfaces

PubMed Central

Ariga, Katsuhiko; Hill, Jonathan P.; Endo, Hiroshi

2007-01-01

In biological systems, molecular recognition events occur mostly within interfacial environments such as at membrane surfaces, enzyme reaction sites, or at the interior of the DNA double helix. Investigation of molecular recognition at model interfaces provides great insights into biological phenomena. Molecular recognition at interfaces not only has relevance to biological systems but is also important for modern applications such as high sensitivity sensors. Selective binding of guest molecules in solution to host molecules located at solid surfaces is crucial for electronic or photonic detection of analyte substances. In response to these demands, molecular recognition at interfaces has been investigated extensively during the past two decades using Langmuir monolayers, self-assembled monolayers, and lipid assemblies as recognition media. In this review, advances of molecular recognition at interfaces are briefly summarized.

Intrahippocampal injection of Cortistatin-14 impairs recognition memory consolidation in mice through activation of sst2, ghrelin and GABAA/B receptors.

PubMed

Jiang, Jinhong; Peng, Yali; He, Zhen; Wei, Lijuan; Jin, Weidong; Wang, Xiaoli; Chang, Min

2017-07-01

Cortistatin-14 (CST-14), a neuropeptide related to somatostatin, is primarily localized within the cortex and hippocampus. In the hippocampus, CST-14 inhibits CA1 neuronal pyramidal cell firing and co-exists with GABA. However, its role in cognitive is still not clarified. The first aim of our study was to elucidate the role of CST-14 signaling in consolidation and reconsolidation of recognition memory in mice, using novel object recognition task. The results showed that central CST-14 induced in impairment of long-term and short-term recognition memory, indicating memory consolidation impairment effect. Similarly, we found that CST-14 did not impaired long-term and short-term reconsolidation recognition memory. To further investigate the underlying mechanisms of CST-14 in memory process, we used cyclosomatostatin (c-SOM, a selective sst 1-5 receptor antagonist), cyanamid154806 (a selective sst 2 receptor antagonist), ODN-8 (a high affinity and selectivity compound for sst 3 receptor), [d-Lys 3 ]GHRP-6 (a selective ghrelin receptor antagonist), picrotoxin (PTX, a GABA A receptor antagonist), and sacolfen (a GABA B receptor antagonist) to research its effects in recognition. Our results firstly indicated that the memory-impairing effects of CST-14 were significantly reversed by c-SOM, cyanamid154806, [d-Lys 3 ]GHRP-6, PTX and sacolfen, but not ODN-8, suggesting that the blockage of recognition memory consolidation induced by CST-14 involves sst 2 , ghrelin and GABA system. The present study provides a potential strategy to regulate memory processes, providing new evidence that reconsolidation is not a simple reiteration of consolidation. Copyright © 2017 Elsevier B.V. All rights reserved.

The Association of Aging and Aerobic Fitness With Memory

PubMed Central

Bullock, Alexis M.; Mizzi, Allison L.; Kovacevic, Ana; Heisz, Jennifer J.

2018-01-01

The present study examined the differential effects of aging and fitness on memory. Ninety-five young adults (YA) and 81 older adults (OA) performed the Mnemonic Similarity Task (MST) to assess high-interference memory and general recognition memory. Age-related differences in high-interference memory were observed across the lifespan, with performance progressively worsening from young to old. In contrast, age-related differences in general recognition memory were not observed until after 60 years of age. Furthermore, OA with higher aerobic fitness had better high-interference memory, suggesting that exercise may be an important lifestyle factor influencing this aspect of memory. Overall, these findings suggest different trajectories of decline for high-interference and general recognition memory, with a selective role for physical activity in promoting high-interference memory. PMID:29593524

Recognition of oxytocin by capillary electrochromatography with monolithic tetrapeptide-imprinted polymer used as the stationary phase.

PubMed

Zheng, Chao; Liu, Zhaosheng; Gao, Ruyu; Zhang, Lihua; Zhang, Yukui

2007-07-01

Using YPLG (Tyr-Pro-Leu-Gly), a tetrapeptide, as the template, an imprinted monolithic column was prepared and applied to the selective recognition of oxytocin based on the epitope approach and capillary electrochromatography (CEC). By optimizing the polymerization solution in terms of functional monomer, cross-linking reagent, porogen, and imprinted template via CEC evaluations of synthesized columns, an imprinted monolith with good recognition capacity (the imprinting factors for YPLG and oxytocin were 4.499 and 4.013, respectively) and high column efficiency (theoretical plates for YPLG and oxytocin were 22,995 plates/m and 16,952 plates/m, respectively) was achieved. In addition, the effects of various experimental parameters on the recognition of oxytocin, including the organic modifier content, the buffer concentration, and the pH value, were studied systematically. Furthermore, a mixture of oxytocin and other proteins was analyzed using this monolithic CEC column, and oxytocin was eluted much more slowly than other large biomolecules, which demonstrated the high selective recognition ability of such an imprinted monolith for oxytocin with PLG (Pro-Leu-Gly) as the epitope. Figure Separation of a mixture of oxytocin, BSA, bovine hemoglobin, ovalbumin, and lysozyme on the open column, the blank monolithic column, and the monolithic YPLG-imprinted column.

Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

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

Wang Xiaojia; Mao Qirong; Zhan Yongzhao

There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions.more » The experiments show that this method can improve the recognition rate and the time of feature extraction.« less

Fluoride-driven 'turn on' ESPT in the binding with a novel benzimidazole-based sensor.

PubMed

Liu, Kai; Zhao, Xiaojun; Liu, Qingxiang; Huo, Jianzhong; Zhu, Bolin; Diao, Shihua

2015-01-01

A novel fluorescence sensor (BIP) bearing NH and OH subunits displayed a highly selective and sensitive recognition property for fluoride over other anions. Fluoride-driven ESPT, poorly used in anion recognition and sensing, was suggested to be responsible for the fluorescence enhancement with a blue shift of 35 nm in the emission spectrum.

Generation of Dynamic Combinatorial Libraries Using Hydrazone‐Functionalized Surface Mimetics

PubMed Central

Hewitt, Sarah H.

2018-01-01

Dynamic combinatorial chemistry (DCC) represents an approach, whereby traditional supramolecular scaffolds used for protein surface recognition might be exploited to achieve selective high affinity target recognition. Synthesis, in situ screening and amplification under selection pressure allows the generation of ligands, which bear different moieties capable of making multivalent non‐covalent interactions with target proteins. Generic tetracarboxyphenyl porphyrin scaffolds bearing four hydrazide moieties have been used to form dynamic combinatorial libraries (DCLs) using aniline‐catalyzed reversible hydrazone exchange reactions, in 10 % DMSO, 5 mm NH4OAc, at pH 6.75. High resolution mass spectrometry (HRMS) was used to monitor library composition and establish conditions under which equilibria were established.

Dual recognition unit strategy improves the specificity of the adenosine triphosphate (ATP) aptamer biosensor for cerebral ATP assay.

PubMed

Yu, Ping; He, Xiulan; Zhang, Li; Mao, Lanqun

2015-01-20

Adenosine triphosphate (ATP) aptamer has been widely used as a recognition unit for biosensor development; however, its relatively poor specificity toward ATP against adenosine-5'-diphosphate (ADP) and adenosine-5'-monophosphate (AMP) essentially limits the application of the biosensors in real systems, especially in the complex cerebral system. In this study, for the first time, we demonstrate a dual recognition unit strategy (DRUS) to construct a highly selective and sensitive ATP biosensor by combining the recognition ability of aptamer toward A nucleobase and of polyimidazolium toward phosphate. The biosensors are constructed by first confining the polyimidazolium onto a gold surface by surface-initiated atom transfer radical polymerization (SI-ATRP), and then the aptamer onto electrode surface by electrostatic self-assembly to form dual-recognition-unit-functionalized electrodes. The constructed biosensor based on DRUS not only shows an ultrahigh sensitivity toward ATP with a detection limit down to the subattomole level but also an ultrahigh selectivity toward ATP without interference from ADP and AMP. The constructed biosensor is used for selective and sensitive sensing of the extracellular ATP in the cerebral system by combining in vivo microdialysis and can be used as a promising neurotechnology to probing cerebral ATP concentration.

Comparison of emotion recognition from facial expression and music.

PubMed

Gaspar, Tina; Labor, Marina; Jurić, Iva; Dumancić, Dijana; Ilakovac, Vesna; Heffer, Marija

2011-01-01

The recognition of basic emotions in everyday communication involves interpretation of different visual and auditory clues. The ability to recognize emotions is not clearly determined as their presentation is usually very short (micro expressions), whereas the recognition itself does not have to be a conscious process. We assumed that the recognition from facial expressions is selected over the recognition of emotions communicated through music. In order to compare the success rate in recognizing emotions presented as facial expressions or in classical music works we conducted a survey which included 90 elementary school and 87 high school students from Osijek (Croatia). The participants had to match 8 photographs of different emotions expressed on the face and 8 pieces of classical music works with 8 offered emotions. The recognition of emotions expressed through classical music pieces was significantly less successful than the recognition of emotional facial expressions. The high school students were significantly better at recognizing facial emotions than the elementary school students, whereas girls were better than boys. The success rate in recognizing emotions from music pieces was associated with higher grades in mathematics. Basic emotions are far better recognized if presented on human faces than in music, possibly because the understanding of facial emotions is one of the oldest communication skills in human society. Female advantage in emotion recognition was selected due to the necessity of their communication with the newborns during early development. The proficiency in recognizing emotional content of music and mathematical skills probably share some general cognitive skills like attention, memory and motivation. Music pieces were differently processed in brain than facial expressions and consequently, probably differently evaluated as relevant emotional clues.

A malonitrile-functionalized metal-organic framework for hydrogen sulfide detection and selective amino acid molecular recognition

NASA Astrophysics Data System (ADS)

Li, Haiwei; Feng, Xiao; Guo, Yuexin; Chen, Didi; Li, Rui; Ren, Xiaoqian; Jiang, Xin; Dong, Yuping; Wang, Bo

2014-03-01

A novel porous polymeric fluorescence probe, MN-ZIF-90, has been designed and synthesized for quantitative hydrogen sulfide (H2S) fluorescent detection and highly selective amino acid recognition. This distinct crystalline structure, derived from rational design and malonitrile functionalization, can trigger significant enhancement of its fluorescent intensity when exposed to H2S or cysteine molecules. Indeed this new metal-organic framework (MOF) structure shows high selectivity of biothiols over other amino acids and exhibits favorable stability. Moreover, in vitro viability assays on HeLa cells show low cytotoxicity of MN-ZIF-90 and its imaging contrast efficiency is further demonstrated by fluorescence microscopy studies. This facile yet powerful strategy also offers great potential of using open-framework materials (i.e. MOFs) as the novel platform for sensing and other biological applications.

Preparation and recognition performance of creatinine-imprinted material prepared with novel surface-imprinting technique.

PubMed

Gao, Baojiao; Li, Yanbin; Zhang, Zhenguo

2010-08-01

By adopting the novel surface molecular imprinting technique put forward by us not long ago, a creatinine molecule-imprinted material with high performance was prepared. The functional macromolecule polymethacrylic acid (PMAA) was first grafted on the surfaces of micron-sized silica gel particles in the manner of "grafting from" using 3-methacryloxypropyltrimethoxysilane (MPS) as intermedia, resulting in the grafted particles PMAA/SiO(2). Subsequently, the molecular imprinting was carried out towards the grafted macromolecule PMAA using creatinine as template and with ethylene glycol diglycidyl ether (EGGE) as crosslinker by right of the intermolecular hydrogen bonding and electrostatic interaction between the grafted PMAA and creatinine molecules. Finally, the creatinine-imprinted material MIP-PMAA/SiO(2) was obtained. The binding character of MIP-PMAA/SiO(2) for creatinine was investigated in depth with both batch and column methods and using N-hydroxysuccinimide and creatine as two contrast substances, whose chemical structures are similar to creatinine to a certain degree. The experimental results show that the surface-imprinted material MIP-PMAA/SiO(2) has excellent binding affinity and high recognition selectivity for creatinine. Before imprinting, PMAA/SiO(2) particles nearly has not recognition selectivity for creatinine, and the selectivity coefficients of PMAA/SiO(2) for creatinine relative to N-hydroxysuccinimide and creatine are only 1.23 and 1.30, respectively. However, after imprinting, the selectivity coefficients of MIP-PMAA/SiO(2) for creatinine in respect to N-hydroxysuccinimide and creatine are remarkably enhanced to 11.64 and 12.87, respectively, displaying the excellent recognition selectivity and binding affinity towards creatinine molecules. Copyright 2010 Elsevier B.V. All rights reserved.

Informative Feature Selection for Object Recognition via Sparse PCA

DTIC Science & Technology

2011-04-07

constraint on images collected from low-power camera net- works instead of high-end photography is that establishing wide-baseline feature correspondence of...variable selection tool for selecting informative features in the object images captured from low-resolution cam- era sensor networks. Firstly, we...More examples can be found in Figure 4 later. 3. Identifying Informative Features Classical PCA is a well established tool for the analysis of high

Definition of a high-affinity Gag recognition structure mediating packaging of a retroviral RNA genome

PubMed Central

Gherghe, Cristina; Lombo, Tania; Leonard, Christopher W.; Datta, Siddhartha A. K.; Bess, Julian W.; Gorelick, Robert J.; Rein, Alan; Weeks, Kevin M.

2010-01-01

All retroviral genomic RNAs contain a cis-acting packaging signal by which dimeric genomes are selectively packaged into nascent virions. However, it is not understood how Gag (the viral structural protein) interacts with these signals to package the genome with high selectivity. We probed the structure of murine leukemia virus RNA inside virus particles using SHAPE, a high-throughput RNA structure analysis technology. These experiments showed that NC (the nucleic acid binding domain derived from Gag) binds within the virus to the sequence UCUG-UR-UCUG. Recombinant Gag and NC proteins bound to this same RNA sequence in dimeric RNA in vitro; in all cases, interactions were strongest with the first U and final G in each UCUG element. The RNA structural context is critical: High-affinity binding requires base-paired regions flanking this motif, and two UCUG-UR-UCUG motifs are specifically exposed in the viral RNA dimer. Mutating the guanosine residues in these two motifs—only four nucleotides per genomic RNA—reduced packaging 100-fold, comparable to the level of nonspecific packaging. These results thus explain the selective packaging of dimeric RNA. This paradigm has implications for RNA recognition in general, illustrating how local context and RNA structure can create information-rich recognition signals from simple single-stranded sequence elements in large RNAs. PMID:20974908

Adolescents' ability to read different emotional faces relates to their history of maltreatment and type of psychopathology.

PubMed

Leist, Tatyana; Dadds, Mark R

2009-04-01

Emotional processing styles appear to characterize various forms of psychopathology and environmental adversity in children. For example, autistic, anxious, high- and low-emotion conduct problem children, and children who have been maltreated, all appear to show specific deficits and strengths in recognizing the facial expressions of emotions. Until now, the relationships between emotion recognition, antisocial behaviour, emotional problems, callous-unemotional (CU) traits and early maltreatment have never been assessed simultaneously in one study, and the specific associations of emotion recognition to maltreatment and child characteristics are therefore unknown. We examined facial-emotion processing in a sample of 23 adolescents selected for high-risk status on the variables of interest. As expected, maltreatment and child characteristics showed unique associations. CU traits were uniquely related to impairments in fear recognition. Antisocial behaviour was uniquely associated with better fear recognition, but impaired anger recognition. Emotional problems were associated with better recognition of anger and sadness, but lower recognition of neutral faces. Maltreatment was predictive of superior recognition of fear and sadness. The findings are considered in terms of social information-processing theories of psychopathology. Implications for clinical interventions are discussed.

Monopolar Detection Thresholds Predict Spatial Selectivity of Neural Excitation in Cochlear Implants: Implications for Speech Recognition

PubMed Central

2016-01-01

The objectives of the study were to (1) investigate the potential of using monopolar psychophysical detection thresholds for estimating spatial selectivity of neural excitation with cochlear implants and to (2) examine the effect of site removal on speech recognition based on the threshold measure. Detection thresholds were measured in Cochlear Nucleus® device users using monopolar stimulation for pulse trains that were of (a) low rate and long duration, (b) high rate and short duration, and (c) high rate and long duration. Spatial selectivity of neural excitation was estimated by a forward-masking paradigm, where the probe threshold elevation in the presence of a forward masker was measured as a function of masker-probe separation. The strength of the correlation between the monopolar thresholds and the slopes of the masking patterns systematically reduced as neural response of the threshold stimulus involved interpulse interactions (refractoriness and sub-threshold adaptation), and spike-rate adaptation. Detection threshold for the low-rate stimulus most strongly correlated with the spread of forward masking patterns and the correlation reduced for long and high rate pulse trains. The low-rate thresholds were then measured for all electrodes across the array for each subject. Subsequently, speech recognition was tested with experimental maps that deactivated five stimulation sites with the highest thresholds and five randomly chosen ones. Performance with deactivating the high-threshold sites was better than performance with the subjects’ clinical map used every day with all electrodes active, in both quiet and background noise. Performance with random deactivation was on average poorer than that with the clinical map but the difference was not significant. These results suggested that the monopolar low-rate thresholds are related to the spatial neural excitation patterns in cochlear implant users and can be used to select sites for more optimal speech recognition performance. PMID:27798658

Entity recognition in the biomedical domain using a hybrid approach.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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-definition video exploitation.

Molecular imprinting at walls of silica nanotubes for TNT recognition.

PubMed

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.

Free recall test experience potentiates strategy-driven effects of value on memory.

PubMed

Cohen, Michael S; Rissman, Jesse; Hovhannisyan, Mariam; Castel, Alan D; Knowlton, Barbara J

2017-10-01

People tend to show better memory for information that is deemed valuable or important. By one mechanism, individuals selectively engage deeper, semantic encoding strategies for high value items (Cohen, Rissman, Suthana, Castel, & Knowlton, 2014). By another mechanism, information paired with value or reward is automatically strengthened in memory via dopaminergic projections from midbrain to hippocampus (Shohamy & Adcock, 2010). We hypothesized that the latter mechanism would primarily enhance recollection-based memory, while the former mechanism would strengthen both recollection and familiarity. We also hypothesized that providing interspersed tests during study is a key to encouraging selective engagement of strategies. To test these hypotheses, we presented participants with sets of words, and each word was associated with a high or low point value. In some experiments, free recall tests were given after each list. In all experiments, a recognition test was administered 5 minutes after the final word list. Process dissociation was accomplished via remember/know judgments at recognition, a recall test probing both item memory and memory for a contextual detail (word plurality), and a task dissociation combining a recognition test for plurality (intended to probe recollection) with a speeded item recognition test (to probe familiarity). When recall tests were administered after study lists, high value strengthened both recollection and familiarity. When memory was not tested after each study list, but rather only at the end, value increased recollection but not familiarity. These dual process dissociations suggest that interspersed recall tests guide learners' use of metacognitive control to selectively apply effective encoding strategies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Counter-propagation network with variable degree variable step size LMS for single switch typing recognition.

PubMed

Yang, Cheng-Huei; Luo, Ching-Hsing; Yang, Cheng-Hong; Chuang, Li-Yeh

2004-01-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, including mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for disabled persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. This restriction is a major hindrance. Therefore, a switch adaptive automatic recognition method with a high recognition rate is needed. The proposed system combines counter-propagation networks with a variable degree variable step size LMS algorithm. It is divided into five stages: space recognition, tone recognition, learning process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods in the literature.

Recollection and familiarity in amnesic mild cognitive impairment.

PubMed

Serra, Laura; Bozzali, Marco; Cercignani, Mara; Perri, Roberta; Fadda, Lucia; Caltagirone, Carlo; Carlesimo, Giovanni A

2010-05-01

To investigate whether, in patients with amnesic mild cognitive impairment (a-MCI), recognition deficits are mainly due to a selective impairment of recollection rather than familiarity. Nineteen patients with a-MCI and 23 sex-, age-, and education-matched healthy controls underwent two experimental investigations, using the Process Dissociation Procedure (PDP) and the Remember/Know (R/K) procedure, to assess the differential contribution of recollection and familiarity to their recognition performance. Both experimental procedures revealed a selective preservation of familiarity in a-MCI patients. Moreover, the R/K procedure showed a statistically significant impairment of recollection in a-MCI patients for words that were either read or anagrammed during the study phase. A-MCI is known to be commonly associated with a high risk of conversion to Alzheimer's disease (AD). Several previous studies have demonstrated a characteristic impairment of episodic memory in a-MCI, with an early dysfunction of recognition. Our findings are consistent with the knowledge of neurodegeneration occurring in AD, which is characterized, at the earliest disease stages, by a selective involvement of the entorhinal cortex. Moreover, the current study supports the dual process model of recognition, which hypothesizes recollection and familiarity to be independent processes associated with distinct anatomical substrates.

Autonomous learning in gesture recognition by using lobe component analysis

NASA Astrophysics Data System (ADS)

Lu, Jian; Weng, Juyang

2007-02-01

Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.

A virus resonance light scattering sensor based on mussel-inspired molecularly imprinted polymers for high sensitive and high selective detection of Hepatitis A Virus.

PubMed

Yang, Bin; Gong, Hang; Chen, Chunyan; Chen, Xiaoming; Cai, Changqun

2017-01-15

We described a novel resonance light scattering (RLS) sensor for the specific recognition of trace quantities of Hepatitis A Virus (HAV); the sensor was based on a mussel-inspired hepatitis molecularly imprinted polymer. As a recognition element, polydopamine (PDA)-coated totivirus-imprinted polymer was introduced on the surface of SiO 2 nanoparticles (virus-imprinted SiO 2 @PDA NPs) using an efficient one-step synthesis method. The target virus was selectively captured by the imprinted polymer films, thereby increasing the RLS intensity. A simple fluorescence spectrophotometer was employed to measure the changes in the intensity. The enhanced RLS intensity (∆I RLS ) was proportional to the concentration of HAV in the range of 0.04-6.0nmol∙L -1 , with a low limit of detection of 8.6pmol∙L -1 . The selectivity study confirmed that the resultant HAV-imprinted SiO 2 @PDA NPs possessed high selectivity for HAV. The sensor was successfully applied for the direct detection of additional HAV from a 20,000-fold dilution of human serum. The proposed strategy is simple, eco-friendly, highly selective, and sensitive. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative expression and immunogenicity of MAGE-3 and -6 in upper aerodigestive tract cancer.

PubMed

Filho, Pedro A Andrade; López-Albaitero, Andrés; Xi, Liqiang; Gooding, William; Godfrey, Tony; Ferris, Robert L

2009-10-15

The MAGE antigens are frequently expressed cancer vaccine targets. However, quantitative analysis of MAGE expression in upper aerodigestive tract (UADT) tumor cells and its association with T-cell recognition has not been performed, hindering the selection of appropriate candidates for MAGE-specific immunotherapy. Using quantitative RT-PCR (QRT-PCR), we evaluated the expression of MAGE-3/6 in 65 UADT cancers, 48 normal samples from tumor matched sites and 7 HLA-A*0201+ squamous cell carcinoma of the head and neck (SCCHN) cell lines. Expression results were confirmed using Western blot. HLA-A*0201:MAGE-3- (271-279) specific cytotoxic T lymphocytes (MAGE-CTL) from SCCHN patients and healthy donors showed that MAGE-3/6 expression was highly associated with CTL recognition in vitro. On the basis of the MAGE-3/6 expression, we could identify 31 (47%) of the 65 UADT tumors, which appeared to express MAGE-3/6 at levels that correlated with efficient CTL recognition. To confirm that the level of MAGE-3 expression was responsible for CTL recognition, 2 MAGE-3/6 mRNA(high) SCCHN cell lines, PCI-13 and PCI-30, were subjected to MAGE-3/6-specific knockdown. RNAi-transfected cells showed that MAGE expression and MAGE-CTL recognition were significantly reduced. Furthermore, treatment of cells expressing low MAGE-3/6 mRNA with a demethylating agent, 5-aza-2'-deoxycytidine (DAC), increased the expression of MAGE-3/6 and CTL recognition. Thus, using QRT-PCR UADT cancers frequently express MAGE-3/6 at levels sufficient for CTL recognition, supporting the use of a QRT-PCR-based assay for the selection of candidates likely to respond to MAGE-3/6 immunotherapy. Demethylating agents could increase the number of patients amenable for targeting epigenetically modified tumor antigens in vaccine trials.

A Joint Gaussian Process Model for Active Visual Recognition with Expertise Estimation in Crowdsourcing

PubMed Central

Long, Chengjiang; Hua, Gang; Kapoor, Ashish

2015-01-01

We present a noise resilient probabilistic model for active learning of a Gaussian process classifier from crowds, i.e., a set of noisy labelers. It explicitly models both the overall label noise and the expertise level of each individual labeler with two levels of flip models. Expectation propagation is adopted for efficient approximate Bayesian inference of our probabilistic model for classification, based on which, a generalized EM algorithm is derived to estimate both the global label noise and the expertise of each individual labeler. The probabilistic nature of our model immediately allows the adoption of the prediction entropy for active selection of data samples to be labeled, and active selection of high quality labelers based on their estimated expertise to label the data. We apply the proposed model for four visual recognition tasks, i.e., object category recognition, multi-modal activity recognition, gender recognition, and fine-grained classification, on four datasets with real crowd-sourced labels from the Amazon Mechanical Turk. The experiments clearly demonstrate the efficacy of the proposed model. In addition, we extend the proposed model with the Predictive Active Set Selection Method to speed up the active learning system, whose efficacy is verified by conducting experiments on the first three datasets. The results show our extended model can not only preserve a higher accuracy, but also achieve a higher efficiency. PMID:26924892

Corona Phase Molecular Recognition (CoPhMoRe) to Enable New Nanosensor Interfaces

NASA Astrophysics Data System (ADS)

Strano, Michael

2015-03-01

Our lab at MIT has been interested in how the 1D and 2D electronic structures of carbon nanotubes and graphene respectively can be utilized to advance new concepts in molecular detection. We introduce CoPhMoRe or corona phase molecular recognition as a method of discovering synthetic antibodies, or nanotube-templated recognition sites from a heteropolymer library. We show that certain synthetic heteropolymers, once constrained onto a single-walled carbon nanotube by chemical adsorption, also form a new corona phase that exhibits highly selective recognition for specific molecules. To prove the generality of this phenomenon, we report three examples of heteropolymers-nanotube recognition complexes for riboflavin, L-thyroxine and estradiol. The platform opens new opportunities to create synthetic recognition sites for molecular detection. We have also extended this molecular recognition technique to neurotransmitters, producing the first fluorescent sensor for dopamine. Another area of advancement in biosensor development is the use of near infrared fluorescent carbon nanotube sensors for in-vivo detection. Here, we show that PEG-ligated d(AAAT)7 DNA wrapped SWNT are selective for nitric oxide, a vasodilator of blood vessels, and can be tail vein injected into mice and localized within the viable mouse liver. We use an SJL mouse model to study liver inflammation in vivo using the spatially and spectrally resolved nIR signature of the localized SWNT sensors.

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

PubMed

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.

Natural scene logo recognition by joint boosting feature selection in salient regions

NASA Astrophysics Data System (ADS)

Fan, Wei; Sun, Jun; Naoi, Satoshi; Minagawa, Akihiro; Hotta, Yoshinobu

2011-01-01

Logos are considered valuable intellectual properties and a key component of the goodwill of a business. In this paper, we propose a natural scene logo recognition method which is segmentation-free and capable of processing images extremely rapidly and achieving high recognition rates. The classifiers for each logo are trained jointly, rather than independently. In this way, common features can be shared across multiple classes for better generalization. To deal with large range of aspect ratio of different logos, a set of salient regions of interest (ROI) are extracted to describe each class. We ensure the selected ROIs to be both individually informative and two-by-two weakly dependant by a Class Conditional Entropy Maximization criteria. Experimental results on a large logo database demonstrate the effectiveness and efficiency of our proposed method.

Verbal Serial List Learning in Mild Cognitive Impairment: A Profile Analysis of Interference, Forgetting, and Errors

PubMed Central

Libon, David J.; Bondi, Mark W.; Price, Catherine C.; Lamar, Melissa; Eppig, Joel; Wambach, Denene M.; Nieves, Christine; Delano-Wood, Lisa; Giovannetti, Tania; Lippa, Carol; Kabasakalian, Anahid; Cosentino, Stephanie; Swenson, Rod; Penney, Dana L.

2012-01-01

Using cluster analysis Libon et al. (2010) found three verbal serial list-learning profiles involving delay memory test performance in patients with mild cognitive impairment (MCI). Amnesic MCI (aMCI) patients presented with low scores on delay free recall and recognition tests; mixed MCI (mxMCI) patients scored higher on recognition compared to delay free recall tests; and dysexecutive MCI (dMCI) patients generated relatively intact scores on both delay test conditions. The aim of the current research was to further characterize memory impairment in MCI by examining forgetting/savings, interference from a competing word list, intrusion errors/perseverations, intrusion word frequency, and recognition foils in these three statistically determined MCI groups compared to normal control (NC) participants. The aMCI patients exhibited little savings, generated more highly prototypic intrusion errors, and displayed indiscriminate responding to delayed recognition foils. The mxMCI patients exhibited higher saving scores, fewer and less prototypic intrusion errors, and selectively endorsed recognition foils from the interference list. dMCI patients also selectively endorsed recognition foils from the interference list but performed similarly compared to NC participants. These data suggest the existence of distinct memory impairments in MCI and caution against the routine use of a single memory test score to operationally define MCI. PMID:21880171

Speech emotion recognition methods: A literature review

NASA Astrophysics Data System (ADS)

Basharirad, Babak; Moradhaseli, Mohammadreza

2017-10-01

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

Electrochromic Molecular Imprinting Sensor for Visual and Smartphone-Based Detections.

PubMed

Capoferri, Denise; Álvarez-Diduk, Ruslan; Del Carlo, Michele; Compagnone, Dario; Merkoçi, Arben

2018-05-01

Electrochromic effect and molecularly imprinted technology have been used to develop a sensitive and selective electrochromic sensor. The polymeric matrices obtained using the imprinting technology are robust molecular recognition elements and have the potential to mimic natural recognition entities with very high selectivity. The electrochromic behavior of iridium oxide nanoparticles (IrOx NPs) as physicochemical transducer together with a molecularly imprinted polymer (MIP) as recognition layer resulted in a fast and efficient translation of the detection event. The sensor was fabricated using screen-printing technology with indium tin oxide as a transparent working electrode; IrOx NPs where electrodeposited onto the electrode followed by thermal polymerization of polypyrrole in the presence of the analyte (chlorpyrifos). Two different approaches were used to detect and quantify the pesticide: direct visual detection and smartphone imaging. Application of different oxidation potentials for 10 s resulted in color changes directly related to the concentration of the analyte. For smartphone imaging, at fixed potential, the concentration of the analyte was dependent on the color intensity of the electrode. The electrochromic sensor detects a highly toxic compound (chlorpyrifos) with a 100 fM and 1 mM dynamic range. So far, to the best of our knowledge, this is the first work where an electrochromic MIP sensor uses the electrochromic properties of IrOx to detect a certain analyte with high selectivity and sensitivity.

Fluorescent sensor systems based on nanostructured polymeric membranes for selective recognition of Aflatoxin B1.

PubMed

Sergeyeva, Tetyana; Yarynka, Daria; Piletska, Elena; Lynnik, Rostyslav; Zaporozhets, Olga; Brovko, Oleksandr; Piletsky, Sergey; El'skaya, Anna

2017-12-01

Nanostructured polymeric membranes for selective recognition of aflatoxin B1 were synthesized in situ and used as highly sensitive recognition elements in the developed fluorescent sensor. Artificial binding sites capable of selective recognition of aflatoxin B1 were formed in the structure of the polymeric membranes using the method of molecular imprinting. A composition of molecularly imprinted polymer (MIP) membranes was optimized using the method of computational modeling. The MIP membranes were synthesized using the non-toxic close structural analogue of aflatoxin B1, ethyl-2-oxocyclopentanecarboxylate as a dummy template. The MIP membranes with the optimized composition demonstrated extremely high selectivity towards aflatoxin B1 (AFB1). Negligible binding of close structural analogues of AFB1 - aflatoxins B2 (AFB2), aflatoxin G2 (AFG2), and ochratoxin A (OTA) was demonstrated. Binding of AFB1 by the MIP membranes was investigated as a function of both type and concentration of the functional monomer in the initial monomer composition used for the membranes' synthesis, as well as sample composition. The conditions of the solid-phase extraction of the mycotoxin using the MIP membrane as a stationary phase (pH, ionic strength, buffer concentration, volume of the solution, ratio between water and organic solvent, filtration rate) were optimized. The fluorescent sensor system based on the optimized MIP membranes provided a possibility of AFB1 detection within the range 14-500ngmL -1 demonstrating detection limit (3Ϭ) of 14ngmL -1 . The developed technique was successfully applied for the analysis of model solutions and waste waters from bread-making plants. Copyright © 2017 Elsevier B.V. All rights reserved.

Emotion recognition in fathers and mothers at high-risk for child physical abuse.

PubMed

Asla, Nagore; de Paúl, Joaquín; Pérez-Albéniz, Alicia

2011-09-01

The present study was designed to determine whether parents at high risk for physical child abuse, in comparison with parents at low risk, show deficits in emotion recognition, as well as to examine the moderator effect of gender and stress on the relationship between risk for physical child abuse and emotion recognition. Based on their scores on the Abuse Scale of the CAP Inventory (Milner, 1986), 64 parents at high risk (24 fathers and 40 mothers) and 80 parents at low risk (40 fathers and 40 mothers) for physical child abuse were selected. The Subtle Expression Training Tool/Micro Expression Training Tool (Ekman, 2004a, 2004b) and the Diagnostic Analysis of Nonverbal Accuracy II (Nowicki & Carton, 1993) were used to assess emotion recognition. As expected, parents at high risk, in contrast to parents at low risk, showed deficits in emotion recognition. However, differences between high- and low-risk participants were observed only for fathers, but not for mothers. Whereas fathers at high risk for physical child abuse made more errors than mothers at high risk, no differences between mothers at low risk and fathers at low risk were found. No interaction between stress, gender, and risk status was observed for errors in emotion recognition. The present findings, if confirmed with physical abusers, could be helpful to further our understanding of deficits in processing information of physically abusive parents and to develop treatment strategies specifically focused on emotion recognition. Moreover, if gender differences can be confirmed, the findings could be helpful to develop specific treatment programs for abusive fathers. Copyright © 2011 Elsevier Ltd. All rights reserved.

Fingerprint recognition system by use of graph matching

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2016-12-15

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

Obligatory and facultative brain regions for voice-identity recognition

PubMed Central

Roswandowitz, Claudia; Kappes, Claudia; Obrig, Hellmuth; von Kriegstein, Katharina

2018-01-01

Abstract Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal lobe is only a facultative component of voice-identity recognition in situations where additional face-identity processing is required. PMID:29228111

Obligatory and facultative brain regions for voice-identity recognition.

PubMed

Roswandowitz, Claudia; Kappes, Claudia; Obrig, Hellmuth; von Kriegstein, Katharina

2018-01-01

Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal lobe is only a facultative component of voice-identity recognition in situations where additional face-identity processing is required. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

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

PubMed

Mujahid, Adnan; Mustafa, Ghulam; Dickert, Franz L

2018-06-01

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.

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

PubMed Central

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease. PMID:27977767

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

PubMed

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease.

Multispectral iris recognition based on group selection and game theory

NASA Astrophysics Data System (ADS)

Ahmad, Foysal; Roy, Kaushik

2017-05-01

A commercially available iris recognition system uses only a narrow band of the near infrared spectrum (700-900 nm) while iris images captured in the wide range of 405 nm to 1550 nm offer potential benefits to enhance recognition performance of an iris biometric system. The novelty of this research is that a group selection algorithm based on coalition game theory is explored to select the best patch subsets. In this algorithm, patches are divided into several groups based on their maximum contribution in different groups. Shapley values are used to evaluate the contribution of patches in different groups. Results show that this group selection based iris recognition

A highly sensitive and selective fluorescent sensor for detection of sulfide anion based on the steric hindrance effect

NASA Astrophysics Data System (ADS)

Chen, Guanfan; Tang, Mengzhuo; Fu, Xiufang; Cheng, Fenmin; Zou, Xianghua; Wang, Jingpei; Zeng, Rongjin

2018-01-01

Sulfide anions are not only generated as a byproduct from industrial processes but also as a crucial kind of element in biological systems. Therefore, fluorescent probes for detecting sulfide anion with sensitive and selective characters are highly popular. In this study, we report a highly sensitive and selective fluorescent sensor M1 for detection of sulfide anion based on the steric hindrance effect, where the recognition unit, dinitrobenzenesulfonate ester group is linked to aromatic ortho-position in the porphyrin, and correspondingly the fluorescence of fluorescein is efficiently quenched. Compared with the sensors with recognition unit linked to the other aromatic positions, the fluorescent sensor M1 has a lower fluorescence background. Furthermore, the corresponding fluorescence responses (F/F0) of M1 for mercapto amino-acid GSH, Hcy and Cys, were all far lower than the relative fluorescence ratio F/F0 values for S2-. It means that M1 is sensitive and selective to detection of S2-, and has an anti-disturbance ability to the biologically-relevant thiols, GSH, Hcy and Cys, and has the prospect of application in the exact detection of sulfide anions in living organisms. This approach offers some useful insights for realizing sensitive and selective fluorescent turn-on sensing in the detection assays for other analytes.

Magnetic, core-shell structured and surface molecularly imprinted polymers for the rapid and selective recognition of salicylic acid from aqueous solutions

NASA Astrophysics Data System (ADS)

Zhang, Zulei; Niu, Dechao; Li, Yongsheng; Shi, Jianlin

2018-03-01

In this work, a novel kind of magnetic, core-shell structured and surface molecularly imprinted polymers (MMIPs) for the recognition of salicylic acid (SA) was facilely synthesized through a surface imprinting and sol-gel polymerization approach. The as-synthesized MMIPs exhibit uniform core-shell structure and favorable magnetic properties with a saturation magnetization of 22.8 emu g-1. The binding experiments demonstrated that MMIPs possessed high binding and specific recognition capacity, as well as fast binding kinetics and phase separation rate. The maximum binding capacity of MMIPs is around 36.8 mg g-1, nearly 6 times that of the magnetic non-imprinted polymers (MNIPs). Moreover, the selectivity experiments show that all the relative selectivity coefficients towards SA over its structure analogs are higher than 18, further indicating the markedly enhanced binding selectivity of MMIPs. Furthermore, the MMIPs were successfully applied for the determination of SA in environmental water samples with the recovery rates ranging from 94.0 to 108.0 %. This strategy may provide a versatile approach for the fabrication of well-defined molecularly imprinted polymers on nanomaterials for the analysis of complicated matrixes.

Boronate affinity-based surface molecularly imprinted polymers using glucose as fragment template for excellent recognition of glucosides.

PubMed

Peng, Mijun; Xiang, Haiyan; Hu, Xin; Shi, Shuyun; Chen, Xiaoqing

2016-11-25

Rapid and efficient extraction of bioactive glycosides from complex natural origins poses a difficult challenge, and then is often inherent bottleneck for their highly utilization. Herein, we propose a strategy to fabricate boronate affinity based surface molecularly imprinted polymers (MIPs) for excellent recognition of glucosides. d-glucose was used as fragment template. Boronic acid, dynamic covalent binding with d-glucose under different pH conditions, was selected as functional monomer to improve specificity. Fe 3 O 4 solid core for surface imprinting using tetraethyl orthosilicate (TEOS) as crosslinker could control imprinted shell thickness for favorable adsorption capacity and satisfactory mass transfer rate, improve hydrophilicity, separate easily by a magnet. Model adsorption studies showed that the resulting MIPs show specific recognition of glucosides. The equilibrium data fitted well to Langmuir equation and the adsorption process could be described by pseudo-second order model. Furthermore, the MIPs were successfully applied for selective extraction of three flavonoid glucosides (daidzin, glycitin, and genistin) from soybean. Results indicated that selective extraction of glucosides from complex aqueous media based on the prepared MIPs is simple, rapid, efficient and specific. Moreover, this method opens up a universal route for imprinting saccharide with cis-diol group for glycosides recognition. Copyright © 2016 Elsevier B.V. All rights reserved.

Protein-targeted corona phase molecular recognition

PubMed Central

Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

2016-01-01

Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications. PMID:26742890

Binding-induced DNA walker for signal amplification in highly selective electrochemical detection of protein.

PubMed

Ji, Yuhang; Zhang, Lei; Zhu, Longyi; Lei, Jianping; Wu, Jie; Ju, Huangxian

2017-10-15

A binding-induced DNA walker-assisted signal amplification was developed for highly selective electrochemical detection of protein. Firstly, the track of DNA walker was constructed by self-assembly of the high density ferrocene (Fc)-labeled anchor DNA and aptamer 1 on the gold electrode surface. Sequentially, a long swing-arm chain containing aptamer 2 and walking strand DNA was introduced onto gold electrode through aptamers-target specific recognition, and thus initiated walker strand sequences to hybridize with anchor DNA. Then, the DNA walker was activated by the stepwise cleavage of the hybridized anchor DNA by nicking endonuclease to release multiple Fc molecules for signal amplification. Taking thrombin as the model target, the Fc-generated electrochemical signal decreased linearly with logarithm value of thrombin concentration ranging from 10pM to 100nM with a detection limit of 2.5pM under the optimal conditions. By integrating the specific recognition of aptamers to target with the enzymatic cleavage of nicking endonuclease, the aptasensor showed the high selectivity. The binding-induced DNA walker provides a promising strategy for signal amplification in electrochemical biosensor, and has the extensive applications in sensitive and selective detection of the various targets. Copyright © 2017 Elsevier B.V. All rights reserved.

Individual differences in cortical face selectivity predict behavioral performance in face recognition

PubMed Central

Huang, Lijie; Song, Yiying; Li, Jingguang; Zhen, Zonglei; Yang, Zetian; Liu, Jia

2014-01-01

In functional magnetic resonance imaging studies, object selectivity is defined as a higher neural response to an object category than other object categories. Importantly, object selectivity is widely considered as a neural signature of a functionally-specialized area in processing its preferred object category in the human brain. However, the behavioral significance of the object selectivity remains unclear. In the present study, we used the individual differences approach to correlate participants' face selectivity in the face-selective regions with their behavioral performance in face recognition measured outside the scanner in a large sample of healthy adults. Face selectivity was defined as the z score of activation with the contrast of faces vs. non-face objects, and the face recognition ability was indexed as the normalized residual of the accuracy in recognizing previously-learned faces after regressing out that for non-face objects in an old/new memory task. We found that the participants with higher face selectivity in the fusiform face area (FFA) and the occipital face area (OFA), but not in the posterior part of the superior temporal sulcus (pSTS), possessed higher face recognition ability. Importantly, the association of face selectivity in the FFA and face recognition ability cannot be accounted for by FFA response to objects or behavioral performance in object recognition, suggesting that the association is domain-specific. Finally, the association is reliable, confirmed by the replication from another independent participant group. In sum, our finding provides empirical evidence on the validity of using object selectivity as a neural signature in defining object-selective regions in the human brain. PMID:25071513

Selective Electrocatalytic Degradation of Odorous Mercaptans Derived from S-Au Bond Recongnition on a Dendritic Gold/Boron-Doped Diamond Composite Electrode.

PubMed

Chai, Shouning; Wang, Yujing; Zhang, Ya-Nan; Liu, Meichuan; Wang, Yanbin; Zhao, Guohua

2017-07-18

To improve selectivity of electrocatalytic degradation of toxic, odorous mercaptans, the fractal-structured dendritic Au/BDD (boron-doped diamond) anode with molecular recognition is fabricated through a facile replacement method. SEM and TEM characterizations show that the gold dendrites are single crystals and have high population of the Au (111) facet. The distinctive structure endows the electrode with advantages of low resistivity, high active surface area, and prominent electrocatalytic activity. To evaluate selectivity, the dendritic Au/BDD is applied in degrading two groups of synthetic wastewater containing thiophenol/2-mercaptobenzimidazole (targets) and phenol/2-hydroxybenzimidazole (interferences), respectively. Results show that targets removals reach 91%/94%, while interferences removals are only 58%/48% in a short time. The corresponding degradation kinetic constants of targets are 3.25 times and 4.1 times that of interferences in the same group, demonstrating modification of dendritic gold on BDD could effectively enhance electrocatalytic target-selectivity. XPS and EXAFS further reveal that the selective electrocatalytic degradation derives from preferential recognition and fast adsorption to thiophenol depending on strong Au-S bond. The efficient, selective degradation is attributed to the synergetic effects between accumulative behavior and outstanding electrochemical performances. This work provides a new strategy for selective electrochemical degradation of contaminants for actual wastewater treatment.

Bag-of-visual-phrases and hierarchical deep models for traffic sign detection and recognition in mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yu, Yongtao; Li, Jonathan; Wen, Chenglu; Guan, Haiyan; Luo, Huan; Wang, Cheng

2016-03-01

This paper presents a novel algorithm for detection and recognition of traffic signs in mobile laser scanning (MLS) data for intelligent transportation-related applications. The traffic sign detection task is accomplished based on 3-D point clouds by using bag-of-visual-phrases representations; whereas the recognition task is achieved based on 2-D images by using a Gaussian-Bernoulli deep Boltzmann machine-based hierarchical classifier. To exploit high-order feature encodings of feature regions, a deep Boltzmann machine-based feature encoder is constructed. For detecting traffic signs in 3-D point clouds, the proposed algorithm achieves an average recall, precision, quality, and F-score of 0.956, 0.946, 0.907, and 0.951, respectively, on the four selected MLS datasets. For on-image traffic sign recognition, a recognition accuracy of 97.54% is achieved by using the proposed hierarchical classifier. Comparative studies with the existing traffic sign detection and recognition methods demonstrate that our algorithm obtains promising, reliable, and high performance in both detecting traffic signs in 3-D point clouds and recognizing traffic signs on 2-D images.

Fluorescent chemosensor based on urea/thiourea moiety for sensing of Hg(II) ions in an aqueous medium with high sensitivity and selectivity: A comparative account on effect of molecular architecture on chemosensing

NASA Astrophysics Data System (ADS)

Mishra, Jayanti; Kaur, Harpreet; Ganguli, Ashok K.; Kaur, Navneet

2018-06-01

Mercury is a well-known heavy metal ion which is extremely poisonous to health but is still employed in the form of mercury salts and organomercury compounds in various industrial, anthropological and agricultural activities. Henceforth, its sensing in aqueous medium is an area of great interest in order to avoid its hazardous effect. In the present manuscript, urea/thiourea linkage bearing four organic ligands (1a, 1b, 2a and 2b) are synthesized by a three-step synthetic approach. The organic ligands were then employed to develop organic nanoparticles by re-precipitation method which was further probed for their selective recognition behavior in an aqueous medium using fluorescence spectroscopy. The fluorescence emission profile of the ONPs is used as a tool for the tracking of sensing behavior. The ONPs of 1b has shown selective recognition towards Hg(II) in aqueous medium evidenced by enhancement of fluorescence emission intensity after complexation of 1b ONP with Hg(II), among several alkali, alkaline earth and transition metal ions with a detection limit of the order of 0.84 μM. The ability of the proposed sensor to sense Hg(II) ions with high selectivity and sensitivity could be accounted to photo-induced electron transfer (PET) "OFF" mechanism at λem = 390 nm. This study reveals the application of the proposed thiourea-based sensor for the selective recognition of the Hg(II) ions in an aqueous medium.

Efficient live face detection to counter spoof attack in face recognition systems

NASA Astrophysics Data System (ADS)

Biswas, Bikram Kumar; Alam, Mohammad S.

2015-03-01

Face recognition is a critical tool used in almost all major biometrics based security systems. But recognition, authentication and liveness detection of the face of an actual user is a major challenge because an imposter or a non-live face of the actual user can be used to spoof the security system. In this research, a robust technique is proposed which detects liveness of faces in order to counter spoof attacks. The proposed technique uses a three-dimensional (3D) fast Fourier transform to compare spectral energies of a live face and a fake face in a mathematically selective manner. The mathematical model involves evaluation of energies of selective high frequency bands of average power spectra of both live and non-live faces. It also carries out proper recognition and authentication of the face of the actual user using the fringe-adjusted joint transform correlation technique, which has been found to yield the highest correlation output for a match. Experimental tests show that the proposed technique yields excellent results for identifying live faces.

Direct protein interaction underlies gene-for-gene specificity and coevolution of the flax resistance genes and flax rust avirulence genes

PubMed Central

Dodds, Peter N.; Lawrence, Gregory J.; Catanzariti, Ann-Maree; Teh, Trazel; Wang, Ching-I. A.; Ayliffe, Michael A.; Kobe, Bostjan; Ellis, Jeffrey G.

2006-01-01

Plant resistance proteins (R proteins) recognize corresponding pathogen avirulence (Avr) proteins either indirectly through detection of changes in their host protein targets or through direct R–Avr protein interaction. Although indirect recognition imposes selection against Avr effector function, pathogen effector molecules recognized through direct interaction may overcome resistance through sequence diversification rather than loss of function. Here we show that the flax rust fungus AvrL567 genes, whose products are recognized by the L5, L6, and L7 R proteins of flax, are highly diverse, with 12 sequence variants identified from six rust strains. Seven AvrL567 variants derived from Avr alleles induce necrotic responses when expressed in flax plants containing corresponding resistance genes (R genes), whereas five variants from avr alleles do not. Differences in recognition specificity between AvrL567 variants and evidence for diversifying selection acting on these genes suggest they have been involved in a gene-specific arms race with the corresponding flax R genes. Yeast two-hybrid assays indicate that recognition is based on direct R–Avr protein interaction and recapitulate the interaction specificity observed in planta. Biochemical analysis of Escherichia coli-produced AvrL567 proteins shows that variants that escape recognition nevertheless maintain a conserved structure and stability, suggesting that the amino acid sequence differences directly affect the R–Avr protein interaction. We suggest that direct recognition associated with high genetic diversity at corresponding R and Avr gene loci represents an alternative outcome of plant–pathogen coevolution to indirect recognition associated with simple balanced polymorphisms for functional and nonfunctional R and Avr genes. PMID:16731621

Attitudes and Opinions from the Nation's High Achieving Teens: 29th Annual Survey of High Achievers.

ERIC Educational Resources Information Center

Who's Who among American High School Students, Lake Forest, IL.

This report presents the 1998 statistical findings of the annual survey to determine the attitudes of national high school student leaders. Questionnaires were completed by 3,123 high school juniors and seniors, all of whom were selected for recognition in "Who's Who among American High School Students." In addition to demographic…

16th Annual Survey of High Achievers: Attitudes and Opinions from the Nation's High Achieving Teens.

ERIC Educational Resources Information Center

Who's Who among American High School Students, Northbrook, IL.

The report presents data from 2,043 questionnaires completed by secondary student leaders and high achievers. Ss were selected for recognition in "Who's Who Among American High School Students" by their principals or guidance counselors, national youth organizations, or the publishing company because of high achievement in academics, activities,…

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark; Selinsky, T.

2002-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user's tendencies while the user is selecting targets and to increase the user's productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Error Rates in Users of Automatic Face Recognition Software

PubMed Central

White, David; Dunn, James D.; Schmid, Alexandra C.; Kemp, Richard I.

2015-01-01

In recent years, wide deployment of automatic face recognition systems has been accompanied by substantial gains in algorithm performance. However, benchmarking tests designed to evaluate these systems do not account for the errors of human operators, who are often an integral part of face recognition solutions in forensic and security settings. This causes a mismatch between evaluation tests and operational accuracy. We address this by measuring user performance in a face recognition system used to screen passport applications for identity fraud. Experiment 1 measured target detection accuracy in algorithm-generated ‘candidate lists’ selected from a large database of passport images. Accuracy was notably poorer than in previous studies of unfamiliar face matching: participants made over 50% errors for adult target faces, and over 60% when matching images of children. Experiment 2 then compared performance of student participants to trained passport officers–who use the system in their daily work–and found equivalent performance in these groups. Encouragingly, a group of highly trained and experienced “facial examiners” outperformed these groups by 20 percentage points. We conclude that human performance curtails accuracy of face recognition systems–potentially reducing benchmark estimates by 50% in operational settings. Mere practise does not attenuate these limits, but superior performance of trained examiners suggests that recruitment and selection of human operators, in combination with effective training and mentorship, can improve the operational accuracy of face recognition systems. PMID:26465631

Well-defined magnetic surface imprinted nanoparticles for selective enrichment of 2,4-dichlorophenoxyacetic acid in real samples.

PubMed

Sheng, Le; Jin, Yulong; He, Yonghuan; Huang, Yanyan; Yan, Liushui; Zhao, Rui

2017-11-01

Superparamagnetic core-shell molecularly imprinted polymer nanoparticles (MIPs) were prepared via surface initiated reversible-addition fragmentation chain transfer (si-RAFT) polymerization for the selective recognition of 2,4-dichlorophenoxyacetic acid (2,4-D) in real samples. The construction of uniform core-shell structure with a 50nm MIP layer was successfully accomplished, which favored mass transfer and resulted in fast recognition kinetics. The static equilibrium experiments revealed the satisfied adsorption capacity and imprinting efficiency of Fe 3 O 4 @MIP. Moreover, the Fe 3 O 4 @MIP exhibited high selectivity and affinity towards 2,4-D over structural analogues. The prepared Fe 3 O 4 @MIP nanoparticles were used for the selective enrichment of 2,4-D in tap water and Chinese cabbage samples. Combined with RP-HPLC, the recoveries of 2,4-D were calculated from 93.1% to 103.3% with RSD of 1.7-5.4% (n = 3) in Chinese cabbage samples. This work provides a versatile approach for fabricating well-constructed core-shell MIP nanoparticles for rapid enrichment and highly selective separation of target molecules in real samples. Copyright © 2017 Elsevier B.V. All rights reserved.

The challenge of localizing the anterior temporal face area: a possible solution.

PubMed

Axelrod, Vadim; Yovel, Galit

2013-11-01

Humans recognize faces exceptionally well. However, the neural correlates of face recognition are still elusive. Accumulated evidence in recent years suggests that the anterior temporal lobe (ATL), in particular face-selective region in the ATL, is a probable locus of face recognition. Unfortunately, functional MRI (fMRI) studies encounter severe signal drop-out in the ventral ATL, where that ATL face area resides. Consequently, all previous studies localized this region in no more than half of the subjects and its volume was relatively small. Thus, a systematic exploration of the properties of the ATL face area is scarce. In the current high-resolution fMRI study we used coronal slice orientation, which permitted us to localize the ATL face area in all the subjects. Furthermore, the volume of the area was much larger than was reported in previous studies. Direct within subjects comparison with data collected with the commonly used axial slice orientation confirmed that the advantage of the coronal slice orientation in revealing a reliable and larger face-selective area in the ATL. Finally, by displaying the face-selective activations resultant from coronal and axial scanning together, we demonstrate an organization principle of a chain of face-selective regions along the posterior-anterior axis in the ventral temporal lobe that is highly reproducible across all subjects. By using the procedure proposed here, a significant progress can be made in studying the neural correlates of face recognition. Copyright © 2013 Elsevier Inc. All rights reserved.

A novel stable 3D luminescent uranyl complex for highly efficient and sensitive recognition of Ru3+ and biomolecules

NASA Astrophysics Data System (ADS)

Tian, Hong-Hong; Chen, Liang-Ting; Zhang, Rong-Lan; Zhao, Jian-She; Liu, Chi-Yang; Weng, Ng Seik

2018-02-01

A novel highly stable 3D luminescent uranyl coordination polymer, namely {[UO2(L)]·DMA}n (1), was assembled with uranyl salt and a glycine-derivative ligand [6-(carboxymethyl-amino)-4-oxo-4,5-dihydro-[1,3,5]triazin-2-ylamino]-acetic acid (H2L) under solvothermal reaction. Besides, It was found that complex 1 possesses excellent luminescent properties, particularly the efficient selectivity and sensitivity in the recognition of Ru3+, biomacromolecule bovine serum albumin (BSA), biological small molecules dopamine (DA), ascorbic acid (AA) and uric acid (UA) in the water solution based on a "turn-off" mechanism. Accordingly, the luminescent explorations also demonstrated that complex 1 could be acted as an efficient luminescent probe with high quenching efficiency and low detection limit for selectively detecting Ru3+ and biomolecules (DA, AA, UA and BSA). It was noted that the framework structure of complex 1 still remains highly stable after quenching, which was verified by powder X-ray diffraction (PXRD).

Highly selective SERS probe for Hg(II) detection using tryptophan-protected popcorn shaped gold nanoparticles.

PubMed

Senapati, Tapas; Senapati, Dulal; Singh, Anant Kumar; Fan, Zhen; Kanchanapally, Rajashekhar; Ray, Paresh Chandra

2011-10-07

Contamination of the environment with toxic Hg(II) is becoming a huge concern throughout the world now. Driven by the need, this communication reports for the first time a tryptophan protected popcorn shaped gold nanomaterials based SERS probe for rapid, easy and highly selective recognition of Hg(II) ions in the 5 ppb level from aqueous solution, with high sensitivity and selectivity over competing analytes. We demonstrate that our SERS assay is capable of measuring the amount of Hg(II) in alkaline battery. This journal is © The Royal Society of Chemistry 2011

Human activity recognition based on feature selection in smart home using back-propagation algorithm.

PubMed

Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei

2014-09-01

In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Hyperspectral face recognition with spatiospectral information fusion and PLS regression.

PubMed

Uzair, Muhammad; Mahmood, Arif; Mian, Ajmal

2015-03-01

Hyperspectral imaging offers new opportunities for face recognition via improved discrimination along the spectral dimension. However, it poses new challenges, including low signal-to-noise ratio, interband misalignment, and high data dimensionality. Due to these challenges, the literature on hyperspectral face recognition is not only sparse but is limited to ad hoc dimensionality reduction techniques and lacks comprehensive evaluation. We propose a hyperspectral face recognition algorithm using a spatiospectral covariance for band fusion and partial least square regression for classification. Moreover, we extend 13 existing face recognition techniques, for the first time, to perform hyperspectral face recognition.We formulate hyperspectral face recognition as an image-set classification problem and evaluate the performance of seven state-of-the-art image-set classification techniques. We also test six state-of-the-art grayscale and RGB (color) face recognition algorithms after applying fusion techniques on hyperspectral images. Comparison with the 13 extended and five existing hyperspectral face recognition techniques on three standard data sets show that the proposed algorithm outperforms all by a significant margin. Finally, we perform band selection experiments to find the most discriminative bands in the visible and near infrared response spectrum.

Facial recognition using multisensor images based on localized kernel eigen spaces.

PubMed

Gundimada, Satyanadh; Asari, Vijayan K

2009-06-01

A feature selection technique along with an information fusion procedure for improving the recognition accuracy of a visual and thermal image-based facial recognition system is presented in this paper. A novel modular kernel eigenspaces approach is developed and implemented on the phase congruency feature maps extracted from the visual and thermal images individually. Smaller sub-regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are then projected into higher dimensional spaces using kernel methods. The proposed localized nonlinear feature selection procedure helps to overcome the bottlenecks of illumination variations, partial occlusions, expression variations and variations due to temperature changes that affect the visual and thermal face recognition techniques. AR and Equinox databases are used for experimentation and evaluation of the proposed technique. The proposed feature selection procedure has greatly improved the recognition accuracy for both the visual and thermal images when compared to conventional techniques. Also, a decision level fusion methodology is presented which along with the feature selection procedure has outperformed various other face recognition techniques in terms of recognition accuracy.

Chiral recognition ability of an (S)-naproxen- imprinted monolith by capillary electrochromatography.

PubMed

Xu, Yan-Li; Liu, Zhao-Sheng; Wang, He-Fang; Yan, Chao; Gao, Ru-Yu

2005-02-01

The racemic naproxen was selectively recognized by capillary electrochromatography (CEC) on an (S)-naproxen-imprinted monolith, which was prepared by an in situ thermal-initiated polymerization. The recognition selectivity of a selected monolith strictly relied on the CEC conditions involved. The factors that influence the imprinting selectivity as well as the electroosmotic flow (EOF), including the applied voltage, organic solvent, salt concentration and pH value of the buffer, column temperature, and surfactant modifiers were systematically studied. Once the column was prepared, the experiment results showed that the successful chiral recognition was dependent on CEC variables. For example: the recognition could be observed in acetonitrile and ethanol electrolytes, while methanol and dimethyl sulfoxide (DMSO) electrolytes had no chiral recognition ability. The buffer with pH values of 2.6 or 3.0 at a higher salt concentration had chiral recognition ability. Column temperatures of 25-35 degrees C were optimal. Three surfactants, sodium dodecyl sulfate (SDS), cetyltrimethylammonium bromide (CTAB), and polyoxyethylene sorbitan monolaurate (Tween 20), can improve the recognition. Baseline resolution was obtained under optimized conditions and the column efficiency of the later eluent (S)-naproxen was 90 000 plates/m.

Wavelength- or Polarization-Selective Thermal Infrared Detectors for Multi-Color or Polarimetric Imaging Using Plasmonics and Metamaterials

PubMed Central

Ogawa, Shinpei; Kimata, Masafumi

2017-01-01

Wavelength- or polarization-selective thermal infrared (IR) detectors are promising for various novel applications such as fire detection, gas analysis, multi-color imaging, multi-channel detectors, recognition of artificial objects in a natural environment, and facial recognition. However, these functions require additional filters or polarizers, which leads to high cost and technical difficulties related to integration of many different pixels in an array format. Plasmonic metamaterial absorbers (PMAs) can impart wavelength or polarization selectivity to conventional thermal IR detectors simply by controlling the surface geometry of the absorbers to produce surface plasmon resonances at designed wavelengths or polarizations. This enables integration of many different pixels in an array format without any filters or polarizers. We review our recent advances in wavelength- and polarization-selective thermal IR sensors using PMAs for multi-color or polarimetric imaging. The absorption mechanism defined by the surface structures is discussed for three types of PMAs—periodic crystals, metal-insulator-metal and mushroom-type PMAs—to demonstrate appropriate applications. Our wavelength- or polarization-selective uncooled IR sensors using various PMAs and multi-color image sensors are then described. Finally, high-performance mushroom-type PMAs are investigated. These advanced functional thermal IR detectors with wavelength or polarization selectivity will provide great benefits for a wide range of applications. PMID:28772855

Wavelength- or Polarization-Selective Thermal Infrared Detectors for Multi-Color or Polarimetric Imaging Using Plasmonics and Metamaterials.

PubMed

Ogawa, Shinpei; Kimata, Masafumi

2017-05-04

Wavelength- or polarization-selective thermal infrared (IR) detectors are promising for various novel applications such as fire detection, gas analysis, multi-color imaging, multi-channel detectors, recognition of artificial objects in a natural environment, and facial recognition. However, these functions require additional filters or polarizers, which leads to high cost and technical difficulties related to integration of many different pixels in an array format. Plasmonic metamaterial absorbers (PMAs) can impart wavelength or polarization selectivity to conventional thermal IR detectors simply by controlling the surface geometry of the absorbers to produce surface plasmon resonances at designed wavelengths or polarizations. This enables integration of many different pixels in an array format without any filters or polarizers. We review our recent advances in wavelength- and polarization-selective thermal IR sensors using PMAs for multi-color or polarimetric imaging. The absorption mechanism defined by the surface structures is discussed for three types of PMAs-periodic crystals, metal-insulator-metal and mushroom-type PMAs-to demonstrate appropriate applications. Our wavelength- or polarization-selective uncooled IR sensors using various PMAs and multi-color image sensors are then described. Finally, high-performance mushroom-type PMAs are investigated. These advanced functional thermal IR detectors with wavelength or polarization selectivity will provide great benefits for a wide range of applications.

Examination of the neighborhood activation theory in normal and hearing-impaired listeners.

PubMed

Dirks, D D; Takayanagi, S; Moshfegh, A; Noffsinger, P D; Fausti, S A

2001-02-01

Experiments were conducted to examine the effects of lexical information on word recognition among normal hearing listeners and individuals with sensorineural hearing loss. The lexical factors of interest were incorporated in the Neighborhood Activation Model (NAM). Central to this model is the concept that words are recognized relationally in the context of other phonemically similar words. NAM suggests that words in the mental lexicon are organized into similarity neighborhoods and the listener is required to select the target word from competing lexical items. Two structural characteristics of similarity neighborhoods that influence word recognition have been identified; "neighborhood density" or the number of phonemically similar words (neighbors) for a particular target item and "neighborhood frequency" or the average frequency of occurrence of all the items within a neighborhood. A third lexical factor, "word frequency" or the frequency of occurrence of a target word in the language, is assumed to optimize the word recognition process by biasing the system toward choosing a high frequency over a low frequency word. Three experiments were performed. In the initial experiments, word recognition for consonant-vowel-consonant (CVC) monosyllables was assessed in young normal hearing listeners by systematically partitioning the items into the eight possible lexical conditions that could be created by two levels of the three lexical factors, word frequency (high and low), neighborhood density (high and low), and average neighborhood frequency (high and low). Neighborhood structure and word frequency were estimated computationally using a large, on-line lexicon-based Webster's Pocket Dictionary. From this program 400 highly familiar, monosyllables were selected and partitioned into eight orthogonal lexical groups (50 words/group). The 400 words were presented randomly to normal hearing listeners in speech-shaped noise (Experiment 1) and "in quiet" (Experiment 2) as well as to an elderly group of listeners with sensorineural hearing loss in the speech-shaped noise (Experiment 3). The results of three experiments verified predictions of NAM in both normal hearing and hearing-impaired listeners. In each experiment, words from low density neighborhoods were recognized more accurately than those from high density neighborhoods. The presence of high frequency neighbors (average neighborhood frequency) produced poorer recognition performance than comparable conditions with low frequency neighbors. Word frequency was found to have a highly significant effect on word recognition. Lexical conditions with high word frequencies produced higher performance scores than conditions with low frequency words. The results supported the basic tenets of NAM theory and identified both neighborhood structural properties and word frequency as significant lexical factors affecting word recognition when listening in noise and "in quiet." The results of the third experiment permit extension of NAM theory to individuals with sensorineural hearing loss. Future development of speech recognition tests should allow for the effects of higher level cognitive (lexical) factors on lower level phonemic processing.

Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems.

PubMed

Gao, Lei; Bourke, A K; Nelson, John

2014-06-01

Physical activity has a positive impact on people's well-being and it had been shown to decrease the occurrence of chronic diseases in the older adult population. To date, a substantial amount of research studies exist, which focus on activity recognition using inertial sensors. Many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers to improve the overall recognition accuracy. In addition, the implementation of the advanced feature extraction algorithms and the complex classifiers exceed the computing ability of most current wearable sensor platforms. This paper proposes a method to adopt multiple sensors on distributed body locations to overcome this problem. The objective of the proposed system is to achieve higher recognition accuracy with "light-weight" signal processing algorithms, which run on a distributed computing based sensor system comprised of computationally efficient nodes. For analysing and evaluating the multi-sensor system, eight subjects were recruited to perform eight normal scripted activities in different life scenarios, each repeated three times. Thus a total of 192 activities were recorded resulting in 864 separate annotated activity states. The methods for designing such a multi-sensor system required consideration of the following: signal pre-processing algorithms, sampling rate, feature selection and classifier selection. Each has been investigated and the most appropriate approach is selected to achieve a trade-off between recognition accuracy and computing execution time. A comparison of six different systems, which employ single or multiple sensors, is presented. The experimental results illustrate that the proposed multi-sensor system can achieve an overall recognition accuracy of 96.4% by adopting the mean and variance features, using the Decision Tree classifier. The results demonstrate that elaborate classifiers and feature sets are not required to achieve high recognition accuracies on a multi-sensor system. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition

PubMed Central

Mala, S.; Latha, K.

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition. PMID:25574185

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

PubMed

Mala, S; Latha, K

2014-01-01

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

Magnetic deep eutectic solvents molecularly imprinted polymers for the selective recognition and separation of protein.

PubMed

Liu, Yanjin; Wang, Yuzhi; Dai, Qingzhou; Zhou, Yigang

2016-09-14

A novel and facile magnetic deep eutectic solvents (DES) molecularly imprinted polymers (MIPs) for the selective recognition and separation of Bovine hemoglobin (BHb) was prepared. The new-type DES was adopted as the functional monomer which would bring molecular imprinted technology to a new direction. The amounts of DES were optimized. The obtained magnetic DES-MIPs were characterized with fourier transform infrared spectrometry (FT-IR), thermogravimetric analysis (TGA), field emission scanning electron microscope (FESEM), dynamic light scattering (DLS), elemental analysis and vibrating sample magnetometer (VSM). The results suggested that the imprinted polymers were successfully formed and possessed a charming magnetism. The maximum adsorption capability (Qmax) and dissociation constant (KL) were analyzed by Langmuir isotherms (R(2) = 0.9983) and the value were estimated to be 175.44 mg/g and 0.035 mg/mL for the imprinted particles. And the imprinted particles showed a high imprinting factor of 4.77. In addition, the magnetic DES-MIPs presented outstanding recognition specificity and selectivity so that it can be utilized to separate template protein from the mixture of proteins and real samples. Last but not least, the combination of deep eutectic solvents and molecular imprinted technology in this paper provides a new perspective for the recognition and separation of proteins. Copyright © 2016 Elsevier B.V. All rights reserved.

Integration trumps selection in object recognition.

PubMed

Saarela, Toni P; Landy, Michael S

2015-03-30

Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several "cues" (color, luminance, texture, etc.), and humans can integrate sensory cues to improve detection and recognition [1-3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue invariance by responding to a given shape independent of the visual cue defining it [5-8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10, 11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11, 12], imaging [13-16], and single-cell and neural population recordings [17, 18]. Besides single features, attention can select whole objects [19-21]. Objects are among the suggested "units" of attention because attention to a single feature of an object causes the selection of all of its features [19-21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integration trumps selection in object recognition

PubMed Central

Saarela, Toni P.; Landy, Michael S.

2015-01-01

Summary Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several “cues” (color, luminance, texture etc.), and humans can integrate sensory cues to improve detection and recognition [1–3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue-invariance by responding to a given shape independent of the visual cue defining it [5–8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10,11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11,12], imaging [13–16], and single-cell and neural population recordings [17,18]. Besides single features, attention can select whole objects [19–21]. Objects are among the suggested “units” of attention because attention to a single feature of an object causes the selection of all of its features [19–21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near-optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154

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

PubMed

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.

High Achievers: 23rd Annual Survey. Attitudes and Opinions from the Nation's High Achieving Teens.

ERIC Educational Resources Information Center

Who's Who among American High School Students, Northbrook, IL.

This report presents data from an annual survey of high school student leaders and high achievers. It is noted that of the nearly 700,000 high achievers featured in this edition, 5,000 students were sent the survey and 2,092 questionnaires were completed. Subjects were high school juniors and seniors selected for recognition by their principals or…

Sensitive fluorescence on-off probes for the fast detection of a chemical warfare agent mimic.

PubMed

Khan, Muhammad Shar Jhahan; Wang, Ya-Wen; Senge, Mathias O; Peng, Yu

2018-01-15

Two highly sensitive probes bearing a nucleophilic imine moiety have been utilized for the selective detection of chemical warfare agent (CWA) mimics. Diethyl chlorophosphate (DCP) was used as mimic CWAs. Both iminocoumarin-benzothiazole-based probes not only demonstrated a remarkable fluorescence ON-OFF response and good recognition, but also exhibited fast response times (10s) along with color changes upon addition of DCP. Limits of detection for the two sensors 1 and 2 were calculated as 0.065μM and 0.21μM, respectively, which are much lower than most other reported probes. These two probes not only show high sensitivity and selectivity in solution, but can also be applied for the recognition of DCP in the gas state, with significant color changes easily observed by the naked eye. Copyright © 2017 Elsevier B.V. All rights reserved.

Poly(ionic liquid) based chemosensors for detection of basic amino acids in aqueous medium

NASA Astrophysics Data System (ADS)

Li, Xinjuan; Wang, Kai; Ma, Nana; Jia, Xianbin

2017-09-01

Naked-eye detection of amino acids in water is of great significance in the field of bio-analytical applications. Herein, polymerized ionic liquids (PILs) with controlled chain length structures were synthesized via reversible addition-fragmentation chain-transfer (RAFT) polymerization and post-quaternization approach. The amino acids recognition performance of PILs with different alkyl chain lengths and molecular weights was evaluated by naked-eye color change and ultraviolet-visible (UV-vis) spectral studies. These PILs were successfully used for highly sensitive and selective detection of Arg, Lys and His in water. The recognition performance was improved effectively with increased molecular weight of PILs. The biosensitivity of the PILs in water was strongly dependent on their aggregation effect and polarization effect. Highly sensitive and selective detection of amino acids was successfully accomplished by introducing positively charged pyridinium moieties and controlled RAFT radical polymerization.

Molecular recognition in poly(epsilon-caprolactone)-based thermoplastic elastomers.

PubMed

Wisse, Eva; Spiering, A J H; van Leeuwen, Ellen N M; Renken, Raymond A E; Dankers, Patricia Y W; Brouwer, Linda A; van Luyn, Marja J A; Harmsen, Martin C; Sommerdijk, Nico A J M; Meijer, E W

2006-12-01

The molecular recognition properties of the hydrogen bonding segments in biodegradable thermoplastic elastomers were explored, aiming at the further functionalization of these potentially interesting biomaterials. A poly(epsilon-caprolactone)-based poly(urea) 2 was synthesized and characterized in terms of mechanical properties, processibility and histocompatibility. Comparison of the data with those obtained from the structurally related poly(urethane urea) 1 revealed that the difference in hard segment structure does not significantly affect the potency for application as a biomaterial. Nevertheless, the small differences in hard block composition had a strong effect on the molecular recognition properties of the hydrogen bonding segments. High selectivity was found for poly(urea) 2 in which bisureidobutylene-functionalized azobenzene dye 3 was selectively incorporated while bisureidopentylene-functionalized azobenzene dye 4 was completely released. In contrast, the incorporation of both dyes in poly(urethane urea) 1 led in both cases to their gradual release in time. Thermal analysis of the polymers in combination with variable temperature infrared experiments indicated that the hard blocks in 1 showed a sharp melting point, whereas those in 2 showed a very broad melting trajectory. This suggests a more precise organization of the hydrogen bonding segments in the hard blocks of poly(urea) 2 compared to poly(urethane urea) 1 and explains the results from the molecular recognition experiments. Preliminary results revealed that a bisureidobutylene-functionalized GRGDS peptide showed more supramolecular interaction with the PCL-based poly(urea), containing the bisureidobutylene recognition unit, as compared to HMW PCL, lacking this recognition unit.

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

PubMed

Liu, Chuanjun; Wyszynski, Bartosz; Yatabe, Rui; Hayashi, Kenshi; Toko, Kiyoshi

2017-02-16

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 effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor.

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

PubMed Central

Liu, Chuanjun; Wyszynski, Bartosz; Yatabe, Rui; Hayashi, Kenshi; Toko, Kiyoshi

2017-01-01

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 effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor. PMID:28212347

Fast cat-eye effect target recognition based on saliency extraction

NASA Astrophysics Data System (ADS)

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.

Fast and accurate face recognition based on image compression

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2017-05-01

Image compression is desired for many image-related applications especially for network-based applications with bandwidth and storage constraints. The face recognition community typical reports concentrate on the maximal compression rate that would not decrease the recognition accuracy. In general, the wavelet-based face recognition methods such as EBGM (elastic bunch graph matching) and FPB (face pattern byte) are of high performance but run slowly due to their high computation demands. The PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) algorithms run fast but perform poorly in face recognition. In this paper, we propose a novel face recognition method based on standard image compression algorithm, which is termed as compression-based (CPB) face recognition. First, all gallery images are compressed by the selected compression algorithm. Second, a mixed image is formed with the probe and gallery images and then compressed. Third, a composite compression ratio (CCR) is computed with three compression ratios calculated from: probe, gallery and mixed images. Finally, the CCR values are compared and the largest CCR corresponds to the matched face. The time cost of each face matching is about the time of compressing the mixed face image. We tested the proposed CPB method on the "ASUMSS face database" (visible and thermal images) from 105 subjects. The face recognition accuracy with visible images is 94.76% when using JPEG compression. On the same face dataset, the accuracy of FPB algorithm was reported as 91.43%. The JPEG-compressionbased (JPEG-CPB) face recognition is standard and fast, which may be integrated into a real-time imaging device.

"Sign-on/off" sensing interface design and fabrication for propyl gallate recognition and sensitive detection.

PubMed

Dai, Yunlong; Li, Xueyan; Fan, Limei; Lu, Xiaojing; Kan, Xianwen

2016-12-15

A new strategy based on sign-on and sign-off was proposed for propyl gallate (PG) determination by an electrochemical sensor. The successively modified poly(thionine) (PTH) and molecular imprinted polymer (MIP) showed an obvious electrocatalysis and a good recognition toward PG, respectively. Furthermore, the rebound PG molecules in imprinted cavities not only were oxidized but also blocked the electron transmission channels for PTH redox. Thus, a sign-on from PG current and a sign-off from PTH current were combined as a dual-sign for PG detection. Meanwhile, the modified MIP endowed the sensor with recognition capacity. The electrochemical experimental results demonstrated that the prepared sensor possessed good selectivity and high sensitivity. A linear ranging from 5.0×10(-8) to 1.0×10(-4)mol/L for PG detection was obtained with a limit of detection of 2.4×10(-8)mol/L. And the sensor has been applied to analyze PG in real samples with satisfactory results. The simple, low cost, and effective strategy reported here can be further used to prepare electrochemical sensors for other compounds selective recognition and sensitive detection. Copyright © 2016 Elsevier B.V. All rights reserved.

SD-MSAEs: Promoter recognition in human genome based on deep feature extraction.

PubMed

Xu, Wenxuan; Zhang, Li; Lu, Yaping

2016-06-01

The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different regions of DNA sequences. In this paper, we choose context feature and use a set of methods of SD to select the most effective n-mers distinguishing promoter regions from other DNA regions in human genome. Extracted from the total possible combinations of n-mers, we can get four sparse distributions based on promoter and non-promoters training samples. The informative n-mers are selected by optimizing the differentiating extents of these distributions. Specially, we combine the advantage of statistical divergence and multiple sparse auto-encoders (MSAEs) in deep learning to extract deep feature for promoter recognition. And then we apply multiple SVMs and a decision model to construct a human promoter recognition method called SD-MSAEs. Framework is flexible that it can integrate new feature extraction or new classification models freely. Experimental results show that our method has high sensitivity and specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

South Carolina Elementary Teachers' Perceptions of Principals' Transformational Leadership in Academically Recognized and Other, High Poverty Schools

ERIC Educational Resources Information Center

Lewis, Julian Carlton

2012-01-01

This study investigated selected elementary school teachers' perceptions of principals' leadership. Ten South Carolina schools were selected based on the criterion of 50% or higher poverty index. Five schools included the feature of recognition by the state for academic success for one year or more over the 2003-2006 timeframe. One hundred three…

22nd Annual Survey of High Achievers: Attitudes and Opinions from the Nation's High Achieving Teens.

ERIC Educational Resources Information Center

Who's Who among American High School Students, Northbrook, IL.

This study surveyed high school students (N=1,879) who were student leaders or high achievers in the spring of 1991 for the purpose of determining their attitudes. Students were members of the junior or senior high school class during the 1990-91 academic year and were selected for recognition by their principals or guidance counselors, other…

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Identification of Matra Region and Overlapping Characters for OCR of Printed Bengali Scripts

NASA Astrophysics Data System (ADS)

Goswami, Subhra Sundar

One of the important reasons for poor recognition rate in optical character recognition (OCR) system is the error in character segmentation. In case of Bangla scripts, the errors occur due to several reasons, which include incorrect detection of matra (headline), over-segmentation and under-segmentation. We have proposed a robust method for detecting the headline region. Existence of overlapping characters (in under-segmented parts) in scanned printed documents is a major problem in designing an effective character segmentation procedure for OCR systems. In this paper, a predictive algorithm is developed for effectively identifying overlapping characters and then selecting the cut-borders for segmentation. Our method can be successfully used in achieving high recognition result.

Potential transducers based man-tailored biomimetic sensors for selective recognition of dextromethorphan as an antitussive drug.

PubMed

El-Naby, Eman H; Kamel, Ayman H

2015-09-01

A biomimetic potentiometric sensor for specific recognition of dextromethorphan (DXM), a drug classified according to the Drug Enforcement Administration (DEA) as a "drug of concern", is designed and characterized. A molecularly imprinted polymer (MIP), with special molecular recognition properties of DXM, was prepared by thermal polymerization in which DXM acted as template molecule, methacrylic acid (MAA) and acrylonitrile (AN) acted as functional monomers in the presence of ethylene glycol dimethacrylate (EGDMA) as crosslinker. The sensors showed a high selectivity and a sensitive response to the template in aqueous system. Electrochemical evaluation of these sensors revealed near-Nernstian response with slopes of 49.6±0.5 and 53.4±0.5 mV decade(-1) with a detection limit of 1.9×10(-6), and 1.0×10(-6) mol L(-1) DXM with MIP/MAA and MIP/AN membrane based sensors, respectively. Significantly improved accuracy, precision, response time, stability, selectivity and sensitivity were offered by these simple and cost-effective potentiometric sensors compared with other standard techniques. The method has the requisite accuracy, sensitivity and precision to assay DXM in pharmaceutical products. Copyright © 2015 Elsevier B.V. All rights reserved.

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark

2003-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user s tendencies while the user is selecting targets and to increase the user s productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

A virus-MIPs fluorescent sensor based on FRET for highly sensitive detection of JEV.

PubMed

Liang, Caishuang; Wang, Huan; He, Kui; Chen, Chunyan; Chen, Xiaoming; Gong, Hang; Cai, Changqun

2016-11-01

Major stumbling blocks in the recognition and detection of virus are the unstable biological recognition element or the complex detection means. Here a fluorescent sensor based on virus-molecular imprinted polymers (virus-MIPs) was designed for specific recognition and highly sensitive detection of Japanese encephalitis virus (JEV). The virus-MIPs were anchored on the surface of silica microspheres modified by fluorescent dye, pyrene-1-carboxaldehyde (PC). The fluorescence intensity of PC can be enhanced by the principle of fluorescence resonance energy transfer (FRET), where virus acted as energy donor and PC acted as energy acceptor. The enhanced fluorescence intensity was proportional to the concentration of virus in the range of 24-960pM, with a limit of detection (LOD, 3σ) of 9.6pM, and the relative standard deviation was 1.99%. In additional, the specificity study confirmed the resultant MIPs has high-selectivity for JEV. This sensor would become a new key for the detection of virus because of its high sensitive, simple operation, high stability and low cost. Copyright © 2016. Published by Elsevier B.V.

Optimized Periocular Template Selection for Human Recognition

PubMed Central

Sa, Pankaj K.; Majhi, Banshidhar

2013-01-01

A novel approach for selecting a rectangular template around periocular region optimally potential for human recognition is proposed. A comparatively larger template of periocular image than the optimal one can be slightly more potent for recognition, but the larger template heavily slows down the biometric system by making feature extraction computationally intensive and increasing the database size. A smaller template, on the contrary, cannot yield desirable recognition though the smaller template performs faster due to low computation for feature extraction. These two contradictory objectives (namely, (a) to minimize the size of periocular template and (b) to maximize the recognition through the template) are aimed to be optimized through the proposed research. This paper proposes four different approaches for dynamic optimal template selection from periocular region. The proposed methods are tested on publicly available unconstrained UBIRISv2 and FERET databases and satisfactory results have been achieved. Thus obtained template can be used for recognition of individuals in an organization and can be generalized to recognize every citizen of a nation. PMID:23984370

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

PubMed

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.

Quantitative Expression and Immunogenicity of MAGE-3 and -6 in Upper Aerodigestive Tract Cancer

PubMed Central

Andrade Filho, Pedro A.; López-Albaitero, Andrés; Xi, Liqiang; Gooding, William; Godfrey, Tony; Ferris, Robert L.

2009-01-01

The MAGE antigens are frequently expressed cancer vaccine targets. However, quantitative analysis of MAGE expression in upper aero-digestive tract (UADT) tumor cells and its association with T cell recognition has not been performed, hindering the selection of appropriate candidates for MAGE specific immunotherapy. Using quantitative RT-PCR (QRT-PCR), we evaluated the expression of MAGE-3/6 in 65 UADT cancers, 48 normal samples from tumor matched sites and 7 HLA-A*0201+squamous cell carcinoma of the head and neck (SCCHN) cell lines. Expression results were confirmed using western blot. HLA-A*0201:MAGE-3(271–279) specific cytotoxic T lymphocytes (MAGE-CTL) from SCCHN patients and healthy donors showed that MAGE-3/6 expression was highly associated with CTL recognition in vitro. Based on MAGE-3/6 expression we could identify 31 (47%) of the 65 UADT tumors which appeared to express MAGE-3/6 at levels that correlated with efficient CTL recognition. To confirm that the level of MAGE-3 expression was responsible for CTL recognition, two MAGE-3/6 mRNAhigh SCCHN cell lines, PCI-13 and PCI-30, were subjected to MAGE-3/6 specific knockdown. RNAi–transfected cells showed that MAGE expression, and MAGE-CTL recognition, were significantly reduced. Furthermore, treatment of cells expressing low MAGE-3/6 mRNA with a demethylating agent, 5-aza-2'-deoxycytidine (DAC), increased the expression of MAGE-3/6 and CTL recognition. Thus, using QRT-PCR UADT cancers frequently express MAGE-3/6 at levels sufficient for CTL recognition, supporting the use of a QRT-PCR based assay for the selection of candidates likely to respond to MAGE-3/6 immunotherapy. Demethylating agents could increase the number of patients amenable for targeting epigenetically modified tumor antigens in vaccine trials. PMID:19610063

Evolution of kin recognition mechanisms in a fish.

PubMed

Hain, Timothy J A; Garner, Shawn R; Ramnarine, Indar W; Neff, Bryan D

2017-03-01

Both selection and phylogenetic history can influence the evolution of phenotypic traits. Here we used recently characterized variation in kin recognition mechanisms among six guppy populations to explore the phylogenetic history of this trait. Guppies can use two different kin recognition mechanisms: either phenotype matching, in which individuals are identified based on comparison with a recognition template, or familiarity, in which individuals are remembered based on previous interactions. Across the six populations, we identified four transitions in recognition mechanism: phenotype matching evolved once and was subsequently lost in a single population, whereas familiarity evolved twice. Based on a molecular clock, these transitions occurred among populations that had diverged on a timescale of hundreds of thousands of years, which is two orders of magnitude faster than previously documented transitions in recognition mechanisms. A randomization test provided no evidence that recognition mechanisms were constrained by phylogeny, suggesting that recognition mechanisms have the capacity to evolve rapidly, although the specific selection pressures that may be contributing to variation in recognition mechanisms across populations remain unknown.

In vitro selection of single-stranded DNA molecular recognition elements against S. aureus alpha toxin and sensitive detection in human serum.

PubMed

Hong, Ka L; Battistella, Luisa; Salva, Alysia D; Williams, Ryan M; Sooter, Letha J

2015-01-27

Alpha toxin is one of the major virulence factors secreted by Staphylococcus aureus, a bacterium that is responsible for a wide variety of infections in both community and hospital settings. Due to the prevalence of S. aureus related infections and the emergence of methicillin-resistant S. aureus, rapid and accurate diagnosis of S. aureus infections is crucial in benefiting patient health outcomes. In this study, a rigorous Systematic Evolution of Ligands by Exponential Enrichment (SELEX) variant previously developed by our laboratory was utilized to select a single-stranded DNA molecular recognition element (MRE) targeting alpha toxin with high affinity and specificity. At the end of the 12-round selection, the selected MRE had an equilibrium dissociation constant (Kd) of 93.7 ± 7.0 nM. Additionally, a modified sandwich enzyme-linked immunosorbent assay (ELISA) was developed by using the selected ssDNA MRE as the toxin-capturing element and a sensitive detection of 200 nM alpha toxin in undiluted human serum samples was achieved.

Selective attention meets spontaneous recognition memory: Evidence for effects at retrieval.

PubMed

Moen, Katherine C; Miller, Jeremy K; Lloyd, Marianne E

2017-03-01

Previous research on the effects of Divided Attention on recognition memory have shown consistent impairments during encoding but more variable effects at retrieval. The present study explored whether effects of Selective Attention at retrieval and subsequent testing were parallel to those of Divided Attention. Participants studied a list of pictures and then had a recognition memory test that included both full attention and selective attention (the to be responded to object was overlaid atop a blue outlined object) trials. All participants then completed a second recognition memory test. The results of 2 experiments suggest that subsequent tests consistently show impacts of the status of the ignored stimulus, and that having an initial test changes performance on a later test. The results are discussed in relation to effect of attention on memory more generally as well as spontaneous recognition memory research. Copyright © 2017 Elsevier Inc. All rights reserved.

Hierarchical sampling for metastable conformers determines biomolecular recognition: the case of malectin and diglucosylated N-glycan interactions.

PubMed

Mamidi, Ashalatha Sreshty; Surolia, Avadhesha

2015-01-01

Structural information over the entire course of binding interactions based on the analyses of energy landscapes is described, which provides a framework to understand the events involved during biomolecular recognition. Conformational dynamics of malectin's exquisite selectivity for diglucosylated N-glycan (Dig-N-glycan), a highly flexible oligosaccharide comprising of numerous dihedral torsion angles, are described as an example. For this purpose, a novel approach based on hierarchical sampling for acquiring metastable molecular conformations constituting low-energy minima for understanding the structural features involved in a biologic recognition is proposed. For this purpose, four variants of principal component analysis were employed recursively in both Cartesian space and dihedral angles space that are characterized by free energy landscapes to select the most stable conformational substates. Subsequently, k-means clustering algorithm was implemented for geometric separation of the major native state to acquire a final ensemble of metastable conformers. A comparison of malectin complexes was then performed to characterize their conformational properties. Analyses of stereochemical metrics and other concerted binding events revealed surface complementarity, cooperative and bidentate hydrogen bonds, water-mediated hydrogen bonds, carbohydrate-aromatic interactions including CH-π and stacking interactions involved in this recognition. Additionally, a striking structural transition from loop to β-strands in malectin CRD upon specific binding to Dig-N-glycan is observed. The interplay of the above-mentioned binding events in malectin and Dig-N-glycan supports an extended conformational selection model as the underlying binding mechanism.

Using hypnosis to disrupt face processing: mirrored-self misidentification delusion and different visual media

PubMed Central

Connors, Michael H.; Barnier, Amanda J.; Coltheart, Max; Langdon, Robyn; Cox, Rochelle E.; Rivolta, Davide; Halligan, Peter W.

2014-01-01

Mirrored-self misidentification delusion is the belief that one’s reflection in the mirror is not oneself. This experiment used hypnotic suggestion to impair normal face processing in healthy participants and recreate key aspects of the delusion in the laboratory. From a pool of 439 participants, 22 high hypnotisable participants (“highs”) and 20 low hypnotisable participants were selected on the basis of their extreme scores on two separately administered measures of hypnotisability. These participants received a hypnotic induction and a suggestion for either impaired (i) self-face recognition or (ii) impaired recognition of all faces. Participants were tested on their ability to recognize themselves in a mirror and other visual media – including a photograph, live video, and handheld mirror – and their ability to recognize other people, including the experimenter and famous faces. Both suggestions produced impaired self-face recognition and recreated key aspects of the delusion in highs. However, only the suggestion for impaired other-face recognition disrupted recognition of other faces, albeit in a minority of highs. The findings confirm that hypnotic suggestion can disrupt face processing and recreate features of mirrored-self misidentification. The variability seen in participants’ responses also corresponds to the heterogeneity seen in clinical patients. An important direction for future research will be to examine sources of this variability within both clinical patients and the hypnotic model. PMID:24994973

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

PubMed

Hustedde, C G; Wiley, T L

1991-12-01

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

Selective Attention in Vision: Recognition Memory for Superimposed Line Drawings.

ERIC Educational Resources Information Center

Goldstein, E. Bruce; Fink, Susan I.

1981-01-01

Four experiments show that observers can selectively attend to one of two stationary superimposed pictures. Selective recognition occurred with large displays in which observers were free to make eye movements during a 3-sec exposure and with small displays in which observers were instructed to fixate steadily on a point. (Author/RD)

Face recognition algorithm based on Gabor wavelet and locality preserving projections

NASA Astrophysics Data System (ADS)

Liu, Xiaojie; Shen, Lin; Fan, Honghui

2017-07-01

In order to solve the effects of illumination changes and differences of personal features on the face recognition rate, this paper presents a new face recognition algorithm based on Gabor wavelet and Locality Preserving Projections (LPP). The problem of the Gabor filter banks with high dimensions was solved effectively, and also the shortcoming of the LPP on the light illumination changes was overcome. Firstly, the features of global image information were achieved, which used the good spatial locality and orientation selectivity of Gabor wavelet filters. Then the dimensions were reduced by utilizing the LPP, which well-preserved the local information of the image. The experimental results shown that this algorithm can effectively extract the features relating to facial expressions, attitude and other information. Besides, it can reduce influence of the illumination changes and the differences in personal features effectively, which improves the face recognition rate to 99.2%.

Recognizing What Matters: Value Improves Recognition by Selectively Enhancing Recollection

PubMed Central

Hennessee, Joseph P.; Castel, Alan D.; Knowlton, Barbara J.

2017-01-01

We examined the effects of value on recognition by assessing its contribution to recollection and familiarity. In three experiments, participants studied English words, each associated with a point-value they would earn for correct recognition, with the goal of maximizing their score. In Experiment 1, participants provided Remember/Know judgments. In Experiment 2 participants indicated whether items were recollected or if not, their degree of familiarity along a 6-point scale. In Experiment 3, recognition of words was accompanied by a test of memory for incidental details. Across all experiments, participants were more likely to recognize items with higher point-value. Furthermore, value appeared to primarily enhance recollection, as effects on familiarity were small and not consistent across experiments. Recollection of high-value items appears to be accompanied by fewer incidental details, suggesting that value increases focus on items at the expense of irrelevant information. PMID:28827894

Fuzzy support vector machines for adaptive Morse code recognition.

PubMed

Yang, Cheng-Hong; Jin, Li-Cheng; Chuang, Li-Yeh

2006-11-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, facilitating mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. Therefore, an adaptive automatic recognition method with a high recognition rate is needed. The proposed system uses both fuzzy support vector machines and the variable-degree variable-step-size least-mean-square algorithm to achieve these objectives. We apply fuzzy memberships to each point, and provide different contributions to the decision learning function for support vector machines. Statistical analyses demonstrated that the proposed method elicited a higher recognition rate than other algorithms in the literature.

Breaking cover: neural responses to slow and fast camouflage-breaking motion.

PubMed

Yin, Jiapeng; Gong, Hongliang; An, Xu; Chen, Zheyuan; Lu, Yiliang; Andolina, Ian M; McLoughlin, Niall; Wang, Wei

2015-08-22

Primates need to detect and recognize camouflaged animals in natural environments. Camouflage-breaking movements are often the only visual cue available to accomplish this. Specifically, sudden movements are often detected before full recognition of the camouflaged animal is made, suggesting that initial processing of motion precedes the recognition of motion-defined contours or shapes. What are the neuronal mechanisms underlying this initial processing of camouflaged motion in the primate visual brain? We investigated this question using intrinsic-signal optical imaging of macaque V1, V2 and V4, along with computer simulations of the neural population responses. We found that camouflaged motion at low speed was processed as a direction signal by both direction- and orientation-selective neurons, whereas at high-speed camouflaged motion was encoded as a motion-streak signal primarily by orientation-selective neurons. No population responses were found to be invariant to the camouflage contours. These results suggest that the initial processing of camouflaged motion at low and high speeds is encoded as direction and motion-streak signals in primate early visual cortices. These processes are consistent with a spatio-temporal filter mechanism that provides for fast processing of motion signals, prior to full recognition of camouflage-breaking animals. © 2015 The Authors.

Breaking cover: neural responses to slow and fast camouflage-breaking motion

PubMed Central

Yin, Jiapeng; Gong, Hongliang; An, Xu; Chen, Zheyuan; Lu, Yiliang; Andolina, Ian M.; McLoughlin, Niall; Wang, Wei

2015-01-01

Primates need to detect and recognize camouflaged animals in natural environments. Camouflage-breaking movements are often the only visual cue available to accomplish this. Specifically, sudden movements are often detected before full recognition of the camouflaged animal is made, suggesting that initial processing of motion precedes the recognition of motion-defined contours or shapes. What are the neuronal mechanisms underlying this initial processing of camouflaged motion in the primate visual brain? We investigated this question using intrinsic-signal optical imaging of macaque V1, V2 and V4, along with computer simulations of the neural population responses. We found that camouflaged motion at low speed was processed as a direction signal by both direction- and orientation-selective neurons, whereas at high-speed camouflaged motion was encoded as a motion-streak signal primarily by orientation-selective neurons. No population responses were found to be invariant to the camouflage contours. These results suggest that the initial processing of camouflaged motion at low and high speeds is encoded as direction and motion-streak signals in primate early visual cortices. These processes are consistent with a spatio-temporal filter mechanism that provides for fast processing of motion signals, prior to full recognition of camouflage-breaking animals. PMID:26269500

The re-emergence of felid camouflage with the decay of predator recognition in deer under relaxed selection

PubMed Central

Stankowich, Theodore; Coss, Richard G

2006-01-01

When a previously common predator disappears owing to local extinction, the strong source of natural selection on prey to visually recognize that predator becomes relaxed. At present, we do not know the extent to which recognition of a specific predator is generalized to similar looking predators or how a specific predator-recognition cue, such as coat pattern, degrades under prolonged relaxed selection. Using predator models, we show that deer exhibit a more rapid and stronger antipredator response to their current predator, the puma, than to a leopard displaying primitive rosettes similar to a locally extinct predator, an early jaguar. Presentation of a novel tiger with a striped coat engendered an intermediate speed of predator recognition and strength of antipredator behaviour. Responses to the leopard model slightly exceeded responses to a non-threatening deer model, suggesting that thousands of years of relaxed selection have led to the loss of recognition of the spotted coat as a jaguar-recognition cue, and that the spotted coat has regained its ability to camouflage the felid form. Our results shed light on the evolutionary arms race between adoption of camouflage to facilitate hunting and the ability of prey to quickly recognize predators by their formerly camouflaging patterns. PMID:17148247

Process analysis of recycled thermoplasts from consumer electronics by laser-induced plasma spectroscopy.

PubMed

Fink, Herbert; Panne, Ulrich; Niessner, Reinhard

2002-09-01

An experimental setup for direct elemental analysis of recycled thermoplasts from consumer electronics by laser-induced plasma spectroscopy (LIPS, or laser-induced breakdown spectroscopy, LIBS) was realized. The combination of a echelle spectrograph, featuring a high resolution with a broad spectral coverage, with multivariate methods, such as PLS, PCR, and variable subset selection via a genetic algorithm, resulted in considerable improvements in selectivity and sensitivity for this complex matrix. With a normalization to carbon as internal standard, the limits of detection were in the ppm range. A preliminary pattern recognition study points to the possibility of polymer recognition via the line-rich echelle spectra. Several experiments at an extruder within a recycling plant demonstrated successfully the capability of LIPS for different kinds of routine on-line process analysis.

The Fisher-Markov selector: fast selecting maximally separable feature subset for multiclass classification with applications to high-dimensional data.

PubMed

Cheng, Qiang; Zhou, Hongbo; Cheng, Jie

2011-06-01

Selecting features for multiclass classification is a critically important task for pattern recognition and machine learning applications. Especially challenging is selecting an optimal subset of features from high-dimensional data, which typically have many more variables than observations and contain significant noise, missing components, or outliers. Existing methods either cannot handle high-dimensional data efficiently or scalably, or can only obtain local optimum instead of global optimum. Toward the selection of the globally optimal subset of features efficiently, we introduce a new selector--which we call the Fisher-Markov selector--to identify those features that are the most useful in describing essential differences among the possible groups. In particular, in this paper we present a way to represent essential discriminating characteristics together with the sparsity as an optimization objective. With properly identified measures for the sparseness and discriminativeness in possibly high-dimensional settings, we take a systematic approach for optimizing the measures to choose the best feature subset. We use Markov random field optimization techniques to solve the formulated objective functions for simultaneous feature selection. Our results are noncombinatorial, and they can achieve the exact global optimum of the objective function for some special kernels. The method is fast; in particular, it can be linear in the number of features and quadratic in the number of observations. We apply our procedure to a variety of real-world data, including mid--dimensional optical handwritten digit data set and high-dimensional microarray gene expression data sets. The effectiveness of our method is confirmed by experimental results. In pattern recognition and from a model selection viewpoint, our procedure says that it is possible to select the most discriminating subset of variables by solving a very simple unconstrained objective function which in fact can be obtained with an explicit expression.

Object recognition with hierarchical discriminant saliency networks.

PubMed

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 computer vision literatures. This demonstrates benefits for all the functional enhancements of the HDSN, the class tuning inherent to discriminant saliency, and saliency layers based on templates of increasing target selectivity and invariance. Altogether, these experiments suggest that there are non-trivial benefits in integrating attention and recognition.

Temporal voice areas exist in autism spectrum disorder but are dysfunctional for voice identity recognition

PubMed Central

Borowiak, Kamila; von Kriegstein, Katharina

2016-01-01

The ability to recognise the identity of others is a key requirement for successful communication. Brain regions that respond selectively to voices exist in humans from early infancy on. Currently, it is unclear whether dysfunction of these voice-sensitive regions can explain voice identity recognition impairments. Here, we used two independent functional magnetic resonance imaging studies to investigate voice processing in a population that has been reported to have no voice-sensitive regions: autism spectrum disorder (ASD). Our results refute the earlier report that individuals with ASD have no responses in voice-sensitive regions: Passive listening to vocal, compared to non-vocal, sounds elicited typical responses in voice-sensitive regions in the high-functioning ASD group and controls. In contrast, the ASD group had a dysfunction in voice-sensitive regions during voice identity but not speech recognition in the right posterior superior temporal sulcus/gyrus (STS/STG)—a region implicated in processing complex spectrotemporal voice features and unfamiliar voices. The right anterior STS/STG correlated with voice identity recognition performance in controls but not in the ASD group. The findings suggest that right STS/STG dysfunction is critical for explaining voice recognition impairments in high-functioning ASD and show that ASD is not characterised by a general lack of voice-sensitive responses. PMID:27369067

Recognition of Time-Compressed and Natural Speech with Selective Temporal Enhancements by Young and Elderly Listeners

ERIC Educational Resources Information Center

Gordon-Salant, Sandra; Fitzgibbons, Peter J.; Friedman, Sarah A.

2007-01-01

Purpose: The goal of this experiment was to determine whether selective slowing of speech segments improves recognition performance by young and elderly listeners. The hypotheses were (a) the benefits of time expansion occur for rapid speech but not for natural-rate speech, (b) selective time expansion of consonants produces greater score…

A new molecularly imprinted polymer (MIP)-based electrochemical sensor for monitoring 2,4,6-trinitrotoluene (TNT) in natural waters and soil samples.

PubMed

Alizadeh, Taher; Zare, Mashaalah; Ganjali, Mohamad Reza; Norouzi, Parviz; Tavana, Babak

2010-01-15

A high selective voltammetric sensor for 2,4,6-trinitrotoluene (TNT) was introduced. TNT selective MIP and non-imprinted polymer (NIP) were synthesized and then used for carbon paste (CP) electrode preparation. The MIP, incorporated in the carbon paste electrode, functioned as selectively recognition element and pre-concentrator agent for TNT determination. The prepared electrode was used for TNT measurement by the three steps procedure, including analyte extraction in the electrode, electrode washing and electrochemical measurement of TNT. The MIP-CP electrode showed very high recognition ability in comparison to NIP-CP. It was shown that electrode washing after TNT extraction led to enhanced selectivity. The response of square wave voltammetry for TNT determination by proposed electrode was higher than that of differential pulse voltammetry. Some parameters affecting sensor response were optimized and then a calibration curve plotted. A dynamic linear range of 5x10(-9) to 1x10(-6) mol l(-1) was obtained. The detection limit of the sensor was calculated equal to 1.5x10(-9) mol l(-1). This sensor was used successfully for TNT determination in different water and soil samples. Copyright 2009 Elsevier B.V. All rights reserved.

Colorimetric and fluorescent detection of hydrazine with high sensitivity and excellent selectivity

NASA Astrophysics Data System (ADS)

Shi, Bingjie; Qi, Sujie; Yu, Mingming; Liu, Chunxia; Li, Zhanxian; Wei, Liuhe; Ni, Zhonghai

2018-01-01

It is critical to develop probes for rapid, selective, and sensitive detection of the highly toxic hydrazine in both environmental and biological science. In this work, under mild condition, a novel colorimetric and off-on fluorescent probe was synthesized for rapid recognition of hydrazine with excellent selectivity over other various species including some biological species, metal ions and anions. The limit of quantification (LOQ) value was 1.5 × 10- 4 M-3.2 × 10- 3 M (colorimetric method) and 1.5 × 10- 4 M - 3.2 × 10- 3 M (fluorescent method) with as low as detection limit of 46.2 μM.

Infrared face recognition based on LBP histogram and KW feature selection

NASA Astrophysics Data System (ADS)

Xie, Zhihua

2014-07-01

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

Imaging Systems: What, When, How.

ERIC Educational Resources Information Center

Lunin, Lois F.; And Others

1992-01-01

The three articles in this special section on document image files discuss intelligent character recognition, including comparison with optical character recognition; selection of displays for document image processing, focusing on paperlike displays; and imaging hardware, software, and vendors, including guidelines for system selection. (MES)

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

PubMed

Fang, Hongqing; Chen, Long; Srinivasan, Raghavendiran

2014-01-01

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

The biometric-based module of smart grid system

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.

Biomimetic Strategies for Sensing Biological Species

PubMed Central

Hussain, Munawar; Wackerlig, Judith; Lieberzeit, Peter A.

2013-01-01

The starting point of modern biosensing was the application of actual biological species for recognition. Increasing understanding of the principles underlying such recognition (and biofunctionality in general), however, has triggered a dynamic field in chemistry and materials sciences that aims at joining the best of two worlds by combining concepts derived from nature with the processability of manmade materials, e.g., sensitivity and ruggedness. This review covers different biomimetic strategies leading to highly selective (bio)chemical sensors: the first section covers molecularly imprinted polymers (MIP) that attempt to generate a fully artificial, macromolecular mold of a species in order to detect it selectively. A different strategy comprises of devising polymer coatings to change the biocompatibility of surfaces that can also be used to immobilized natural receptors/ligands and thus stabilize them. Rationally speaking, this leads to self-assembled monolayers closely resembling cell membranes, sometimes also including bioreceptors. Finally, this review will highlight some approaches to generate artificial analogs of natural recognition materials and biomimetic approaches in nanotechnology. It mainly focuses on the literature published since 2005. PMID:25587400

Core List of Astronomy and Physics Journals

NASA Astrophysics Data System (ADS)

Bryson, Liz; Fortner, Diane; Yorks, Pamela

This is a list of highly-used and highly-cited physics and astronomy journals. "Use" is measured largely on paper-journal counts from selective academic research-level libraries. Citation count titles are drawn from Institute for Scientific Information (ISI) data. Recognition is given to entrepreneurial electronic-only or new-style electronic journals. Selective news, magazine, and general science journals are omitted. The compilers welcome questions, suggestions for additions, or other advice. Comments may be sent c/o Diane Fortner, Physics Library, University of California, Berkeley. Dfortner@library.berkeley.edu

Effects of cholinergic deafferentation of the rhinal cortex on visual recognition memory in monkeys.

PubMed

Turchi, Janita; Saunders, Richard C; Mishkin, Mortimer

2005-02-08

Excitotoxic lesion studies have confirmed that the rhinal cortex is essential for visual recognition ability in monkeys. To evaluate the mnemonic role of cholinergic inputs to this cortical region, we compared the visual recognition performance of monkeys given rhinal cortex infusions of a selective cholinergic immunotoxin, ME20.4-SAP, with the performance of monkeys given control infusions into this same tissue. The immunotoxin, which leads to selective cholinergic deafferentation of the infused cortex, yielded recognition deficits of the same magnitude as those produced by excitotoxic lesions of this region, providing the most direct demonstration to date that cholinergic activation of the rhinal cortex is essential for storing the representations of new visual stimuli and thereby enabling their later recognition.

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

NASA Astrophysics Data System (ADS)

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. These coordinators organize the program and provide continuity to the program. The success of UCICOP can be measured by the high praise and gratitude expressed by the teachers, students and volunteers.

The Gravity of High-Skilled Migration Policies.

PubMed

Czaika, Mathias; Parsons, Christopher R

2017-04-01

Combining unique, annual, bilateral data on labor flows of highly skilled immigrants for 10 OECD destinations between 2000 and 2012, with new databases comprising both unilateral and bilateral policy instruments, we present the first judicious cross-country assessment of policies aimed to attract and select high-skilled workers. Points-based systems are much more effective in attracting and selecting high-skilled migrants than requiring a job offer, labor market tests, and shortage lists. Offers of permanent residency, while attracting the highly skilled, overall reduce the human capital content of labor flows because they prove more attractive to non-high-skilled workers. Bilateral recognition of diploma and social security agreements foster greater flows of high-skilled workers and improve the skill selectivity of immigrant flows. Conversely, double taxation agreements deter high-skilled migrants, although they do not alter overall skill selectivity. Our results are robust to a variety of empirical specifications that account for destination-specific amenities, multilateral resistance to migration, and the endogeneity of immigration policies.

The hierarchical brain network for face recognition.

PubMed

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

Finding the Right Candidate for the Right Position: A Fast NMR-Assisted Combinatorial Method for Optimizing Nucleic Acids Binders.

PubMed

Jiménez-Moreno, Ester; Montalvillo-Jiménez, Laura; Santana, Andrés G; Gómez, Ana M; Jiménez-Osés, Gonzalo; Corzana, Francisco; Bastida, Agatha; Jiménez-Barbero, Jesús; Cañada, Francisco Javier; Gómez-Pinto, Irene; González, Carlos; Asensio, Juan Luis

2016-05-25

Development of strong and selective binders from promiscuous lead compounds represents one of the most expensive and time-consuming tasks in drug discovery. We herein present a novel fragment-based combinatorial strategy for the optimization of multivalent polyamine scaffolds as DNA/RNA ligands. Our protocol provides a quick access to a large variety of regioisomer libraries that can be tested for selective recognition by combining microdialysis assays with simple isotope labeling and NMR experiments. To illustrate our approach, 20 small libraries comprising 100 novel kanamycin-B derivatives have been prepared and evaluated for selective binding to the ribosomal decoding A-Site sequence. Contrary to the common view of NMR as a low-throughput technique, we demonstrate that our NMR methodology represents a valuable alternative for the detection and quantification of complex mixtures, even integrated by highly similar or structurally related derivatives, a common situation in the context of a lead optimization process. Furthermore, this study provides valuable clues about the structural requirements for selective A-site recognition.

Transfer Learning with Convolutional Neural Networks for SAR Ship Recognition

NASA Astrophysics Data System (ADS)

Zhang, Di; Liu, Jia; Heng, Wang; Ren, Kaijun; Song, Junqiang

2018-03-01

Ship recognition is the backbone of marine surveillance systems. Recent deep learning methods, e.g. Convolutional Neural Networks (CNNs), have shown high performance for optical images. Learning CNNs, however, requires a number of annotated samples to estimate numerous model parameters, which prevents its application to Synthetic Aperture Radar (SAR) images due to the limited annotated training samples. Transfer learning has been a promising technique for applications with limited data. To this end, a novel SAR ship recognition method based on CNNs with transfer learning has been developed. In this work, we firstly start with a CNNs model that has been trained in advance on Moving and Stationary Target Acquisition and Recognition (MSTAR) database. Next, based on the knowledge gained from this image recognition task, we fine-tune the CNNs on a new task to recognize three types of ships in the OpenSARShip database. The experimental results show that our proposed approach can obviously increase the recognition rate comparing with the result of merely applying CNNs. In addition, compared to existing methods, the proposed method proves to be very competitive and can learn discriminative features directly from training data instead of requiring pre-specification or pre-selection manually.

Transformed by Literacy

ERIC Educational Resources Information Center

Szachowicz, Susan

2010-01-01

When low test scores demanded a hard look at the curriculum, literacy became a focus for improvement at Brockton (MA) High School. Schoolwide training for teachers and a rolling implementation model ensured consistency and reinforcement of the skills. Results came in improved scores and national recognitions, including selection as a National…

A new N-imidazolyl-1,8-naphthalimide based fluorescence sensor for fluoride detection.

PubMed

Wang, Junqi; Yang, Lingyun; Hou, Chen; Cao, Haishi

2012-08-21

A chemosensor is reported with high sensitivity and selectivity for detection of fluoride anion. The recognition mechanism is attributed to a fluoride-triggered disruption of the hydrogen bond between imidazole and naphthalimide moieties, resulting in a noncoplanar geometry with low fluorescence.

Highly selective on-off fluorescence recognition of Fe3+ based on a coumarin derivative and its application in live-cell imaging

NASA Astrophysics Data System (ADS)

Warrier, Sona; Kharkar, Prashant S.

2018-01-01

A novel coumarin chemosensor, 7-hydroxy-2-oxo-N-(pyridin-2-ylmethyl)chromene-3-carboxamide (Probe 1), demonstrated significant selectivity towards Fe3+ ions. Probe 1 exhibited high fluorescence emission profile at 447 nm, excellent selectivity towards Fe3+ over other biologically important metal ions (Al3+, Ba2+, Co2+, Cu2+, Zn2+, Cd2+, Hg2+, Pb2+ and Sn2+). Interestingly, there was 30-fold decrease in fluorescence intensity upon Fe3+ binding. The limit of detection of Fe3+ was found to be 0.76 μM ( 40 ppb). Probe 1 also exhibited high potential as an intracellular chemosensor for Fe3+.

Computerized system for recognition of autism on the basis of gene expression microarray data.

PubMed

Latkowski, Tomasz; Osowski, Stanislaw

2015-01-01

The aim of this paper is to provide a means to recognize a case of autism using gene expression microarrays. The crucial task is to discover the most important genes which are strictly associated with autism. The paper presents an application of different methods of gene selection, to select the most representative input attributes for an ensemble of classifiers. The set of classifiers is responsible for distinguishing autism data from the reference class. Simultaneous application of a few gene selection methods enables analysis of the ill-conditioned gene expression matrix from different points of view. The results of selection combined with a genetic algorithm and SVM classifier have shown increased accuracy of autism recognition. Early recognition of autism is extremely important for treatment of children and increases the probability of their recovery and return to normal social communication. The results of this research can find practical application in early recognition of autism on the basis of gene expression microarray analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

In Vitro Selection of a Single-Stranded DNA Molecular Recognition Element against the Pesticide Fipronil and Sensitive Detection in River Water

PubMed Central

Sooter, Letha J.

2017-01-01

Fipronil is a commonly used insecticide that has been shown to have environmental and human health risks. The current standard methods of detection for fipronil and its metabolites, such as GC-MS, are time consuming and labor intensive. In this study, a variant of systematic evolution of ligands by exponential enrichment (SELEX), was utilized to identify the first single-stranded DNA (ssDNA) molecular recognition element (MRE) that binds to fipronil with high affinity (Kd = 48 ± 8 nM). The selected MRE displayed low cross binding activity on various environmentally relevant, structurally unrelated herbicides and pesticides, in addition to broad-spectrum binding activity on major metabolites of fipronil and a structurally similar pesticide in prepared river samples. Additionally, a proof-of-principle fluorescent detection assay was developed by using the selected ssDNA MRE as a signal-reporting element, with a limit of detection of 105 nM in a prepared river water sample. PMID:29283416

Modifying Memory: Selectively Enhancing and Updating Personal Memories for a Museum Tour by Reactivating Them

PubMed Central

St. Jacques, Peggy L.; Schacter, Daniel L.

2013-01-01

Memory can be modified when reactivated, but little is known about how the properties and extent of reactivation can selectively affect subsequent memory. We developed a novel museum paradigm to directly investigate reactivation-induced plasticity for personal memories. Participants reactivated memories triggered by photos taken from a camera they wore during a museum tour and made relatedness judgments on novel photos taken from a different tour of the same museum. Subsequent recognition memory for events at the museum was better for memories that were highly reactivated (i.e., the retrieval cues during reactivation matched the encoding experience) than for memories that were reactivated at a lower level (i.e., the retrieval cues during reactivation mismatched the encoding experience), but reactivation also increased false recognition of photographs depicting stops that were not experienced during the museum tour. Reactivation thus enables memories to be selectively enhanced and distorted via updating, thereby supporting the dynamic and flexible nature of memory. PMID:23406611

A light-up probe targeting for Bcl-2 2345 G-quadruplex DNA with carbazole TO

NASA Astrophysics Data System (ADS)

Gu, Yingchun; Lin, Dayong; Tang, Yalin; Fei, Xuening; Wang, Cuihong; Zhang, Baolian; Zhou, Jianguo

2018-02-01

As its significant role, the selective recognition of G-quadruplex with specific structures and functions is important in biological and medicinal chemistry. Carbazole derivatives have been reported as a kind of fluorescent probe with many excellent optical properties. In the present study, the fluorescence of the dye (carbazole TO) increased almost 70 fold in the presence of bcl-2 2345 G4 compared to that alone in aqueous buffer condition with almost no fluorescence and 10-30 fold than those in the presence of other DNAs. The binding study results by activity inhibition of G4/Hemin peroxidase experiment, NMR titration and molecular docking simulation showed the high affinity and selectivity to bcl-2 2345 G4 arises from its end-stacking interaction with G-quartet. It is said that a facile approach with excellent sensitive, good selectivity and quick response for bcl-2 2345 G-quadruplex was developed and may be used for antitumor recognition or antitumor agents.

Aging selectively impairs recollection in recognition memory for pictures: Evidence from modeling and ROC curves

PubMed Central

Howard, Marc W.; Bessette-Symons, Brandy; Zhang, Yaofei; Hoyer, William J.

2006-01-01

Younger and older adults were tested on recognition memory for pictures. The Yonelinas high threshold (YHT) model, a formal implementation of two-process theory, fit the response distribution data of both younger and older adults significantly better than a normal unequal variance signal detection model. Consistent with this finding, non-linear zROC curves were obtained for both groups. Estimates of recollection from the YHT model were significantly higher for younger than older adults. This deficit was not a consequence of a general decline in memory; older adults showed comparable overall accuracy and in fact a non-significant increase in their familiarity scores. Implications of these results for theories of recognition memory and the mnemonic deficit associated with aging are discussed. PMID:16594795

A Fault Recognition System for Gearboxes of Wind Turbines

NASA Astrophysics Data System (ADS)

Yang, Zhiling; Huang, Haiyue; Yin, Zidong

2017-12-01

Costs of maintenance and loss of power generation caused by the faults of wind turbines gearboxes are the main components of operation costs for a wind farm. Therefore, the technology of condition monitoring and fault recognition for wind turbines gearboxes is becoming a hot topic. A condition monitoring and fault recognition system (CMFRS) is presented for CBM of wind turbines gearboxes in this paper. The vibration signals from acceleration sensors at different locations of gearbox and the data from supervisory control and data acquisition (SCADA) system are collected to CMFRS. Then the feature extraction and optimization algorithm is applied to these operational data. Furthermore, to recognize the fault of gearboxes, the GSO-LSSVR algorithm is proposed, combining the least squares support vector regression machine (LSSVR) with the Glowworm Swarm Optimization (GSO) algorithm. Finally, the results show that the fault recognition system used in this paper has a high rate for identifying three states of wind turbines’ gears; besides, the combination of date features can affect the identifying rate and the selection optimization algorithm presented in this paper can get a pretty good date feature subset for the fault recognition.

Speaker-independent phoneme recognition with a binaural auditory image model

NASA Astrophysics Data System (ADS)

Francis, Keith Ivan

1997-09-01

This dissertation presents phoneme recognition techniques based on a binaural fusion of outputs of the auditory image model and subsequent azimuth-selective phoneme recognition in a noisy environment. Background information concerning speech variations, phoneme recognition, current binaural fusion techniques and auditory modeling issues is explained. The research is constrained to sources in the frontal azimuthal plane of a simulated listener. A new method based on coincidence detection of neural activity patterns from the auditory image model of Patterson is used for azimuth-selective phoneme recognition. The method is tested in various levels of noise and the results are reported in contrast to binaural fusion methods based on various forms of correlation to demonstrate the potential of coincidence- based binaural phoneme recognition. This method overcomes smearing of fine speech detail typical of correlation based methods. Nevertheless, coincidence is able to measure similarity of left and right inputs and fuse them into useful feature vectors for phoneme recognition in noise.

Understanding gender bias in face recognition: effects of divided attention at encoding.

PubMed

Palmer, Matthew A; Brewer, Neil; Horry, Ruth

2013-03-01

Prior research has demonstrated a female own-gender bias in face recognition, with females better at recognizing female faces than male faces. We explored the basis for this effect by examining the effect of divided attention during encoding on females' and males' recognition of female and male faces. For female participants, divided attention impaired recognition performance for female faces to a greater extent than male faces in a face recognition paradigm (Study 1; N=113) and an eyewitness identification paradigm (Study 2; N=502). Analysis of remember-know judgments (Study 2) indicated that divided attention at encoding selectively reduced female participants' recollection of female faces at test. For male participants, divided attention selectively reduced recognition performance (and recollection) for male stimuli in Study 2, but had similar effects on recognition of male and female faces in Study 1. Overall, the results suggest that attention at encoding contributes to the female own-gender bias by facilitating the later recollection of female faces. Copyright © 2013 Elsevier B.V. All rights reserved.

Probing ligand recognition of the opioid pan antagonist AT-076 at nociceptin, kappa, mu, and delta opioid receptors through structure-activity relationships.

PubMed

Journigan, V Blair; Polgar, Willma E; Tuan, Edward W; Lu, James; Daga, Pankaj R; Zaveri, Nurulain T

2017-10-16

Few opioid ligands binding to the three classic opioid receptor subtypes, mu, kappa and delta, have high affinity at the fourth opioid receptor, the nociceptin/orphanin FQ receptor (NOP). We recently reported the discovery of AT-076 (1), (R)-7-hydroxy-N-((S)-1-(4-(3-hydroxyphenyl)piperidin-1-yl)-3-methylbutan-2-yl)-1,2,3,4-tetrahydroisoquinoline-3-carboxamide, a pan antagonist with nanomolar affinity for all four subtypes. Since AT-076 binds with high affinity at all four subtypes, we conducted a structure-activity relationship (SAR) study to probe ligand recognition features important for pan opioid receptor activity, using chemical modifications of key pharmacophoric groups. SAR analysis of the resulting analogs suggests that for the NOP receptor, the entire AT-076 scaffold is crucial for high binding affinity, but the binding mode is likely different from that of NOP antagonists C-24 and SB-612111 bound in the NOP crystal structure. On the other hand, modifications of the 3-hydroxyphenyl pharmacophore, but not the 7-hydroxy Tic pharmacophore, are better tolerated at kappa and mu receptors and yield very high affinity multifunctional (e.g. 12) or highly selective (e.g. 16) kappa ligands. With the availability of the opioid receptor crystal structures, our SAR analysis of the common chemotype of AT-076 suggests rational approaches to modulate binding selectivity, enabling the design of multifunctional or selective opioid ligands from such scaffolds.

Road sign recognition with fuzzy adaptive pre-processing models.

PubMed

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

PubMed Central

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

Is the emotion recognition deficit associated with frontotemporal dementia caused by selective inattention to diagnostic facial features?

PubMed

Oliver, Lindsay D; Virani, Karim; Finger, Elizabeth C; Mitchell, Derek G V

2014-07-01

Frontotemporal dementia (FTD) is a debilitating neurodegenerative disorder characterized by severely impaired social and emotional behaviour, including emotion recognition deficits. Though fear recognition impairments seen in particular neurological and developmental disorders can be ameliorated by reallocating attention to critical facial features, the possibility that similar benefits can be conferred to patients with FTD has yet to be explored. In the current study, we examined the impact of presenting distinct regions of the face (whole face, eyes-only, and eyes-removed) on the ability to recognize expressions of anger, fear, disgust, and happiness in 24 patients with FTD and 24 healthy controls. A recognition deficit was demonstrated across emotions by patients with FTD relative to controls. Crucially, removal of diagnostic facial features resulted in an appropriate decline in performance for both groups; furthermore, patients with FTD demonstrated a lack of disproportionate improvement in emotion recognition accuracy as a result of isolating critical facial features relative to controls. Thus, unlike some neurological and developmental disorders featuring amygdala dysfunction, the emotion recognition deficit observed in FTD is not likely driven by selective inattention to critical facial features. Patients with FTD also mislabelled negative facial expressions as happy more often than controls, providing further evidence for abnormalities in the representation of positive affect in FTD. This work suggests that the emotional expression recognition deficit associated with FTD is unlikely to be rectified by adjusting selective attention to diagnostic features, as has proven useful in other select disorders. Copyright © 2014 Elsevier Ltd. All rights reserved.

Molecular recognition at adenine nucleotide (P2) receptors in platelets.

PubMed

Jacobson, Kenneth A; Mamedova, Liaman; Joshi, Bhalchandra V; Besada, Pedro; Costanzi, Stefano

2005-04-01

Transmembrane signaling through P2Y receptors for extracellular nucleotides controls a diverse array of cellular processes, including thrombosis. Selective agonists and antagonists of the two P2Y receptors present on the platelet surface-the G (q)-coupled P2Y (1) subtype and the G (i)-coupled P2Y (12) subtype-are now known. High-affinity antagonists of each have been developed from nucleotide structures. The (N)-methanocarba bisphosphate derivatives MRS2279 and MRS2500 are potent and selective P2Y (1) receptor antagonists. The carbocyclic nucleoside AZD6140 is an uncharged, orally active P2Y (12) receptor antagonist of nM affinity. Another nucleotide receptor on the platelet surface, the P2X (1) receptor, the activation of which may also be proaggregatory, especially under conditions of high shear stress, has high-affinity ligands, although high selectivity has not yet been achieved. Although alpha,beta-methylene-adenosine triphosphate (ATP) is the classic agonist for the P2X (1) receptor, where it causes rapid desensitization, the agonist BzATP is among the most potent in activating this subtype. The aromatic sulfonates NF279 and NF449 are potent antagonists of the P2X (1) receptor. The structures of the two platelet P2Y receptors have been modeled, based on a rhodopsin template, to explain the basis for nucleotide recognition within the putative transmembrane binding sites. The P2Y (1) receptor model, especially, has been exploited in the design and optimization of antagonists targeted to interact selectively with that subtype.

Déjà vu in unilateral temporal-lobe epilepsy is associated with selective familiarity impairments on experimental tasks of recognition memory.

PubMed

Martin, Chris B; Mirsattari, Seyed M; Pruessner, Jens C; Pietrantonio, Sandra; Burneo, Jorge G; Hayman-Abello, Brent; Köhler, Stefan

2012-11-01

In déjà vu, a phenomenological impression of familiarity for the current visual environment is experienced with a sense that it should in fact not feel familiar. The fleeting nature of this phenomenon in daily life, and the difficulty in developing experimental paradigms to elicit it, has hindered progress in understanding déjà vu. Some neurological patients with temporal-lobe epilepsy (TLE) consistently experience déjà vu at the onset of their seizures. An investigation of such patients offers a unique opportunity to shed light on its possible underlying mechanisms. In the present study, we sought to determine whether unilateral TLE patients with déjà vu (TLE+) show a unique pattern of interictal memory deficits that selectively affect familiarity assessment. In Experiment 1, we employed a Remember-Know paradigm for categorized visual scenes and found evidence for impairments that were limited to familiarity-based responses. In Experiment 2, we administered an exclusion task for highly similar categorized visual scenes that placed both recognition processes in opposition. TLE+ patients again displayed recognition impairments, and these impairments spared their ability to engage recollective processes so as to counteract familiarity. The selective deficits we observed in TLE+ patients contrasted with the broader pattern of recognition-memory impairments that was present in a control group of unilateral patients without déjà vu (TLE-). MRI volumetry revealed that ipsilateral medial temporal structures were less broadly affected in TLE+ than in TLE- patients, with a trend for more focal volume reductions in the rhinal cortices of the TLE+ group. The current findings establish a first empirical link between déjà vu in TLE and processes of familiarity assessment, as defined and measured in current cognitive models. They also reveal a pattern of selectivity in recognition impairments that is rarely observed and, thus, of significant theoretical interest to the memory literature at large. Copyright © 2012 Elsevier Ltd. All rights reserved.

Good Practices for Learning to Recognize Actions Using FV and VLAD.

PubMed

Wu, Jianxin; Zhang, Yu; Lin, Weiyao

2016-12-01

High dimensional representations such as Fisher vectors (FV) and vectors of locally aggregated descriptors (VLAD) have shown state-of-the-art accuracy for action recognition in videos. The high dimensionality, on the other hand, also causes computational difficulties when scaling up to large-scale video data. This paper makes three lines of contributions to learning to recognize actions using high dimensional representations. First, we reviewed several existing techniques that improve upon FV or VLAD in image classification, and performed extensive empirical evaluations to assess their applicability for action recognition. Our analyses of these empirical results show that normality and bimodality are essential to achieve high accuracy. Second, we proposed a new pooling strategy for VLAD and three simple, efficient, and effective transformations for both FV and VLAD. Both proposed methods have shown higher accuracy than the original FV/VLAD method in extensive evaluations. Third, we proposed and evaluated new feature selection and compression methods for the FV and VLAD representations. This strategy uses only 4% of the storage of the original representation, but achieves comparable or even higher accuracy. Based on these contributions, we recommend a set of good practices for action recognition in videos for practitioners in this field.

Molecular recognition of organic ammonium ions in solution using synthetic receptors

PubMed Central

Späth, Andreas

2010-01-01

Summary Ammonium ions are ubiquitous in chemistry and molecular biology. Considerable efforts have been undertaken to develop synthetic receptors for their selective molecular recognition. The type of host compounds for organic ammonium ion binding span a wide range from crown ethers to calixarenes to metal complexes. Typical intermolecular interactions are hydrogen bonds, electrostatic and cation–π interactions, hydrophobic interactions or reversible covalent bond formation. In this review we discuss the different classes of synthetic receptors for organic ammonium ion recognition and illustrate the scope and limitations of each class with selected examples from the recent literature. The molecular recognition of ammonium ions in amino acids is included and the enantioselective binding of chiral ammonium ions by synthetic receptors is also covered. In our conclusion we compare the strengths and weaknesses of the different types of ammonium ion receptors which may help to select the best approach for specific applications. PMID:20502608

Recognition of facial emotions in neuropsychiatric disorders.

PubMed

Kohler, Christian G; Turner, Travis H; Gur, Raquel E; Gur, Ruben C

2004-04-01

Recognition of facial emotions represents an important aspect of interpersonal communication and is governed by select neural substrates. We present data on emotion recognition in healthy young adults utilizing a novel set of color photographs of evoked universal emotions. In addition, we review the recent literature on emotion recognition in psychiatric and neurologic disorders, and studies that compare different disorders.

Witnesses' blindness for their own facial recognition decisions: a field study.

PubMed

Sagana, Anna; Sauerland, Melanie; Merckelbach, Harald

2013-01-01

In a field study, we examined choice blindness for eyewitnesses' facial recognition decisions. Seventy-one pedestrians were engaged in a conversation by two experimenters who pretended to be tourists in the center of a European city. After a short interval, pedestrians were asked to identify the two experimenters from separate simultaneous six-person photo lineups. Following each of the two forced-choice recognition decisions, they were confronted with their selection and asked to motivate their decision. However, for one of the recognition decisions, the chosen lineup member was exchanged with a previously unidentified member. Blindness for this identity manipulation occurred at the rate of 40.8%. Furthermore, the detection rate varied as a function of similarity (high vs. low) between the original choice and the manipulated outcome. Finally, choice manipulations undermined the confidence-accuracy relation for detectors to a greater degree than for blind participants. Stimulus ambiguity is discussed as a moderator of choice blindness. Copyright © 2013 John Wiley & Sons, Ltd.

Selective visual attention and motivation: the consequences of value learning in an attentional blink task.

PubMed

Raymond, Jane E; O'Brien, Jennifer L

2009-08-01

Learning to associate the probability and value of behavioral outcomes with specific stimuli (value learning) is essential for rational decision making. However, in demanding cognitive conditions, access to learned values might be constrained by limited attentional capacity. We measured recognition of briefly presented faces seen previously in a value-learning task involving monetary wins and losses; the recognition task was performed both with and without constraints on available attention. Regardless of available attention, recognition was substantially enhanced for motivationally salient stimuli (i.e., stimuli highly predictive of outcomes), compared with equally familiar stimuli that had weak or no motivational salience, and this effect was found regardless of valence (win or loss). However, when attention was constrained (because stimuli were presented during an attentional blink, AB), valence determined recognition; win-associated faces showed no AB, but all other faces showed large ABs. Motivational salience acts independently of attention to modulate simple perceptual decisions, but when attention is limited, visual processing is biased in favor of reward-associated stimuli.

The Hierarchical Brain Network for Face Recognition

PubMed Central

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level. PMID:23527282

Ordinal feature selection for iris and palmprint recognition.

PubMed

Sun, Zhenan; Wang, Libin; Tan, Tieniu

2014-09-01

Ordinal measures have been demonstrated as an effective feature representation model for iris and palmprint recognition. However, ordinal measures are a general concept of image analysis and numerous variants with different parameter settings, such as location, scale, orientation, and so on, can be derived to construct a huge feature space. This paper proposes a novel optimization formulation for ordinal feature selection with successful applications to both iris and palmprint recognition. The objective function of the proposed feature selection method has two parts, i.e., misclassification error of intra and interclass matching samples and weighted sparsity of ordinal feature descriptors. Therefore, the feature selection aims to achieve an accurate and sparse representation of ordinal measures. And, the optimization subjects to a number of linear inequality constraints, which require that all intra and interclass matching pairs are well separated with a large margin. Ordinal feature selection is formulated as a linear programming (LP) problem so that a solution can be efficiently obtained even on a large-scale feature pool and training database. Extensive experimental results demonstrate that the proposed LP formulation is advantageous over existing feature selection methods, such as mRMR, ReliefF, Boosting, and Lasso for biometric recognition, reporting state-of-the-art accuracy on CASIA and PolyU databases.

Feature Selection for Speech Emotion Recognition in Spanish and Basque: On the Use of Machine Learning to Improve Human-Computer Interaction

PubMed Central

Arruti, Andoni; Cearreta, Idoia; Álvarez, Aitor; Lazkano, Elena; Sierra, Basilio

2014-01-01

Study of emotions in human–computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested. PMID:25279686

Differential effects of m1 and m2 receptor antagonists in perirhinal cortex on visual recognition memory in monkeys

PubMed Central

Wu, Wei; Saunders, Richard C.; Mishkin, Mortimer; Turchi, Janita

2012-01-01

Microinfusions of the nonselective muscarinic antagonist scopolamine into perirhinal cortex impairs performance on visual recognition tasks, indicating that muscarinic receptors in this region play a pivotal role in recognition memory. To assess the mnemonic effects of selective blockade in perirhinal cortex of muscarinic receptor subtypes, we locally infused either the m1-selective antagonist pirenzepine or the m2-selective antagonist methoctramine in animals performing one-trial visual recognition, and compared these scores with those following infusions of equivalent volumes of saline. Compared to these control infusions, injections of pirenzepine, but not of methoctramine, significantly impaired recognition accuracy. Further, similar doses of scopolamine and pirenzepine yielded similar deficits, suggesting that the deficits obtained earlier with scopolamine were due mainly, if not exclusively, to blockade of m1 receptors. The present findings indicate that m1 and m2 receptors have functionally dissociable roles, and that the formation of new visual memories is critically dependent on the cholinergic activation of m1 receptors located on perirhinal cells. PMID:22561485

Differential effects of m1 and m2 receptor antagonists in perirhinal cortex on visual recognition memory in monkeys.

PubMed

Wu, Wei; Saunders, Richard C; Mishkin, Mortimer; Turchi, Janita

2012-07-01

Microinfusions of the nonselective muscarinic antagonist scopolamine into perirhinal cortex impairs performance on visual recognition tasks, indicating that muscarinic receptors in this region play a pivotal role in recognition memory. To assess the mnemonic effects of selective blockade in perirhinal cortex of muscarinic receptor subtypes, we locally infused either the m1-selective antagonist pirenzepine or the m2-selective antagonist methoctramine in animals performing one-trial visual recognition, and compared these scores with those following infusions of equivalent volumes of saline. Compared to these control infusions, injections of pirenzepine, but not of methoctramine, significantly impaired recognition accuracy. Further, similar doses of scopolamine and pirenzepine yielded similar deficits, suggesting that the deficits obtained earlier with scopolamine were due mainly, if not exclusively, to blockade of m1 receptors. The present findings indicate that m1 and m2 receptors have functionally dissociable roles, and that the formation of new visual memories is critically dependent on the cholinergic activation of m1 receptors located on perirhinal cells. Published by Elsevier Inc.

Aptamer Recognition of Multiplexed Small-Molecule-Functionalized Substrates.

PubMed

Nakatsuka, Nako; Cao, Huan H; Deshayes, Stephanie; Melkonian, Arin Lucy; Kasko, Andrea M; Weiss, Paul S; Andrews, Anne M

2018-05-31

Aptamers are chemically synthesized oligonucleotides or peptides with molecular recognition capabilities. We investigated recognition of substrate-tethered small-molecule targets, using neurotransmitters as examples, and fluorescently labeled DNA aptamers. Substrate regions patterned via microfluidic channels with dopamine or L-tryptophan were selectively recognized by previously identified dopamine or L-tryptophan aptamers, respectively. The on-substrate dissociation constant determined for the dopamine aptamer was comparable to, though slightly greater than the previously determined solution dissociation constant. Using pre-functionalized neurotransmitter-conjugated oligo(ethylene glycol) alkanethiols and microfluidics patterning, we produced multiplexed substrates to capture and to sort aptamers. Substrates patterned with L-DOPA, L-DOPS, and L-5-HTP enabled comparison of the selectivity of the dopamine aptamer for different targets via simultaneous determination of in situ binding constants. Thus, beyond our previous demonstrations of recognition by protein binding partners (i.e., antibodies and G-protein-coupled receptors), strategically optimized small-molecule-functionalized substrates show selective recognition of nucleic acid binding partners. These substrates are useful for side-by-side target comparisons, and future identification and characterization of novel aptamers targeting neurotransmitters or other important small-molecules.

A computational method for selecting short peptide sequences for inorganic material binding.

PubMed

Nayebi, Niloofar; Cetinel, Sibel; Omar, Sara Ibrahim; Tuszynski, Jack A; Montemagno, Carlo

2017-11-01

Discovering or designing biofunctionalized materials with improved quality highly depends on the ability to manipulate and control the peptide-inorganic interaction. Various peptides can be used as assemblers, synthesizers, and linkers in the material syntheses. In another context, specific and selective material-binding peptides can be used as recognition blocks in mining applications. In this study, we propose a new in silico method to select short 4-mer peptides with high affinity and selectivity for a given target material. This method is illustrated with the calcite (104) surface as an example, which has been experimentally validated. A calcite binding peptide can play an important role in our understanding of biomineralization. A practical aspect of calcite is a need for it to be selectively depressed in mining sites. © 2017 Wiley Periodicals, Inc.

Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

PubMed Central

Zhao, Yu-Xiang; Chou, Chien-Hsing

2016-01-01

In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters. PMID:27314346

Highly selective on-off fluorescence recognition of Fe3+ based on a coumarin derivative and its application in live-cell imaging.

PubMed

Warrier, Sona; Kharkar, Prashant S

2018-01-05

A novel coumarin chemosensor, 7-hydroxy-2-oxo-N-(pyridin-2-ylmethyl)chromene-3-carboxamide (Probe 1), demonstrated significant selectivity towards Fe 3+ ions. Probe 1 exhibited high fluorescence emission profile at 447nm, excellent selectivity towards Fe 3+ over other biologically important metal ions (Al 3+ , Ba 2+ , Co 2+ , Cu 2+ , Zn 2+ , Cd 2+ , Hg 2+ , Pb 2+ and Sn 2+ ). Interestingly, there was ~30-fold decrease in fluorescence intensity upon Fe 3+ binding. The limit of detection of Fe 3+ was found to be 0.76μM (~40ppb). Probe 1 also exhibited high potential as an intracellular chemosensor for Fe 3+ . Copyright © 2017 Elsevier B.V. All rights reserved.

A new selective developmental deficit: Impaired object recognition with normal face recognition.

PubMed

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 recognition. Copyright © 2010 Elsevier Srl. All rights reserved.

Attention and memory bias to facial emotions underlying negative symptoms of schizophrenia.

PubMed

Jang, Seon-Kyeong; Park, Seon-Cheol; Lee, Seung-Hwan; Cho, Yang Seok; Choi, Kee-Hong

2016-01-01

This study assessed bias in selective attention to facial emotions in negative symptoms of schizophrenia and its influence on subsequent memory for facial emotions. Thirty people with schizophrenia who had high and low levels of negative symptoms (n = 15, respectively) and 21 healthy controls completed a visual probe detection task investigating selective attention bias (happy, sad, and angry faces randomly presented for 50, 500, or 1000 ms). A yes/no incidental facial memory task was then completed. Attention bias scores and recognition errors were calculated. Those with high negative symptoms exhibited reduced attention to emotional faces relative to neutral faces; those with low negative symptoms showed the opposite pattern when faces were presented for 500 ms regardless of the valence. Compared to healthy controls, those with high negative symptoms made more errors for happy faces in the memory task. Reduced attention to emotional faces in the probe detection task was significantly associated with less pleasure and motivation and more recognition errors for happy faces in schizophrenia group only. Attention bias away from emotional information relatively early in the attentional process and associated diminished positive memory may relate to pathological mechanisms for negative symptoms.

Beyond the Memory Mechanism: Person-Selective and Nonselective Processes in Recognition of Personally Familiar Faces

ERIC Educational Resources Information Center

Sugiura, Motoaki; Mano, Yoko; Sasaki, Akihiro; Sadato, Norihiro

2011-01-01

Special processes recruited during the recognition of personally familiar people have been assumed to reflect the rich episodic and semantic information that selectively represents each person. However, the processes may also include person nonselective ones, which may require interpretation in terms beyond the memory mechanism. To examine this…

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

PubMed

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

2018-05-01

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

Pattern Recognition Using Artificial Neural Network: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

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

Analytical applications of aptamers

NASA Astrophysics Data System (ADS)

Tombelli, S.; Minunni, M.; Mascini, M.

2007-05-01

Aptamers are single stranded DNA or RNA ligands which can be selected for different targets starting from a library of molecules containing randomly created sequences. Aptamers have been selected to bind very different targets, from proteins to small organic dyes. Aptamers are proposed as alternatives to antibodies as biorecognition elements in analytical devices with ever increasing frequency. This in order to satisfy the demand for quick, cheap, simple and highly reproducible analytical devices, especially for protein detection in the medical field or for the detection of smaller molecules in environmental and food analysis. In our recent experience, DNA and RNA aptamers, specific for three different proteins (Tat, IgE and thrombin), have been exploited as bio-recognition elements to develop specific biosensors (aptasensors). These recognition elements have been coupled to piezoelectric quartz crystals and surface plasmon resonance (SPR) devices as transducers where the aptamers have been immobilized on the gold surface of the crystals electrodes or on SPR chips, respectively.

Kin Recognition in a Clonal Fish, Poecilia formosa

PubMed Central

Makowicz, Amber M.; Tiedemann, Ralph; Schlupp, Ingo

2016-01-01

Relatedness strongly influences social behaviors in a wide variety of species. For most species, the highest typical degree of relatedness is between full siblings with 50% shared genes. However, this is poorly understood in species with unusually high relatedness between individuals: clonal organisms. Although there has been some investigation into clonal invertebrates and yeast, nothing is known about kin selection in clonal vertebrates. We show that a clonal fish, the Amazon molly (Poecilia formosa), can distinguish between different clonal lineages, associating with genetically identical, sister clones, and use multiple sensory modalities. Also, they scale their aggressive behaviors according to the relatedness to other females: they are more aggressive to non-related clones. Our results demonstrate that even in species with very small genetic differences between individuals, kin recognition can be adaptive. Their discriminatory abilities and regulation of costly behaviors provides a powerful example of natural selection in species with limited genetic diversity. PMID:27483372

High sensitive detection of copper II ions using D-penicillamine-coated gold nanorods based on localized surface plasmon resonance

NASA Astrophysics Data System (ADS)

Hong, Yoochan; Jo, Seongjae; Park, Joohyung; Park, Jinsung; Yang, Jaemoon

2018-05-01

In this paper, we describe the development of a nanoplasmonic biosensor based on the localized surface plasmon resonance (LSPR) effect that enables a sensitive and selective recognition of copper II ions. First, we fabricated the nanoplasmonics as LSPR substrates using gold nanorods (GNR) and the nano-adsorption method. The LSPR sensitivity of the nanoplasmonics was evaluated using various solvents with different refractive indexes. Subsequently, D-penicillamine (DPA)—a chelating agent of copper II ions—was conjugated to the surface of the GNR. The limit of detection (LOD) for the DPA-conjugated nanoplasmonics was 100 pM. Furthermore, selectivity tests were conducted using various divalent cations, and sensitivity tests were conducted on the nanoplasmonics under blood-like environments. Finally, the developed nanoplasmonic biosensor based on GNR shows great potential for the effective recognition of copper II ions, even in human blood conditions.

High sensitive detection of copper II ions using D-penicillamine-coated gold nanorods based on localized surface plasmon resonance.

PubMed

Hong, Yoochan; Jo, Seongjae; Park, Joohyung; Park, Jinsung; Yang, Jaemoon

2018-05-25

In this paper, we describe the development of a nanoplasmonic biosensor based on the localized surface plasmon resonance (LSPR) effect that enables a sensitive and selective recognition of copper II ions. First, we fabricated the nanoplasmonics as LSPR substrates using gold nanorods (GNR) and the nano-adsorption method. The LSPR sensitivity of the nanoplasmonics was evaluated using various solvents with different refractive indexes. Subsequently, D-penicillamine (DPA)-a chelating agent of copper II ions-was conjugated to the surface of the GNR. The limit of detection (LOD) for the DPA-conjugated nanoplasmonics was 100 pM. Furthermore, selectivity tests were conducted using various divalent cations, and sensitivity tests were conducted on the nanoplasmonics under blood-like environments. Finally, the developed nanoplasmonic biosensor based on GNR shows great potential for the effective recognition of copper II ions, even in human blood conditions.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters.

PubMed

Rempel, David; Camilleri, Matt J; Lee, David L

2015-10-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input.

A Series of Fluorescent and Colorimetric Chemodosimeters for Selective Recognition of Cyanide Based on the FRET Mechanism.

PubMed

Hua, Ying-Xi; Shao, Yongliang; Wang, Ya-Wen; Peng, Yu

2017-06-16

A series of fluorescence "turn-on" probes (PY, AN, NA, B1, and B2) have been developed and successfully applied to detect cyanide anions based on the Michael addition reaction and FRET mechanism. These probes demonstrated good selectivity, high sensitivity, and very fast recognition for CN - . In particular, the fluorescence response of probe NA finished within 3 s. Low limits of detection (down to 63 nM) are also obtained in these probes with remarkable fluorescence enhancement factors. In addition, fluorescence colors of these probes turned to blue, yellow, or orange upon sensing CN - . In UV-vis mode, all of them showed ratiometric response for CN - . 1 H NMR titration experiments and TDDFT calculations were taken to verify the mechanism of the specific reaction and fluorescence properties of the corresponding compounds. Moreover, silica gel plates with these probes were also fabricated and utilized to detect cyanide.

On the effectiveness of vocal imitations and verbal descriptions of sounds.

PubMed

Lemaitre, Guillaume; Rocchesso, Davide

2014-02-01

Describing unidentified sounds with words is a frustrating task and vocally imitating them is often a convenient way to address the issue. This article reports on a study that compared the effectiveness of vocal imitations and verbalizations to communicate different referent sounds. The stimuli included mechanical and synthesized sounds and were selected on the basis of participants' confidence in identifying the cause of the sounds, ranging from easy-to-identify to unidentifiable sounds. The study used a selection of vocal imitations and verbalizations deemed adequate descriptions of the referent sounds. These descriptions were used in a nine-alternative forced-choice experiment: Participants listened to a description and picked one sound from a list of nine possible referent sounds. Results showed that recognition based on verbalizations was maximally effective when the referent sounds were identifiable. Recognition accuracy with verbalizations dropped when identifiability of the sounds decreased. Conversely, recognition accuracy with vocal imitations did not depend on the identifiability of the referent sounds and was as high as with the best verbalizations. This shows that vocal imitations are an effective means of representing and communicating sounds and suggests that they could be used in a number of applications.

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

NASA Astrophysics Data System (ADS)

Lu, Yan; Yan, Chang-Ling; Gao, Shu-Yan

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).

Precision autophagy directed by receptor regulators - emerging examples within the TRIM family.

PubMed

Kimura, Tomonori; Mandell, Michael; Deretic, Vojo

2016-03-01

Selective autophagy entails cooperation between target recognition and assembly of the autophagic apparatus. Target recognition is conducted by receptors that often recognize tags, such as ubiquitin and galectins, although examples of selective autophagy independent of these tags are emerging. It is less known how receptors cooperate with the upstream autophagic regulators, beyond the well-characterized association of receptors with Atg8 or its homologs, such as LC3B (encoded by MAP1LC3B), on autophagic membranes. The molecular details of the emerging role in autophagy of the family of proteins called TRIMs shed light on the coordination between cargo recognition and the assembly and activation of the principal autophagy regulators. In their autophagy roles, TRIMs act both as receptors and as platforms ('receptor regulators') for the assembly of the core autophagy regulators, such as ULK1 and Beclin 1 in their activated state. As autophagic receptors, TRIMs can directly recognize endogenous or exogenous targets, obviating a need for intermediary autophagic tags, such as ubiquitin and galectins. The receptor and regulatory features embodied within the same entity allow TRIMs to govern cargo degradation in a highly exact process termed 'precision autophagy'. © 2016. Published by The Company of Biologists Ltd.

Too little, too late: reduced visual span and speed characterize pure alexia.

PubMed

Starrfelt, Randi; Habekost, Thomas; Leff, Alexander P

2009-12-01

Whether normal word reading includes a stage of visual processing selectively dedicated to word or letter recognition is highly debated. Characterizing pure alexia, a seemingly selective disorder of reading, has been central to this debate. Two main theories claim either that 1) Pure alexia is caused by damage to a reading specific brain region in the left fusiform gyrus or 2) Pure alexia results from a general visual impairment that may particularly affect simultaneous processing of multiple items. We tested these competing theories in 4 patients with pure alexia using sensitive psychophysical measures and mathematical modeling. Recognition of single letters and digits in the central visual field was impaired in all patients. Visual apprehension span was also reduced for both letters and digits in all patients. The only cortical region lesioned across all 4 patients was the left fusiform gyrus, indicating that this region subserves a function broader than letter or word identification. We suggest that a seemingly pure disorder of reading can arise due to a general reduction of visual speed and span, and explain why this has a disproportionate impact on word reading while recognition of other visual stimuli are less obviously affected.

Too Little, Too Late: Reduced Visual Span and Speed Characterize Pure Alexia

PubMed Central

Habekost, Thomas; Leff, Alexander P.

2009-01-01

Whether normal word reading includes a stage of visual processing selectively dedicated to word or letter recognition is highly debated. Characterizing pure alexia, a seemingly selective disorder of reading, has been central to this debate. Two main theories claim either that 1) Pure alexia is caused by damage to a reading specific brain region in the left fusiform gyrus or 2) Pure alexia results from a general visual impairment that may particularly affect simultaneous processing of multiple items. We tested these competing theories in 4 patients with pure alexia using sensitive psychophysical measures and mathematical modeling. Recognition of single letters and digits in the central visual field was impaired in all patients. Visual apprehension span was also reduced for both letters and digits in all patients. The only cortical region lesioned across all 4 patients was the left fusiform gyrus, indicating that this region subserves a function broader than letter or word identification. We suggest that a seemingly pure disorder of reading can arise due to a general reduction of visual speed and span, and explain why this has a disproportionate impact on word reading while recognition of other visual stimuli are less obviously affected. PMID:19366870

A Multifunctional Bimetallic Molecular Device for Ultrasensitive Detection, Naked-Eye Recognition, and Elimination of Cyanide Ions.

PubMed

Chow, Cheuk-Fai; Ho, Pui-Yu; Wong, Wing-Leung; Gong, Cheng-Bin

2015-09-07

A new bimetallic Fe(II) -Cu(II) complex was synthesized, characterized, and applied as a selective and sensitive sensor for cyanide detection in water. This complex is the first multifunctional device that can simultaneously detect cyanide ions in real water samples, amplify the colorimetric signal upon detection for naked-eye recognition at the parts-per-million (ppb) level, and convert the toxic cyanide ion into the much safer cyanate ion in situ. The mechanism of the bimetallic complex for high-selectivity recognition and signaling toward cyanide ions was investigated through a series of binding kinetics of the complex with different analytes, including CN(-) , SO4 (2-) , HCO3 (-) , HPO4 (2-) , N3 (-) , CH3 COO(-) , NCS(-) , NO3 (-) , and Cl(-) ions. In addition, the use of the indicator/catalyst displacement assay (ICDA) is demonstrated in the present system in which one metal center acts as a receptor and inhibitor and is bridged to another metal center that is responsible for signal transduction and catalysis, thus showing a versatile approach to the design of new multifunctional devices. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recent advances on aptamer-based biosensors to detection of platelet-derived growth factor.

PubMed

Razmi, Nasrin; Baradaran, Behzad; Hejazi, Maryam; Hasanzadeh, Mohammad; Mosafer, Jafar; Mokhtarzadeh, Ahad; de la Guardia, Miguel

2018-08-15

Platelet-derived growth factor (PDGF-BB), a significant serum cytokine, is an important protein biomarker in diagnosis and recognition of cancer, which straightly rolled in proceeding of various cell transformations, including tumor growth and its development. Fibrosis, atherosclerosis are certain appalling diseases, which PDGF-BB is near to them. Generally, the expression amount of PDGF-BB increases in human life-threatening tumors serving as an indicator for tumor angiogenesis. Thus, identification and quantification of PDGF-BB in biomedical fields are particularly important. Affinity chromatography, immunohistochemical methods and enzyme-linked immunosorbent assay (ELISA), conventional methods for PDGF-BB detection, requiring high-cost and complicated instrumentation, take too much time and offer deficient sensitivity and selectivity, which restrict their usage in real applications. Hence, it is essential to design and build enhanced systems and platforms for the recognition and quantification of protein biomarkers. In the past few years, biosensors especially aptasensors have been received noticeable attention for the detection of PDGF-BB owing to their high sensitivity, selectivity, accuracy, fast response, and low cost. Since the role and importance of developing aptasensors in cancer diagnosis is undeniable. In this review, optical and electrochemical aptasensors, which have been applied by many researchers for PDGF-BB cancer biomarker detection, have been mentioned and merits and demerits of them have been explained and compared. Efforts related to design and development of aptamer-based biosensors using nanoparticles for sensitive and selective detection of PDGF-BB have been reviewed considering: Aptamer importance as recognition elements, principal, application and the recent improvements and developments of aptamer based optical and electrochemical methods. In addition, commercial biosensors and future perspectives for rapid and on-site detection of PDGF-BB have been summarized. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-12-01

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

Nucleic acid constructs containing orthogonal site selective recombinases (OSSRs)

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

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

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

Emotion effects on implicit and explicit musical memory in normal aging.

PubMed

Narme, Pauline; Peretz, Isabelle; Strub, Marie-Laure; Ergis, Anne-Marie

2016-12-01

Normal aging affects explicit memory while leaving implicit memory relatively spared. Normal aging also modifies how emotions are processed and experienced, with increasing evidence that older adults (OAs) focus more on positive information than younger adults (YAs). The aim of the present study was to investigate how age-related changes in emotion processing influence explicit and implicit memory. We used emotional melodies that differed in terms of valence (positive or negative) and arousal (high or low). Implicit memory was assessed with a preference task exploiting exposure effects, and explicit memory with a recognition task. Results indicated that effects of valence and arousal interacted to modulate both implicit and explicit memory in YAs. In OAs, recognition was poorer than in YAs; however, recognition of positive and high-arousal (happy) studied melodies was comparable. Insofar as socioemotional selectivity theory (SST) predicts a preservation of the recognition of positive information, our findings are not fully consistent with the extension of this theory to positive melodies since recognition of low-arousal (peaceful) studied melodies was poorer in OAs. In the preference task, YAs showed stronger exposure effects than OAs, suggesting an age-related decline of implicit memory. This impairment is smaller than the one observed for explicit memory (recognition), extending to the musical domain the dissociation between explicit memory decline and implicit memory relative preservation in aging. Finally, the disproportionate preference for positive material seen in OAs did not translate into stronger exposure effects for positive material suggesting no age-related emotional bias in implicit memory. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

DTIC Science & Technology

2014-07-01

Macmillan & Creelman , 2005). This is a quite high degree of discriminability and it means that when the decision model predicts a probability of...ROC analysis. Pattern Recognition Letters, 27(8), 861-874. Retrieved from Google Scholar. Macmillan, N. A., & Creelman , C. D. (2005). Detection

Highly selective medium for isolation of Listeria monocytogenes from food.

PubMed Central

al-Zoreky, N; Sandine, W E

1990-01-01

A new selective medium (Al-Zoreky-Sandine listeria medium [ASLM]) was formulated to recover Listeria monocytogenes from food specimens; the medium completely inhibited common food microflora. Recognition of Listeria colonies is evident by black discoloration of the medium due to esculin hydrolysis without need for special illuminating equipment. The medium contains acriflavin, ceftazidime, and moxalactam as selective agents. Compared with Listeria Selective Agar, ASLM was equally effective in recovering L. monocytogenes. However, ASLM inhibited micrococci, enterococci, and gram-negative bacteria, especially a strain that mimicked L. monocytogenes on Listeria Selective Agar. The new medium was able to recover heat injured cells with only 15% less count than the nonselective medium. Images PMID:2126701

A solvent-dependent fluorescent detection method for Fe(3+) and Hg(2+) based on a rhodamine B derivative.

PubMed

Li, Xutian; Yin, Yue; Deng, Junjie; Zhong, Huixian; Tang, Jian; Chen, Zhi; Yang, Liting; Ma, Li-Jun

2016-07-01

A new rhodamine B-benzofurazan based fluorescent probe (1) for Fe(3+) and Hg(2+) was synthesized. In aqueous solution containing 30% (v/v) ethanol, probe 1 shows a high selective fluorescent enhancement recognition to Fe(3+) with a binding ratio of 1:1 (probe 1: Fe(3+)), when the concentration of Fe(3+) is less than that of the probe. When the concentration of Fe(3+) is higher than that of the probe, it shows fluorescent "turn-on" response to Fe(3+) by opening the rhodamine spirolactam with a binding ratio of 1:2 (probe 1: Fe(3+)). Furthermore, probe 1 displays a high selectivity and a hypersensitivity (detection limit is 4.4nM) to Hg(2+) with a binding ratio of 1:1 in ethanol. NMR and UV-vis experiments indicate that the different fluorescent recognition signals to Fe(3+) and Hg(2+) are derived from different binding modes of 1-Fe(3+) and 1-Hg(2+). Copyright © 2016 Elsevier B.V. All rights reserved.

A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.

PubMed

Zhu, Yanan; Ouyang, Qi; Mao, Youdong

2017-07-21

Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecular complexes. However, high-resolution cryo-EM reconstruction often requires hundreds of thousands of single-particle images. Particle extraction from experimental micrographs thus can be laborious and presents a major practical bottleneck in cryo-EM structural determination. Existing computational methods for particle picking often use low-resolution templates for particle matching, making them susceptible to reference-dependent bias. It is critical to develop a highly efficient template-free method for the automatic recognition of particle images from cryo-EM micrographs. We developed a deep learning-based algorithmic framework, DeepEM, for single-particle recognition from noisy cryo-EM micrographs, enabling automated particle picking, selection and verification in an integrated fashion. The kernel of DeepEM is built upon a convolutional neural network (CNN) composed of eight layers, which can be recursively trained to be highly "knowledgeable". Our approach exhibits an improved performance and accuracy when tested on the standard KLH dataset. Application of DeepEM to several challenging experimental cryo-EM datasets demonstrated its ability to avoid the selection of un-wanted particles and non-particles even when true particles contain fewer features. The DeepEM methodology, derived from a deep CNN, allows automated particle extraction from raw cryo-EM micrographs in the absence of a template. It demonstrates an improved performance, objectivity and accuracy. Application of this novel method is expected to free the labor involved in single-particle verification, significantly improving the efficiency of cryo-EM data processing.

Chirality detection of amino acid enantiomers by organic electrochemical transistor.

PubMed

Zhang, Lijun; Wang, Guiheng; Xiong, Can; Zheng, Lei; He, Jianbo; Ding, Yunsheng; Lu, Hongbo; Zhang, Guobing; Cho, Kilwon; Qiu, Longzhen

2018-05-15

Chiral recognition of α-amino acids is attracting increasing interest due to the importance of α-amino acids in protein metabolism as well as in food products and pharmaceuticals. Organic electrochemical transistors (OECTs) with gate electrodes modified with molecularly imprinted polymer (MIP) films were fabricated and successfully used as highly selective and sensitive chiral recognition biosensors for d/l-tryptophan (d/l-Trp) and d/l-tyrosine (d/l-Tyr). The MIP films, which can specifically recognize and has an electrocatalytic effect on the oxidation of Trp and Tyr, together with the amplification function of an OECT, provide a highly sensitive and selective OECT biosensor. The sensor showed a linear response range for l-Trp and L-Tyr from 300 nM to 10 μM with a sensitivity of 3.19 and 3.64 μA/μM, respectivity. And the detection limit for L-Trp and L-Tyr is of 2 nM and 30 nM (S/N > 3). The selectivity factors of L-Trp, D-Trp, L-Tyr and D-Tyr to their enantiomers are 11.6, 3.5, 14.5 and 2.6, respectively. This method can pave the way for widespread applications of OECT-based sensors in chiral material identification. Copyright © 2018 Elsevier B.V. All rights reserved.

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores.

PubMed

El-Safty, Sherif A; Shenashen, Mohamed A; Sakai, Masaru; Elshehy, Emad; Halada, Kohmei

2015-12-06

Developing low-cost, efficient processes for recovering and recycling palladium, gold and cobalt metals from urban mine remains a significant challenge in industrialized countries. Here, the development of optical mesosensors/adsorbents (MSAs) for efficient recognition and selective recovery of Pd(II), Au(III), and Co(II) from urban mine was achieved. A simple, general method for preparing MSAs based on using high-order mesoporous monolithic scaffolds was described. Hierarchical cubic Ia3d wagon-wheel-shaped MSAs were fabricated by anchoring chelating agents (colorants) into three-dimensional pores and micrometric particle surfaces of the mesoporous monolithic scaffolds. Findings show, for the first time, evidence of controlled optical recognition of Pd(II), Au(III), and Co(II) ions and a highly selective system for recovery of Pd(II) ions (up to ~95%) in ores and industrial wastes. Furthermore, the controlled assessment processes described herein involve evaluation of intrinsic properties (e.g., visual signal change, long-term stability, adsorption efficiency, extraordinary sensitivity, selectivity, and reusability); thus, expensive, sophisticated instruments are not required. Results show evidence that MSAs will attract worldwide attention as a promising technological means of recovering and recycling palladium, gold and cobalt metals.

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores

PubMed Central

El-Safty, Sherif A.; Shenashen, Mohamed A.; Sakai, Masaru; Elshehy, Emad; Halada, Kohmei

2015-01-01

Developing low-cost, efficient processes for recovering and recycling palladium, gold and cobalt metals from urban mine remains a significant challenge in industrialized countries. Here, the development of optical mesosensors/adsorbents (MSAs) for efficient recognition and selective recovery of Pd(II), Au(III), and Co(II) from urban mine was achieved. A simple, general method for preparing MSAs based on using high-order mesoporous monolithic scaffolds was described. Hierarchical cubic Ia3d wagon-wheel-shaped MSAs were fabricated by anchoring chelating agents (colorants) into three-dimensional pores and micrometric particle surfaces of the mesoporous monolithic scaffolds. Findings show, for the first time, evidence of controlled optical recognition of Pd(II), Au(III), and Co(II) ions and a highly selective system for recovery of Pd(II) ions (up to ~95%) in ores and industrial wastes. Furthermore, the controlled assessment processes described herein involve evaluation of intrinsic properties (e.g., visual signal change, long-term stability, adsorption efficiency, extraordinary sensitivity, selectivity, and reusability); thus, expensive, sophisticated instruments are not required. Results show evidence that MSAs will attract worldwide attention as a promising technological means of recovering and recycling palladium, gold and cobaltmetals. PMID:26709467

Crozier's paradox revisited: maintenance of genetic recognition systems by disassortative mating.

PubMed

Holman, Luke; van Zweden, Jelle S; Linksvayer, Timothy A; d'Ettorre, Patrizia

2013-09-27

Organisms are predicted to behave more favourably towards relatives, and kin-biased cooperation has been found in all domains of life from bacteria to vertebrates. Cooperation based on genetic recognition cues is paradoxical because it disproportionately benefits individuals with common phenotypes, which should erode the required cue polymorphism. Theoretical models suggest that many recognition loci likely have some secondary function that is subject to diversifying selection, keeping them variable. Here, we use individual-based simulations to investigate the hypothesis that the dual use of recognition cues to facilitate social behaviour and disassortative mating (e.g. for inbreeding avoidance) can maintain cue diversity over evolutionary time. Our model shows that when organisms mate disassortatively with respect to their recognition cues, cooperation and recognition locus diversity can persist at high values, especially when outcrossed matings produce more surviving offspring. Mating system affects cue diversity via at least four distinct mechanisms, and its effects interact with other parameters such as population structure. Also, the attrition of cue diversity is less rapid when cooperation does not require an exact cue match. Using a literature review, we show that there is abundant empirical evidence that heritable recognition cues are simultaneously used in social and sexual behaviour. Our models show that mate choice is one possible resolution of the paradox of genetic kin recognition, and the literature review suggests that genetic recognition cues simultaneously inform assortative cooperation and disassortative mating in a large range of taxa. However, direct evidence is scant and there is substantial scope for future work.

Thioflavin T as an efficient fluorescence sensor for selective recognition of RNA G-quadruplexes

NASA Astrophysics Data System (ADS)

Xu, Shujuan; Li, Qian; Xiang, Junfeng; Yang, Qianfan; Sun, Hongxia; Guan, Aijiao; Wang, Lixia; Liu, Yan; Yu, Lijia; Shi, Yunhua; Chen, Hongbo; Tang, Yalin

2016-04-01

RNA G-quadruplexes (G4s) play important roles in translational regulation, mRNA processing events and gene expression. Therefore, a fluorescent probe that is capable of efficiently recognizing RNA G-quadruplex structures among other RNA forms is highly desirable. In this study, a water-soluble fluorogenic dye (i.e., Thioflavin T (ThT)) was employed to recognize RNA G-quadruplex structures using UV-Vis absorption spectra, fluorescence spectra and emission lifetime experiments. By stacking on the G-tetrad, the ThT probe exhibited highly specific recognition of RNA G-quadruplex structures with striking fluorescence enhancement compared with other RNA forms. The specific binding demonstrates that ThT is an efficient fluorescence sensor that can distinguish G4 and non-G4 RNA structures.

Molecular Recognition of Fluorine Impacts Substrate Selectivity in the Fluoroacetyl-CoA Thioesterase FlK

PubMed Central

2015-01-01

The fluoroacetate-producing bacterium Streptomyces cattleya has evolved a fluoroacetyl-CoA thioesterase (FlK) that exhibits a remarkably high level of discrimination for its cognate substrate compared to the cellularly abundant analogue acetyl-CoA, which differs only by the absence of the fluorine substitution. A major determinant of FlK specificity derives from its ability to take advantage of the unique properties of fluorine to enhance the reaction rate, allowing fluorine discrimination under physiological conditions where both substrates are likely to be present at saturating concentrations. Using a combination of pH–rate profiles, pre-steady-state kinetic experiments, and Taft analysis of wild-type and mutant FlKs with a set of substrate analogues, we explore the role of fluorine in controlling the enzyme acylation and deacylation steps. Further analysis of chiral (R)- and (S)-[2H1]fluoroacetyl-CoA substrates demonstrates that a kinetic isotope effect (1.7 ± 0.2) is observed for only the (R)-2H1 isomer, indicating that deacylation requires recognition of the prochiral fluoromethyl group to position the α-carbon for proton abstraction. Taken together, the selectivity for the fluoroacetyl-CoA substrate appears to rely not only on the enhanced polarization provided by the electronegative fluorine substitution but also on molecular recognition of fluorine in both formation and breakdown of the acyl-enzyme intermediate to control active site reactivity. These studies provide insights into the basis of fluorine selectivity in a naturally occurring enzyme–substrate pair, with implications for drug design and the development of fluorine-selective biocatalysts. PMID:24635371

Novel aspects of sialoglycan recognition by the Siglec-like domains of streptococcal SRR glycoproteins.

PubMed

Bensing, Barbara A; Khedri, Zahra; Deng, Lingquan; Yu, Hai; Prakobphol, Akraporn; Fisher, Susan J; Chen, Xi; Iverson, Tina M; Varki, Ajit; Sullam, Paul M

2016-11-01

Serine-rich repeat glycoproteins are adhesins expressed by commensal and pathogenic Gram-positive bacteria. A subset of these adhesins, expressed by oral streptococci, binds sialylated glycans decorating human salivary mucin MG2/MUC7, and platelet glycoprotein GPIb. Specific sialoglycan targets were previously identified for the ligand-binding regions (BRs) of GspB and Hsa, two serine-rich repeat glycoproteins expressed by Streptococcus gordonii While GspB selectively binds sialyl-T antigen, Hsa displays broader specificity. Here we examine the binding properties of four additional BRs from Streptococcus sanguinis or Streptococcus mitis and characterize the molecular determinants of ligand selectivity and affinity. Each BR has two domains that are essential for sialoglycan binding by GspB. One domain is structurally similar to the glycan-binding module of mammalian Siglecs (sialic acid-binding immunoglobulin-like lectins), including an arginine residue that is critical for glycan recognition, and that resides within a novel, conserved YTRY motif. Despite low sequence similarity to GspB, one of the BRs selectively binds sialyl-T antigen. Although the other three BRs are highly similar to Hsa, each displayed a unique ligand repertoire, including differential recognition of sialyl Lewis antigens and sulfated glycans. These differences in glycan selectivity were closely associated with differential binding to salivary and platelet glycoproteins. Specificity of sialoglycan adherence is likely an evolving trait that may influence the propensity of streptococci expressing Siglec-like adhesins to cause infective endocarditis. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Orthographic recognition in late adolescents: an assessment through event-related brain potentials.

PubMed

González-Garrido, Andrés Antonio; Gómez-Velázquez, Fabiola Reveca; Rodríguez-Santillán, Elizabeth

2014-04-01

Reading speed and efficiency are achieved through the automatic recognition of written words. Difficulties in learning and recognizing the orthography of words can arise despite reiterative exposure to texts. This study aimed to investigate, in native Spanish-speaking late adolescents, how different levels of orthographic knowledge might result in behavioral and event-related brain potential differences during the recognition of orthographic errors. Forty-five healthy high school students were selected and divided into 3 equal groups (High, Medium, Low) according to their performance on a 5-test battery of orthographic knowledge. All participants performed an orthographic recognition task consisting of the sequential presentation of a picture (object, fruit, or animal) followed by a correctly, or incorrectly, written word (orthographic mismatch) that named the picture just shown. Electroencephalogram (EEG) recording took place simultaneously. Behavioral results showed that the Low group had a significantly lower number of correct responses and increased reaction times while processing orthographical errors. Tests showed significant positive correlations between higher performance on the experimental task and faster and more accurate reading. The P150 and P450 components showed higher voltages in the High group when processing orthographic errors, whereas N170 seemed less lateralized to the left hemisphere in the lower orthographic performers. Also, trials with orthographic errors elicited a frontal P450 component that was only evident in the High group. The present results show that higher levels of orthographic knowledge correlate with high reading performance, likely because of faster and more accurate perceptual processing, better visual orthographic representations, and top-down supervision, as the event-related brain potential findings seem to suggest.

Computational Design of Ligand Binding Proteins with High Affinity and Selectivity

PubMed Central

Dou, Jiayi; Doyle, Lindsey; Nelson, Jorgen W.; Schena, Alberto; Jankowski, Wojciech; Kalodimos, Charalampos G.; Johnsson, Kai; Stoddard, Barry L.; Baker, David

2014-01-01

The ability to design proteins with high affinity and selectivity for any given small molecule would have numerous applications in biosensing, diagnostics, and therapeutics, and is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition phenomena. Attempts to design ligand binding proteins have met with little success, however, and the computational design of precise molecular recognition between proteins and small molecules remains an “unsolved problem”1. We describe a general method for the computational design of small molecule binding sites with pre-organized hydrogen bonding and hydrophobic interfaces and high overall shape complementary to the ligand, and use it to design protein binding sites for the steroid digoxigenin (DIG). Of 17 designs that were experimentally characterized, two bind DIG; the highest affinity design has the lowest predicted interaction energy and the most pre-organized binding site in the set. A comprehensive binding-fitness landscape of this design generated by library selection and deep sequencing was used to guide optimization of binding affinity to a picomolar level, and two X-ray co-crystal structures of optimized complexes show atomic level agreement with the design models. The designed binder has a high selectivity for DIG over the related steroids digitoxigenin, progesterone, and β-estradiol, which can be reprogrammed through the designed hydrogen-bonding interactions. Taken together, the binding fitness landscape, co-crystal structures, and thermodynamic binding parameters illustrate how increases in binding affinity can result from distal sequence changes that limit the protein ensemble to conformers making the most energetically favorable interactions with the ligand. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics, and diagnostics. PMID:24005320

Image enhancement and advanced information extraction techniques for ERTS-1 data

NASA Technical Reports Server (NTRS)

Malila, W. A. (Principal Investigator); Nalepka, R. F.; Sarno, J. E.

1975-01-01

The author has identified the following significant results. It was demonstrated and concluded that: (1) the atmosphere has significant effects on ERTS MSS data which can seriously degrade recognition performance; (2) the application of selected signature extension techniques serve to reduce the deleterious effects of both the atmosphere and changing ground conditions on recognition performance; and (3) a proportion estimation algorithm for overcoming problems in acreage estimation accuracy resulting from the coarse spatial resolution of the ERTS MSS, was able to significantly improve acreage estimation accuracy over that achievable by conventional techniques, especially for high contrast targets such as lakes and ponds.

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

A validity problem in measuring exposure to mass media campaigns.

PubMed

Brown, J D; Bauman, K E; Padgett, C A

1990-01-01

Recognition of radio and television messages included in three mass media campaigns designed to keep adolescents from starting to smoke cigarettes was measured in six treatment and four control cities (Standard Metropolitan Statistical Areas) in the southeastern United States. The telephone survey of 574 randomly selected adolescents found high recognition of campaign messages even in the areas where the campaigns had not been broadcast. Campaign messages that differed significantly from other anti-smoking messages were less likely to be falsely recognized. These results reinforce the need to include true control groups in mass media evaluations and to construct distinctive messages if exposure is an important aspect of campaign evaluation.

Oxytocin (OT) and arginine-vasopressin (AVP) act on OT receptors and not AVP V1a receptors to enhance social recognition in adult Syrian hamsters (Mesocricetus auratus).

PubMed

Song, Zhimin; Larkin, Tony E; Malley, Maureen O'; Albers, H Elliott

2016-05-01

Social recognition is a fundamental requirement for all forms of social relationships. A majority of studies investigating the neural mechanisms underlying social recognition in rodents have investigated relatively neutral social stimuli such as juveniles or ovariectomized females over short time intervals (e.g., 2h). The present study developed a new testing model to study social recognition among adult males using a potent social stimulus. Flank gland odors are used extensively in social communication in Syrian hamsters and convey important information such as dominance status. We found that the recognition of flank gland odors after a 3min exposure lasted for at least 24h, substantially longer than the recognition of other social cues in rats and mice. Intracerebroventricular injections of OT and AVP prolonged the recognition of flank gland odor for up to 48h. Selective OTR but not V1aR agonists, mimicked these enhancing effects of OT and AVP. Similarly, selective OTR but not V1aR antagonists blocked recognition of the odors after 20min. In contrast, the recognition of non-social stimuli was not blocked by either the OTR or the V1aR antagonists. Our findings suggest both OT and AVP enhance social recognition via acting on OTRs and not V1aRs and that the recognition enhancing effects of OT and AVP are limited to social stimuli. Copyright © 2016 Elsevier Inc. All rights reserved.

Recognition of voice commands using adaptation of foreign language speech recognizer via selection of phonetic transcriptions

NASA Astrophysics Data System (ADS)

Maskeliunas, Rytis; Rudzionis, Vytautas

2011-06-01

In recent years various commercial speech recognizers have become available. These recognizers provide the possibility to develop applications incorporating various speech recognition techniques easily and quickly. All of these commercial recognizers are typically targeted to widely spoken languages having large market potential; however, it may be possible to adapt available commercial recognizers for use in environments where less widely spoken languages are used. Since most commercial recognition engines are closed systems the single avenue for the adaptation is to try set ways for the selection of proper phonetic transcription methods between the two languages. This paper deals with the methods to find the phonetic transcriptions for Lithuanian voice commands to be recognized using English speech engines. The experimental evaluation showed that it is possible to find phonetic transcriptions that will enable the recognition of Lithuanian voice commands with recognition accuracy of over 90%.

Information-based approach to performance estimation and requirements allocation in multisensor fusion for target recognition

NASA Astrophysics Data System (ADS)

Harney, Robert C.

1997-03-01

A novel methodology offering the potential for resolving two of the significant problems of implementing multisensor target recognition systems, i.e., the rational selection of a specific sensor suite and optimal allocation of requirements among sensors, is presented. Based on a sequence of conjectures (and their supporting arguments) concerning the relationship of extractable information content to recognition performance of a sensor system, a set of heuristics (essentially a reformulation of Johnson's criteria applicable to all sensor and data types) is developed. An approach to quantifying the information content of sensor data is described. Coupling this approach with the widely accepted Johnson's criteria for target recognition capabilities results in a quantitative method for comparing the target recognition ability of diverse sensors (imagers, nonimagers, active, passive, electromagnetic, acoustic, etc.). Extension to describing the performance of multiple sensors is straightforward. The application of the technique to sensor selection and requirements allocation is discussed.

Classification Influence of Features on Given Emotions and Its Application in Feature Selection

NASA Astrophysics Data System (ADS)

Xing, Yin; Chen, Chuang; Liu, Li-Long

2018-04-01

In order to solve the problem that there is a large amount of redundant data in high-dimensional speech emotion features, we analyze deeply the extracted speech emotion features and select better features. Firstly, a given emotion is classified by each feature. Secondly, the recognition rate is ranked in descending order. Then, the optimal threshold of features is determined by rate criterion. Finally, the better features are obtained. When applied in Berlin and Chinese emotional data set, the experimental results show that the feature selection method outperforms the other traditional methods.

Molecularly imprinted polymers with synthetic dummy template for simultaneously selective removal and enrichment of ginkgolic acids from Ginkgo biloba L. leaves extracts.

PubMed

Ji, Wenhua; Ma, Xiuli; Xie, Hongkai; Chen, Lingxiao; Wang, Xiao; Zhao, Hengqiang; Huang, Luqi

2014-11-14

Dummy molecularly imprinted polymers (DMIPs) for simultaneously selective removal and enrichment of ginkgolic acids (GAs) during the processing of Ginkgo biloba leaves have been prepared. Two dummy template molecule with similar structural skeleton to GAs, 6-methoxysalicylic acid (MOSA, DT-1) and 6-hexadecyloxysalicylic acid (HOSA, DT-2), have been designed and synthesized. The performance of the DMIPs and NIPs were evaluated including selective recognition capacity, adsorption isotherm, and adsorption kinetics. The selective recognition capacity of the three GAs with four analogues on the sorbents illustrated that the DMIPs sorbents have high specificity for GAs. An efficient method based on DMIP-HOSA coupled with solid-phase extraction (SPE) was developed for simultaneously selective removal and enrichment of ginkgolic acids (GAs) during the processing of Ginkgo biloba leaves. The method showed excellent recoveries (82.5-88.7%) and precision (RSD 0.5-2.6%, n=5) for licorice extracts, Gastrodia elata extracts and pepper extracts spiked at three concentration levels each (50, 100, 200 μg mL(-1)). The results indicated that GAs and standardized Ginkgo biloba leaves extracts could be obtained simultaneously through the DMIP-SPE. Copyright © 2014 Elsevier B.V. All rights reserved.

Succession of splicing regulatory elements determines cryptic 5΄ss functionality

PubMed Central

Brillen, Anna-Lena; Schöneweis, Katrin; Walotka, Lara; Hartmann, Linda; Müller, Lisa; Ptok, Johannes; Kaisers, Wolfgang; Poschmann, Gereon; Stühler, Kai; Buratti, Emanuele

2017-01-01

Abstract A critical step in exon definition is the recognition of a proper splice donor (5΄ss) by the 5’ end of U1 snRNA. In the selection of appropriate 5΄ss, cis-acting splicing regulatory elements (SREs) are indispensable. As a model for 5΄ss recognition, we investigated cryptic 5΄ss selection within the human fibrinogen Bβ-chain gene (FGB) exon 7, where we identified several exonic SREs that simultaneously acted on up- and downstream cryptic 5΄ss. In the FGB exon 7 model system, 5΄ss selection iteratively proceeded along an alternating sequence of U1 snRNA binding sites and interleaved SREs which in principle supported different 3’ exon ends. Like in a relay race, SREs either suppressed a potential 5΄ss and passed the splicing baton on or splicing actually occurred. From RNA-Seq data, we systematically selected 19 genes containing exons with silent U1 snRNA binding sites competing with nearby highly used 5΄ss. Extensive SRE analysis by different algorithms found authentic 5΄ss significantly more supported by SREs than silent U1 snRNA binding sites, indicating that our concept may permit generalization to a model for 5΄ss selection and 3’ exon end definition. PMID:28039323

Stimulus Similarity and Encoding Time Influence Incidental Recognition Memory in Adult Monkeys with Selective Hippocampal Lesions

ERIC Educational Resources Information Center

Zeamer, Alyson; Meunier, Martine; Bachevalier, Jocelyne

2011-01-01

Recognition memory impairment after selective hippocampal lesions in monkeys is more profound when measured with visual paired-comparison (VPC) than with delayed nonmatching-to-sample (DNMS). To clarify this issue, we assessed the impact of stimuli similarity and encoding duration on the VPC performance in monkeys with hippocampal lesions and…

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Activity recognition using dynamic multiple sensor fusion in body sensor networks.

PubMed

Gao, Lei; Bourke, Alan K; Nelson, John

2012-01-01

Multiple sensor fusion is a main research direction for activity recognition. However, there are two challenges in those systems: the energy consumption due to the wireless transmission and the classifier design because of the dynamic feature vector. This paper proposes a multi-sensor fusion framework, which consists of the sensor selection module and the hierarchical classifier. The sensor selection module adopts the convex optimization to select the sensor subset in real time. The hierarchical classifier combines the Decision Tree classifier with the Naïve Bayes classifier. The dataset collected from 8 subjects, who performed 8 scenario activities, was used to evaluate the proposed system. The results show that the proposed system can obviously reduce the energy consumption while guaranteeing the recognition accuracy.

Selective attention to emotional cues and emotion recognition in healthy subjects: the role of mineralocorticoid receptor stimulation.

PubMed

Schultebraucks, Katharina; Deuter, Christian E; Duesenberg, Moritz; Schulze, Lars; Hellmann-Regen, Julian; Domke, Antonia; Lockenvitz, Lisa; Kuehl, Linn K; Otte, Christian; Wingenfeld, Katja

2016-09-01

Selective attention toward emotional cues and emotion recognition of facial expressions are important aspects of social cognition. Stress modulates social cognition through cortisol, which acts on glucocorticoid (GR) and mineralocorticoid receptors (MR) in the brain. We examined the role of MR activation on attentional bias toward emotional cues and on emotion recognition. We included 40 healthy young women and 40 healthy young men (mean age 23.9 ± 3.3), who either received 0.4 mg of the MR agonist fludrocortisone or placebo. A dot-probe paradigm was used to test for attentional biases toward emotional cues (happy and sad faces). Moreover, we used a facial emotion recognition task to investigate the ability to recognize emotional valence (anger and sadness) from facial expression in four graded categories of emotional intensity (20, 30, 40, and 80 %). In the emotional dot-probe task, we found a main effect of treatment and a treatment × valence interaction. Post hoc analyses revealed an attentional bias away from sad faces after placebo intake and a shift in selective attention toward sad faces compared to placebo. We found no attentional bias toward happy faces after fludrocortisone or placebo intake. In the facial emotion recognition task, there was no main effect of treatment. MR stimulation seems to be important in modulating quick, automatic emotional processing, i.e., a shift in selective attention toward negative emotional cues. Our results confirm and extend previous findings of MR function. However, we did not find an effect of MR stimulation on emotion recognition.

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

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

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

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

Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation

PubMed Central

Liu, Ju-Chi; Chou, Hung-Chyun; Chen, Chien-Hsiu; Lin, Yi-Tseng

2016-01-01

A high efficient time-shift correlation algorithm was proposed to deal with the peak time uncertainty of P300 evoked potential for a P300-based brain-computer interface (BCI). The time-shift correlation series data were collected as the input nodes of an artificial neural network (ANN), and the classification of four LED visual stimuli was selected as the output node. Two operating modes, including fast-recognition mode (FM) and accuracy-recognition mode (AM), were realized. The proposed BCI system was implemented on an embedded system for commanding an adult-size humanoid robot to evaluate the performance from investigating the ground truth trajectories of the humanoid robot. When the humanoid robot walked in a spacious area, the FM was used to control the robot with a higher information transfer rate (ITR). When the robot walked in a crowded area, the AM was used for high accuracy of recognition to reduce the risk of collision. The experimental results showed that, in 100 trials, the accuracy rate of FM was 87.8% and the average ITR was 52.73 bits/min. In addition, the accuracy rate was improved to 92% for the AM, and the average ITR decreased to 31.27 bits/min. due to strict recognition constraints. PMID:27579033

Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation.

PubMed

Liu, Ju-Chi; Chou, Hung-Chyun; Chen, Chien-Hsiu; Lin, Yi-Tseng; Kuo, Chung-Hsien

2016-01-01

A high efficient time-shift correlation algorithm was proposed to deal with the peak time uncertainty of P300 evoked potential for a P300-based brain-computer interface (BCI). The time-shift correlation series data were collected as the input nodes of an artificial neural network (ANN), and the classification of four LED visual stimuli was selected as the output node. Two operating modes, including fast-recognition mode (FM) and accuracy-recognition mode (AM), were realized. The proposed BCI system was implemented on an embedded system for commanding an adult-size humanoid robot to evaluate the performance from investigating the ground truth trajectories of the humanoid robot. When the humanoid robot walked in a spacious area, the FM was used to control the robot with a higher information transfer rate (ITR). When the robot walked in a crowded area, the AM was used for high accuracy of recognition to reduce the risk of collision. The experimental results showed that, in 100 trials, the accuracy rate of FM was 87.8% and the average ITR was 52.73 bits/min. In addition, the accuracy rate was improved to 92% for the AM, and the average ITR decreased to 31.27 bits/min. due to strict recognition constraints.

Molecular basis of cyclooxygenase enzymes (COXs) selective inhibition

PubMed Central

Limongelli, Vittorio; Bonomi, Massimiliano; Marinelli, Luciana; Gervasio, Francesco Luigi; Cavalli, Andrea; Novellino, Ettore; Parrinello, Michele

2010-01-01

The widely used nonsteroidal anti-inflammatory drugs block the cyclooxygenase enzymes (COXs) and are clinically used for the treatment of inflammation, pain, and cancers. A selective inhibition of the different isoforms, particularly COX-2, is desirable, and consequently a deeper understanding of the molecular basis of selective inhibition is of great demand. Using an advanced computational technique we have simulated the full dissociation process of a highly potent and selective inhibitor, SC-558, in both COX-1 and COX-2. We have found a previously unreported alternative binding mode in COX-2 explaining the time-dependent inhibition exhibited by this class of inhibitors and consequently their long residence time inside this isoform. Our metadynamics-based approach allows us to illuminate the highly dynamical character of the ligand/protein recognition process, thus explaining a wealth of experimental data and paving the way to an innovative strategy for designing new COX inhibitors with tuned selectivity. PMID:20215464

Using Temporal Modulation Sensitivity to Select Stimulation Sites for Processor MAPs in Cochlear Implant Listeners

PubMed Central

Garadat, Soha N.; Zwolan, Teresa A.; Pfingst, Bryan E.

2013-01-01

Previous studies in our laboratory showed that temporal acuity as assessed by modulation detection thresholds (MDTs) varied across activation sites and that this site-to-site variability was subject specific. Using two 10-channel MAPs, the previous experiments showed that processor MAPs that had better across-site mean (ASM) MDTs yielded better speech recognition than MAPs with poorer ASM MDTs tested in the same subject. The current study extends our earlier work on developing more optimal fitting strategies to test the feasibility of using a site-selection approach in the clinical domain. This study examined the hypothesis that revising the clinical speech processor MAP for cochlear implant (CI) recipients by turning off selected sites that have poorer temporal acuity and reallocating frequencies to the remaining electrodes would lead to improved speech recognition. Twelve CI recipients participated in the experiments. We found that site selection procedure based on MDTs in the presence of a masker resulted in improved performance on consonant recognition and recognition of sentences in noise. In contrast, vowel recognition was poorer with the experimental MAP than with the clinical MAP, possibly due to reduced spectral resolution when sites were removed from the experimental MAP. Overall, these results suggest a promising path for improving recipient outcomes using personalized processor-fitting strategies based on a psychophysical measure of temporal acuity. PMID:23881208

Molecular evolution of candidate male reproductive genes in the brown algal model Ectocarpus.

PubMed

Lipinska, Agnieszka P; Van Damme, Els J M; De Clerck, Olivier

2016-01-05

Evolutionary studies of genes that mediate recognition between sperm and egg contribute to our understanding of reproductive isolation and speciation. Surface receptors involved in fertilization are targets of sexual selection, reinforcement, and other evolutionary forces including positive selection. This observation was made across different lineages of the eukaryotic tree from land plants to mammals, and is particularly evident in free-spawning animals. Here we use the brown algal model species Ectocarpus (Phaeophyceae) to investigate the evolution of candidate gamete recognition proteins in a distant major phylogenetic group of eukaryotes. Male gamete specific genes were identified by comparing transcriptome data covering different stages of the Ectocarpus life cycle and screened for characteristics expected from gamete recognition receptors. Selected genes were sequenced in a representative number of strains from distant geographical locations and varying stages of reproductive isolation, to search for signatures of adaptive evolution. One of the genes (Esi0130_0068) showed evidence of selective pressure. Interestingly, that gene displayed domain similarities to the receptor for egg jelly (REJ) protein involved in sperm-egg recognition in sea urchins. We have identified a male gamete specific gene with similarity to known gamete recognition receptors and signatures of adaptation. Altogether, this gene could contribute to gamete interaction during reproduction as well as reproductive isolation in Ectocarpus and is therefore a good candidate for further functional evaluation.

Selective habituation shapes acoustic predator recognition in harbour seals.

PubMed

Deecke, Volker B; Slater, Peter J B; Ford, John K B

2002-11-14

Predation is a major force in shaping the behaviour of animals, so that precise identification of predators will confer substantial selective advantages on animals that serve as food to others. Because experience with a predator can be lethal, early researchers studying birds suggested that predator recognition does not require learning. However, a predator image that can be modified by learning and experience will be advantageous in situations where cues associated with the predator are highly variable or change over time. In this study, we investigated the response of harbour seals (Phoca vitulina) to the underwater calls of different populations of killer whales (Orcinus orca). We found that the seals responded strongly to the calls of mammal-eating killer whales and unfamiliar fish-eating killer whales but not to the familiar calls of the local fish-eating population. This demonstrates that wild harbour seals are capable of complex acoustic discrimination and that they modify their predator image by selectively habituating to the calls of harmless killer whales. Fear in these animals is therefore focused on local threats by learning and experience.

Xenophagic pathways and their bacterial subversion in cellular self-defense - παντα ρει - everything is in flux.

PubMed

Radomski, Nadine; Rebbig, Annica; Leonhardt, Ralf M; Knittler, Michael R

2017-11-02

Autophagy is an evolutionarily ancient and highly conserved eukaryotic mechanism that targets cytoplasmic material for degradation. Autophagic flux involves the formation of autophagosomes and their degradation by lysosomes. The process plays a crucial role in maintaining cellular homeostasis and responds to various environmental conditions. While autophagy had previously been thought to be a non-selective process, it is now clear that it can also selectively target cellular organelles, such as mitochondria (referred to as mitophagy) and/or invading pathogens (referred to as xenophagy). Selective autophagy is characterized by specific substrate recognition and requires distinct cellular adaptor proteins. Here we review xenophagic mechanisms involved in the recognition and autolysosomal or autophagolysosomal degradation of different intracellular bacteria. In this context, we also discuss a recently discovered cellular self-defense pathway, termed mito-xenophagy, which occurs during bacterial infection of dendritic cells and depends on a TNF-α-mediated metabolic switch from oxidative phosphorylation to glycolysis. Copyright © 2017 Elsevier GmbH. All rights reserved.

ERP markers of target selection discriminate children with high vs. low working memory capacity.

PubMed

Shimi, Andria; Nobre, Anna Christina; Scerif, Gaia

2015-01-01

Selective attention enables enhancing a subset out of multiple competing items to maximize the capacity of our limited visual working memory (VWM) system. Multiple behavioral and electrophysiological studies have revealed the cognitive and neural mechanisms supporting adults' selective attention of visual percepts for encoding in VWM. However, research on children is more limited. What are the neural mechanisms involved in children's selection of incoming percepts in service of VWM? Do these differ from the ones subserving adults' selection? Ten-year-olds and adults used a spatial arrow cue to select a colored item for later recognition from an array of four colored items. The temporal dynamics of selection were investigated through EEG signals locked to the onset of the memory array. Both children and adults elicited significantly more negative activity over posterior scalp locations contralateral to the item to-be-selected for encoding (N2pc). However, this activity was elicited later and for longer in children compared to adults. Furthermore, although children as a group did not elicit a significant N2pc during the time-window in which N2pc was elicited in adults, the magnitude of N2pc during the "adult time-window" related to their behavioral performance during the later recognition phase of the task. This in turn highlights how children's neural activity subserving attention during encoding relates to better subsequent VWM performance. Significant differences were observed when children were divided into groups of high vs. low VWM capacity as a function of cueing benefit. Children with large cue benefits in VWM capacity elicited an adult-like contralateral negativity following attentional selection of the to-be-encoded item, whereas children with low VWM capacity did not. These results corroborate the close coupling between selective attention and VWM from childhood and elucidate further the attentional mechanisms constraining VWM performance in children.

Early top-down control of visual processing predicts working memory performance

PubMed Central

Rutman, Aaron M.; Clapp, Wesley C.; Chadick, James Z.; Gazzaley, Adam

2009-01-01

Selective attention confers a behavioral benefit for both perceptual and working memory (WM) performance, often attributed to top-down modulation of sensory neural processing. However, the direct relationship between early activity modulation in sensory cortices during selective encoding and subsequent WM performance has not been established. To explore the influence of selective attention on WM recognition, we used electroencephalography (EEG) to study the temporal dynamics of top-down modulation in a selective, delayed-recognition paradigm. Participants were presented with overlapped, “double-exposed” images of faces and natural scenes, and were instructed to either remember the face or the scene while simultaneously ignoring the other stimulus. Here, we present evidence that the degree to which participants modulate the early P100 (97–129 ms) event-related potential (ERP) during selective stimulus encoding significantly correlates with their subsequent WM recognition. These results contribute to our evolving understanding of the mechanistic overlap between attention and memory. PMID:19413473

Conserved conformational selection mechanism of Hsp70 chaperone-substrate interactions

PubMed Central

Velyvis, Algirdas; Zoltsman, Guy; Rosenzweig, Rina; Bouvignies, Guillaume

2018-01-01

Molecular recognition is integral to biological function and frequently involves preferred binding of a molecule to one of several exchanging ligand conformations in solution. In such a process the bound structure can be selected from the ensemble of interconverting ligands a priori (conformational selection, CS) or may form once the ligand is bound (induced fit, IF). Here we focus on the ubiquitous and conserved Hsp70 chaperone which oversees the integrity of the cellular proteome through its ATP-dependent interaction with client proteins. We directly quantify the flux along CS and IF pathways using solution NMR spectroscopy that exploits a methyl TROSY effect and selective isotope-labeling methodologies. Our measurements establish that both bacterial and human Hsp70 chaperones interact with clients by selecting the unfolded state from a pre-existing array of interconverting structures, suggesting a conserved mode of client recognition among Hsp70s and highlighting the importance of molecular dynamics in this recognition event. PMID:29460778

Validating a two-high-threshold measurement model for confidence rating data in recognition.

PubMed

Bröder, Arndt; Kellen, David; Schütz, Julia; Rohrmeier, Constanze

2013-01-01

Signal Detection models as well as the Two-High-Threshold model (2HTM) have been used successfully as measurement models in recognition tasks to disentangle memory performance and response biases. A popular method in recognition memory is to elicit confidence judgements about the presumed old/new status of an item, allowing for the easy construction of ROCs. Since the 2HTM assumes fewer latent memory states than response options are available in confidence ratings, the 2HTM has to be extended by a mapping function which models individual rating scale usage. Unpublished data from 2 experiments in Bröder and Schütz (2009) validate the core memory parameters of the model, and 3 new experiments show that the response mapping parameters are selectively affected by manipulations intended to affect rating scale use, and this is independent of overall old/new bias. Comparisons with SDT show that both models behave similarly, a case that highlights the notion that both modelling approaches can be valuable (and complementary) elements in a researcher's toolbox.

Implementation of a high-speed face recognition system that uses an optical parallel correlator.

PubMed

Watanabe, Eriko; Kodate, Kashiko

2005-02-10

We implement a fully automatic fast face recognition system by using a 1000 frame/s optical parallel correlator designed and assembled by us. The operational speed for the 1:N (i.e., matching one image against N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 s, including the preprocessing and postprocessing times. The binary real-only matched filter is devised for the sake of face recognition, and the system is optimized by the false-rejection rate (FRR) and the false-acceptance rate (FAR), according to 300 samples selected by the biometrics guideline. From trial 1:N identification experiments with the optical parallel correlator, we acquired low error rates of 2.6% FRR and 1.3% FAR. Facial images of people wearing thin glasses or heavy makeup that rendered identification difficult were identified with this system.

Synthesis of a specific monolithic column with artificial recognition sites for L-glutamic acid via cryo-crosslinking of imprinted nanoparticles.

PubMed

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.

Breast Cancer Recognition Using a Novel Hybrid Intelligent Method

PubMed Central

Addeh, Jalil; Ebrahimzadeh, Ata

2012-01-01

Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. This paper presents a novel hybrid intelligent method for recognition of breast cancer tumors. The proposed method includes three main modules: the feature extraction module, the classifier module, and the optimization module. In the feature extraction module, fuzzy features are proposed as the efficient characteristic of the patterns. In the classifier module, because of the promising generalization capability of support vector machines (SVM), a SVM-based classifier is proposed. In support vector machine training, the hyperparameters have very important roles for its recognition accuracy. Therefore, in the optimization module, the bees algorithm (BA) is proposed for selecting appropriate parameters of the classifier. The proposed system is tested on Wisconsin Breast Cancer database and simulation results show that the recommended system has a high accuracy. PMID:23626945

Comparison of multi-recognition molecularly imprinted polymers for recognition of melamine, cyromazine, triamterene, and trimethoprim.

PubMed

Wang, Xian-Hua; Zhang, Jing; Peng, Chao; Dong, Qian; Huang, Yan-Ping; Liu, Zhao-Sheng

2015-09-01

Three fragmental templates, including 2,4-diamino-6-methyl-1,3,5-triazine (DMT), cyromazine (CYR), and trimethoprim (TME), were used to prepare the fragment molecularly imprinted polymers (FMIPs), respectively, in polar ternary porogen which was composed of ionic liquid ([BMIM]BF4), methanol, and water. The morphology, specific surface areas, and selectivity of the obtained FMIPs for fragmental analogues were systematically characterized. The experimental results showed that the FMIPs possessed the best specific recognition ability to the relative template and the greatest imprinting factor (IF) was 5.25, 6.69, and 7.11 of DMT on DMT-MIPs, CYR on CYR-MIPs, and TME on TME-MIPs, respectively. In addition, DMT-MIPs also showed excellent recognition capability for fragmental analogues including CYR, melamine (MEL), triamterene (TAT), and TME, and the IFs were 2.08, 3.89, 2.18, and 2.60, respectively. The effects of pH and temperature on the retention of the fragmental and structural analogues were studied in detail. Van't Hoff analysis indicated that the retention and selectivity on FMIPs were an entropy-driven process, i.e., steric interaction. The resulting DMT-MIPs were used as a solid-phase extraction material to enrich CYR, MEL, TAT, and TME in different bio-matrix samples for high-performance liquid chromatography analysis. The developed method had acceptable recoveries (86.8-98.6%, n = 3) and precision (2.7-4.6%) at three spiked levels (0.05-0.5 μg g(-1)).

Leveling the playing field: attention mitigates the effects of intelligence on memory.

PubMed

Markant, Julie; Amso, Dima

2014-05-01

Effective attention and memory skills are fundamental to typical development and essential for achievement during the formal education years. It is critical to identify the specific mechanisms linking efficiency of attentional selection of an item and the quality of its memory retention. The present study capitalized on the spatial cueing paradigm to examine the role of selection via suppression in modulating children and adolescents' memory encoding. By varying a single parameter, the spatial cueing task can elicit either a simple orienting mechanism (i.e., facilitation) or one that involves both target selection and simultaneous suppression of competing information (i.e., IOR). We modified this paradigm to include images of common items in target locations. Participants were not instructed to learn the items and were not told they would be completing a memory test later. Following the cueing task, we imposed a 7-min delay and then asked participants to complete a recognition memory test. Results indicated that selection via suppression promoted recognition memory among 7-17year-olds. Moreover, individual differences in the extent of suppression during encoding predicted recognition memory accuracy. When basic cueing facilitated orienting to target items during encoding, IQ was the best predictor of recognition memory performance for the attended items. In contrast, engaging suppression (i.e., IOR) during encoding counteracted individual differences in intelligence, effectively improving recognition memory performance among children with lower IQs. This work demonstrates that engaging selection via suppression during learning and encoding improves memory retention and has broad implications for developing effective educational techniques. Copyright © 2014 Elsevier B.V. All rights reserved.

Leveling the playing field: Attention mitigates the effects of intelligence on memory

PubMed Central

Markant, Julie; Amso, Dima

2014-01-01

Effective attention and memory skills are fundamental to typical development and essential for achievement during the formal education years. It is critical to identify the specific mechanisms linking efficiency of attentional selection of an item and the quality of its memory retention. The present study capitalized on the spatial cueing paradigm to examine the role of selection via suppression in modulating children and adolescents’ memory encoding. By varying a single parameter, the spatial cueing task can elicit either a simple orienting mechanism (i.e., facilitation) or one that involves both target selection and simultaneous suppression of competing information (i.e., IOR). We modified this paradigm to include images of common items in target locations. Participants were not instructed to learn the items and were not told they would be completing a memory test later. Following the cueing task, we imposed a seven-minute delay and then asked participants to complete a recognition memory test. Results indicated that selection via suppression promoted recognition memory among 7-17 year-olds. Moreover, individual differences in the extent of suppression during encoding predicted recognition memory accuracy. When basic cueing facilitated orienting to target items during encoding, IQ was the best predictor of recognition memory performance for the attended items. In contrast, engaging suppression (i.e, IOR) during encoding counteracted individual differences in intelligence, effectively improving recognition memory performance among children with lower IQs. This work demonstrates that engaging selection via suppression during learning and encoding improves memory retention and has broad implications for developing effective educational techniques. PMID:24549142

Postprocessing for character recognition using pattern features and linguistic information

NASA Astrophysics Data System (ADS)

Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

1993-04-01

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

Fluorenone based fluorescent probe for selective "turn-on" detection of pyrophosphate and alanine

NASA Astrophysics Data System (ADS)

Daniel Thangadurai, T.; Nithya, I.; Manjubaashini, N.; Bhuvanesh, N.; Bharathi, G.; Nandhakumar, R.; Nataraj, D.

2018-06-01

To sense biologically important entities with different size and dimensions, a fluorenone based fluorescent receptor was designed and synthesized. Probe 1 displayed a distinct fluorescence enhancement emission at 565 nm for pyrophosphate and 530 nm for alanine in polar solvent. The fluorescence titration experiments confirm 1:1 stoichiometric ratio with high-binding constant and very low limit of detection (LoD) values. Receptor 1 showed a highly selective and sensitive recognition to HP2O73 - and to alanine over other competitive anions and amino acids. In addition, the fluorescence lifetime measurement and reversible binding study results support the practical importance of 1.

Genome-Wide Analysis and Evolution of the Pto-Like Protein Kinase (PLPK) Gene Family in Pepper

PubMed Central

Venkatesh, Jelli; Jahn, Molly; Kang, Byoung-Cheorl

2016-01-01

The tomato Pto gene, which encodes a serine/threonine kinase (STK) domain-containing protein, confers resistance to bacterial speck disease caused by Pseudomonas syringae pv. tomato (Pst). In this study, in vivo recognition assays using PVX constructs showed that AvrPto was specifically recognized in the pepper genotypes. This AvrPto recognition caused a nonhost hypersensitive response (HR) and localization of the PVX::AvrPto fusion protein to inoculated pepper leaf tissues, which indicates the presence of a similar Pto recognition mechanism in pepper as in tomato. However, genome-wide analysis in pepper revealed no Pto clade corresponding to that in tomato, suggesting an alternative system for Pto recognition in pepper. Nevertheless, 25 Pto-like protein kinases (PLPKs) with a highly conserved STK domain have been identified in the pepper genome. For the majority of the amino acid sites in the STK domain of Ptos and PLPKs, nonsynonymous (dN) to synonymous (dS) nucleotide substitution ratios (ω) were less than one, suggesting that purifying selection played a predominant role in the evolutionary process. However, some amino acid sites were found to be subjected to episodic positive selection in the course of evolution of Pto homologs, and, thus, different evolutionary processes might have shaped the Pto gene family in plants. Based on RNA-seq data, PLPK genes and other Pto pathway genes, such as Prf, Pti1, Pti5, and Pti6 were expressed in all tested pepper genotypes. Therefore, the nonhost HR against Pst in pepper may be due to the recognition of the AvrPto effector by a PLPK homolog, and subsequent action of downstream components of the Pto signaling pathway. However, the possibility remains that the recognition of AvrPto in pepper plants may involve activities of other receptor like kinases (RLKs). The identification of the PLPKs in this study will serve as a foundation for further efforts to understand the roles of PLPKs in nonhost resistance. PMID:27536870

Age-related differences in emotion recognition ability: a cross-sectional study.

PubMed

Mill, Aire; Allik, Jüri; Realo, Anu; Valk, Raivo

2009-10-01

Experimental studies indicate that recognition of emotions, particularly negative emotions, decreases with age. However, there is no consensus at which age the decrease in emotion recognition begins, how selective this is to negative emotions, and whether this applies to both facial and vocal expression. In the current cross-sectional study, 607 participants ranging in age from 18 to 84 years (mean age = 32.6 +/- 14.9 years) were asked to recognize emotions expressed either facially or vocally. In general, older participants were found to be less accurate at recognizing emotions, with the most distinctive age difference pertaining to a certain group of negative emotions. Both modalities revealed an age-related decline in the recognition of sadness and -- to a lesser degree -- anger, starting at about 30 years of age. Although age-related differences in the recognition of expression of emotion were not mediated by personality traits, 2 of the Big 5 traits, openness and conscientiousness, made an independent contribution to emotion-recognition performance. Implications of age-related differences in facial and vocal emotion expression and early onset of the selective decrease in emotion recognition are discussed in terms of previous findings and relevant theoretical models.

On Becoming Themselves: The 1964-1968 Presidential Scholars 40 Years Later

ERIC Educational Resources Information Center

Kaufmann, Felice A.; Matthews, Dona J.

2012-01-01

Every year since 1964, approximately 120 high-school seniors have been selected for presidential recognition, from across the United States. As the first cohort of Presidential Scholars enters their 60s, we wanted to hear what they think about the roles that academic, professional, and personal achievement have played in their lives and to…

Influence of leaf color in a dry bean mapping population on Empoasca sp. populations and host plant resistance.

USDA-ARS?s Scientific Manuscript database

Visual cues may be the first line of host plant recognition and an important determining factor when selecting host plants for feeding and oviposition, especially for highly polyphagous insects, such as leafhoppers, which have a broad range of potential host plants. Temperate Empoasca fabae and trop...

Improving the Success of Middle Grade Students. Middle School Matters Program No. 2

ERIC Educational Resources Information Center

Belfanz, Robert; Rodriguez, Gina; Brasiel, Sarah J.

2013-01-01

A student's experience in the middle grades is a selection of classes they go through in a day. If they experience inconsistent expectations across those classes, they and the school will struggle to achieve high outcomes. Middle grade students need to have common behavioral and academic expectations, recognitions, and consequences throughout the…

The Interaction of Lexical Semantics and Cohort Competition in Spoken Word Recognition: An fMRI Study

ERIC Educational Resources Information Center

Zhuang, Jie; Randall, Billi; Stamatakis, Emmanuel A.; Marslen-Wilson, William D.; Tyler, Lorraine K.

2011-01-01

Spoken word recognition involves the activation of multiple word candidates on the basis of the initial speech input--the "cohort"--and selection among these competitors. Selection may be driven primarily by bottom-up acoustic-phonetic inputs or it may be modulated by other aspects of lexical representation, such as a word's meaning…

Interdependence of Inhibitor Recognition in HIV-1 Protease

PubMed Central

2017-01-01

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. PMID:28358514

Interdependence of Inhibitor Recognition in HIV-1 Protease.

PubMed

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.

Personal glucose meters for detection and quantification of a broad range of analytes

DOEpatents

Lu, Yi; Xiang, Yu

2015-02-03

A general methodology for the development of highly sensitive and selective sensors that can achieve portable, low-cost and quantitative detection of a broad range of targets using only a personal glucose meter (PGM) is disclosed. The method uses recognition molecules that are specific for a target agent, enzymes that can convert an enzyme substrate into glucose, and PGM. Also provided are sensors, which can include a solid support to which is attached a recognition molecule that permits detection of a target agent, wherein the recognition molecule specifically binds to the target agent in the presence of the target agent but not significantly to other agents as well as an enzyme that can catalyze the conversion of a substance into glucose, wherein the enzyme is attached directly or indirectly to the recognition molecule, and wherein in the presence of the target agent the enzyme can convert the substance into glucose. The disclosed sensors can be part of a lateral flow device. Methods of using such sensors for detecting target agents are also provided.

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

PubMed

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.

Appearance-based representative samples refining method for palmprint recognition

NASA Astrophysics Data System (ADS)

Wen, Jiajun; Chen, Yan

2012-07-01

The sparse representation can deal with the lack of sample problem due to utilizing of all the training samples. However, the discrimination ability will degrade when more training samples are used for representation. We propose a novel appearance-based palmprint recognition method. We aim to find a compromise between the discrimination ability and the lack of sample problem so as to obtain a proper representation scheme. Under the assumption that the test sample can be well represented by a linear combination of a certain number of training samples, we first select the representative training samples according to the contributions of the samples. Then we further refine the training samples by an iteration procedure, excluding the training sample with the least contribution to the test sample for each time. Experiments on PolyU multispectral palmprint database and two-dimensional and three-dimensional palmprint database show that the proposed method outperforms the conventional appearance-based palmprint recognition methods. Moreover, we also explore and find out the principle of the usage for the key parameters in the proposed algorithm, which facilitates to obtain high-recognition accuracy.

Two-dimensional shape recognition using oriented-polar representation

NASA Astrophysics Data System (ADS)

Hu, Neng-Chung; Yu, Kuo-Kan; Hsu, Yung-Li

1997-10-01

To deal with such a problem as object recognition of position, scale, and rotation invariance (PSRI), we utilize some PSRI properties of images obtained from objects, for example, the centroid of the image. The corresponding position of the centroid to the boundary of the image is invariant in spite of rotation, scale, and translation of the image. To obtain the information of the image, we use the technique similar to Radon transform, called the oriented-polar representation of a 2D image. In this representation, two specific points, the centroid and the weighted mean point, are selected to form an initial ray, then the image is sampled with N angularly equispaced rays departing from the initial rays. Each ray contains a number of intersections and the distance information obtained from the centroid to the intersections. The shape recognition algorithm is based on the least total error of these two items of information. Together with a simple noise removal and a typical backpropagation neural network, this algorithm is simple, but the PSRI is achieved with a high recognition rate.

Domain repertoires as a tool to derive protein recognition rules.

PubMed

Zucconi, A; Panni, S; Paoluzi, S; Castagnoli, L; Dente, L; Cesareni, G

2000-08-25

Several approaches, some of which are described in this issue, have been proposed to assemble a complete protein interaction map. These are often based on high throughput methods that explore the ability of each gene product to bind any other element of the proteome of the organism. Here we propose that a large number of interactions can be inferred by revealing the rules underlying recognition specificity of a small number (a few hundreds) of families of protein recognition modules. This can be achieved through the construction and characterization of domain repertoires. A domain repertoire is assembled in a combinatorial fashion by allowing each amino acid position in the binding site of a given protein recognition domain to vary to include all the residues allowed at that position in the domain family. The repertoire is then searched by phage display techniques with any target of interest and from the primary structure of the binding site of the selected domains one derives rules that are used to infer the formation of complexes between natural proteins in the cell.

Recognition without Awareness: Encoding and Retrieval Factors

ERIC Educational Resources Information Center

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

2015-01-01

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

Enhancing Adsorption Capacity while Maintaining Specific Recognition Performance of Mesoporous Silica: A Novel Imprinting Strategy with Amphiphilic Ionic Liquid as Surfactant.

PubMed

Ding, Shichao; Li, Zhiling; Cheng, Yuan; Du, Chunbao; Gao, Junfeng; Zhang, Yong-Wei; Zhang, Nan; Li, Zhaotong; Chang, Ninghui; Hu, Xiaoling

2018-06-21

In order to facilitate the broad applications of molecular recognition materials in biomedical areas, it is critical to enhance their adsorption capacity while maintaining their excellent recognition performance. In this work, we designed and synthesized well-defined peptide-imprinted mesoporous silica (PIMS) for specific recognition of an immunostimulating hexapeptide from human casein (IHHC) by using amphiphilic ionic liquid as the surfactant to anchor IHHC via a combination of one step sol-gel method and docking oriented imprinting approach. Thereinto, theoretical calculation was employed to reveal the multiple binding interactions and dual-template configuration between amphiphilic ionic liquid and IHHC. The fabricated PIMS was characterized and an in-depth analysis of specific recognition mechanism was conducted. Results revealed that both adsorption and recognition capabilities of PIMS far exceeded that of the NIMS's. More significantly, the PIMS exhibited a superior binding capacity (60.5 mg g-1), which could increase 18.9% than the previous work. The corresponding imprinting factor and selectivity coefficient could reach up to 4.51 and 3.30, respectively. The PIMS also possessed lickety-split kinetic binding for IHHC, which the equilibrium time was only 10 min. All of these merits were due to the high surface area and the synergistic effect of multiple interactions (including hydrogen bonding, π-π stacking, ion-ion electrostatic interactions and van der Waals interactions, etc.) between PIMS and IHHC in imprinted sites. The present work suggests the potential application of PIMS for large-scale and high-effective separation of IHHC, which may lead to their broad applications in drug/gene deliver, biosensors, catalyst and so on. © 2018 IOP Publishing Ltd.

Selection to outsmart the germs: The evolution of disease recognition and social cognition.

PubMed

Kessler, Sharon E; Bonnell, Tyler R; Byrne, Richard W; Chapman, Colin A

2017-07-01

The emergence of providing care to diseased conspecifics must have been a turning point during the evolution of hominin sociality. On a population level, care may have minimized the costs of socially transmitted diseases at a time of increasing social complexity, although individual care-givers probably incurred increased transmission risks. We propose that care-giving likely originated within kin networks, where the costs may have been balanced by fitness increases obtained through caring for ill kin. We test a novel hypothesis of hominin cognitive evolution in which disease may have selected for the cognitive ability to recognize when a conspecific is infected. Because diseases may produce symptoms that are likely detectable via the perceptual-cognitive pathways integral to social cognition, we suggest that disease recognition and social cognition may have evolved together. Using agent-based modeling, we test 1) under what conditions disease can select for increasing disease recognition and care-giving among kin, 2) whether providing care produces greater selection for cognition than an avoidance strategy, and 3) whether care-giving alters the progression of the disease through the population. The greatest selection was produced by diseases with lower risks to the care-giver and prevalences low enough not to disrupt the kin networks. When care-giving and avoidance strategies were compared, only care-giving reduced the severity of the disease outbreaks and subsequent population crashes. The greatest selection for increased cognitive abilities occurred early in the model runs when the outbreaks and population crashes were most severe. Therefore, over the course of human evolution, repeated introductions of novel diseases into naïve populations could have produced sustained selection for increased disease recognition and care-giving behavior, leading to the evolution of increased cognition, social complexity, and, eventually, medical care in humans. Finally, we lay out predictions derived from our disease recognition hypothesis that we encourage paleoanthropologists, bioarchaeologists, primatologists, and paleogeneticists to test. Copyright © 2017 Elsevier Ltd. All rights reserved.

A new pre-classification method based on associative matching method

NASA Astrophysics Data System (ADS)

Katsuyama, Yutaka; Minagawa, Akihiro; Hotta, Yoshinobu; Omachi, Shinichiro; Kato, Nei

2010-01-01

Reducing the time complexity of character matching is critical to the development of efficient Japanese Optical Character Recognition (OCR) systems. To shorten processing time, recognition is usually split into separate preclassification and recognition stages. For high overall recognition performance, the pre-classification stage must both have very high classification accuracy and return only a small number of putative character categories for further processing. Furthermore, for any practical system, the speed of the pre-classification stage is also critical. The associative matching (AM) method has often been used for fast pre-classification, because its use of a hash table and reliance solely on logical bit operations to select categories makes it highly efficient. However, redundant certain level of redundancy exists in the hash table because it is constructed using only the minimum and maximum values of the data on each axis and therefore does not take account of the distribution of the data. We propose a modified associative matching method that satisfies the performance criteria described above but in a fraction of the time by modifying the hash table to reflect the underlying distribution of training characters. Furthermore, we show that our approach outperforms pre-classification by clustering, ANN and conventional AM in terms of classification accuracy, discriminative power and speed. Compared to conventional associative matching, the proposed approach results in a 47% reduction in total processing time across an evaluation test set comprising 116,528 Japanese character images.

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

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

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

2009-01-01

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

Identification of computer-generated facial composites.

PubMed

Kovera, M B; Penrod, S D; Pappas, C; Thill, D L

1997-04-01

Two studies examined the effectiveness of the Mac-a-Mug Pro, a computerized facial composite production system. In the first study, college freshmen prepared from memory composites of other students and faculty from their former high schools. Other students who had attended the same high schools could not recognize the composites of either students or faculty members when the composites of individuals known to them (n = 10) were mixed with composites of a large number (n = 40) of strangers. Neither preparer familiarity with the target, preparer-assessed composite quality, nor viewer familiarity predicted composite recognition. Study 2 indicated that naive witnesses who viewed the composites could not select the people depicted in the composites from photo lineups (1 target and 4 foils). The results raise questions about the efficacy of composite systems as tools to promote recognition of suspects in criminal contexts.

Terrain type recognition using ERTS-1 MSS images

NASA Technical Reports Server (NTRS)

Gramenopoulos, N.

1973-01-01

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

A Structural and Mutagenic Blueprint for Molecular Recognition of Strychnine and d-Tubocurarine by Different Cys-Loop Receptors

PubMed Central

Kuzmin, Dmitry; van Elk, René; Krijnen, Liz; Yakel, Jerrel L.; Tsetlin, Victor; Smit, August B.; Ulens, Chris

2011-01-01

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-HT3R. PMID:21468359

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

PubMed

Brams, Marijke; Pandya, Anshul; Kuzmin, Dmitry; van Elk, René; Krijnen, Liz; Yakel, Jerrel L; Tsetlin, Victor; Smit, August B; Ulens, Chris

2011-03-01

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(3)R.

Strategic value-directed learning and memory in Alzheimer's disease and behavioural-variant frontotemporal dementia.

PubMed

Wong, Stephanie; Irish, Muireann; Savage, Greg; Hodges, John R; Piguet, Olivier; Hornberger, Michael

2018-02-12

In healthy adults, the ability to prioritize learning of highly valued information is supported by executive functions and enhances subsequent memory retrieval for this information. In Alzheimer's disease (AD) and behavioural-variant frontotemporal dementia (bvFTD), marked deficits are evident in learning and memory, presenting in the context of executive dysfunction. It is unclear whether these patients show a typical memory bias for higher valued stimuli. We administered a value-directed word-list learning task to AD (n = 10) and bvFTD (n = 21) patients and age-matched healthy controls (n = 22). Each word was assigned a low, medium or high point value, and participants were instructed to maximize the number of points earned across three learning trials. Participants' memory for the words was assessed on a delayed recall trial, followed by a recognition test for the words and corresponding point values. Relative to controls, both patient groups showed poorer overall learning, delayed recall and recognition. Despite these impairments, patients with AD preferentially recalled high-value words on learning trials and showed significant value-directed enhancement of recognition memory for the words and points. Conversely, bvFTD patients did not prioritize recall of high-value words during learning trials, and this reduced selectivity was related to inhibitory dysfunction. Nonetheless, bvFTD patients showed value-directed enhancement of recognition memory for the point values, suggesting a mismatch between memory of high-value information and the ability to apply this in a motivationally salient context. Our findings demonstrate that value-directed enhancement of memory may persist to some degree in patients with dementia, despite pronounced deficits in learning and memory. © 2018 The British Psychological Society.

Design and development of molecularly imprinted polymers for the selective extraction of deltamethrin in olive oil: An integrated computational-assisted approach.

PubMed

Martins, Nuno; Carreiro, Elisabete P; Locati, Abel; Ramalho, João P Prates; Cabrita, Maria João; Burke, Anthony J; Garcia, Raquel

2015-08-28

This work firstly addresses the design and development of molecularly imprinted systems selective for deltamethrin aiming to provide a suitable sorbent for solid phase (SPE) extraction that will be further used for the implementation of an analytical methodology for the trace analysis of the target pesticide in spiked olive oil samples. To achieve this goal, a preliminary evaluation of the molecular recognition and selectivity of the molecularly imprinted polymers has been performed. In order to investigate the complexity of the mechanistic basis for template selective recognition in these polymeric matrices, the use of a quantum chemical approach has been attempted providing new insights about the mechanisms underlying template recognition, and in particular the crucial role of the crosslinker agent and the solvent used. Thus, DFT calculations corroborate the results obtained by experimental molecular recognition assays enabling one to select the most suitable imprinting system for MISPE extraction technique which encompasses acrylamide as functional monomer and ethylene glycol dimethacrylate as crosslinker. Furthermore, an analytical methodology comprising a sample preparation step based on solid phase extraction has been implemented using this "tailor made" imprinting system as sorbent, for the selective isolation/pre-concentration of deltamethrin from olive oil samples. Molecularly imprinted solid phase extraction (MISPE) methodology was successfully applied for the clean-up of spiked olive oil samples, with recovery rates up to 94%. Copyright © 2015 Elsevier B.V. All rights reserved.

A simulation system to hide dynamic objects selectively at visible wavelengths

NASA Astrophysics Data System (ADS)

Cheng, Qiluan; Zhang, Shu; Ding, Chizhu; Tan, Zuojun; Wang, Guo Ping

2018-04-01

Currently, invisibility devices are increasingly approaching practical application requirements, such as using easily obtained materials for construction and hiding dynamic objects. Here, using phase retrieval and computer-generated holography techniques, we design an invisibility system in simulation to produce a phase-conjugation signal that changes with the dynamic object to hide it. This system is highly selective for the hidden objects, i.e., it only hides the target object and has no effect on the others. Such function may provide our invisibility system with great potential in special fields, such as biology and military applications for living and dynamic target recognition, selective camouflaging, and others.

Feature Selection on Hyperspectral Data for Dismount Skin Analysis

DTIC Science & Technology

2014-03-27

19 2.4.1 Melanosome Estimation . . . . . . . . . . . . . . . . . . . . . . . 19 2.4.2 Facial Recognition using...require compliant interaction in order to establish their identification. Previously, traditional facial recognition systems have been enhanced by HSI by...calculated as a fundamental method to differentiate between people [38]. In addition, the area of facial recognition has benefited from the rich spectral

Knowledge of a Second Language Influences Auditory Word Recognition in the Native Language

ERIC Educational Resources Information Center

Lagrou, Evelyne; Hartsuiker, Robert J.; Duyck, Wouter

2011-01-01

Many studies in bilingual visual word recognition have demonstrated that lexical access is not language selective. However, research on bilingual word recognition in the auditory modality has been scarce, and it has yielded mixed results with regard to the degree of this language nonselectivity. In the present study, we investigated whether…

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

Treesearch

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

2016-01-01

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

The recognition signal hypothesis for the adaptive evolution of religion : a phylogenetic test with Christian denominations.

PubMed

Matthews, Luke J

2012-06-01

Recent research on the evolution of religion has focused on whether religion is an unselected by-product of evolutionary processes or if it is instead an adaptation by natural selection. Adaptive hypotheses for religion include direct fitness benefits from improved health and indirect fitness benefits mediated by costly signals and/or cultural group selection. Herein, I propose that religious denominations achieve indirect fitness gains for members through the use of ecologically arbitrary beliefs, rituals, and moral rules that function as recognition markers of cultural inheritance analogous to kin and species recognition of genetic inheritance in biology. This recognition signal hypotheses could act in concert with either costly signaling or cultural group selection to produce evolutionarily altruistic behaviors within denominations. Using a cultural phylogenetic analysis, I show that a large set of religious behaviors among extant Christian denominations supports the prediction of the recognition signal hypothesis that characters change more frequently near historical schisms. By incorporating demographic data into the model, I show that more-distinctive denominations, as measured through dissimilar characteristics, appear to be protected from intrusion by nonmembers in mixed-denomination households, and that they may be experiencing greater biological growth of their populations even in the present day.

The influence of slavemaking lifestyle, caste and sex on chemical profiles in Temnothorax ants: insights into the evolution of cuticular hydrocarbons

PubMed Central

Kleeberg, Isabelle

2017-01-01

Chemical communication is central for the formation and maintenance of insect societies. Generally, social insects only allow nest-mates into their colony, which are recognized by their cuticular hydrocarbons (CHCs). Social parasites, which exploit insect societies, are selected to circumvent host recognition. Here, we studied whether chemical strategies to reduce recognition evolved convergently in slavemaking ants, and whether they extend to workers, queens and males alike. We studied CHCs of three social parasites and their related hosts to investigate whether the parasitic lifestyle selects for specific chemical traits that reduce host recognition. Slavemaker profiles were characterized by shorter-chained hydrocarbons and a shift from methyl-branched alkanes to n-alkanes, presumably to reduce recognition cue quantity. These shifts were consistent across independent origins of slavery and were found in isolated ants and those emerging in their mother colony. Lifestyle influenced profiles of workers most profoundly, with little effect on virgin queen profiles. We detected an across-species caste signal, with workers, for which nest-mate recognition is particularly important, carrying more and longer-chained hydrocarbons and males exhibiting a larger fraction of n-alkanes. This comprehensive study of CHCs across castes and species reveals how lifestyle-specific selection can result in convergent evolution of chemical phenotypes. PMID:28298345

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

PubMed

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.

Porous and magnetic molecularly imprinted polymers via Pickering high internal phase emulsions polymerization for selective adsorption of λ-cyhalothrin

NASA Astrophysics Data System (ADS)

Wu, Yunlong; Ma, Yue; Pan, Jianming; Gu, Runxing; Luo, Jialu

2017-03-01

A novel macroporous magnetic molecularly imprinted polymer (MMIPs) of was prepared by W/O Pickering (high internal phase emulsions) HIPEs polymerization, and then it was adopted as adsorbent for selective adsorption of λ-cyhalothrin (LC). In static conditions, adsorption capacity of LC increased rapidly in the first 60 min and reached to equilibrium in approximately 2.0 h. Excellent conformity of the second-order model confirmed the chemical nature of the interaction between the LC and imprinted sites. The fitting adsorption isotherm was a Langmuir type, and the maximum monolayer adsorption capacity at 298 K was 404.4 µmol g-1. Thermodynamic parameters suggested the specific adsorption at 298 K was an exothermic, spontaneous, and entropy decreased process. Competitive recognition studies of the MMIPs were performed with diethyl phthalate (DEP) and the structurally similar compound fenvalerate (FL), and the MMIPs, which displayed high selectivity for LC.

Porous and Magnetic Molecularly Imprinted Polymers via Pickering High Internal Phase Emulsions Polymerization for Selective Adsorption of λ-Cyhalothrin.

PubMed

Wu, Yunlong; Ma, Yue; Pan, Jianming; Gu, Runxing; Luo, Jialu

2017-01-01

A novel macroporous magnetic molecularly imprinted polymer (MMIPs) of was prepared by W/O Pickering (high internal phase emulsions) HIPEs polymerization, and then it was adopted as adsorbent for selective adsorption of λ-cyhalothrin (LC). In static conditions, adsorption capacity of LC increased rapidly in the first 60 min and reached to equilibrium in ~2.0 h. Excellent conformity of the second-order model confirmed the chemical nature of the interaction between the LC and imprinted sites. The fitting adsorption isotherm was a Langmuir type, and the maximum monolayer adsorption capacity at 298 K was 404.4 μmol g -1 . Thermodynamic parameters suggested the specific adsorption at 298 K was an exothermic, spontaneous, and entropy decreased process. Competitive recognition studies of the MMIPs were performed with diethyl phthalate (DEP) and the structurally similar compound fenvalerate (FL), and the MMIPs, which displayed high selectivity for LC.

Porous and Magnetic Molecularly Imprinted Polymers via Pickering High Internal Phase Emulsions Polymerization for Selective Adsorption of λ-Cyhalothrin

PubMed Central

Wu, Yunlong; Ma, Yue; Pan, Jianming; Gu, Runxing; Luo, Jialu

2017-01-01

A novel macroporous magnetic molecularly imprinted polymer (MMIPs) of was prepared by W/O Pickering (high internal phase emulsions) HIPEs polymerization, and then it was adopted as adsorbent for selective adsorption of λ-cyhalothrin (LC). In static conditions, adsorption capacity of LC increased rapidly in the first 60 min and reached to equilibrium in ~2.0 h. Excellent conformity of the second-order model confirmed the chemical nature of the interaction between the LC and imprinted sites. The fitting adsorption isotherm was a Langmuir type, and the maximum monolayer adsorption capacity at 298 K was 404.4 μmol g−1. Thermodynamic parameters suggested the specific adsorption at 298 K was an exothermic, spontaneous, and entropy decreased process. Competitive recognition studies of the MMIPs were performed with diethyl phthalate (DEP) and the structurally similar compound fenvalerate (FL), and the MMIPs, which displayed high selectivity for LC. PMID:28401145

A face and palmprint recognition approach based on discriminant DCT feature extraction.

PubMed

Jing, Xiao-Yuan; Zhang, David

2004-12-01

In the field of image processing and recognition, discrete cosine transform (DCT) and linear discrimination are two widely used techniques. Based on them, we present a new face and palmprint recognition approach in this paper. It first uses a two-dimensional separability judgment to select the DCT frequency bands with favorable linear separability. Then from the selected bands, it extracts the linear discriminative features by an improved Fisherface method and performs the classification by the nearest neighbor classifier. We detailedly analyze theoretical advantages of our approach in feature extraction. The experiments on face databases and palmprint database demonstrate that compared to the state-of-the-art linear discrimination methods, our approach obtains better classification performance. It can significantly improve the recognition rates for face and palmprint data and effectively reduce the dimension of feature space.

Preparation of ellagic acid molecularly imprinted polymeric microspheres based on distillation-precipitation polymerization for the efficient purification of a crude extract.

PubMed

Zhang, Hua; Zhao, Shangge; Zhang, Lu; Han, Bo; Yao, Xincheng; Chen, Wen; Hu, Yanli

2016-08-01

Molecularly imprinted polymeric microspheres with a high recognition ability toward the template molecule, ellagic acid, were synthesized based on distillation-precipitation polymerization. The as-obtained polymers were characterized by scanning electron microscopy, infrared spectroscopy, and thermogravimetric analysis. Static, dynamic, and selective binding tests were adopted to study the binding properties and the molecular recognition ability of the prepared polymers for ellagic acid. The results indicated that the maximum static adsorption capacity of the prepared polymers toward ellagic acid was 37.07 mg/g and the adsorption equilibrium time was about 100 min when the concentration of ellagic acid was 40 mg/mL. Molecularly imprinted polymeric microspheres were also highly selective toward ellagic acid compared with its analogue quercetin. It was found that the content of ellagic acid in the pomegranate peel extract was enhanced from 23 to 86% after such molecularly imprinted solid-phase extraction process. This work provides an efficient way for effective separation and enrichment of ellagic acid from complex matrix, which is especially valuable in industrial production. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimizing one-shot learning with binary synapses.

PubMed

Romani, Sandro; Amit, Daniel J; Amit, Yali

2008-08-01

A network of excitatory synapses trained with a conservative version of Hebbian learning is used as a model for recognizing the familiarity of thousands of once-seen stimuli from those never seen before. Such networks were initially proposed for modeling memory retrieval (selective delay activity). We show that the same framework allows the incorporation of both familiarity recognition and memory retrieval, and estimate the network's capacity. In the case of binary neurons, we extend the analysis of Amit and Fusi (1994) to obtain capacity limits based on computations of signal-to-noise ratio of the field difference between selective and non-selective neurons of learned signals. We show that with fast learning (potentiation probability approximately 1), the most recently learned patterns can be retrieved in working memory (selective delay activity). A much higher number of once-seen learned patterns elicit a realistic familiarity signal in the presence of an external field. With potentiation probability much less than 1 (slow learning), memory retrieval disappears, whereas familiarity recognition capacity is maintained at a similarly high level. This analysis is corroborated in simulations. For analog neurons, where such analysis is more difficult, we simplify the capacity analysis by studying the excess number of potentiated synapses above the steady-state distribution. In this framework, we derive the optimal constraint between potentiation and depression probabilities that maximizes the capacity.

Coding of visual object features and feature conjunctions in the human brain.

PubMed

Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

2008-01-01

Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

Molecular recognition principles and stationary-phase characteristics of topoisomer-selective chemoaffinity materials for chromatographic separation of circular plasmid DNA topoisomers.

PubMed

Mahut, Marek; Lindner, Wolfgang; Lämmerhofer, Michael

2012-01-18

We recently discovered the molecular recognition capability of a quinine carbamate ligand attached to silica as a powerful chemoaffinity material for the chromatographic separation of circular plasmid topoisomers of different linking numbers. In this paper we develop structure-selectivity relationship studies to figure out the essential structural features for topoisomer recognition. By varying different moieties of the original cinchonan-derived selector, it was shown that intercalation by the quinoline moiety of the ligand as assumed initially as the working hypothesis is not an essential feature for topoisomer recognition during chromatography. We found that the key elements for topoisomer selectivity are the presence of a rigid weak anion-exchange site and a H-donor site separated from each other in a defined distance by a 4-atom spacer. Additionally, incorporation of the weak anion-exchange site into a cyclic ring structure provides greater rigidity of the ligand molecule and turned out to be advantageous, if not mandatory, for (close to) baseline separation. © 2011 American Chemical Society

Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

PubMed

Li, Baopu; Meng, Max Q-H

2012-05-01

Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

Four base recognition by triplex-forming oligonucleotides at physiological pH

PubMed Central

Rusling, David A.; Powers, Vicki E. C.; Ranasinghe, Rohan T.; Wang, Yang; Osborne, Sadie D.; Brown, Tom; Fox, Keith R.

2005-01-01

We have achieved recognition of all 4 bp by triple helix formation at physiological pH, using triplex-forming oligonucleotides that contain four different synthetic nucleotides. BAU [2′-aminoethoxy-5-(3-aminoprop-1-ynyl)uridine] recognizes AT base pairs with high affinity, MeP (3-methyl-2 aminopyridine) binds to GC at higher pHs than cytosine, while APP (6-(3-aminopropyl)-7-methyl-3H-pyrrolo[2,3-d]pyrimidin-2(7H)-one) and S [N-(4-(3-acetamidophenyl)thiazol-2-yl-acetamide)] bind to CG and TA base pairs, respectively. Fluorescence melting and DNase I footprinting demonstrate successful triplex formation at a 19mer oligopurine sequence that contains two CG and two TA interruptions. The complexes are pH dependent, but are still stable at pH 7.0. BAU, MeP and APP retain considerable selectivity, and single base pair changes opposite these residues cause a large reduction in affinity. In contrast, S is less selective and tolerates CG pairs as well as TA. PMID:15911633

Detection of glycoprotein using fiber optic surface plasmon resonance sensors with boronic acid

NASA Astrophysics Data System (ADS)

Wang, Fang; Zhang, Yang; Liu, Zigeng; Qian, Siyu; Gu, Yiying; Jing, Zhenguo; Sun, Changsen; Peng, Wei

2017-04-01

In this paper, we present a tilted fiber Bragg gratings (TFBG) based surface Plasmon resonance (SPR) label-free sensors with boronic acid derivative (ABA-PBA) as receptor molecule to detect glycoprotein with high sensitivity and selectivity. Tilted fiber Bragg gratings (TFBG) as a near infrared wavelengths detecting element can be able to excite a number of cladding modes whose properties can be detected accurately by measuring the variation of transmitted spectra. A 10° TFBG coated by 50nm gold film was manufactured to stimulate surface plasmon resonance on the surface of the sensor. The sensor was loaded with boronic acid derivative as the recognition molecule which has been widely used in various areas for the recognition matrix of diol-containing biomolecules. The proposed TFBG-SPR sensors exhibit good selectivity and repeatability with the protein concentration sensitivity up to 2.867dB/ (mg/ml) and the limit of detection was 2*10-5g/ml.

Physical Activity Recognition with Mobile Phones: Challenges, Methods, and Applications

NASA Astrophysics Data System (ADS)

Yang, Jun; Lu, Hong; Liu, Zhigang; Boda, Péter Pál

In this book chapter, we present a novel system that recognizes and records the physical activity of a person using a mobile phone. The sensor data is collected by built-in accelerometer sensor that measures the motion intensity of the device. The system recognizes five everyday activities in real-time, i.e., stationary, walking, running, bicycling, and in vehicle. We first introduce the sensor's data format, sensor calibration, signal projection, feature extraction, and selection methods. Then we have a detailed discussion and comparison of different choices of feature sets and classifiers. The design and implementation of one prototype system is presented along with resource and performance benchmark on Nokia N95 platform. Results show high recognition accuracies for distinguishing the five activities. The last part of the chapter introduces one demo application built on top of our system, physical activity diary, and a selection of potential applications in mobile wellness, mobile social sharing and contextual user interface domains.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters

PubMed Central

Rempel, David; Camilleri, Matt J.; Lee, David L.

2015-01-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input. PMID:26028955

Matrine- and oxymatrine-imprinted monodisperse polymers prepared by precipitation polymerization and their applications for the selective extraction of matrine-type alkaloids from Sophora flavescens Aiton.

PubMed

Funaya, Noriko; Haginaka, Jun

2012-07-27

Matrine (MT)- and oxymatrine (OMT)-imprinted monodisperse polymers have been prepared by precipitation polymerization. The prepared molecularly imprinted polymers (MIPs) for MT and OMT, MIP(MT) and MIP(OMT), were monodispersed microspheres of 3.3 and 3.9 μm in diameter, respectively. Binding experiments and Scatchard analyses revealed that two classes of binding sites were formed on MIP(MT) and MIP(OMT). In addition to shape recognition, ionic and hydrophobic interactions seemed to affect the retention and recognition of MT and OMT on MIP(MT) and MIP(OMT), respectively, in low acetonitrile content, and ionic and hydrophilic interactions affected these properties in high acetonitrile content. MIP(MT) was used to selectively extract MT and sophocarpine (13,14-dehydromatrine) from Sophora flavescens root, while MIP(OMT) was used to extract OMT and oxysophocarpine (13,14-dehydrooxymatrine). Copyright © 2012 Elsevier B.V. All rights reserved.

Nonlinear frequency compression: Influence of start frequency and input bandwidth on consonant and vowel recognitiona)

PubMed Central

Alexander, Joshua M.

2016-01-01

By varying parameters that control nonlinear frequency compression (NFC), this study examined how different ways of compressing inaudible mid- and/or high-frequency information at lower frequencies influences perception of consonants and vowels. Twenty-eight listeners with mild to moderately severe hearing loss identified consonants and vowels from nonsense syllables in noise following amplification via a hearing aid simulator. Low-pass filtering and the selection of NFC parameters fixed the output bandwidth at a frequency representing a moderately severe (3.3 kHz, group MS) or a mild-to-moderate (5.0 kHz, group MM) high-frequency loss. For each group (n = 14), effects of six combinations of NFC start frequency (SF) and input bandwidth [by varying the compression ratio (CR)] were examined. For both groups, the 1.6 kHz SF significantly reduced vowel and consonant recognition, especially as CR increased; whereas, recognition was generally unaffected if SF increased at the expense of a higher CR. Vowel recognition detriments for group MS were moderately correlated with the size of the second formant frequency shift following NFC. For both groups, significant improvement (33%–50%) with NFC was confined to final /s/ and /z/ and to some VCV tokens, perhaps because of listeners' limited exposure to each setting. No set of parameters simultaneously maximized recognition across all tokens. PMID:26936574

Spatiotemporal dynamics underlying object completion in human ventral visual cortex.

PubMed

Tang, Hanlin; Buia, Calin; Madhavan, Radhika; Crone, Nathan E; Madsen, Joseph R; Anderson, William S; Kreiman, Gabriel

2014-08-06

Natural vision often involves recognizing objects from partial information. Recognition of objects from parts presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. Here we recorded intracranial field potentials of 113 visually selective electrodes from epilepsy patients in response to whole and partial objects. Responses along the ventral visual stream, particularly the inferior occipital and fusiform gyri, remained selective despite showing only 9%-25% of the object areas. However, these visually selective signals emerged ∼100 ms later for partial versus whole objects. These processing delays were particularly pronounced in higher visual areas within the ventral stream. This latency difference persisted when controlling for changes in contrast, signal amplitude, and the strength of selectivity. These results argue against a purely feedforward explanation of recognition from partial information, and provide spatiotemporal constraints on theories of object recognition that involve recurrent processing. Copyright © 2014 Elsevier Inc. All rights reserved.

A microfluidic chip containing a molecularly imprinted polymer and a DNA aptamer for voltammetric determination of carbofuran.

PubMed

Li, Shuhuai; Li, Jianping; Luo, Jinhui; Xu, Zhi; Ma, Xionghui

2018-05-11

An electrochemical microfluidic chip is described for the determination of the insecticide carbofuran. It is making use of a molecularly imprinted film (MIP) and a DNA aptamer as dual recognition units. The analyte (carbofuran) is transported to the MIP and captured at the identification site in the channel. Then, carbofuran is eluted with carbinol-acetic acid and transported to the DNA aptamer on the testing position of the chip. It is captured again, this time by the aptamer, and detected by differential pulse voltammetry (DPV). The dual recognition (by aptamer and MIP) results in outstanding selectivity. Additionally, graphene oxide-supported gold nanoparticles (GO-AuNPs) were used to improve the sensitivity of electrochemical detector. DPV response is linear in the 0.2 to 50 nM carbofuran concentration range at a potential of -1.2 V, with a 67 pM detection limit. The method has attractive features such as its potential for high throughput, high degree of automation, and high integration. Conceivably, the method may be extended to other analytes for which appropriate MIPs and aptamers are available. Graphical abstract Schematic of an electrochemical microfluidic chip for carbofuran detection based on a molecularly imprinted film (MIP) and a DNA aptamer as dual recognition units. In the chip, targets were recognized by MIP and aptamer, respectively. It shows promising potential for the design of electrochemical devices with high throughput, high automation, and high integration.

Under what conditions is recognition spared relative to recall after selective hippocampal damage in humans?

PubMed

Holdstock, J S; Mayes, A R; Roberts, N; Cezayirli, E; Isaac, C L; O'Reilly, R C; Norman, K A

2002-01-01

The claim that recognition memory is spared relative to recall after focal hippocampal damage has been disputed in the literature. We examined this claim by investigating object and object-location recall and recognition memory in a patient, YR, who has adult-onset selective hippocampal damage. Our aim was to identify the conditions under which recognition was spared relative to recall in this patient. She showed unimpaired forced-choice object recognition but clearly impaired recall, even when her control subjects found the object recognition task to be numerically harder than the object recall task. However, on two other recognition tests, YR's performance was not relatively spared. First, she was clearly impaired at an equivalently difficult yes/no object recognition task, but only when targets and foils were very similar. Second, YR was clearly impaired at forced-choice recognition of object-location associations. This impairment was also unrelated to difficulty because this task was no more difficult than the forced-choice object recognition task for control subjects. The clear impairment of yes/no, but not of forced-choice, object recognition after focal hippocampal damage, when targets and foils are very similar, is predicted by the neural network-based Complementary Learning Systems model of recognition. This model postulates that recognition is mediated by hippocampally dependent recollection and cortically dependent familiarity; thus hippocampal damage should not impair item familiarity. The model postulates that familiarity is ineffective when very similar targets and foils are shown one at a time and subjects have to identify which items are old (yes/no recognition). In contrast, familiarity is effective in discriminating which of similar targets and foils, seen together, is old (forced-choice recognition). Independent evidence from the remember/know procedure also indicates that YR's familiarity is normal. The Complementary Learning Systems model can also accommodate the clear impairment of forced-choice object-location recognition memory if it incorporates the view that the most complete convergence of spatial and object information, represented in different cortical regions, occurs in the hippocampus.

Two-color SERS microscopy for protein co-localization in prostate tissue with primary antibody-protein A/G-gold nanocluster conjugates

NASA Astrophysics Data System (ADS)

Salehi, Mohammad; Schneider, Lilli; Ströbel, Philipp; Marx, Alexander; Packeisen, Jens; Schlücker, Sebastian

2014-01-01

SERS microscopy is a novel staining technique in immunohistochemistry, which is based on antibodies labeled with functionalized noble metal colloids called SERS labels or nanotags for optical detection. Conventional covalent bioconjugation of these SERS labels cannot prevent blocking of the antigen recognition sites of the antibody. We present a rational chemical design for SERS label-antibody conjugates which addresses this issue. Highly sensitive, silica-coated gold nanoparticle clusters as SERS labels are non-covalently conjugated to primary antibodies by using the chimeric protein A/G, which selectively recognizes the Fc part of antibodies and therefore prevents blocking of the antigen recognition sites. In proof-of-concept two-color imaging experiments for the co-localization of p63 and PSA on non-neoplastic prostate tissue FFPE specimens, we demonstrate the specificity and signal brightness of these rationally designed primary antibody-protein A/G-gold nanocluster conjugates.SERS microscopy is a novel staining technique in immunohistochemistry, which is based on antibodies labeled with functionalized noble metal colloids called SERS labels or nanotags for optical detection. Conventional covalent bioconjugation of these SERS labels cannot prevent blocking of the antigen recognition sites of the antibody. We present a rational chemical design for SERS label-antibody conjugates which addresses this issue. Highly sensitive, silica-coated gold nanoparticle clusters as SERS labels are non-covalently conjugated to primary antibodies by using the chimeric protein A/G, which selectively recognizes the Fc part of antibodies and therefore prevents blocking of the antigen recognition sites. In proof-of-concept two-color imaging experiments for the co-localization of p63 and PSA on non-neoplastic prostate tissue FFPE specimens, we demonstrate the specificity and signal brightness of these rationally designed primary antibody-protein A/G-gold nanocluster conjugates. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr05890e

Molecular imprinting ratiometric fluorescence sensor for highly selective and sensitive detection of phycocyanin.

PubMed

Wang, Xiaoyan; Yu, Jialuo; Kang, Qi; Shen, Dazhong; Li, Jinhua; Chen, Lingxin

2016-03-15

A facile strategy was developed to prepare molecular imprinting ratiometric fluorescence sensor for highly selective and sensitive detection of phycocyanin (PC) based on fluorescence resonance energy transfer (FRET), via a sol-gel polymerization process using nitrobenzoxadiazole (NBD) as fluorescent signal source. The ratio of two fluorescence peak emission intensities of NBD and PC was utilized to determine the concentration of PC, which could effectively reduce the background interference and fluctuation of diverse conditions. As a result, this sensor obtained high sensitivity with a low detection limit of 0.14 nM within 6 min, and excellent recognition specificity for PC over its analogues with a high imprinting factor of 9.1. Furthermore, the sensor attained high recoveries in the range of 93.8-110.2% at three spiking levels of PC, with precisions below 4.7% in seawater and lake water samples. The developed sensor strategy demonstrated simplicity, reliability, rapidity, high selectivity and high sensitivity, proving to be a feasible way to develop high efficient fluorescence sensors and thus potentially applicable for ultratrace analysis of complicated matrices. Copyright © 2015 Elsevier B.V. All rights reserved.

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

PubMed

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

2016-09-22

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

Crossing borders to bind proteins--a new concept in protein recognition based on the conjugation of small organic molecules or short peptides to polypeptides from a designed set.

PubMed

Baltzer, Lars

2011-06-01

A new concept for protein recognition and binding is highlighted. The conjugation of small organic molecules or short peptides to polypeptides from a designed set provides binder molecules that bind proteins with high affinities, and with selectivities that are equal to those of antibodies. The small organic molecules or peptides need to bind the protein targets but only with modest affinities and selectivities, because conjugation to the polypeptides results in molecules with dramatically improved binder performance. The polypeptides are selected from a set of only sixteen sequences designed to bind, in principle, any protein. The small number of polypeptides used to prepare high-affinity binders contrasts sharply with the huge libraries used in binder technologies based on selection or immunization. Also, unlike antibodies and engineered proteins, the polypeptides have unordered three-dimensional structures and adapt to the proteins to which they bind. Binder molecules for the C-reactive protein, human carbonic anhydrase II, acetylcholine esterase, thymidine kinase 1, phosphorylated proteins, the D-dimer, and a number of antibodies are used as examples to demonstrate that affinities are achieved that are higher than those of the small molecules or peptides by as much as four orders of magnitude. Evaluation by pull-down experiments and ELISA-based tests in human serum show selectivities to be equal to those of antibodies. Small organic molecules and peptides are readily available from pools of endogenous ligands, enzyme substrates, inhibitors or products, from screened small molecule libraries, from phage display, and from mRNA display. The technology is an alternative to established binder concepts for applications in drug development, diagnostics, medical imaging, and protein separation.

a Fully Automated Pipeline for Classification Tasks with AN Application to Remote Sensing

NASA Astrophysics Data System (ADS)

Suzuki, K.; Claesen, M.; Takeda, H.; De Moor, B.

2016-06-01

Nowadays deep learning has been intensively in spotlight owing to its great victories at major competitions, which undeservedly pushed `shallow' machine learning methods, relatively naive/handy algorithms commonly used by industrial engineers, to the background in spite of their facilities such as small requisite amount of time/dataset for training. We, with a practical point of view, utilized shallow learning algorithms to construct a learning pipeline such that operators can utilize machine learning without any special knowledge, expensive computation environment, and a large amount of labelled data. The proposed pipeline automates a whole classification process, namely feature-selection, weighting features and the selection of the most suitable classifier with optimized hyperparameters. The configuration facilitates particle swarm optimization, one of well-known metaheuristic algorithms for the sake of generally fast and fine optimization, which enables us not only to optimize (hyper)parameters but also to determine appropriate features/classifier to the problem, which has conventionally been a priori based on domain knowledge and remained untouched or dealt with naïve algorithms such as grid search. Through experiments with the MNIST and CIFAR-10 datasets, common datasets in computer vision field for character recognition and object recognition problems respectively, our automated learning approach provides high performance considering its simple setting (i.e. non-specialized setting depending on dataset), small amount of training data, and practical learning time. Moreover, compared to deep learning the performance stays robust without almost any modification even with a remote sensing object recognition problem, which in turn indicates that there is a high possibility that our approach contributes to general classification problems.

Acute effects of delta-9-tetrahydrocannabinol, cannabidiol and their combination on facial emotion recognition: a randomised, double-blind, placebo-controlled study in cannabis users.

PubMed

Hindocha, Chandni; Freeman, Tom P; Schafer, Grainne; Gardener, Chelsea; Das, Ravi K; Morgan, Celia J A; Curran, H Valerie

2015-03-01

Acute administration of the primary psychoactive constituent of cannabis, Δ-9-tetrahydrocannabinol (THC), impairs human facial affect recognition, implicating the endocannabinoid system in emotional processing. Another main constituent of cannabis, cannabidiol (CBD), has seemingly opposite functional effects on the brain. This study aimed to determine the effects of THC and CBD, both alone and in combination on emotional facial affect recognition. 48 volunteers, selected for high and low frequency of cannabis use and schizotypy, were administered, THC (8mg), CBD (16mg), THC+CBD (8mg+16mg) and placebo, by inhalation, in a 4-way, double-blind, placebo-controlled crossover design. They completed an emotional facial affect recognition task including fearful, angry, happy, sad, surprise and disgust faces varying in intensity from 20% to 100%. A visual analogue scale (VAS) of feeling 'stoned' was also completed. In comparison to placebo, CBD improved emotional facial affect recognition at 60% emotional intensity; THC was detrimental to the recognition of ambiguous faces of 40% intensity. The combination of THC+CBD produced no impairment. Relative to placebo, both THC alone and combined THC+CBD equally increased feelings of being 'stoned'. CBD did not influence feelings of 'stoned'. No effects of frequency of use or schizotypy were found. In conclusion, CBD improves recognition of emotional facial affect and attenuates the impairment induced by THC. This is the first human study examining the effects of different cannabinoids on emotional processing. It provides preliminary evidence that different pharmacological agents acting upon the endocannabinoid system can both improve and impair recognition of emotional faces. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Acute effects of delta-9-tetrahydrocannabinol, cannabidiol and their combination on facial emotion recognition: A randomised, double-blind, placebo-controlled study in cannabis users

PubMed Central

Hindocha, Chandni; Freeman, Tom P.; Schafer, Grainne; Gardener, Chelsea; Das, Ravi K.; Morgan, Celia J.A.; Curran, H. Valerie

2015-01-01

Acute administration of the primary psychoactive constituent of cannabis, Δ-9-tetrahydrocannabinol (THC), impairs human facial affect recognition, implicating the endocannabinoid system in emotional processing. Another main constituent of cannabis, cannabidiol (CBD), has seemingly opposite functional effects on the brain. This study aimed to determine the effects of THC and CBD, both alone and in combination on emotional facial affect recognition. 48 volunteers, selected for high and low frequency of cannabis use and schizotypy, were administered, THC (8 mg), CBD (16 mg), THC+CBD (8 mg+16 mg) and placebo, by inhalation, in a 4-way, double-blind, placebo-controlled crossover design. They completed an emotional facial affect recognition task including fearful, angry, happy, sad, surprise and disgust faces varying in intensity from 20% to 100%. A visual analogue scale (VAS) of feeling ‘stoned’ was also completed. In comparison to placebo, CBD improved emotional facial affect recognition at 60% emotional intensity; THC was detrimental to the recognition of ambiguous faces of 40% intensity. The combination of THC+CBD produced no impairment. Relative to placebo, both THC alone and combined THC+CBD equally increased feelings of being ‘stoned’. CBD did not influence feelings of ‘stoned’. No effects of frequency of use or schizotypy were found. In conclusion, CBD improves recognition of emotional facial affect and attenuates the impairment induced by THC. This is the first human study examining the effects of different cannabinoids on emotional processing. It provides preliminary evidence that different pharmacological agents acting upon the endocannabinoid system can both improve and impair recognition of emotional faces. PMID:25534187

The Moving Window Technique: A Window into Developmental Changes in Attention during Facial Emotion Recognition

ERIC Educational Resources Information Center

Birmingham, Elina; Meixner, Tamara; Iarocci, Grace; Kanan, Christopher; Smilek, Daniel; Tanaka, James W.

2013-01-01

The strategies children employ to selectively attend to different parts of the face may reflect important developmental changes in facial emotion recognition. Using the Moving Window Technique (MWT), children aged 5-12 years and adults ("N" = 129) explored faces with a mouse-controlled window in an emotion recognition task. An…

iFER: facial expression recognition using automatically selected geometric eye and eyebrow features

NASA Astrophysics Data System (ADS)

Oztel, Ismail; Yolcu, Gozde; Oz, Cemil; Kazan, Serap; Bunyak, Filiz

2018-03-01

Facial expressions have an important role in interpersonal communications and estimation of emotional states or intentions. Automatic recognition of facial expressions has led to many practical applications and became one of the important topics in computer vision. We present a facial expression recognition system that relies on geometry-based features extracted from eye and eyebrow regions of the face. The proposed system detects keypoints on frontal face images and forms a feature set using geometric relationships among groups of detected keypoints. Obtained feature set is refined and reduced using the sequential forward selection (SFS) algorithm and fed to a support vector machine classifier to recognize five facial expression classes. The proposed system, iFER (eye-eyebrow only facial expression recognition), is robust to lower face occlusions that may be caused by beards, mustaches, scarves, etc. and lower face motion during speech production. Preliminary experiments on benchmark datasets produced promising results outperforming previous facial expression recognition studies using partial face features, and comparable results to studies using whole face information, only slightly lower by ˜ 2.5 % compared to the best whole face facial recognition system while using only ˜ 1 / 3 of the facial region.

Identities of P2 and P3 Residues of H-2Kb-Bound Peptides Determine Mouse Ly49C Recognition

PubMed Central

Marquez, Elsa A.; Kane, Kevin P.

2015-01-01

Ly49 receptors can be peptide selective in their recognition of MHC-I-peptide complexes, affording them a level of discrimination beyond detecting the presence or absence of specific MHC-I allele products. Despite this ability, little is understood regarding the properties that enable some peptides, when bound to MHC-I molecules, to support Ly49 recognition, but not others. Using RMA-S target cells expressing MHC-I molecules loaded with individual peptides and effector cells expressing the ectodomain of the inhibitory Ly49C receptor, we found that two adjacent amino acid residues, P2 and P3, both buried in the peptide binding groove of H-2Kb, determine mouse Ly49C specificity. If both are aliphatic residues, this is supportive. Whereas, small amino acids at P2 and aromatic amino acids at the P3 auxiliary anchor residue are detrimental to Ly49C recognition. These results resemble those with a rat Ly49 where the identity of a peptide anchor residue determines recognition, suggesting that dependence on specific peptide residues buried in the MHC-I peptide-binding groove may be fundamental to Ly49 peptide selectivity and recognition. PMID:26147851

Balancing Selection at the Tomato RCR3 Guardee Gene Family Maintains Variation in Strength of Pathogen Defense

PubMed Central

Hörger, Anja C.; Ilyas, Muhammad; Stephan, Wolfgang; Tellier, Aurélien; van der Hoorn, Renier A. L.; Rose, Laura E.

2012-01-01

Coevolution between hosts and pathogens is thought to occur between interacting molecules of both species. This results in the maintenance of genetic diversity at pathogen antigens (or so-called effectors) and host resistance genes such as the major histocompatibility complex (MHC) in mammals or resistance (R) genes in plants. In plant–pathogen interactions, the current paradigm posits that a specific defense response is activated upon recognition of pathogen effectors via interaction with their corresponding R proteins. According to the “Guard-Hypothesis,” R proteins (the “guards”) can sense modification of target molecules in the host (the “guardees”) by pathogen effectors and subsequently trigger the defense response. Multiple studies have reported high genetic diversity at R genes maintained by balancing selection. In contrast, little is known about the evolutionary mechanisms shaping the guardee, which may be subject to contrasting evolutionary forces. Here we show that the evolution of the guardee RCR3 is characterized by gene duplication, frequent gene conversion, and balancing selection in the wild tomato species Solanum peruvianum. Investigating the functional characteristics of 54 natural variants through in vitro and in planta assays, we detected differences in recognition of the pathogen effector through interaction with the guardee, as well as substantial variation in the strength of the defense response. This variation is maintained by balancing selection at each copy of the RCR3 gene. Our analyses pinpoint three amino acid polymorphisms with key functional consequences for the coevolution between the guardee (RCR3) and its guard (Cf-2). We conclude that, in addition to coevolution at the “guardee-effector” interface for pathogen recognition, natural selection acts on the “guard-guardee” interface. Guardee evolution may be governed by a counterbalance between improved activation in the presence and prevention of auto-immune responses in the absence of the corresponding pathogen. PMID:22829777

A new fluorescent probe for distinguishing Zn2+ and Cd2+ with high sensitivity and selectivity.

PubMed

Tan, Yiqun; Gao, Junkuo; Yu, Jiancan; Wang, Ziqi; Cui, Yuanjing; Yang, Yu; Qian, Guodong

2013-08-28

A new fluorescence probe for distinguishing Zn(2+) and Cd(2+) is designed and synthesized. For the first time to our knowledge, this probe can recognize similar metal ions by coherently utilizing intramolecular charge transfer (ICT) and different electronic affinities of various metal ions, instead of by selective coordination alone, which may be interfered with and lose its selectivity easily in a complicated environment, providing a distinct recognition even by the naked eye for Zn(2+) and Cd(2+) with the sensitivity at the ppb level. This design strategy may initiate a straightforward approach for the selective detection of various metal ions with similar chemical properties in extensive applications such as environmental, industrial, and bio-science.

Enzyme-Encapsulated Liposome-Linked Immunosorbent Assay Enabling Sensitive Personal Glucose Meter Readout for Portable Detection of Disease Biomarkers.

PubMed

Lin, Bingqian; Liu, Dan; Yan, Jinmao; Qiao, Zhi; Zhong, Yunxin; Yan, Jiawei; Zhu, Zhi; Ji, Tianhai; Yang, Chaoyong James

2016-03-23

There is considerable demand for sensitive, selective, and portable detection of disease-associated proteins, particularly in clinical practice and diagnostic applications. Portable devices are highly desired for detection of disease biomarkers in daily life due to the advantages of being simple, rapid, user-friendly, and low-cost. Herein we report an enzyme-encapsulated liposome-linked immunosorbent assay for sensitive detection of proteins using personal glucose meters (PGM) for portable quantitative readout. Liposomes encapsulating a large amount of amyloglucosidase or invertase are surface-coated with recognition elements such as aptamers or antibodies for target recognition. By translating molecular recognition signal into a large amount of glucose with the encapsulated enzyme, disease biomarkers such as thrombin or C-reactive protein (CRP) can be quantitatively detected by a PGM with a high detection limit of 1.8 or 0.30 nM, respectively. With the advantages of portability, ease of use, and low-cost, the method reported here has potential for portable and quantitative detection of various targets for different POC testing scenarios, such as rapid diagnosis in clinic offices, health monitoring at the bedside, and chemical/biochemical safety control in the field.

Magnet® Hospital Recognition Linked to Lower Central Line-Associated Bloodstream Infection Rates

PubMed Central

Barnes, Hilary; Rearden, Jessica; McHugh, Matthew D.

2016-01-01

Central-line-associated bloodstream infections (CLABSI) are among the deadliest heathcare-associated infections, with an estimated 12–25% mortality rate. In 2014, the Centers for Medicare and Medicaid Services (CMS) began to penalize hospitals for poor performance with respect to selected hospital-acquired conditions, including CLABSI. A structural factor associated with high-quality nursing care and better patient outcomes is The Magnet Recognition Program®. The purpose of this study was to explore the relationship between Magnet status and hospital CLABSI rates. We used propensity score matching to match Magnet and non-Magnet hospitals with similar hospital characteristics. In a matched sample of 291 Magnet hospitals and 291 non-Magnet hospitals, logistic regression models were used to examine whether there was a link between Magnet status and CLABSI rates. Both before and after matching, Magnet hospital status was associated with better (lower than the national average) CLABSI rates (OR = 1.60, 95% CI: 1.10, 2.33 after matching). While established programs such as Magnet recognition are consistently correlated with high-quality nursing work environments and positive patient outcomes, additional research is needed to determine whether Magnet designation produces positive patient outcomes or rewards existing excellence. PMID:26809115

Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2008-08-01

This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition. A curve evolution approach is proposed to effectively segment a nonideal iris image using the modified Mumford-Shah functional. Different enhancement algorithms are concurrently applied on the segmented iris image to produce multiple enhanced versions of the iris image. A support-vector-machine-based learning algorithm selects locally enhanced regions from each globally enhanced image and combines these good-quality regions to create a single high-quality iris image. Two distinct features are extracted from the high-quality iris image. The global textural feature is extracted using the 1-D log polar Gabor transform, and the local topological feature is extracted using Euler numbers. An intelligent fusion algorithm combines the textural and topological matching scores to further improve the iris recognition performance and reduce the false rejection rate, whereas an indexing algorithm enables fast and accurate iris identification. The verification and identification performance of the proposed algorithms is validated and compared with other algorithms using the CASIA Version 3, ICE 2005, and UBIRIS iris databases.

Familiarity and recollection produce distinct eye movement, pupil and medial temporal lobe responses when memory strength is matched.

PubMed

Kafkas, Alexandros; Montaldi, Daniela

2012-11-01

Two experiments explored eye measures (fixations and pupil response patterns) and brain responses (BOLD) accompanying the recognition of visual object stimuli based on familiarity and recollection. In both experiments, the use of a modified remember/know procedure led to high confidence and matched accuracy levels characterising strong familiarity (F3) and recollection (R) responses. In Experiment 1, visual scanning behaviour at retrieval distinguished familiarity-based from recollection-based recognition. Recollection, relative to strength-matched familiarity, involved significantly larger pupil dilations and more dispersed fixation patterns. In Experiment 2, the hippocampus was selectively activated for recollected stimuli, while no evidence of activation was observed in the hippocampus for strong familiarity of matched accuracy. Recollection also activated the parahippocampal cortex (PHC), while the adjacent perirhinal cortex (PRC) was actively engaged in response to strong familiarity (than to recollection). Activity in prefrontal and parietal areas differentiated familiarity and recollection in both the extent and the magnitude of activity they exhibited, while the dorsomedial thalamus showed selective familiarity-related activity, and the ventrolateral and anterior thalamus selective recollection-related activity. These findings are consistent with the view that the hippocampus and PRC play contrasting roles in supporting recollection and familiarity and that these differences are not a result of differences in memory strength. Overall, the combined pupil dilation, eye movement and fMRI data suggest the operation of recognition mechanisms drawing differentially on familiarity and recollection, whose neural bases are distinct within the MTL. Copyright © 2012 Elsevier Ltd. All rights reserved.

A novel "signal-on/off" sensing platform for selective detection of thrombin based on target-induced ratiometric electrochemical biosensing and bio-bar-coded nanoprobe amplification strategy.

PubMed

Wang, Lanlan; Ma, Rongna; Jiang, Liushan; Jia, Liping; Jia, Wenli; Wang, Huaisheng

2017-06-15

A novel dual-signal ratiometric electrochemical aptasensor for highly sensitive and selective detection of thrombin has been designed on the basis of signal-on and signal-off strategy. Ferrocene labeled hairpin probe (Fc-HP), thrombin aptamer and methyl blue labeled bio-bar-coded AuNPs (MB-P3-AuNPs) were rationally introduced for the construction of the assay platform, which combined the advantages of the recognition of aptamer, the amplification of bio-bar-coded nanoprobe, and the ratiometric signaling readout. In the presence of thrombin, the interaction between thrombin and the aptamer leads to the departure of MB-P3-AuNPs from the sensing interface, and the conformation of the single stranded Fc-HP to a hairpin structure to take the Fc confined near the electrode surface. Such conformational changes resulted in the oxidation current of Fc increased and that of MB decreased. Therefore, the recognition event of the target can be dual-signal ratiometric electrochemical readout in both the "signal-off" of MB and the "signal-on" of Fc. The proposed strategy showed a wide linear detection range from 0.003 to 30nM with a detection limit of 1.1 pM. Moreover, it exhibits good performance of excellent selectivity, good stability, and acceptable fabrication reproducibility. By changing the recognition probe, this protocol could be easily expanded into the detection of other targets, showing promising potential applications in disease diagnostics and bioanalysis. Copyright © 2016. Published by Elsevier B.V.

Synthetic lipoprotein as nano-material vehicle in the targeted drug delivery.

PubMed

Zhang, Xueqin; Huang, Gangliang

2017-12-01

High-density lipoprotein (HDL) and low-density lipoprotein (LDL), as human endogenous lipoprotein particles, have low toxicity, high selectivity, and good safety. They can avoid the recognition and clearance of human reticuloendothelial system. These synthetic lipoproteins (sLPs) have been attracted extensive attention as the nanovectors for tumor-targeted drug and gene delivery. Herein, recent advances in the field of anticancer based on these two lipid proteins and recombinant lipoproteins (rLPs) as target delivery vectors were analyzed and discussed.

Selective REM-sleep deprivation does not diminish emotional memory consolidation in young healthy subjects.

PubMed

Morgenthaler, Jarste; Wiesner, Christian D; Hinze, Karoline; Abels, Lena C; Prehn-Kristensen, Alexander; Göder, Robert

2014-01-01

Sleep enhances memory consolidation and it has been hypothesized that rapid eye movement (REM) sleep in particular facilitates the consolidation of emotional memory. The aim of this study was to investigate this hypothesis using selective REM-sleep deprivation. We used a recognition memory task in which participants were shown negative and neutral pictures. Participants (N=29 healthy medical students) were separated into two groups (undisturbed sleep and selective REM-sleep deprived). Both groups also worked on the memory task in a wake condition. Recognition accuracy was significantly better for negative than for neutral stimuli and better after the sleep than the wake condition. There was, however, no difference in the recognition accuracy (neutral and emotional) between the groups. In summary, our data suggest that REM-sleep deprivation was successful and that the resulting reduction of REM-sleep had no influence on memory consolidation whatsoever.

Selective removal of 17β-estradiol with molecularly imprinted particle-embedded cryogel systems.

PubMed

Koç, İlker; Baydemir, Gözde; Bayram, Engin; Yavuz, Handan; Denizli, Adil

2011-09-15

The selective removal of 17β-estradiol (E2) was investigated by using molecularly E2 imprinted (MIP) particle embedded poly(hydroxyethyl methacrylate) (PHEMA) cryogel. PHEMA/MIP composite cryogel was characterized by FTIR, SEM, swelling studies, and surface area measurements. E2 adsorption studies were performed by using aqueous solutions which contain various amounts of E2. The specificity of PHEMA/MIP cryogel to recognition of E2 was performed by using cholesterol and stigmasterol. PHEMA/MIP cryogel exhibited a high binding capacity (5.32 mg/gpolymer) and high selectivity for E2 in the presence of competitive molecules, cholesterol (k(E2/cholesterol) = 7.6) and stigmasterol (k(E2/Stigmasterol) = 85.8). There is no significant decrease in adsorption capacity after several adsorption-desorption cycles. Copyright © 2011 Elsevier B.V. All rights reserved.

Contrasted evolutionary histories of two Toll-like receptors (Tlr4 and Tlr7) in wild rodents (MURINAE)

PubMed Central

2013-01-01

Background In vertebrates, it has been repeatedly demonstrated that genes encoding proteins involved in pathogen-recognition by adaptive immunity (e.g. MHC) are subject to intensive diversifying selection. On the other hand, the role and the type of selection processes shaping the evolution of innate-immunity genes are currently far less clear. In this study we analysed the natural variation and the evolutionary processes acting on two genes involved in the innate-immunity recognition of Microbe-Associated Molecular Patterns (MAMPs). Results We sequenced genes encoding Toll-like receptor 4 (Tlr4) and 7 (Tlr7), two of the key bacterial- and viral-sensing receptors of innate immunity, across 23 species within the subfamily Murinae. Although we have shown that the phylogeny of both Tlr genes is largely congruent with the phylogeny of rodents based on a comparably sized non-immune sequence dataset, we also identified several potentially important discrepancies. The sequence analyses revealed that major parts of both Tlrs are evolving under strong purifying selection, likely due to functional constraints. Yet, also several signatures of positive selection have been found in both genes, with more intense signal in the bacterial-sensing Tlr4 than in the viral-sensing Tlr7. 92% and 100% of sites evolving under positive selection in Tlr4 and Tlr7, respectively, were located in the extracellular domain. Directly in the Ligand-Binding Region (LBR) of TLR4 we identified two rapidly evolving amino acid residues and one site under positive selection, all three likely involved in species-specific recognition of lipopolysaccharide of gram-negative bacteria. In contrast, all putative sites of LBRTLR7 involved in the detection of viral nucleic acids were highly conserved across rodents. Interspecific differences in the predicted 3D-structure of the LBR of both Tlrs were not related to phylogenetic history, while analyses of protein charges clearly discriminated Rattini and Murini clades. Conclusions In consequence of the constraints given by the receptor protein function purifying selection has been a dominant force in evolution of Tlrs. Nevertheless, our results show that episodic diversifying parasite-mediated selection has shaped the present species-specific variability in rodent Tlrs. The intensity of diversifying selection was higher in Tlr4 than in Tlr7, presumably due to structural properties of their ligands. PMID:24028551

Social recognition is context dependent in single male prairie voles

PubMed Central

Zheng, Da-Jiang; Foley, Lauren; Rehman, Asad; Ophir, Alexander G.

2013-01-01

Single males might benefit from knowing the identity of neighbouring males when establishing and defending boundaries. Similarly, males should discriminate between individual females if this leads to more reproductive opportunities. Contextual social cues may alter the value of learning identity. Knowing the identity of competitors that intrude into an animal’s territory may be more salient than knowing the identity of individuals on whose territory an animal is trespassing. Hence, social and environmental context could affect social recognition in many ways. Here we test social recognition of socially monogamous single male prairie voles, Microtus ochrogaster. In experiment 1 we tested recognition of male or female conspecifics and found that males discriminated between different males but not between different females. In experiment 2 we asked whether recognition of males is influenced when males are tested in their own cage (familiar), in a clean cage (neutral) or in the home cage of another male (unfamiliar). Although focal males discriminated between male conspecifics in all three contexts, individual variation in recognition was lower when males were tested in their home cage (in the presence of familiar social cues) compared to when the context lacked social cues (neutral). Experiment 1 indicates that selective pressures may have operated to enhance male territorial behaviour and indiscriminate mate selection. Experiment 2 suggests that the presence of a conspecific cue heightens social recognition and that home-field advantages might extend to social cognition. Taken together, our results indicate social recognition depends on the social and possibly territorial context. PMID:24273328

Social recognition is context dependent in single male prairie voles.

PubMed

Zheng, Da-Jiang; Foley, Lauren; Rehman, Asad; Ophir, Alexander G

2013-11-01

Single males might benefit from knowing the identity of neighbouring males when establishing and defending boundaries. Similarly, males should discriminate between individual females if this leads to more reproductive opportunities. Contextual social cues may alter the value of learning identity. Knowing the identity of competitors that intrude into an animal's territory may be more salient than knowing the identity of individuals on whose territory an animal is trespassing. Hence, social and environmental context could affect social recognition in many ways. Here we test social recognition of socially monogamous single male prairie voles, Microtus ochrogaster . In experiment 1 we tested recognition of male or female conspecifics and found that males discriminated between different males but not between different females. In experiment 2 we asked whether recognition of males is influenced when males are tested in their own cage (familiar), in a clean cage (neutral) or in the home cage of another male (unfamiliar). Although focal males discriminated between male conspecifics in all three contexts, individual variation in recognition was lower when males were tested in their home cage (in the presence of familiar social cues) compared to when the context lacked social cues (neutral). Experiment 1 indicates that selective pressures may have operated to enhance male territorial behaviour and indiscriminate mate selection. Experiment 2 suggests that the presence of a conspecific cue heightens social recognition and that home-field advantages might extend to social cognition. Taken together, our results indicate social recognition depends on the social and possibly territorial context.

Towards automated assistance for operating home medical devices.

PubMed

Gao, Zan; Detyniecki, Marcin; Chen, Ming-Yu; Wu, Wen; Hauptmann, Alexander G; Wactlar, Howard D

2010-01-01

To detect errors when subjects operate a home medical device, we observe them with multiple cameras. We then perform action recognition with a robust approach to recognize action information based on explicitly encoding motion information. This algorithm detects interest points and encodes not only their local appearance but also explicitly models local motion. Our goal is to recognize individual human actions in the operations of a home medical device to see if the patient has correctly performed the required actions in the prescribed sequence. Using a specific infusion pump as a test case, requiring 22 operation steps from 6 action classes, our best classifier selects high likelihood action estimates from 4 available cameras, to obtain an average class recognition rate of 69%.

Face-selective regions show invariance to linear, but not to non-linear, changes in facial images.

PubMed

Baseler, Heidi A; Young, Andrew W; Jenkins, Rob; Mike Burton, A; Andrews, Timothy J

2016-12-01

Familiar face recognition is remarkably invariant across huge image differences, yet little is understood concerning how image-invariant recognition is achieved. To investigate the neural correlates of invariance, we localized the core face-responsive regions and then compared the pattern of fMR-adaptation to different stimulus transformations in each region to behavioural data demonstrating the impact of the same transformations on familiar face recognition. In Experiment 1, we compared linear transformations of size and aspect ratio to a non-linear transformation affecting only part of the face. We found that adaptation to facial identity in face-selective regions showed invariance to linear changes, but there was no invariance to non-linear changes. In Experiment 2, we measured the sensitivity to non-linear changes that fell within the normal range of variation across face images. We found no adaptation to facial identity for any of the non-linear changes in the image, including to faces that varied in different levels of caricature. These results show a compelling difference in the sensitivity to linear compared to non-linear image changes in face-selective regions of the human brain that is only partially consistent with their effect on behavioural judgements of identity. We conclude that while regions such as the FFA may well be involved in the recognition of face identity, they are more likely to contribute to some form of normalisation that underpins subsequent recognition than to form the neural substrate of recognition per se. Copyright © 2016 Elsevier Ltd. All rights reserved.

Plastic antibody for the recognition of chemical warfare agent sulphur mustard.

PubMed

Boopathi, M; Suryanarayana, M V S; Nigam, Anil Kumar; Pandey, Pratibha; Ganesan, K; Singh, Beer; Sekhar, K

2006-06-15

Molecularly imprinted polymers (MIPs) known as plastic antibodies (PAs) represent a new class of materials possessing high selectivity and affinity for the target molecule. Since their discovery, PAs have attracted considerable interest from bio- and chemical laboratories to pharmaceutical institutes. PAs are becoming an important class of synthetic materials mimicking molecular recognition by natural receptors. In addition, they have been utilized as catalysts, sorbents for solid-phase extraction, stationary phase for liquid chromatography and mimics of enzymes. In this paper, first time we report the preparation and characterization of a PA for the recognition of blistering chemical warfare agent sulphur mustard (SM). The SM imprinted PA exhibited more surface area when compared to the control non-imprinted polymer (NIP). In addition, SEM image showed an ordered nano-pattern for the PA of SM that is entirely different from the image of NIP. The imprinting also enhanced SM rebinding ability to the PA when compared to the NIP with an imprinting efficiency (alpha) of 1.3.

Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex

PubMed Central

Liu, Hesheng; Agam, Yigal; Madsen, Joseph R.; Kreiman, Gabriel

2010-01-01

Summary The difficulty of visual recognition stems from the need to achieve high selectivity while maintaining robustness to object transformations within hundreds of milliseconds. Theories of visual recognition differ in whether the neuronal circuits invoke recurrent feedback connections or not. The timing of neurophysiological responses in visual cortex plays a key role in distinguishing between bottom-up and top-down theories. Here we quantified at millisecond resolution the amount of visual information conveyed by intracranial field potentials from 912 electrodes in 11 human subjects. We could decode object category information from human visual cortex in single trials as early as 100 ms post-stimulus. Decoding performance was robust to depth rotation and scale changes. The results suggest that physiological activity in the temporal lobe can account for key properties of visual recognition. The fast decoding in single trials is compatible with feed-forward theories and provides strong constraints for computational models of human vision. PMID:19409272

Bio-Mimetic Sensors Based on Molecularly Imprinted Membranes

PubMed Central

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

Facile and efficient electrochemical enantiomer recognition of phenylalanine using β-Cyclodextrin immobilized on reduced graphene oxide.

PubMed

Zaidi, Shabi Abbas

2017-08-15

This work demonstrates the facile and efficient preparation protocol of β-Cyclodextrin-reduced graphene oxide modified glassy carbon electrode (β-CD/RGO/GCE) sensor for an impressive chiral selectivity analysis for phenylalanine enantiomers. In this work, the immobilization of β-CD over graphene sheets allows the excellent enantiomer recognition due to the large surface area and high conductivity of graphene sheets and extraordinary supramolecular (host-guest interaction) property of β-CD. The proposed sensor was well characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and electrochemical impedance spectroscopy (EIS) techniques. The analytical studies demonstrated that the β-CD/RGO/GCE exhibit superior chiral recognition toward L-phenylalanine as compared to D-phenylalanine. Under optimum conditions, the developed sensor displayed a good linear range from 0.4 to 40µM with the limit of detection (LOD) values of 0.10µM and 0.15µM for l- and D-phenylalanine, respectively. Furthermore, the proposed sensor exhibits good stability and regeneration capacity. Thus, the as-synthesized material can be exploited for electrochemical enantiomer recognition successfully. Copyright © 2017 Elsevier B.V. All rights reserved.

Expanding the universe of cytokines and pattern recognition receptors: galectins and glycans in innate immunity.

PubMed

Cerliani, Juan P; Stowell, Sean R; Mascanfroni, Iván D; Arthur, Connie M; Cummings, Richard D; Rabinovich, Gabriel A

2011-02-01

Effective immunity relies on the recognition of pathogens and tumors by innate immune cells through diverse pattern recognition receptors (PRRs) that lead to initiation of signaling processes and secretion of pro- and anti-inflammatory cytokines. Galectins, a family of endogenous lectins widely expressed in infected and neoplastic tissues have emerged as part of the portfolio of soluble mediators and pattern recognition receptors responsible for eliciting and controlling innate immunity. These highly conserved glycan-binding proteins can control immune cell processes through binding to specific glycan structures on pathogens and tumors or by acting intracellularly via modulation of selective signaling pathways. Recent findings demonstrate that various galectin family members influence the fate and physiology of different innate immune cells including polymorphonuclear neutrophils, mast cells, macrophages, and dendritic cells. Moreover, several pathogens may actually utilize galectins as a mechanism of host invasion. In this review, we aim to highlight and integrate recent discoveries that have led to our current understanding of the role of galectins in host-pathogen interactions and innate immunity. Challenges for the future will embrace the rational manipulation of galectin-glycan interactions to instruct and shape innate immunity during microbial infections, inflammation, and cancer.

Solubility Interactions and the Design of Chemically Selective Sorbent Coatings for Chemical Sensors and Arrays

DTIC Science & Technology

1990-07-27

sorptionpiezoelectric sorption 63 detector, surface acoustic wave, pattern recognition, array, 16. PRICE CODE molecular recognition , 17. SECURITY...1 PIEZOELECTRIC SORPTION DETECTORS ........................................................... 6 SOLUBILITY... SORPTION AND LINEAR SOLVATION ENERGY RELATIONSHIPS (LSER) ................................................................................... 9

[Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

PubMed

Li, Jing; Hong, Wenxue

2014-12-01

The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

Exploring the energy landscape of antibody-antigen complexes: protein dynamics, flexibility, and molecular recognition.

PubMed

Thielges, Megan C; Zimmermann, Jörg; Yu, Wayne; Oda, Masayuki; Romesberg, Floyd E

2008-07-08

The production of antibodies that selectively bind virtually any foreign compound is the hallmark of the immune system. While much is understood about how sequence diversity contributes to this remarkable feat of molecular recognition, little is known about how sequence diversity impacts antibody dynamics, which is also expected to contribute to molecular recognition. Toward this goal, we examined a panel of antibodies elicited to the chromophoric antigen fluorescein. On the basis of isothermal titration calorimetry, we selected six antibodies that bind fluorescein with diverse binding entropies, suggestive of varying contributions of dynamics to molecular recognition. Sequencing revealed that two pairs of antibodies employ homologous heavy chains that were derived from common germline genes, while the other two heavy chains and all six of the light chains were derived from different germline genes and are not homologous. Interestingly, more than half of all the somatic mutations acquired during affinity maturation among the six antibodies are located in positions unlikely to contact fluorescein directly. To quantify and compare the dynamics of the antibody-fluorescein complexes, three-pulse photon echo peak shift and transient grating spectroscopy were employed. All of the antibodies exhibited motions on three distinct time scales, ultrafast motions on the <100 fs time scale, diffusive motions on the picosecond time scale, and motions that occur on time scales longer than nanoseconds and thus appear static. However, the exact frequency of the picosecond time scale motion and the relative contribution of the different motions vary significantly among the antibody-chromophore complexes, revealing a high level of dynamic diversity. Using a hierarchical model, we relate the data to features of the antibodies' energy landscapes as well as their flexibility in terms of elasticity and plasticity. In all, the data provide a consistent picture of antibody flexibility, which interestingly appears to be correlated with binding entropy as well as with germline gene use and the mutations introduced during affinity maturation. The data also provide a gauge of the dynamic diversity of the antibody repertoire and suggest that this diversity might contribute to molecular recognition by facilitating the recognition of the broadest range of foreign molecules.

Utilizing the Cross-Reactivity of MIPs.

PubMed

Yilmaz, Ecevit; Billing, Johan; Nilsson, Carina; Boyd, Brian; Kecili, Rüstem; Nivhede, David; Axelsson, Sara; Rees, Anthony

2015-01-01

The crossreactivity of molecularly imprinted polymers (MIPs) and its practical implications are discussed. Screening of MIP libraries is presented as a fasttrack route to discovery of resins selective towards new targets, exploiting the fact that MIPs imprinted with one type of template molecule also show recognition to related and sometimes also to apparently unrelated molecules. Several examples from our own and others' studies are presented that illustrate this crossreactivity and the pattern of recognition is discussed for selected examples.

Nanostructured aptamer-based sensing platform for highly sensitive recognition of myoglobin.

PubMed

Nia, Neda Ghafori; Azadbakht, Azadeh

2018-06-21

A composite was prepared from PtSn nanoparticles and carbon nanotubes (PtSnNP/CNTs) and applied to the electrochemical determination of myoglobin (Mb). An Mb-aptamer was immobilized on a glassy carbon electrode (GCE), and hexcyanoferrate was used as an electrochemical probe. The PtSnNP/CNTs were synthesized by a microwave-aided ethylene glycol reduction method. Detection is based on electron transfer inhibition that is caused by the folding and conformational change of the Mb-aptamer in the presence of Mb. The amperometric signal for hexacyanoferrate, best measured at 0.2 V vs. Ag/AgCl depends on the concentration of Mb that interacts with the aptamer on the GCE. This approach is selective and sensitive for Mb due to (a) the highly specific recognition ability of the aptamer for Mb, (b) the powerful electronic properties of carbon nanotubes, (c) the arranged decoration of CNTs with PtSnNPs, and (d), the superior electron transfer to hexacyanoferrate. The assay is highly selective, with linear relationships from 0.01-1 nM and 10 nM-200 nM, and a limit of detection as low as 2.2 ± 0.1 pM. The modified GCE was applied to the quantitation of Mb in spiked human serum samples. Graphical abstract Schematic illustration of the method for Mb detection.

Synthesis of monodisperse molecularly imprinted microspheres with multi-recognition ability via precipitation polymerization for the selective extraction of cyromazine, melamine, triamterene and trimethoprim.

PubMed

Wang, Xian-Hua; Xie, Li-Fu; Dong, Qian; Liu, Hao-Long; Huang, Yan-Ping; Liu, Zhao-Sheng

2015-12-15

Through precipitation polymerization, three monodisperse molecularly imprinted polymers (MIPs) containing imprints of 2,4-diamino-6-methyl-1,3,5-triazine (DM), cyromazine (CY) or trimethoprim (TM), were synthesized using methacrylic acid as functional monomer, divinylbenzene as cross-linker, and a mixture of acetonitrile-toluene (90/10, v/v) as porogen. The morphology and selectivity of the MIPs were characterized and compared systematically. The MIPs had the best specific binding in pure acetonitrile, and the data of adsorption experiment were fitted well with Langmuir and Freundlich model. In addition, DM-MIPs showed the excellent binding and multi-recognition capability for CY, melamine (ME), triamterene (TA) and TM, and the binding capacity were 7.18, 7.56, 5.66 and 5.45μmol/g, respectively. Due to the pseudo template and the ability of multi-recognition, DM-MIPs as sorbent material could avoid the effect of template leakage on quantitative analysis. Therefore, DM-MIPs were used as a solid-phase extraction material to enrich ME, CY, TA and TM from different bio-matrix samples for high performance liquid chromatography analysis. Under the optimized conditions, the recoveries of three spiked levels in different bio-matrix samples were ranged from 80.9% to 91.5% with RSD≤4.2 (n=3). Copyright © 2015 Elsevier B.V. All rights reserved.

Online medical symbol recognition using a Tablet PC

NASA Astrophysics Data System (ADS)

Kundu, Amlan; Hu, Qian; Boykin, Stanley; Clark, Cheryl; Fish, Randy; Jones, Stephen; Moore, Stephen

2011-01-01

In this paper we describe a scheme to enhance the usability of a Tablet PC's handwriting recognition system by including medical symbols that are not a part of the Tablet PC's symbol library. The goal of this work is to make handwriting recognition more useful for medical professionals accustomed to using medical symbols in medical records. To demonstrate that this new symbol recognition module is robust and expandable, we report results on both a medical symbol set and an expanded symbol test set which includes selected mathematical symbols.

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Profiling charge complementarity and selectivity for binding at the protein surface.

PubMed

Sulea, Traian; Purisima, Enrico O

2003-05-01

A novel analysis and representation of the protein surface in terms of electrostatic binding complementarity and selectivity is presented. The charge optimization methodology is applied in a probe-based approach that simulates the binding process to the target protein. The molecular surface is color coded according to calculated optimal charge or according to charge selectivity, i.e., the binding cost of deviating from the optimal charge. The optimal charge profile depends on both the protein shape and charge distribution whereas the charge selectivity profile depends only on protein shape. High selectivity is concentrated in well-shaped concave pockets, whereas solvent-exposed convex regions are not charge selective. This suggests the synergy of charge and shape selectivity hot spots toward molecular selection and recognition, as well as the asymmetry of charge selectivity at the binding interface of biomolecular systems. The charge complementarity and selectivity profiles map relevant electrostatic properties in a readily interpretable way and encode information that is quite different from that visualized in the standard electrostatic potential map of unbound proteins.

Novelty preference in patients with developmental amnesia.

PubMed

Munoz, M; Chadwick, M; Perez-Hernandez, E; Vargha-Khadem, F; Mishkin, M

2011-12-01

To re-examine whether or not selective hippocampal damage reduces novelty preference in visual paired comparison (VPC), we presented two different versions of the task to a group of patients with developmental amnesia (DA), each of whom sustained this form of pathology early in life. Compared with normal control participants, the DA group showed a delay-dependent reduction in novelty preference on one version of the task and an overall reduction on both versions combined. Because VPC is widely considered to be a measure of incidental recognition, the results appear to support the view that the hippocampus contributes to recognition memory. A difficulty for this conclusion, however, is that according to one current view the hippocampal contribution to recognition is limited to task conditions that encourage recollection of an item in some associated context, and according to another current view, to recognition of an item with the high confidence judgment that reflects a strong memory. By contrast, VPC, throughout which the participant remains entirely uninstructed other than to view the stimuli, would seem to lack such task conditions and so would likely lead to recognition based on familiarity rather than recollection or, alternatively, weak memories rather than strong. However, before concluding that the VPC impairment therefore contradicts both current views regarding the role of the hippocampus in recognition memory, two possibilities that would resolve this issue need to be investigated. One is that some variable in VPC, such as the extended period of stimulus encoding during familiarization, overrides its incidental nature, and, because this condition promotes either recollection- or strength-based recognition, renders the task hippocampal-dependent. The other possibility is that VPC, rather than providing a measure of incidental recognition, actually assesses an implicit, information-gathering process modulated by habituation, for which the hippocampus is also partly responsible, independent of its role in recognition. Copyright © 2010 Wiley Periodicals, Inc.

Recognition and reading aloud of kana and kanji word: an fMRI study.

PubMed

Ino, Tadashi; Nakai, Ryusuke; Azuma, Takashi; Kimura, Toru; Fukuyama, Hidenao

2009-03-16

It has been proposed that different brain regions are recruited for processing two Japanese writing systems, namely, kanji (morphograms) and kana (syllabograms). However, this difference may depend upon what type of word was used and also on what type of task was performed. Using fMRI, we investigated brain activation for processing kanji and kana words with similar high familiarity in two tasks: word recognition and reading aloud. During both tasks, words and non-words were presented side by side, and the subjects were required to press a button corresponding to the real word in the word recognition task and were required to read aloud the real word in the reading aloud task. Brain activations were similar between kanji and kana during reading aloud task, whereas during word recognition task in which accurate identification and selection were required, kanji relative to kana activated regions of bilateral frontal, parietal and occipitotemporal cortices, all of which were related mainly to visual word-form analysis and visuospatial attention. Concerning the difference of brain activity between two tasks, differential activation was found only in the regions associated with task-specific sensorimotor processing for kana, whereas visuospatial attention network also showed greater activation during word recognition task than during reading aloud task for kanji. We conclude that the differences in brain activation between kanji and kana depend on the interaction between the script characteristics and the task demands.

Gene/protein name recognition based on support vector machine using dictionary as features.

PubMed

Mitsumori, Tomohiro; Fation, Sevrani; Murata, Masaki; Doi, Kouichi; Doi, Hirohumi

2005-01-01

Automated information extraction from biomedical literature is important because a vast amount of biomedical literature has been published. Recognition of the biomedical named entities is the first step in information extraction. We developed an automated recognition system based on the SVM algorithm and evaluated it in Task 1.A of BioCreAtIvE, a competition for automated gene/protein name recognition. In the work presented here, our recognition system uses the feature set of the word, the part-of-speech (POS), the orthography, the prefix, the suffix, and the preceding class. We call these features "internal resource features", i.e., features that can be found in the training data. Additionally, we consider the features of matching against dictionaries to be external resource features. We investigated and evaluated the effect of these features as well as the effect of tuning the parameters of the SVM algorithm. We found that the dictionary matching features contributed slightly to the improvement in the performance of the f-score. We attribute this to the possibility that the dictionary matching features might overlap with other features in the current multiple feature setting. During SVM learning, each feature alone had a marginally positive effect on system performance. This supports the fact that the SVM algorithm is robust on the high dimensionality of the feature vector space and means that feature selection is not required.

Automated night/day standoff detection, tracking, and identification of personnel for installation protection

NASA Astrophysics Data System (ADS)

Lemoff, Brian E.; Martin, Robert B.; Sluch, Mikhail; Kafka, Kristopher M.; McCormick, William; Ice, Robert

2013-06-01

The capability to positively and covertly identify people at a safe distance, 24-hours per day, could provide a valuable advantage in protecting installations, both domestically and in an asymmetric warfare environment. This capability would enable installation security officers to identify known bad actors from a safe distance, even if they are approaching under cover of darkness. We will describe an active-SWIR imaging system being developed to automatically detect, track, and identify people at long range using computer face recognition. The system illuminates the target with an eye-safe and invisible SWIR laser beam, to provide consistent high-resolution imagery night and day. SWIR facial imagery produced by the system is matched against a watch-list of mug shots using computer face recognition algorithms. The current system relies on an operator to point the camera and to review and interpret the face recognition results. Automation software is being developed that will allow the system to be cued to a location by an external system, automatically detect a person, track the person as they move, zoom in on the face, select good facial images, and process the face recognition results, producing alarms and sharing data with other systems when people are detected and identified. Progress on the automation of this system will be presented along with experimental night-time face recognition results at distance.

Northeast Artificial Intelligence Consortium Annual Report. Volume 7. 1988 Research in Automated Photointerpretation

DTIC Science & Technology

1989-10-01

weight based on how powerful the corresponding feature is for object recognition and discrimination. For example, consider an arbitrary weight, denoted...quality of the segmentation, how powerful the features and spatial constraints in the knowledge base are (as far as object recognition is concern...that are powerful for object recognition and discrimination. At this point, this selection is performed heuristically through trial-and-error. As a

Triplex DNA formation-mediated strand displacement reaction for highly sensitive fluorescent detection of melamine.

PubMed

Liu, Xiaojuan; Xu, Ningning; Gai, Panpan; Li, Feng

2018-08-01

Since melamine is a strong hazard to human health, the development of new methods for highly sensitive detection of melamine is highly desirable. Herein, a novel fluorescent biosensing strategy was designed for sensitive and selective melamine assay based on the recognition ability of abasic (AP) site in triplex towards melamine and signal amplification by Mg 2+ -dependent DNAzyme. In this strategy, the melamine-induced formation of triplex DNA was employed to trigger the strand displacement reaction (SDR). The SDR process converted the specific target recognition into the release and activation of Mg 2+ -dependent DNAzyme, which could catalyze the cleavage of fluorophore/quencher labeled DNA substrate (FQ), resulting in a significantly increased fluorescent signal. Under the optimal conditions, the fluorescent signal has a linear relationship with the logarithm of the melamine concentration in a wide range of 0.005-50 μM. The detection limit was estimated to be 0.9 nM (0.1ppb), which is sufficiently sensitive for practical application. Furthermore, this strategy exhibits high selectivity against other potential interfering substances, and the practical application of this strategy for milk samples reveals that the proposed strategy works well for melamine assay in real samples. Therefore, this strategy presents a new method for the sensitive melamine assay and holds great promise for sensing applications in the environment and the food safety field. Copyright © 2018 Elsevier B.V. All rights reserved.

Autistic traits are linked to reduced adaptive coding of face identity and selectively poorer face recognition in men but not women.

PubMed

Rhodes, Gillian; Jeffery, Linda; Taylor, Libby; Ewing, Louise

2013-11-01

Our ability to discriminate and recognize thousands of faces despite their similarity as visual patterns relies on adaptive, norm-based, coding mechanisms that are continuously updated by experience. Reduced adaptive coding of face identity has been proposed as a neurocognitive endophenotype for autism, because it is found in autism and in relatives of individuals with autism. Autistic traits can also extend continuously into the general population, raising the possibility that reduced adaptive coding of face identity may be more generally associated with autistic traits. In the present study, we investigated whether adaptive coding of face identity decreases as autistic traits increase in an undergraduate population. Adaptive coding was measured using face identity aftereffects, and autistic traits were measured using the Autism-Spectrum Quotient (AQ) and its subscales. We also measured face and car recognition ability to determine whether autistic traits are selectively related to face recognition difficulties. We found that men who scored higher on levels of autistic traits related to social interaction had reduced adaptive coding of face identity. This result is consistent with the idea that atypical adaptive face-coding mechanisms are an endophenotype for autism. Autistic traits were also linked with face-selective recognition difficulties in men. However, there were some unexpected sex differences. In women, autistic traits were linked positively, rather than negatively, with adaptive coding of identity, and were unrelated to face-selective recognition difficulties. These sex differences indicate that autistic traits can have different neurocognitive correlates in men and women and raise the intriguing possibility that endophenotypes of autism can differ in males and females. © 2013 Elsevier Ltd. All rights reserved.

Simulation of millimeter-wave body images and its application to biometric recognition

NASA Astrophysics Data System (ADS)

Moreno-Moreno, Miriam; Fierrez, Julian; Vera-Rodriguez, Ruben; Parron, Josep

2012-06-01

One of the emerging applications of the millimeter-wave imaging technology is its use in biometric recognition. This is mainly due to some properties of the millimeter-waves such as their ability to penetrate through clothing and other occlusions, their low obtrusiveness when collecting the image and the fact that they are harmless to health. In this work we first describe the generation of a database comprising 1200 synthetic images at 94 GHz obtained from the body of 50 people. Then we extract a small set of distance-based features from each image and select the best feature subsets for person recognition using the SFFS feature selection algorithm. Finally these features are used in body geometry authentication obtaining promising results.

The role of the thalamic nuclei in recognition memory accompanied by recall during encoding and retrieval: an fMRI study.

PubMed

Pergola, Giulio; Ranft, Alexander; Mathias, Klaus; Suchan, Boris

2013-07-01

The present functional imaging study aimed at investigating the contribution of the mediodorsal nucleus and the anterior nuclei of the thalamus with their related cortical networks to recognition memory and recall. Eighteen subjects performed associative picture encoding followed by a single item recognition test during the functional magnetic resonance imaging session. After scanning, subjects performed a cued recall test using the formerly recognized pictures as cues. This post-scanning test served to classify recognition trials according to subsequent recall performance. In general, single item recognition accompanied by successful recall of the associations elicited stronger activation in the mediodorsal nucleus of the thalamus and in the prefrontal cortices both during encoding and retrieval compared to recognition without recall. In contrast, the anterior nuclei of the thalamus were selectively active during the retrieval phase of recognition followed by recall. A correlational analysis showed that activation of the anterior thalamus during retrieval as assessed by measuring the percent signal changes predicted lower rates of recognition without recall. These findings show that the thalamus is critical for recognition accompanied by recall, and provide the first evidence of a functional segregation of the thalamic nuclei with respect to the memory retrieval phase. In particular, the mediodorsal thalamic-prefrontal cortical network is activated during successful encoding and retrieval of associations, which suggests a role of this system in recall and recollection. The activity of the anterior thalamic-temporal network selectively during retrieval predicts better memory performances across subjects and this confirms the paramount role of this network in recall and recollection. Copyright © 2013 Elsevier Inc. All rights reserved.

Specific recognition of polyphenols by molecularly imprinted polymers based on a ternary deep eutectic solvent.

PubMed

Fu, Najing; Li, Liteng; Liu, Xiao; Fu, Nian; Zhang, Chenchen; Hu, Liandong; Li, Donghao; Tang, Baokun; Zhu, Tao

2017-12-29

Typically, a target compound is selected as a template for a molecularly imprinted polymer (MIP); however, some target compounds are not suitable as templates because of their poor solubility. Using the tailoring properties of a deep eutectic solvent (DES), the insoluble target compound caffeic acid was transformed into a ternary choline chloride-caffeic acid-ethylene glycol (ChCl-CA-EG) DES, which was then employed as a template to prepare MIPs. The ternary DES-based MIPs were characterized by Fourier transform infrared spectroscopy, elemental analysis, scanning electron microscopy, and atomic force microscopy. The effects of time, temperature, ionic strength, and pH on the recognition processes for four polyphenols (caffeic acid, protocatechuic acid, catechin, and epicatechin) by 13 ChCl-CA-EG ternary DES-based MIPs was investigated using high-performance liquid chromatography. The recognition specificity of the MIPs for CA was significantly better than that for the other polyphenols, and the MIPs exhibited obvious characteristics of chromatographic packing materials. In addition, the recognition processes mainly followed a second-order kinetics model and the Freundlich isotherm model, which together indicated that the MIPs mainly recognized the polyphenols by chemical interactions including ion exchange, electron exchange, and new bond formation. Furthermore, the specific recognition ability of the MIPs for polyphenols, which was better than those of C 18 , C 8 , or non-molecularly imprinted polymer adsorbents, was successfully applied to the recognition of polyphenols in a Radix asteris sample. The transformation of an insoluble target compound in a polymeric DES for MIP preparation and recognition is a novel and feasible strategy suitable for use in further MIP research developments. Copyright © 2017 Elsevier B.V. All rights reserved.

Optical detection of λ-cyhalothrin by core-shell fluorescent molecularly imprinted polymers in Chinese spirits.

PubMed

Wang, Jixiang; Gao, Lin; Han, Donglai; Pan, Jianming; Qiu, Hao; Li, Hongji; Wei, Xiao; Dai, Jiangdong; Yang, Jinghai; Yao, Hui; Yan, Yongsheng

2015-03-11

In this study, fluorescent molecularly imprinted polymers (FMIPs), which were for the selective recognition and fluorescence detection of λ-cyhalothrin (LC), were synthesized via fluorescein 5(6)-isothiocyanate (FITC) and 3-aminopropyltriethoxysilane (APTS)/SiO2 particles. The SiO2@FITC-APTS@MIPs were characterized by Fourier transform infrared (FT-IR), UV-vis spectrophotometer (UV-vis), fluorescence spectrophotometer, thermogravimetric analysis (TGA), confocal laser scanning microscope (CLSM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The as-synthesized SiO2@FITC-APTS@MIPs with an imprinted polymer film (thickness was about 100 nm) was demonstrated to be spherically shaped and had good monodispersity, high fluorescence intensity, and good selective recognition. Using fluorescence quenching as the detection tool, the largest fluorescence quenching efficiency (F0/F - 1) of SiO2@FITC-APTS@MIPs is close to 2.5 when the concentration of the LC is 1.0 μM L(-1). In addition, a linear relationship (F0/F - 1= 0.0162C + 0.0272) could be obtained covering a wide concentration range of 0-60 nM L(-1) with a correlation coefficient of 0.9968 described by the Stern-Volmer equation. Moreover, the limit of detection (LOD) of the SiO2@FITC-APTS@MIPs was 9.17 nM L(-1). The experiment results of practical detection revealed that the SiO2@FITC-APTS@MIPs as an attractive recognition element was satisfactory for the determination of LC in Chinese spirits. Therefore, this study demonstrated the potential of SiO2@FITC-APTS@MIPs for the recognition and detection of LC in food.

Spatial Scale in Image Detection and Recognition.

DTIC Science & Technology

1986-02-01

detail and are important in later visual processing when attention has been focused on a particular aspect of the image. Two experiments investigated the...observers also selected the filter condition to be display on each trial prior to the detection or recognition response.

A further examination of word frequency and age-of-acquisition effects in English lexical decision task performance: The role of frequency trajectory.

PubMed

Juhasz, Barbara J; Yap, Melvin J; Raoul, Akila; Kaye, Micaela

2018-04-23

Word frequency is an important predictor of lexical-decision task performance. The current study further examined the role of this variable by exploring the influence of frequency trajectory. Frequency trajectory is measured by how often a word occurs in childhood relative to adulthood. Past research on the role of this variable in word recognition has produced equivocal results. In the current study, words were selected based on their frequencies in Grade 1 (child frequency) and Grade 13 (college frequency). In Experiment 1, four frequency trajectory conditions were factorially examined in a lexical-decision task with English words: high-to-high (world), high-to-low (uncle), low-to-high (brain) and low-to-low (opera). an interaction between Grade 1 and college frequency demonstrated that words in the low-to-high condition were processed significantly faster and more accurately than words in the low-to-low condition, whereas the high-to-high and high-to-low conditions did not differ significantly. In Experiment 2, an advantage for words with an increasing frequency trajectory was also supported in regression analyses on both lexical decision and naming times for 3,039 items selected from the English Lexicon Project (Balota et al., 2007). This was replicated in Experiment 3, based on a regression analysis of 2,680 words from the British Lexicon Project (BLP; Keuleers, Lacey, Rastle, & Brysbaert, 2012). In all analyses, rated age-of-acquisition also significantly impacted word recognition. Together, the results suggest that the age at which a word is initially learned as well as its frequency trajectory across childhood impact performance in the lexical-decision task. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Incorporation of extra amino acids in peptide recognition probe to improve specificity and selectivity of an electrochemical peptide-based sensor.

PubMed

Zaitouna, Anita J; Maben, Alex J; Lai, Rebecca Y

2015-07-30

We investigated the effect of incorporating extra amino acids (AA) at the n-terminus of the thiolated and methylene blue-modified peptide probe on both specificity and selectivity of an electrochemical peptide-based (E-PB) HIV sensor. The addition of a flexible (SG)3 hexapeptide is, in particular, useful in improving sensor selectivity, whereas the addition of a highly hydrophilic (EK)3 hexapeptide has shown to be effective in enhancing sensor specificity. Overall, both E-PB sensors fabricated using peptide probes with the added AA (SG-EAA and EK-EAA) showed better specificity and selectivity, especially when compared to the sensor fabricated using a peptide probe without the extra AA (EAA). For example, the selectivity factor recorded in the 50% saliva was ∼2.5 for the EAA sensor, whereas the selectivity factor was 7.8 for both the SG-EAA and EK-EAA sensors. Other sensor properties such as the limit of detection and dynamic range were minimally affected by the addition of the six AA sequence. The limit of detection was 0.5 nM for the EAA sensor and 1 nM for both SG-EAA and EK-EAA sensors. The saturation target concentration was ∼200 nM for all three sensors. Unlike previously reported E-PB HIV sensors, the peptide probe functions as both the recognition element and antifouling passivating agent; this modification eliminates the need to include an additional antifouling diluent, which simplifies the sensor design and fabrication protocol. Copyright © 2015 Elsevier B.V. All rights reserved.

Triple Helical Recognition of Pyrimidine Inversions in Polypurine Tracts of RNA by Nucleobase-modified PNA

PubMed Central

Gupta, Pankaj; Zengeya, Thomas; Rozners, Eriks

2013-01-01

Peptide nucleic acids containing 2-pyrimidinone (P) and 3-oxo-2,3-dihydropyridazine (E) heterocycles recognized C-G and U-A inversions in a polypurine tract of double helical RNA with high affinity and sequence selectivity at pH 6.25. E-modified PNA bound strongly to bacterial A-site RNA, while no binding was observed to the human A-site RNA. PMID:21909545

Selective AR Modulators that Distinguish Proliferative from Differentiative Gene Promoters

DTIC Science & Technology

2017-08-01

Public Release; Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author(s) and should not be...Research and Materiel Command Fort Detrick, Maryland 21702-5012 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT...recognition, we performed a high -throughput screen for compounds eliciting differential AR activity on cARE vs. sARE reporters. Of 10,000 compounds

Pyrrole-coupled salicylimine-based fluorescence "turn on" probe for highly selective recognition of Zn²⁺ ions in mixed aqueous media: Application in living cell imaging.

PubMed

Bhosale, Jitendra; Fegade, Umesh; Bondhopadhyay, Banashree; Kaur, Simanpreet; Singh, Narinder; Basu, Anupam; Dabur, Rajesh; Bendre, Ratnamala; Kuwar, Anil

2015-06-01

Cation sensing behaviour of a pyrrole-based derivative (2-hydroxyl 3 methyl 6 isopropyl benzaldehyde}-3,4-dimethyl-1H-pyrrole-2-carbohydrazide (receptor 3) has been explored and is found to be selective towards Zn(2+) over a variety of tested cations. The receptor 3 has shown high selectivity and sensitivity towards Zn(2+) over the other alkali, alkaline earth and transition metal ions. In the presence of Zn(2+), absorption band of receptor 3 has shown the red shift. The sensing behaviour has been suggested to continue via enhancement process which has further been supported by UV-vis absorption and theoretical density functional theory (DFT) calculations indicating the formation of a 1:1 complex between the pyrrole based receptor 3 and Zn(2+). The present work is presenting a highly selective dual channel colorimetric sensor for zinc with great sensitivity. The developed sensor was successfully applied to image intracellular Zn(2+) in living cells. Copyright © 2015 John Wiley & Sons, Ltd.

High MHC diversity maintained by balancing selection in an otherwise genetically monomorphic mammal

PubMed Central

Aguilar, Andres; Roemer, Gary; Debenham, Sally; Binns, Matthew; Garcelon, David; Wayne, Robert K.

2004-01-01

The San Nicolas Island fox (Urocyon littoralis dickeyi) is genetically the most monomorphic sexually reproducing animal population yet reported and has no variation in hypervariable genetic markers. Such low levels of variation imply lower resistance to pathogens, reduced fitness, and problems in distinguishing kin from non-kin. In vertebrates, the MHC contains genes that influence disease resistance and kin recognition and may be under intense balancing selection in some populations. Hence, genetic variation at the MHC might persist despite the extreme monomorphism shown by neutral markers. We examine variation of five loci within the MHC of San Nicolas Island foxes and find remarkably high levels of variation. Further, we show by simulation that genetic monomorphism at neutral loci and high MHC variation could arise only through an extreme population bottleneck of <10 individuals, ≈10–20 generations ago, accompanied by unprecedented selection coefficients of >0.5 on MHC loci. These results support the importance of balancing selection as a mechanism to maintain variation in natural populations and expose the difficulty of using neutral markers as surrogates for variation in fitness-related loci. PMID:14990802

Selective recognition of parallel and anti-parallel thrombin-binding aptamer G-quadruplexes by different fluorescent dyes

PubMed Central

Zhao, Dan; Dong, Xiongwei; Jiang, Nan; Zhang, Dan; Liu, Changlin

2014-01-01

G-quadruplexes (G4) have been found increasing potential in applications, such as molecular therapeutics, diagnostics and sensing. Both Thioflavin T (ThT) and N-Methyl mesoporphyrin IX (NMM) become fluorescent in the presence of most G4, but thrombin-binding aptamer (TBA) has been reported as the only exception of the known G4-forming oligonucleotides when ThT is used as a high-throughput assay to identify G4 formation. Here, we investigate the interactions between ThT/NMM and TBA through fluorescence spectroscopy, circular dichroism and molecular docking simulation experiments in the absence or presence of cations. The results display that a large ThT fluorescence enhancement can be observed only when ThT bind to the parallel TBA quadruplex, which is induced to form by ThT in the absence of cations. On the other hand, great promotion in NMM fluorescence can be obtained only in the presence of anti-parallel TBA quadruplex, which is induced to fold by K+ or thrombin. The highly selective recognition of TBA quadruplex with different topologies by the two probes may be useful to investigate the interactions between conformation-specific G4 and the associated proteins, and could also be applied in label-free fluorescent sensing of other biomolecules. PMID:25245945

Single domain antibodies are specially suited for quantitative determination of gliadins under denaturing conditions.

PubMed

Doña, Vanina; Urrutia, Mariela; Bayardo, Mariela; Alzogaray, Vanina; Goldbaum, Fernando Alberto; Chirdo, Fernando G

2010-01-27

Food intended for celiac patients' consumption must be analyzed for the presence of toxic prolamins using high detectability tests. Though 60% ethanol is the most commonly used solvent for prolamins extraction, 2-mercaptoethanol (2-ME) and guanidinium chloride (GuHCl) can be added to increase protein recovery. However, ethanol and denaturing agents interfere with antigen recognition when conventional antibodies are used. In the present work, a new method for gliadins quantification is shown. The method is based on the selection of llama single domain antibody fragments able to operate under denaturing conditions. Six out of 28 VHH-phages obtained retained their binding capacity in 15% ethanol. Selected clones presented a long CDR3 region containing two additional cysteines that could be responsible for the higher stability. One of the clones (named VHH26) was fully operative in the presence of 15% ethanol, 0.5% 2-ME, and 0.5 M GuHCl. Capture ELISA using VHH26 was able to detect gliadins in samples shown as negatives by conventional ELISA. Therefore, this new strategy appears as an excellent platform for quantitative determination of proteins or any other immunogenic compound, in the presence of denaturing agents, when specific recognition units with high stability are required.

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

PubMed

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

2013-09-27

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

Recognition of Watson-Crick base pairs: constraints and limits due to geometric selection and tautomerism

PubMed Central

Yusupov, Marat; Yusupova, Gulnara

2014-01-01

The natural bases of nucleic acids have a strong preference for one tautomer form, guaranteeing fidelity in their hydrogen bonding potential. However, base pairs observed in recent crystal structures of polymerases and ribosomes are best explained by an alternative base tautomer, leading to the formation of base pairs with Watson-Crick-like geometries. These observations set limits to geometric selection in molecular recognition of complementary Watson-Crick pairs for fidelity in replication and translation processes. PMID:24765524

Cesium cation templated selective synthesis of a "cone-shaped" sugar macrotricyclic cryptand: A dual anion-cation molecular recognition of potassium tartrate.

PubMed

Porwanski, S; Moretti, F; Dumarcay-Charbonnier, F; Marsura, A

2016-05-01

Cesium templated Staudinger-aza-Wittig tandem reaction (S.A.W.) has been used in the synthesis of a bis-diazacrown-bis-cellobiosyl-tetra-ureido cryptand. A novel macrotricyclic compound having a "cone-shaped" configuration was selectively obtained. Additionally, first results on potential recognition properties of the cryptand are also given. Copyright © 2015 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Robust Speech Processing & Recognition: Speaker ID, Language ID, Speech Recognition/Keyword Spotting, Diarization/Co-Channel/Environmental Characterization, Speaker State Assessment

DTIC Science & Technology

2015-10-01

Scoring, Gaussian Backend , etc.) as shown in Fig. 39. The methods in this domain also emphasized the ability to perform data purification for both...investigation using the same infrastructure was undertaken to explore Lombard effect “flavor” detection for improved speaker ID. The study The presence of...dimension selection and compared to a common N-gram frequency based selection. 2.1.2: Exploration on NN/DBN backend : Since Deep Neural Networks (DNN) have

Sperm Bindin Divergence under Sexual Selection and Concerted Evolution in Sea Stars.

PubMed

Patiño, Susana; Keever, Carson C; Sunday, Jennifer M; Popovic, Iva; Byrne, Maria; Hart, Michael W

2016-08-01

Selection associated with competition among males or sexual conflict between mates can create positive selection for high rates of molecular evolution of gamete recognition genes and lead to reproductive isolation between species. We analyzed coding sequence and repetitive domain variation in the gene encoding the sperm acrosomal protein bindin in 13 diverse sea star species. We found that bindin has a conserved coding sequence domain structure in all 13 species, with several repeated motifs in a large central region that is similar among all sea stars in organization but highly divergent among genera in nucleotide and predicted amino acid sequence. More bindin codons and lineages showed positive selection for high relative rates of amino acid substitution in genera with gonochoric outcrossing adults (and greater expected strength of sexual selection) than in selfing hermaphrodites. That difference is consistent with the expectation that selfing (a highly derived mating system) may moderate the strength of sexual selection and limit the accumulation of bindin amino acid differences. The results implicate both positive selection on single codons and concerted evolution within the repetitive region in bindin divergence, and suggest that both single amino acid differences and repeat differences may affect sperm-egg binding and reproductive compatibility. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Adjunctive selective estrogen receptor modulator increases neural activity in the hippocampus and inferior frontal gyrus during emotional face recognition in schizophrenia.

PubMed

Ji, E; Weickert, C S; Lenroot, R; Kindler, J; Skilleter, A J; Vercammen, A; White, C; Gur, R E; Weickert, T W

2016-05-03

Estrogen has been implicated in the development and course of schizophrenia with most evidence suggesting a neuroprotective effect. Treatment with raloxifene, a selective estrogen receptor modulator, can reduce symptom severity, improve cognition and normalize brain activity during learning in schizophrenia. People with schizophrenia are especially impaired in the identification of negative facial emotions. The present study was designed to determine the extent to which adjunctive raloxifene treatment would alter abnormal neural activity during angry facial emotion recognition in schizophrenia. Twenty people with schizophrenia (12 men, 8 women) participated in a 13-week, randomized, double-blind, placebo-controlled, crossover trial of adjunctive raloxifene treatment (120 mg per day orally) and performed a facial emotion recognition task during functional magnetic resonance imaging after each treatment phase. Two-sample t-tests in regions of interest selected a priori were performed to assess activation differences between raloxifene and placebo conditions during the recognition of angry faces. Adjunctive raloxifene significantly increased activation in the right hippocampus and left inferior frontal gyrus compared with the placebo condition (family-wise error, P<0.05). There was no significant difference in performance accuracy or reaction time between active and placebo conditions. To the best of our knowledge, this study provides the first evidence suggesting that adjunctive raloxifene treatment changes neural activity in brain regions associated with facial emotion recognition in schizophrenia. These findings support the hypothesis that estrogen plays a modifying role in schizophrenia and shows that adjunctive raloxifene treatment may reverse abnormal neural activity during facial emotion recognition, which is relevant to impaired social functioning in men and women with schizophrenia.

A novel surface imprinted polymer/magnetic hydroxyapatite nanocomposite for selective dibenzothiophene scavenging

NASA Astrophysics Data System (ADS)

Ali, Hager R.; El-Maghrabi, Heba H.; Zahran, Fouad; Moustafa, Yasser Mohamed

2017-12-01

Highly selective adsorbent for dibenzothiophene (DBT) was successfully designed and prepared. Molecularly imprinted polymer (MIP) and magnetic hydroxyapatite (MHAP) were used as building blocks for the novel nanocomposite adsorbent. MIP/MHAP was synthesized by grafting polymerization and surface molecular imprinting using DBT as a template molecule. The microstructure and morphology of the designed nanoadsorbent were examined via FTIR, SEM and VSM. Specific surface area and pore size distribution were determined by Quantachrome Nova 3200S automated gas sorption apparatus. Additionally, static adsorption experiments, isotherms and selective recognition adsorption studies were carried out. Reversed-phase high performance liquid chromatography (RP-HPLC) was used to determine DBT. The experimental data exhibits excellent adsorption capacity for DBT reaches 247 mg/g within 60 min. Competitive adsorption results proved that MIP/MHAP have a greater affinity towards DBT molecules than benzothiophene analogues. Pseudo-second-order model and the Langmuir isotherm were used to describe the adsorption process.

Highly sensitive and selective fluoride detection in water through fluorophore release from a metal-organic framework

PubMed Central

Hinterholzinger, Florian M.; Rühle, Bastian; Wuttke, Stefan; Karaghiosoff, Konstantin; Bein, Thomas

2013-01-01

The detection, differentiation and visualization of compounds such as gases, liquids or ions are key challenges for the design of selective optical chemosensors. Optical chemical sensors employ a transduction mechanism that converts a specific analyte recognition event into an optical signal. Here we report a novel concept for fluoride ion sensing where a porous crystalline framework serves as a host for a fluorescent reporter molecule. The detection is based on the decomposition of the host scaffold which induces the release of the fluorescent dye molecule. Specifically, the hybrid composite of the metal-organic framework NH2-MIL-101(Al) and fluorescein acting as reporter shows an exceptional turn-on fluorescence in aqueous fluoride-containing solutions. Using this novel strategy, the optical detection of fluoride is extremely sensitive and highly selective in the presence of many other anions. PMID:24008779

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

PubMed

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.

Rare earth separations by selective borate crystallization

PubMed Central

Yin, Xuemiao; Wang, Yaxing; Bai, Xiaojing; Wang, Yumin; Chen, Lanhua; Xiao, Chengliang; Diwu, Juan; Du, Shiyu; Chai, Zhifang; Albrecht-Schmitt, Thomas E.; Wang, Shuao

2017-01-01

Lanthanides possess similar chemical properties rendering their separation from one another a challenge of fundamental chemical and global importance given their incorporation into many advanced technologies. New separation strategies combining green chemistry with low cost and high efficiency remain highly desirable. We demonstrate that the subtle bonding differences among trivalent lanthanides can be amplified during the crystallization of borates, providing chemical recognition of specific lanthanides that originates from Ln3+ coordination alterations, borate polymerization diversity and soft ligand coordination selectivity. Six distinct phases are obtained under identical reaction conditions across lanthanide series, further leading to an efficient and cost-effective separation strategy via selective crystallization. As proof of concept, Nd/Sm and Nd/Dy are used as binary models to demonstrate solid/aqueous and solid/solid separation processes. Controlling the reaction kinetics gives rise to enhanced separation efficiency of Nd/Sm system and a one-step quantitative separation of Nd/Dy with the aid of selective density-based flotation. PMID:28290448

Mesoporous structured MIPs@CDs fluorescence sensor for highly sensitive detection of TNT.

PubMed

Xu, Shoufang; Lu, Hongzhi

2016-11-15

A facile strategy was developed to prepare mesoporous structured molecularly imprinted polymers capped carbon dots (M-MIPs@CDs) fluorescence sensor for highly sensitive and selective determination of TNT. The strategy using amino-CDs directly as "functional monomer" for imprinting simplify the imprinting process and provide well recognition sites accessibility. The as-prepared M-MIPs@CDs sensor, using periodic mesoporous silica as imprinting matrix, and amino-CDs directly as "functional monomer", exhibited excellent selectivity and sensitivity toward TNT with detection limit of 17nM. The recycling process was sustainable for 10 times without obvious efficiency decrease. The feasibility of the developed method in real samples was successfully evaluated through the analysis of TNT in soil and water samples with satisfactory recoveries of 88.6-95.7%. The method proposed in this work was proved to be a convenient and practical way to prepare high sensitive and selective fluorescence MIPs@CDs sensors. Copyright © 2016 Elsevier B.V. All rights reserved.

A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

PubMed

Halliday, Drew W R; MacDonald, Stuart W S; Scherf, K Suzanne; Sherf, Suzanne K; Tanaka, James W

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

A Reciprocal Model of Face Recognition and Autistic Traits: Evidence from an Individual Differences Perspective

PubMed Central

Halliday, Drew W. R.; MacDonald, Stuart W. S.; Sherf, Suzanne K.; Tanaka, James W.

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals. PMID:24853862

Ultrasensitive electrochemical aptasensor based on sandwich architecture for selective label-free detection of colorectal cancer (CT26) cells.

PubMed

Hashkavayi, Ayemeh Bagheri; Raoof, Jahan Bakhsh; Ojani, Reza; Kavoosian, Saeid

2017-06-15

Colorectal cancer is one of the most common cancers in the world and has no effective treatment. Therefore, development of new methods for early diagnosis is instantly required. Biological recognition probes such as synthetic receptor and aptamer is one of the candidate recognition layers to detect important biomolecules. In this work, an electrochemical aptasensor was developed by fabricating an aptamer-cell-aptamer sandwich architecture on an SBA-15-3-aminopropyltriethoxysilane (SBA-15-pr-NH 2 ) and Au nanoparticles (AuNPs) modified graphite screen printed electrode (GSPE) surface for the selective, label-free detection of CT26 cancer cells. Based on the incubation of the thiolated aptamer with CT26 cells, the electron-transfer resistance of Fe (CN) 6 3-/4- redox couple increased considerably on the aptasensor surface. The results obtained from cyclic voltammetry and electrochemical impedance spectroscopy studies showed that the fabricated aptasensor can specifically identify CT26 cells in the concentration ranges of 10-1.0×10 5 cells/mL and 1.0×10 5 -6.0×10 6 cells/mL, respectively, with a detection limit of 2cells/mL. Applying the thiol terminated aptamer (5TR1) as a recognition layer led to a sensor with high affinity for CT26 cancer cells, compared to control cancer cells of AGS cells, VERO Cells, PC3 cells and SKOV-3 cells. Therefore a simple, rapid, label free, inexpensive, excellent, sensitive and selective electrochemical aptasensor based on sandwich architecture was developed for detection of CT26 Cells. Copyright © 2016 Elsevier B.V. All rights reserved.

Preparation, Characterization and Application of a Molecularly Imprinted Polymer for Selective Recognition of Sulpiride

PubMed Central

Zhang, Wei; She, Xuhui; Wang, Liping; Fan, Huajun; Zhou, Qing; Huang, Xiaowen; Tang, James Z.

2017-01-01

A novel molecular imprinting polymer (MIP) was prepared by bulk polymerization using sulpiride as the template molecule, itaconic acid (ITA) as the functional monomer and ethylene glycol dimethacrylate (EGDMA) as the crosslinker. The formation of the MIP was determined as the molar ratio of sulpiride-ITA-EGDMA of 1:4:15 by single-factor experiments. The MIP showed good adsorption property with imprinting factor α of 5.36 and maximum adsorption capacity of 61.13 μmol/g, and was characterized by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FT-IR) and surface area analysis. With the structural analogs (amisulpride, tiapride, lidocaine and cisapride) and small molecules containing a mono-functional group (p-toluenesulfonamide, formamide and 1-methylpyrrolidine) as substrates, static adsorption, kinetic adsorption, and rebinding experiments were also performed to investigate the selective adsorption ability, kinetic characteristic, and recognition mechanism of the MIP. A serial study suggested that the highly selective recognition ability of the MIP mainly depended on binding sites provided by N-functional groups of amide and amine. Moreover, the MIP as solid-phase extractant was successfully applied to extraction of sulpiride from the mixed solution (consisted of p-toluenesulfonamide, sulfamethoxazole, sulfanilamide, p-nitroaniline, acetanilide and trimethoprim) and serum sample, and extraction recoveries ranged from 81.57% to 86.63%. The tentative tests of drug release in stimulated intestinal fluid (pH 6.8) demonstrated that the tablet with the MIP–sulpiride could obviously inhibit sulpiride release rate. Thus, ITA-based MIP is an efficient and promising alternative to solid-phase adsorbent for extraction of sulpiride and removal of interferences in biosample analysis, and could be used as a potential carrier for controlled drug release. PMID:28772831

Control chart pattern recognition using RBF neural network with new training algorithm and practical features.

PubMed

Addeh, Abdoljalil; Khormali, Aminollah; Golilarz, Noorbakhsh Amiri

2018-05-04

The control chart patterns are the most commonly used statistical process control (SPC) tools to monitor process changes. When a control chart produces an out-of-control signal, this means that the process has been changed. In this study, a new method based on optimized radial basis function neural network (RBFNN) is proposed for control chart patterns (CCPs) recognition. The proposed method consists of four main modules: feature extraction, feature selection, classification and learning algorithm. In the feature extraction module, shape and statistical features are used. Recently, various shape and statistical features have been presented for the CCPs recognition. In the feature selection module, the association rules (AR) method has been employed to select the best set of the shape and statistical features. In the classifier section, RBFNN is used and finally, in RBFNN, learning algorithm has a high impact on the network performance. Therefore, a new learning algorithm based on the bees algorithm has been used in the learning module. Most studies have considered only six patterns: Normal, Cyclic, Increasing Trend, Decreasing Trend, Upward Shift and Downward Shift. Since three patterns namely Normal, Stratification, and Systematic are very similar to each other and distinguishing them is very difficult, in most studies Stratification and Systematic have not been considered. Regarding to the continuous monitoring and control over the production process and the exact type detection of the problem encountered during the production process, eight patterns have been investigated in this study. The proposed method is tested on a dataset containing 1600 samples (200 samples from each pattern) and the results showed that the proposed method has a very good performance. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Near-IR Two-Photon Fluorescent Sensor for K(+) Imaging in Live Cells.

PubMed

Sui, Binglin; Yue, Xiling; Kim, Bosung; Belfield, Kevin D

2015-08-19

A new two-photon excited fluorescent K(+) sensor is reported. The sensor comprises three moieties, a highly selective K(+) chelator as the K(+) recognition unit, a boron-dipyrromethene (BODIPY) derivative modified with phenylethynyl groups as the fluorophore, and two polyethylene glycol chains to afford water solubility. The sensor displays very high selectivity (>52-fold) in detecting K(+) over other physiological metal cations. Upon binding K(+), the sensor switches from nonfluorescent to highly fluorescent, emitting red to near-IR (NIR) fluorescence. The sensor exhibited a good two-photon absorption cross section, 500 GM at 940 nm. Moreover, it is not sensitive to pH in the physiological pH range. Time-dependent cell imaging studies via both one- and two-photon fluorescence microscopy demonstrate that the sensor is suitable for dynamic K(+) sensing in living cells.

Word learning emerges from the interaction of online referent selection and slow associative learning.

PubMed

McMurray, Bob; Horst, Jessica S; Samuelson, Larissa K

2012-10-01

Classic approaches to word learning emphasize referential ambiguity: In naming situations, a novel word could refer to many possible objects, properties, actions, and so forth. To solve this, researchers have posited constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative in which referent selection is an online process and independent of long-term learning. We illustrate this theoretical approach with a dynamic associative model in which referent selection emerges from real-time competition between referents and learning is associative (Hebbian). This model accounts for a range of findings including the differences in expressive and receptive vocabulary, cross-situational learning under high degrees of ambiguity, accelerating (vocabulary explosion) and decelerating (power law) learning, fast mapping by mutual exclusivity (and differences in bilinguals), improvements in familiar word recognition with development, and correlations between speed of processing and learning. Together it suggests that (a) association learning buttressed by dynamic competition can account for much of the literature; (b) familiar word recognition is subserved by the same processes that identify the referents of novel words (fast mapping); (c) online competition may allow the children to leverage information available in the task to augment performance despite slow learning; (d) in complex systems, associative learning is highly multifaceted; and (e) learning and referent selection, though logically distinct, can be subtly related. It suggests more sophisticated ways of describing the interaction between situation- and developmental-time processes and points to the need for considering such interactions as a primary determinant of development. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Ionophores and receptors using cation-pi interactions: collarenes.

PubMed

Choi, H S; Suh, S B; Cho, S J; Kim, K S

1998-10-13

Cation-pi interactions are important forces in molecular recognition by biological receptors, enzyme catalysis, and crystal engineering. We have harnessed these interactions in designing molecular systems with circular arrangement of benzene units that are capable of acting as ionophores and models for biological receptors. [n]Collarenes are promising candidates with high selectivity for a specific cation, depending on n, because of their structural rigidity and well-defined cavity size. The interaction energies of [n]collarenes with cations have been evaluated by using ab initio calculations. The selectivity of these [n]collarenes in aqueous solution was revealed by using statistical perturbation theory in conjunction with Monte Carlo and molecular dynamics simulations. It has been observed that in [n]collarenes the ratio of the interaction energies of a cation with it and the cation with the basic building unit (benzene) can be correlated to its ion selectivity. We find that collarenes are excellent and efficient ionophores that bind cations through cation-pi interactions. [6]Collarene is found to be a selective host for Li+ and Mg2+, [8]collarene for K+ and Sr2+, and [10]collarene for Cs+ and Ba2+. This finding indicates that [10]collarene and [8]collarene could be used for effective separation of highly radioactive isotopes, 137Cs and 90Sr, which are major constituents of nuclear wastes. More interestingly, collarenes of larger cavity size can be useful in capturing organic cations. [12]Collarene exhibits a pronounced affinity for tetramethylammonium cation and acetylcholine, which implies that it could serve as a model for acetylcholinestrase. Thus, collarenes can prove to be novel and effective ionophores/model-receptors capable of heralding a new direction in molecular recognition and host-guest chemistry.

Monitoring of facial stress during space flight: Optical computer recognition combining discriminative and generative methods

NASA Astrophysics Data System (ADS)

Dinges, David F.; Venkataraman, Sundara; McGlinchey, Eleanor L.; Metaxas, Dimitris N.

2007-02-01

Astronauts are required to perform mission-critical tasks at a high level of functional capability throughout spaceflight. Stressors can compromise their ability to do so, making early objective detection of neurobehavioral problems in spaceflight a priority. Computer optical approaches offer a completely unobtrusive way to detect distress during critical operations in space flight. A methodology was developed and a study completed to determine whether optical computer recognition algorithms could be used to discriminate facial expressions during stress induced by performance demands. Stress recognition from a facial image sequence is a subject that has not received much attention although it is an important problem for many applications beyond space flight (security, human-computer interaction, etc.). This paper proposes a comprehensive method to detect stress from facial image sequences by using a model-based tracker. The image sequences were captured as subjects underwent a battery of psychological tests under high- and low-stress conditions. A cue integration-based tracking system accurately captured the rigid and non-rigid parameters of different parts of the face (eyebrows, lips). The labeled sequences were used to train the recognition system, which consisted of generative (hidden Markov model) and discriminative (support vector machine) parts that yield results superior to using either approach individually. The current optical algorithm methods performed at a 68% accuracy rate in an experimental study of 60 healthy adults undergoing periods of high-stress versus low-stress performance demands. Accuracy and practical feasibility of the technique is being improved further with automatic multi-resolution selection for the discretization of the mask, and automated face detection and mask initialization algorithms.

Gender differences in emotion recognition: Impact of sensory modality and emotional category.

PubMed

Lambrecht, Lena; Kreifelts, Benjamin; Wildgruber, Dirk

2014-04-01

Results from studies on gender differences in emotion recognition vary, depending on the types of emotion and the sensory modalities used for stimulus presentation. This makes comparability between different studies problematic. This study investigated emotion recognition of healthy participants (N = 84; 40 males; ages 20 to 70 years), using dynamic stimuli, displayed by two genders in three different sensory modalities (auditory, visual, audio-visual) and five emotional categories. The participants were asked to categorise the stimuli on the basis of their nonverbal emotional content (happy, alluring, neutral, angry, and disgusted). Hit rates and category selection biases were analysed. Women were found to be more accurate in recognition of emotional prosody. This effect was partially mediated by hearing loss for the frequency of 8,000 Hz. Moreover, there was a gender-specific selection bias for alluring stimuli: Men, as compared to women, chose "alluring" more often when a stimulus was presented by a woman as compared to a man.

Robust Indoor Human Activity Recognition Using Wireless Signals.

PubMed

Wang, Yi; Jiang, Xinli; Cao, Rongyu; Wang, Xiyang

2015-07-15

Wireless signals-based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI) of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP) and access points (AP). First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions' CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO) signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM) based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.

Study to determine potential flight applications and human factors design guidelines for voice recognition and synthesis systems

NASA Astrophysics Data System (ADS)

White, R. W.; Parks, D. L.

1985-07-01

A study was conducted to determine potential commercial aircraft flight deck applications and implementation guidelines for voice recognition and synthesis. At first, a survey of voice recognition and synthesis technology was undertaken to develop a working knowledge base. Then, numerous potential aircraft and simulator flight deck voice applications were identified and each proposed application was rated on a number of criteria in order to achieve an overall payoff rating. The potential voice recognition applications fell into five general categories: programming, interrogation, data entry, switch and mode selection, and continuous/time-critical action control. The ratings of the first three categories showed the most promise of being beneficial to flight deck operations. Possible applications of voice synthesis systems were categorized as automatic or pilot selectable and many were rated as being potentially beneficial. In addition, voice system implementation guidelines and pertinent performance criteria are proposed. Finally, the findings of this study are compared with those made in a recent NASA study of a 1995 transport concept.

Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

PubMed Central

Islam, Md. Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al. PMID:25114676

Morphological and population genomic evidence that human faces have evolved to signal individual identity.

PubMed

Sheehan, Michael J; Nachman, Michael W

2014-09-16

Facial recognition plays a key role in human interactions, and there has been great interest in understanding the evolution of human abilities for individual recognition and tracking social relationships. Individual recognition requires sufficient cognitive abilities and phenotypic diversity within a population for discrimination to be possible. Despite the importance of facial recognition in humans, the evolution of facial identity has received little attention. Here we demonstrate that faces evolved to signal individual identity under negative frequency-dependent selection. Faces show elevated phenotypic variation and lower between-trait correlations compared with other traits. Regions surrounding face-associated single nucleotide polymorphisms show elevated diversity consistent with frequency-dependent selection. Genetic variation maintained by identity signalling tends to be shared across populations and, for some loci, predates the origin of Homo sapiens. Studies of human social evolution tend to emphasize cognitive adaptations, but we show that social evolution has shaped patterns of human phenotypic and genetic diversity as well.

On the limited recognition of inorganic surfaces by short peptides compared with antibodies.

PubMed

Artzy-Schnirman, Arbel; Abu-Shah, Enas; Dishon, Matan; Soifer, Hadas; Sivan, Yotam; Reiter, Yoram; Benhar, Itai; Sivan, Uri

2014-06-01

The vast potential applications of biomolecules that bind inorganic surfaces led mostly to the isolation of short peptides that target selectively specific materials. The demonstrated differential affinity toward certain surfaces created the impression that the recognition capacity of short peptides may match that of rigid biomolecules. In the following, we challenge this view by comparing the capacity of antibody molecules to discriminate between the (100) and (111A) facets of a gallium arsenide semiconductor crystal with the capacity of short peptides to do the same. Applying selection from several peptide and single chain phage display libraries, we find a number of antibody molecules that bind preferentially a given crystal facet but fail to isolate, in dozens of attempts, a single peptide capable of such recognition. The experiments underscore the importance of rigidity to the recognition of inorganic flat targets and therefore set limitations on potential applications of short peptides in biomimetics. Copyright © 2014 European Peptide Society and John Wiley & Sons, Ltd.

Feature and score fusion based multiple classifier selection for iris recognition.

PubMed

Islam, Md Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Study to determine potential flight applications and human factors design guidelines for voice recognition and synthesis systems

NASA Technical Reports Server (NTRS)

White, R. W.; Parks, D. L.

1985-01-01

A study was conducted to determine potential commercial aircraft flight deck applications and implementation guidelines for voice recognition and synthesis. At first, a survey of voice recognition and synthesis technology was undertaken to develop a working knowledge base. Then, numerous potential aircraft and simulator flight deck voice applications were identified and each proposed application was rated on a number of criteria in order to achieve an overall payoff rating. The potential voice recognition applications fell into five general categories: programming, interrogation, data entry, switch and mode selection, and continuous/time-critical action control. The ratings of the first three categories showed the most promise of being beneficial to flight deck operations. Possible applications of voice synthesis systems were categorized as automatic or pilot selectable and many were rated as being potentially beneficial. In addition, voice system implementation guidelines and pertinent performance criteria are proposed. Finally, the findings of this study are compared with those made in a recent NASA study of a 1995 transport concept.

Selective recognition of 6-mercaptopurine based on luminescent metal-organic frameworks Fe-MIL-88NH₂.

PubMed

Sun, Zhengjuan; Liu, Yali; Li, Yuanfang

2015-03-15

A novel and rapid spectrofluorometry method for the recognition of 6-mercaptopurine (6-MP) has been developed based on luminescent metal-organic frameworks Fe-MIL-88NH2 as fluorescent probe. The strong fluorescence of Fe-MIL-88NH2 at 430 nm could be quenched by 6-MP directly, and the Fe-MIL-88NH2 shows high selectivity for 6-MP compared to other thiol-containing amino acids such as homocysteine (Hcy), cysteine (Cys), glutathione (GSH), etc. Under optimal conditions, the relative fluorescence intensity was linearly proportional to the concentration of 6-MP in the range of 5-600 μM with the detection limit at 1.17 μM (S/N=3). Furthermore, the present approach has been successfully applied to the determination of 6-MP in human serum samples. The possible fluorescence quenching mechanism has also been investigated, where it is revealed that the quenching was attributed to competition of absorption of the light source energy as well as electron transfer between Fe-MIL-88NH2 and 6-MP. Copyright © 2014 Elsevier B.V. All rights reserved.

Radioligand Recognition of Insecticide Targets.

PubMed

Casida, John E

2018-04-04

Insecticide radioligands allow the direct recognition and analysis of the targets and mechanisms of toxic action critical to effective and safe pest control. These radioligands are either the insecticides themselves or analogs that bind at the same or coupled sites. Preferred radioligands and their targets, often in both insects and mammals, are trioxabicyclooctanes for the γ-aminobutyric acid (GABA) receptor, avermectin for the glutamate receptor, imidacloprid for the nicotinic receptor, ryanodine and chlorantraniliprole for the ryanodine receptor, and rotenone or pyridaben for NADH + ubiquinone oxidoreductase. Pyrethroids and other Na + channel modulator insecticides are generally poor radioligands due to lipophilicity and high nonspecific binding. For target site validation, the structure-activity relationships competing with the radioligand in the binding assays should be the same as that for insecticidal activity or toxicity except for rapidly detoxified or proinsecticide analogs. Once the radioligand assay is validated for relevance, it will often help define target site modifications on selection of resistant pest strains, selectivity between insects and mammals, and interaction with antidotes and other chemicals at modulator sites. Binding assays also serve for receptor isolation and photoaffinity labeling to characterize the interactions involved.

Upconversion particles coated with molecularly imprinted polymers as fluorescence probe for detection of clenbuterol.

PubMed

Tang, Yiwei; Gao, Ziyuan; Wang, Shuo; Gao, Xue; Gao, Jingwen; Ma, Yong; Liu, Xiuying; Li, Jianrong

2015-09-15

A novel fluorescence probe based on upconversion particles, YF3:Yb(3+), Er(3+), coating with molecularly imprinted polymers (MIPs@UCPs) has been synthesized for selective recognition of the analyte clenbuterol (CLB), which was characterized by scan electron microscope and X-ray powder diffraction. The fluorescence of the MIPs@UCPs probe is quenched specifically by CLB, and the effect is much stronger than the NIPs@UCPs (non-imprinting polymers, NIPs). Good linear correlation was obtained for CLB over the concentration range of 5.0-100.0 μg L(-1) with a detection limit of 0.12 μg L(-1) (S/N=3). The developed method was also used in the determination of CLB in water and pork samples, and the recoveries ranged from 81.66% to 102.46% were obtained with relative standard deviation of 2.96-4.98% (n=3). The present study provides a new and general tactics to synthesize MIPs@UCPs fluorescence probe with highly selective recognition ability to the CLB and is desirable for application widely in the near future. Copyright © 2015 Elsevier B.V. All rights reserved.

Age-specific effects of voluntary exercise on memory and the older brain.

PubMed

Siette, Joyce; Westbrook, R Frederick; Cotman, Carl; Sidhu, Kuldip; Zhu, Wanlin; Sachdev, Perminder; Valenzuela, Michael J

2013-03-01

Physical exercise in early adulthood and mid-life improves cognitive function and enhances brain plasticity, but the effects of commencing exercise in late adulthood are not well-understood. We investigated the effects of voluntary exercise in the restoration of place recognition memory in aged rats and examined hippocampal changes of synaptic density and neurogenesis. We found a highly selective age-related deficit in place recognition memory that is stable across retest sessions and correlates strongly with loss of hippocampal synapses. Additionally, 12 weeks of voluntary running at 20 months of age removed the deficit in the hippocampally dependent place recognition memory. Voluntary running restored presynaptic density in the dentate gyrus and CA3 hippocampal subregions in aged rats to levels beyond those observed in younger animals, in which exercise had no functional or synaptic effects. By contrast, hippocampal neurogenesis, a possible memory-related mechanism, increased in both young and aged rats after physical exercise but was not linked with performance in the place recognition task. We used graph-based network analysis based on synaptic covariance patterns to characterize efficient intrahippocampal connectivity. This analysis revealed that voluntary running completely reverses the profound degradation of hippocampal network efficiency that accompanies sedentary aging. Furthermore, at an individual animal level, both overall hippocampal presynaptic density and subregional connectivity independently contribute to prediction of successful place recognition memory performance. Our findings emphasize the unique synaptic effects of exercise on the aged brain and their specific relevance to a hippocampally based memory system for place recognition. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

A functional applied material on recognition of metal ion zinc based on the double azine compound.

PubMed

Wei, Taibao; Liang, Guoyan; Chen, Xiaopeng; Qi, Jin; Lin, Qi; Zhang, Youming; Yao, Hong

2017-05-18

A colorimetric and fluorescent probe L has been designed and synthesized, which bearing the double azine moiety and showing a detection limit of 2.725 × 10 -7  M towards Zn 2+ . Based on the basic recognition mechanism of ESIPT and CHEF effect, the L has high selectivity and sensitivity to only Zn 2+ (not Fe 3+ , Hg 2+ , Ag + , Ca 2+ , Co 2+ , Ni 2+ , Cd 2+ , Pb 2+ , Cr 3+ , and Mg 2+ ) within the physiological pH range (pH = 7.0-8.4) and showed a fluorescence switch. Moreover, this detection progress occured in the DMSO/H 2 O ∼ HEPES buffer (80/20, v/v; pH 7.23) solution which can conveniently used on test strip.

Handwritten digits recognition based on immune network

NASA Astrophysics Data System (ADS)

Li, Yangyang; Wu, Yunhui; Jiao, Lc; Wu, Jianshe

2011-11-01

With the development of society, handwritten digits recognition technique has been widely applied to production and daily life. It is a very difficult task to solve these problems in the field of pattern recognition. In this paper, a new method is presented for handwritten digit recognition. The digit samples firstly are processed and features extraction. Based on these features, a novel immune network classification algorithm is designed and implemented to the handwritten digits recognition. The proposed algorithm is developed by Jerne's immune network model for feature selection and KNN method for classification. Its characteristic is the novel network with parallel commutating and learning. The performance of the proposed method is experimented to the handwritten number datasets MNIST and compared with some other recognition algorithms-KNN, ANN and SVM algorithm. The result shows that the novel classification algorithm based on immune network gives promising performance and stable behavior for handwritten digits recognition.

Intrusion recognition for optic fiber vibration sensor based on the selective attention mechanism

NASA Astrophysics Data System (ADS)

Xu, Haiyan; Xie, Yingjuan; Li, Min; Zhang, Zhuo; Zhang, Xuewu

2017-11-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, an intrusion recognition based on the auditory selective attention mechanism is proposed. Firstly, considering the time-frequency of vibration, the spectrogram is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Based on these maps, the feature matrix is formed after normalization. The system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises. What's more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.

Insights into deep-sea adaptations and host-symbiont interactions: A comparative transcriptome study on Bathymodiolus mussels and their coastal relatives.

PubMed

Zheng, Ping; Wang, Minxiao; Li, Chaolun; Sun, Xiaoqing; Wang, Xiaocheng; Sun, Yan; Sun, Song

2017-10-01

Mussels (Bivalve: Mytilidae) have adapted to various habitats, from fresh water to the deep sea. To understand their adaptive characteristics in different habitats, particularly in the bathymodiolin mussels in deep-sea chemosynthetic ecosystems, we conducted a comparative transcriptomic analysis between deep-sea bathymodiolin mussels and their shallow-water relatives. A number of gene families related to stress responses were shared across all mussels, without specific or significantly expanded families in deep-sea species, indicating that all mussels are capable of adapting to diverse harsh environments, but that different members of the same gene family may be preferentially utilized by different species. One of the most extraordinary trait of bathymodiolin mussels is their endosymbiosis. Lineage-specific and positively selected TLRs and highly expressed C1QDC proteins were identified in the gills of the bathymodiolins, suggesting their possible functions in symbiont recognition. However, pattern recognition receptors of the bathymodiolins were globally reduced, facilitating the invasion and maintenance of the symbionts obtained by either endocytosis or phagocytosis. Additionally, various transporters were positively selected or more highly expressed in the deep-sea mussels, indicating a means by which necessary materials could be provided for the symbionts. Key genes supporting lysosomal activity were also positively selected or more highly expressed in the deep-sea mussels, suggesting that nutrition fixed by the symbionts can be absorbed in a "farming" way wherein the symbionts are digested by lysosomes. Regulation of key physiological processes including lysosome activity, apoptosis and immune reactions is needed to maintain a stable host-symbiont relationship, but the mechanisms are still unclear. © 2017 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Conjugates of classical DNA/RNA binder with nucleobase: chemical, biochemical and biomedical applications.

PubMed

Saftic, Dijana; Ban, Zeljka; Matic, Josipa; Tumir, Lidija-Marija; Piantanida, Ivo

2018-05-07

Among the most intensively studied classes of small molecules (molecular weight < 650) in biomedical research are small molecules that non-covalently bind to DNA/RNA, and another intensively studied class are nucleobase derivatives. Both classes have been intensively elaborated in many books and reviews. However, conjugates consisting of DNA/RNA binder covalently linked to nucleobase are much less studied and have not been reviewed in the last two decades. Therefore, this review summarized reports on the design of classical DNA/RNA binder - nucleobase conjugates, as well as data about their interactions with various DNA or RNA targets, and even in some cases protein targets involved. According to these data, the most important structural aspects of selective or even specific recognition between small molecule and target are proposed, and where possible related biochemical and biomedical aspects were discussed. The general conclusion is that this, rather new class of molecules showed an amazing set of recognition tools for numerous DNA or RNA targets in the last two decades, as well as few intriguing in vitro and in vivo selectivities. Several lead research lines show promising advancements toward either novel, highly selective markers or bioactive, potentially druggable molecules. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Human striatal activation during adjustment of the response criterion in visual word recognition.

PubMed

Kuchinke, Lars; Hofmann, Markus J; Jacobs, Arthur M; Frühholz, Sascha; Tamm, Sascha; Herrmann, Manfred

2011-02-01

Results of recent computational modelling studies suggest that a general function of the striatum in human cognition is related to shifting decision criteria in selection processes. We used functional magnetic resonance imaging (fMRI) in 21 healthy subjects to examine the hemodynamic responses when subjects shift their response criterion on a trial-by-trial basis in the lexical decision paradigm. Trial-by-trial criterion setting is obtained when subjects respond faster in trials following a word trial than in trials following nonword trials - irrespective of the lexicality of the current trial. Since selection demands are equally high in the current trials, we expected to observe neural activations that are related to response criterion shifting. The behavioural data show sequential effects with faster responses in trials following word trials compared to trials following nonword trials, suggesting that subjects shifted their response criterion on a trial-by-trial basis. The neural responses revealed a signal increase in the striatum only in trials following word trials. This striatal activation is therefore likely to be related to response criterion setting. It demonstrates a role of the striatum in shifting decision criteria in visual word recognition, which cannot be attributed to pure error-related processing or the selection of a preferred response. Copyright © 2010 Elsevier Inc. All rights reserved.

The use of selective adsorbents in capillary electrophoresis-mass spectrometry for analyte preconcentration and microreactions: a powerful three-dimensional tool for multiple chemical and biological applications.

PubMed

Guzman, N A; Stubbs, R J

2001-10-01

Much attention has recently been directed to the development and application of online sample preconcentration and microreactions in capillary electrophoresis using selective adsorbents based on chemical or biological specificity. The basic principle involves two interacting chemical or biological systems with high selectivity and affinity for each other. These molecular interactions in nature usually involve noncovalent and reversible chemical processes. Properly bound to a solid support, an "affinity ligand" can selectively adsorb a "target analyte" found in a simple or complex mixture at a wide range of concentrations. As a result, the isolated analyte is enriched and highly purified. When this affinity technique, allowing noncovalent chemical interactions and biochemical reactions to occur, is coupled on-line to high-resolution capillary electrophoresis and mass spectrometry, a powerful tool of chemical and biological information is created. This paper describes the concept of biological recognition and affinity interaction on-line with high-resolution separation, the fabrication of an "analyte concentrator-microreactor", optimization conditions of adsorption and desorption, the coupling to mass spectrometry, and various applications of clinical and pharmaceutical interest.

Scanning probe recognition microscopy investigation of tissue scaffold properties

PubMed Central

Fan, Yuan; Chen, Qian; Ayres, Virginia M; Baczewski, Andrew D; Udpa, Lalita; Kumar, Shiva

2007-01-01

Scanning probe recognition microscopy is a new scanning probe microscopy technique which enables selective scanning along individual nanofibers within a tissue scaffold. Statistically significant data for multiple properties can be collected by repetitively fine-scanning an identical region of interest. The results of a scanning probe recognition microscopy investigation of the surface roughness and elasticity of a series of tissue scaffolds are presented. Deconvolution and statistical methods were developed and used for data accuracy along curved nanofiber surfaces. Nanofiber features were also independently analyzed using transmission electron microscopy, with results that supported the scanning probe recognition microscopy-based analysis. PMID:18203431

Scanning probe recognition microscopy investigation of tissue scaffold properties.

PubMed

Fan, Yuan; Chen, Qian; Ayres, Virginia M; Baczewski, Andrew D; Udpa, Lalita; Kumar, Shiva

2007-01-01

Scanning probe recognition microscopy is a new scanning probe microscopy technique which enables selective scanning along individual nanofibers within a tissue scaffold. Statistically significant data for multiple properties can be collected by repetitively fine-scanning an identical region of interest. The results of a scanning probe recognition microscopy investigation of the surface roughness and elasticity of a series of tissue scaffolds are presented. Deconvolution and statistical methods were developed and used for data accuracy along curved nanofiber surfaces. Nanofiber features were also independently analyzed using transmission electron microscopy, with results that supported the scanning probe recognition microscopy-based analysis.

Assessment and importance of personality disorders in medical patients: an update.

PubMed

Dhossche, D M; Shevitz, S A

1999-06-01

Personality disorders in medical patients have received less attention than depression, anxiety, or somatization. We conducted a selective literature search to assess the role of personality disorders in medical patients. Review of recent studies suggests a high prevalence and morbidity of personality disorders in medical populations. Important correlates in selected groups are depression, somatization, noncompliance, sexual risk taking, and substance abuse. Difficulties in physician-patient relationships are also frequently reported. Psychiatric interventions are considered beneficial, though no single treatment of choice is available. We recommend that physicians consider the possibility of personality disorders in medical patients to choose appropriate treatments for selected symptoms. Training in interviewing skills may enhance recognition of personality disorders and management of associated psychiatric conditions.

The Doors and People Test: The Effect of Frontal Lobe Lesions on Recall and Recognition Memory Performance

PubMed Central

2016-01-01

Objective: Memory deficits in patients with frontal lobe lesions are most apparent on free recall tasks that require the selection, initiation, and implementation of retrieval strategies. The effect of frontal lesions on recognition memory performance is less clear with some studies reporting recognition memory impairments but others not. The majority of these studies do not directly compare recall and recognition within the same group of frontal patients, assessing only recall or recognition memory performance. Other studies that do compare recall and recognition in the same frontal group do not consider recall or recognition tests that are comparable for difficulty. Recognition memory impairments may not be reported because recognition memory tasks are less demanding. Method: This study aimed to investigate recall and recognition impairments in the same group of 47 frontal patients and 78 healthy controls. The Doors and People Test was administered as a neuropsychological test of memory as it assesses both verbal and visual recall and recognition using subtests that are matched for difficulty. Results: Significant verbal and visual recall and recognition impairments were found in the frontal patients. Conclusion: These results demonstrate that when frontal patients are assessed on recall and recognition memory tests of comparable difficulty, memory impairments are found on both types of episodic memory test. PMID:26752123

The Doors and People Test: The effect of frontal lobe lesions on recall and recognition memory performance.

PubMed

MacPherson, Sarah E; Turner, Martha S; Bozzali, Marco; Cipolotti, Lisa; Shallice, Tim

2016-03-01

Memory deficits in patients with frontal lobe lesions are most apparent on free recall tasks that require the selection, initiation, and implementation of retrieval strategies. The effect of frontal lesions on recognition memory performance is less clear with some studies reporting recognition memory impairments but others not. The majority of these studies do not directly compare recall and recognition within the same group of frontal patients, assessing only recall or recognition memory performance. Other studies that do compare recall and recognition in the same frontal group do not consider recall or recognition tests that are comparable for difficulty. Recognition memory impairments may not be reported because recognition memory tasks are less demanding. This study aimed to investigate recall and recognition impairments in the same group of 47 frontal patients and 78 healthy controls. The Doors and People Test was administered as a neuropsychological test of memory as it assesses both verbal and visual recall and recognition using subtests that are matched for difficulty. Significant verbal and visual recall and recognition impairments were found in the frontal patients. These results demonstrate that when frontal patients are assessed on recall and recognition memory tests of comparable difficulty, memory impairments are found on both types of episodic memory test. (c) 2016 APA, all rights reserved).

A highly selective and picomolar level photoelectrochemical sensor for PCB 101 detection in environmental water samples.

PubMed

Shi, Huijie; Zhao, Jinzhi; Wang, Yingling; Zhao, Guohua

2016-07-15

A highly selective and sensitive photoelectrochemical (PEC) sensor was fabricated for fast and convenient detection of PCB 101 in environmental water samples with a low detection limit of 1.0×10(-14)molL(-1) based on single crystalline TiO2 nanorods (NRs). By integration with molecular imprinting (MI) technique, the PEC sensor's selectivity towards PCB 101 was significantly improved, so that the interference caused by 100-fold excess of PCB 126 and PCB 77 which had similar structure with PCB 101 was below 37%, not to mention other coexisted pollutants. This high selectivity could be attributed to the high-quality expression of the molecular imprinting sites on the rigid and smooth surface of single crystalline TiO2 NRs on which PCB 101 could be selectively and preferentially adsorbed. The oriented and multiple halogen bonds formed between PCB 101 and the molecular imprinting sites played a critical role in improving the recognition ability of the PEC sensor. Meanwhile, the one dimensional nanorods structure of TiO2 was beneficial for the efficient separation of photogenerated electrons and holes, leading to enhanced photocurrent response and further improving the sensitivity of the PEC sensor. Copyright © 2016 Elsevier B.V. All rights reserved.

Molecular Imprinting of Macromolecules for Sensor Applications

PubMed Central

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

2017-01-01

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. PMID:28422082

Phase effects in masking by harmonic complexes: speech recognition.

PubMed

Deroche, Mickael L D; Culling, John F; Chatterjee, Monita

2013-12-01

Harmonic complexes that generate highly modulated temporal envelopes on the basilar membrane (BM) mask a tone less effectively than complexes that generate relatively flat temporal envelopes, because the non-linear active gain of the BM selectively amplifies a low-level tone in the dips of a modulated masker envelope. The present study examines a similar effect in speech recognition. Speech reception thresholds (SRTs) were measured for a voice masked by harmonic complexes with partials in sine phase (SP) or in random phase (RP). The masker's fundamental frequency (F0) was 50, 100 or 200 Hz. SRTs were considerably lower for SP than for RP maskers at 50-Hz F0, but the two converged at 100-Hz F0, while at 200-Hz F0, SRTs were a little higher for SP than RP maskers. The results were similar whether the target voice was male or female and whether the masker's spectral profile was flat or speech-shaped. Although listening in the masker dips has been shown to play a large role for artificial stimuli such as Schroeder-phase complexes at high levels, it contributes weakly to speech recognition in the presence of harmonic maskers with different crest factors at more moderate sound levels (65 dB SPL). Copyright © 2013 Elsevier B.V. All rights reserved.

Molecular Imprinting of Macromolecules for Sensor Applications.

PubMed

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.

Evolution of Novel Signal Traits in the Absence of Female Preferences in Neoconocephalus Katydids (Orthoptera, Tettigoniidae)

PubMed Central

Bush, Sarah L.; Schul, Johannes

2010-01-01

Background Significance Communication signals that function to bring together the sexes are important for maintaining reproductive isolation in many taxa. Changes in male calls are often attributed to sexual selection, in which female preferences initiate signal divergence. Natural selection can also influence signal traits if calls attract predators or parasitoids, or if calling is energetically costly. Neutral evolution is often neglected in the context of acoustic communication. Methodology/Principal Findings We describe a signal trait that appears to have evolved in the absence of either sexual or natural selection. In the katydid genus Neoconocephalus, calls with a derived pattern in which pulses are grouped into pairs have evolved five times independently. We have previously shown that in three of these species, females require the double pulse pattern for call recognition, and hence the recognition system of the females is also in a derived state. Here we describe the remaining two species and find that although males produce the derived call pattern, females use the ancestral recognition mechanism in which no pulse pattern is required. Females respond equally well to the single and double pulse calls, indicating that the derived trait is selectively neutral in the context of mate recognition. Conclusions/Significance These results suggest that 1) neutral changes in signal traits could be important in the diversification of communication systems, and 2) males rather than females may be responsible for initiating signal divergence. PMID:20805980

Semantic Ambiguity: Do Multiple Meanings Inhibit or Facilitate Word Recognition?

PubMed

Haro, Juan; Ferré, Pilar

2018-06-01

It is not clear whether multiple unrelated meanings inhibit or facilitate word recognition. Some studies have found a disadvantage for words having multiple meanings with respect to unambiguous words in lexical decision tasks (LDT), whereas several others have shown a facilitation for such words. In the present study, we argue that these inconsistent findings may be due to the approach employed to select ambiguous words across studies. To address this issue, we conducted three LDT experiments in which we varied the measure used to classify ambiguous and unambiguous words. The results suggest that multiple unrelated meanings facilitate word recognition. In addition, we observed that the approach employed to select ambiguous words may affect the pattern of experimental results. This evidence has relevant implications for theoretical accounts of ambiguous words processing and representation.

HAPTEN DESIGN FOR COMPOUND-SELECTIVE ANTIBODIES: ELISAS FOR ENVIRONMENTALLY DELETERIOUS SMALL MOLECULES. (R825433)

EPA Science Inventory

We have developed an enzyme-linked immunosorbent assay (ELISA) for the herbicide simazine with virtually no recognition of propazine and very low (8%) recognition of atrazine. In this research we have developed a generalized "size-exclusion" concept for designing immun...

Optical Character Recognition.

ERIC Educational Resources Information Center

Converso, L.; Hocek, S.

1990-01-01

This paper describes computer-based optical character recognition (OCR) systems, focusing on their components (the computer, the scanner, the OCR, and the output device); how the systems work; and features to consider in selecting a system. A list of 26 questions to ask to evaluate systems for potential purchase is included. (JDD)

SH2 Domains Recognize Contextual Peptide Sequence Information to Determine Selectivity*

PubMed Central

Liu, Bernard A.; Jablonowski, Karl; Shah, Eshana E.; Engelmann, Brett W.; Jones, Richard B.; Nash, Piers D.

2010-01-01

Selective ligand recognition by modular protein interaction domains is a primary determinant of specificity in signaling pathways. Src homology 2 (SH2) domains fulfill this capacity immediately downstream of tyrosine kinases, acting to recruit their host polypeptides to ligand proteins harboring phosphorylated tyrosine residues. The degree to which SH2 domains are selective and the mechanisms underlying selectivity are fundamental to understanding phosphotyrosine signaling networks. An examination of interactions between 50 SH2 domains and a set of 192 phosphotyrosine peptides corresponding to physiological motifs within FGF, insulin, and IGF-1 receptor pathways indicates that individual SH2 domains have distinct recognition properties and exhibit a remarkable degree of selectivity beyond that predicted by previously described binding motifs. The underlying basis for such selectivity is the ability of SH2 domains to recognize both permissive amino acid residues that enhance binding and non-permissive amino acid residues that oppose binding in the vicinity of the essential phosphotyrosine. Neighboring positions affect one another so local sequence context matters to SH2 domains. This complex linguistics allows SH2 domains to distinguish subtle differences in peptide ligands. This newly appreciated contextual dependence substantially increases the accessible information content embedded in the peptide ligands that can be effectively integrated to determine binding. This concept may serve more broadly as a paradigm for subtle recognition of physiological ligands by protein interaction domains. PMID:20627867

A target recognition method for maritime surveillance radars based on hybrid ensemble selection

NASA Astrophysics Data System (ADS)

Fan, Xueman; Hu, Shengliang; He, Jingbo

2017-11-01

In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

Lithium Ion Recognition with Nanofluidic Diodes through Host-Guest Complexation in Confined Geometries.

PubMed

Ali, Mubarak; Ahmed, Ishtiaq; Ramirez, Patricio; Nasir, Saima; Mafe, Salvador; Niemeyer, Christof M; Ensinger, Wolfgang

2018-05-15

The lithium ion recognition is receiving significant attention because of its application in pharmaceuticals, lubricants and, especially, in energy technology. We present a nanofluidic device for specific lithium ion recognition via host-guest complexation in a confined environment. A lithium-selective receptor molecule, the aminoethyl-benzo-12-crown-4 (BC12C4-NH 2 ), is designed and functionalized on single conical nanopores in polyethylene terephthalate (PET) membranes. The native carboxylic acid groups on the pore walls are covalently linked with the crown ether moieties and the process is monitored from the changes in the current-voltage ( I- V) curves. The B12-crown-4 moieties are known to specifically bind with lithium ions and when the modified pore is exposed to different alkali metal chloride solutions separately, significant changes in the ion current and rectification are only observed for lithium chloride. This fact suggests the generation of positively charged B12C4-Li + complexes on the pore surface. Furthermore, the nanofluidic diode is able to recognize the lithium ion even in the presence of high concentrations of potassium ions in the external electrolyte solution. Thus, this nanodevice suggests a strategy to miniaturize nanofluidic porous systems for efficient recognition, extraction, and separation of lithium from raw materials.

Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry.

PubMed

Chowdhury, Alok Kumar; Tjondronegoro, Dian; Chandran, Vinod; Trost, Stewart G

2017-09-01

To investigate whether the use of ensemble learning algorithms improve physical activity recognition accuracy compared to the single classifier algorithms, and to compare the classification accuracy achieved by three conventional ensemble machine learning methods (bagging, boosting, random forest) and a custom ensemble model comprising four algorithms commonly used for activity recognition (binary decision tree, k nearest neighbor, support vector machine, and neural network). The study used three independent data sets that included wrist-worn accelerometer data. For each data set, a four-step classification framework consisting of data preprocessing, feature extraction, normalization and feature selection, and classifier training and testing was implemented. For the custom ensemble, decisions from the single classifiers were aggregated using three decision fusion methods: weighted majority vote, naïve Bayes combination, and behavior knowledge space combination. Classifiers were cross-validated using leave-one subject out cross-validation and compared on the basis of average F1 scores. In all three data sets, ensemble learning methods consistently outperformed the individual classifiers. Among the conventional ensemble methods, random forest models provided consistently high activity recognition; however, the custom ensemble model using weighted majority voting demonstrated the highest classification accuracy in two of the three data sets. Combining multiple individual classifiers using conventional or custom ensemble learning methods can improve activity recognition accuracy from wrist-worn accelerometer data.

A fluorescein-based chemosensor for relay fluorescence recognition of Cu(ii) ions and biothiols in water and its applications to a molecular logic gate and living cell imaging.

PubMed

Fu, Zhen-Hai; Yan, Lu-Bin; Zhang, Xiaolong; Zhu, Fan-Fan; Han, Xin-Long; Fang, Jianguo; Wang, Ya-Wen; Peng, Yu

2017-05-16

Relay recognition of copper(ii) ions and biothiols via a fluorescence "on-off-on" cascade was designed and realized as a new sequential combination of cations and small molecules. Probe 1 bearing a fluorescein skeleton was thus synthesized, which performed well in 100% HEPES buffer (pH = 7.0) solution, as a highly sensitive, selective fluorescence sensor for Cu 2+ . The limit of detection (LOD, 0.017 ppm) was obtained, and this value is much lower than 1.3 ppm, allowed by US EPA. The 1 : 1 complex generated from fast sensing of Cu 2+ when excited at 491 nm, showed good relay recognition for biothiols (i.e., Cys, Hcy and GSH with low detection limits of 0.12 μM, 0.036 μM and 0.024 μM, respectively) via remarkable fluorescence enhancement. The origin of this relay process was disclosed through ESI-MS and corresponding density functional theory (DFT) computations. Notably, probe 1 can be utilized for the construction of a molecular logic gate with the IMPLICATION function by using the above fluorescence changes. Moreover, this relay recognition was also applied to HepG2 cell imaging successfully.

Chemically mediated species recognition in closely related Podarcis wall lizards.

PubMed

Barbosa, Diana; Font, Enrique; Desfilis, Ester; Carretero, Miguel A

2006-07-01

In many animals, chemical signals play an important role in species recognition and may contribute to reproductive isolation and speciation. The Iberian lizards of the genus Podarcis, with up to nine currently recognized lineages that are often sympatric, are highly chemosensory and provide an excellent model for the study of chemically mediated species recognition in closely related taxa. In this study, we tested the ability of male and female lizards of two sister species with widely overlapping distribution ranges (Podarcis bocagei and P. hispanica type 1) to discriminate between conspecific and heterospecific mates by using only substrate-borne chemical cues. We scored the number of tongue flicks directed at the paper substrate by each individual in a terrarium previously occupied by a conspecific or a heterospecific lizard of the opposite sex. Results show that males of P. bocagei and P. hispanica type 1 are capable of discriminating chemically between conspecifics and heterospecifics of the opposite sex, but females are not. These results suggest that differences in female, but not male, chemical cues may underlie species recognition and contribute to reproductive isolation in these species. The apparent inability of females to discriminate conspecific from heterospecific males, which is not because of reduced baseline exploration rates, is discussed in the context of sexual selection theory and species discrimination.

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

PubMed

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.

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

PubMed Central

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

Optogenetic Stimulation of Prefrontal Glutamatergic Neurons Enhances Recognition Memory.

PubMed

Benn, Abigail; Barker, Gareth R I; Stuart, Sarah A; Roloff, Eva V L; Teschemacher, Anja G; Warburton, E Clea; Robinson, Emma S J

2016-05-04

Finding effective cognitive enhancers is a major health challenge; however, modulating glutamatergic neurotransmission has the potential to enhance performance in recognition memory tasks. Previous studies using glutamate receptor antagonists have revealed that the medial prefrontal cortex (mPFC) plays a central role in associative recognition memory. The present study investigates short-term recognition memory using optogenetics to target glutamatergic neurons within the rodent mPFC specifically. Selective stimulation of glutamatergic neurons during the online maintenance of information enhanced associative recognition memory in normal animals. This cognitive enhancing effect was replicated by local infusions of the AMPAkine CX516, but not CX546, which differ in their effects on EPSPs. This suggests that enhancing the amplitude, but not the duration, of excitatory synaptic currents improves memory performance. Increasing glutamate release through infusions of the mGluR7 presynaptic receptor antagonist MMPIP had no effect on performance. These results provide new mechanistic information that could guide the targeting of future cognitive enhancers. Our work suggests that improved associative-recognition memory can be achieved by enhancing endogenous glutamatergic neuronal activity selectively using an optogenetic approach. We build on these observations to recapitulate this effect using drug treatments that enhance the amplitude of EPSPs; however, drugs that alter the duration of the EPSP or increase glutamate release lack efficacy. This suggests that both neural and temporal specificity are needed to achieve cognitive enhancement. Copyright © 2016 Benn et al.

Impaired recognition of scary music following unilateral temporal lobe excision.

PubMed

Gosselin, Nathalie; Peretz, Isabelle; Noulhiane, Marion; Hasboun, Dominique; Beckett, Christine; Baulac, Michel; Samson, Séverine

2005-03-01

Music constitutes an ideal means to create a sense of suspense in films. However, there has been minimal investigation into the underlying cerebral organization for perceiving danger created by music. In comparison, the amygdala's role in recognition of fear in non-musical contexts has been well established. The present study sought to fill this gap in exploring how patients with amygdala resection recognize emotional expression in music. To this aim, we tested 16 patients with left (LTR; n = 8) or right (RTR; n = 8) medial temporal resection (including amygdala) for the relief of medically intractable seizures and 16 matched controls in an emotion recognition task involving instrumental music. The musical selections were purposely created to induce fear, peacefulness, happiness and sadness. Participants were asked to rate to what extent each musical passage expressed these four emotions on 10-point scales. In order to check for the presence of a perceptual problem, the same musical selections were presented to the participants in an error detection task. None of the patients was found to perform below controls in the perceptual task. In contrast, both LTR and RTR patients were found to be impaired in the recognition of scary music. Recognition of happy and sad music was normal. These findings suggest that the anteromedial temporal lobe (including the amygdala) plays a role in the recognition of danger in a musical context.

A highly sensitive and selective aptamer-based colorimetric sensor for the rapid detection of PCB 77.

PubMed

Cheng, Ruojie; Liu, Siyao; Shi, Huijie; Zhao, Guohua

2018-01-05

A highly sensitive, specific and simple colorimetric sensor based on aptamer was established for the detection of polychlorinated biphenyls (PCB 77). The use of unmodified gold nanoparticles as a colorimetric probe for aptamer sensors enabled the highly sensitive and selective detection of polychlorinated biphenyls (PCB 77). A linear range of 0.5nM to 900nM was obtained for the colorimetric assay with a minimum detection limit of 0.05nM. In addition, by the methods of circular dichroism, UV and naked eyes, we found that the 35 base fragments retained after cutting 5 bases from the 5 'end of aptamer plays the most significant role in the PCB 77 specific recognition process. We found a novel way to truncated nucleotides to optimize the detection of PCB 77, and the selected nucleotides also could achieve high affinity with PCB 77. At the same time, the efficient detection of the PCB 77 by our colorimetric sensor in the complex environmental water samples was realized, which shows a good application prospect. Copyright © 2017 Elsevier B.V. All rights reserved.

Design of molecular imprinted polymers compatible with aqueous environment.

PubMed

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.

More Pronounced Deficits in Facial Emotion Recognition for Schizophrenia than Bipolar Disorder

PubMed Central

Goghari, Vina M; Sponheim, Scott R

2012-01-01

Schizophrenia and bipolar disorder are typically separated in diagnostic systems. Behavioural, cognitive, and brain abnormalities associated with each disorder nonetheless overlap. We evaluated the diagnostic specificity of facial emotion recognition deficits in schizophrenia and bipolar disorder to determine whether select aspects of emotion recognition differed for the two disorders. The investigation used an experimental task that included the same facial images in an emotion recognition condition and an age recognition condition (to control for processes associated with general face recognition) in 27 schizophrenia patients, 16 bipolar I patients, and 30 controls. Schizophrenia and bipolar patients exhibited both shared and distinct aspects of facial emotion recognition deficits. Schizophrenia patients had deficits in recognizing angry facial expressions compared to healthy controls and bipolar patients. Compared to control participants, both schizophrenia and bipolar patients were more likely to mislabel facial expressions of anger as fear. Given that schizophrenia patients exhibited a deficit in emotion recognition for angry faces, which did not appear due to generalized perceptual and cognitive dysfunction, improving recognition of threat-related expression may be an important intervention target to improve social functioning in schizophrenia. PMID:23218816

Distinct roles of basal forebrain cholinergic neurons in spatial and object recognition memory.

PubMed

Okada, Kana; Nishizawa, Kayo; Kobayashi, Tomoko; Sakata, Shogo; Kobayashi, Kazuto

2015-08-06

Recognition memory requires processing of various types of information such as objects and locations. Impairment in recognition memory is a prominent feature of amnesia and a symptom of Alzheimer's disease (AD). Basal forebrain cholinergic neurons contain two major groups, one localized in the medial septum (MS)/vertical diagonal band of Broca (vDB), and the other in the nucleus basalis magnocellularis (NBM). The roles of these cell groups in recognition memory have been debated, and it remains unclear how they contribute to it. We use a genetic cell targeting technique to selectively eliminate cholinergic cell groups and then test spatial and object recognition memory through different behavioural tasks. Eliminating MS/vDB neurons impairs spatial but not object recognition memory in the reference and working memory tasks, whereas NBM elimination undermines only object recognition memory in the working memory task. These impairments are restored by treatment with acetylcholinesterase inhibitors, anti-dementia drugs for AD. Our results highlight that MS/vDB and NBM cholinergic neurons are not only implicated in recognition memory but also have essential roles in different types of recognition memory.

Genetic Mapping in Mice Reveals the Involvement of Pcdh9 in Long-Term Social and Object Recognition and Sensorimotor Development.

PubMed

Bruining, Hilgo; Matsui, Asuka; Oguro-Ando, Asami; Kahn, René S; Van't Spijker, Heleen M; Akkermans, Guus; Stiedl, Oliver; van Engeland, Herman; Koopmans, Bastijn; van Lith, Hein A; Oppelaar, Hugo; Tieland, Liselotte; Nonkes, Lourens J; Yagi, Takeshi; Kaneko, Ryosuke; Burbach, J Peter H; Yamamoto, Nobuhiko; Kas, Martien J

2015-10-01

Quantitative genetic analysis of basic mouse behaviors is a powerful tool to identify novel genetic phenotypes contributing to neurobehavioral disorders. Here, we analyzed genetic contributions to single-trial, long-term social and nonsocial recognition and subsequently studied the functional impact of an identified candidate gene on behavioral development. Genetic mapping of single-trial social recognition was performed in chromosome substitution strains, a sophisticated tool for detecting quantitative trait loci (QTL) of complex traits. Follow-up occurred by generating and testing knockout (KO) mice of a selected QTL candidate gene. Functional characterization of these mice was performed through behavioral and neurological assessments across developmental stages and analyses of gene expression and brain morphology. Chromosome substitution strain 14 mapping studies revealed an overlapping QTL related to long-term social and object recognition harboring Pcdh9, a cell-adhesion gene previously associated with autism spectrum disorder. Specific long-term social and object recognition deficits were confirmed in homozygous (KO) Pcdh9-deficient mice, while heterozygous mice only showed long-term social recognition impairment. The recognition deficits in KO mice were not associated with alterations in perception, multi-trial discrimination learning, sociability, behavioral flexibility, or fear memory. Rather, KO mice showed additional impairments in sensorimotor development reflected by early touch-evoked biting, rotarod performance, and sensory gating deficits. This profile emerged with structural changes in deep layers of sensory cortices, where Pcdh9 is selectively expressed. This behavior-to-gene study implicates Pcdh9 in cognitive functions required for long-term social and nonsocial recognition. This role is supported by the involvement of Pcdh9 in sensory cortex development and sensorimotor phenotypes. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Structural Basis of Egg Coat-Sperm Recognition at Fertilization.

PubMed

Raj, Isha; Sadat Al Hosseini, Hamed; Dioguardi, Elisa; Nishimura, Kaoru; Han, Ling; Villa, Alessandra; de Sanctis, Daniele; Jovine, Luca

2017-06-15

Recognition between sperm and the egg surface marks the beginning of life in all sexually reproducing organisms. This fundamental biological event depends on the species-specific interaction between rapidly evolving counterpart molecules on the gametes. We report biochemical, crystallographic, and mutational studies of domain repeats 1-3 of invertebrate egg coat protein VERL and their interaction with cognate sperm protein lysin. VERL repeats fold like the functionally essential N-terminal repeat of mammalian sperm receptor ZP2, whose structure is also described here. Whereas sequence-divergent repeat 1 does not bind lysin, repeat 3 binds it non-species specifically via a high-affinity, largely hydrophobic interface. Due to its intermediate binding affinity, repeat 2 selectively interacts with lysin from the same species. Exposure of a highly positively charged surface of VERL-bound lysin suggests that complex formation both disrupts the organization of egg coat filaments and triggers their electrostatic repulsion, thereby opening a hole for sperm penetration and fusion. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Aptamers: Active Targeting Ligands for Cancer Diagnosis and Therapy

PubMed Central

Wu, Xu; Chen, Jiao; Wu, Min; Zhao, Julia Xiaojun

2015-01-01

Aptamers, including DNA, RNA and peptide aptamers, are a group of promising recognition units that can specifically bind to target molecules and cells. Due to their excellent specificity and high affinity to targets, aptamers have attracted great attention in various fields in which selective recognition units are required. They have been used in biosensing, drug delivery, disease diagnosis and therapy (especially for cancer treatment). In this review, we summarized recent applications of DNA and RNA aptamers in cancer theranostics. The specific binding ability of aptamers to cancer-related markers and cancer cells ensured their high performance for early diagnosis of cancer. Meanwhile, the efficient targeting ability of aptamers to cancer cells and tissues provided a promising way to deliver imaging agents and drugs for cancer imaging and therapy. Furthermore, with the development of nanoscience and nanotechnology, the conjugation of aptamers with functional nanomaterials paved an exciting way for the fabrication of theranostic agents for different types of cancers, which might be a powerful tool for cancer treatment. PMID:25699094

Rotor-stator molecular crystals of fullerenes with cubane.

PubMed

Pekker, Sándor; Kováts, Eva; Oszlányi, Gábor; Bényei, Gyula; Klupp, Gyöngyi; Bortel, Gábor; Jalsovszky, István; Jakab, Emma; Borondics, Ferenc; Kamarás, Katalin; Bokor, Mónika; Kriza, György; Tompa, Kálmán; Faigel, Gyula

2005-10-01

Cubane (C8H8) and fullerene (C60) are famous cage molecules with shapes of platonic or archimedean solids. Their remarkable chemical and solid-state properties have induced great scientific interest. Both materials form polymorphic crystals of molecules with variable orientational ordering. The idea of intercalating fullerene with cubane was raised several years ago but no attempts at preparation have been reported. Here we show that C60 and similarly C70 form high-symmetry molecular crystals with cubane owing to topological molecular recognition between the convex surface of fullerenes and the concave cubane. Static cubane occupies the octahedral voids of the face-centred-cubic structures and acts as a bearing between the rotating fullerene molecules. The smooth contact of the rotor and stator molecules decreases significantly the temperature of orientational ordering. These materials have great topochemical importance: at elevated temperatures they transform to high-stability covalent derivatives although preserving their crystalline appearance. The size-dependent molecular recognition promises selective formation of related structures with higher fullerenes and/or substituted cubanes.

Halloysite-based dopamine-imprinted polymer for selective protein capture.

PubMed

Zhu, Xiaohong; Li, Hui; Liu, Hui; Peng, Wei; Zhong, Shian; Wang, Yan

2016-06-01

We describe a facile, general, and highly efficient approach to obtain polydopamine-coated molecularly imprinted polymer based on halloysite nanotubes for bovine serum albumin. The method combined surface molecular imprinting and one-step immobilized template technique. Hierarchically structured polymer was prepared in physiological conditions adopting dopamine as functional monomer. A thin layer of polydopamine can be coated on the surface of amino-modified halloysite nanotubes by self-polymerization, and the thickness of the imprinted shells can be controlled by the mass ratio of matrix and dopamine. The polymer was characterized by Fourier transform infrared spectrometry, transmission electron microscopy, and thermogravimetric analysis. The prepared material showed high binding capacity (45.4 mg/g) and specific recognition behavior toward the template protein. In addition, stability and regeneration analyses indicated that the imprinted polymer exhibited excellent reusability (relative standard deviation < 9% for batch-to-batch evaluation). Therefore, the developed polymer is effective for protein recognition and separation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cell specific aptamer-photosensitizer conjugates as a molecular tool in photodynamic therapy

PubMed Central

Mallikaratchy, Prabodhika; Tang, Zhiwen

2010-01-01

This paper describes the application of a molecular construct of a photosensitizer and an aptamer for photo-therapeutically targeting tumor cells. The key step in increasing selectivity in chemotherapeutic drugs is to create effective molecular platforms that could target cancer cells but not normal cells. Recently, we have developed a strategy via cell-SELEX (Systematic Evolution of Ligands by Exponential Enrichment) to obtain cell specific aptamers using intact viable cells as targets to select aptamers that can recognize cell membrane proteins with high selectivity and excellent affinity. We have identified an aptamer TD05 that only recognizes Ramos cells, a Burkitt’s lymphoma cell line. Here, the high specificity of aptamers in target cell binding and an efficient phototherapy reagent, Ce6, are molecularly engineered to construct a highly selective Aptamer-photosensitizer conjugates (APS) to effectively destroy target cancer cells. Introduction of the APS conjugates followed by irradiation of light selectively destroyed target Ramos cells but not acute lymphoblastic leukemia and myeloid leukemia cell lines. This study demonstrates that the use of cancer specific aptamers conjugated to a photosensitizer will enhance the selectivity of photodynamic therapy. Coupled with the advantages of the cell-SELEX in generating multiple effective aptamers for diseased cell recognition, we will be able to develop highly efficient photosensitizer based therapeutical reagents for clinical applications. PMID:18058891

Advancements of molecularly imprinted polymers in the food safety field.

PubMed

Wang, Peilong; Sun, Xiaohua; Su, Xiaoou; Wang, Tie

2016-06-07

Molecularly imprinted technology (MIT) has been widely employed to produce stable, robust and cheap molecularly imprinted polymer (MIP) materials that possess selective binding sites for recognition of target analytes in food, such as pesticides, veterinary drugs, mycotoxins, illegal drugs and so on. Because of high selectivity and specificity, MIPs have drawn great attention in the food safety field. In this review, the recent developments of MIPs in various applications for food safety, including sample preparation, chromatographic separation, sensing, immunoassay etc., have been summarized. We particularly discuss the advancements and limitations in these applications, as well as attempts carried out for their improvement.

Understanding selective molecular recognition in integrated carbon nanotube-polymer sensors by simulating physical analyte binding on carbon nanotube-polymer scaffolds.

PubMed

Lin, Shangchao; Zhang, Jingqing; Strano, Michael S; Blankschtein, Daniel

2014-08-28

Macromolecular scaffolds made of polymer-wrapped single-walled carbon nanotubes (SWCNTs) have been explored recently (Zhang et al., Nature Nanotechnology, 2013) as a new class of molecular-recognition motifs. However, selective analyte recognition is still challenging and lacks the underlying fundamental understanding needed for its practical implementation in biological sensors. In this report, we combine coarse-grained molecular dynamics (CGMD) simulations, physical adsorption/binding theories, and photoluminescence (PL) experiments to provide molecular insight into the selectivity of such sensors towards a large set of biologically important analytes. We find that the physical binding affinities of the analytes on a bare SWCNT partially correlate with their distribution coefficients in a bulk water/octanol system, suggesting that the analyte hydrophobicity plays a key role in determining the binding affinities of the analytes considered, along with the various specific interactions between the analytes and the polymer anchor groups. Two distinct categories of analytes are identified to demonstrate a complex picture for the correlation between optical sensor signals and the simulated binding affinities. Specifically, a good correlation was found between the sensor signals and the physical binding affinities of the three hormones (estradiol, melatonin, and thyroxine), the neurotransmitter (dopamine), and the vitamin (riboflavin) to the SWCNT-polymer scaffold. The four amino acids (aspartate, glycine, histidine, and tryptophan) and the two monosaccharides (fructose and glucose) considered were identified as blank analytes which are unable to induce sensor signals. The results indicate great success of our physical adsorption-based model in explaining the ranking in sensor selectivities. The combined framework presented here can be used to screen and select polymers that can potentially be used for creating synthetic molecular recognition motifs.

Portfolio as a Teaching Method: A Capstone Project to Promote Recognition of Professional Growth

ERIC Educational Resources Information Center

Wolffe, Robert; Crowe, Helja Antola; Evens, Wayne; McConnaughay, Kelly

2013-01-01

A reflective portfolio as a capstone assignment was selected to accomplish recognition by teachers completing a science, technology, mathematics, engineering master's program for elementary teachers about their professional and personal changes and to provide program evaluators additional qualitative data regarding attainment of program goals. As…

Context and Spoken Word Recognition in a Novel Lexicon

ERIC Educational Resources Information Center

Revill, Kathleen Pirog; Tanenhaus, Michael K.; Aslin, Richard N.

2008-01-01

Three eye movement studies with novel lexicons investigated the role of semantic context in spoken word recognition, contrasting 3 models: restrictive access, access-selection, and continuous integration. Actions directed at novel shapes caused changes in motion (e.g., looming, spinning) or state (e.g., color, texture). Across the experiments,…

Wide screening of phage-displayed libraries identifies immune targets in planta.

PubMed

Rioja, Cristina; Van Wees, Saskia C; Charlton, Keith A; Pieterse, Corné M J; Lorenzo, Oscar; García-Sánchez, Susana

2013-01-01

Microbe-Associated Molecular Patterns and virulence effectors are recognized by plants as a first step to mount a defence response against potential pathogens. This recognition involves a large family of extracellular membrane receptors and other immune proteins located in different sub-cellular compartments. We have used phage-display technology to express and select for Arabidopsis proteins able to bind bacterial pathogens. To rapidly identify microbe-bound phage, we developed a monitoring method based on microarrays. This combined strategy allowed for a genome-wide screening of plant proteins involved in pathogen perception. Two phage libraries for high-throughput selection were constructed from cDNA of plants infected with Pseudomonas aeruginosa PA14, or from combined samples of the virulent isolate DC3000 of Pseudomonas syringae pv. tomato and its avirulent variant avrRpt2. These three pathosystems represent different degrees in the specificity of plant-microbe interactions. Libraries cover up to 2 × 10(7) different plant transcripts that can be displayed as functional proteins on the surface of T7 bacteriophage. A number of these were selected in a bio-panning assay for binding to Pseudomonas cells. Among the selected clones we isolated the ethylene response factor ATERF-1, which was able to bind the three bacterial strains in competition assays. ATERF-1 was rapidly exported from the nucleus upon infiltration of either alive or heat-killed Pseudomonas. Moreover, aterf-1 mutants exhibited enhanced susceptibility to infection. These findings suggest that ATERF-1 contains a microbe-recognition domain with a role in plant defence. To identify other putative pathogen-binding proteins on a genome-wide scale, the copy number of selected-vs.-total clones was compared by hybridizing phage cDNAs with Arabidopsis microarrays. Microarray analysis revealed a set of 472 candidates with significant fold change. Within this set defence-related genes, including well-known targets of bacterial effectors, are over-represented. Other genes non-previously related to defence can be associated through this study with general or strain-specific recognition of Pseudomonas.

Imprint-coating synthesis of selective functionalized ordered mesoporous sorbents for separation and sensors

DOEpatents

Dai, Sheng; Burleigh, Mark C.; Shin, Yongsoon

2001-01-01

The present invention relates generally to mesoporous sorbent materials having high capacity, high selectivity, fast kinetics, and molecular recognition capability. The invention also relates to a process for preparing these mesoporous substrates through molecular imprinting techniques which differ from convention techniques in that a template molecule is bound to one end of bifunctional ligands to form a complex prior to binding of the bifunctional ligands to the substrate. The present invention also relates to methods of using the mesoporous sorbent materials, for example, in the separation of toxic metals from process effluents, paints, and other samples; detection of target molecules, such as amino acids, drugs, herbicides, fertilizers, and TNT, in samples; separation and/or detection of substances using chromatography; imaging agents; sensors; coatings; and composites.

The Magnet Nursing Services Recognition Program

PubMed Central

Aiken, Linda H.; Havens, Donna S.; Sloane, Douglas M.

2015-01-01

OVERVIEW In an environment rife with controversy about patient safety in hospitals, medical error rates, and nursing shortages, consumers need to know how good the care is at their local hospitals. Nursing’s best kept secret is the single most effective mechanism for providing that type of comparative information to consumers, a seal of approval for quality nursing care: designation of magnet hospital status by the American Nurses Credentialing Center (ANCC). Magnet designation, or recognition of the “best” hospitals, was conceived in the early 1980s when the American Academy of Nursing (AAN) conducted a study to identify which hospitals attracted and retained nurses and which organizational features were shared by these successful hospitals, referred to as magnet hospitals. In the 1990s, the American Nurses Association (ANA), through the ANCC, established a formal program to acknowledge excellence in nursing services: the Magnet Nursing Services Recognition Program. The purpose of the current study is to examine whether hospitals selected for recognition by the ANCC application process—ANCC-accredited hospitals—are as successful in creating environments in which excellent nursing care is provided as the original AAN magnet hospitals were. We found that at ANCC-recognized magnet hospitals nurses had lower burnout rates and higher levels of job satisfaction and gave the quality of care provided at their hospitals higher ratings than did nurses at the AAN magnet hospitals. Our findings validate the ability of the Magnet Nursing Services Recognition Program to successfully identify hospitals that provide high-quality nursing care. PMID:19641439

On the road to invariant recognition: explaining tradeoff and morph properties of cells in inferotemporal cortex using multiple-scale task-sensitive attentive learning.

PubMed

Grossberg, Stephen; Markowitz, Jeffrey; Cao, Yongqiang

2011-12-01

Visual object recognition is an essential accomplishment of advanced brains. Object recognition needs to be tolerant, or invariant, with respect to changes in object position, size, and view. In monkeys and humans, a key area for recognition is the anterior inferotemporal cortex (ITa). Recent neurophysiological data show that ITa cells with high object selectivity often have low position tolerance. We propose a neural model whose cells learn to simulate this tradeoff, as well as ITa responses to image morphs, while explaining how invariant recognition properties may arise in stages due to processes across multiple cortical areas. These processes include the cortical magnification factor, multiple receptive field sizes, and top-down attentive matching and learning properties that may be tuned by task requirements to attend to either concrete or abstract visual features with different levels of vigilance. The model predicts that data from the tradeoff and image morph tasks emerge from different levels of vigilance in the animals performing them. This result illustrates how different vigilance requirements of a task may change the course of category learning, notably the critical features that are attended and incorporated into learned category prototypes. The model outlines a path for developing an animal model of how defective vigilance control can lead to symptoms of various mental disorders, such as autism and amnesia. Copyright © 2011 Elsevier Ltd. All rights reserved.

Discriminant WSRC for Large-Scale Plant Species Recognition.

PubMed

Zhang, Shanwen; Zhang, Chuanlei; Zhu, Yihai; You, Zhuhong

2017-01-01

In sparse representation based classification (SRC) and weighted SRC (WSRC), it is time-consuming to solve the global sparse representation problem. A discriminant WSRC (DWSRC) is proposed for large-scale plant species recognition, including two stages. Firstly, several subdictionaries are constructed by dividing the dataset into several similar classes, and a subdictionary is chosen by the maximum similarity between the test sample and the typical sample of each similar class. Secondly, the weighted sparse representation of the test image is calculated with respect to the chosen subdictionary, and then the leaf category is assigned through the minimum reconstruction error. Different from the traditional SRC and its improved approaches, we sparsely represent the test sample on a subdictionary whose base elements are the training samples of the selected similar class, instead of using the generic overcomplete dictionary on the entire training samples. Thus, the complexity to solving the sparse representation problem is reduced. Moreover, DWSRC is adapted to newly added leaf species without rebuilding the dictionary. Experimental results on the ICL plant leaf database show that the method has low computational complexity and high recognition rate and can be clearly interpreted.

Deep learning based hand gesture recognition in complex scenes

NASA Astrophysics Data System (ADS)

Ni, Zihan; Sang, Nong; Tan, Cheng

2018-03-01

Recently, region-based convolutional neural networks(R-CNNs) have achieved significant success in the field of object detection, but their accuracy is not too high for small objects and similar objects, such as the gestures. To solve this problem, we present an online hard example testing(OHET) technology to evaluate the confidence of the R-CNNs' outputs, and regard those outputs with low confidence as hard examples. In this paper, we proposed a cascaded networks to recognize the gestures. Firstly, we use the region-based fully convolutional neural network(R-FCN), which is capable of the detection for small object, to detect the gestures, and then use the OHET to select the hard examples. To enhance the accuracy of the gesture recognition, we re-classify the hard examples through VGG-19 classification network to obtain the final output of the gesture recognition system. Through the contrast experiments with other methods, we can see that the cascaded networks combined with the OHET reached to the state-of-the-art results of 99.3% mAP on small and similar gestures in complex scenes.

Action Recognition Using Nonnegative Action Component Representation and Sparse Basis Selection.

PubMed

Wang, Haoran; Yuan, Chunfeng; Hu, Weiming; Ling, Haibin; Yang, Wankou; Sun, Changyin

2014-02-01

In this paper, we propose using high-level action units to represent human actions in videos and, based on such units, a novel sparse model is developed for human action recognition. There are three interconnected components in our approach. First, we propose a new context-aware spatial-temporal descriptor, named locally weighted word context, to improve the discriminability of the traditionally used local spatial-temporal descriptors. Second, from the statistics of the context-aware descriptors, we learn action units using the graph regularized nonnegative matrix factorization, which leads to a part-based representation and encodes the geometrical information. These units effectively bridge the semantic gap in action recognition. Third, we propose a sparse model based on a joint l2,1-norm to preserve the representative items and suppress noise in the action units. Intuitively, when learning the dictionary for action representation, the sparse model captures the fact that actions from the same class share similar units. The proposed approach is evaluated on several publicly available data sets. The experimental results and analysis clearly demonstrate the effectiveness of the proposed approach.

Memory bias for threatening information in anxiety and anxiety disorders: a meta-analytic review.

PubMed

Mitte, Kristin

2008-11-01

Although some theories suggest that anxious individuals selectively remember threatening stimuli, findings remain contradictory despite a considerable amount of research. A quantitative integration of 165 studies with 9,046 participants (clinical and nonclinical samples) examined whether a memory bias exists and which moderator variables influence its magnitude. Implicit memory bias was investigated in lexical decision/stimulus identification and word-stem completion paradigms; explicit memory bias was investigated in recognition and recall paradigms. Overall, effect sizes showed no significant impact of anxiety on implicit memory and recognition. Analyses indicated a memory bias for recall, whose magnitude depended on experimental study procedures like the encoding procedure or retention interval. Anxiety influenced recollection of previous experiences; anxious individuals favored threat-related information. Across all paradigms, clinical status was not significantly linked to effect sizes, indicating no qualitative difference in information processing between anxiety patients and high-anxious persons. The large discrepancy between study effects in recall and recognition indicates that future research is needed to identify moderator variables for avoidant and preferred remembering.

40 CFR 105.11 - Who selects the award winners?

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 22 2014-07-01 2013-07-01 true Who selects the award winners? 105.11 Section 105.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS RECOGNITION AWARDS UNDER THE CLEAN WATER ACT Selection Criteria § 105.11 Who selects the award winners? After...

40 CFR 105.11 - Who selects the award winners?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 21 2010-07-01 2010-07-01 false Who selects the award winners? 105.11 Section 105.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS RECOGNITION AWARDS UNDER THE CLEAN WATER ACT Selection Criteria § 105.11 Who selects the award winners? After...

40 CFR 105.11 - Who selects the award winners?

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 23 2012-07-01 2012-07-01 false Who selects the award winners? 105.11 Section 105.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS RECOGNITION AWARDS UNDER THE CLEAN WATER ACT Selection Criteria § 105.11 Who selects the award winners? After...

40 CFR 105.11 - Who selects the award winners?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 22 2011-07-01 2011-07-01 false Who selects the award winners? 105.11 Section 105.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS RECOGNITION AWARDS UNDER THE CLEAN WATER ACT Selection Criteria § 105.11 Who selects the award winners? After...

A Small Aptamer with Strong and Specific Recognition of the Triphosphate of ATP

PubMed Central

Sazani, Peter L.; Larralde, Rosa

2004-01-01

We report the in vitro selection of an RNA-based ATP aptamer with the ability to discriminate between adenosine ligands based on their 5‘ phosphorylation state. Previous selection of ATP aptamers yielded molecules that do not significantly discriminate between ligands at the 5‘ position. By applying a selective pressure that demands recognition of the 5‘ triphosphate, we obtained an aptamer that binds to ATP with a Kd of approximately 5 μM, and to AMP with a Kd of approximately 5.5 mM, a difference of 1100-fold. This aptamer demonstrates the ability of small RNAs to interact with negatively charged moieties. PMID:15237981

Chemical Posttranslational Modification with Designed Rhodium(II) Catalysts.

PubMed

Martin, S C; Minus, M B; Ball, Z T

2016-01-01

Natural enzymes use molecular recognition to perform exquisitely selective transformations on nucleic acids, proteins, and natural products. Rhodium(II) catalysts mimic this selectivity, using molecular recognition to allow selective modification of proteins with a variety of functionalized diazo reagents. The rhodium catalysts and the diazo reactivity have been successfully applied to a variety of protein folds, the chemistry succeeds in complex environments such as cell lysate, and a simple protein blot method accurately assesses modification efficiency. The studies with rhodium catalysts provide a new tool to study and probe protein-binding events, as well as a new synthetic approach to protein conjugates for medical, biochemical, or materials applications. © 2016 Elsevier Inc. All rights reserved.

Looking inside the Ocean: Toward an Autonomous Imaging System for Monitoring Gelatinous Zooplankton

PubMed Central

Corgnati, Lorenzo; Marini, Simone; Mazzei, Luca; Ottaviani, Ennio; Aliani, Stefano; Conversi, Alessandra; Griffa, Annalisa

2016-01-01

Marine plankton abundance and dynamics in the open and interior ocean is still an unknown field. The knowledge of gelatinous zooplankton distribution is especially challenging, because this type of plankton has a very fragile structure and cannot be directly sampled using traditional net based techniques. To overcome this shortcoming, Computer Vision techniques can be successfully used for the automatic monitoring of this group.This paper presents the GUARD1 imaging system, a low-cost stand-alone instrument for underwater image acquisition and recognition of gelatinous zooplankton, and discusses the performance of three different methodologies, Tikhonov Regularization, Support Vector Machines and Genetic Programming, that have been compared in order to select the one to be run onboard the system for the automatic recognition of gelatinous zooplankton. The performance comparison results highlight the high accuracy of the three methods in gelatinous zooplankton identification, showing their good capability in robustly selecting relevant features. In particular, Genetic Programming technique achieves the same performances of the other two methods by using a smaller set of features, thus being the most efficient in avoiding computationally consuming preprocessing stages, that is a crucial requirement for running on an autonomous imaging system designed for long lasting deployments, like the GUARD1. The Genetic Programming algorithm has been installed onboard the system, that has been operationally tested in a two-months survey in the Ligurian Sea, providing satisfactory results in terms of monitoring and recognition performances. PMID:27983638

Optimization of spectral bands for hyperspectral remote sensing of forest vegetation

NASA Astrophysics Data System (ADS)

Dmitriev, Egor V.; Kozoderov, Vladimir V.

2013-10-01

Optimization principles of accounting for the most informative spectral channels in hyperspectral remote sensing data processing serve to enhance the efficiency of the employed high-productive computers. The problem of pattern recognition of the remotely sensed land surface objects with the accent on the forests is outlined from the point of view of the spectral channels optimization on the processed hyperspectral images. The relevant computational procedures are tested using the images obtained by the produced in Russia hyperspectral camera that was installed on a gyro-stabilized platform to conduct the airborne flight campaigns. The Bayesian classifier is used for the pattern recognition of the forests with different tree species and age. The probabilistically optimal algorithm constructed on the basis of the maximum likelihood principle is described to minimize the probability of misclassification given by this classifier. The classification error is the major category to estimate the accuracy of the applied algorithm by the known holdout cross-validation method. Details of the related techniques are presented. Results are shown of selecting the spectral channels of the camera while processing the images having in mind radiometric distortions that diminish the classification accuracy. The spectral channels are selected of the obtained subclasses extracted from the proposed validation techniques and the confusion matrices are constructed that characterize the age composition of the classified pine species as well as the broad age-class recognition for the pine and birch species with the fully illuminated parts of their crowns.

A system for diagnosis of wheat leaf diseases based on Android smartphone

NASA Astrophysics Data System (ADS)

Xie, Xinhua; Zhang, Xiangqian; He, Bing; Liang, Dong; Zhang, Dongyang; Huang, Linsheng

2016-10-01

Owing to the shortages of inconvenience, expensive and high professional requirements etc. for conventional recognition devices of wheat leaf diseases, it does not satisfy the requirements of uploading and releasing timely investigation data in the large-scale field, which may influence the effectiveness of prevention and control for wheat diseases. In this study, a fast, accurate, and robust diagnose system of wheat leaf diseases based on android smartphone was developed, which comprises of two parts—the client and the server. The functions of the client include image acquisition, GPS positioning, corresponding, and knowledge base of disease prevention and control. The server includes image processing, feature extraction, and selection, and classifier establishing. The recognition process of the system goes as follow: when disease images were collected in fields and sent to the server by android smartphone, and then image processing of disease spots was carried out by the server. Eighteen larger weight features were selected by algorithm relief-F and as the input of Relevance Vector Machine (RVM), and the automatic identification of wheat stripe rust and powdery mildew was realized. The experimental results showed that the average recognition rate and predicted speed of RVM model were 5.56% and 7.41 times higher than that of Support Vector Machine (SVM). And application discovered that it needs about 1 minute to get the identification result. Therefore, it can be concluded that the system could be used to recognize wheat diseases and real-time investigate in fields.

Effective Connectivity from Early Visual Cortex to Posterior Occipitotemporal Face Areas Supports Face Selectivity and Predicts Developmental Prosopagnosia

PubMed Central

Garrido, Lucia; Driver, Jon; Dolan, Raymond J.; Duchaine, Bradley C.; Furl, Nicholas

2016-01-01

Face processing is mediated by interactions between functional areas in the occipital and temporal lobe, and the fusiform face area (FFA) and anterior temporal lobe play key roles in the recognition of facial identity. Individuals with developmental prosopagnosia (DP), a lifelong face recognition impairment, have been shown to have structural and functional neuronal alterations in these areas. The present study investigated how face selectivity is generated in participants with normal face processing, and how functional abnormalities associated with DP, arise as a function of network connectivity. Using functional magnetic resonance imaging and dynamic causal modeling, we examined effective connectivity in normal participants by assessing network models that include early visual cortex (EVC) and face-selective areas and then investigated the integrity of this connectivity in participants with DP. Results showed that a feedforward architecture from EVC to the occipital face area, EVC to FFA, and EVC to posterior superior temporal sulcus (pSTS) best explained how face selectivity arises in both controls and participants with DP. In this architecture, the DP group showed reduced connection strengths on feedforward connections carrying face information from EVC to FFA and EVC to pSTS. These altered network dynamics in DP contribute to the diminished face selectivity in the posterior occipitotemporal areas affected in DP. These findings suggest a novel view on the relevance of feedforward projection from EVC to posterior occipitotemporal face areas in generating cortical face selectivity and differences in face recognition ability. SIGNIFICANCE STATEMENT Areas of the human brain showing enhanced activation to faces compared to other objects or places have been extensively studied. However, the factors leading to this face selectively have remained mostly unknown. We show that effective connectivity from early visual cortex to posterior occipitotemporal face areas gives rise to face selectivity. Furthermore, people with developmental prosopagnosia, a lifelong face recognition impairment, have reduced face selectivity in the posterior occipitotemporal face areas and left anterior temporal lobe. We show that this reduced face selectivity can be predicted by effective connectivity from early visual cortex to posterior occipitotemporal face areas. This study presents the first network-based account of how face selectivity arises in the human brain. PMID:27030766

PCANet: A Simple Deep Learning Baseline for Image Classification?

PubMed

Chan, Tsung-Han; Jia, Kui; Gao, Shenghua; Lu, Jiwen; Zeng, Zinan; Ma, Yi

2015-12-01

In this paper, we propose a very simple deep learning network for image classification that is based on very basic data processing components: 1) cascaded principal component analysis (PCA); 2) binary hashing; and 3) blockwise histograms. In the proposed architecture, the PCA is employed to learn multistage filter banks. This is followed by simple binary hashing and block histograms for indexing and pooling. This architecture is thus called the PCA network (PCANet) and can be extremely easily and efficiently designed and learned. For comparison and to provide a better understanding, we also introduce and study two simple variations of PCANet: 1) RandNet and 2) LDANet. They share the same topology as PCANet, but their cascaded filters are either randomly selected or learned from linear discriminant analysis. We have extensively tested these basic networks on many benchmark visual data sets for different tasks, including Labeled Faces in the Wild (LFW) for face verification; the MultiPIE, Extended Yale B, AR, Facial Recognition Technology (FERET) data sets for face recognition; and MNIST for hand-written digit recognition. Surprisingly, for all tasks, such a seemingly naive PCANet model is on par with the state-of-the-art features either prefixed, highly hand-crafted, or carefully learned [by deep neural networks (DNNs)]. Even more surprisingly, the model sets new records for many classification tasks on the Extended Yale B, AR, and FERET data sets and on MNIST variations. Additional experiments on other public data sets also demonstrate the potential of PCANet to serve as a simple but highly competitive baseline for texture classification and object recognition.

PACS administrators' and radiologists' perspective on the importance of features for PACS selection.

PubMed

Joshi, Vivek; Narra, Vamsi R; Joshi, Kailash; Lee, Kyootai; Melson, David

2014-08-01

Picture archiving and communication systems (PACS) play a critical role in radiology. This paper presents the criteria important to PACS administrators for selecting a PACS. A set of criteria are identified and organized into an integrative hierarchical framework. Survey responses from 48 administrators are used to identify the relative weights of these criteria through an analytical hierarchy process. The five main dimensions for PACS selection in order of importance are system continuity and functionality, system performance and architecture, user interface for workflow management, user interface for image manipulation, and display quality. Among the subdimensions, the highest weights were assessed for security, backup, and continuity; tools for continuous performance monitoring; support for multispecialty images; and voice recognition/transcription. PACS administrators' preferences were generally in line with that of previously reported results for radiologists. Both groups assigned the highest priority to ensuring business continuity and preventing loss of data through features such as security, backup, downtime prevention, and tools for continuous PACS performance monitoring. PACS administrators' next high priorities were support for multispecialty images, image retrieval speeds from short-term and long-term storage, real-time monitoring, and architectural issues of compatibility and integration with other products. Thus, next to ensuring business continuity, administrators' focus was on issues that impact their ability to deliver services and support. On the other hand, radiologists gave high priorities to voice recognition, transcription, and reporting; structured reporting; and convenience and responsiveness in manipulation of images. Thus, radiologists' focus appears to be on issues that may impact their productivity, effort, and accuracy.

Microwave-assisted RAFT polymerization of well-constructed magnetic surface molecularly imprinted polymers for specific recognition of benzimidazole residues

NASA Astrophysics Data System (ADS)

Chen, Fangfang; Wang, Jiayu; Chen, Huiru; Lu, Ruicong; Xie, Xiaoyu

2018-03-01

Magnetic nanoparticles have been widely used as support core for fast separation, which could be directly separated from complicated matrices using an external magnet in few minutes. Surface imprinting based on magnetic core has shown favorable adsorption and separation performance, including good adsorption capacity, fast adsorption kinetics and special selectivity adsorption. Reversible addition-fragmentation chain transfer (RAFT) is an ideal choice for producing well-defined complex architecture with mild reaction conditions. We herein describe the preparation of well-constructed magnetic molecularly imprinted polymers (MMIPs) for the recognition of benzimidazole (BMZ) residues via the microwave-assisted RAFT polymerization. The merits of RAFT polymerization assisting with microwave heating allowed successful and more efficient preparation of well-constructed imprinted coats. Moreover, the polymerization time dramatically shortened and was just 1/24th of the time taken by conventional heating. The results indicated that a uniform nanoscale imprinted layer was formed on the Fe3O4 core successfully, and enough saturation magnetization of MMIPs (16.53 emu g-1) was got for magnetic separation. The desirable adsorption capacity (30.18 μmol g-1) and high selectivity toward template molecule with a selectivity coefficient (k) of 13.85 of MMIPs were exhibited by the adsorption isothermal assay and competitive binding assay, respectively. A solid phase extraction enrichment approach was successfully established for the determination of four BMZ residues from apple samples using MMIPs coupled to HPLC. Overall, this study provides a versatile approach for highly efficient fabrication of well-constructed MMIPs for enrichment and determination of target molecules from complicated samples.

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

PubMed

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

2014-01-01

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

Feature Extraction and Selection Strategies for Automated Target Recognition

NASA Technical Reports Server (NTRS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Feature extraction and selection strategies for automated target recognition

NASA Astrophysics Data System (ADS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-04-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory regionof- interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Molecular recognition in protein modification with rhodium metallopeptides

PubMed Central

Ball, Zachary T.

2015-01-01

Chemical manipulation of natural, unengineered proteins is a daunting challenge which tests the limits of reaction design. By combining transition-metal or other catalysts with molecular recognition ideas, it is possible to achieve site-selective protein reactivity without the need for engineered recognition sequences or reactive sites. Some recent examples in this area have used ruthenium photocatalysis, pyridine organocatalysis, and rhodium(II) metallocarbene catalysis, indicating that the fundamental ideas provide opportunities for using diverse reactivity on complex protein substrates and in complex cell-like environments. PMID:25588960

Profiling Charge Complementarity and Selectivity for Binding at the Protein Surface

PubMed Central

Sulea, Traian; Purisima, Enrico O.

2003-01-01

A novel analysis and representation of the protein surface in terms of electrostatic binding complementarity and selectivity is presented. The charge optimization methodology is applied in a probe-based approach that simulates the binding process to the target protein. The molecular surface is color coded according to calculated optimal charge or according to charge selectivity, i.e., the binding cost of deviating from the optimal charge. The optimal charge profile depends on both the protein shape and charge distribution whereas the charge selectivity profile depends only on protein shape. High selectivity is concentrated in well-shaped concave pockets, whereas solvent-exposed convex regions are not charge selective. This suggests the synergy of charge and shape selectivity hot spots toward molecular selection and recognition, as well as the asymmetry of charge selectivity at the binding interface of biomolecular systems. The charge complementarity and selectivity profiles map relevant electrostatic properties in a readily interpretable way and encode information that is quite different from that visualized in the standard electrostatic potential map of unbound proteins. PMID:12719221

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

PubMed

Berg, E M; Lippman, L G

2001-04-01

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

Mexican sign language recognition using normalized moments and artificial neural networks

NASA Astrophysics Data System (ADS)

Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita

2014-09-01

This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

The effects of list-method directed forgetting on recognition memory.

PubMed

Benjamin, Aaron S

2006-10-01

It is an almost universally accepted claim that the list-method procedure of inducing directed forgetting does not affect recognition. However, previous studies have omitted a critical comparison in reaching this conclusion. This article reports evidence that recognition of material learned after cue presentation is superior for conditions in which the material that preceded cue presentation was designated as to-be-forgotten. Because the absence of an effect of directed-forgetting instructions on recognition is the linchpin of the theoretical claim that retrieval inhibition and not selective rehearsal underlies that effect, the present results call into question the need to postulate a role for inhibition in directed forgetting.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Sexually antagonistic selection on genetic variation underlying both male and female same-sex sexual behavior.

PubMed

Berger, David; You, Tao; Minano, Maravillas R; Grieshop, Karl; Lind, Martin I; Arnqvist, Göran; Maklakov, Alexei A

2016-05-13

Intralocus sexual conflict, arising from selection for different alleles at the same locus in males and females, imposes a constraint on sex-specific adaptation. Intralocus sexual conflict can be alleviated by the evolution of sex-limited genetic architectures and phenotypic expression, but pleiotropic constraints may hinder this process. Here, we explored putative intralocus sexual conflict and genetic (co)variance in a poorly understood behavior with near male-limited expression. Same-sex sexual behaviors (SSBs) generally do not conform to classic evolutionary models of adaptation but are common in male animals and have been hypothesized to result from perception errors and selection for high male mating rates. However, perspectives incorporating sex-specific selection on genes shared by males and females to explain the expression and evolution of SSBs have largely been neglected. We performed two parallel sex-limited artificial selection experiments on SSB in male and female seed beetles, followed by sex-specific assays of locomotor activity and male sex recognition (two traits hypothesized to be functionally related to SSB) and adult reproductive success (allowing us to assess fitness consequences of genetic variance in SSB and its correlated components). Our experiments reveal both shared and sex-limited genetic variance for SSB. Strikingly, genetically correlated responses in locomotor activity and male sex-recognition were associated with sexually antagonistic fitness effects, but these effects differed qualitatively between male and female selection lines, implicating intralocus sexual conflict at both male- and female-specific genetic components underlying SSB. Our study provides experimental support for the hypothesis that widespread pleiotropy generates pervasive intralocus sexual conflict governing the expression of SSBs, suggesting that SSB in one sex can occur due to the expression of genes that carry benefits in the other sex.

Recognizable-image selection for fingerprint recognition with a mobile-device camera.

PubMed

Lee, Dongjae; Choi, Kyoungtaek; Choi, Heeseung; Kim, Jaihie

2008-02-01

This paper proposes a recognizable-image selection algorithm for fingerprint-verification systems that use a camera embedded in a mobile device. A recognizable image is defined as the fingerprint image which includes the characteristics that are sufficiently discriminating an individual from other people. While general camera systems obtain focused images by using various gradient measures to estimate high-frequency components, mobile cameras cannot acquire recognizable images in the same way because the obtained images may not be adequate for fingerprint recognition, even if they are properly focused. A recognizable image has to meet the following two conditions: First, valid region in the recognizable image should be large enough compared with other nonrecognizable images. Here, a valid region is a well-focused part, and ridges in the region are clearly distinguishable from valleys. In order to select valid regions, this paper proposes a new focus-measurement algorithm using the secondary partial derivatives and a quality estimation utilizing the coherence and symmetry of gradient distribution. Second, rolling and pitching degrees of a finger measured from the camera plane should be within some limit for a recognizable image. The position of a core point and the contour of a finger are used to estimate the degrees of rolling and pitching. Experimental results show that our proposed method selects valid regions and estimates the degrees of rolling and pitching properly. In addition, fingerprint-verification performance is improved by detecting the recognizable images.

Reading Ability and Print Exposure: Item Response Theory Analysis of the Author Recognition Test

PubMed Central

Moore, Mariah; Gordon, Peter C.

2015-01-01

In the Author Recognition Test (ART) participants are presented with a series of names and foils and are asked to indicate which ones they recognize as authors. The test is a strong predictor of reading skill, with this predictive ability generally explained as occurring because author knowledge is likely acquired through reading or other forms of print exposure. This large-scale study (1012 college student participants) used Item Response Theory (IRT) to analyze item (author) characteristics to facilitate identification of the determinants of item difficulty, provide a basis for further test development, and to optimize scoring of the ART. Factor analysis suggests a potential two factor structure of the ART differentiating between literary vs. popular authors. Effective and ineffective author names were identified so as to facilitate future revisions of the ART. Analyses showed that the ART is a highly significant predictor of time spent encoding words as measured using eye-tracking during reading. The relationship between the ART and time spent reading provided a basis for implementing a higher penalty for selecting foils, rather than the standard method of ART scoring (names selected minus foils selected). The findings provide novel support for the view that the ART is a valid indicator of reading volume. Further, they show that frequency data can be used to select items of appropriate difficulty and that frequency data from corpora based on particular time periods and types of text may allow test adaptation for different populations. PMID:25410405

Reading ability and print exposure: item response theory analysis of the author recognition test.

PubMed

Moore, Mariah; Gordon, Peter C

2015-12-01

In the author recognition test (ART), participants are presented with a series of names and foils and are asked to indicate which ones they recognize as authors. The test is a strong predictor of reading skill, and this predictive ability is generally explained as occurring because author knowledge is likely acquired through reading or other forms of print exposure. In this large-scale study (1,012 college student participants), we used item response theory (IRT) to analyze item (author) characteristics in order to facilitate identification of the determinants of item difficulty, provide a basis for further test development, and optimize scoring of the ART. Factor analysis suggested a potential two-factor structure of the ART, differentiating between literary and popular authors. Effective and ineffective author names were identified so as to facilitate future revisions of the ART. Analyses showed that the ART is a highly significant predictor of the time spent encoding words, as measured using eyetracking during reading. The relationship between the ART and time spent reading provided a basis for implementing a higher penalty for selecting foils, rather than the standard method of ART scoring (names selected minus foils selected). The findings provide novel support for the view that the ART is a valid indicator of reading volume. Furthermore, they show that frequency data can be used to select items of appropriate difficulty, and that frequency data from corpora based on particular time periods and types of texts may allow adaptations of the test for different populations.

Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

PubMed

Syed Abdul Mutalib, Sharifah Norsukhairin; Juahir, Hafizan; Azid, Azman; Mohd Sharif, Sharifah; Latif, Mohd Talib; Aris, Ahmad Zaharin; Zain, Sharifuddin M; Dominick, Doreena

2013-09-01

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

Single-Stranded DNA Aptamers against Pathogens and Toxins: Identification and Biosensing Applications

PubMed Central

Hong, Ka Lok

2015-01-01

Molecular recognition elements (MREs) can be short sequences of single-stranded DNA, RNA, small peptides, or antibody fragments. They can bind to user-defined targets with high affinity and specificity. There has been an increasing interest in the identification and application of nucleic acid molecular recognition elements, commonly known as aptamers, since they were first described in 1990 by the Gold and Szostak laboratories. A large number of target specific nucleic acids MREs and their applications are currently in the literature. This review first describes the general methodologies used in identifying single-stranded DNA (ssDNA) aptamers. It then summarizes advancements in the identification and biosensing application of ssDNA aptamers specific for bacteria, viruses, their associated molecules, and selected chemical toxins. Lastly, an overview of the basic principles of ssDNA aptamer-based biosensors is discussed. PMID:26199940

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

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

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

1994-01-01

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

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

PubMed

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.

Computational Design of Metal Ion Sequestering Agents

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

Hay, Benjamin P.; Rapko, Brian M.

Organic ligands that exhibit a high degree of metal ion recognition are essential precursors for developing separation processes and sensors for metal ions. Since the beginning of the nuclear era, much research has focused on discovering ligands that target specific radionuclides. Members of the Group 1A and 2A cations (e.g., Cs, Sr, Ra) and the f-block metals (actinides and lanthanides) are of primary concern to DOE. Although there has been some success in identifying ligand architectures that exhibit a degree of metal ion recognition, the ability to control binding affinity and selectivity remains a significant challenge. The traditional approach formore » discovering such ligands has involved lengthy programs of organic synthesis and testing that, in the absence of reliable methods for screening compounds before synthesis, have resulted in much wasted research effort.« less

Magnetic molecularly imprinted polymer for aspirin recognition and controlled release

NASA Astrophysics Data System (ADS)

Kan, Xianwen; Geng, Zhirong; Zhao, Yao; Wang, Zhilin; Zhu, Jun-Jie

2009-04-01

Core-shell structural magnetic molecularly imprinted polymers (magnetic MIPs) with combined properties of molecular recognition and controlled release were prepared and characterized. Magnetic MIPs were synthesized by the co-polymerization of methacrylic acid (MAA) and trimethylolpropane trimethacrylate (TRIM) around aspirin (ASP) at the surface of double-bond-functionalized Fe3O4 nanoparticles in chloroform. The obtained spherical magnetic MIPs with diameters of about 500 nm had obvious superparamagnetism and could be separated quickly by an external magnetic field. Binding experiments were carried out to evaluate the properties of magnetic MIPs and magnetic non-molecularly imprinted polymers (magnetic NIPs). The results demonstrated that the magnetic MIPs had high adsorption capacity and selectivity to ASP. Moreover, release profiles and release rate of ASP from the ASP-loaded magnetic MIPs indicated that the magnetic MIPs also had potential applications in drug controlled release.

Exposure to childhood adversity and deficits in emotion recognition: results from a large, population-based sample.

PubMed

Dunn, Erin C; Crawford, Katherine M; Soare, Thomas W; Button, Katherine S; Raffeld, Miriam R; Smith, Andrew D A C; Penton-Voak, Ian S; Munafò, Marcus R

2018-03-07

Emotion recognition skills are essential for social communication. Deficits in these skills have been implicated in mental disorders. Prior studies of clinical and high-risk samples have consistently shown that children exposed to adversity are more likely than their unexposed peers to have emotion recognition skills deficits. However, only one population-based study has examined this association. We analyzed data from children participating in the Avon Longitudinal Study of Parents and Children, a prospective birth cohort (n = 6,506). We examined the association between eight adversities, assessed repeatedly from birth to age 8 (caregiver physical or emotional abuse; sexual or physical abuse; maternal psychopathology; one adult in the household; family instability; financial stress; parent legal problems; neighborhood disadvantage) and the ability to recognize facial displays of emotion measured using the faces subtest of the Diagnostic Assessment of Non-Verbal Accuracy (DANVA) at age 8.5 years. In addition to examining the role of exposure (vs. nonexposure) to each type of adversity, we also evaluated the role of the timing, duration, and recency of each adversity using a Least Angle Regression variable selection procedure. Over three-quarters of the sample experienced at least one adversity. We found no evidence to support an association between emotion recognition deficits and previous exposure to adversity, either in terms of total lifetime exposure, timing, duration, or recency, or when stratifying by sex. Results from the largest population-based sample suggest that even extreme forms of adversity are unrelated to emotion recognition deficits as measured by the DANVA, suggesting the possible immutability of emotion recognition in the general population. These findings emphasize the importance of population-based studies to generate generalizable results. © 2018 Association for Child and Adolescent Mental Health.

Activity recognition from minimal distinguishing subsequence mining

NASA Astrophysics Data System (ADS)

Iqbal, Mohammad; Pao, Hsing-Kuo

2017-08-01

Human activity recognition is one of the most important research topics in the era of Internet of Things. To separate different activities given sensory data, we utilize a Minimal Distinguishing Subsequence (MDS) mining approach to efficiently find distinguishing patterns among different activities. We first transform the sensory data into a series of sensor triggering events and operate the MDS mining procedure afterwards. The gap constraints are also considered in the MDS mining. Given the multi-class nature of most activity recognition tasks, we modify the MDS mining approach from a binary case to a multi-class one to fit the need for multiple activity recognition. We also study how to select the best parameter set including the minimal and the maximal support thresholds in finding the MDSs for effective activity recognition. Overall, the prediction accuracy is 86.59% on the van Kasteren dataset which consists of four different activities for recognition.

Intellectual factors in false memories of patients with schizophrenia.

PubMed

Zhu, Bi; Chen, Chuansheng; Loftus, Elizabeth F; Dong, Qi; Lin, Chongde; Li, Jun

2018-07-01

The current study explored the intellectual factors in false memories of 139 patients with schizophrenia, using a recognition task and an IQ test. The full-scale IQ score of the participants ranged from 57 to 144 (M = 100, SD = 14). The full IQ score had a negative correlation with false recognition in patients with schizophrenia, and positive correlations with high-confidence true recognition and discrimination rates. Further analyses with the subtests' scores revealed that false recognition was negatively correlated with scores of performance IQ (and one of its subtests: picture arrangement), whereas true recognition was positively correlated with scores of verbal IQ (and two of its subtests: information and digit span). High-IQ patients had less false recognition (overall or high-confidence false recognition), more high-confidence true recognition, and higher discrimination abilities than those with low IQ. These findings contribute to a better understanding of the cognitive mechanism in false memory of patients with schizophrenia, and are of practical relevance to the evaluation of memory reliability in patients with different intellectual levels. Copyright © 2018 Elsevier B.V. All rights reserved.

Strategies to Improve Activity Recognition Based on Skeletal Tracking: Applying Restrictions Regarding Body Parts and Similarity Boundaries †

PubMed Central

Gutiérrez-López-Franca, Carlos; Hervás, Ramón; Johnson, Esperanza

2018-01-01

This paper aims to improve activity recognition systems based on skeletal tracking through the study of two different strategies (and its combination): (a) specialized body parts analysis and (b) stricter restrictions for the most easily detectable activities. The study was performed using the Extended Body-Angles Algorithm, which is able to analyze activities using only a single key sample. This system allows to select, for each considered activity, which are its relevant joints, which makes it possible to monitor the body of the user selecting only a subset of the same. But this feature of the system has both advantages and disadvantages. As a consequence, in the past we had some difficulties with the recognition of activities that only have a small subset of the joints of the body as relevant. The goal of this work, therefore, is to analyze the effect produced by the application of several strategies on the results of an activity recognition system based on skeletal tracking joint oriented devices. Strategies that we applied with the purpose of improve the recognition rates of the activities with a small subset of relevant joints. Through the results of this work, we aim to give the scientific community some first indications about which considered strategy is better. PMID:29789478

The Effect of Remote Masking on the Reception of Speech by Young School-Age Children.

PubMed

Youngdahl, Carla L; Healy, Eric W; Yoho, Sarah E; Apoux, Frédéric; Holt, Rachael Frush

2018-02-15

Psychoacoustic data indicate that infants and children are less likely than adults to focus on a spectral region containing an anticipated signal and are more susceptible to remote masking of a signal. These detection tasks suggest that infants and children, unlike adults, do not listen selectively. However, less is known about children's ability to listen selectively during speech recognition. Accordingly, the current study examines remote masking during speech recognition in children and adults. Adults and 7- and 5-year-old children performed sentence recognition in the presence of various spectrally remote maskers. Intelligibility was determined for each remote-masker condition, and performance was compared across age groups. It was found that speech recognition for 5-year-olds was reduced in the presence of spectrally remote noise, whereas the maskers had no effect on the 7-year-olds or adults. Maskers of different bandwidth and remoteness had similar effects. In accord with psychoacoustic data, young children do not appear to focus on a spectral region of interest and ignore other regions during speech recognition. This tendency may help account for their typically poorer speech perception in noise. This study also appears to capture an important developmental stage, during which a substantial refinement in spectral listening occurs.

Arginine Vasopressin selectively enhances recognition of sexual cues in male humans.

PubMed

Guastella, Adam J; Kenyon, Amanda R; Unkelbach, Christian; Alvares, Gail A; Hickie, Ian B

2011-02-01

Arginine Vasopressin modulates complex social and sexual behavior by enhancing social recognition, pair bonding, and aggression in non-human mammals. The influence of Arginine Vasopressin in human social and sexual behavior is, however, yet to be fully understood. We evaluated whether Arginine Vasopressin nasal spray facilitated recognition of positive and negative social and sexual stimuli over non-social stimuli. We used a recognition task that has already been shown to be sensitive to the influence of Oxytocin nasal spray (Unkelbach et al., 2008). In a double-blind, randomized, placebo-controlled, between-subjects design, 41 healthy male volunteers were administered Arginine Vasopressin (20 IU) or a placebo nasal spray after a 45 min wait period and then completed the recognition task. Results showed that the participants administered Arginine Vasopressin nasal spray were faster to detect sexual words over other types of words. This effect appeared for both positively and negatively valenced words. Results demonstrate for the first time that Arginine Vasopressin selectively enhances human cognition for sexual stimuli, regardless of valence. They further extend animal and human genetic studies linking Arginine Vasopressin to sexual behavior in males. Findings suggest an important cognitive mechanism that could enhance sexual behaviors in humans. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Influence of auditory attention on sentence recognition captured by the neural phase.

PubMed

Müller, Jana Annina; Kollmeier, Birger; Debener, Stefan; Brand, Thomas

2018-03-07

The aim of this study was to investigate whether attentional influences on speech recognition are reflected in the neural phase entrained by an external modulator. Sentences were presented in 7 Hz sinusoidally modulated noise while the neural response to that modulation frequency was monitored by electroencephalogram (EEG) recordings in 21 participants. We implemented a selective attention paradigm including three different attention conditions while keeping physical stimulus parameters constant. The participants' task was either to repeat the sentence as accurately as possible (speech recognition task), to count the number of decrements implemented in modulated noise (decrement detection task), or to do both (dual task), while the EEG was recorded. Behavioural analysis revealed reduced performance in the dual task condition for decrement detection, possibly reflecting limited cognitive resources. EEG analysis revealed no significant differences in power for the 7 Hz modulation frequency, but an attention-dependent phase difference between tasks. Further phase analysis revealed a significant difference 500 ms after sentence onset between trials with correct and incorrect responses for speech recognition, indicating that speech recognition performance and the neural phase are linked via selective attention mechanisms, at least shortly after sentence onset. However, the neural phase effects identified were small and await further investigation. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Recognition of Frequency Modulated Whistle-Like Sounds by a Bottlenose Dolphin (Tursiops truncatus) and Humans with Transformations in Amplitude, Duration and Frequency.

PubMed

Branstetter, Brian K; DeLong, Caroline M; Dziedzic, Brandon; Black, Amy; Bakhtiari, Kimberly

2016-01-01

Bottlenose dolphins (Tursiops truncatus) use the frequency contour of whistles produced by conspecifics for individual recognition. Here we tested a bottlenose dolphin's (Tursiops truncatus) ability to recognize frequency modulated whistle-like sounds using a three alternative matching-to-sample paradigm. The dolphin was first trained to select a specific object (object A) in response to a specific sound (sound A) for a total of three object-sound associations. The sounds were then transformed by amplitude, duration, or frequency transposition while still preserving the frequency contour of each sound. For comparison purposes, 30 human participants completed an identical task with the same sounds, objects, and training procedure. The dolphin's ability to correctly match objects to sounds was robust to changes in amplitude with only a minor decrement in performance for short durations. The dolphin failed to recognize sounds that were frequency transposed by plus or minus ½ octaves. Human participants demonstrated robust recognition with all acoustic transformations. The results indicate that this dolphin's acoustic recognition of whistle-like sounds was constrained by absolute pitch. Unlike human speech, which varies considerably in average frequency, signature whistles are relatively stable in frequency, which may have selected for a whistle recognition system invariant to frequency transposition.

Recognition of Frequency Modulated Whistle-Like Sounds by a Bottlenose Dolphin (Tursiops truncatus) and Humans with Transformations in Amplitude, Duration and Frequency

PubMed Central

Branstetter, Brian K.; DeLong, Caroline M.; Dziedzic, Brandon; Black, Amy; Bakhtiari, Kimberly

2016-01-01

Bottlenose dolphins (Tursiops truncatus) use the frequency contour of whistles produced by conspecifics for individual recognition. Here we tested a bottlenose dolphin’s (Tursiops truncatus) ability to recognize frequency modulated whistle-like sounds using a three alternative matching-to-sample paradigm. The dolphin was first trained to select a specific object (object A) in response to a specific sound (sound A) for a total of three object-sound associations. The sounds were then transformed by amplitude, duration, or frequency transposition while still preserving the frequency contour of each sound. For comparison purposes, 30 human participants completed an identical task with the same sounds, objects, and training procedure. The dolphin’s ability to correctly match objects to sounds was robust to changes in amplitude with only a minor decrement in performance for short durations. The dolphin failed to recognize sounds that were frequency transposed by plus or minus ½ octaves. Human participants demonstrated robust recognition with all acoustic transformations. The results indicate that this dolphin’s acoustic recognition of whistle-like sounds was constrained by absolute pitch. Unlike human speech, which varies considerably in average frequency, signature whistles are relatively stable in frequency, which may have selected for a whistle recognition system invariant to frequency transposition. PMID:26863519

Abnormal Facial Emotion Recognition in Depression: Serial Testing in an Ultra-Rapid-Cycling Patient.

ERIC Educational Resources Information Center

George, Mark S.; Huggins, Teresa; McDermut, Wilson; Parekh, Priti I.; Rubinow, David; Post, Robert M.

1998-01-01

Mood disorder subjects have a selective deficit in recognizing human facial emotion. Whether the facial emotion recognition errors persist during normal mood states (i.e., are state vs. trait dependent) was studied in one male bipolar II patient. Results of five sessions are presented and discussed. (Author/EMK)

Visual Word Recognition by Bilinguals in a Sentence Context: Evidence for Nonselective Lexical Access

ERIC Educational Resources Information Center

Duyck, Wouter; Van Assche, Eva; Drieghe, Denis; Hartsuiker, Robert J.

2007-01-01

Recent research on bilingualism has shown that lexical access in visual word recognition by bilinguals is not selective with respect to language. In the present study, the authors investigated language-independent lexical access in bilinguals reading sentences, which constitutes a strong unilingual linguistic context. In the first experiment,…

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

PubMed

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.

The Linguistic Affiliation Constraint and Phoneme Recognition in Diglossic Arabic

ERIC Educational Resources Information Center

Saiegh-Haddad, Elinor; Levin, Iris; Hende, Nareman; Ziv, Margalit

2011-01-01

This study tested the effect of the phoneme's linguistic affiliation (Standard Arabic versus Spoken Arabic) on phoneme recognition among five-year-old Arabic native speaking kindergarteners (N=60). Using a picture selection task of words beginning with the same phoneme, and through careful manipulation of the phonological properties of target…

PATTERN RECOGNITION APPROACH TO MEDICAL DIAGNOSIS,

DTIC Science & Technology

A sequential method of pattern recognition was used to recognize hyperthyroidism in a sample of 2219 patients being treated at the Straub Clinic in...the most prominent class features are selected. Thus, the symptoms which best distinguish hyperthyroidism are extracted at every step and the number of tests required to reach a diagnosis is reduced. (Author)

Selection of Norway spruce somatic embryos by computer vision

NASA Astrophysics Data System (ADS)

Hamalainen, Jari J.; Jokinen, Kari J.

1993-05-01

A computer vision system was developed for the classification of plant somatic embryos. The embryos are in a Petri dish that is transferred with constant speed and they are recognized as they pass a line scan camera. A classification algorithm needs to be installed for every plant species. This paper describes an algorithm for the recognition of Norway spruce (Picea abies) embryos. A short review of conifer micropropagation by somatic embryogenesis is also given. The recognition algorithm is based on features calculated from the boundary of the object. Only part of the boundary corresponding to the developing cotyledons (2 - 15) and the straight sides of the embryo are used for recognition. An index of the length of the cotyledons describes the developmental stage of the embryo. The testing set for classifier performance consisted of 118 embryos and 478 nonembryos. With the classification tolerances chosen 69% of the objects classified as embryos by a human classifier were selected and 31$% rejected. Less than 1% of the nonembryos were classified as embryos. The basic features developed can probably be easily adapted for the recognition of other conifer somatic embryos.

Recognition and identification of famous faces in patients with unilateral temporal lobe epilepsy.

PubMed

Seidenberg, Michael; Griffith, Randall; Sabsevitz, David; Moran, Maria; Haltiner, Alan; Bell, Brian; Swanson, Sara; Hammeke, Thomas; Hermann, Bruce

2002-01-01

We examined the performance of 21 patients with unilateral temporal lobe epilepsy (TLE) and hippocampal damage (10 lefts, and 11 rights) and 10 age-matched controls on the recognition and identification (name and occupation) of well-known faces. Famous face stimuli were selected from four time periods; 1970s, 1980s, 1990-1994, and 1995-1996. Differential patterns of performance were observed for the left and right TLE group across distinct face processing components. The left TLE group showed a selective impairment in naming famous faces while they performed similar to the controls in face recognition and semantic identification (i.e. occupation). In contrast, the right TLE group was impaired across all components of face memory; face recognition, semantic identification, and face naming. Face naming impairment in the left TLE group was characterized by a temporal gradient with better naming performance for famous faces from more distant time periods. Findings are discussed in terms of the role of the temporal lobe system for the acquisition, retention, and retrieval of face semantic networks, and the differential effects of lateralized temporal lobe lesions in this process.

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

NASA Astrophysics Data System (ADS)

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.

Fabrication of a high selectivity magnetic solid phase extraction adsorbent based on β-cyclodextrin and application for recognition of plant growth regulators.

PubMed

Chen, Jiuyan; Cao, Shurui; Zhu, Ming; Xi, Cunxian; Zhang, Lei; Li, Xianliang; Wang, Guomin; Zhou, Yuantao; Chen, Zhiqiong

2018-04-27

An adsorbent, consisting of silica-coated Fe 3 O 4 grafted graphene oxide and β-cyclodextrin (Fe 3 O 4 @SiO 2 /GO/β-CD), which possessed the merits of antioxidation, superparamagnetism, high surface area, high supramolecular recognition and environment friendly, was successfully fabricated. Considering the synergy between β-CD and graphene oxide in adsorption mechanism, the synthesized adsorbent could grasp compounds especially with aromatic structures through π-π interaction, hydrophobic interaction and host-guest inclusion complex forming. Based on the advantages, a magnetic solid phase extraction (MSPE) method for 9 PGRs using Fe 3 O 4 @SiO 2 /GO/β-CD as adsorbents was developed in this study. The characterizations of Fe 3 O 4 @SiO 2 /GO/β-CD were performed on Fourier transform infrared spectrometry (FT-IR), X-ray photoelectron spectroscopy (XPS), CHNS/O elemental analyzer, scanning electron microscopy (SEM) and vibrating sample magnetometry (VSM). Under the optimal MSPE condition, the Fe 3 O 4 @SiO 2 /GO/β-CD exhibited selectivity capability toward 9 PGRs when compared with Fe 3 O 4 @SiO 2 /GO. Meanwhile, the selectivity capability of Fe 3 O 4 @SiO 2 /GO/β-CD was higher than that of Fe 3 O 4 @SiO 2 /GO/α-CD except for 4-FPA. When the developed MSPE procedure was coupled with ultra-high performance liquid chromatography-triple quadrupole linear ion trap mass spectrometry (UHPLC-QTrap-MS/MS) to quantitative analysis of 9 PGRs, linearities ranging from 2 to 50 μg/kg were achieved for 9 PGRs with the correlation coefficients (r 2 ) in the range of 0.9975-0.9999. The limits of detection (LODs) for 9 analytes varied from 0.04 to 0.29 μg/kg. Finally, the proposed technique was applied to analyze PGRs residues in mutiple vegetable samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Selectivity Enhancement by Using Double-Layer MOX-Based Gas Sensors Prepared by Flame Spray Pyrolysis (FSP).

PubMed

Rebholz, Julia; Grossmann, Katharina; Pham, David; Pokhrel, Suman; Mädler, Lutz; Weimar, Udo; Barsan, Nicolae

2016-09-06

Here we present a novel concept for the selective recognition of different target gases with a multilayer semiconducting metal oxide (SMOX)-based sensor device. Direct current (DC) electrical resistance measurements were performed during exposure to CO and ethanol as single gases and mixtures of highly porous metal oxide double- and single-layer sensors obtained by flame spray pyrolysis. The results show that the calculated resistance ratios of the single- and double-layer sensors are a good indicator for the presence of specific gases in the atmosphere, and can constitute some building blocks for the development of chemical logic devices. Due to the inherent lack of selectivity of SMOX-based gas sensors, such devices could be especially relevant for domestic applications.

Selectivity Enhancement by Using Double-Layer MOX-Based Gas Sensors Prepared by Flame Spray Pyrolysis (FSP)

PubMed Central

Rebholz, Julia; Grossmann, Katharina; Pham, David; Pokhrel, Suman; Mädler, Lutz; Weimar, Udo; Barsan, Nicolae

2016-01-01

Here we present a novel concept for the selective recognition of different target gases with a multilayer semiconducting metal oxide (SMOX)-based sensor device. Direct current (DC) electrical resistance measurements were performed during exposure to CO and ethanol as single gases and mixtures of highly porous metal oxide double- and single-layer sensors obtained by flame spray pyrolysis. The results show that the calculated resistance ratios of the single- and double-layer sensors are a good indicator for the presence of specific gases in the atmosphere, and can constitute some building blocks for the development of chemical logic devices. Due to the inherent lack of selectivity of SMOX-based gas sensors, such devices could be especially relevant for domestic applications. PMID:27608028

Recognition of names of eminent psychologists.

PubMed

Duncan, C P

1976-10-01

Faculty members, graduate students, undergraduate majors, and introductory psychology students checked those names they recognized in the list of 228 deceased psychologists, rated for eminence, provided by Annin, Boring, and Watson. Mean percentage recognition was less than 50% for the 128 American psychologists, and less than 25% for the 100 foreign psychologists, by the faculty subjects. The other three groups of subjects gave even lower recognition scores. Recognition was probably also influenced by recency; median year of death of the American psychologists was 1955, of the foreign psychologists, 1943. High recognition (defined as recognition by 80% or more of the faculty group) was achieved by only 34 psychologists, almost all of them American. These highly recognized psychologists also had high eminence ratings, but there was an equal number of psychologists with high eminence ratings that were poorly recognized.

Supramolecular recognition control of polyethylene glycol modified N-doped graphene quantum dots: tunable selectivity for alkali and alkaline-earth metal ions.

PubMed

Yang, Siwei; Sun, Jing; Zhu, Chong; He, Peng; Peng, Zheng; Ding, Guqiao

2016-02-07

The graphene quantum dot based fluorescent probe community needs unambiguous evidence about the control on the ion selectivity. In this paper, polyethylene glycol modified N-doped graphene quantum dots (PN-GQDs) were synthesized by alkylation reaction between graphene quantum dots and organic halides. We demonstrate the tunable selectivity and sensitivity by controlling the supramolecular recognition through the length and the end group size of the polyether chain on PN-GQDs. The relationship formulae between the selectivity/detection limit and polyether chains are experimentally deduced. The polyether chain length determines the interaction between the PN-GQDs and ions with different ratios of charge to radius, which in turn leads to a good selectivity control. Meanwhile the detection limit shows an exponential growth with the size of end groups of the polyether chain. The PN-GQDs can be used as ultrasensitive and selective fluorescent probes for Li(+), Na(+), K(+), Mg(2+), Ca(2+) and Sr(2+), respectively.