Jet-Based Local Image Descriptors

DEFF Research Database (Denmark)

Larsen, Anders Boesen Lindbo; Darkner, Sune; Dahl, Anders Lindbjerg

2012-01-01

We present a general novel image descriptor based on higherorder differential geometry and investigate the effect of common descriptor choices. Our investigation is twofold in that we develop a jet-based descriptor and perform a comparative evaluation with current state-of-the-art descriptors on ...

Unconscious Congruency Priming from Unpracticed Words Is Modulated by Prime-Target Semantic Relatedness

Science.gov (United States)

Ortells, Juan J.; Mari-Beffa, Paloma; Plaza-Ayllon, Vanesa

2013-01-01

Participants performed a 2-choice categorization task on visible word targets that were preceded by novel (unpracticed) prime words. The prime words were presented for 33 ms and followed either immediately (Experiments 1-3) or after a variable delay (Experiments 1 and 4) by a pattern mask. Both subjective and objective measures of prime visibility…

Mordred: a molecular descriptor calculator.

Science.gov (United States)

Moriwaki, Hirotomo; Tian, Yu-Shi; Kawashita, Norihito; Takagi, Tatsuya

2018-02-06

Molecular descriptors are widely employed to present molecular characteristics in cheminformatics. Various molecular-descriptor-calculation software programs have been developed. However, users of those programs must contend with several issues, including software bugs, insufficient update frequencies, and software licensing constraints. To address these issues, we propose Mordred, a developed descriptor-calculation software application that can calculate more than 1800 two- and three-dimensional descriptors. It is freely available via GitHub. Mordred can be easily installed and used in the command line interface, as a web application, or as a high-flexibility Python package on all major platforms (Windows, Linux, and macOS). Performance benchmark results show that Mordred is at least twice as fast as the well-known PaDEL-Descriptor and it can calculate descriptors for large molecules, which cannot be accomplished by other software. Owing to its good performance, convenience, number of descriptors, and a lax licensing constraint, Mordred is a promising choice of molecular descriptor calculation software that can be utilized for cheminformatics studies, such as those on quantitative structure-property relationships.

The great descriptor melting pot: mixing descriptors for the common good of QSAR models.

Science.gov (United States)

Tseng, Yufeng J; Hopfinger, Anton J; Esposito, Emilio Xavier

2012-01-01

The usefulness and utility of QSAR modeling depends heavily on the ability to estimate the values of molecular descriptors relevant to the endpoints of interest followed by an optimized selection of descriptors to form the best QSAR models from a representative set of the endpoints of interest. The performance of a QSAR model is directly related to its molecular descriptors. QSAR modeling, specifically model construction and optimization, has benefited from its ability to borrow from other unrelated fields, yet the molecular descriptors that form QSAR models have remained basically unchanged in both form and preferred usage. There are many types of endpoints that require multiple classes of descriptors (descriptors that encode 1D through multi-dimensional, 4D and above, content) needed to most fully capture the molecular features and interactions that contribute to the endpoint. The advantages of QSAR models constructed from multiple, and different, descriptor classes have been demonstrated in the exploration of markedly different, and principally biological systems and endpoints. Multiple examples of such QSAR applications using different descriptor sets are described and that examined. The take-home-message is that a major part of the future of QSAR analysis, and its application to modeling biological potency, ADME-Tox properties, general use in virtual screening applications, as well as its expanding use into new fields for building QSPR models, lies in developing strategies that combine and use 1D through nD molecular descriptors.

DDC Descriptor Frequencies.

Science.gov (United States)

Klingbiel, Paul H.; Jacobs, Charles R.

This report summarizes the frequency of use of the 7144 descriptors used for indexing technical reports in the Defense Documentation Center (DDC) collection. The descriptors are arranged alphabetically in the first section and by frequency in the second section. The frequency data cover about 427,000 AD documents spanning the interval from March…

BCL::EMAS — Enantioselective Molecular Asymmetry Descriptor for 3D-QSAR

Directory of Open Access Journals (Sweden)

Mariusz Butkiewicz

2012-08-01

Full Text Available Stereochemistry is an important determinant of a molecule’s biological activity. Stereoisomers can have different degrees of efficacy or even opposing effects when interacting with a target protein. Stereochemistry is a molecular property difficult to represent in 2D-QSAR as it is an inherently three-dimensional phenomenon. A major drawback of most proposed descriptors for 3D-QSAR that encode stereochemistry is that they require a heuristic for defining all stereocenters and rank-ordering its substituents. Here we propose a novel 3D-QSAR descriptor termed Enantioselective Molecular ASymmetry (EMAS that is capable of distinguishing between enantiomers in the absence of such heuristics. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. A radial-distribution function (RDF determines a signed volume of tetrahedrons of all triplets of atoms and the molecule center. The descriptor can be enriched with atom-centric properties such as partial charge. This descriptor showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r² = 0.89, q² = 0.78. Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS for inhibitors and substrates of cytochrome P450 (PUBCHEM AID891.

FEATURE DESCRIPTOR BY CONVOLUTION AND POOLING AUTOENCODERS

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L. Chen

2015-03-01

Full Text Available In this paper we present several descriptors for feature-based matching based on autoencoders, and we evaluate the performance of these descriptors. In a training phase, we learn autoencoders from image patches extracted in local windows surrounding key points determined by the Difference of Gaussian extractor. In the matching phase, we construct key point descriptors based on the learned autoencoders, and we use these descriptors as the basis for local keypoint descriptor matching. Three types of descriptors based on autoencoders are presented. To evaluate the performance of these descriptors, recall and 1-precision curves are generated for different kinds of transformations, e.g. zoom and rotation, viewpoint change, using a standard benchmark data set. We compare the performance of these descriptors with the one achieved for SIFT. Early results presented in this paper show that, whereas SIFT in general performs better than the new descriptors, the descriptors based on autoencoders show some potential for feature based matching.

Eye movements and word skipping during reading: Effects of word length and predictability

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Rayner, Keith; Slattery, Timothy J.; Drieghe, Denis; Liversedge, Simon P.

2012-01-01

The extent to which target words were predictable from prior context was varied: half of the target words were predictable and the other half were unpredictable. In addition, the length of the target word varied: the target words were short (4–6 letters), medium (7–9 letters), or long (10–12 letters). Length and predictability both yielded strong effects on the probability of skipping the target words and on the amount of time readers fixated the target words (when they were not skipped). However, there was no interaction in any of the measures examined for either skipping or fixation time. The results demonstrate that word predictability (due to contextual constraint) and word length have strong and independent influences on word skipping and fixation durations. Furthermore, since the long words extended beyond the word identification span, the data indicate that skipping can occur on the basis of partial information in relation to word identity. PMID:21463086

SPMK AND GRABCUT BASED TARGET EXTRACTION FROM HIGH RESOLUTION REMOTE SENSING IMAGES

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W. Cui

2016-06-01

Full Text Available Target detection and extraction from high resolution remote sensing images is a basic and wide needed application. In this paper, to improve the efficiency of image interpretation, we propose a detection and segmentation combined method to realize semi-automatic target extraction. We introduce the dense transform color scale invariant feature transform (TC-SIFT descriptor and the histogram of oriented gradients (HOG & HSV descriptor to characterize the spatial structure and color information of the targets. With the k-means cluster method, we get the bag of visual words, and then, we adopt three levels’ spatial pyramid (SP to represent the target patch. After gathering lots of different kinds of target image patches from many high resolution UAV images, and using the TC-SIFT-SP and the multi-scale HOG & HSV feature, we constructed the SVM classifier to detect the target. In this paper, we take buildings as the targets. Experiment results show that the target detection accuracy of buildings can reach to above 90%. Based on the detection results which are a series of rectangle regions of the targets. We select the rectangle regions as candidates for foreground and adopt the GrabCut based and boundary regularized semi-auto interactive segmentation algorithm to get the accurate boundary of the target. Experiment results show its accuracy and efficiency. It can be an effective way for some special targets extraction.

Spmk and Grabcut Based Target Extraction from High Resolution Remote Sensing Images

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Cui, Weihong; Wang, Guofeng; Feng, Chenyi; Zheng, Yiwei; Li, Jonathan; Zhang, Yi

2016-06-01

Target detection and extraction from high resolution remote sensing images is a basic and wide needed application. In this paper, to improve the efficiency of image interpretation, we propose a detection and segmentation combined method to realize semi-automatic target extraction. We introduce the dense transform color scale invariant feature transform (TC-SIFT) descriptor and the histogram of oriented gradients (HOG) & HSV descriptor to characterize the spatial structure and color information of the targets. With the k-means cluster method, we get the bag of visual words, and then, we adopt three levels' spatial pyramid (SP) to represent the target patch. After gathering lots of different kinds of target image patches from many high resolution UAV images, and using the TC-SIFT-SP and the multi-scale HOG & HSV feature, we constructed the SVM classifier to detect the target. In this paper, we take buildings as the targets. Experiment results show that the target detection accuracy of buildings can reach to above 90%. Based on the detection results which are a series of rectangle regions of the targets. We select the rectangle regions as candidates for foreground and adopt the GrabCut based and boundary regularized semi-auto interactive segmentation algorithm to get the accurate boundary of the target. Experiment results show its accuracy and efficiency. It can be an effective way for some special targets extraction.

Design of an optimal preview controller for linear discrete-time descriptor systems with state delay

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Cao, Mengjuan; Liao, Fucheng

2015-04-01

In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.

Dual descriptors within the framework of spin-polarized density functional theory.

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Chamorro, E; Pérez, P; Duque, M; De Proft, F; Geerlings, P

2008-08-14

Spin-polarized density functional theory (SP-DFT) allows both the analysis of charge-transfer (e.g., electrophilic and nucleophilic reactivity) and of spin-polarization processes (e.g., photophysical changes arising from electron transitions). In analogy with the dual descriptor introduced by Morell et al. [J. Phys. Chem. A 109, 205 (2005)], we introduce new dual descriptors intended to simultaneously give information of the molecular regions where the spin-polarization process linking states of different multiplicity will drive electron density and spin density changes. The electronic charge and spin rearrangement in the spin forbidden radiative transitions S(0)-->T(n,pi(*)) and S(0)-->T(pi,pi(*)) in formaldehyde and ethylene, respectively, have been used as benchmark examples illustrating the usefulness of the new spin-polarization dual descriptors. These quantities indicate those regions where spin-orbit coupling effects are at work in such processes. Additionally, the qualitative relationship between the topology of the spin-polarization dual descriptors and the vertical singlet triplet energy gap in simple substituted carbene series has been also discussed. It is shown that the electron density and spin density rearrangements arise in agreement with spectroscopic experimental evidence and other theoretical results on the selected target systems.

A comparison between space-time video descriptors

Science.gov (United States)

Costantini, Luca; Capodiferro, Licia; Neri, Alessandro

2013-02-01

The description of space-time patches is a fundamental task in many applications such as video retrieval or classification. Each space-time patch can be described by using a set of orthogonal functions that represent a subspace, for example a sphere or a cylinder, within the patch. In this work, our aim is to investigate the differences between the spherical descriptors and the cylindrical descriptors. In order to compute the descriptors, the 3D spherical and cylindrical Zernike polynomials are employed. This is important because both the functions are based on the same family of polynomials, and only the symmetry is different. Our experimental results show that the cylindrical descriptor outperforms the spherical descriptor. However, the performances of the two descriptors are similar.

Topological Substituent Descriptors

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Mircea V. DIUDEA

2002-12-01

Full Text Available Motivation. Substituted 1,3,5-triazines are known as useful herbicidal substances. In view of reducing the cost of biological screening, computational methods are carried out for evaluating the biological activity of organic compounds. Often a class of bioactives differs only in the substituent attached to a basic skeleton. In such cases substituent descriptors will give the same prospecting results as in case of using the whole molecule description, but with significantly reduced computational time. Such descriptors are useful in describing steric effects involved in chemical reactions. Method. Molecular topology is the method used for substituent description and multi linear regression analysis as a statistical tool. Results. Novel topological descriptors, XLDS and Ws, based on the layer matrix of distance sums and walks in molecular graphs, respectively, are proposed for describing the topology of substituents linked on a chemical skeleton. They are tested for modeling the esterification reaction in the class of benzoic acids and herbicidal activity of 2-difluoromethylthio-4,6-bis(monoalkylamino-1,3,5-triazines. Conclusions. Ws substituent descriptor, based on walks in graph, satisfactorily describes the steric effect of alkyl substituents behaving in esterification reaction, with good correlations to the Taft and Charton steric parameters, respectively. Modeling the herbicidal activity of the seo of 1,3,5-triazines exceeded the models reported in literature, so far.

Processing negative valence of word pairs that include a positive word.

Science.gov (United States)

Itkes, Oksana; Mashal, Nira

2016-09-01

Previous research has suggested that cognitive performance is interrupted by negative relative to neutral or positive stimuli. We examined whether negative valence affects performance at the word or phrase level. Participants performed a semantic decision task on word pairs that included either a negative or a positive target word. In Experiment 1, the valence of the target word was congruent with the overall valence conveyed by the word pair (e.g., fat kid). As expected, response times were slower in the negative condition relative to the positive condition. Experiment 2 included target words that were incongruent with the overall valence of the word pair (e.g., fat salary). Response times were longer for word pairs whose overall valence was negative relative to positive, even though these word pairs included a positive word. Our findings support the Cognitive Primacy Hypothesis, according to which emotional valence is extracted after conceptual processing is complete.

TreeBASIS Feature Descriptor and Its Hardware Implementation

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Spencer Fowers

2014-01-01

Full Text Available This paper presents a novel feature descriptor called TreeBASIS that provides improvements in descriptor size, computation time, matching speed, and accuracy. This new descriptor uses a binary vocabulary tree that is computed using basis dictionary images and a test set of feature region images. To facilitate real-time implementation, a feature region image is binary quantized and the resulting quantized vector is passed into the BASIS vocabulary tree. A Hamming distance is then computed between the feature region image and the effectively descriptive basis dictionary image at a node to determine the branch taken and the path the feature region image takes is saved as a descriptor. The TreeBASIS feature descriptor is an excellent candidate for hardware implementation because of its reduced descriptor size and the fact that descriptors can be created and features matched without the use of floating point operations. The TreeBASIS descriptor is more computationally and space efficient than other descriptors such as BASIS, SIFT, and SURF. Moreover, it can be computed entirely in hardware without the support of a CPU for additional software-based computations. Experimental results and a hardware implementation show that the TreeBASIS descriptor compares well with other descriptors for frame-to-frame homography computation while requiring fewer hardware resources.

[Effect of concreteness of target words on verbal working memory: an evaluation using Japanese version of reading span test].

Science.gov (United States)

Kondo, H; Osaka, N

2000-04-01

Effects of concreteness and representation mode (kanji/hiragana) of target words on working memory during reading was tested using Japanese version of reading span test (RST), developed by Osaka and Osaka (1994). Concreteness and familiarity of target words and difficulty of sentences were carefully controlled. The words with high concreteness resulted in significantly higher RST scores, which suggests the high efficiency of working memory in processing these words. The results suggest that high concrete noun-words associated with visual clues consume less working memory capacity during reading. The effect of representation mode is different between subjects with high-RST and low-RST scores. Characteristic of the high concrete words that may be responsible for the effectiveness of processing are discussed.

Accuracy of geographically targeted internet advertisements on Google AdWords for recruitment in a randomized trial.

Science.gov (United States)

Jones, Ray B; Goldsmith, Lesley; Williams, Christopher J; Kamel Boulos, Maged N

2012-06-20

Google AdWords are increasingly used to recruit people into research studies and clinical services. They offer the potential to recruit from targeted control areas in cluster randomized controlled trials (RCTs), but little is known about the feasibility of accurately targeting ads by location and comparing with control areas. To examine the accuracy and contamination of control areas by a location-targeted online intervention using Google AdWords in a pilot cluster RCT. Based on previous use of online cognitive behavioral therapy for depression and population size, we purposively selected 16 of the 121 British postcode areas and randomized them to three intervention and one (do-nothing) control arms. Two intervention arms included use of location-targeted AdWords, and we compared these with the do-nothing control arm. We did not raise the visibility of our research website to normal Web searches. Users who clicked on the ad were directed to our project website, which collected the computer Internet protocol (IP) address, date, and time. Visitors were asked for their postcode area and to complete the Patient Health Questionnaire (depression). They were then offered links to several online depression resources. Google Analytics largely uses IP methods to estimate location, but AdWords uses additional information. We compared locations assessed by (1) Analytics, and (2) as self-identified by users. Ads were shown 300,523 times with 4207 click-throughs. There were few site visits except through AdWord click-throughs. Both methods of location assessment agreed there was little contamination of control areas. According to Analytics, 69.75% (2617/3752) of participants were in intervention areas, only 0% (8/3752) in control areas, but 30.04% (1127/3752) in other areas. However, according to user-stated postcodes, only 20.7% (463/2237) were in intervention areas, 1% (22/2236) in control areas, but 78.31% (1751/2236) in other areas. Both location assessments suggested most

Density-Based 3D Shape Descriptors

Directory of Open Access Journals (Sweden)

Schmitt Francis

2007-01-01

Full Text Available We propose a novel probabilistic framework for the extraction of density-based 3D shape descriptors using kernel density estimation. Our descriptors are derived from the probability density functions (pdf of local surface features characterizing the 3D object geometry. Assuming that the shape of the 3D object is represented as a mesh consisting of triangles with arbitrary size and shape, we provide efficient means to approximate the moments of geometric features on a triangle basis. Our framework produces a number of 3D shape descriptors that prove to be quite discriminative in retrieval applications. We test our descriptors and compare them with several other histogram-based methods on two 3D model databases, Princeton Shape Benchmark and Sculpteur, which are fundamentally different in semantic content and mesh quality. Experimental results show that our methodology not only improves the performance of existing descriptors, but also provides a rigorous framework to advance and to test new ones.

Fingerprint Identification Using SIFT-Based Minutia Descriptors and Improved All Descriptor-Pair Matching

Directory of Open Access Journals (Sweden)

Jiuqiang Han

2013-03-01

Full Text Available The performance of conventional minutiae-based fingerprint authentication algorithms degrades significantly when dealing with low quality fingerprints with lots of cuts or scratches. A similar degradation of the minutiae-based algorithms is observed when small overlapping areas appear because of the quite narrow width of the sensors. Based on the detection of minutiae, Scale Invariant Feature Transformation (SIFT descriptors are employed to fulfill verification tasks in the above difficult scenarios. However, the original SIFT algorithm is not suitable for fingerprint because of: (1 the similar patterns of parallel ridges; and (2 high computational resource consumption. To enhance the efficiency and effectiveness of the algorithm for fingerprint verification, we propose a SIFT-based Minutia Descriptor (SMD to improve the SIFT algorithm through image processing, descriptor extraction and matcher. A two-step fast matcher, named improved All Descriptor-Pair Matching (iADM, is also proposed to implement the 1:N verifications in real-time. Fingerprint Identification using SMD and iADM (FISiA achieved a significant improvement with respect to accuracy in representative databases compared with the conventional minutiae-based method. The speed of FISiA also can meet real-time requirements.

Structural protein descriptors in 1-dimension and their sequence-based predictions.

Science.gov (United States)

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

Separability of local reactivity descriptors

Indian Academy of Sciences (India)

Unknown

Abstract. The size-dependence of different local reactivity descriptors of dimer A2 and AB type of sys- tems is discussed. We derive analytic results of these descriptors calculated using finite difference approximation. In particular, we studied Fukui functions, relative electrophilicity and relative nucleo- philicity, local softness ...

Descriptor Learning via Supervised Manifold Regularization for Multioutput Regression.

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Zhen, Xiantong; Yu, Mengyang; Islam, Ali; Bhaduri, Mousumi; Chan, Ian; Li, Shuo

2017-09-01

Multioutput regression has recently shown great ability to solve challenging problems in both computer vision and medical image analysis. However, due to the huge image variability and ambiguity, it is fundamentally challenging to handle the highly complex input-target relationship of multioutput regression, especially with indiscriminate high-dimensional representations. In this paper, we propose a novel supervised descriptor learning (SDL) algorithm for multioutput regression, which can establish discriminative and compact feature representations to improve the multivariate estimation performance. The SDL is formulated as generalized low-rank approximations of matrices with a supervised manifold regularization. The SDL is able to simultaneously extract discriminative features closely related to multivariate targets and remove irrelevant and redundant information by transforming raw features into a new low-dimensional space aligned to targets. The achieved discriminative while compact descriptor largely reduces the variability and ambiguity for multioutput regression, which enables more accurate and efficient multivariate estimation. We conduct extensive evaluation of the proposed SDL on both synthetic data and real-world multioutput regression tasks for both computer vision and medical image analysis. Experimental results have shown that the proposed SDL can achieve high multivariate estimation accuracy on all tasks and largely outperforms the algorithms in the state of the arts. Our method establishes a novel SDL framework for multioutput regression, which can be widely used to boost the performance in different applications.

Determination of solute descriptors by chromatographic methods

International Nuclear Information System (INIS)

Poole, Colin F.; Atapattu, Sanka N.; Poole, Salwa K.; Bell, Andrea K.

2009-01-01

The solvation parameter model is now well established as a useful tool for obtaining quantitative structure-property relationships for chemical, biomedical and environmental processes. The model correlates a free-energy related property of a system to six free-energy derived descriptors describing molecular properties. These molecular descriptors are defined as L (gas-liquid partition coefficient on hexadecane at 298 K), V (McGowan's characteristic volume), E (excess molar refraction), S (dipolarity/polarizability), A (hydrogen-bond acidity), and B (hydrogen-bond basicity). McGowan's characteristic volume is trivially calculated from structure and the excess molar refraction can be calculated for liquids from their refractive index and easily estimated for solids. The remaining four descriptors are derived by experiment using (largely) two-phase partitioning, chromatography, and solubility measurements. In this article, the use of gas chromatography, reversed-phase liquid chromatography, micellar electrokinetic chromatography, and two-phase partitioning for determining solute descriptors is described. A large database of experimental retention factors and partition coefficients is constructed after first applying selection tools to remove unreliable experimental values and an optimized collection of varied compounds with descriptor values suitable for calibrating chromatographic systems is presented. These optimized descriptors are demonstrated to be robust and more suitable than other groups of descriptors characterizing the separation properties of chromatographic systems.

Determination of solute descriptors by chromatographic methods.

Science.gov (United States)

Poole, Colin F; Atapattu, Sanka N; Poole, Salwa K; Bell, Andrea K

2009-10-12

The solvation parameter model is now well established as a useful tool for obtaining quantitative structure-property relationships for chemical, biomedical and environmental processes. The model correlates a free-energy related property of a system to six free-energy derived descriptors describing molecular properties. These molecular descriptors are defined as L (gas-liquid partition coefficient on hexadecane at 298K), V (McGowan's characteristic volume), E (excess molar refraction), S (dipolarity/polarizability), A (hydrogen-bond acidity), and B (hydrogen-bond basicity). McGowan's characteristic volume is trivially calculated from structure and the excess molar refraction can be calculated for liquids from their refractive index and easily estimated for solids. The remaining four descriptors are derived by experiment using (largely) two-phase partitioning, chromatography, and solubility measurements. In this article, the use of gas chromatography, reversed-phase liquid chromatography, micellar electrokinetic chromatography, and two-phase partitioning for determining solute descriptors is described. A large database of experimental retention factors and partition coefficients is constructed after first applying selection tools to remove unreliable experimental values and an optimized collection of varied compounds with descriptor values suitable for calibrating chromatographic systems is presented. These optimized descriptors are demonstrated to be robust and more suitable than other groups of descriptors characterizing the separation properties of chromatographic systems.

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

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Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

2017-02-03

The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluating color descriptors for object and scene recognition.

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van de Sande, Koen E A; Gevers, Theo; Snoek, Cees G M

2010-09-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition. Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors (software to compute the color descriptors from this paper is available from http://www.colordescriptors.com) in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a data set with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain. From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results further reveal that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the data set and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8 percent on the PASCAL VOC 2007 and by 7 percent on the Mediamill Challenge.

Descriptors of server capabilities in China

DEFF Research Database (Denmark)

Adeyemi, Oluseyi; Slepniov, Dmitrij; Wæhrens, Brian Vejrum

are relevant to determine subsidiary roles and as an indication of the capabilities required. These descriptors are identified through extensive literature review and validated by case studies of two Danish multinational companies subsidiaries operating in China. They provided the empirical basis......China with the huge market potential it possesses is an important issue for subsidiaries of western multinational companies. The objective of this paper is therefore to strengthen researchers’ and practitioners’ perspectives on what are the descriptors of server capabilities. The descriptors...

How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space.

Science.gov (United States)

Koutsoukas, Alexios; Paricharak, Shardul; Galloway, Warren R J D; Spring, David R; Ijzerman, Adriaan P; Glen, Robert C; Marcus, David; Bender, Andreas

2014-01-27

Chemical diversity is a widely applied approach to select structurally diverse subsets of molecules, often with the objective of maximizing the number of hits in biological screening. While many methods exist in the area, few systematic comparisons using current descriptors in particular with the objective of assessing diversity in bioactivity space have been published, and this shortage is what the current study is aiming to address. In this work, 13 widely used molecular descriptors were compared, including fingerprint-based descriptors (ECFP4, FCFP4, MACCS keys), pharmacophore-based descriptors (TAT, TAD, TGT, TGD, GpiDAPH3), shape-based descriptors (rapid overlay of chemical structures (ROCS) and principal moments of inertia (PMI)), a connectivity-matrix-based descriptor (BCUT), physicochemical-property-based descriptors (prop2D), and a more recently introduced molecular descriptor type (namely, "Bayes Affinity Fingerprints"). We assessed both the similar behavior of the descriptors in assessing the diversity of chemical libraries, and their ability to select compounds from libraries that are diverse in bioactivity space, which is a property of much practical relevance in screening library design. This is particularly evident, given that many future targets to be screened are not known in advance, but that the library should still maximize the likelihood of containing bioactive matter also for future screening campaigns. Overall, our results showed that descriptors based on atom topology (i.e., fingerprint-based descriptors and pharmacophore-based descriptors) correlate well in rank-ordering compounds, both within and between descriptor types. On the other hand, shape-based descriptors such as ROCS and PMI showed weak correlation with the other descriptors utilized in this study, demonstrating significantly different behavior. We then applied eight of the molecular descriptors compared in this study to sample a diverse subset of sample compounds (4%) from an

Word skipping: effects of word length, predictability, spelling and reading skill.

Science.gov (United States)

Slattery, Timothy J; Yates, Mark

2017-08-31

Readers eyes often skip over words as they read. Skipping rates are largely determined by word length; short words are skipped more than long words. However, the predictability of a word in context also impacts skipping rates. Rayner, Slattery, Drieghe and Liversedge (2011) reported an effect of predictability on word skipping for even long words (10-13 characters) that extend beyond the word identification span. Recent research suggests that better readers and spellers have an enhanced perceptual span (Veldre & Andrews, 2014). We explored whether reading and spelling skill interact with word length and predictability to impact word skipping rates in a large sample (N=92) of average and poor adult readers. Participants read the items from Rayner et al. (2011) while their eye movements were recorded. Spelling skill (zSpell) was assessed using the dictation and recognition tasks developed by Sally Andrews and colleagues. Reading skill (zRead) was assessed from reading speed (words per minute) and accuracy of three 120 word passages each with 10 comprehension questions. We fit linear mixed models to the target gaze duration data and generalized linear mixed models to the target word skipping data. Target word gaze durations were significantly predicted by zRead while, the skipping likelihoods were significantly predicted by zSpell. Additionally, for gaze durations, zRead significantly interacted with word predictability as better readers relied less on context to support word processing. These effects are discussed in relation to the lexical quality hypothesis and eye movement models of reading.

Word frequency and the attentional blink: the effects of target difficulty on retrieval and consolidation processes.

Directory of Open Access Journals (Sweden)

Stefan M Wierda

Full Text Available BACKGROUND: When a second target (T2 is presented in close succession of a first target (T1 within a stream of non-targets, people often fail to detect T2-a deficit known as the attentional blink (AB. Two types of theories can be distinguished that have tried to account for this phenomenon. Whereas attentional-control theories suggest that protection of consolidation processes induces the AB, limited-resource theories claim that the AB is caused by a lack of resources. According to the latter type of theories, increasing difficulty of one or both targets should increase the magnitude of the AB. Similarly, attentional-control theories predict that a difficult T1 increases the AB due to prolonged processing. However, the prediction for T2 is not as straightforward. Prolonged processing of T2 could cause conflicts and increase the AB. However, if consolidation of T2 is postponed without loss of identity, the AB might be attenuated. METHODOLOGY/PRINCIPAL FINDINGS: Participants performed an AB task that consisted of a stream of distractor non-words and two target words. Difficulty of T1 and T2 was manipulated by varying word-frequency. Overall performance for high-frequency words was better than for low-frequency words. When T1 was highly frequent, the AB was reduced. The opposite effect was found for T2. When T2 was highly frequent, performance during the AB period was relatively worse than for a low-frequency T2. A threaded-cognition model of the AB was presented that simulated the observed pattern of behavior by taking changes in the time-course of retrieval and consolidation processes into account. Our results were replicated in a subsequent ERP study. CONCLUSIONS/SIGNIFICANCE: The finding that a difficult low-frequency T2 reduces the magnitude of the AB is at odds with limited-resource accounts of the AB. However, it was successfully accounted for by the threaded-cognition model, thus providing an explanation in terms of attentional control.

Word frequency and the attentional blink: the effects of target difficulty on retrieval and consolidation processes.

Science.gov (United States)

Wierda, Stefan M; Taatgen, Niels A; van Rijn, Hedderik; Martens, Sander

2013-01-01

When a second target (T2) is presented in close succession of a first target (T1) within a stream of non-targets, people often fail to detect T2-a deficit known as the attentional blink (AB). Two types of theories can be distinguished that have tried to account for this phenomenon. Whereas attentional-control theories suggest that protection of consolidation processes induces the AB, limited-resource theories claim that the AB is caused by a lack of resources. According to the latter type of theories, increasing difficulty of one or both targets should increase the magnitude of the AB. Similarly, attentional-control theories predict that a difficult T1 increases the AB due to prolonged processing. However, the prediction for T2 is not as straightforward. Prolonged processing of T2 could cause conflicts and increase the AB. However, if consolidation of T2 is postponed without loss of identity, the AB might be attenuated. Participants performed an AB task that consisted of a stream of distractor non-words and two target words. Difficulty of T1 and T2 was manipulated by varying word-frequency. Overall performance for high-frequency words was better than for low-frequency words. When T1 was highly frequent, the AB was reduced. The opposite effect was found for T2. When T2 was highly frequent, performance during the AB period was relatively worse than for a low-frequency T2. A threaded-cognition model of the AB was presented that simulated the observed pattern of behavior by taking changes in the time-course of retrieval and consolidation processes into account. Our results were replicated in a subsequent ERP study. The finding that a difficult low-frequency T2 reduces the magnitude of the AB is at odds with limited-resource accounts of the AB. However, it was successfully accounted for by the threaded-cognition model, thus providing an explanation in terms of attentional control.

Surface Area Distribution Descriptor for object matching

Directory of Open Access Journals (Sweden)

Mohamed F. Gafar

2010-07-01

Full Text Available Matching 3D objects by their similarity is a fundamental problem in computer vision, computer graphics and many other fields. The main challenge in object matching is to find a suitable shape representation that can be used to accurately and quickly discriminate between similar and dissimilar shapes. In this paper we present a new volumetric descriptor to represent 3D objects. The proposed descriptor is used to match objects under rigid transformations including uniform scaling. The descriptor represents the object by dividing it into shells, acquiring the area distribution of the object through those shells. The computed areas are normalised to make the descriptor scale-invariant in addition to rotation and translation invariant. The effectiveness and stability of the proposed descriptor to noise and variant sampling density as well as the effectiveness of the similarity measures are analysed and demonstrated through experimental results.

Descriptor revision belief change through direct choice

CERN Document Server

Hansson, Sven Ove

2017-01-01

This book provides a critical examination of how the choice of what to believe is represented in the standard model of belief change. In particular the use of possible worlds and infinite remainders as objects of choice is critically examined. Descriptors are introduced as a versatile tool for expressing the success conditions of belief change, addressing both local and global descriptor revision. The book presents dynamic descriptors such as Ramsey descriptors that convey how an agent’s beliefs tend to be changed in response to different inputs. It also explores sentential revision and demonstrates how local and global operations of revision by a sentence can be derived as a special case of descriptor revision. Lastly, the book examines revocation, a generalization of contraction in which a specified sentence is removed in a process that may possibly also involve the addition of some new information to the belief set.

The Activation of Embedded Words in Spoken Word Recognition.

Science.gov (United States)

Zhang, Xujin; Samuel, Arthur G

2015-01-01

The current study investigated how listeners understand English words that have shorter words embedded in them. A series of auditory-auditory priming experiments assessed the activation of six types of embedded words (2 embedded positions × 3 embedded proportions) under different listening conditions. Facilitation of lexical decision responses to targets (e.g., pig) associated with words embedded in primes (e.g., hamster ) indexed activation of the embedded words (e.g., ham ). When the listening conditions were optimal, isolated embedded words (e.g., ham ) primed their targets in all six conditions (Experiment 1a). Within carrier words (e.g., hamster ), the same set of embedded words produced priming only when they were at the beginning or comprised a large proportion of the carrier word (Experiment 1b). When the listening conditions were made suboptimal by expanding or compressing the primes, significant priming was found for isolated embedded words (Experiment 2a), but no priming was produced when the carrier words were compressed/expanded (Experiment 2b). Similarly, priming was eliminated when the carrier words were presented with one segment replaced by noise (Experiment 3). When cognitive load was imposed, priming for embedded words was again found when they were presented in isolation (Experiment 4a), but not when they were embedded in the carrier words (Experiment 4b). The results suggest that both embedded position and proportion play important roles in the activation of embedded words, but that such activation only occurs under unusually good listening conditions.

Learning discriminant face descriptor.

Science.gov (United States)

Lei, Zhen; Pietikäinen, Matti; Li, Stan Z

2014-02-01

Local feature descriptor is an important module for face recognition and those like Gabor and local binary patterns (LBP) have proven effective face descriptors. Traditionally, the form of such local descriptors is predefined in a handcrafted way. In this paper, we propose a method to learn a discriminant face descriptor (DFD) in a data-driven way. The idea is to learn the most discriminant local features that minimize the difference of the features between images of the same person and maximize that between images from different people. In particular, we propose to enhance the discriminative ability of face representation in three aspects. First, the discriminant image filters are learned. Second, the optimal neighborhood sampling strategy is soft determined. Third, the dominant patterns are statistically constructed. Discriminative learning is incorporated to extract effective and robust features. We further apply the proposed method to the heterogeneous (cross-modality) face recognition problem and learn DFD in a coupled way (coupled DFD or C-DFD) to reduce the gap between features of heterogeneous face images to improve the performance of this challenging problem. Extensive experiments on FERET, CAS-PEAL-R1, LFW, and HFB face databases validate the effectiveness of the proposed DFD learning on both homogeneous and heterogeneous face recognition problems. The DFD improves POEM and LQP by about 4.5 percent on LFW database and the C-DFD enhances the heterogeneous face recognition performance of LBP by over 25 percent.

Object classification and detection with context kernel descriptors

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2014-01-01

Context information is important in object representation. By embedding context cue of image attributes into kernel descriptors, we propose a set of novel kernel descriptors called Context Kernel Descriptors (CKD) for object classification and detection. The motivation of CKD is to use spatial...... consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature selection, Kernel Entropy Component Analysis (KECA) is exploited to learn a subset of discriminative CKD. Different from Kernel Principal Component...

Understanding the role of culture in pain: Māori practitioner perspectives of pain descriptors.

Science.gov (United States)

Magnusson, Jane E; Fennell, Joyce A

2011-01-21

There is growing interest in the role of cultural diversity within healthcare settings yet minority ethnic groups are underrepresented in the healthcare literature, including the literature on pain. To better assess and treat pain in different cultures the perspectives and experiences of that culture must be taken into consideration and therefore the present study was undertaken to better understand Māori perspectives of pain. Māori healthcare providers and kaumātua (tribal leaders/elders) completed questionnaires relating to the experience of pain and were asked to provide feedback regarding the suitability of words and phrases typically used to describe symptoms of pain and pain-related disability. Participants were also asked to provide words, or phrases (in te reo Māori or English) representing characteristics of pain which had not been provided but would be useful in the assessment of pain in a Māori population. All of the pain descriptors, and 92% of the phrases regarding the experience of pain, provided were endorsed by the majority of participants demonstrating that, as in many cultures, Māori perceive pain as a multidimensional experience impacting them on physiological, psychological, and social dimensions and that the terms and phrases of measures commonly used to assess pain appropriately capture their pain experiences. The implications of these findings are that established measures can be used when assessing pain in Māori. However, it is beneficial to confirm that the descriptors used in those measures accurately capture the experiences being measured.

Color descriptors for object category recognition

NARCIS (Netherlands)

van de Sande, K.E.A.; Gevers, T.; Snoek, C.G.M.

2008-01-01

Category recognition is important to access visual information on the level of objects. A common approach is to compute image descriptors first and then to apply machine learning to achieve category recognition from annotated examples. As a consequence, the choice of image descriptors is of great

DEVELOPING CEFR ILLUSTRATIVE DESCRIPTORS OF ASPECTS OF MEDIATION

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Brian North

2016-04-01

Full Text Available This article reports on a project commissioned and coordinated by the Council of Europe to develop descriptors for the category ‘Mediation’ in the Common European Framework of Reference for Languages. Mediation is the fourth communicative language activity presented in CEFR Chapter 4, complementing reception, interaction and production. Descriptors for mediation had not been developed in the 1993–6 Swiss National Research Project that produced the original set of illustrative descriptors for the CEFR. The work took place in the context of a wider 2013–6 project to provide an extended set of CEFR illustrative descriptors. The article describes the way in which the approach taken to mediation in the project is broader than the one taken in the presentation of mediation in the CEFR text in 2001. In addition to information transfer (conveying received information the new scheme also embraces the construction of meaning and relational mediation: the process of establishing and managing interpersonal relationships in order to create a positive, collaborative environment. Descriptors were also developed for other, related, areas. The article briefly summarises the three phases of validation to which the draft descriptors were subjected before being calibrated to the mathematic scale underlying the CEFR’s levels and descriptors.

The Activation of Embedded Words in Spoken Word Recognition

Science.gov (United States)

Zhang, Xujin; Samuel, Arthur G.

2015-01-01

The current study investigated how listeners understand English words that have shorter words embedded in them. A series of auditory-auditory priming experiments assessed the activation of six types of embedded words (2 embedded positions × 3 embedded proportions) under different listening conditions. Facilitation of lexical decision responses to targets (e.g., pig) associated with words embedded in primes (e.g., hamster) indexed activation of the embedded words (e.g., ham). When the listening conditions were optimal, isolated embedded words (e.g., ham) primed their targets in all six conditions (Experiment 1a). Within carrier words (e.g., hamster), the same set of embedded words produced priming only when they were at the beginning or comprised a large proportion of the carrier word (Experiment 1b). When the listening conditions were made suboptimal by expanding or compressing the primes, significant priming was found for isolated embedded words (Experiment 2a), but no priming was produced when the carrier words were compressed/expanded (Experiment 2b). Similarly, priming was eliminated when the carrier words were presented with one segment replaced by noise (Experiment 3). When cognitive load was imposed, priming for embedded words was again found when they were presented in isolation (Experiment 4a), but not when they were embedded in the carrier words (Experiment 4b). The results suggest that both embedded position and proportion play important roles in the activation of embedded words, but that such activation only occurs under unusually good listening conditions. PMID:25593407

Molecular structure descriptors in the computer-aided design of biologically active compounds

International Nuclear Information System (INIS)

Raevsky, Oleg A

1999-01-01

The current state of description of molecular structure in computer-aided molecular design of biologically active compounds by means of descriptors is analysed. The information contents of descriptors increases in the following sequence: element-level descriptors-structural formulae descriptors-electronic structure descriptors-molecular shape descriptors-intermolecular interaction descriptors. Each subsequent class of descriptors normally covers information contained in the previous-level ones. It is emphasised that it is practically impossible to describe all the features of a molecular structure in terms of any single class of descriptors. It is recommended to optimise the number of descriptors used by means of appropriate statistical procedures and characteristics of structure-property models based on these descriptors. The bibliography includes 371 references.

Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

Science.gov (United States)

Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

2018-03-21

Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

Recognition of handwritten characters using local gradient feature descriptors

NARCIS (Netherlands)

Surinta, Olarik; Karaaba, Mahir F.; Schomaker, Lambert R.B.; Wiering, Marco A.

2015-01-01

Abstract In this paper we propose to use local gradient feature descriptors, namely the scale invariant feature transform keypoint descriptor and the histogram of oriented gradients, for handwritten character recognition. The local gradient feature descriptors are used to extract feature vectors

Differential cognitive processing of Kanji and Kana words: do orthographic and semantic codes function in parallel in word matching task.

Science.gov (United States)

Kawakami, A; Hatta, T; Kogure, T

2001-12-01

Relative engagements of the orthographic and semantic codes in Kanji and Hiragana word recognition were investigated. In Exp. 1, subjects judged whether the pairs of Kanji words (prime and target) presented sequentially were physically identical to each other in the word condition. In the sentence condition, subjects decided whether the target word was valid for the prime sentence presented in advance. The results showed that the response times to the target swords orthographically similar (to the prime) were significantly slower than to semantically related target words in the word condition and that this was also the case in the sentence condition. In Exp. 2, subjects judged whether the target word written in Hiragana was physically identical to the prime word in the word condition. In the sentence condition, subjects decided if the target word was valid for the previously presented prime sentence. Analysis indicated that response times to orthographically similar words were slower than to semantically related words in the word condition but not in the sentence condition wherein the response times to the semantically and orthographically similar words were largely the same. Based on these results, differential contributions of orthographic and semantic codes in cognitive processing of Japanese Kanji and Hiragana words was discussed.

A Universal 3D Voxel Descriptor for Solid-State Material Informatics with Deep Convolutional Neural Networks.

Science.gov (United States)

Kajita, Seiji; Ohba, Nobuko; Jinnouchi, Ryosuke; Asahi, Ryoji

2017-12-05

Material informatics (MI) is a promising approach to liberate us from the time-consuming Edisonian (trial and error) process for material discoveries, driven by machine-learning algorithms. Several descriptors, which are encoded material features to feed computers, were proposed in the last few decades. Especially to solid systems, however, their insufficient representations of three dimensionality of field quantities such as electron distributions and local potentials have critically hindered broad and practical successes of the solid-state MI. We develop a simple, generic 3D voxel descriptor that compacts any field quantities, in such a suitable way to implement convolutional neural networks (CNNs). We examine the 3D voxel descriptor encoded from the electron distribution by a regression test with 680 oxides data. The present scheme outperforms other existing descriptors in the prediction of Hartree energies that are significantly relevant to the long-wavelength distribution of the valence electrons. The results indicate that this scheme can forecast any functionals of field quantities just by learning sufficient amount of data, if there is an explicit correlation between the target properties and field quantities. This 3D descriptor opens a way to import prominent CNNs-based algorithms of supervised, semi-supervised and reinforcement learnings into the solid-state MI.

Ensembles of Novel Visual Keywords Descriptors for Image Categorization

NARCIS (Netherlands)

Abdullah, Azizi; Veltkamp, Remco C.; Wiering, Marco

2010-01-01

Object recognition systems need effective image descriptors to obtain good performance levels. Currently, the most widely used image descriptor is the SIFT descriptor that computes histograms of orientation gradients around points in an image. A possible problem of this approach is that the number

JET ENGINE INLET DISTORTION SCREEN AND DESCRIPTOR EVALUATION

Directory of Open Access Journals (Sweden)

Jiří Pečinka

2017-02-01

Full Text Available Total pressure distortion is one of the three basic flow distortions (total pressure, total temperature and swirl distortion that might appear at the inlet of a gas turbine engine (GTE during operation. Different numerical parameters are used for assessing the total pressure distortion intensity and extent. These summary descriptors are based on the distribution of total pressure in the aerodynamic interface plane. There are two descriptors largely spread around the world, however, three or four others are still in use and can be found in current references. The staff at the University of Defence decided to compare the most common descriptors using basic flow distortion patterns in order to select the most appropriate descriptor for future department research. The most common descriptors were identified based on their prevalence in widely accessible publications. The construction and use of these descriptors are reviewed in the paper. Subsequently, they are applied to radial, angular, and combined distortion patterns of different intensities and with varied mass flow rates. The tests were performed on a specially designed test bench using an electrically driven standalone industrial centrifugal compressor, sucking air through the inlet of a TJ100 small turbojet engine. Distortion screens were placed into the inlet channel to create the desired total pressure distortions. Of the three basic distortions, only the total pressure distortion descriptors were evaluated. However, both total and static pressures were collected using a multi probe rotational measurement system.

Emotion Words: Adding Face Value.

Science.gov (United States)

Fugate, Jennifer M B; Gendron, Maria; Nakashima, Satoshi F; Barrett, Lisa Feldman

2017-06-12

Despite a growing number of studies suggesting that emotion words affect perceptual judgments of emotional stimuli, little is known about how emotion words affect perceptual memory for emotional faces. In Experiments 1 and 2 we tested how emotion words (compared with control words) affected participants' abilities to select a target emotional face from among distractor faces. Participants were generally more likely to false alarm to distractor emotional faces when primed with an emotion word congruent with the face (compared with a control word). Moreover, participants showed both decreased sensitivity (d') to discriminate between target and distractor faces, as well as altered response biases (c; more likely to answer "yes") when primed with an emotion word (compared with a control word). In Experiment 3 we showed that emotion words had more of an effect on perceptual memory judgments when the structural information in the target face was limited, as well as when participants were only able to categorize the face with a partially congruent emotion word. The overall results are consistent with the idea that emotion words affect the encoding of emotional faces in perceptual memory. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Szeged Matrix Property Indices as Descriptors to Characterize Fullerenes

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Jäntschi Lorentz

2016-12-01

Full Text Available Fullerenes are class of allotropes of carbon organized as closed cages or tubes of carbon atoms. The fullerenes with small number of atoms were not frequently investigated. This paper presents a detailed treatment of total strain energy as function of structural feature extracted from isomers of C40 fullerene using Szeged Matrix Property Indices (SMPI. The paper has a two-fold structure. First, the total strain energy of C40 fullerene isomers (40 structures was linked with SMPI descriptors under two scenarios, one which incorporate just the SMPI descriptors and the other one which contains also five calculated properties (dipole moment, scf-binding-energy, scf-core-energy, scf-electronic-energy, and heat of formation. Second, the performing models identified on C40 fullerene family or the descriptors of these models were used to predict the total strain energy on C42 fullerene isomers. The obtained results show that the inclusion of properties in the pool of descriptors led to the reduction of accurate linear models. One property, namely scf-binding-energy proved a significant contribution to total strain energy of C40 fullerene isomers. However, the top-three most performing models contain just SMPI descriptors. A model with four descriptors proved most accurate model and show fair abilities in prediction of the same property on C42 fullerene isomers when the approach considered the descriptors identified on C40 as the predicting descriptors for C42 fullerene isomers.

Semantic processing of unattended parafoveal words.

Science.gov (United States)

Di Pace, E; Longoni, A M; Zoccolotti, P

1991-08-01

The influence that a context word presented either foveally or parafoveally, may exert on the processing of a subsequent target word was studied in a semantic decision task. Fourteen subjects participated in the experiment. They were presented with word-nonword pairs (prime). One member of the pair (which the subjects had to attend to) appeared centrally, the other parafoveally. The prime was followed by a target at two inter-stimulus intervals (ISI; 200 and 2000 msec). The word stimulus of the pair could be semantically related or unrelated to the target. The subjects' task was to classify the target as animal or not animal by pressing one of two buttons as quickly as possible. When the target word was semantically associated with the foveal (attended) word the reaction times were faster for both ISIs; when it was associated with the parafoveal (unattended) word in the prime pair, there were facilitatory effects only in the short ISI condition. A second experiment was run in order to evaluate the possibility that the obtained results were due to identification of the parafoveal stimulus. The same prime-target pairs of experiment 1 (without the target stimuli) were used. The prime-target pairs were presented to fourteen subjects who were requested to name the foveal (attended) stimulus and subsequently, if possible, the parafoveal (unattended) one. Even in this condition, percentage of identification of the unattended word was only 15%, suggesting that previous findings were not due to identification of unattended stimuli. Results are discussed in relation to Posner and Snyder's (1975) dual coding theory.

Automatic evaluation stimuli – The most frequently used words to describe physical activity and the pleasantness of physical activity

Directory of Open Access Journals (Sweden)

Amanda Lea Rebar

2016-08-01

Full Text Available Physical activity is partially regulated by non-conscious processes including automatic evaluations – the spontaneous affective reactions we have to physical activity that lead us to approach or avoid physical activity opportunities. A sound understanding of which words best represent the concepts of physical activity and pleasantness (as associated with physical activity is needed to improve the measurement of automatic evaluations and related constructs (e.g., automatic self-schemas, attentional biases. The first aim of this study was to establish population-level evidence of the most common word stimuli for physical activity and pleasantness. Given that response latency measures have been applied to assess automatic evaluations of physical activity and exercise, the second aim was to determine whether people use the same behavior and pleasant descriptors for physical activity and exercise. Australian adults (N = 1,318; 54.3% women; 48.9% aged 55 years or older were randomly assigned to one of two groups, through a computer-generated 1:1 ratio allocation, to be asked to list either five behaviors and pleasant descriptors of physical activity (n = 686 or of exercise (n = 632. The words were independently coded twice as to whether they were novel words or the same as another (i.e., same stem or same meaning. Intercoder reliability varied between moderate and strong (agreement = 50.1% to 97.8%; κ = 0.48 to 0.82. A list of the 20 most common behavior and pleasantness words were established based on how many people reported them, weighted by the ranking (1-5 people gave them. The words people described as physical activity were mostly the same as those people used to describe exercise. The most common behavior words were ‘walking,’ ‘running,’ ‘swimming,’ ‘bike riding,’ and ‘gardening’; and the most common pleasant descriptor words were ‘relaxing,’ ‘happiness,’ ‘enjoyment,’ ‘exhilarating,’ ‘exhausting,’ and

Shape-tailored local descriptors and their application to segmentation and tracking

KAUST Repository

Khan, Naeemullah; Algarni, Marei Saeed Mohammed; Yezzi, Anthony; Sundaramoorthi, Ganesh

2015-01-01

We propose new dense descriptors for texture segmentation. Given a region of arbitrary shape in an image, these descriptors are formed from shape-dependent scale spaces of oriented gradients. These scale spaces are defined by Poisson-like partial differential equations. A key property of our new descriptors is that they do not aggregate image data across the boundary of the region, in contrast to existing descriptors based on aggregation of oriented gradients. As an example, we show how the descriptor can be incorporated in a Mumford-Shah energy for texture segmentation. We test our method on several challenging datasets for texture segmentation and textured object tracking. Experiments indicate that our descriptors lead to more accurate segmentation than non-shape dependent descriptors and the state-of-the-art in texture segmentation.

Shape-tailored local descriptors and their application to segmentation and tracking

KAUST Repository

Khan, Naeemullah

2015-06-07

We propose new dense descriptors for texture segmentation. Given a region of arbitrary shape in an image, these descriptors are formed from shape-dependent scale spaces of oriented gradients. These scale spaces are defined by Poisson-like partial differential equations. A key property of our new descriptors is that they do not aggregate image data across the boundary of the region, in contrast to existing descriptors based on aggregation of oriented gradients. As an example, we show how the descriptor can be incorporated in a Mumford-Shah energy for texture segmentation. We test our method on several challenging datasets for texture segmentation and textured object tracking. Experiments indicate that our descriptors lead to more accurate segmentation than non-shape dependent descriptors and the state-of-the-art in texture segmentation.

Sound insulation between dwellings - Descriptors applied in building regulations in Europe

DEFF Research Database (Denmark)

Rasmussen, Birgit; Rindel, Jens Holger

2010-01-01

Regulatory sound insulation requirements for dwellings have existed since the 1950s in some countries and descriptors for evaluation of sound insulation have existed for nearly as long. However, the descriptors have changed considerably over time, from simple arithmetic averaging of frequency bands...... was carried out of legal sound insulation requirements in 24 countries in Europe. The comparison of requirements for sound insulation between dwellings revealed significant differences in descriptors as well as levels. This paper focuses on descriptors and summarizes the history of descriptors, the problems...... of the present situation and the benefits of consensus concerning descriptors for airborne and impact sound insulation between dwellings. The descriptors suitable for evaluation should be well-defined under practical situations in buildings and be measurable. Measurement results should be reproducible...

Comparing different kinds of words and word-word relations to test an habituation model of priming.

Science.gov (United States)

Rieth, Cory A; Huber, David E

2017-06-01

Huber and O'Reilly (2003) proposed that neural habituation exists to solve a temporal parsing problem, minimizing blending between one word and the next when words are visually presented in rapid succession. They developed a neural dynamics habituation model, explaining the finding that short duration primes produce positive priming whereas long duration primes produce negative repetition priming. The model contains three layers of processing, including a visual input layer, an orthographic layer, and a lexical-semantic layer. The predicted effect of prime duration depends both on this assumed representational hierarchy and the assumption that synaptic depression underlies habituation. The current study tested these assumptions by comparing different kinds of words (e.g., words versus non-words) and different kinds of word-word relations (e.g., associative versus repetition). For each experiment, the predictions of the original model were compared to an alternative model with different representational assumptions. Experiment 1 confirmed the prediction that non-words and inverted words require longer prime durations to eliminate positive repetition priming (i.e., a slower transition from positive to negative priming). Experiment 2 confirmed the prediction that associative priming increases and then decreases with increasing prime duration, but remains positive even with long duration primes. Experiment 3 replicated the effects of repetition and associative priming using a within-subjects design and combined these effects by examining target words that were expected to repeat (e.g., viewing the target word 'BACK' after the prime phrase 'back to'). These results support the originally assumed representational hierarchy and more generally the role of habituation in temporal parsing and priming. Copyright © 2017 Elsevier Inc. All rights reserved.

The FREPA Descriptors

DEFF Research Database (Denmark)

Daryai-Hansen, Petra; Jaeger, Catherine

2015-01-01

, attitudes and skills, (b) a database of teaching material and (c) a training kit for teachers. The paper presents the FREPA descriptors by comparing them to Byram’s definition of intercultural communicative competence and Deardorff’s intercultural competence model and emphasises that FREPA deepens...

The Effects of Target Word Properties on the Incidental Acquisition of Vocabulary through Reading

Science.gov (United States)

Reynolds, Barry Lee

2016-01-01

The primary aim of this investigation was to determine what combination of target word variables (frequency, patternedness, length, cognateness, lexicalization) could best predict the difficulty of incidentally acquiring vocabulary through reading. A group of adult English First Language (EL1) (n = 20) and adult English as a Foreign Language (EFL)…

Correspondence dictionary from free English term to INIS descriptors

International Nuclear Information System (INIS)

1993-03-01

This dictionary is intended for the on-line users of INIS database who select controlled terms (INIS descriptors) starting from free terms. The purpose of terminology control is (1) to reduce the ambiguity of the term use among different subject fields, and (2) to improve the recall by coordinating the synonyms. The controlled terms are collected in the thesaurus, but it is not always easy to find suitable descriptors. This dictionary has been compiled by analyzing existing records, and provides the specialists' know-how of converting free terms to descriptors. Besides the compilation of this dictionary, the characteristics of the assigned descriptors were also clarified. (J.P.N.)

Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

Science.gov (United States)

Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

2018-06-15

Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

Learning to assign binary weights to binary descriptor

Science.gov (United States)

Huang, Zhoudi; Wei, Zhenzhong; Zhang, Guangjun

2016-10-01

Constructing robust binary local feature descriptors are receiving increasing interest due to their binary nature, which can enable fast processing while requiring significantly less memory than their floating-point competitors. To bridge the performance gap between the binary and floating-point descriptors without increasing the computational cost of computing and matching, optimal binary weights are learning to assign to binary descriptor for considering each bit might contribute differently to the distinctiveness and robustness. Technically, a large-scale regularized optimization method is applied to learn float weights for each bit of the binary descriptor. Furthermore, binary approximation for the float weights is performed by utilizing an efficient alternatively greedy strategy, which can significantly improve the discriminative power while preserve fast matching advantage. Extensive experimental results on two challenging datasets (Brown dataset and Oxford dataset) demonstrate the effectiveness and efficiency of the proposed method.

Visual attention shift to printed words during spoken word recognition in Chinese: The role of phonological information.

Science.gov (United States)

Shen, Wei; Qu, Qingqing; Tong, Xiuhong

2018-05-01

The aim of this study was to investigate the extent to which phonological information mediates the visual attention shift to printed Chinese words in spoken word recognition by using an eye-movement technique with a printed-word paradigm. In this paradigm, participants are visually presented with four printed words on a computer screen, which include a target word, a phonological competitor, and two distractors. Participants are then required to select the target word using a computer mouse, and the eye movements are recorded. In Experiment 1, phonological information was manipulated at the full-phonological overlap; in Experiment 2, phonological information at the partial-phonological overlap was manipulated; and in Experiment 3, the phonological competitors were manipulated to share either fulloverlap or partial-overlap with targets directly. Results of the three experiments showed that the phonological competitor effects were observed at both the full-phonological overlap and partial-phonological overlap conditions. That is, phonological competitors attracted more fixations than distractors, which suggested that phonological information mediates the visual attention shift during spoken word recognition. More importantly, we found that the mediating role of phonological information varies as a function of the phonological similarity between target words and phonological competitors.

Searching for the right word: Hybrid visual and memory search for words.

Science.gov (United States)

Boettcher, Sage E P; Wolfe, Jeremy M

2015-05-01

In "hybrid search" (Wolfe Psychological Science, 23(7), 698-703, 2012), observers search through visual space for any of multiple targets held in memory. With photorealistic objects as the stimuli, response times (RTs) increase linearly with the visual set size and logarithmically with the memory set size, even when over 100 items are committed to memory. It is well-established that pictures of objects are particularly easy to memorize (Brady, Konkle, Alvarez, & Oliva Proceedings of the National Academy of Sciences, 105, 14325-14329, 2008). Would hybrid-search performance be similar if the targets were words or phrases, in which word order can be important, so that the processes of memorization might be different? In Experiment 1, observers memorized 2, 4, 8, or 16 words in four different blocks. After passing a memory test, confirming their memorization of the list, the observers searched for these words in visual displays containing two to 16 words. Replicating Wolfe (Psychological Science, 23(7), 698-703, 2012), the RTs increased linearly with the visual set size and logarithmically with the length of the word list. The word lists of Experiment 1 were random. In Experiment 2, words were drawn from phrases that observers reported knowing by heart (e.g., "London Bridge is falling down"). Observers were asked to provide four phrases, ranging in length from two words to no less than 20 words (range 21-86). All words longer than two characters from the phrase, constituted the target list. Distractor words were matched for length and frequency. Even with these strongly ordered lists, the results again replicated the curvilinear function of memory set size seen in hybrid search. One might expect to find serial position effects, perhaps reducing the RTs for the first (primacy) and/or the last (recency) members of a list (Atkinson & Shiffrin, 1968; Murdock Journal of Experimental Psychology, 64, 482-488, 1962). Surprisingly, we showed no reliable effects of word order

Branch length similarity entropy-based descriptors for shape representation

Science.gov (United States)

Kwon, Ohsung; Lee, Sang-Hee

2017-11-01

In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.

Aggregating Local Descriptors for Epigraphs Recognition

OpenAIRE

Amato, Giuseppe; Falchi, Fabrizio; Rabitti, Fausto; Vadicamo, Lucia

2014-01-01

In this paper, we consider the task of recognizing epigraphs in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 epigraphs, we used a k-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in evaluating state-of-the-art visual object recognition techniques in this specific context. The experimental results conducted show that Vector of Locally Aggregated Descriptors obtained aggregating SIFT descriptors ...

Bag-of-features based medical image retrieval via multiple assignment and visual words weighting

KAUST Repository

Wang, Jingyan

2011-11-01

Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights. © 2011 IEEE.

Bag-of-features based medical image retrieval via multiple assignment and visual words weighting

KAUST Repository

Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

2011-01-01

Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights. © 2011 IEEE.

Semantic context effects and priming in word association.

Science.gov (United States)

Zeelenberg, René; Pecher, Diane; Shiffrin, Richard M; Raaijmakers, Jeroen G W

2003-09-01

Two experiments investigated priming in word association, an implicit memory task. In the study phase of Experiment 1, semantically ambiguous target words were presented in sentences that biased their interpretation. The appropriate interpretation of the target was either congruent or incongruent with the cue presented in a subsequent word association task. Priming (i.e., a higher proportion of target responses relative to a nonstudied baseline) was obtained for the congruent condition, but not for the incongruent condition. In Experiment 2, study sentences emphasized particular meaning aspects of nonambiguous targets. The word association task showed a higher proportion of target responses for targets studied in the more congruent sentence context than for targets studied in the less congruent sentence context. These results indicate that priming in word association depends largely on the storage of information relating the cue and target.

Descriptors of sensation confirm the multidimensional nature of desire to void.

Science.gov (United States)

Das, Rebekah; Buckley, Jonathan D; Williams, Marie T

2015-02-01

To collect and categorize descriptors of "desire to void" sensation, determine the reliability of descriptor categories and assess whether descriptor categories discriminate between people with and without symptoms of overactive bladder. This observational, repeated measures study involved 64 Australian volunteers (47 female), aged 50 years or more, with and without symptoms of overactive bladder. Descriptors of desire to void sensation were derived from a structured interview (conducted on two occasions, 1 week apart). Descriptors were recorded verbatim and categorized in a three-stage process. Overactive bladder status was determined by the Overactive Bladder Awareness Tool and the Overactive Bladder Symptom Score. McNemar's test assessed the reliability of descriptors volunteered between two occasions and Partial Least Squares Regression determined whether language categories discriminated according to overactive bladder status. Post hoc Chi squared analysis and relative risk calculation determined the size and direction of overactive bladder prediction. Thirteen language categories (Urgency, Fullness, Pressure, Tickle/tingle, Pain/ache, Heavy, Normal, Intense, Sudden, Annoying, Uncomfortable, Anxiety, and Unique somatic) encapsulated 344 descriptors of sensation. Descriptor categories were stable between two interviews. The categories "Urgency" and "Fullness" predicted overactive bladder status. Participants who volunteered "Urgency" descriptors were twice as likely to have overactive bladder and participants who volunteered "Fullness" descriptors were almost three times as likely not to have overactive bladder. The sensation of desire to void is reliably described over sessions separated by a week, the language used reflects multiple dimensions of sensation, and can predict overactive bladder status. © 2013 Wiley Periodicals, Inc.

Evaluating Color Descriptors for Object and Scene Recognition

NARCIS (Netherlands)

van de Sande, K.E.A.; Gevers, T.; Snoek, C.G.M.

2010-01-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been

RANZAR Body Systems Framework of diagnostic imaging examination descriptors

International Nuclear Information System (INIS)

Pitman, Alexander D.; Penlington, Lisa; Doromal, Darren; Vukolova, Natalia; Slater, Gregory

2014-01-01

A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were ‘greyed out’. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities.

RANZCR Body Systems Framework of diagnostic imaging examination descriptors.

Science.gov (United States)

Pitman, Alexander G; Penlington, Lisa; Doromal, Darren; Slater, Gregory; Vukolova, Natalia

2014-08-01

A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were 'greyed out'. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities. © 2014 The Royal Australian and New Zealand College of Radiologists.

Gabor Weber Local Descriptor for Bovine Iris Recognition

Directory of Open Access Journals (Sweden)

Shengnan Sun

2013-01-01

Full Text Available Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD. We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersection is adopted to measure the similarity between different GWLD histograms. The experimental results on the SEU bovine iris database verify the representation power of our proposed local descriptor.

A group of facial normal descriptors for recognizing 3D identical twins

KAUST Repository

Li, Huibin

2012-09-01

In this paper, to characterize and distinguish identical twins, three popular texture descriptors: i.e. local binary patterns (LBPs), gabor filters (GFs) and local gabor binary patterns (LGBPs) are employed to encode the normal components (x, y and z) of the 3D facial surfaces of identical twins respectively. A group of facial normal descriptors are thus achieved, including Normal Local Binary Patterns descriptor (N-LBPs), Normal Gabor Filters descriptor (N-GFs) and Normal Local Gabor Binary Patterns descriptor (N-LGBPs). All these normal encoding based descriptors are further fed into sparse representation classifier (SRC) for identification. Experimental results on the 3D TEC database demonstrate that these proposed normal encoding based descriptors are very discriminative and efficient, achieving comparable performance to the best of state-of-the-art algorithms. © 2012 IEEE.

Conceptual processing in music as revealed by N400 effects on words and musical targets.

Science.gov (United States)

Daltrozzo, Jérôme; Schön, Daniele

2009-10-01

The cognitive processing of concepts, that is, abstract general ideas, has been mostly studied with language. However, other domains, such as music, can also convey concepts. Koelsch et al. [Koelsch, S., Kasper, E., Sammler, D., Schulze, K., Gunter, T., & Friederici, A. D. Music, language and meaning: Brain signatures of semantic processing. Nature Neuroscience, 7, 302-307, 2004] showed that 10 sec of music can influence the semantic processing of words. However, the length of the musical excerpts did not allow the authors to study the effect of words on musical targets. In this study, we decided to replicate Koelsch et al. findings using 1-sec musical excerpts (Experiment 1). This allowed us to study the reverse influence, namely, of a linguistic context on conceptual processing of musical excerpts (Experiment 2). In both experiments, we recorded behavioral and electrophysiological responses while participants were presented 50 related and 50 unrelated pairs (context/target). Experiments 1 and 2 showed a larger N400 component of the event-related brain potentials to targets following a conceptually unrelated compared to a related context. The presence of an N400 effect with musical targets suggests that music may convey concepts. The relevance of these results for the comprehension of music as a structured set of conceptual units and for the domain specificity of the mechanisms underlying N400 effects are discussed.

Developing descriptors to predict mechanical properties of nanotubes.

Science.gov (United States)

Borders, Tammie L; Fonseca, Alexandre F; Zhang, Hengji; Cho, Kyeongjae; Rusinko, Andrew

2013-04-22

Descriptors and quantitative structure property relationships (QSPR) were investigated for mechanical property prediction of carbon nanotubes (CNTs). 78 molecular dynamics (MD) simulations were carried out, and 20 descriptors were calculated to build quantitative structure property relationships (QSPRs) for Young's modulus and Poisson's ratio in two separate analyses: vacancy only and vacancy plus methyl functionalization. In the first analysis, C(N2)/C(T) (number of non-sp2 hybridized carbons per the total carbons) and chiral angle were identified as critical descriptors for both Young's modulus and Poisson's ratio. Further analysis and literature findings indicate the effect of chiral angle is negligible at larger CNT radii for both properties. Raman spectroscopy can be used to measure C(N2)/C(T), providing a direct link between experimental and computational results. Poisson's ratio approaches two different limiting values as CNT radii increases: 0.23-0.25 for chiral and armchair CNTs and 0.10 for zigzag CNTs (surface defects <3%). In the second analysis, the critical descriptors were C(N2)/C(T), chiral angle, and M(N)/C(T) (number of methyl groups per total carbons). These results imply new types of defects can be represented as a new descriptor in QSPR models. Finally, results are qualified and quantified against experimental data.

Interference of spoken word recognition through phonological priming from visual objects and printed words

OpenAIRE

McQueen, J.; Huettig, F.

2014-01-01

Three cross-modal priming experiments examined the influence of pre-exposure to pictures and printed words on the speed of spoken word recognition. Targets for auditory lexical decision were spoken Dutch words and nonwords, presented in isolation (Experiments 1 and 2) or after a short phrase (Experiment 3). Auditory stimuli were preceded by primes which were pictures (Experiments 1 and 3) or those pictures’ printed names (Experiment 2). Prime-target pairs were phonologically onsetrelated (e.g...

RAID: a relation-augmented image descriptor

KAUST Repository

Guerrero, Paul; Mitra, Niloy J.; Wonka, Peter

2016-01-01

As humans, we regularly interpret scenes based on how objects are related, rather than based on the objects themselves. For example, we see a person riding an object X or a plank bridging two objects. Current methods provide limited support to search for content based on such relations. We present RAID, a relation-augmented image descriptor that supports queries based on inter-region relations. The key idea of our descriptor is to encode region-to-region relations as the spatial distribution of point-to-region relationships between two image regions. RAID allows sketch-based retrieval and requires minimal training data, thus making it suited even for querying uncommon relations. We evaluate the proposed descriptor by querying into large image databases and successfully extract nontrivial images demonstrating complex inter-region relations, which are easily missed or erroneously classified by existing methods. We assess the robustness of RAID on multiple datasets even when the region segmentation is computed automatically or very noisy.

RAID: a relation-augmented image descriptor

KAUST Repository

Guerrero, Paul

2016-07-11

As humans, we regularly interpret scenes based on how objects are related, rather than based on the objects themselves. For example, we see a person riding an object X or a plank bridging two objects. Current methods provide limited support to search for content based on such relations. We present RAID, a relation-augmented image descriptor that supports queries based on inter-region relations. The key idea of our descriptor is to encode region-to-region relations as the spatial distribution of point-to-region relationships between two image regions. RAID allows sketch-based retrieval and requires minimal training data, thus making it suited even for querying uncommon relations. We evaluate the proposed descriptor by querying into large image databases and successfully extract nontrivial images demonstrating complex inter-region relations, which are easily missed or erroneously classified by existing methods. We assess the robustness of RAID on multiple datasets even when the region segmentation is computed automatically or very noisy.

Character context: a shape descriptor for Arabic handwriting recognition

Science.gov (United States)

Mudhsh, Mohammed; Almodfer, Rolla; Duan, Pengfei; Xiong, Shengwu

2017-11-01

In the handwriting recognition field, designing good descriptors are substantial to obtain rich information of the data. However, the handwriting recognition research of a good descriptor is still an open issue due to unlimited variation in human handwriting. We introduce a "character context descriptor" that efficiently dealt with the structural characteristics of Arabic handwritten characters. First, the character image is smoothed and normalized, then the character context descriptor of 32 feature bins is built based on the proposed "distance function." Finally, a multilayer perceptron with regularization is used as a classifier. On experimentation with a handwritten Arabic characters database, the proposed method achieved a state-of-the-art performance with recognition rate equal to 98.93% and 99.06% for the 66 and 24 classes, respectively.

Three-Dimensional Model Retrieval Using Dynamic Multi-Descriptor Fusion

Institute of Scientific and Technical Information of China (English)

Jau-Ling Shi; Chang-Hsing Lee; Yao-Wen Hou; Po-Ting Yeh

2017-01-01

In this paper, we propose a dynamic multi-descriptor fusion (DMDF) approach to improving the retrieval accuracy of 3-dimensional (3D) model retrieval systems. First, an independent retrieval list is generated by using each individual descriptor. Second, we propose an automatic relevant/irrelevant models selection (ARMS) approach to selecting the relevant and irrelevant 3D models automatically without any user interaction. A weighted distance, in which the weight associated with each individual descriptor is learnt by using the selected relevant and irrelevant models, is used to measure the similarity between two 3D models. Furthermore, a descriptor-dependent adaptive query point movement (AQPM) approach is employed to update every feature vector. This set of new feature vectors is used to index 3D models in the next search process. Four 3D model databases are used to compare the retrieval accuracy of our proposed DMDF approach with several descriptors as well as some well-known information fusion methods. Experimental results have shown that our proposed DMDF approach provides a promising retrieval result and always yields the best retrieval accuracy.

[Representation of letter position in visual word recognition process].

Science.gov (United States)

Makioka, S

1994-08-01

Two experiments investigated the representation of letter position in visual word recognition process. In Experiment 1, subjects (12 undergraduates and graduates) were asked to detect a target word in a briefly-presented probe. Probes consisted of two kanji words. The latters which formed targets (critical letters) were always contained in probes. (e.g. target: [symbol: see text] probe: [symbol: see text]) High false alarm rate was observed when critical letters occupied the same within-word relative position (left or right within the word) in the probe words as in the target word. In Experiment 2 (subject were ten undergraduates and graduates), spaces adjacent to probe words were replaced by randomly chosen hiragana letters (e.g. [symbol: see text]), because spaces are not used to separate words in regular Japanese sentences. In addition to the effect of within-word relative position as in Experiment 1, the effect of between-word relative position (left or right across the probe words) was observed. These results suggest that information about within-word relative position of a letter is used in word recognition process. The effect of within-word relative position was explained by a connectionist model of word recognition.

Correspondence dictionary from free English term to INIS descriptors

International Nuclear Information System (INIS)

1991-12-01

This dictionary is intended for the on-line users of INIS database who select controlled terms (INIS descriptors) starting from free terms. The purpose of terminology control is (1) to reduce the ambiguity of the term use among different subject fields, and (2) to improve the recall by coordinating the synonyms. The controlled terms are collected in the thesaurus, but it is not always easy to find suitable descriptors. This dictionary has been compiled by analyzing existing records, and provides the specialists' know-how of converting free terms to descriptors. The 5,000 records in the physics field were selected, and analyzed by the physicists from the Department of Physics, Ibaraki University. Besides the compilation of this dictionary, the characteristics of the assigned descriptors were also clarified. (J.P.N.)

Shape descriptors for mode-shape recognition and model updating

International Nuclear Information System (INIS)

Wang, W; Mottershead, J E; Mares, C

2009-01-01

The most widely used method for comparing mode shapes from finite elements and experimental measurements is the Modal Assurance Criterion (MAC), which returns a single numerical value and carries no explicit information on shape features. New techniques, based on image processing (IP) and pattern recognition (PR) are described in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD), presented in this article, are the most popular shape descriptors having properties that include efficiency of expression, robustness to noise, invariance to geometric transformation and rotation, separation of local and global shape features and computational efficiency. The comparison of mode shapes is readily achieved by assembling the shape features of each mode shape into multi-dimensional shape feature vectors (SFVs) and determining the distances separating them.

Shaking Takete and Flowing Maluma. Non-Sense Words Are Associated with Motion Patterns.

Directory of Open Access Journals (Sweden)

Markus Koppensteiner

Full Text Available People assign the artificial words takete and kiki to spiky, angular figures and the artificial words maluma and bouba to rounded figures. We examined whether such a cross-modal correspondence could also be found for human body motion. We transferred the body movements of speakers onto two-dimensional coordinates and created animated stick-figures based on this data. Then we invited people to judge these stimuli using the words takete-maluma, bouba-kiki, and several verbal descriptors that served as measures of angularity/smoothness. In addition to this we extracted the quantity of motion, the velocity of motion and the average angle between motion vectors from the coordinate data. Judgments of takete (and kiki were related to verbal descriptors of angularity, a high quantity of motion, high velocity and sharper angles. Judgments of maluma (or bouba were related to smooth movements, a low velocity, a lower quantity of motion and blunter angles. A forced-choice experiment during which we presented subsets with low and high rankers on our motion measures revealed that people preferably assigned stimuli displaying fast movements with sharp angles in motion vectors to takete and stimuli displaying slow movements with blunter angles in motion vectors to maluma. Results indicated that body movements share features with information inherent in words such as takete and maluma and that people perceive the body movements of speakers on the level of changes in motion direction (e.g., body moves to the left and then back to the right. Follow-up studies are needed to clarify whether impressions of angularity and smoothness have similar communicative values across different modalities and how this affects social judgments and person perception.

Shaking Takete and Flowing Maluma. Non-Sense Words Are Associated with Motion Patterns.

Science.gov (United States)

Koppensteiner, Markus; Stephan, Pia; Jäschke, Johannes Paul Michael

2016-01-01

People assign the artificial words takete and kiki to spiky, angular figures and the artificial words maluma and bouba to rounded figures. We examined whether such a cross-modal correspondence could also be found for human body motion. We transferred the body movements of speakers onto two-dimensional coordinates and created animated stick-figures based on this data. Then we invited people to judge these stimuli using the words takete-maluma, bouba-kiki, and several verbal descriptors that served as measures of angularity/smoothness. In addition to this we extracted the quantity of motion, the velocity of motion and the average angle between motion vectors from the coordinate data. Judgments of takete (and kiki) were related to verbal descriptors of angularity, a high quantity of motion, high velocity and sharper angles. Judgments of maluma (or bouba) were related to smooth movements, a low velocity, a lower quantity of motion and blunter angles. A forced-choice experiment during which we presented subsets with low and high rankers on our motion measures revealed that people preferably assigned stimuli displaying fast movements with sharp angles in motion vectors to takete and stimuli displaying slow movements with blunter angles in motion vectors to maluma. Results indicated that body movements share features with information inherent in words such as takete and maluma and that people perceive the body movements of speakers on the level of changes in motion direction (e.g., body moves to the left and then back to the right). Follow-up studies are needed to clarify whether impressions of angularity and smoothness have similar communicative values across different modalities and how this affects social judgments and person perception.

8th Workshop on Coupled Descriptor Systems

CERN Document Server

Bartel, Andreas; Günther, Michael; Maten, E; Müller, Peter

2014-01-01

This book contains the proceedings of the 8th Workshop on Coupled Descriptor Systems held March 2013 in the Castle of Eringerfeld, Geseke in the neighborhood of Paderborn, Germany. It examines the wide range of current research topics in descriptor systems, including mathematical modeling, index analysis, wellposedness of problems, stiffness and different time-scales, cosimulation and splitting methods and convergence analysis. In addition, the book also presents applications from the automotive and circuit industries that show that descriptor systems provide challenging problems from the point of view of both theory and practice.   The book contains nine papers and is organized into three parts: control, simulation, and model order reduction. It will serve as an ideal resource for applied mathematicians and engineers, in particular those from mechanics and electromagnetics, who work with coupled differential equations.

Interference of spoken word recognition through phonological priming from visual objects and printed words

NARCIS (Netherlands)

McQueen, J.M.; Hüttig, F.

2014-01-01

Three cross-modal priming experiments examined the influence of preexposure to pictures and printed words on the speed of spoken word recognition. Targets for auditory lexical decision were spoken Dutch words and nonwords, presented in isolation (Experiments 1 and 2) or after a short phrase

Words and melody are intertwined in perception of sung words: EEG and behavioral evidence.

Directory of Open Access Journals (Sweden)

Reyna L Gordon

Full Text Available Language and music, two of the most unique human cognitive abilities, are combined in song, rendering it an ecological model for comparing speech and music cognition. The present study was designed to determine whether words and melodies in song are processed interactively or independently, and to examine the influence of attention on the processing of words and melodies in song. Event-Related brain Potentials (ERPs and behavioral data were recorded while non-musicians listened to pairs of sung words (prime and target presented in four experimental conditions: same word, same melody; same word, different melody; different word, same melody; different word, different melody. Participants were asked to attend to either the words or the melody, and to perform a same/different task. In both attentional tasks, different word targets elicited an N400 component, as predicted based on previous results. Most interestingly, different melodies (sung with the same word elicited an N400 component followed by a late positive component. Finally, ERP and behavioral data converged in showing interactions between the linguistic and melodic dimensions of sung words. The finding that the N400 effect, a well-established marker of semantic processing, was modulated by musical melody in song suggests that variations in musical features affect word processing in sung language. Implications of the interactions between words and melody are discussed in light of evidence for shared neural processing resources between the phonological/semantic aspects of language and the melodic/harmonic aspects of music.

Modular Chemical Descriptor Language (MCDL: Stereochemical modules

Directory of Open Access Journals (Sweden)

Gakh Andrei A

2011-01-01

Full Text Available Abstract Background In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures. Results In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDL processing module software packages. Conclusions Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format.

Local Descriptors of Dynamic and Nondynamic Correlation.

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Ramos-Cordoba, Eloy; Matito, Eduard

2017-06-13

Quantitatively accurate electronic structure calculations rely on the proper description of electron correlation. A judicious choice of the approximate quantum chemistry method depends upon the importance of dynamic and nondynamic correlation, which is usually assesed by scalar measures. Existing measures of electron correlation do not consider separately the regions of the Cartesian space where dynamic or nondynamic correlation are most important. We introduce real-space descriptors of dynamic and nondynamic electron correlation that admit orbital decomposition. Integration of the local descriptors yields global numbers that can be used to quantify dynamic and nondynamic correlation. Illustrative examples over different chemical systems with varying electron correlation regimes are used to demonstrate the capabilities of the local descriptors. Since the expressions only require orbitals and occupation numbers, they can be readily applied in the context of local correlation methods, hybrid methods, density matrix functional theory, and fractional-occupancy density functional theory.

Acoustic-phonetic cues to word boundary location: Evidence from word spotting

OpenAIRE

Dumay, Nicolas; Content, Alain; Frauenfelder, Ulrich Hans

1999-01-01

This research examined acoustic-phonetic cues to word boundary location in French consonant clusters, and assessed their use in on-line lexical segmentation. Two word-spotting experiments manipulated the alignment between word targets and syllable boundaries. A perceptual cost of such misalignment was observed for obstruent-liquid clusters but not for /s/ + obstruent clusters. For the former clusters, the analysis of a corpus of utterances showed systematic variations in segment durations as ...

Short local descriptors from 2D connected pattern spectra

NARCIS (Netherlands)

Bosilj, Petra; Kijak, Ewa; Wilkinson, Michael H. F.; Lefèvre, Sebastien

2015-01-01

We propose a local region descriptor based on connected pattern spectra, and combined with normalized central moments. The descriptors are calculated for MSER regions of the image, and their performance compared against SIFT. The MSER regions were chosen because they can be efficiently selected by

Word Translation Entropy

DEFF Research Database (Denmark)

Schaeffer, Moritz; Dragsted, Barbara; Hvelplund, Kristian Tangsgaard

This study reports on an investigation into the relationship between the number of translation alternatives for a single word and eye movements on the source text. In addition, the effect of word order differences between source and target text on eye movements on the source text is studied. In p...

Cooperative Control for Multiple Autonomous Vehicles Using Descriptor Functions

Directory of Open Access Journals (Sweden)

Marta Niccolini

2014-01-01

Full Text Available The paper presents a novel methodology for the control management of a swarm of autonomous vehicles. The vehicles, or agents, may have different skills, and be employed for different missions. The methodology is based on the definition of descriptor functions that model the capabilities of the single agent and each task or mission. The swarm motion is controlled by minimizing a suitable norm of the error between agents’ descriptor functions and other descriptor functions which models the entire mission. The validity of the proposed technique is tested via numerical simulation, using different task assignment scenarios.

Object classfication from RGB-D images using depth context kernel descriptors

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2015-01-01

Context cue is important in object classification. By embedding the depth context cue of image attributes into kernel descriptors, we propose a new set of depth image descriptors called depth context kernel descriptors (DCKD) for RGB-D based object classification. The motivation of DCKD is to use...... the depth consistency of image attributes defined within a neighboring region to improve the robustness of descriptor matching in the kernel space. Moreover, a novel joint spatial-depth pooling (JSDP) scheme, which further partitions image sub-regions using the depth cue and pools features in both 2D image...

Lagrangian descriptors in dissipative systems.

Science.gov (United States)

Junginger, Andrej; Hernandez, Rigoberto

2016-11-09

The reaction dynamics of time-dependent systems can be resolved through a recrossing-free dividing surface associated with the transition state trajectory-that is, the unique trajectory which is bound to the barrier region for all time in response to a given time-dependent potential. A general procedure based on the minimization of Lagrangian descriptors has recently been developed by Craven and Hernandez [Phys. Rev. Lett., 2015, 115, 148301] to construct this particular trajectory without requiring perturbative expansions relative to the naive transition state point at the top of the barrier. The extension of the method to account for dissipation in the equations of motion requires additional considerations established in this paper because the calculation of the Lagrangian descriptor involves the integration of trajectories in forward and backward time. The two contributions are in general very different because the friction term can act as a source (in backward time) or sink (in forward time) of energy, leading to the possibility that information about the phase space structure may be lost due to the dominance of only one of the terms. To compensate for this effect, we introduce a weighting scheme within the Lagrangian descriptor and demonstrate that for thermal Langevin dynamics it preserves the essential phase space structures, while they are lost in the nonweighted case.

Gun bore flaw image matching based on improved SIFT descriptor

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Zeng, Luan; Xiong, Wei; Zhai, You

2013-01-01

In order to increase the operation speed and matching ability of SIFT algorithm, the SIFT descriptor and matching strategy are improved. First, a method of constructing feature descriptor based on sector area is proposed. By computing the gradients histogram of location bins which are parted into 6 sector areas, a descriptor with 48 dimensions is constituted. It can reduce the dimension of feature vector and decrease the complexity of structuring descriptor. Second, it introduce a strategy that partitions the circular region into 6 identical sector areas starting from the dominate orientation. Consequently, the computational complexity is reduced due to cancellation of rotation operation for the area. The experimental results indicate that comparing with the OpenCV SIFT arithmetic, the average matching speed of the new method increase by about 55.86%. The matching veracity can be increased even under some variation of view point, illumination, rotation, scale and out of focus. The new method got satisfied results in gun bore flaw image matching. Keywords: Metrology, Flaw image matching, Gun bore, Feature descriptor

Sparse B-spline polynomial descriptors for human activity recognition

NARCIS (Netherlands)

Oikonomopoulos, Antonios; Pantic, Maja; Patras, Ioannis

2009-01-01

The extraction and quantization of local image and video descriptors for the subsequent creation of visual codebooks is a technique that has proved very effective for image and video retrieval applications. In this paper we build on this concept and propose a new set of visual descriptors that

Color Independent Components Based SIFT Descriptors for Object/Scene Classification

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Ai, Dan-Ni; Han, Xian-Hua; Ruan, Xiang; Chen, Yen-Wei

In this paper, we present a novel color independent components based SIFT descriptor (termed CIC-SIFT) for object/scene classification. We first learn an efficient color transformation matrix based on independent component analysis (ICA), which is adaptive to each category in a database. The ICA-based color transformation can enhance contrast between the objects and the background in an image. Then we compute CIC-SIFT descriptors over all three transformed color independent components. Since the ICA-based color transformation can boost the objects and suppress the background, the proposed CIC-SIFT can extract more effective and discriminative local features for object/scene classification. The comparison is performed among seven SIFT descriptors, and the experimental classification results show that our proposed CIC-SIFT is superior to other conventional SIFT descriptors.

The role of verbal memory in regressions during reading is modulated by the target word's recency in memory.

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Guérard, Katherine; Saint-Aubin, Jean; Maltais, Marilyne; Lavoie, Hugo

2014-10-01

During reading, a number of eye movements are made backward, on words that have already been read. Recent evidence suggests that such eye movements, called regressions, are guided by memory. Several studies point to the role of spatial memory, but evidence for the role of verbal memory is more limited. In the present study, we examined the factors that modulate the role of verbal memory in regressions. Participants were required to make regressions on target words located in sentences displayed on one or two lines. Verbal interference was shown to affect regressions, but only when participants executed a regression on a word located in the first part of the sentence, irrespective of the number of lines on which the sentence was displayed. Experiments 2 and 3 showed that the effect of verbal interference on words located in the first part of the sentence disappeared when participants initiated the regression from the middle of the sentence. Our results suggest that verbal memory is recruited to guide regressions, but only for words read a longer time ago.

Local intensity area descriptor for facial recognition in ideal and noise conditions

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Tran, Chi-Kien; Tseng, Chin-Dar; Chao, Pei-Ju; Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Lee, Tsair-Fwu

2017-03-01

We propose a local texture descriptor, local intensity area descriptor (LIAD), which is applied for human facial recognition in ideal and noisy conditions. Each facial image is divided into small regions from which LIAD histograms are extracted and concatenated into a single feature vector to represent the facial image. The recognition is performed using a nearest neighbor classifier with histogram intersection and chi-square statistics as dissimilarity measures. Experiments were conducted with LIAD using the ORL database of faces (Olivetti Research Laboratory, Cambridge), the Face94 face database, the Georgia Tech face database, and the FERET database. The results demonstrated the improvement in accuracy of our proposed descriptor compared to conventional descriptors [local binary pattern (LBP), uniform LBP, local ternary pattern, histogram of oriented gradients, and local directional pattern]. Moreover, the proposed descriptor was less sensitive to noise and had low histogram dimensionality. Thus, it is expected to be a powerful texture descriptor that can be used for various computer vision problems.

Modeling multiple visual words assignment for bag-of-features based medical image retrieval

KAUST Repository

Wang, Jim Jing-Yan

2012-01-01

In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments\\' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

Modeling multiple visual words assignment for bag-of-features based medical image retrieval

KAUST Repository

Wang, Jim Jing-Yan; Almasri, Islam

2012-01-01

In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

Interference of spoken word recognition through phonological priming from visual objects and printed words.

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McQueen, James M; Huettig, Falk

2014-01-01

Three cross-modal priming experiments examined the influence of preexposure to pictures and printed words on the speed of spoken word recognition. Targets for auditory lexical decision were spoken Dutch words and nonwords, presented in isolation (Experiments 1 and 2) or after a short phrase (Experiment 3). Auditory stimuli were preceded by primes, which were pictures (Experiments 1 and 3) or those pictures' printed names (Experiment 2). Prime-target pairs were phonologically onset related (e.g., pijl-pijn, arrow-pain), were from the same semantic category (e.g., pijl-zwaard, arrow-sword), or were unrelated on both dimensions. Phonological interference and semantic facilitation were observed in all experiments. Priming magnitude was similar for pictures and printed words and did not vary with picture viewing time or number of pictures in the display (either one or four). These effects arose even though participants were not explicitly instructed to name the pictures and where strategic naming would interfere with lexical decision making. This suggests that, by default, processing of related pictures and printed words influences how quickly we recognize spoken words.

Evidence for simultaneous syntactic processing of multiple words during reading.

Directory of Open Access Journals (Sweden)

Joshua Snell

Full Text Available A hotly debated issue in reading research concerns the extent to which readers process parafoveal words, and how parafoveal information might influence foveal word recognition. We investigated syntactic word processing both in sentence reading and in reading isolated foveal words when these were flanked by parafoveal words. In Experiment 1 we found a syntactic parafoveal preview benefit in sentence reading, meaning that fixation durations on target words were decreased when there was a syntactically congruent preview word at the target location (n during the fixation on the pre-target (n-1. In Experiment 2 we used a flanker paradigm in which participants had to classify foveal target words as either noun or verb, when those targets were flanked by syntactically congruent or incongruent words (stimulus on-time 170 ms. Lower response times and error rates in the congruent condition suggested that higher-order (syntactic information can be integrated across foveal and parafoveal words. Although higher-order parafoveal-on-foveal effects have been elusive in sentence reading, results from our flanker paradigm show that the reading system can extract higher-order information from multiple words in a single glance. We propose a model of reading to account for the present findings.

Impact of low alcohol verbal descriptors on perceived strength: An experimental study.

Science.gov (United States)

Vasiljevic, Milica; Couturier, Dominique-Laurent; Marteau, Theresa M

2018-02-01

Low alcohol labels are a set of labels that carry descriptors such as 'low' or 'lighter' to denote alcohol content in beverages. There is growing interest from policymakers and producers in lower strength alcohol products. However, there is a lack of evidence on how the general population perceives verbal descriptors of strength. The present research examines consumers' perceptions of strength (% ABV) and appeal of alcohol products using low or high alcohol verbal descriptors. A within-subjects experimental study in which participants rated the strength and appeal of 18 terms denoting low (nine terms), high (eight terms) and regular (one term) strengths for either (1) wine or (2) beer according to drinking preference. Thousand six hundred adults (796 wine and 804 beer drinkers) sampled from a nationally representative UK panel. Low, Lower, Light, Lighter, and Reduced formed a cluster and were rated as denoting lower strength products than Regular, but higher strength than the cluster with intensifiers consisting of Extra Low, Super Low, Extra Light, and Super Light. Similar clustering in perceived strength was observed amongst the high verbal descriptors. Regular was the most appealing strength descriptor, with the low and high verbal descriptors using intensifiers rated least appealing. The perceived strength and appeal of alcohol products diminished the more the verbal descriptors implied a deviation from Regular. The implications of these findings are discussed in terms of policy implications for lower strength alcohol labelling and associated public health outcomes. Statement of contribution What is already known about this subject? Current UK and EU legislation limits the number of low strength verbal descriptors and the associated alcohol by volume (ABV) to 1.2% ABV and lower. There is growing interest from policymakers and producers to extend the range of lower strength alcohol products above the current cap of 1.2% ABV set out in national legislation. There

Functional Constructivism: In Search of Formal Descriptors.

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Trofimova, Irina

2017-10-01

The Functional Constructivism (FC) paradigm is an alternative to behaviorism and considers behavior as being generated every time anew, based on an individual's capacities, environmental resources and demands. Walter Freeman's work provided us with evidence supporting the FC principles. In this paper we make parallels between gradual construction processes leading to the formation of individual behavior and habits, and evolutionary processes leading to the establishment of biological systems. Referencing evolutionary theory, several formal descriptors of such processes are proposed. These FC descriptors refer to the most universal aspects for constructing consistent structures: expansion of degrees of freedom, integration processes based on internal and external compatibility between systems and maintenance processes, all given in four different classes of systems: (a) Zone of Proximate Development (poorly defined) systems; (b) peer systems with emerging reproduction of multiple siblings; (c) systems with internalized integration of behavioral elements ('cruise controls'); and (d) systems capable of handling low-probability, not yet present events. The recursive dynamics within this set of descriptors acting on (traditional) downward, upward and horizontal directions of evolution, is conceptualized as diagonal evolution, or di-evolution. Two examples applying these FC descriptors to taxonomy are given: classification of the functionality of neuro-transmitters and temperament traits; classification of mental disorders. The paper is an early step towards finding a formal language describing universal tendencies in highly diverse, complex and multi-level transient systems known in ecology and biology as 'contingency cycles.'

Gabor Weber Local Descriptor for Bovine Iris Recognition

OpenAIRE

Sun, Shengnan; Zhao, Lindu; Yang, Shicai

2013-01-01

Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD). We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersectio...

A 3D model retrieval approach based on Bayesian networks lightfield descriptor

Science.gov (United States)

Xiao, Qinhan; Li, Yanjun

2009-12-01

A new 3D model retrieval methodology is proposed by exploiting a novel Bayesian networks lightfield descriptor (BNLD). There are two key novelties in our approach: (1) a BN-based method for building lightfield descriptor; and (2) a 3D model retrieval scheme based on the proposed BNLD. To overcome the disadvantages of the existing 3D model retrieval methods, we explore BN for building a new lightfield descriptor. Firstly, 3D model is put into lightfield, about 300 binary-views can be obtained along a sphere, then Fourier descriptors and Zernike moments descriptors can be calculated out from binaryviews. Then shape feature sequence would be learned into a BN model based on BN learning algorithm; Secondly, we propose a new 3D model retrieval method by calculating Kullback-Leibler Divergence (KLD) between BNLDs. Beneficial from the statistical learning, our BNLD is noise robustness as compared to the existing methods. The comparison between our method and the lightfield descriptor-based approach is conducted to demonstrate the effectiveness of our proposed methodology.

Complex Correlation Measure: a novel descriptor for Poincaré plot

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Gubbi Jayavardhana

2009-08-01

Full Text Available Abstract Background Poincaré plot is one of the important techniques used for visually representing the heart rate variability. It is valuable due to its ability to display nonlinear aspects of the data sequence. However, the problem lies in capturing temporal information of the plot quantitatively. The standard descriptors used in quantifying the Poincaré plot (SD1, SD2 measure the gross variability of the time series data. Determination of advanced methods for capturing temporal properties pose a significant challenge. In this paper, we propose a novel descriptor "Complex Correlation Measure (CCM" to quantify the temporal aspect of the Poincaré plot. In contrast to SD1 and SD2, the CCM incorporates point-to-point variation of the signal. Methods First, we have derived expressions for CCM. Then the sensitivity of descriptors has been shown by measuring all descriptors before and after surrogation of the signal. For each case study, lag-1 Poincaré plots were constructed for three groups of subjects (Arrhythmia, Congestive Heart Failure (CHF and those with Normal Sinus Rhythm (NSR, and the new measure CCM was computed along with SD1 and SD2. ANOVA analysis distribution was used to define the level of significance of mean and variance of SD1, SD2 and CCM for different groups of subjects. Results CCM is defined based on the autocorrelation at different lags of the time series, hence giving an in depth measurement of the correlation structure of the Poincaré plot. A surrogate analysis was performed, and the sensitivity of the proposed descriptor was found to be higher as compared to the standard descriptors. Two case studies were conducted for recognizing arrhythmia and congestive heart failure (CHF subjects from those with NSR, using the Physionet database and demonstrated the usefulness of the proposed descriptors in biomedical applications. CCM was found to be a more significant (p = 6.28E-18 parameter than SD1 and SD2 in discriminating

Auditory phonological priming in children and adults during word repetition

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Cleary, Miranda; Schwartz, Richard G.

2004-05-01

Short-term auditory phonological priming effects involve changes in the speed with which words are processed by a listener as a function of recent exposure to other similar-sounding words. Activation of phonological/lexical representations appears to persist beyond the immediate offset of a word, influencing subsequent processing. Priming effects are commonly cited as demonstrating concurrent activation of word/phonological candidates during word identification. Phonological priming is controversial, the direction of effects (facilitating versus slowing) varying with the prime-target relationship. In adults, it has repeatedly been demonstrated, however, that hearing a prime word that rhymes with the following target word (ISI=50 ms) decreases the time necessary to initiate repetition of the target, relative to when the prime and target have no phonemic overlap. Activation of phonological representations in children has not typically been studied using this paradigm, auditory-word + picture-naming tasks being used instead. The present study employed an auditory phonological priming paradigm being developed for use with normal-hearing and hearing-impaired children. Initial results from normal-hearing adults replicate previous reports of faster naming times for targets following a rhyming prime word than for targets following a prime having no phonemes in common. Results from normal-hearing children will also be reported. [Work supported by NIH-NIDCD T32DC000039.

Improved nucleic acid descriptors for siRNA efficacy prediction.

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Sciabola, Simone; Cao, Qing; Orozco, Modesto; Faustino, Ignacio; Stanton, Robert V

2013-02-01

Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies.

Novel topological descriptors for analyzing biological networks

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Varmuza Kurt K

2010-06-01

Full Text Available Abstract Background Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g., atom- and bond-types when considering molecular graphs. Indeed, this feature is important to characterize biological networks more meaningfully instead of only considering pure topological information. Results In this paper, we put the emphasis on analyzing a special type of biological networks, namely bio-chemical structures. First, we derive entropic measures to calculate the information content of vertex- and edge-labeled graphs and investigate some useful properties thereof. Second, we apply the mentioned measures combined with other well-known descriptors to supervised machine learning methods for predicting Ames mutagenicity. Moreover, we investigate the influence of our topological descriptors - measures for only unlabeled vs. measures for labeled graphs - on the prediction performance of the underlying graph classification problem. Conclusions Our study demonstrates that the application of entropic measures to molecules representing graphs is useful to characterize such structures meaningfully. For instance, we have found that if one extends the measures for determining the structural information content of unlabeled graphs to labeled graphs, the uniqueness of the resulting indices is higher. Because measures to structurally characterize labeled graphs are clearly underrepresented so far, the further development of such methods might be valuable and fruitful for solving problems within biological network analysis.

Elevating Baseline Activation Does Not Facilitate Reading of Unattended Words

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Lien, Mei-Ching; Kouchi, Scott; Ruthruff, Eric; Lachter, Joel B.

2009-01-01

Previous studies have disagreed the extent to which people extract meaning from words presented outside the focus of spatial attention. The present study, examined a possible explanation for such discrepancies, inspired by attenuation theory: unattended words can be read more automatically when they have a high baseline level of activation (e.g., due to frequent repetition or due to being expected in a given context). We presented a brief prime word in lowercase, followed by a target word in uppercase. Participants indicated whether the target word belonged to a particular category (e.g., "sport"). When we drew attention to the prime word using a visual cue, the prime produced substantial priming effects on target responses (i.e., faster responses when the prime and target words were identical or from the same category than when they belonged to different categories). When prime words were not attended, however, they produced no priming effects. This finding replicated even when there were only 4 words, each repeated 160 times during the experiment. Even with a very high baseline level of activation, it appears that very little word processing is possible without spatial attention.

Ligand Electron Density Shape Recognition Using 3D Zernike Descriptors

Science.gov (United States)

Gunasekaran, Prasad; Grandison, Scott; Cowtan, Kevin; Mak, Lora; Lawson, David M.; Morris, Richard J.

We present a novel approach to crystallographic ligand density interpretation based on Zernike shape descriptors. Electron density for a bound ligand is expanded in an orthogonal polynomial series (3D Zernike polynomials) and the coefficients from this expansion are employed to construct rotation-invariant descriptors. These descriptors can be compared highly efficiently against large databases of descriptors computed from other molecules. In this manuscript we describe this process and show initial results from an electron density interpretation study on a dataset containing over a hundred OMIT maps. We could identify the correct ligand as the first hit in about 30 % of the cases, within the top five in a further 30 % of the cases, and giving rise to an 80 % probability of getting the correct ligand within the top ten matches. In all but a few examples, the top hit was highly similar to the correct ligand in both shape and chemistry. Further extensions and intrinsic limitations of the method are discussed.

Improving scale invariant feature transform-based descriptors with shape-color alliance robust feature

Science.gov (United States)

Wang, Rui; Zhu, Zhengdan; Zhang, Liang

2015-05-01

Constructing appropriate descriptors for interest points in image matching is a critical aspect task in computer vision and pattern recognition. A method as an extension of the scale invariant feature transform (SIFT) descriptor called shape-color alliance robust feature (SCARF) descriptor is presented. To address the problem that SIFT is designed mainly for gray images and lack of global information for feature points, the proposed approach improves the SIFT descriptor by means of a concentric-rings model, as well as integrating the color invariant space and shape context with SIFT to construct the SCARF descriptor. The SCARF method developed is more robust than the conventional SIFT with respect to not only the color and photometrical variations but also the measuring similarity as a global variation between two shapes. A comparative evaluation of different descriptors is carried out showing that the SCARF approach provides better results than the other four state-of-the-art related methods.

Deep-Learning-Based Drug-Target Interaction Prediction.

Science.gov (United States)

Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei

2017-04-07

Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

The Evaluation of Angiotensin-Converting Enzyme Inhibitors in Renal Elimination with Selected Molecular Descriptors

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Trbojevic Jovana

2017-06-01

Full Text Available Angiotensin-converting enzyme (ACE inhibitors modulate the function of the renin-angiotensin-aldosterone system, and they are commonly prescribed antihypertensive drugs especially in patients with renal failure. In this study, the relationships between several molecular properties of eight ACE inhibitors (enalapril, quinapril, fosinopril, ramipril, benazepril, perindopril, moexipril, trandolapril and their renal elimination data, from relevant literature, were investigated. The ’molecular descriptors of the ACE inhibitors, which included aqueous solubility data (logS; an electronic descriptor, polar surface area (PSA;, a constitutional parameter, molecular mass (Mr; and a geometric descriptor, volume value (Vol, as well as lipophilicity descriptors (logP values, were calculated using different software packages. Simple linear regression analysis showed the best correlation between renal elimination data and lipophilicity descriptor AClogP values (R2 = 0.5742. In the next stage of the study, multiple linear regression was applied to assess a higher correlation between the ACE inhibitors’ renal elimination data and lipophilicity, AClogP, with one additional descriptor as an independent variable. Good correlations were established between renal elimination data from the literature and the AClogP lipophilicity descriptor using the constitutional parameter (molecular mass (R2 = 0.7425 or the geometric descriptor (volume value (R2 = 0.7224 as an independent variable. The application of computed molecular descriptors in evaluating drug elimination is of great importance in drug research.

NOTE - Characterization of genetic variability among common bean genotypes by morphological descriptors

Directory of Open Access Journals (Sweden)

Marilene Santos de Lima

2012-01-01

Full Text Available The purpose of this study was to characterize the genetic variability in 100 genotypes of the Active Germplasm Bank of common bean of the Federal University of Viçosa, by morphological descriptors, classify them in groups of genetic similarity and to identify the degree of relevance of descriptors of genetic divergence. The genotypes were evaluated based on 22 quantitative and qualitative morphological descriptors. The highyielding genotypes V 7936, Gold Gate, LM 95103904, 1829 S 349 Venezuela, and PF 9029975, CNFC 9454 andFe 732015, with upright growth, have potential for use as parents in common bean breeding programs. By genetic divergence analysis, the genotypes were clustered in eight groups of genetic dissimilarity. By methods of principal components, 9 of the 22 descriptors were eliminated, for being redundant or little variable, suggesting that 10-20 morphological descriptors can be used in studies of characterization of genetic variation.

Simple idea to generate fragment and pharmacophore descriptors and their implications in chemical informatics.

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Catana, Cornel

2009-03-01

Using a well-defined set of fragments/pharmacophores, a new methodology to calculate fragment/ pharmacophore descriptors for any molecule onto which at least one fragment/pharmacophore can be mapped is presented. To each fragment/pharmacophore present in a molecule, we attach a descriptor that is calculated by identifying the molecule's atoms onto which it maps and summing over its constituent atomic descriptors. The attached descriptors are named C-fragment/pharmacophore descriptors, and this methodology can be applied to any descriptors defined at the atomic level, such as the partition coefficient, molar refractivity, electrotopological state, etc. By using this methodology, the same fragment/pharmacophore can be shown to have different values in different molecules resulting in better discrimination power. As we know, fragment and pharmacophore fingerprints have a lot of applications in chemical informatics. This study has attempted to find the impact of replacing the traditional value of "1" in a fingerprint with real numbers derived form C-fragment/pharmacophore descriptors. One way to do this is to assess the utility of C-fragment/ pharmacophore descriptors in modeling different end points. Here, we exemplify with data from CYP and hERG. The fact that, in many cases, the obtained models were fairly successful and C-fragment descriptors were ranked among the top ones supports the idea that they play an important role in correlation. When we modeled hERG with C-pharmacophore descriptors, however, the model performances decreased slightly, and we attribute this, mainly to the fact that there is no technique capable of handling multiple instances (states). We hope this will open new research, especially in the emerging field of machine learning. Further research is needed to see the impact of C-fragment/pharmacophore descriptors in similarity/dissimilarity applications.

New polynomial-based molecular descriptors with low degeneracy.

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Matthias Dehmer

Full Text Available In this paper, we introduce a novel graph polynomial called the 'information polynomial' of a graph. This graph polynomial can be derived by using a probability distribution of the vertex set. By using the zeros of the obtained polynomial, we additionally define some novel spectral descriptors. Compared with those based on computing the ordinary characteristic polynomial of a graph, we perform a numerical study using real chemical databases. We obtain that the novel descriptors do have a high discrimination power.

The retrieval efficiency test of descriptors and free vocabulary terms in INIS on-line search

International Nuclear Information System (INIS)

Ebinuma, Yukio; Takahashi, Satoko

1981-01-01

The test was done for 1) search topics with appropriate descriptors, 2) search topics with considerably broader descriptors, 3) search topics with no appropriate descriptors. As to (1) and (2) the retrieval efficiency was the same both on descriptor system and on keyword system (descriptors + free terms), and the search formulas were easily constructed. As to (3) the descriptor system ensured the recall ratio but decreased the precision ratio. On the other hand the keyword system made the construction of search formulas easy and resulted in good retrieval efficiency. The search system which is available both for full match method of descriptors and truncation method of keywords is desirable because each method can be selected according to the searcher's strategy and search topics. Free-term system seems unnecessary. (author)

The effects of variant descriptors on the potential effectiveness of plain packaging.

Science.gov (United States)

Borland, Ron; Savvas, Steven

2014-01-01

To examine the effects that variant descriptor labels on cigarette packs have on smokers' perceptions of those packs and the cigarettes contained within. As part of two larger web-based studies (each involved 160 young adult ever-smokers 18-29 years old), respondents were shown a computer image of a plain cigarette pack and sets of related variant descriptors. The sets included terms that varied in terms of descriptors of colours as names, flavour strength, degrees of filter venting, filter types, quality, type of cigarette and numbers. For each set, respondents rated the highest and lowest of two or three of the following four characteristics: quality, strongest or weakest in taste, delivers most or least tar/nicotine, and most or least level of harm. There were significant differences on all four ratings. Quality ratings were the least differentiated. Except for colour descriptors, where 'Gold' rated high in quality but medium in other ratings, ratings of quality, harm, strength and delivery were all positively associated when rated on the same descriptors. Descriptor labels on cigarette packs, can affect smokers' perceptions of the characteristics of the cigarettes contained within. Therefore, they are a potential means by which product differentiation can occur. In particular, having variants differing in perceived strength while not differing in deliveries of harmful ingredients is particularly problematic. Any packaging policy should take into account the possibility that variant descriptors can mislead smokers into making inappropriate product attributions.

Utterance-final position and pitch marking aid word learning in school-age children.

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Filippi, Piera; Laaha, Sabine; Fitch, W Tecumseh

2017-08-01

We investigated the effects of word order and prosody on word learning in school-age children. Third graders viewed photographs belonging to one of three semantic categories while hearing four-word nonsense utterances containing a target word. In the control condition, all words had the same pitch and, across trials, the position of the target word was varied systematically within each utterance. The only cue to word-meaning mapping was the co-occurrence of target words and referents. This cue was present in all conditions. In the Utterance-final condition, the target word always occurred in utterance-final position, and at the same fundamental frequency as all the other words of the utterance. In the Pitch peak condition, the position of the target word was varied systematically within each utterance across trials, and produced with pitch contrasts typical of infant-directed speech (IDS). In the Pitch peak + Utterance-final condition, the target word always occurred in utterance-final position, and was marked with a pitch contrast typical of IDS. Word learning occurred in all conditions except the control condition. Moreover, learning performance was significantly higher than that observed with simple co-occurrence ( control condition) only for the Pitch peak + Utterance-final condition. We conclude that, for school-age children, the combination of words' utterance-final alignment and pitch enhancement boosts word learning.

Presentation of words to separate hemispheres prevents interword illusory conjunctions.

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Liederman, J; Sohn, Y S

1999-03-01

We tested the hypothesis that division of inputs between the hemispheres could prevent interword letter migrations in the form of illusory conjunctions. The task was to decide whether a centrally-presented consonant-vowel-consonant (CVC) target word matched one of four CVC words presented to a single hemisphere or divided between the hemispheres in a subsequent test display. During half of the target-absent trials, known as conjunction trials, letters from two separate words (e.g., "tag" and "cop") in the test display could be mistaken for a target word (e.g., "top"). For the other half of the target-absent trails, the test display did not match any target consonants (Experiment 1, N = 16) or it matched one target consonant (Experiment 2, N = 29), the latter constituting true "feature" trials. Bi- as compared to unihemispheric presentation significantly reduced the number of conjunction, but not feature, errors. Illusory conjunctions did not occur when the words were presented to separate hemispheres.

On the Alignment of Shapes Represented by Fourier Descriptors

DEFF Research Database (Denmark)

Sjöstrand, Karl; Ericsson, Anders; Larsen, Rasmus

2006-01-01

The representation of shapes by Fourier descriptors is a time-honored technique that has received relatively little attention lately. Nevertheless, it has many benefits and is applicable for describing a range of medical structures in two dimensions. Delineations in medical applications often...... consist of continuous outlines of structures, where no information of correspondence between samples exist. In this article, we discuss an alignment method that works directly with the functional representation of Fourier descriptors, and that is optimal in a least-squares sense. With corresponding...... represented by common landmarks can be constructed in an automatic fashion. If the aligned Fourier descriptors are inverse transformed from the frequency domain to the spatial domain, a set of roughly aligned landmarks are obtained. The positions of these are then adjusted along the contour of the objects...

Improving scale invariant feature transform with local color contrastive descriptor for image classification

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Guo, Sheng; Huang, Weilin; Qiao, Yu

2017-01-01

Image representation and classification are two fundamental tasks toward version understanding. Shape and texture provide two key features for visual representation and have been widely exploited in a number of successful local descriptors, e.g., scale invariant feature transform (SIFT), local binary pattern descriptor, and histogram of oriented gradient. Unlike these gradient-based descriptors, this paper presents a simple yet efficient local descriptor, named local color contrastive descriptor (LCCD), which captures the contrastive aspects among local regions or color channels for image representation. LCCD is partly inspired by the neural science facts that color contrast plays important roles in visual perception and there exist strong linkages between color and shape. We leverage f-divergence as a robust measure to estimate the contrastive features between different spatial locations and multiple channels. Our descriptor enriches local image representation with both color and contrast information. Due to that LCCD does not explore any gradient information, individual LCCD does not yield strong performance. But we verified experimentally that LCCD can compensate strongly SIFT. Extensive experimental results on image classification show that our descriptor improves the performance of SIFT substantially by combination on three challenging benchmarks, including MIT Indoor-67 database, SUN397, and PASCAL VOC 2007.

Stereo matching based on SIFT descriptor with illumination and camera invariance

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Niu, Haitao; Zhao, Xunjie; Li, Chengjin; Peng, Xiang

2010-10-01

Stereo matching is the process of finding corresponding points in two or more images. The description of interest points is a critical aspect of point correspondence which is vital in stereo matching. SIFT descriptor has been proven to be better on the distinctiveness and robustness than other local descriptors. However, SIFT descriptor does not involve color information of feature point which provides powerfully distinguishable feature in matching tasks. Furthermore, in a real scene, image color are affected by various geometric and radiometric factors,such as gamma correction and exposure. These situations are very common in stereo images. For this reason, the color recorded by a camera is not a reliable cue, and the color consistency assumption is no longer valid between stereo images in real scenes. Hence the performance of other SIFT-based stereo matching algorithms can be severely degraded under the radiometric variations. In this paper, we present a new improved SIFT stereo matching algorithms that is invariant to various radiometric variations between left and right images. Unlike other improved SIFT stereo matching algorithms, we explicitly employ the color formation model with the parameters of lighting geometry, illuminant color and camera gamma in SIFT descriptor. Firstly, we transform the input color images to log-chromaticity color space, thus a linear relationship can be established. Then, we use a log-polar histogram to build three color invariance components for SIFT descriptor. So that our improved SIFT descriptor is invariant to lighting geometry, illuminant color and camera gamma changes between left and right images. Then we can match feature points between two images and use SIFT descriptor Euclidean distance as a geometric measure in our data sets to make it further accurate and robust. Experimental results show that our method is superior to other SIFT-based algorithms including conventional stereo matching algorithms under various

A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification

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Huai Yu

2016-03-01

Full Text Available Scene classification plays an important role in understanding high-resolution satellite (HRS remotely sensed imagery. For remotely sensed scenes, both color information and texture information provide the discriminative ability in classification tasks. In recent years, substantial performance gains in HRS image classification have been reported in the literature. One branch of research combines multiple complementary features based on various aspects such as texture, color and structure. Two methods are commonly used to combine these features: early fusion and late fusion. In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode color, texture and structure features using a hierarchical structure-Color Binary Partition Tree (CBPT, which we call the CTS descriptor. Specifically, we first build the hierarchical representation of HRS imagery using the CBPT. Then we quantize the texture and color features of dense regions. Next, we analyze and extract the co-occurrence patterns of regions based on the hierarchical structure. Finally, we encode local descriptors to obtain the final CTS descriptor and test its discriminative capability using object categorization and scene classification with HRS images. The proposed descriptor contains the spectral, textural and structural information of the HRS imagery and is also robust to changes in illuminant color, scale, orientation and contrast. The experimental results demonstrate that the proposed CTS descriptor achieves competitive classification results compared with state-of-the-art algorithms.

Image feature detectors and descriptors foundations and applications

CERN Document Server

Hassaballah, Mahmoud

2016-01-01

This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition. .

Early attentional bias for negative words when competition is induced.

Science.gov (United States)

Ho, Ming-Chou; Li, Shuo-Heng; Yeh, Su-Ling

2016-05-01

Previous research (Zeelenberg, Wagenmakers, & Rotteveel, 2006) revealed that emotionally meaningful words were identified significantly better than neutral words, with no difference between positive and negative words. Since in that study only a single target word was displayed at a time, we hypothesized that the equivalent performances for positive and negative words were due to a lack of competition. To test this, in our Experiment 1, we replicated Zeelenberg and colleagues' finding, using emotion-laden Chinese words and the identical data-limited method, which measured the accuracy of a briefly shown target. We then introduced competition in Experiment 2 by simultaneously presenting two words during the target frame, and found evidence for an early attentional bias to negative words. In Experiment 3, we confirmed that the bias in Experiment 2 was not due to the inevitable repetition of stimuli. Taken together, these results support our hypothesis that, in the presence of competition, negative words receive attentional priority and consequently have enhanced perceptual representations.

Rapid modulation of spoken word recognition by visual primes.

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Okano, Kana; Grainger, Jonathan; Holcomb, Phillip J

2016-02-01

In a masked cross-modal priming experiment with ERP recordings, spoken Japanese words were primed with words written in one of the two syllabary scripts of Japanese. An early priming effect, peaking at around 200ms after onset of the spoken word target, was seen in left lateral electrode sites for Katakana primes, and later effects were seen for both Hiragana and Katakana primes on the N400 ERP component. The early effect is thought to reflect the efficiency with which words in Katakana script make contact with sublexical phonological representations involved in spoken language comprehension, due to the particular way this script is used by Japanese readers. This demonstrates fast-acting influences of visual primes on the processing of auditory target words, and suggests that briefly presented visual primes can influence sublexical processing of auditory target words. The later N400 priming effects, on the other hand, most likely reflect cross-modal influences on activity at the level of whole-word phonology and semantics.

Activation of words with phonological overlap

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Claudia K. Friedrich

2013-08-01

Full Text Available Multiple lexical representations overlapping with the input (cohort neighbors are temporarily activated in the listener’s mental lexicon when speech unfolds in time. Activation for cohort neighbors appears to rapidly decline as soon as there is mismatch with the input. However, it is a matter of debate whether or not they are completely excluded from further processing. We recorded behavioral data and event-related brain potentials (ERPs in auditory-visual word onset priming during a lexical decision task. As primes we used the first two syllables of spoken German words. In a carrier word condition, the primes were extracted from spoken versions of the target words (ano-ANORAK 'anorak'. In a cohort neighbor condition, the primes were taken from words that overlap with the target word up to the second nucleus (ana- taken from ANANAS 'pineapple'. Relative to a control condition, where primes and targets were unrelated, lexical decision responses for cohort neighbors were delayed. This reveals that cohort neighbors are disfavored by the decision processes at the behavioral front end. In contrast, left-anterior ERPs reflected long-lasting facilitated processing of cohort neighbors. We interpret these results as evidence for extended parallel processing of cohort neighbors. That is, in parallel to the preparation and elicitation of delayed lexical decision responses to cohort neighbors, aspects of the processing system appear to keep track of those less efficient candidates.

Discourse context and the recognition of reduced and canonical spoken words

OpenAIRE

Brouwer, S.; Mitterer, H.; Huettig, F.

2013-01-01

In two eye-tracking experiments we examined whether wider discourse information helps the recognition of reduced pronunciations (e.g., 'puter') more than the recognition of canonical pronunciations of spoken words (e.g., 'computer'). Dutch participants listened to sentences from a casual speech corpus containing canonical and reduced target words. Target word recognition was assessed by measuring eye fixation proportions to four printed words on a visual display: the target, a "reduced form" ...

Descriptor Data Bank (DDB): A Cloud Platform for Multiperspective Modeling of Protein-Ligand Interactions.

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Ashtawy, Hossam M; Mahapatra, Nihar R

2018-01-22

Protein-ligand (PL) interactions play a key role in many life processes such as molecular recognition, molecular binding, signal transmission, and cell metabolism. Examples of interaction forces include hydrogen bonding, hydrophobic effects, steric clashes, electrostatic contacts, and van der Waals attractions. Currently, a large number of hypotheses and perspectives to model these interaction forces are scattered throughout the literature and largely forgotten. Instead, had they been assembled and utilized collectively, they would have substantially improved the accuracy of predicting binding affinity of protein-ligand complexes. In this work, we present Descriptor Data Bank (DDB), a data-driven platform on the cloud for facilitating multiperspective modeling of PL interactions. DDB is an open-access hub for depositing, hosting, executing, and sharing descriptor extraction tools and data for a large number of interaction modeling hypotheses. The platform also implements a machine-learning (ML) toolbox for automatic descriptor filtering and analysis and scoring function (SF) fitting and prediction. The descriptor filtering module is used to filter out irrelevant and/or noisy descriptors and to produce a compact subset from all available features. We seed DDB with 16 diverse descriptor extraction tools developed in-house and collected from the literature. The tools altogether generate over 2700 descriptors that characterize (i) proteins, (ii) ligands, and (iii) protein-ligand complexes. The in-house descriptors we extract are protein-specific which are based on pairwise primary and tertiary alignment of protein structures followed by clustering and trilateration. We built and used DDB's ML library to fit SFs to the in-house descriptors and those collected from the literature. We then evaluated them on several data sets that were constructed to reflect real-world drug screening scenarios. We found that multiperspective SFs that were constructed using a large number

Automatic summarization of soccer highlights using audio-visual descriptors.

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Raventós, A; Quijada, R; Torres, Luis; Tarrés, Francesc

2015-01-01

Automatic summarization generation of sports video content has been object of great interest for many years. Although semantic descriptions techniques have been proposed, many of the approaches still rely on low-level video descriptors that render quite limited results due to the complexity of the problem and to the low capability of the descriptors to represent semantic content. In this paper, a new approach for automatic highlights summarization generation of soccer videos using audio-visual descriptors is presented. The approach is based on the segmentation of the video sequence into shots that will be further analyzed to determine its relevance and interest. Of special interest in the approach is the use of the audio information that provides additional robustness to the overall performance of the summarization system. For every video shot a set of low and mid level audio-visual descriptors are computed and lately adequately combined in order to obtain different relevance measures based on empirical knowledge rules. The final summary is generated by selecting those shots with highest interest according to the specifications of the user and the results of relevance measures. A variety of results are presented with real soccer video sequences that prove the validity of the approach.

Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign

Science.gov (United States)

Sliwoski, Gregory; Mendenhall, Jeffrey; Meiler, Jens

2016-03-01

Quantitative structure-activity relationship (QSAR) is a branch of computer aided drug discovery that relates chemical structures to biological activity. Two well established and related QSAR descriptors are two- and three-dimensional autocorrelation (2DA and 3DA). These descriptors encode the relative position of atoms or atom properties by calculating the separation between atom pairs in terms of number of bonds (2DA) or Euclidean distance (3DA). The sums of all values computed for a given small molecule are collected in a histogram. Atom properties can be added with a coefficient that is the product of atom properties for each pair. This procedure can lead to information loss when signed atom properties are considered such as partial charge. For example, the product of two positive charges is indistinguishable from the product of two equivalent negative charges. In this paper, we present variations of 2DA and 3DA called 2DA_Sign and 3DA_Sign that avoid information loss by splitting unique sign pairs into individual histograms. We evaluate these variations with models trained on nine datasets spanning a range of drug target classes. Both 2DA_Sign and 3DA_Sign significantly increase model performance across all datasets when compared with traditional 2DA and 3DA. Lastly, we find that limiting 3DA_Sign to maximum atom pair distances of 6 Å instead of 12 Å further increases model performance, suggesting that conformational flexibility may hinder performance with longer 3DA descriptors. Consistent with this finding, limiting the number of bonds in 2DA_Sign from 11 to 5 fails to improve performance.

Music Identification System Using MPEG-7 Audio Signature Descriptors

Science.gov (United States)

You, Shingchern D.; Chen, Wei-Hwa; Chen, Woei-Kae

2013-01-01

This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query) audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system's database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control. PMID:23533359

Music Identification System Using MPEG-7 Audio Signature Descriptors

Directory of Open Access Journals (Sweden)

Shingchern D. You

2013-01-01

Full Text Available This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system’s database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control.

Visualization and processing of higher order descriptors for multi-valued data

CERN Document Server

Schultz, Thomas

2015-01-01

Modern imaging techniques and computational simulations yield complex multi-valued data that require higher-order mathematical descriptors. This book addresses topics of importance when dealing with such data, including frameworks for image processing, visualization, and statistical analysis of higher-order descriptors. It also provides examples of the successful use of higher-order descriptors in specific applications and a glimpse of the next generation of diffusion MRI. To do so, it combines contributions on new developments, current challenges in this area, and state-of-the-art surveys.   Compared to the increasing importance of higher-order descriptors in a range of applications, tools for analysis and processing are still relatively hard to come by. Even though application areas such as medical imaging, fluid dynamics, and structural mechanics are very different in nature they face many shared challenges. This book provides an interdisciplinary perspective on this topic with contributions from key rese...

A Novel Fast and Robust Binary Affine Invariant Descriptor for Image Matching

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Xiujie Qu

2014-01-01

Full Text Available As the current binary descriptors have disadvantages of high computational complexity, no affine invariance, and the high false matching rate with viewpoint changes, a new binary affine invariant descriptor, called BAND, is proposed. Different from other descriptors, BAND has an irregular pattern, which is based on local affine invariant region surrounding a feature point, and it has five orientations, which are obtained by LBP effectively. Ultimately, a 256 bits binary string is computed by simple random sampling pattern. Experimental results demonstrate that BAND has a good matching result in the conditions of rotating, image zooming, noising, lighting, and small-scale perspective transformation. It has better matching performance compared with current mainstream descriptors, while it costs less time.

Breast density pattern characterization by histogram features and texture descriptors

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Pedro Cunha Carneiro

2017-04-01

Full Text Available Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammographic images into categories of breast density using an Artificial Neural Network. Methods We used 307 mammographic images from the INbreast digital database, extracting histogram features and texture descriptors of all mammograms and selecting them with the K-means technique. Then, these groups of selected features were used as inputs of an Artificial Neural Network to classify the images automatically into the four categories reported by radiologists. Results An average accuracy of 92.9% was obtained in a few tests using only some of the Haralick texture descriptors. Also, the accuracy rate increased to 98.95% when texture descriptors were mixed with some features based on a histogram. Conclusion Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images. From this paper, it was possible to automate the feature selection and the classification with acceptable error rates since the extraction of the features is suitable to the characteristics of the images involving the problem.

Discriminating Power of FISWG Characteristic Descriptors Under Different Forensic Use Cases

NARCIS (Netherlands)

Zeinstra, Christopher Gerard; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

2016-01-01

FISWG characteristic descriptors are facial features that can be used for evidence evaluation during forensic case work. In this paper we investigate the discriminating power of a biometric system that uses these characteristic descriptors as features under different forensic use cases. We show that

Whole-Word Phonological Representations of Disyllabic Words in the Chinese Lexicon: Data From Acquired Dyslexia

Directory of Open Access Journals (Sweden)

Sam-Po Law

2005-01-01

Full Text Available This study addresses the issue of the existence of whole-word phonological representations of disyllabic and multisyllabic words in the Chinese mental lexicon. A Cantonese brain-injured dyslexic individual with semantic deficits, YKM, was assessed on his abilities to read aloud and to comprehend disyllabic words containing homographic heterophonous characters, the pronunciation of which can only be disambiguated in word context. Superior performance on reading to comprehension was found. YKM could produce the target phonological forms without understanding the words. The dissociation is taken as evidence for whole-word representations for these words at the phonological level. The claim is consistent with previous account for discrepancy of the frequencies of tonal errors between reading aloud and object naming in Cantonese reported of another case study of similar deficits. Theoretical arguments for whole-word form representations for all multisyllabic Chinese words are also discussed.

Spatial attention in written word perception

Directory of Open Access Journals (Sweden)

Veronica eMontani

2014-02-01

Full Text Available The role of attention in visual word recognition and reading aloud is a long debated issue. Studies of both developmental and acquired reading disorders provide growing evidence that spatial attention is critically involved in word reading, in particular for the phonological decoding of unfamiliar letter strings. However, studies on healthy participants have produced contrasting results. The aim of this study was to investigate how the allocation of spatial attention may influence the perception of letter strings in skilled readers. High frequency words, low frequency words and pseudowords were briefly and parafoveally presented either in the left or the right visual field. Attentional allocation was modulated by the presentation of a spatial cue before the target string. Accuracy in reporting the target string was modulated by the spatial cue but this effect varied with the type of string. For unfamiliar strings, processing was facilitated when attention was focused on the string location and hindered when it was diverted from the target. This finding is consistent the assumptions of the CDP+ model of reading aloud, as well as with familiarity sensitivity models that argue for a flexible use of attention according with the specific requirements of the string. Moreover, we found that processing of high-frequency words was facilitated by an extra-large focus of attention. The latter result is consistent with the hypothesis that a broad distribution of attention is the default mode during reading of familiar words because it might optimally engage the broad receptive fields of the highest detectors in the hierarchical system for visual word recognition.

Using novel descriptor accounting for ligand-receptor interactions to define and visually explore biologically relevant chemical space.

Science.gov (United States)

Rabal, Obdulia; Oyarzabal, Julen

2012-05-25

The definition and pragmatic implementation of biologically relevant chemical space is critical in addressing navigation strategies in the overlapping regions where chemistry and therapeutically relevant targets reside and, therefore, also key to performing an efficient drug discovery project. Here, we describe the development and implementation of a simple and robust method for representing biologically relevant chemical space as a general reference according to current knowledge, independently of any reference space, and analyzing chemical structures accordingly. Underlying our method is the generation of a novel descriptor (LiRIf) that converts structural information into a one-dimensional string accounting for the plausible ligand-receptor interactions as well as for topological information. Capitalizing on ligand-receptor interactions as a descriptor enables the clustering, profiling, and comparison of libraries of compounds from a chemical biology and medicinal chemistry perspective. In addition, as a case study, R-groups analysis is performed to identify the most populated ligand-receptor interactions according to different target families (GPCR, kinases, etc.), as well as to evaluate the coverage of biologically relevant chemical space by structures annotated in different databases (ChEMBL, Glida, etc.).

Positive implicit attitudes toward odor words.

Science.gov (United States)

Bulsing, Patricia J; Smeets, Monique A M; van den Hout, Marcel A

2007-07-01

Associations between certain odors and for instance health effects may lead to positive or negative attitudes toward these odors. However, in experiments we conducted using the Implicit Association Test (IAT), we encountered attitudes even to odor "words." The IAT is based on the principle that reaction times measuring the association between words from a target dimension (in this case, odor vs. a neutral reference category) and an attribute dimension (i.e., positive or negative words) reflect the attitude to the target, where attitude-congruent associations between target and attribute are reflected by shorter reaction times. In a first experiment, we found distinctly positive attitudes to the concept odor in a student sample, which was replicated in a second experiment. In the main experiment, subjects in the aromatherapy group, who prefer using scented consumer products for relaxation purposes, showed a significantly more positive attitude toward odor words in the IAT than a control group, who did not have such a preference. The fact that results from the implicit test were not always associated with explicitly stated attitudes toward the odor words attests to the fact that the IAT measures the attitude of interest in a different way. As such, the IAT has added value in circumstances where explicit tests can be biased.

Descriptors for ions and ion-pairs for use in linear free energy relationships.

Science.gov (United States)

Abraham, Michael H; Acree, William E

2016-01-22

The determination of Abraham descriptors for single ions is reviewed, and equations are given for the partition of single ions from water to a number of solvents. These ions include permanent anions and cations and ionic species such as carboxylic acid anions, phenoxide anions and protonated base cations. Descriptors for a large number of ions and ionic species are listed, and equations for the prediction of Abraham descriptors for ionic species are given. The application of descriptors for ions and ionic species to physicochemical processes is given; these are to water-solvent partitions, HPLC retention data, immobilised artificial membranes, the Finkelstein reaction and diffusion in water. Applications to biological processes include brain permeation, microsomal degradation of drugs, skin permeation and human intestinal absorption. The review concludes with a section on the determination of descriptors for ion-pairs. Copyright © 2015 Elsevier B.V. All rights reserved.

L2 Word Recognition: Influence of L1 Orthography on Multi-syllabic Word Recognition.

Science.gov (United States)

Hamada, Megumi

2017-10-01

L2 reading research suggests that L1 orthographic experience influences L2 word recognition. Nevertheless, the findings on multi-syllabic words in English are still limited despite the fact that a vast majority of words are multi-syllabic. The study investigated whether L1 orthography influences the recognition of multi-syllabic words, focusing on the position of an embedded word. The participants were Arabic ESL learners, Chinese ESL learners, and native speakers of English. The task was a word search task, in which the participants identified a target word embedded in a pseudoword at the initial, middle, or final position. The search accuracy and speed indicated that all groups showed a strong preference for the initial position. The accuracy data further indicated group differences. The Arabic group showed higher accuracy in the final than middle, while the Chinese group showed the opposite and the native speakers showed no difference between the two positions. The findings suggest that L2 multi-syllabic word recognition involves unique processes.

Genetic divergence among Brazilian turmeric germplasm using morpho-agronomical descriptors

Directory of Open Access Journals (Sweden)

Mário Sérgio Sigrist

2011-01-01

Full Text Available Turmeric (Curcuma longa L. is a vegetatively-propagated crop which is used as a natural dye in the food industryand also presents many biological active compounds. Turmeric conventional breeding is difficult and often limited to germplasmselection. The aim of this study was to evaluate the genetic divergence among turmeric accessions available in Brazil using sevenmorpho-agronomical descriptors. Overall genetic divergence was low, although some divergent genotypes were identified. Fourmain groups of genotypes were identified and could be further used in breeding programs. Canonical variable analysis suggestedthat some descriptors were more important to discriminate accessions and also that one of the descriptors could be discarded. Theresults provided useful insights for better management of the germplasm collection, optimizing conservational and breeding efforts.

Innovative design method of automobile profile based on Fourier descriptor

Science.gov (United States)

Gao, Shuyong; Fu, Chaoxing; Xia, Fan; Shen, Wei

2017-10-01

Aiming at the innovation of the contours of automobile side, this paper presents an innovative design method of vehicle side profile based on Fourier descriptor. The design flow of this design method is: pre-processing, coordinate extraction, standardization, discrete Fourier transform, simplified Fourier descriptor, exchange descriptor innovation, inverse Fourier transform to get the outline of innovative design. Innovative concepts of the innovative methods of gene exchange among species and the innovative methods of gene exchange among different species are presented, and the contours of the innovative design are obtained separately. A three-dimensional model of a car is obtained by referring to the profile curve which is obtained by exchanging xenogeneic genes. The feasibility of the method proposed in this paper is verified by various aspects.

Space-Valence Priming with Subliminal and Supraliminal Words

Directory of Open Access Journals (Sweden)

Ulrich eAnsorge

2013-02-01

Full Text Available To date it is unclear whether (1 awareness-independent non-evaluative semantic processes influence affective semantics and whether (2 awareness-independent affective semantics influence non-evaluative semantic processing. In the current study, we investigated these questions with the help of subliminal (masked primes and visible targets in a space-valence across-category congruence effect. In line with (1, we found that subliminal space prime words influenced valence classification of supraliminal target words (Experiment 1: Classifications were faster with a congruent prime (e.g., the prime ‘up’ before the target ‘happy’ than with an incongruent prime (e.g., the prime ‘up’ before the target ‘sad’. In contrast to (2, no influence of subliminal valence primes on the classification of supraliminal space targets into up- and down-words was found (Experiment 2. Control conditions showed that standard masked response-priming effects were found with both subliminal prime types, and that an across-category congruence effect was also found with supraliminal valence primes and spatial target words. The final Experiment 3 confirmed that the across-category congruence effect indeed reflected priming of target categorization of a relevant meaning category. Together, the data jointly confirmed prediction (1 that awareness-independent non-evaluative semantic priming influences valence judgments.

Multiple dimensions of relatedness among words: Conjoint effects of form and meaning in word recognition★

OpenAIRE

Pastizzo, Matthew John; Feldman, Laurie Beth

2009-01-01

Words can be similar with respect to form (viz., spelling, pronunciation), meaning, or both form and meaning. In three lexical decision experiments (48 ms forward masked, 116 ms, and 250 ms SOAs), targets (e.g., FLOAT) followed prime words related by form only (e.g., COAT), meaning only (e.g., SWIM), or form and meaning (e.g., BOAT). BOAT–FLOAT and SWIM–FLOAT type pairs showed reduced target decision latencies relative to unrelated controls when primes were unmasked, but not when they were ma...

A Novel 2.5D Feature Descriptor Compensating for Depth Rotation

DEFF Research Database (Denmark)

Hagelskjær, Frederik; Buch, Anders Glent; Krüger, Norbert

2017-01-01

We introduce a novel type of local image descriptor based on Gabor filter responses. Our method operates on RGB-D images. We use the depth information to compensate for perspective distortions caused by out-of-plane rotations. The descriptor contains the responses of a multi-resolution Gabor bank...

Dyspnea descriptors developed in Brazil: application in obese patients and in patients with cardiorespiratory diseases.

Science.gov (United States)

Teixeira, Christiane Aires; Rodrigues Júnior, Antonio Luiz; Straccia, Luciana Cristina; Vianna, Elcio Dos Santos Oliveira; Silva, Geruza Alves da; Martinez, José Antônio Baddini

2011-01-01

To develop a set of descriptive terms applied to the sensation of dyspnea (dyspnea descriptors) for use in Brazil and to investigate the usefulness of these descriptors in four distinct clinical conditions that can be accompanied by dyspnea. We collected 111 dyspnea descriptors from 67 patients and 10 health professionals. These descriptors were analyzed and reduced to 15 based on their frequency of use, similarity of meaning, and potential pathophysiological value. Those 15 descriptors were applied in 50 asthma patients, 50 COPD patients, 30 patients with heart failure, and 50 patients with class II or III obesity. The three best descriptors, as selected by the patients, were studied by cluster analysis. Potential associations between the identified clusters and the four clinical conditions were also investigated. The use of this set of descriptors led to a solution with seven clusters, designated sufoco (suffocating), aperto (tight), rápido (rapid), fadiga (fatigue), abafado (stuffy), trabalho/inspiração (work/inhalation), and falta de ar (shortness of breath). Overlapping of descriptors was quite common among the patients, regardless of their clinical condition. Asthma was significantly associated with the sufoco and trabalho/inspiração clusters, whereas COPD and heart failure were associated with the sufoco, trabalho/inspiração, and falta de ar clusters. Obesity was associated only with the falta de ar cluster. In Brazil, patients who are accustomed to perceiving dyspnea employ various descriptors in order to describe the symptom, and these descriptors can be grouped into similar clusters. In our study sample, such clusters showed no usefulness in differentiating among the four clinical conditions evaluated.

From acoustic descriptors to evoked quality of car door sounds.

Science.gov (United States)

Bezat, Marie-Céline; Kronland-Martinet, Richard; Roussarie, Vincent; Ystad, Sølvi

2014-07-01

This article describes the first part of a study aiming at adapting the mechanical car door construction to the drivers' expectancies in terms of perceived quality of cars deduced from car door sounds. A perceptual cartography of car door sounds is obtained from various listening tests aiming at revealing both ecological and analytical properties linked to evoked car quality. In the first test naive listeners performed absolute evaluations of five ecological properties (i.e., solidity, quality, weight, closure energy, and success of closure). Then experts in the area of automobile doors categorized the sounds according to organic constituents (lock, joints, door panel), in particular whether or not the lock mechanism could be perceived. Further, a sensory panel of naive listeners identified sensory descriptors such as classical descriptors or onomatopoeia that characterize the sounds, hereby providing an analytic description of the sounds. Finally, acoustic descriptors were calculated after decomposition of the signal into a lock and a closure component by the Empirical Mode Decomposition (EMD) method. A statistical relationship between the acoustic descriptors and the perceptual evaluations of the car door sounds could then be obtained through linear regression analysis.

Accumulation of different visual feature descriptors in a coherent framework

DEFF Research Database (Denmark)

Jessen, J.B.; Pilz, F.; Kraft, Dirk

2011-01-01

We present a temporal accumulation scheme which disambiguates different kinds of visual 3D descriptors within one coherent framework. The accumulation consists of a twofold process: First, by means of a Bayesian filtering outliers become eliminated and second, the precision of the extracted infor...... information becomes enhanced by means of an unscented Kalman filtering process. It is a particular property of our algorithm to be able to deal with different kinds of visual descriptors by the very same mechanism. We show quantitative and qualitative results.......We present a temporal accumulation scheme which disambiguates different kinds of visual 3D descriptors within one coherent framework. The accumulation consists of a twofold process: First, by means of a Bayesian filtering outliers become eliminated and second, the precision of the extracted...

Generating descriptive visual words and visual phrases for large-scale image applications.

Science.gov (United States)

Zhang, Shiliang; Tian, Qi; Hua, Gang; Huang, Qingming; Gao, Wen

2011-09-01

Bag-of-visual Words (BoWs) representation has been applied for various problems in the fields of multimedia and computer vision. The basic idea is to represent images as visual documents composed of repeatable and distinctive visual elements, which are comparable to the text words. Notwithstanding its great success and wide adoption, visual vocabulary created from single-image local descriptors is often shown to be not as effective as desired. In this paper, descriptive visual words (DVWs) and descriptive visual phrases (DVPs) are proposed as the visual correspondences to text words and phrases, where visual phrases refer to the frequently co-occurring visual word pairs. Since images are the carriers of visual objects and scenes, a descriptive visual element set can be composed by the visual words and their combinations which are effective in representing certain visual objects or scenes. Based on this idea, a general framework is proposed for generating DVWs and DVPs for image applications. In a large-scale image database containing 1506 object and scene categories, the visual words and visual word pairs descriptive to certain objects or scenes are identified and collected as the DVWs and DVPs. Experiments show that the DVWs and DVPs are informative and descriptive and, thus, are more comparable with the text words than the classic visual words. We apply the identified DVWs and DVPs in several applications including large-scale near-duplicated image retrieval, image search re-ranking, and object recognition. The combination of DVW and DVP performs better than the state of the art in large-scale near-duplicated image retrieval in terms of accuracy, efficiency and memory consumption. The proposed image search re-ranking algorithm: DWPRank outperforms the state-of-the-art algorithm by 12.4% in mean average precision and about 11 times faster in efficiency.

Coordination of Word Recognition and Oculomotor Control During Reading: The Role of Implicit Lexical Decisions

Science.gov (United States)

Choi, Wonil; Gordon, Peter C.

2013-01-01

The coordination of word-recognition and oculomotor processes during reading was evaluated in two eye-tracking experiments that examined how word skipping, where a word is not fixated during first-pass reading, is affected by the lexical status of a letter string in the parafovea and ease of recognizing that string. Ease of lexical recognition was manipulated through target-word frequency (Experiment 1) and through repetition priming between prime-target pairs embedded in a sentence (Experiment 2). Using the gaze-contingent boundary technique the target word appeared in the parafovea either with full preview or with transposed-letter (TL) preview. The TL preview strings were nonwords in Experiment 1 (e.g., bilnk created from the target blink), but were words in Experiment 2 (e.g., sacred created from the target scared). Experiment 1 showed greater skipping for high-frequency than low-frequency target words in the full preview condition but not in the TL preview (nonword) condition. Experiment 2 showed greater skipping for target words that repeated an earlier prime word than for those that did not, with this repetition priming occurring both with preview of the full target and with preview of the target’s TL neighbor word. However, time to progress from the word after the target was greater following skips of the TL preview word, whose meaning was anomalous in the sentence context, than following skips of the full preview word whose meaning fit sensibly into the sentence context. Together, the results support the idea that coordination between word-recognition and oculomotor processes occurs at the level of implicit lexical decisions. PMID:23106372

Professional WordPress design and development

CERN Document Server

Williams, Brad; Stern, Hal

2014-01-01

The highest rated WordPress development and design book on the market is back with an all new third edition. Professional WordPress is the only WordPress book targeted to developers, with advanced content that exploits the full functionality of the most popular CMS in the world. Fully updated to align with WordPress 4.1, this edition has updated examples with all new screenshots, and full exploration of additional tasks made possible by the latest tools and features. You will gain insight into real projects that currently use WordPress as an application framework, as well as the basic usage a

Bag of frequencies: a descriptor of pulmonary nodules in Computed Tomography images

NARCIS (Netherlands)

Ciompi, F.; Jacobs, C.; Scholten, E.T.; Wille, M.M.W.; Jong, P.A. de; Prokop, M.; Ginneken, B. van

2015-01-01

We present a novel descriptor for the characterization of pulmonary nodules in computed tomography (CT) images. The descriptor encodes information on nodule morphology and has scale-invariant and rotation-invariant properties. Information on nodule morphology is captured by sampling intensity

Deconstructing field-induced ketene isomerization through Lagrangian descriptors.

Science.gov (United States)

Craven, Galen T; Hernandez, Rigoberto

2016-02-07

The time-dependent geometrical separatrices governing state transitions in field-induced ketene isomerization are constructed using the method of Lagrangian descriptors. We obtain the stable and unstable manifolds of time-varying transition states as dynamic phase space objects governing configurational changes when the ketene molecule is subjected to an oscillating electric field. The dynamics of the isomerization reaction are modeled through classical trajectory studies on the Gezelter-Miller potential energy surface and an approximate dipole moment model which is coupled to a time-dependent electric field. We obtain a representation of the reaction geometry, over varying field strengths and oscillation frequencies, by partitioning an initial phase space into basins labeled according to which product state is reached at a given time. The borders between these basins are in agreement with those obtained using Lagrangian descriptors, even in regimes exhibiting chaotic dynamics. Major outcomes of this work are: validation and extension of a transition state theory framework built from Lagrangian descriptors, elaboration of the applicability for this theory to periodically- and aperiodically-driven molecular systems, and prediction of regimes in which isomerization of ketene and its derivatives may be controlled using an external field.

GenMol trademark supramolecular descriptors predicting reliable sensitivity of energetic compounds

Energy Technology Data Exchange (ETDEWEB)

Benazet, Stephane; Jacob, Guy [SNPE Materiaux Energetiques, Vert Le Petit (France); Pepe, Gerard [CINaM UPR-CNRS 3118, Campus de Luminy Case, Marseille (France)

2009-04-15

Structure/activity relationship methodology has been applied to the problem of the prediction of the energetic molecule's sensitivity. This parameter knowledge is of great importance to increase the safety of operations in the field of synthesis and manipulation of such compounds. It has been shown that descriptors of the solid state interactions and surface topology issued from GenMol {sup trademark} software calculations greatly enhanced the correlation between measured and predicted sensitivity. As the structural parameters used to establish the descriptors are experimental ones, their physical significance is particularly preserved which allows to give a good prediction for impact or friction sensitivity by the so defined descriptors. (Abstract Copyright [2009], Wiley Periodicals, Inc.)

Spatial attention in written word perception.

Science.gov (United States)

Montani, Veronica; Facoetti, Andrea; Zorzi, Marco

2014-01-01

The role of attention in visual word recognition and reading aloud is a long debated issue. Studies of both developmental and acquired reading disorders provide growing evidence that spatial attention is critically involved in word reading, in particular for the phonological decoding of unfamiliar letter strings. However, studies on healthy participants have produced contrasting results. The aim of this study was to investigate how the allocation of spatial attention may influence the perception of letter strings in skilled readers. High frequency words (HFWs), low frequency words and pseudowords were briefly and parafoveally presented either in the left or the right visual field. Attentional allocation was modulated by the presentation of a spatial cue before the target string. Accuracy in reporting the target string was modulated by the spatial cue but this effect varied with the type of string. For unfamiliar strings, processing was facilitated when attention was focused on the string location and hindered when it was diverted from the target. This finding is consistent the assumptions of the CDP+ model of reading aloud, as well as with familiarity sensitivity models that argue for a flexible use of attention according with the specific requirements of the string. Moreover, we found that processing of HFWs was facilitated by an extra-large focus of attention. The latter result is consistent with the hypothesis that a broad distribution of attention is the default mode during reading of familiar words because it might optimally engage the broad receptive fields of the highest detectors in the hierarchical system for visual word recognition.

Effects of Auditory and Visual Priming on the Identification of Spoken Words.

Science.gov (United States)

Shigeno, Sumi

2017-04-01

This study examined the effects of preceding contextual stimuli, either auditory or visual, on the identification of spoken target words. Fifty-one participants (29% males, 71% females; mean age = 24.5 years, SD = 8.5) were divided into three groups: no context, auditory context, and visual context. All target stimuli were spoken words masked with white noise. The relationships between the context and target stimuli were as follows: identical word, similar word, and unrelated word. Participants presented with context experienced a sequence of six context stimuli in the form of either spoken words or photographs. Auditory and visual context conditions produced similar results, but the auditory context aided word identification more than the visual context in the similar word relationship. We discuss these results in the light of top-down processing, motor theory, and the phonological system of language.

Local self-similarity descriptor for point-of-interest reconstruction of real-world scenes

International Nuclear Information System (INIS)

Gao, Xianglu; Wan, Weibing; Zhao, Qunfei; Zhang, Xianmin

2015-01-01

Scene reconstruction is utilized commonly in close-range photogrammetry, with diverse applications in fields such as industry, biology, and aerospace industries. Presented surfaces or wireframe three-dimensional (3D) model reconstruction applications are either too complex or too inflexible to accommodate various types of real-world scenes, however. This paper proposes an algorithm for acquiring point-of-interest (referred to throughout the study as POI) coordinates in 3D space, based on multi-view geometry and a local self-similarity descriptor. After reconstructing several POIs specified by a user, a concise and flexible target object measurement method, which obtains the distance between POIs, is described in detail. The proposed technique is able to measure targets with high accuracy even in the presence of obstacles and non-Lambertian surfaces. The method is so flexible that target objects can be measured with a handheld digital camera. Experimental results further demonstrate the effectiveness of the algorithm. (paper)

Design of an Optimal Preview Controller for Linear Discrete-Time Descriptor Noncausal Multirate Systems

Directory of Open Access Journals (Sweden)

Mengjuan Cao

2014-01-01

Full Text Available The linear discrete-time descriptor noncausal multirate system is considered for the presentation of a new design approach for optimal preview control. First, according to the characteristics of causal controllability and causal observability, the descriptor noncausal system is constructed into a descriptor causal closed-loop system. Second, by using the characteristics of the causal system and elementary transformation, the descriptor causal closed-loop system is transformed into a normal system. Then, taking advantage of the discrete lifting technique, the normal multirate system is converted to a single-rate system. By making use of the standard preview control method, we construct the descriptor augmented error system. The quadratic performance index for the multirate system is given, which can be changed into one for the single-rate system. In addition, a new single-rate system is obtained, the optimal control law of which is given. Returning to the original system, the optimal preview controller for linear discrete-time descriptor noncausal multirate systems is derived. The stabilizability and detectability of the lifted single-rate system are discussed in detail. The optimal preview control design techniques are illustrated by simulation results for a simple example.

Emotionally enhanced memory for negatively arousing words: storage or retrieval advantage?

Science.gov (United States)

Nadarevic, Lena

2017-12-01

People typically remember emotionally negative words better than neutral words. Two experiments are reported that investigate whether emotionally enhanced memory (EEM) for negatively arousing words is based on a storage or retrieval advantage. Participants studied non-word-word pairs that either involved negatively arousing or neutral target words. Memory for these target words was tested by means of a recognition test and a cued-recall test. Data were analysed with a multinomial model that allows the disentanglement of storage and retrieval processes in the present recognition-then-cued-recall paradigm. In both experiments the multinomial analyses revealed no storage differences between negatively arousing and neutral words but a clear retrieval advantage for negatively arousing words in the cued-recall test. These findings suggest that EEM for negatively arousing words is driven by associative processes.

Processing and Representation of Ambiguous Words in Chinese Reading: Evidence from Eye Movements.

Science.gov (United States)

Shen, Wei; Li, Xingshan

2016-01-01

In the current study, we used eye tracking to investigate whether senses of polysemous words and meanings of homonymous words are represented and processed similarly or differently in Chinese reading. Readers read sentences containing target words which was either homonymous words or polysemous words. The contexts of text preceding the target words were manipulated to bias the participants toward reading the ambiguous words according to their dominant, subordinate, or neutral meanings. Similarly, disambiguating regions following the target words were also manipulated to favor either the dominant or subordinate meanings of ambiguous words. The results showed that there were similar eye movement patterns when Chinese participants read sentences containing homonymous and polysemous words. The study also found that participants took longer to read the target word and the disambiguating text following it when the prior context and disambiguating regions favored divergent meanings rather than the same meaning. These results suggested that homonymy and polysemy are represented similarly in the mental lexicon when a particular meaning (sense) is fully specified by disambiguating information. Furthermore, multiple meanings (senses) are represented as separate entries in the mental lexicon.

Tracking the time course of word-frequency effects in auditory word recognition with event-related potentials.

Science.gov (United States)

Dufour, Sophie; Brunellière, Angèle; Frauenfelder, Ulrich H

2013-04-01

Although the word-frequency effect is one of the most established findings in spoken-word recognition, the precise processing locus of this effect is still a topic of debate. In this study, we used event-related potentials (ERPs) to track the time course of the word-frequency effect. In addition, the neighborhood density effect, which is known to reflect mechanisms involved in word identification, was also examined. The ERP data showed a clear frequency effect as early as 350 ms from word onset on the P350, followed by a later effect at word offset on the late N400. A neighborhood density effect was also found at an early stage of spoken-word processing on the PMN, and at word offset on the late N400. Overall, our ERP differences for word frequency suggest that frequency affects the core processes of word identification starting from the initial phase of lexical activation and including target word selection. They thus rule out any interpretation of the word frequency effect that is limited to a purely decisional locus after word identification has been completed. Copyright © 2012 Cognitive Science Society, Inc.

Temperature and relative humidity influence the ripening descriptors of Camembert-type cheeses throughout ripening.

Science.gov (United States)

Leclercq-Perlat, M-N; Sicard, M; Perrot, N; Trelea, I C; Picque, D; Corrieu, G

2015-02-01

Ripening descriptors are the main factors that determine consumers' preferences of soft cheeses. Six descriptors were defined to represent the sensory changes in Camembert cheeses: Penicillium camemberti appearance, cheese odor and rind color, creamy underrind thickness and consistency, and core hardness. To evaluate the effects of the main process parameters on these descriptors, Camembert cheeses were ripened under different temperatures (8, 12, and 16°C) and relative humidity (RH; 88, 92, and 98%). The sensory descriptors were highly dependent on the temperature and RH used throughout ripening in a ripening chamber. All sensory descriptor changes could be explained by microorganism growth, pH, carbon substrate metabolism, and cheese moisture, as well as by microbial enzymatic activities. On d 40, at 8°C and 88% RH, all sensory descriptors scored the worst: the cheese was too dry, its odor and its color were similar to those of the unripe cheese, the underrind was driest, and the core was hardest. At 16°C and 98% RH, the odor was strongly ammonia and the color was dark brown, and the creamy underrind represented the entire thickness of the cheese but was completely runny, descriptors indicative of an over ripened cheese. Statistical analysis showed that the best ripening conditions to achieve an optimum balance between cheese sensory qualities and marketability were 13±1°C and 94±1% RH. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

SVM prediction of ligand-binding sites in bacterial lipoproteins employing shape and physio-chemical descriptors.

Science.gov (United States)

Kadam, Kiran; Prabhakar, Prashant; Jayaraman, V K

2012-11-01

Bacterial lipoproteins play critical roles in various physiological processes including the maintenance of pathogenicity and numbers of them are being considered as potential candidates for generating novel vaccines. In this work, we put forth an algorithm to identify and predict ligand-binding sites in bacterial lipoproteins. The method uses three types of pocket descriptors, namely fpocket descriptors, 3D Zernike descriptors and shell descriptors, and combines them with Support Vector Machine (SVM) method for the classification. The three types of descriptors represent shape-based properties of the pocket as well as its local physio-chemical features. All three types of descriptors, along with their hybrid combinations are evaluated with SVM and to improve classification performance, WEKA-InfoGain feature selection is applied. Results obtained in the study show that the classifier successfully differentiates between ligand-binding and non-binding pockets. For the combination of three types of descriptors, 10 fold cross-validation accuracy of 86.83% is obtained for training while the selected model achieved test Matthews Correlation Coefficient (MCC) of 0.534. Individually or in combination with new and existing methods, our model can be a very useful tool for the prediction of potential ligand-binding sites in bacterial lipoproteins.

Dense Descriptors for Optical Flow Estimation: A Comparative Study

Directory of Open Access Journals (Sweden)

Ahmadreza Baghaie

2017-02-01

Full Text Available Estimating the displacements of intensity patterns between sequential frames is a very well-studied problem, which is usually referred to as optical flow estimation. The first assumption among many of the methods in the field is the brightness constancy during movements of pixels between frames. This assumption is proven to be not true in general, and therefore, the use of photometric invariant constraints has been studied in the past. One other solution can be sought by use of structural descriptors rather than pixels for estimating the optical flow. Unlike sparse feature detection/description techniques and since the problem of optical flow estimation tries to find a dense flow field, a dense structural representation of individual pixels and their neighbors is computed and then used for matching and optical flow estimation. Here, a comparative study is carried out by extending the framework of SIFT-flow to include more dense descriptors, and comprehensive comparisons are given. Overall, the work can be considered as a baseline for stimulating more interest in the use of dense descriptors for optical flow estimation.

An Advanced Rotation Invariant Descriptor for SAR Image Registration

Directory of Open Access Journals (Sweden)

Yuming Xiang

2017-07-01

Full Text Available The Scale-Invariant Feature Transform (SIFT algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms.

Parallel language activation during word processing in bilinguals: Evidence from word production in sentence context

NARCIS (Netherlands)

Starreveld, P.A.; de Groot, A.M.B.; Rossmark, B.M.M.; van Hell, J.G.

2014-01-01

In two picture-naming experiments we examined whether bilinguals co-activate the non-target language during word production in the target language. The pictures were presented out-of-context (Experiment 1) or in visually presented sentence contexts (Experiment 2). In both experiments different

Words that describe chronic musculoskeletal pain: implications for assessing pain quality across cultures.

Science.gov (United States)

Sharma, Saurab; Pathak, Anupa; Jensen, Mark P

2016-01-01

People from different cultures who speak different languages may experience pain differently. This possible variability has important implications for evaluating the validity of pain quality measures that are directly translated into different languages without cultural adaptations. The aim of this study was to evaluate the impact of language and culture on the validity of pain quality measures by comparing the words that individuals with chronic pain from Nepal use to describe their pain with those used by patients from the USA. A total of 101 individuals with chronic musculoskeletal pain in Nepal were asked to describe their pain. The rates of the different pain descriptor domains and phrases used by the Nepali sample were then compared to the published rates of descriptors used by patients from the USA. The content validity of commonly used measures for assessing pain quality was then evaluated. While there was some similarity between patients from Nepal and the USA in how they describe pain, there were also important differences, especially in how pain quality was described. For example, many patients from Nepal used metaphors to describe their pain. Also, the patients from Nepal often used a category of pain descriptor - which describes a physical state - not used by patients from the USA. Only the original McGill Pain Questionnaire was found to have content validity for assessing pain quality in patients from Nepal, although other existing pain quality measures could be adapted to be content valid by adding one or two additional descriptors, depending on the measure in question. The findings indicate that direct translations of measures that are developed using samples of patients from one country or culture are not necessarily content valid for use in other countries or cultures; some adaptations may be required in order for such measures to be most useful in new language and culture.

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

Science.gov (United States)

Ehresmann, Bernd; de Groot, Marcel J; Alex, Alexander; Clark, Timothy

2004-01-01

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

Descriptors for antimicrobial peptides

DEFF Research Database (Denmark)

Jenssen, Håvard

2011-01-01

of these are currently being used in quantitative structure--activity relationship (QSAR) studies for AMP optimization. Additionally, some key commercial computational tools are discussed, and both successful and less successful studies are referenced, illustrating some of the challenges facing AMP scientists. Through...... examples of different peptide QSAR studies, this review highlights some of the missing links and illuminates some of the questions that would be interesting to challenge in a more systematic fashion. Expert opinion: Computer-aided peptide QSAR using molecular descriptors may provide the necessary edge...

Tracking image features with PCA-SURF descriptors

CSIR Research Space (South Africa)

Pancham, A

2015-05-01

Full Text Available IAPR International Conference on Machine Vision Applications, May 18-22, 2015, Tokyo, JAPAN Tracking Image Features with PCA-SURF Descriptors Ardhisha Pancham CSIR, UKZN South Africa apancham@csir.co.za Daniel Withey CSIR South Africa...

Deployment of spatial attention to words in central and peripheral vision.

Science.gov (United States)

Ducrot, Stéphanie; Grainger, Jonathan

2007-05-01

Four perceptual identification experiments examined the influence of spatial cues on the recognition of words presented in central vision (with fixation on either the first or last letter of the target word) and in peripheral vision (displaced left or right of a central fixation point). Stimulus location had a strong effect on word identification accuracy in both central and peripheral vision, showing a strong right visual field superiority that did not depend on eccentricity. Valid spatial cues improved word identification for peripherally presented targets but were largely ineffective for centrally presented targets. Effects of spatial cuing interacted with visual field effects in Experiment 1, with valid cues reducing the right visual field superiority for peripherally located targets, but this interaction was shown to depend on the type of neutral cue. These results provide further support for the role of attentional factors in visual field asymmetries obtained with targets in peripheral vision but not with centrally presented targets.

Analysis Relationship Among Descriptor, References and Citation to Contruct the Inherent Structure of Document Collection

International Nuclear Information System (INIS)

Hasibuan, Zainal A.; Mustangimah

2001-01-01

There are many characteristics can be used to identify a document which cover characteristics of the documents, cited documents, and citing documents This research explored the inherent structure of a document collection as one of main components of information retrieval system. The characteristics examined are: descriptors, references (cited documents), and citations (citing documents). Three independent variables were studied: co-descriptor, bibliographic coupling, and co-citation. A test collection was constructed by searching on a single descriptor i nformation retrieval i n the CD-ROM version of Education Resource Information Clearinghouse (ERIC), covering the period 1981 through 1985. Descriptors were extracted from ERIC; cited and citing documents associated with the test collection were derived from Social Sciences Citation Index (SSCI), covering the period 1981 through 1990. Three hypothesis were tested in this study, that are: (1) the higher the frequency of co-descriptors between documents, the higher the frequencies of their bibliographic coupling and co-citation; (2) the higher the frequency of bibliographic coupling between documents, the higher the frequencies of their co-citation and co-descriptors; and (3) the higher the frequency of co-citation between documents, the higher the frequencies of their co-descriptors and bibliographic coupling. The results showed that all of three hypothesis are supported statistically and there is a significant linear relationship among the observed variables. It is mean that there is a significant relationship among descriptors, references, and citation, so that it can be used to construct the inherent structure of document collection in order to improve information retrieval system performance

Increasing adolescents' depth of understanding of cross-curriculum words: an intervention study.

Science.gov (United States)

Spencer, Sarah; Clegg, Judy; Lowe, Hilary; Stackhouse, Joy

2017-09-01

There is some evidence that vocabulary intervention is effective for children, although further research is needed to confirm the impact of intervention within contexts of social disadvantage. Very little is known about the effectiveness of interventions to increase adolescent knowledge of cross-curriculum words. To evaluate the effectiveness of an intervention programme designed to develop adolescents' knowledge of cross-curriculum words. Participants were 35 adolescents aged between 12 and 14 years who were at risk of educational underachievement with low scores on a range of assessments. Participants received a 10-week intervention programme in small groups, targeting 10 cross-curriculum words (e.g., 'summarize'). This was evaluated using a bespoke outcome measure (the Word Knowledge Profile). The study involved an AABA design, with a repeated baseline, delayed intervention cohort and blind assessment. Intervention included both semantic and phonological information about the target words and involved the adolescents using the words in multiple contexts. Results were promising and participants' knowledge of the targeted words significantly increased following intervention. Progress was demonstrated on the Word Knowledge Profile on the item requiring participants to define the word (for the summer intervention group only). This increase in depth of knowledge was seen on taught words but not on matched non-taught words. Cross-curriculum words are not consistently understood by adolescents at risk of low educational attainment within a low socio-economic context. A 10-week intervention programme resulted in some increases to the depth of knowledge of targeted cross-curriculum words. © 2017 Royal College of Speech and Language Therapists.

Vocabulary Word Instruction for Students Who Read Braille

Science.gov (United States)

Savaiano, Mackenzie E.; Compton, Donald L.; Hatton, Deborah D.; Lloyd, Blair P.

2016-01-01

The association made between the meaning, spelling, and pronunciation of a word has been shown to help children remember the meanings of words. The present study addressed whether the presence of a target word in Braille during instruction facilitated vocabulary learning more efficiently than an auditory-only instructional condition. The authors…

Fourier descriptor classification of differential eddy current probe impedance plane trajectories

International Nuclear Information System (INIS)

Lord, W.; Satish, S.R.

1984-01-01

This chapter describes the use of a parametric model for representing the two-dimensional eddy current impedance plane trajectory. The main advantage of this approach is the ability to reconstruct the trajectory from the model coefficients. Fourier descriptors are used to facilitate defect classification. The Fourier descriptors are obtained by expanding the complex contour function in a Fourier series. Functions of Fourier coefficients which are invariant under transformation of the trajectory are derived and incorporated into a feature vector. Defect classification is obtained by using the K-Means algorithm to cluster the feature vectors. It is demonstrated that the Fourier descriptor approach represents a powerful tool which have several advantages over nonparametric approaches including its insensitivity to drift in the eddy current instrument as well as variations in the probe speed

Illusory words: the roles of attention and of top-down constraints in conjoining letters to form words.

Science.gov (United States)

Treisman, A; Souther, J

1986-02-01

When attention is divided among four briefly exposed syllables, subjects mistakenly detect targets whose letters are present in the display but in the wrong combinations. These illusory conjunctions are somewhat more frequent when the target is a word and when the distractors are nonwords, but the effects of lexical status are small, and no longer reach significance in free report of the same displays. Search performance is further impaired if the nonwords are unpronounceable consonant strings rather than consonant-vowel-consonant strings, but the decrement is due to missed targets rather than to increased conjunction errors. The results are discussed in relation to feature-integration theory and to current models of word perception.

Artificial intelligence systems based on texture descriptors for vaccine development.

Science.gov (United States)

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2011-02-01

The aim of this work is to analyze and compare several feature extraction methods for peptide classification that are based on the calculation of texture descriptors starting from a matrix representation of the peptide. This texture-based representation of the peptide is then used to train a support vector machine classifier. In our experiments, the best results are obtained using local binary patterns variants and the discrete cosine transform with selected coefficients. These results are better than those previously reported that employed texture descriptors for peptide representation. In addition, we perform experiments that combine standard approaches based on amino acid sequence. The experimental section reports several tests performed on a vaccine dataset for the prediction of peptides that bind human leukocyte antigens and on a human immunodeficiency virus (HIV-1). Experimental results confirm the usefulness of our novel descriptors. The matlab implementation of our approaches is available at http://bias.csr.unibo.it/nanni/TexturePeptide.zip.

Assigning Main Orientation to an EOH Descriptor on Multispectral Images.

Science.gov (United States)

Li, Yong; Shi, Xiang; Wei, Lijun; Zou, Junwei; Chen, Fang

2015-07-01

This paper proposes an approach to compute an EOH (edge-oriented histogram) descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform) on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor). In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

Modulation of motor-meaning congruity effects for valenced words

OpenAIRE

Brookshire, Geoffrey; Ivry, Richard; Casasanto, Daniel

2010-01-01

We investigated the extent to which emotionally valenced words automatically cue spatio-motor representations. Participants made speeded button presses, moving their hand upward or downward while viewing words with positive or negative valence. Only the color of the words was relevant to the response; on target trials, there was no requirement to read the words or process their meaning. In Experiment 1, upward responses were faster for positive words, and downward for negative words. This eff...

IN SILICO EVALUATION OF ANGIOTENSIN II RECEPTOR ANTAGONIST’S PLASMA PROTEIN BINDING USING COMPUTED MOLECULAR DESCRIPTORS

Directory of Open Access Journals (Sweden)

Jadranka Odović

2014-03-01

Full Text Available The discovery of new pharmacologically active substances and drugs modeling led to necessity of predicting drugs properties and its ADME data. Angiotensin II receptor antagonists are a group of pharmaceuticals which modulate the renin-angiotensin-aldosterone system and today represent the most commonly prescribed anti-hypertensive drugs. The aim of this study was to compare different molecular properties of seven angiotensin II receptor antagonists / blockers (ARBs, (eprosartan, irbesartan, losartan, olmesartan, telmisartan, valsartan and their plasma protein binding (PPB data. Several ARBs molecular descriptors were calculated using software package Molinspiration Depiction Software as well as Virtual Computational Chemistry Laboratory (electronic descriptor – PSA, constitutional parameter – Mw, geometric descriptor – Vol, lipophilicity descriptors - logP values, aqueous solubility data – logS. The correlations between all collected descriptors and plasma protein binding data obtained from relevant literature were established. In the simple linear regression poor correlations were obtained in relationships between PPB data and all calculated molecular descriptors. In the next stage of the study multiple linear regression (MLR was used for correlation of PPB data with two different descriptors as independent variables. The best correlation (R2=0.70 with P<0.05 was established between PPB data and molecular weight with addition of volume values as independent variables. The possible application of computed molecular descriptors in drugs protein binding evaluation can be of great importance in drug research.

MANIPULATING L2 LEARNERS' ONLINE DICTIONARY USE AND ITS EFFECT ON L2 WORD RETENTION

Directory of Open Access Journals (Sweden)

Elke Peters

2007-02-01

Full Text Available This study explored the effect of two enhancement techniques on L2 learners' look-up behaviour during a reading task and word retention afterwards amongst Flemish learners of German: a Vocabulary Test Announcement and Task-induced Word Relevance. Eighty-four participants were recruited for this study. They were randomly assigned to one of two groups: 1 not forewarned of an upcoming vocabulary test (incidental condition or 2 forewarned of a vocabulary test (intentional condition. Task-induced Word Relevance was operationalized by a reading comprehension task. The relevance factor comprised two levels: plus-relevant and minus-relevant target words. Plus-relevant words needed to be looked up and used receptively in order to answer the comprehension questions. In other words, the reading comprehension task could not be accomplished without knowing the meaning of the plus-relevant words. The minus-relevant target words, on the other hand, were not linked to the reading comprehension questions. Our findings show a significant effect of Test Announcement and Word Relevance on whether a target word is looked up. In addition, Word Relevance also affects the frequency of clicks on target words. Word retention is only influenced by Task-induced Word Relevance. The effect of Word Relevance is durable.

Words, Words, Words: English, Vocabulary.

Science.gov (United States)

Lamb, Barbara

The Quinmester course on words gives the student the opportunity to increase his proficiency by investigating word origins, word histories, morphology, and phonology. The course includes the following: dictionary skills and familiarity with the "Oxford,""Webster's Third," and "American Heritage" dictionaries; word…

A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors

Energy Technology Data Exchange (ETDEWEB)

Carriger, John F. [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States); Martin, Todd M. [U.S. Environmental Protection Agency, Office of Research and Development, Sustainable Technology Division, Cincinnati, OH, 45220 (United States); Barron, Mace G., E-mail: barron.mace@epa.gov [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States)

2016-11-15

Highlights: • A Bayesian network was developed to classify chemical mode of action (MoA). • The network was based on the aquatic toxicity MoA for over 1000 chemicals. • A Markov blanket algorithm selected a subset of theoretical molecular descriptors. • Sensitivity analyses found influential descriptors for classifying the MoAs. • Overall precision of the Bayesian MoA classification model was 80%. - Abstract: The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the dataset of 1098 chemicals with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2%. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally complex dataset can simplify analysis and interpretation by

New descriptors of T-wave morphology are independent of heart rate

DEFF Research Database (Denmark)

Andersen, Mads Peter; Xue, Joel Q; Graff, Claus

2008-01-01

from daytime Holter recordings. Duration parameters (QT, ToTe, TpTe, and others), a number of basic T-wave morphology parameters (amplitude, area, and others) as well as advanced morphology descriptors (asymmetry, flatness, and others) were measured automatically. Heart rate dependence was examined...... by means of analysis of covariance. The results showed clear heart rate dependence for the QT interval (R(2) = 0.53-0.57) and a moderate degree of heart rate dependence for the basic morphology parameters (amplitude, area, and others) (R(2) = 0.17-0.42). Both the advanced T-wave descriptors (asymmetry......T-wave morphology descriptors are sensitive to drug-induced changes and may be a useful addition to the QT interval in cardiac safety trials. Intrasubject heart rate dependence of T-wave morphology was investigated in a sample of 39 healthy individuals. Ten-second electrocardiograms were obtained...

Finding the Best Feature Detector-Descriptor Combination

DEFF Research Database (Denmark)

Dahl, Anders Lindbjerg; Aanæs, Henrik; Pedersen, Kim Steenstrup

2011-01-01

, not statistically significantly better than some other methods. As a byproduct of this investigation, we have also tested various DAISY type descriptors, and found that the difference among their performance is statistically insignificant using this dataset. Furthermore, we have not been able to produce results...

Automated detection of microaneurysms using robust blob descriptors

Science.gov (United States)

Adal, K.; Ali, S.; Sidibé, D.; Karnowski, T.; Chaum, E.; Mériaudeau, F.

2013-03-01

Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fundus images. Then, Hessian-based candidate selection algorithm is applied to extract image regions which are more likely to be MAs. For each candidate region, robust low-level blob descriptors such as Speeded Up Robust Features (SURF) and Intensity Normalized Radon Transform are extracted to characterize candidate MA regions. The combined features are then classified using SVM which has been trained using ten manually annotated training images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. Preliminary results show the competitiveness of the proposed candidate selection techniques against state-of-the art methods as well as the promising future for the proposed descriptors to be used in the localization of MAs from fundus images.

Automatic Prompt System in the Process of Mapping plWordNet on Princeton WordNet

Directory of Open Access Journals (Sweden)

Paweł Kędzia

2015-06-01

Full Text Available Automatic Prompt System in the Process of Mapping plWordNet on Princeton WordNet The paper offers a critical evaluation of the power and usefulness of an automatic prompt system based on the extended Relaxation Labelling algorithm in the process of (manual mapping plWordNet on Princeton WordNet. To this end the results of manual mapping – that is inter-lingual relations between plWN and PWN synsets – are juxtaposed with the automatic prompts that were generated for the source language synsets to be mapped. We check the number and type of inter-lingual relations introduced on the basis of automatic prompts and the distance of the respective prompt synsets from the actual target language synsets.

Episodic Specificity in Acquiring Thematic Knowledge of Novel Words from Descriptive Episodes.

Science.gov (United States)

Zhang, Meichao; Chen, Shuang; Wang, Lin; Yang, Xiaohong; Yang, Yufang

2017-01-01

The current study examined whether thematic relations of the novel words could be acquired via descriptive episodes, and if yes, whether it could be generalized to thematically related words in a different scenario. In Experiment 1, a lexical decision task was used where the novel words served as primes for target words in four conditions: (1) corresponding concepts of the novel words, (2) thematically related words in the same episodes as that in learning condition, (3) thematically related words in different episodes, or (4) unrelated words served as targets. Event related potentials elicited by the targets revealed that compared to the unrelated words, the corresponding concepts and thematically related words in the same episodes elicited smaller N400s with a frontal-central distribution, whereas the thematically related words in different episodes elicited an enhanced late positive component. Experiment 2 further showed a priming effect of the corresponding concepts on the thematically related words in the same episodes as well as in a different episode, indicating that the absence of a priming effect of the learned novel words on the thematically related words in different episode could not be attributed to inappropriate selection of thematically related words in the two conditions. These results indicate that only the corresponding concepts and the thematically related words in the learning episodes were successfully primed, whereas the thematic association between the novel words and the thematically related words in different scenarios could only be recognized in a late processing stage. Our findings suggest that thematic knowledge of novel words is organized via separate scenarios, which are represented in a clustered manner in the semantic network.

Anticipatory coarticulation facilitates word recognition in toddlers.

Science.gov (United States)

Mahr, Tristan; McMillan, Brianna T M; Saffran, Jenny R; Ellis Weismer, Susan; Edwards, Jan

2015-09-01

Children learn from their environments and their caregivers. To capitalize on learning opportunities, young children have to recognize familiar words efficiently by integrating contextual cues across word boundaries. Previous research has shown that adults can use phonetic cues from anticipatory coarticulation during word recognition. We asked whether 18-24 month-olds (n=29) used coarticulatory cues on the word "the" when recognizing the following noun. We performed a looking-while-listening eyetracking experiment to examine word recognition in neutral vs. facilitating coarticulatory conditions. Participants looked to the target image significantly sooner when the determiner contained facilitating coarticulatory cues. These results provide the first evidence that novice word-learners can take advantage of anticipatory sub-phonemic cues during word recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

Exploring the role of quantum chemical descriptors in modeling acute toxicity of diverse chemicals to Daphnia magna.

Science.gov (United States)

Reenu; Vikas

2015-09-01

Various quantum-mechanically computed molecular and thermodynamic descriptors along with physico-chemical, electrostatic and topological descriptors are compared while developing quantitative structure-activity relationships (QSARs) for the acute toxicity of 252 diverse organic chemicals towards Daphnia magna. QSAR models based on the quantum-chemical descriptors, computed with routinely employed advanced semi-empirical and ab-initio methods, along with the electron-correlation contribution (CORR) of the descriptors, are analyzed for the external predictivity of the acute toxicity. The models with reliable internal stability and external predictivity are found to be based on the HOMO energy along with the physico-chemical, electrostatic and topological descriptors. Besides this, the total energy and electron-correlation energy are also observed as highly reliable descriptors, suggesting that the intra-molecular interactions between the electrons play an important role in the origin of the acute toxicity, which is in fact an unexplored phenomenon. The models based on quantum-chemical descriptors such as chemical hardness, absolute electronegativity, standard Gibbs free energy and enthalpy are also observed to be reliable. A comparison of the robust models based on the quantum-chemical descriptors computed with various quantum-mechanical methods suggests that the advanced semi-empirical methods such as PM7 can be more reliable than the ab-initio methods which are computationally more expensive. Copyright © 2015 Elsevier Inc. All rights reserved.

What is the Phonological Word in Dagbani? A Positional ...

African Journals Online (AJOL)

This paper offers a phonological diagnostic for defining the word in Dagbani, a Gur language of Ghana. It shows that a morphological unit that constitutes a complete word blocks contrast-neutralising phonological processes from target segments within its boundaries when triggered across its boundary. In sub-word units, ...

Propuesta de descriptores para Acca sellowiana (Berg. Burret

Directory of Open Access Journals (Sweden)

María Puppo

2014-12-01

Full Text Available Guayabo del país o goiaba serrana [Acca sellowiana (Berg. Burret] es uno de los recursos fitogenéticos subutilizados más valiosos de Uruguay y Brasil. Este árbol de fruto comestible, es endémico de una estrecha región sudamericana que abarca el noreste uruguayo y sur de Brasil, donde su cultivo se limita al uso doméstico o a pequeños huertos comerciales. El uso de los materiales de la especie se ve limitado por el desconocimiento de la diversidad presente tanto en poblaciones naturales como en materiales cultivados. El objetivo de este trabajo fue la elaboración de una lista de descriptores que permita la caracterización y evaluación de los materiales para la conservación, uso sostenible e incorporación de diversidad en los programas de mejoramiento genético. Se elaboró una lista preliminar de 41 descriptores morfo-fenológicos de hoja, flor y fruto, que se aplicó in situ a 204 individuos pertenecientes a cuatro poblaciones silvestres del noreste del Uruguay. Con el método de Máxima Verosimilitud Restringida se estimaron los componentes de la varianza entre poblaciones (s²P, entre individuos dentro de poblaciones (s²I(P, entre muestras dentro de individuo (s²M(IP y sus intervalos de confianza utilizando un Modelo Lineal Mixto. Para la determinación del poder discriminante de las variables cuantitativas se adoptó como criterio estadístico la comparación de IC (límite inferior ICs²I(P>límite superior ICs²M(IP y se calculó la razón entre s²I(P/s²M(IP. Para las variables cualitativas se calculó el estadístico F para la determinación de las diferencias significativas entre individuos con el objetivo de identificar descriptores discriminantes de individuos. También se determinaron las variables que discriminan poblaciones. Se validaron siete descriptores cualitativos (forma de fruto, posición de los sépalos, color de pulpa, color interno de la cáscara, dureza de cáscara, clases de distancia estigma-estambres y

Relationship between Dyspnea Descriptors and Underlying Causes of the Symptom; a Cross-sectional Study.

Science.gov (United States)

Sajadi, Seyyed Mohammad Ali; Majidi, Alireza; Abdollahimajd, Fahimeh; Jalali, Fatemeh

2017-01-01

History taking and physical examination help clinicians identify the patient's problem and effectively treat it. This study aimed to evaluate the descriptors of dyspnea in patients presenting to emergency department (ED) with asthma, congestive heart failure (CHF), and chronic obstructive pulmonary disease (COPD). This cross-sectional study was conducted on all patients presenting to ED with chief complaint of dyspnea, during 2 years. The patients were asked to describe their dyspnea by choosing three items from the valid and reliable questionnaire or articulating their sensation. The relationship between dyspnea descriptors and underlying cause of symptom was evaluated using SPSS version 16. 312 patients with the mean age of 60.96±17.01 years were evaluated (53.2% male). Most of the patients were > 65 years old (48.7%) and had basic level of education (76.9%). "My breath doesn't go out all the way" with 83.1%, "My chest feels tight " with 45.8%, and "I feel that my airway is obstructed" with 40.7%, were the most frequent dyspnea descriptors in asthma patients. "My breathing requires work" with 46.3%, "I feel that I am suffocating" with 31.5%, and "My breath doesn't go out all the way" with 29.6%, were the most frequent dyspnea descriptors in COPD patients. "My breathing is heavy" with 74.4%, "A hunger for more air" with 24.4%, and "I cannot get enough air" with 23.2%, were the most frequent dyspnea descriptors in CHF patients. Except for "My breath does not go in all the way", there was significant correlation between studied dyspnea descriptors and underlying disease (p = 0.001 for all analyses). It seems that dyspnea descriptors along with other findings from history and physical examination could be helpful in differentiating the causes of the symptom in patients presenting to ED suffering from dyspnea.

Dependence of QSAR models on the selection of trial descriptor sets: a demonstration using nanotoxicity endpoints of decorated nanotubes.

Science.gov (United States)

Shao, Chi-Yu; Chen, Sing-Zuo; Su, Bo-Han; Tseng, Yufeng J; Esposito, Emilio Xavier; Hopfinger, Anton J

2013-01-28

Little attention has been given to the selection of trial descriptor sets when designing a QSAR analysis even though a great number of descriptor classes, and often a greater number of descriptors within a given class, are now available. This paper reports an effort to explore interrelationships between QSAR models and descriptor sets. Zhou and co-workers (Zhou et al., Nano Lett. 2008, 8 (3), 859-865) designed, synthesized, and tested a combinatorial library of 80 surface modified, that is decorated, multi-walled carbon nanotubes for their composite nanotoxicity using six endpoints all based on a common 0 to 100 activity scale. Each of the six endpoints for the 29 most nanotoxic decorated nanotubes were incorporated as the training set for this study. The study reported here includes trial descriptor sets for all possible combinations of MOE, VolSurf, and 4D-fingerprints (FP) descriptor classes, as well as including and excluding explicit spatial contributions from the nanotube. Optimized QSAR models were constructed from these multiple trial descriptor sets. It was found that (a) both the form and quality of the best QSAR models for each of the endpoints are distinct and (b) some endpoints are quite dependent upon 4D-FP descriptors of the entire nanotube-decorator complex. However, other endpoints yielded equally good models only using decorator descriptors with and without the decorator-only 4D-FP descriptors. Lastly, and most importantly, the quality, significance, and interpretation of a QSAR model were found to be critically dependent on the trial descriptor sets used within a given QSAR endpoint study.

Assigning Main Orientation to an EOH Descriptor on Multispectral Images

Directory of Open Access Journals (Sweden)

Yong Li

2015-07-01

Full Text Available This paper proposes an approach to compute an EOH (edge-oriented histogram descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor. In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

Cavity Versus Ligand Shape Descriptors: Application to Urokinase Binding Pockets.

Science.gov (United States)

Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Camproux, Anne-Claude; Petitjean, Michel

2017-11-01

We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA-ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere. The DISC values were computed with the freeware PCI. The pocket descriptors and their high correspondences with ligand descriptors are crucial for polypharmacology prediction. We found that the protein heavy atoms lining the urokinases binding pockets are either located on the surface of their convex hull or lie close to this surface. We also found that the radii of the urokinases binding pockets and the radii of their ligands are highly correlated (r = 0.9).

How lingering representations of abandoned context words affect speech production.

Science.gov (United States)

Tydgat, Ilse; Diependaele, Kevin; Hartsuiker, Robert J; Pickering, Martin J

2012-07-01

Four experiments tested whether and how initially planned but then abandoned speech can influence the production of a subsequent resumption. Participants named initial pictures, which were sometimes suddenly replaced by target pictures that were related in meaning or word form or were unrelated. They then had to stop and resume with the name of the target picture. Target picture naming latencies were measured separately for trials in which the initial speech was skipped, interrupted, or completed. Semantically related initial pictures helped the production of the target word, although the effect dissipated once the utterance of the initial picture name had been completed. In contrast, phonologically related initial pictures hindered the production of the target word, but only for trials in which the name of the initial picture had at least partly been uttered. This semantic facilitation and phonological interference did not depend on the time interval between the initial and target picture, which was either varied between 200 ms and 400 ms (Experiments 1-2) or was kept constant at 300 ms (Experiments 3-4). We discuss the implications of these results for models of speech self-monitoring and for models of problem-free word production. Copyright © 2012 Elsevier B.V. All rights reserved.

WORD-ATTACK SKILLS FOR INDONESIAN LEARNERS

Directory of Open Access Journals (Sweden)

Joko Pranowo

2006-01-01

Full Text Available The typical drawbacks that affect most Indonesian learners studying English as the target language concern the strategies in dealing with new dictions. The rule of thumb is that the learners are usually tempted to directly look up the meaning in a dictionary when other ways such as guessing the meaning from the context or by dissecting the words into smaller units so that they are able to get a hint from the base word cannot be engineered. As a result of this activity then, they miss crucial points in the realm of word enrichment. This article will shed some light on how to deal with new words and claim that it is not the meaning of a new word that should be the first priority.

Skipping of Chinese characters does not rely on word-based processing.

Science.gov (United States)

Lin, Nan; Angele, Bernhard; Hua, Huimin; Shen, Wei; Zhou, Junyi; Li, Xingshan

2018-02-01

Previous eye-movement studies have indicated that people tend to skip extremely high-frequency words in sentence reading, such as "the" in English and "/de" in Chinese. Two alternative hypotheses have been proposed to explain how this frequent skipping happens in Chinese reading: one assumes that skipping happens when the preview has been fully identified at the word level (word-based skipping); the other assumes that skipping happens whenever the preview character is easy to identify regardless of whether lexical processing has been completed or not (character-based skipping). Using the gaze-contingent display change paradigm, we examined the two hypotheses by substituting the preview of the third character of a four-character Chinese word with the high-frequency Chinese character "/de", which should disrupt the ongoing word-level processing. The character-based skipping hypothesis predicts that this manipulation will enhance the skipping probability of the target character (i.e., the third character of the target word), because the character "/de" has much higher character frequency than the original character. The word-based skipping hypothesis instead predicts a reduction of the skipping probability of the target character because the presence of the character "/de" is lexically infelicitous at word level. The results supported the character-based skipping hypothesis, indicating that in Chinese reading the decision of skipping a character can be made before integrating it into a word.

Can we apply the MRI BI-RADS lexicon morphology descriptors on contrast-enhanced spectral mammography?

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Kamal, Rasha M; Helal, Maha H; Mansour, Sahar M; Haggag, Marwa A; Nada, Omniya M; Farahat, Iman G; Alieldin, Nelly H

2016-07-12

To assess the feasibility of using the MRI breast imaging reporting and data system (BI-RADS) lexicon morphology descriptors to characterize enhancing breast lesions identified on contrast-enhanced spectral mammography (CESM). The study is a retrospective analysis of the morphology descriptors of 261 enhancing breast lesions identified on CESM in 239 patients. We presented the morphological categorization of the included lesions into focus, mass and non-mass. Further classifications included (1) the multiplicity for "focus" category, (2) the shape, margin and internal enhancement for "mass" category and (3) the distribution and internal enhancement for "non-mass" category. Each morphology descriptor was evaluated individually (irrespective of all other descriptors) by calculating its sensitivity, specificity, positive-predictive value (PPV) and negative-predictive value (NPV) and likelihood ratios (LRs). The study included 68/261 (26.1%) benign lesions and 193/261 (73.9%) malignant lesions. Intensely enhancing foci, whether single (7/12, 58.3%) or multiple (2/12, 16.7%), were malignant. Descriptors of "irregular"-shape (PPV: 92.4%) and "non-circumscribed" margin (odds ratio: 55.2, LR positive: 4.77; p-value: <0.001) were more compatible with malignancy. Internal mass enhancement patterns showed a very low specificity (58.0%) and NPV (40.0%). Non-mass enhancement (NME) was detected in 81/261 lesions. Asymmetrical NME in 81% (n = 52/81) lesions was malignant lesions and internal enhancement patterns indicative of malignancy were the heterogeneous and clumped ones. We can apply the MRI morphology descriptors to characterize lesions on CESM, but with few expectations. In many situations, irregular-shaped, non-circumscribed masses and NME with focal, ductal or segmental distribution and heterogeneous or clumped enhancement are the most suggestive descriptors of malignant pathologies. (1) The MRI BI-RADS lexicon morphology descriptors can be applied in the

Fast human pose estimation using 3D Zernike descriptors

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Berjón, Daniel; Morán, Francisco

2012-03-01

Markerless video-based human pose estimation algorithms face a high-dimensional problem that is frequently broken down into several lower-dimensional ones by estimating the pose of each limb separately. However, in order to do so they need to reliably locate the torso, for which they typically rely on time coherence and tracking algorithms. Their losing track usually results in catastrophic failure of the process, requiring human intervention and thus precluding their usage in real-time applications. We propose a very fast rough pose estimation scheme based on global shape descriptors built on 3D Zernike moments. Using an articulated model that we configure in many poses, a large database of descriptor/pose pairs can be computed off-line. Thus, the only steps that must be done on-line are the extraction of the descriptors for each input volume and a search against the database to get the most likely poses. While the result of such process is not a fine pose estimation, it can be useful to help more sophisticated algorithms to regain track or make more educated guesses when creating new particles in particle-filter-based tracking schemes. We have achieved a performance of about ten fps on a single computer using a database of about one million entries.

See Before You Jump: Full Recognition of Parafoveal Words Precedes Skips During Reading

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Gordon, Peter C.; Plummer, Patrick; Choi, Wonil

2013-01-01

Serial attention models of eye-movement control during reading were evaluated in an eye-tracking experiment that examined how lexical activation combines with visual information in the parafovea to affect word skipping (where a word is not fixated during first-pass reading). Lexical activation was manipulated by repetition priming created through prime-target pairs embedded within a sentence. The boundary technique (Rayner, 1975) was used to determine whether the target word was fully available during parafoveal preview or whether it was available with transposed letters (e.g., Herman changed to Hreman). With full parafoveal preview, the target word was skipped more frequently when it matched the earlier prime word (i.e., was repeated) than when it did not match the earlier prime word (i.e., was new). With transposed-letter (TL) preview, repetition had no effect on skipping rates despite the great similarity of the TL preview string to the target word and substantial evidence that TL strings activate the words from which they are derived (Perea & Lupker, 2003). These results show that lexically-based skipping is based on full recognition of the letter string in parafoveal preview and does not involve using the contextual constraint to compensate for the reduced information available from the parafovea. These results are consistent with models of eye-movement control during reading in which successive words in a text are processed one at a time (serially) and in which word recognition strongly influences eye movements. PMID:22686842

Awareness of breathing: the structure of language descriptors of respiratory sensations.

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Petersen, Sibylle; Orth, Bernhard; Ritz, Thomas

2008-01-01

Recent research suggests that dyspnea is not a single sensation but a multidimensional construct reflected in different verbal descriptors that can provide useful diagnostic information. In this study superordinated clusters of dyspnea were investigated in combination with a dimensional approach. We examined the use of 20 respiratory symptom descriptors by healthy volunteers who completed a protocol of seven experimental conditions: Quiet breathing, breath holding, paced breathing, climbing stairs, resistive load breathing, voluntary hyperinflation, and voluntary hyperventilation. We analyzed the ratings of these descriptors with multidimensional scaling (MDS) and cluster analysis. While similarities with prior studies were found on a lower fusion level, we were able to demonstrate the usefulness of interpreting higher fusion levels with four clusters related to work of breathing, coordination, suffocation, and struggling for air, merging into two superordinated clusters, effort and air hunger that are compatible with widely accepted primary components of dyspnea. MDS results also suggested that future studies should consider further breathing sensations related to cognitive control of breathing.

Meaningful Words and Non-Words Repetitive Articulatory Rate (Oral Diadochokinesis) in Persian Speaking Children.

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Zamani, Peyman; Rezai, Hossein; Garmatani, Neda Tahmasebi

2017-08-01

Repetitive articulatory rate or Oral Diadochokinesis (oral-DDK) shows a guideline for appraisal and diagnosis of subjects with oral-motor disorder. Traditionally, meaningless words repetition has been utilized in this task and preschool children have challenges with them. Therefore, we aimed to determine some meaningful words in order to test oral-DDK in Persian speaking preschool children. Participants were 142 normally developing children, (age range 4-6 years), who were asked to produce /motæka, golabi/ as two meaningful Persian words and /pa-ta-ka/ as non-word in conventional oral-DDK task. We compared the time taken for 10-times fast repetitions of two meaningful Persian words and the tri-syllabic nonsense word /pa-ta-ka/. Praat software was used to calculate the average time that subjects took to produce the target items. In 4-5 year old children, [Formula: see text] of time taken for 10-times repetitions of /pa-ta-ka, motæka, golabi/ were [Formula: see text], and [Formula: see text] seconds respectively, and in 5-6 year old children were [Formula: see text], and [Formula: see text] seconds respectively. Findings showed that the main effect of type of words on oral diadochokinesis was significant ([Formula: see text]). Children repeated meaningful words /motæka, golabi/ faster than the non-word /pa-ta-ka/. Sex and age factors had no effect on time taken for repetition of oral-DDK test. It is suggested that Speech Therapists can use meaningful words to facilitate oral-DDK test for children.

Externally predictive quantitative modeling of supercooled liquid vapor pressure of polychlorinated-naphthalenes through electron-correlation based quantum-mechanical descriptors.

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Vikas; Chayawan

2014-01-01

For predicting physico-chemical properties related to environmental fate of molecules, quantitative structure-property relationships (QSPRs) are valuable tools in environmental chemistry. For developing a QSPR, molecular descriptors computed through quantum-mechanical methods are generally employed. The accuracy of a quantum-mechanical method, however, rests on the amount of electron-correlation estimated by the method. In this work, single-descriptor QSPRs for supercooled liquid vapor pressure of chloronaphthalenes and polychlorinated-naphthalenes are developed using molecular descriptors based on the electron-correlation contribution of the quantum-mechanical descriptor. The quantum-mechanical descriptors for which the electron-correlation contribution is analyzed include total-energy, mean polarizability, dipole moment, frontier orbital (HOMO/LUMO) energy, and density-functional theory (DFT) based descriptors, namely, absolute electronegativity, chemical hardness, and electrophilicity index. A total of 40 single-descriptor QSPRs were developed using molecular descriptors computed with advanced semi-empirical (SE) methods, namely, RM1, PM7, and ab intio methods, namely, Hartree-Fock and DFT. The developed QSPRs are validated using state-of-the-art external validation procedures employing an external prediction set. From the comparison of external predictivity of the models, it is observed that the single-descriptor QSPRs developed using total energy and correlation energy are found to be far more robust and predictive than those developed using commonly employed descriptors such as HOMO/LUMO energy and dipole moment. The work proposes that if real external predictivity of a QSPR model is desired to be explored, particularly, in terms of intra-molecular interactions, correlation-energy serves as a more appropriate descriptor than the polarizability. However, for developing QSPRs, computationally inexpensive advanced SE methods such as PM7 can be more reliable than

Eye movements when reading sentences with handwritten words.

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Perea, Manuel; Marcet, Ana; Uixera, Beatriz; Vergara-Martínez, Marta

2016-10-17

The examination of how we read handwritten words (i.e., the original form of writing) has typically been disregarded in the literature on reading. Previous research using word recognition tasks has shown that lexical effects (e.g., the word-frequency effect) are magnified when reading difficult handwritten words. To examine this issue in a more ecological scenario, we registered the participants' eye movements when reading handwritten sentences that varied in the degree of legibility (i.e., sentences composed of words in easy vs. difficult handwritten style). For comparison purposes, we included a condition with printed sentences. Results showed a larger reading cost for sentences with difficult handwritten words than for sentences with easy handwritten words, which in turn showed a reading cost relative to the sentences with printed words. Critically, the effect of word frequency was greater for difficult handwritten words than for easy handwritten words or printed words in the total times on a target word, but not on first-fixation durations or gaze durations. We examine the implications of these findings for models of eye movement control in reading.

Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors.

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Núbia Rosa da Silva

Full Text Available The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.

Advances in structural damage assessment using strain measurements and invariant shape descriptors

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Patki, Amol Suhas

to the area surrounding the damage, while damage in orthotropic materials tends to have more global repercussions. This calls for analysis of full-field strain distributions adding to the complexity of post-damage life estimation. This study explores shape descriptors used in the field of medical imagery, military targeting and biometric recognition for obtaining a qualitative and quantitative comparison between full-field strain data recorded from damaged composite panels using sophisticated experimental techniques. These descriptors are capable of decomposing images with 103 to 106 pixels into a feature vector with only a few hundred elements. This ability of shape descriptors to achieve enormous reduction in strain data, while providing unique representation, makes them a practical choice for the purpose of structural damage assessment. Consequently, it is relatively easy to statistically compare the shape descriptors of the full-field strain maps using similarity measures rather than the strain maps themselves. However, the wide range of geometric and design features in engineering components pose difficulties in the application of traditional shape description techniques. Thus a new shape descriptor is developed which is applicable to a wide range of specimen geometries. This work also illustrates how shape description techniques can be applied to full-field finite element model validations and updating.

The influence of certain molecular descriptors of fecal elimination of angiotensin II receptor antagonists

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Trbojević-Stanković Jasna B.

2015-01-01

Full Text Available Angiotensin II receptor antagonists (ARBs modulate the function of the renin-angiotensin-aldosterone system and are commonly prescribed antihypertensive drugs, especially in patients with renal failure. In this study, the relationship between several molecular properties of seven ARBs (candesartan, eprosartan, irbesartan, losartan, olmesartan, telmisartan, valsartan and their fecal elimination data obtained from the literature were investigated. The ARB molecular descriptors were calculated using three software packages. Simple linear regression analysis showed the best 2 correlation between fecal elimination data and lipophilicity descriptor, ClogP values (R2 = 0.725. Multiple linear regression was applied to examine the correlation of ARBs’ fecal elimination data with their lipophilicity and one additional, calculated descriptor. The best correlation (R2 = 0.909 with an acceptable probability value, P <0.05 was established between the ARB fecal elimination data and their lipophilicity and aqueous solubility data. Applying computed molecular descriptors for evaluating drug elimination is of great importance in drug research.

Estudio de la variabilidad genética en habichuela Phaseolus vulgaris L., mediante descriptores morfológicos y bioquímicos

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Gutierrez J. A.

2004-04-01

. After SDS-PAGE analysis Andean (T, C, and H and Mesoamerican [S, Sb, CH and H(S+1] types of phaseolin were detected in the sample, suggesting a higher contribution of the Mesoamerican gene pool to the genotype of snap beans. Also it was observed that, at the same zones of collection in some secondary centers, snap beans were originated and dispersed differently as compared to dry beans. A higher number of hybrid genotypes were detected among genetic pools when the three markers were used. Results seems to indicate that snap beans developed under environmental effects of the temperate zones, have a more complex genetic structure and higher rates of allogamy than those observed at primary centers of domestication. The results obtained using the three descriptors show that total genetic diversity for snap beans is similar to that of dry beans, but the snap beans population structure observed in this study is different to that reported for dry beans. Key words: Genetic variability, morphological descriptors, isozymes, seed protein, genetic pool.

Cueing listeners to attend to a target talker progressively improves word report as the duration of the cue-target interval lengthens to 2,000 ms.

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Holmes, Emma; Kitterick, Padraig T; Summerfield, A Quentin

2018-04-25

Endogenous attention is typically studied by presenting instructive cues in advance of a target stimulus array. For endogenous visual attention, task performance improves as the duration of the cue-target interval increases up to 800 ms. Less is known about how endogenous auditory attention unfolds over time or the mechanisms by which an instructive cue presented in advance of an auditory array improves performance. The current experiment used five cue-target intervals (0, 250, 500, 1,000, and 2,000 ms) to compare four hypotheses for how preparatory attention develops over time in a multi-talker listening task. Young adults were cued to attend to a target talker who spoke in a mixture of three talkers. Visual cues indicated the target talker's spatial location or their gender. Participants directed attention to location and gender simultaneously ("objects") at all cue-target intervals. Participants were consistently faster and more accurate at reporting words spoken by the target talker when the cue-target interval was 2,000 ms than 0 ms. In addition, the latency of correct responses progressively shortened as the duration of the cue-target interval increased from 0 to 2,000 ms. These findings suggest that the mechanisms involved in preparatory auditory attention develop gradually over time, taking at least 2,000 ms to reach optimal configuration, yet providing cumulative improvements in speech intelligibility as the duration of the cue-target interval increases from 0 to 2,000 ms. These results demonstrate an improvement in performance for cue-target intervals longer than those that have been reported previously in the visual or auditory modalities.

The Temporal Dynamics of Spoken Word Recognition in Adverse Listening Conditions

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Brouwer, Susanne; Bradlow, Ann R.

2016-01-01

This study examined the temporal dynamics of spoken word recognition in noise and background speech. In two visual-world experiments, English participants listened to target words while looking at four pictures on the screen: a target (e.g. "candle"), an onset competitor (e.g. "candy"), a rhyme competitor (e.g.…

The Slow Developmental Time Course of Real-Time Spoken Word Recognition

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Rigler, Hannah; Farris-Trimble, Ashley; Greiner, Lea; Walker, Jessica; Tomblin, J. Bruce; McMurray, Bob

2015-01-01

This study investigated the developmental time course of spoken word recognition in older children using eye tracking to assess how the real-time processing dynamics of word recognition change over development. We found that 9-year-olds were slower to activate the target words and showed more early competition from competitor words than…

The role of grammatical category information in spoken word retrieval.

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Duràn, Carolina Palma; Pillon, Agnesa

2011-01-01

We investigated the role of lexical syntactic information such as grammatical gender and category in spoken word retrieval processes by using a blocking paradigm in picture and written word naming experiments. In Experiments 1, 3, and 4, we found that the naming of target words (nouns) from pictures or written words was faster when these target words were named within a list where only words from the same grammatical category had to be produced (homogeneous category list: all nouns) than when they had to be produced within a list comprising also words from another grammatical category (heterogeneous category list: nouns and verbs). On the other hand, we detected no significant facilitation effect when the target words had to be named within a homogeneous gender list (all masculine nouns) compared to a heterogeneous gender list (both masculine and feminine nouns). In Experiment 2, using the same blocking paradigm by manipulating the semantic category of the items, we found that naming latencies were significantly slower in the semantic category homogeneous in comparison with the semantic category heterogeneous condition. Thus semantic category homogeneity caused an interference, not a facilitation effect like grammatical category homogeneity. Finally, in Experiment 5, nouns in the heterogeneous category condition had to be named just after a verb (category-switching position) or a noun (same-category position). We found a facilitation effect of category homogeneity but no significant effect of position, which showed that the effect of category homogeneity found in Experiments 1, 3, and 4 was not due to a cost of switching between grammatical categories in the heterogeneous grammatical category list. These findings supported the hypothesis that grammatical category information impacts word retrieval processes in speech production, even when words are to be produced in isolation. They are discussed within the context of extant theories of lexical production.

Fourier descriptors analysis of anisotropy and preferred Orientation in geological samples

International Nuclear Information System (INIS)

Santiago Buey, C. de

2011-01-01

This study focuses on the use of Fourier descriptors to evaluate and quantify two specific fabric characteristics of geological materials: anisotropy of particles or voids morphologies and particle orientation. To this end, a theoretical section of a rock was created, made of ellipses and rectangles of different axes ratios and different orientations. The Fourier descriptors method was applied to calculate the anisotropy and orientation of each particle and, finally, a rose diagram was constructed to represent the particles orientations distribution and to observe the presence or not of any preferred orientation. (Author) 15 refs.

Morphological descriptors and micro satellite diversity among scarlet ...

African Journals Online (AJOL)

Solanum aethiopicum L. groups is an important leaf and fruit vegetable, largely consumed in sub Saharan Africa. Genetic variation pattern among 35 accessions belonging to S. aethiopicum groups and sources of donor parents were investigated using morphological descriptors and SSR marker pairs. The Principal ...

Can the meaning of multiple words be integrated unconsciously?

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van Gaal, Simon; Naccache, Lionel; Meuwese, Julia D I; van Loon, Anouk M; Leighton, Alexandra H; Cohen, Laurent; Dehaene, Stanislas

2014-05-05

What are the limits of unconscious language processing? Can language circuits process simple grammatical constructions unconsciously and integrate the meaning of several unseen words? Using behavioural priming and electroencephalography (EEG), we studied a specific rule-based linguistic operation traditionally thought to require conscious cognitive control: the negation of valence. In a masked priming paradigm, two masked words were successively (Experiment 1) or simultaneously presented (Experiment 2), a modifier ('not'/'very') and an adjective (e.g. 'good'/'bad'), followed by a visible target noun (e.g. 'peace'/'murder'). Subjects indicated whether the target noun had a positive or negative valence. The combination of these three words could either be contextually consistent (e.g. 'very bad - murder') or inconsistent (e.g. 'not bad - murder'). EEG recordings revealed that grammatical negations could unfold partly unconsciously, as reflected in similar occipito-parietal N400 effects for conscious and unconscious three-word sequences forming inconsistent combinations. However, only conscious word sequences elicited P600 effects, later in time. Overall, these results suggest that multiple unconscious words can be rapidly integrated and that an unconscious negation can automatically 'flip the sign' of an unconscious adjective. These findings not only extend the limits of subliminal combinatorial language processes, but also highlight how consciousness modulates the grammatical integration of multiple words.

Word encoding during sleep is suggested by correlations between word-evoked up-states and post-sleep semantic priming

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Simon eRuch

2014-11-01

Full Text Available To test whether humans can encode words during sleep we played everyday words to men while they were napping and assessed priming from sleep-played words following waking. Words were presented during non-rapid eye movement (NREM sleep. Priming was assessed using a semantic and a perceptual priming test. These tests measured differences in the processing of words that had been or had not been played during sleep. Synonyms to sleep-played words were the targets in the semantic priming test that tapped the meaning of sleep-played words. All men responded to sleep-played words by producing up-states in their electroencephalogram. Up-states are NREM sleep-specific phases of briefly increased neuronal excitability. The word-evoked up-states might have promoted word processing during sleep. Yet, the mean performance in the priming tests administered following sleep was at chance level, which suggests that participants as a group failed to show priming following sleep. However, performance in the two priming tests was positively correlated to each other and to the magnitude of the word-evoked up-states. Hence, the larger a participant’s word-evoked up-states, the larger his perceptual and semantic priming. Those participants who scored high on all variables must have encoded words during sleep. We conclude that some humans are able to encode words during sleep, but more research is needed to pin down the factors that modulate this ability.

Bayesian screening for active compounds in high-dimensional chemical spaces combining property descriptors and molecular fingerprints.

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Vogt, Martin; Bajorath, Jürgen

2008-01-01

Bayesian classifiers are increasingly being used to distinguish active from inactive compounds and search large databases for novel active molecules. We introduce an approach to directly combine the contributions of property descriptors and molecular fingerprints in the search for active compounds that is based on a Bayesian framework. Conventionally, property descriptors and fingerprints are used as alternative features for virtual screening methods. Following the approach introduced here, probability distributions of descriptor values and fingerprint bit settings are calculated for active and database molecules and the divergence between the resulting combined distributions is determined as a measure of biological activity. In test calculations on a large number of compound activity classes, this methodology was found to consistently perform better than similarity searching using fingerprints and multiple reference compounds or Bayesian screening calculations using probability distributions calculated only from property descriptors. These findings demonstrate that there is considerable synergy between different types of property descriptors and fingerprints in recognizing diverse structure-activity relationships, at least in the context of Bayesian modeling.

English word frequency and recognition in bilinguals: Inter-corpus comparison and error analysis.

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Shi, Lu-Feng

2015-01-01

This study is the second of a two-part investigation on lexical effects on bilinguals' performance on a clinical English word recognition test. Focus is on word-frequency effects using counts provided by four corpora. Frequency of occurrence was obtained for 200 NU-6 words from the Hoosier mental lexicon (HML) and three contemporary corpora, American National Corpora, Hyperspace analogue to language (HAL), and SUBTLEX(US). Correlation analysis was performed between word frequency and error rate. Ten monolinguals and 30 bilinguals participated. Bilinguals were further grouped according to their age of English acquisition and length of schooling/working in English. Word frequency significantly affected word recognition in bilinguals who acquired English late and had limited schooling/working in English. When making errors, bilinguals tended to replace the target word with a word of a higher frequency. Overall, the newer corpora outperformed the HML in predicting error rate. Frequency counts provided by contemporary corpora predict bilinguals' recognition of English monosyllabic words. Word frequency also helps explain top replacement words for misrecognized targets. Word-frequency effects are especially prominent for bilinguals foreign born and educated.

Character Decomposition and Transposition Processes in Chinese Compound Words Modulates Attentional Blink.

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Cao, Hongwen; Gao, Min; Yan, Hongmei

2016-01-01

The attentional blink (AB) is the phenomenon in which the identification of the second of two targets (T2) is attenuated if it is presented less than 500 ms after the first target (T1). Although the AB is eliminated in canonical word conditions, it remains unclear whether the character order in compound words affects the magnitude of the AB. Morpheme decomposition and transposition of Chinese two-character compound words can provide an effective means to examine AB priming and to assess combinations of the component representations inherent to visual word identification. In the present study, we examined the processing of consecutive targets in a rapid serial visual presentation (RSVP) paradigm using Chinese two-character compound words in which the two characters were transposed to form meaningful words or meaningless combinations (reversible, transposed, or canonical words). We found that when two Chinese characters that form a compound word, regardless of their order, are presented in an RSVP sequence, the likelihood of an AB for the second character is greatly reduced or eliminated compared to when the two characters constitute separate words rather than a compound word. Moreover, the order of the report for the two characters is more likely to be reversed when the normal order of the two characters in a compound word is reversed, especially when the interval between the presentation of the two characters is extremely short. These findings are more consistent with the cognitive strategy hypothesis than the resource-limited hypothesis during character decomposition and transposition of Chinese two-character compound words. These results suggest that compound characters are perceived as a unit, rather than two separate words. The data further suggest that readers could easily understand the text with character transpositions in compound words during Chinese reading.

The time course of spoken word recognition in Mandarin Chinese: a unimodal ERP study.

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Huang, Xianjun; Yang, Jin-Chen; Zhang, Qin; Guo, Chunyan

2014-10-01

In the present study, two experiments were carried out to investigate the time course of spoken word recognition in Mandarin Chinese using both event-related potentials (ERPs) and behavioral measures. To address the hypothesis that there is an early phonological processing stage independent of semantics during spoken word recognition, a unimodal word-matching paradigm was employed, in which both prime and target words were presented auditorily. Experiment 1 manipulated the phonological relations between disyllabic primes and targets, and found an enhanced P2 (200-270 ms post-target onset) as well as a smaller early N400 to word-initial phonological mismatches over fronto-central scalp sites. Experiment 2 manipulated both phonological and semantic relations between monosyllabic primes and targets, and replicated the phonological mismatch-associated P2, which was not modulated by semantic relations. Overall, these results suggest that P2 is a sensitive electrophysiological index of early phonological processing independent of semantics in Mandarin Chinese spoken word recognition. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluating descriptors for the lateral translocation of membrane proteins.

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Domanova, Olga; Borbe, Stefan; Mühlfeld, Stefanie; Becker, Martin; Kubitz, Ralf; Häussinger, Dieter; Berlage, Thomas

2011-01-01

Microscopic images of tissue sections are used for diagnosis and monitoring of therapy, by analysis of protein patterns correlating to disease states. Spatial protein distribution is influenced by protein translocation between different membrane compartments and quantified by comparison of microscopic images of biological samples. Cholestatic liver diseases are characterized by translocation of transport proteins, and quantification of their dislocation offers new diagnostic options. However, reliable and unbiased tools are lacking. The nowadays used manual method is slow, subjective and error-prone. We have developed a new workflow based on automated image analysis and improved it by the introduction of scale-free descriptors for the translocation quantification. This fast and unbiased method can substitute the manual analysis, and the suggested descriptors perform better than the earlier used statistical variance.

A new texture descriptor based on local micro-pattern for detection of architectural distortion in mammographic images

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de Oliveira, Helder C. R.; Moraes, Diego R.; Reche, Gustavo A.; Borges, Lucas R.; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.

2017-03-01

This paper presents a new local micro-pattern texture descriptor for the detection of Architectural Distortion (AD) in digital mammography images. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automatic detection of AD, but their performance are still unsatisfactory. The proposed descriptor, Local Mapped Pattern (LMP), is a generalization of the Local Binary Pattern (LBP), which is considered one of the most powerful feature descriptor for texture classification in digital images. Compared to LBP, the LMP descriptor captures more effectively the minor differences between the local image pixels. Moreover, LMP is a parametric model which can be optimized for the desired application. In our work, the LMP performance was compared to the LBP and four Haralick's texture descriptors for the classification of 400 regions of interest (ROIs) extracted from clinical mammograms. ROIs were selected and divided into four classes: AD, normal tissue, microcalcifications and masses. Feature vectors were used as input to a multilayer perceptron neural network, with a single hidden layer. Results showed that LMP is a good descriptor to distinguish AD from other anomalies in digital mammography. LMP performance was slightly better than the LBP and comparable to Haralick's descriptors (mean classification accuracy = 83%).

The Influence of the Phonological Neighborhood Clustering Coefficient on Spoken Word Recognition

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Chan, Kit Ying; Vitevitch, Michael S.

2009-01-01

Clustering coefficient--a measure derived from the new science of networks--refers to the proportion of phonological neighbors of a target word that are also neighbors of each other. Consider the words "bat", "hat", and "can", all of which are neighbors of the word "cat"; the words "bat" and…

Word wheels

CERN Document Server

Clark, Kathryn

2013-01-01

Targeting the specific problems learners have with language structure, these multi-sensory exercises appeal to all age groups including adults. Exercises use sight, sound and touch and are also suitable for English as an Additional Lanaguage and Basic Skills students.Word Wheels includes off-the-shelf resources including lesson plans and photocopiable worksheets, an interactive CD with practice exercises, and support material for the busy teacher or non-specialist staff, as well as homework activities.

Preview Effects of Plausibility and Character Order in Reading Chinese Transposed Words: Evidence from Eye Movements

Science.gov (United States)

Yang, Jinmian

2013-01-01

The current paper examined the role of plausibility information in the parafovea for Chinese readers by using two-character transposed words (in which the order of the component characters is reversed but are still words). In two eye-tracking experiments, readers received a preview of a target word that was (1) identical to the target word, (2) a…

Modelling of retention of pesticides in reversed-phase high-performance liquid chromatography: Quantitative structure-retention relationships based on solute quantum-chemical descriptors and experimental (solvatochromic and spin-probe) mobile phase descriptors

International Nuclear Information System (INIS)

D'Archivio, Angelo Antonio; Ruggieri, Fabrizio; Mazzeo, Pietro; Tettamanti, Enzo

2007-01-01

A quantitative structure-retention relationship (QSRR) analysis based on multilinear regression (MLR) and artificial neural networks (ANNs) is carried out to model the combined effect of solute structure and eluent composition on the retention behaviour of pesticides in isocratic reversed-phase high-performance liquid chromatography (RP-HPLC). The octanol-water partition coefficient and four quantum chemical descriptors (the total dipole moment, the mean polarizability, the anisotropy of the polarizability and a descriptor of hydrogen-bonding based on the atomic charges on acidic and basic chemical functionalities) are considered as solute descriptors. In order to identify suitable mobile phase descriptors, encoding composition-dependent properties of both methanol- and acetonitrile-containing mobile phases, the Kamlet-Taft solvatochromic parameters (polarity-dipolarity, hydrogen-bond acidity and hydrogen-bond basicity, π * , α and β, respectively) and the 14 N hyperfine-splitting constant (a N ) of a spin-probe dissolved in the eluent are examined. A satisfactory description of mobile phase properties influencing the solute retention is provided by a N and β or alternatively π * and β. The two seven-parameter models resulting from combination of a N and β, or π * and β, with the solute descriptors were tested on a set of 26 pesticides representative of 10 different chemical classes in a wide range of mobile phase composition (30-60% (v/v) water-methanol and 30-70% (v/v) water-acetonitrile). Within the explored experimental range, the acidity of the eluent, as quantified by α, is almost constant, and this parameter is in fact irrelevant. The results reveal that a N and π * , that can be considered as interchangeable mobile phase descriptors, are the most influent variables in the respective models. The predictive ability of the proposed models, as tested on an external data set, is quite good (Q 2 close to 0.94) when a MLR approach is used, but the

Modelling of retention of pesticides in reversed-phase high-performance liquid chromatography: Quantitative structure-retention relationships based on solute quantum-chemical descriptors and experimental (solvatochromic and spin-probe) mobile phase descriptors

Energy Technology Data Exchange (ETDEWEB)

D' Archivio, Angelo Antonio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)]. E-mail: darchivi@univaq.it; Ruggieri, Fabrizio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy); Mazzeo, Pietro [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy); Tettamanti, Enzo [Dipartimento di Scienze Biomediche Comparate, Universita di Teramo, P.zzale A. Moro 45, 64100 Teramo (Italy)

2007-06-19

A quantitative structure-retention relationship (QSRR) analysis based on multilinear regression (MLR) and artificial neural networks (ANNs) is carried out to model the combined effect of solute structure and eluent composition on the retention behaviour of pesticides in isocratic reversed-phase high-performance liquid chromatography (RP-HPLC). The octanol-water partition coefficient and four quantum chemical descriptors (the total dipole moment, the mean polarizability, the anisotropy of the polarizability and a descriptor of hydrogen-bonding based on the atomic charges on acidic and basic chemical functionalities) are considered as solute descriptors. In order to identify suitable mobile phase descriptors, encoding composition-dependent properties of both methanol- and acetonitrile-containing mobile phases, the Kamlet-Taft solvatochromic parameters (polarity-dipolarity, hydrogen-bond acidity and hydrogen-bond basicity, {pi} {sup *}, {alpha} and {beta}, respectively) and the {sup 14}N hyperfine-splitting constant (a {sub N}) of a spin-probe dissolved in the eluent are examined. A satisfactory description of mobile phase properties influencing the solute retention is provided by a {sub N} and {beta} or alternatively {pi} {sup *} and {beta}. The two seven-parameter models resulting from combination of a {sub N} and {beta}, or {pi} {sup *} and {beta}, with the solute descriptors were tested on a set of 26 pesticides representative of 10 different chemical classes in a wide range of mobile phase composition (30-60% (v/v) water-methanol and 30-70% (v/v) water-acetonitrile). Within the explored experimental range, the acidity of the eluent, as quantified by {alpha}, is almost constant, and this parameter is in fact irrelevant. The results reveal that a {sub N} and {pi} {sup *}, that can be considered as interchangeable mobile phase descriptors, are the most influent variables in the respective models. The predictive ability of the proposed models, as tested on an

75 FR 2879 - Use of Tobacco Marketing Descriptors to Convey Modified Risk; Request for Comments

Science.gov (United States)

2010-01-19

... information, research, and ideas on tobacco product marketing descriptors that may be considered similar to...] Use of Tobacco Marketing Descriptors to Convey Modified Risk; Request for Comments AGENCY: Food and... authority to regulate the manufacture, marketing, and distribution of tobacco products to protect the public...

Word Meaning Frequencies Affect Negative Compatibility Effects In Masked Priming.

Science.gov (United States)

Brocher, Andreas; Koenig, Jean-Pierre

2016-01-01

Negative compatibility effects (NCEs)-that is, slower responses to targets in related than unrelated prime-target pairs, have been observed in studies using stimulus-response (S-R) priming with stimuli like arrows and plus signs. Although there is no consensus on the underlying mechanism, explanations tend to locate NCEs within the motor-response system. A characteristic property of perceptuo-motor NCEs is a biphasic pattern of activation: A brief period in which very briefly presented (typically) masked primes facilitate processing of related targets is followed by a phase of target processing impairment. In this paper, we present data that suggest that NCEs are not restricted to S-R priming with low-level visual stimuli: The brief (50 ms), backward masked (250 ms) presentation of ambiguous words (bank) leads to slower responses than baseline to words related to the more frequent (rob) but not less frequent meaning (swim). Importantly, we found that slowed responses are preceded by a short phase of response facilitation, replicating the biphasic pattern reported for arrows and plus signs. The biphasic pattern of priming and the fact that the NCEs were found only for target words that are related to their prime word's more frequent meaning has strong implications for any theory of NCEs that locate these effects exclusively within the motor-response system.

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

2016-08-29

In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

Unknown author

2016-01-01

In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.

Word translation entropy in translation

DEFF Research Database (Denmark)

Schaeffer, Moritz; Dragsted, Barbara; Hvelplund, Kristian Tangsgaard

2016-01-01

This study reports on an investigation into the relationship between the number of translation alternatives for a single word and eye movements on the source text. In addition, the effect of word order differences between source and target text on eye movements on the source text is studied....... In particular, the current study investigates the effect of these variables on early and late eye movement measures. Early eye movement measures are indicative of processes that are more automatic while late measures are more indicative of conscious processing. Most studies that found evidence of target...... language activation during source text reading in translation, i.e. co-activation of the two linguistic systems, employed late eye movement measures or reaction times. The current study therefore aims to investigate if and to what extent earlier eye movement measures in reading for translation show...

How Justice Can Affect Jury Training Abstract Words Promotes Generalization to Concrete Words in Patients with Aphasia

Science.gov (United States)

Sandberg, Chaleece; Kiran, Swathi

2014-01-01

Developing language treatments that not only improve trained items but also promote generalization to untrained items is a major focus in aphasia research. This study is a replication and extension of previous work that found that training abstract words in a particular context-category promotes generalization to concrete words but not vice versa (Kiran, Sandberg, & Abbott, 2009). Twelve persons with aphasia (5 female) with varying types and degrees of severity participated in a generative naming treatment based on the complexity account of treatment efficacy (CATE; Thompson, Shapiro, Kiran, & Sobecks, 2003). All participants were trained to generate abstract words in a particular context-category by analyzing the semantic features of the target words. Two other context-categories were used as controls. Ten of the twelve participants improved on the trained abstract words in the trained context-category. Eight of the ten participants who responded to treatment also generalized to concrete words in the same context-category. These results suggest that this treatment is both efficacious and efficient. We discuss possible mechanisms of training and generalization effects. PMID:24805853

morphological descriptors and micro satellite diversity among scarlet ...

African Journals Online (AJOL)

Prof. Adipala Ekwamu

distinctness, similarities and overlap among groups. The Kumba and Aculeatum groups are related for multi- locular characteristic of the fruits. The Nei's coefficients for morphological descriptors and SSR data indicated that S. aethiopicum groups showed a wide genetic base. MM1102 and MM457 showed high relatedness ...

Molecular Descriptors Family on Structure Activity Relationships 1. Review of the Methodology

Directory of Open Access Journals (Sweden)

Lorentz JÄNTSCHI

2005-01-01

Full Text Available This review cumulates the knowledge about the use of Molecular Descriptors Family usage on Structure Activity Relationships. The methodology is augmented through the general Structure Activity Relationships methodology. The obtained models in a series of five papers are quantitatively analyzed by comparing with previous reported results by using of the correlated correlations tests. The scores for a series of 13 data sets unpublished yet results are presented. Two unrestricted online access portals to the Molecular Descriptors Family Structure Activity Relationship models results are given.

Lagrangian descriptors of driven chemical reaction manifolds.

Science.gov (United States)

Craven, Galen T; Junginger, Andrej; Hernandez, Rigoberto

2017-08-01

The persistence of a transition state structure in systems driven by time-dependent environments allows the application of modern reaction rate theories to solution-phase and nonequilibrium chemical reactions. However, identifying this structure is problematic in driven systems and has been limited by theories built on series expansion about a saddle point. Recently, it has been shown that to obtain formally exact rates for reactions in thermal environments, a transition state trajectory must be constructed. Here, using optimized Lagrangian descriptors [G. T. Craven and R. Hernandez, Phys. Rev. Lett. 115, 148301 (2015)PRLTAO0031-900710.1103/PhysRevLett.115.148301], we obtain this so-called distinguished trajectory and the associated moving reaction manifolds on model energy surfaces subject to various driving and dissipative conditions. In particular, we demonstrate that this is exact for harmonic barriers in one dimension and this verification gives impetus to the application of Lagrangian descriptor-based methods in diverse classes of chemical reactions. The development of these objects is paramount in the theory of reaction dynamics as the transition state structure and its underlying network of manifolds directly dictate reactivity and selectivity.

Compositional descriptor-based recommender system for the materials discovery

Science.gov (United States)

Seko, Atsuto; Hayashi, Hiroyuki; Tanaka, Isao

2018-06-01

Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies the presence of numerous currently unknown compounds. A powerful machine-learning strategy is mandatory to discover new inorganic compounds from all chemical combinations. Herein we propose a descriptor-based recommender-system approach to estimate the relevance of chemical compositions where crystals can be formed [i.e., chemically relevant compositions (CRCs)]. In addition to data-driven compositional similarity used in the literature, the use of compositional descriptors as a prior knowledge is helpful for the discovery of new compounds. We validate our recommender systems in two ways. First, one database is used to construct a model, while another is used for the validation. Second, we estimate the phase stability for compounds at expected CRCs using density functional theory calculations.

Target Matching Recognition for Satellite Images Based on the Improved FREAK Algorithm

Directory of Open Access Journals (Sweden)

Yantong Chen

2016-01-01

Full Text Available Satellite remote sensing image target matching recognition exhibits poor robustness and accuracy because of the unfit feature extractor and large data quantity. To address this problem, we propose a new feature extraction algorithm for fast target matching recognition that comprises an improved feature from accelerated segment test (FAST feature detector and a binary fast retina key point (FREAK feature descriptor. To improve robustness, we extend the FAST feature detector by applying scale space theory and then transform the feature vector acquired by the FREAK descriptor from decimal into binary. We reduce the quantity of data in the computer and improve matching accuracy by using the binary space. Simulation test results show that our algorithm outperforms other relevant methods in terms of robustness and accuracy.

Clinical descriptors for the recognition of central sensitization pain in patients with knee osteoarthritis

DEFF Research Database (Denmark)

Lluch, Enrique; Nijs, Jo; Courtney, Carol A

2018-01-01

BACKGROUND: Despite growing awareness of the contribution of central pain mechanisms to knee osteoarthritis pain in a subgroup of patients, routine evaluation of central sensitization is yet to be incorporated into clinical practice. AIM: The objective of this perspective is to design a set...... of clinical descriptors for the recognition of central sensitization in patients with knee osteoarthritis that can be implemented in clinical practice. METHODS: A narrative review of original research papers was conducted by nine clinicians and researchers from seven different countries to reach agreement...... hyperalgesia, hypoesthesia and reduced vibration sense. CONCLUSIONS: This article describes a set of clinically relevant descriptors that might indicate the presence of central sensitization in patients with knee osteoarthritis in clinical practice. Although based on research data, the descriptors proposed...

Aging effects on ERP correlates of emotional word discrimination

NARCIS (Netherlands)

Molnar, M.; Toth, B.; Boha, R.; Gaal, Z.A.; Kardos, Z.; File, B.; Stam, C.J.

2013-01-01

ObjectiveTo explore age-, and valence specific ERP-characteristics of word-discrimination processes. Methods: A group of young (mean age: 21.26. yrs) and elderly (mean age: 65.73. yrs) individuals participated. The task was to respond to a word (target) with valence (neutral, negative, positive) and

Partial solvation parameters and LSER molecular descriptors

International Nuclear Information System (INIS)

Panayiotou, Costas

2012-01-01

Graphical abstract: The one-to-one correspondence of LSER molecular descriptors and partial solvation parameters (PSPs) for propionic acid. Highlights: ► Quantum-mechanics based development of a new QSPR predictive method. ► One-to-one correspondence of partial solvation parameters and LSER molecular descriptors. ► Development of alternative routes for the determination of partial solvation parameters and solubility parameters. ► Expansion and enhancement of solubility parameter approach. - Abstract: The partial solvation parameters (PSP) have been defined recently, on the basis of the insight derived from modern quantum chemical calculations, in an effort to overcome some of the inherent restrictions of the original definition of solubility parameter and expand its range of applications. The present work continues along these lines and introduces two new solvation parameters, the van der Waals and the polarity/refractivity ones, which may replace both of the former dispersion and polar PSPs. Thus, one may use either the former scheme of PSPs (dispersion, polar, acidic, and basic) or, equivalently, the new scheme (van der Waals, polarity/refractivity, acidic, basic). The new definitions are made in a simple and straightforward manner and, thus, the strength and appeal of the widely accepted concept of solubility parameter is preserved. The inter-relations of the various PSPs are critically discussed and their values are tabulated for a variety of common substances. The advantage of the new scheme of PSPs is the bridge that makes with the corresponding Abraham’s LSER descriptors. With this bridge, one may exchange information between PSPs, LSER experimental scales, and quantum mechanics calculations such as via the COSMO-RS theory. The proposed scheme is a predictive one and it is applicable to, both, homo-solvated and hetero-solvated compounds. The new scheme is tested for the calculation of activity coefficients at infinite dilution, for octanol

Development and validation of a set of German stimulus- and target words for an attachment related semantic priming paradigm.

Directory of Open Access Journals (Sweden)

Anke Maatz

Full Text Available Experimental research in adult attachment theory is faced with the challenge to adequately activate the adult attachment system. In view of the multitude of methods employed for this purpose so far, this paper suggests to further make use of the methodological advantages of semantic priming. In order to enable the use of such a paradigm in a German speaking context, a set of German words belonging to the semantic categories 'interpersonal closeness', 'interpersonal distance' and 'neutral' were identified and their semantics were validated combining production- and rating method. 164 university students answered corresponding online-questionnaires. Ratings were analysed using analysis of variance (ANOVA and cluster analysis from which three clearly distinct groups emerged. Beyond providing validated stimulus- and target words which can be used to activate the adult attachment system in a semantic priming paradigm, the results of this study point at important links between attachment and stress which call for further investigation in the future.

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

Directory of Open Access Journals (Sweden)

Lei Qin

2014-05-01

Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

Influence of Lexical Factors on Word-Finding Accuracy, Error Patterns, and Substitution Types

Science.gov (United States)

Newman, Rochelle S.; German, Diane J.; Jagielko, Jennifer R.

2018-01-01

This retrospective, exploratory investigation examined the types of target words that 66 children with/without word-finding difficulties (WFD) had difficulty naming, and the types of errors they made. Words were studied with reference to lexical factors (LFs) that might influence naming performance: word frequency, familiarity, length, phonotactic…

Using probabilistic model as feature descriptor on a smartphone device for autonomous navigation of unmanned ground vehicles

Science.gov (United States)

Desai, Alok; Lee, Dah-Jye

2013-12-01

There has been significant research on the development of feature descriptors in the past few years. Most of them do not emphasize real-time applications. This paper presents the development of an affine invariant feature descriptor for low resource applications such as UAV and UGV that are equipped with an embedded system with a small microprocessor, a field programmable gate array (FPGA), or a smart phone device. UAV and UGV have proven suitable for many promising applications such as unknown environment exploration, search and rescue operations. These applications required on board image processing for obstacle detection, avoidance and navigation. All these real-time vision applications require a camera to grab images and match features using a feature descriptor. A good feature descriptor will uniquely describe a feature point thus allowing it to be correctly identified and matched with its corresponding feature point in another image. A few feature description algorithms are available for a resource limited system. They either require too much of the device's resource or too much simplification on the algorithm, which results in reduction in performance. This research is aimed at meeting the needs of these systems without sacrificing accuracy. This paper introduces a new feature descriptor called PRObabilistic model (PRO) for UGV navigation applications. It is a compact and efficient binary descriptor that is hardware-friendly and easy for implementation.

Arabic word recognizer for mobile applications

Science.gov (United States)

Khanna, Nitin; Abdollahian, Golnaz; Brame, Ben; Boutin, Mireille; Delp, Edward J.

2011-03-01

When traveling in a region where the local language is not written using a "Roman alphabet," translating written text (e.g., documents, road signs, or placards) is a particularly difficult problem since the text cannot be easily entered into a translation device or searched using a dictionary. To address this problem, we are developing the "Rosetta Phone," a handheld device (e.g., PDA or mobile telephone) capable of acquiring an image of the text, locating the region (word) of interest within the image, and producing both an audio and a visual English interpretation of the text. This paper presents a system targeted for interpreting words written in Arabic script. The goal of this work is to develop an autonomous, segmentation-free Arabic phrase recognizer, with computational complexity low enough to deploy on a mobile device. A prototype of the proposed system has been deployed on an iPhone with a suitable user interface. The system was tested on a number of noisy images, in addition to the images acquired from the iPhone's camera. It identifies Arabic words or phrases by extracting appropriate features and assigning "codewords" to each word or phrase. On a dictionary of 5,000 words, the system uniquely mapped (word-image to codeword) 99.9% of the words. The system has a 82% recognition accuracy on images of words captured using the iPhone's built-in camera.

Morpho-phonemic analysis boosts word reading for adult struggling readers.

Science.gov (United States)

Gray, Susan H; Ehri, Linnea C; Locke, John L

2018-01-01

A randomized control trial compared the effects of two kinds of vocabulary instruction on component reading skills of adult struggling readers. Participants seeking alternative high school diplomas received 8 h of scripted tutoring to learn forty academic vocabulary words embedded within a civics curriculum. They were matched for language background and reading levels, then randomly assigned to either morpho-phonemic analysis teaching word origins, morpheme and syllable structures, or traditional whole word study teaching multiple sentence contexts, meaningful connections, and spellings. Both groups made comparable gains in learning the target words, but the morpho-phonemic group showed greater gains in reading unfamiliar words on standardized tests of word reading, including word attack and word recognition. Findings support theories of word learning and literacy that promote explicit instruction in word analysis to increase poor readers' linguistic awareness by revealing connections between morphological, phonological, and orthographic structures within words.

Enrichment of true positives from structural alerts through the use of novel atomic fragment based descriptors

DEFF Research Database (Denmark)

Long, A.; Rydberg, Patrik

2013-01-01

To enhance the discrimination rate for methods applying structural alerts and biotransformation rules in the prediction of toxicity and drug metabolism we have developed a set of novel fragment based atomic descriptors. These atomic descriptors encode the properties of the fragments separating an...

An Analysis of Mongolian Culture-Loaded Words and Their Translation Strategies

Science.gov (United States)

Wang, Jian-Jun; He, Long

2014-01-01

With massive cultural exchanges in the world, the translation of culture-loaded words is drawing the attention of translators. Because of different cultural backgrounds and mentalities, the translation of culture-loaded words may lead to misunderstanding or confusion to target readers. Thus, a good mastery of culture-loaded words is a must for…

Effects of Opportunities for Word Retrieval during Second Language Vocabulary Learning

Science.gov (United States)

Barcroft, Joe

2007-01-01

Research suggests that memory for an item improves when one is allowed to retrieve the item (Slamecka & Graf, 1978). This study explored benefits of providing opportunities for target-word retrieval during second language vocabulary learning. English speakers studied new Spanish words while viewing 24 word-picture pairs. They first viewed all 24…

The time course of lexical competition during spoken word recognition in Mandarin Chinese: an event-related potential study.

Science.gov (United States)

Huang, Xianjun; Yang, Jin-Chen

2016-01-20

The present study investigated the effect of lexical competition on the time course of spoken word recognition in Mandarin Chinese using a unimodal auditory priming paradigm. Two kinds of competitive environments were designed. In one session (session 1), only the unrelated and the identical primes were presented before the target words. In the other session (session 2), besides the two conditions in session 1, the target words were also preceded by the cohort primes that have the same initial syllables as the targets. Behavioral results showed an inhibitory effect of the cohort competitors (primes) on target word recognition. The event-related potential results showed that the spoken word recognition processing in the middle and late latency windows is modulated by whether the phonologically related competitors are presented or not. Specifically, preceding activation of the competitors can induce direct competitions between multiple candidate words and lead to increased processing difficulties, primarily at the word disambiguation and selection stage during Mandarin Chinese spoken word recognition. The current study provided both behavioral and electrophysiological evidences for the lexical competition effect among the candidate words during spoken word recognition.

Object tracking on mobile devices using binary descriptors

Science.gov (United States)

Savakis, Andreas; Quraishi, Mohammad Faiz; Minnehan, Breton

2015-03-01

With the growing ubiquity of mobile devices, advanced applications are relying on computer vision techniques to provide novel experiences for users. Currently, few tracking approaches take into consideration the resource constraints on mobile devices. Designing efficient tracking algorithms and optimizing performance for mobile devices can result in better and more efficient tracking for applications, such as augmented reality. In this paper, we use binary descriptors, including Fast Retina Keypoint (FREAK), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent Features (BRIEF), and Binary Robust Invariant Scalable Keypoints (BRISK) to obtain real time tracking performance on mobile devices. We consider both Google's Android and Apple's iOS operating systems to implement our tracking approach. The Android implementation is done using Android's Native Development Kit (NDK), which gives the performance benefits of using native code as well as access to legacy libraries. The iOS implementation was created using both the native Objective-C and the C++ programing languages. We also introduce simplified versions of the BRIEF and BRISK descriptors that improve processing speed without compromising tracking accuracy.

SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

Science.gov (United States)

Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

2013-03-01

Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of the Fourier descriptors method to the morphological classification of particles in geological materials

International Nuclear Information System (INIS)

Manzanas Lopez, J.; Santiago Buey, C.

2010-01-01

This study focuses on the use of Fourier descriptors to quantitatively describe the morphology of particles aggregates or pores in geological materials. Firstly, the mathematical fundaments of the method are explained. Then, the Fourier descriptors method is applied to the Krumbein Scale, a system of measuring roundness and sphericity of particles. the analysis of the comparison shows that there is good correlation between the Sphericity parameter at the Krumbein classifications and the value of the modulus of the Fourier descriptor No-1. This good correlation, along with the mathematical precision which allows to prevent subjective valorisations in the morphological description, corroborates the validity of the method to quantify the sphericity elongation of particles in geological materials. (Author) 12 refs.

The Penefit of Salience: Salient Accented, but Not Unaccented Words Reveal Accent Adaptation Effects.

Science.gov (United States)

Grohe, Ann-Kathrin; Weber, Andrea

2016-01-01

In two eye-tracking experiments, the effects of salience in accent training and speech accentedness on spoken-word recognition were investigated. Salience was expected to increase a stimulus' prominence and therefore promote learning. A training-test paradigm was used on native German participants utilizing an artificial German accent. Salience was elicited by two different criteria: production and listening training as a subjective criterion and accented (Experiment 1) and canonical test words (Experiment 2) as an objective criterion. During training in Experiment 1, participants either read single German words out loud and deliberately devoiced initial voiced stop consonants (e.g., Balken-"beam" pronounced as (*) Palken), or they listened to pre-recorded words with the same accent. In a subsequent eye-tracking experiment, looks to auditorily presented target words with the accent were analyzed. Participants from both training conditions fixated accented target words more often than a control group without training. Training was identical in Experiment 2, but during test, canonical German words that overlapped in onset with the accented words from training were presented as target words (e.g., Palme-"palm tree" overlapped in onset with the training word (*) Palken) rather than accented words. This time, no training effect was observed; recognition of canonical word forms was not affected by having learned the accent. Therefore, accent learning was only visible when the accented test tokens in Experiment 1, which were not included in the test of Experiment 2, possessed sufficient salience based on the objective criterion "accent." These effects were not modified by the subjective criterion of salience from the training modality.

The Effects of Receptive and Productive Learning of Word Pairs on Vocabulary Knowledge

Science.gov (United States)

Webb, Stuart

2009-01-01

English as a foreign language students in Japan learned target words in word pairs receptively and productively. Five aspects of vocabulary knowledge--orthography, association, syntax, grammatical functions, and meaning and form--were each measured by receptive and productive tests. The study uses an innovative methodology in that each target word…

Probability and Surprisal in Auditory Comprehension of Morphologically Complex Words

DEFF Research Database (Denmark)

Balling, Laura Winther; Baayen, R. Harald

2012-01-01

Two auditory lexical decision experiments document for morphologically complex words two points at which the probability of a target word given the evidence shifts dramatically. The first point is reached when morphologically unrelated competitors are no longer compatible with the evidence. Adapt...

Ant colony optimization as a descriptor selection in QSPR modeling: Estimation of the λmax of anthraquinones-based dyes

Directory of Open Access Journals (Sweden)

Morteza Atabati

2016-09-01

Full Text Available Quantitative structure–property relationship (QSPR studies based on ant colony optimization (ACO were carried out for the prediction of λmax of 9,10-anthraquinone derivatives. ACO is a meta-heuristic algorithm, which is derived from the observation of real ants and proposed to feature selection. After optimization of 3D geometry of structures by the semi-empirical quantum-chemical calculation at AM1 level, different descriptors were calculated by the HyperChem and Dragon softwares (1514 descriptors. A major problem of QSPR is the high dimensionality of the descriptor space; therefore, descriptor selection is the most important step. In this paper, an ACO algorithm was used to select the best descriptors. Then selected descriptors were applied for model development using multiple linear regression. The average absolute relative deviation and correlation coefficient for the calibration set were obtained as 3.3% and 0.9591, respectively, while the average absolute relative deviation and correlation coefficient for the prediction set were obtained as 5.0% and 0.9526, respectively. The results showed that the applied procedure is suitable for prediction of λmax of 9,10-anthraquinone derivatives.

Structure-Activity Relationships on the Molecular Descriptors Family Project at the End

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Lorentz JÄNTSCHI

2007-12-01

Full Text Available Molecular Descriptors Family (MDF on the Structure-Activity Relationships (SAR, a promising approach in investigation and quantification of the link between 2D and 3D structural information and the activity, and its potential in the analysis of the biological active compounds is summarized. The approach, attempts to correlate molecular descriptors family generated and calculated on a set of biological active compounds with their observed activity. The estimation as well as prediction abilities of the approach are presented. The obtained MDF SAR models can be used to predict the biological activity of unknown substrates in a series of compounds.

Simple knowledge-based descriptors to predict protein-ligand interactions. Methodology and validation

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Nissink, J. Willem M.; Verdonk, Marcel L.; Klebe, Gerhard

2000-11-01

A new type of shape descriptor is proposed to describe the spatial orientation for non-covalent interactions. It is built from simple, anisotropic Gaussian contributions that are parameterised by 10 adjustable values. The descriptors have been used to fit propensity distributions derived from scatter data stored in the IsoStar database. This database holds composite pictures of possible interaction geometries between a common central group and various interacting moieties, as extracted from small-molecule crystal structures. These distributions can be related to probabilities for the occurrence of certain interaction geometries among different functional groups. A fitting procedure is described that generates the descriptors in a fully automated way. For this purpose, we apply a similarity index that is tailored to the problem, the Split Hodgkin Index. It accounts for the similarity in regions of either high or low propensity in a separate way. Although dependent on the division into these two subregions, the index is robust and performs better than the regular Hodgkin index. The reliability and coverage of the fitted descriptors was assessed using SuperStar. SuperStar usually operates on the raw IsoStar data to calculate propensity distributions, e.g., for a binding site in a protein. For our purpose we modified the code to have it operate on our descriptors instead. This resulted in a substantial reduction in calculation time (factor of five to eight) compared to the original implementation. A validation procedure was performed on a set of 130 protein-ligand complexes, using four representative interacting probes to map the properties of the various binding sites: ammonium nitrogen, alcohol oxygen, carbonyl oxygen, and methyl carbon. The predicted `hot spots' for the binding of these probes were compared to the actual arrangement of ligand atoms in experimentally determined protein-ligand complexes. Results indicate that the version of SuperStar that applies to

Toddlers' sensitivity to within-word coarticulation during spoken word recognition: Developmental differences in lexical competition.

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Zamuner, Tania S; Moore, Charlotte; Desmeules-Trudel, Félix

2016-12-01

To understand speech, listeners need to be able to decode the speech stream into meaningful units. However, coarticulation causes phonemes to differ based on their context. Because coarticulation is an ever-present component of the speech stream, it follows that listeners may exploit this source of information for cues to the identity of the words being spoken. This research investigates the development of listeners' sensitivity to coarticulation cues below the level of the phoneme in spoken word recognition. Using a looking-while-listening paradigm, adults and 2- and 3-year-old children were tested on coarticulation cues that either matched or mismatched the target. Both adults and children predicted upcoming phonemes based on anticipatory coarticulation to make decisions about word identity. The overall results demonstrate that coarticulation cues are a fundamental component of children's spoken word recognition system. However, children did not show the same resolution as adults of the mismatching coarticulation cues and competitor inhibition, indicating that children's processing systems are still developing. Copyright © 2016 Elsevier Inc. All rights reserved.

Excitatory and inhibitory priming by attended and ignored non-recycled words with monolinguals and bilinguals.

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Neumann, Ewald; Nkrumah, Ivy K; Chen, Zhe

2018-03-03

Experiments examining identity priming from attended and ignored novel words (words that are used only once except when repetition is required due to experimental manipulation) in a lexical decision task are reported. Experiment 1 tested English monolinguals whereas Experiment 2 tested Twi (a native language of Ghana, Africa)-English bilinguals. Participants were presented with sequential pairs of stimuli composed of a prime followed by a probe, with each containing two items. The participants were required to name the target word in the prime display, and to make a lexical decision to the target item in the probe display. On attended repetition (AR) trials the probe target item was identical to the target word on the preceding attentional display. On ignored repetition (IR) trials the probe target item was the same as the distractor word in the preceding attentional display. The experiments produced facilitated (positive) priming in the AR trials and delayed (negative) priming in the IR trials. Significantly, the positive and negative priming effects also replicated across both monolingual and bilingual groups of participants, despite the fact that the bilinguals were responding to the task in their non-dominant language.

Feedback nash equilibria for linear quadratic descriptor differential games

NARCIS (Netherlands)

Engwerda, J.C.; Salmah, S.

2012-01-01

In this paper, we consider the non-cooperative linear feedback Nash quadratic differential game with an infinite planning horizon for descriptor systems of index one. The performance function is assumed to be indefinite. We derive both necessary and sufficient conditions under which this game has a

Feedback Nash Equilibria for Linear Quadratic Descriptor Differential Games

NARCIS (Netherlands)

Engwerda, J.C.; Salmah, Y.

2010-01-01

In this note we consider the non-cooperative linear feedback Nash quadratic differential game with an infinite planning horizon for descriptor systems of index one. The performance function is assumed to be indefinite. We derive both necessary and sufficient conditions under which this game has a

Combinatorics on words Christoffel words and repetitions in words

CERN Document Server

Berstel, Jean; Reutenauer, Christophe; Saliola, Franco V

2008-01-01

The two parts of this text are based on two series of lectures delivered by Jean Berstel and Christophe Reutenauer in March 2007 at the Centre de Recherches Mathématiques, Montréal, Canada. Part I represents the first modern and comprehensive exposition of the theory of Christoffel words. Part II presents numerous combinatorial and algorithmic aspects of repetition-free words stemming from the work of Axel Thue-a pioneer in the theory of combinatorics on words. A beginner to the theory of combinatorics on words will be motivated by the numerous examples, and the large variety of exercises, which make the book unique at this level of exposition. The clean and streamlined exposition and the extensive bibliography will also be appreciated. After reading this book, beginners should be ready to read modern research papers in this rapidly growing field and contribute their own research to its development. Experienced readers will be interested in the finitary approach to Sturmian words that Christoffel words offe...

Uncovering the Geometry of Barrierless Reactions Using Lagrangian Descriptors.

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Junginger, Andrej; Hernandez, Rigoberto

2016-03-03

Transition-state theories describing barrierless chemical reactions, or more general activated problems, are often hampered by the lack of a saddle around which the dividing surface can be constructed. For example, the time-dependent transition-state trajectory uncovering the nonrecrossing dividing surface in thermal reactions in the framework of the Langevin equation has relied on perturbative approaches in the vicinity of the saddle. We recently obtained an alternative approach using Lagrangian descriptors to construct time-dependent and recrossing-free dividing surfaces. This is a nonperturbative approach making no reference to a putative saddle. Here we show how the Lagrangian descriptor can be used to obtain the transition-state geometry of a dissipated and thermalized reaction across barrierless potentials. We illustrate the method in the case of a 1D Brownian motion for both barrierless and step potentials; however, the method is not restricted and can be directly applied to different kinds of potentials and higher dimensional systems.

Cross-cultural evidence for multimodal motherese: Asian Indian mothers' adaptive use of synchronous words and gestures.

Science.gov (United States)

Gogate, Lakshmi; Maganti, Madhavilatha; Bahrick, Lorraine E

2015-01-01

In a quasi-experimental study, 24 Asian Indian mothers were asked to teach novel (target) names for two objects and two actions to their children of three different levels of lexical mapping development: prelexical (5-8 months), early lexical (9-17 months), and advanced lexical (20-43 months). Target naming (n=1482) and non-target naming (other, n=2411) were coded for synchronous spoken words and object motion (multimodal motherese) and other naming styles. Indian mothers abundantly used multimodal motherese with target words to highlight novel word-referent relations, paralleling earlier findings from American mothers. They used it with target words more often for prelexical infants than for advanced lexical children and to name target actions later in children's development. Unlike American mothers, Indian mothers also abundantly used multimodal motherese to name target objects later in children's development. Finally, monolingual mothers who spoke a verb-dominant Indian language used multimodal motherese more often than bilingual mothers who also spoke noun-dominant English to their children. The findings suggest that within a dynamic and reciprocal mother-infant communication system, multimodal motherese adapts to unify novel words and referents across cultures. It adapts to children's level of lexical development and to ambient language-specific lexical dominance hierarchies. Copyright © 2014 Elsevier Inc. All rights reserved.

Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

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Genyun Sun

2017-08-01

Full Text Available The region merging algorithm is a widely used segmentation technique for very high resolution (VHR remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods

Defining a Conceptual Topography of Word Concreteness: Clustering Properties of Emotion, Sensation, and Magnitude among 750 English Words

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Joshua Troche

2017-10-01

Full Text Available Cognitive science has a longstanding interest in the ways that people acquire and use abstract vs. concrete words (e.g., truth vs. piano. One dominant theory holds that abstract and concrete words are subserved by two parallel semantic systems. We recently proposed an alternative account of abstract-concrete word representation premised upon a unitary, high dimensional semantic space wherein word meaning is nested. We hypothesize that a range of cognitive and perceptual dimensions (e.g., emotion, time, space, color, size, visual form bound this space, forming a conceptual topography. Here we report a normative study where we examined the clustering properties of a sample of English words (N = 750 spanning a spectrum of concreteness in a continuous manner from highly abstract to highly concrete. Participants (N = 328 rated each target word on a range of 14 cognitive dimensions (e.g., color, emotion, valence, polarity, motion, space. The dimensions reduced to three factors: Endogenous factor, Exogenous factor, and Magnitude factor. Concepts were plotted in a unified, multimodal space with concrete and abstract concepts along a continuous continuum. We discuss theoretical implications and practical applications of this dataset. These word norms are freely available for download and use at http://www.reilly-coglab.com/data/.

Defining a Conceptual Topography of Word Concreteness: Clustering Properties of Emotion, Sensation, and Magnitude among 750 English Words.

Science.gov (United States)

Troche, Joshua; Crutch, Sebastian J; Reilly, Jamie

2017-01-01

Cognitive science has a longstanding interest in the ways that people acquire and use abstract vs. concrete words (e.g., truth vs. piano). One dominant theory holds that abstract and concrete words are subserved by two parallel semantic systems. We recently proposed an alternative account of abstract-concrete word representation premised upon a unitary, high dimensional semantic space wherein word meaning is nested. We hypothesize that a range of cognitive and perceptual dimensions (e.g., emotion, time, space, color, size, visual form) bound this space, forming a conceptual topography. Here we report a normative study where we examined the clustering properties of a sample of English words ( N = 750) spanning a spectrum of concreteness in a continuous manner from highly abstract to highly concrete. Participants ( N = 328) rated each target word on a range of 14 cognitive dimensions (e.g., color, emotion, valence, polarity, motion, space). The dimensions reduced to three factors: Endogenous factor, Exogenous factor, and Magnitude factor. Concepts were plotted in a unified, multimodal space with concrete and abstract concepts along a continuous continuum. We discuss theoretical implications and practical applications of this dataset. These word norms are freely available for download and use at http://www.reilly-coglab.com/data/.

On the Awareness of English Polysemous Words by Arabic-Speaking EFL Learners

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Sulafah Abdul Salam Alnamer

2017-04-01

Full Text Available This study measures the extent to which Arabic-speaking EFL learners are aware of polysemy in English. It also investigates whether the English proficiency level of Arabic-speaking EFL learners plays a role in their ability to distinguish between the various meanings of English polysemous words, and whether they face problems when they encounter these words in unusual contexts (i.e. the contexts that employ the extended meanings of the target polysemous words. To these ends, a translation test in which the participants were asked to give full Arabic translation for fifteen English sentences was designed. The words open, run, and make were the target polysemous words in this study. The Results show that Arabic-speaking EFL learners have little awareness of polysemy in English, and their English proficiency level does play a role in their ability to distinguish between the different meanings of English polysemous words. It was also found that Arabic-speaking EFL learners have no problems guessing the primary meaning of the English polysemous words. However, they face difficulty guessing the extended meanings of polysemous words in unusual contexts. Moreover, some Arabic-speaking EFL learners can guess the extended meanings of the polysemous words they encounter in familiar contexts, or when they understand some cues provided to disambiguate these words. This study concludes with some pedagogical implications and recommendations for further studies.

The Relationships among Cognitive Correlates and Irregular Word, Non-Word, and Word Reading

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Abu-Hamour, Bashir; University, Mu'tah; Urso, Annmarie; Mather, Nancy

2012-01-01

This study explored four hypotheses: (a) the relationships among rapid automatized naming (RAN) and processing speed (PS) to irregular word, non-word, and word reading; (b) the predictive power of various RAN and PS measures, (c) the cognitive correlates that best predicted irregular word, non-word, and word reading, and (d) reading performance of…

Recurring Utterances - Targeting a Breakthrough

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Jacqueline Stark

2014-05-01

The most interesting phenomenon is KB’s production of words from former sessions indicating that they are still ‘active’ and the production of completely novel incorrect words. The observable features indicate that immediate auditory processing is possible in the form of repeating target words. However, as soon as KB must retrieve information from the (semantic lexicon, even after being able to correctly ‘repeat’ the target word several times, he responds with a RU, perseveration, or paraphasia. Several of his productions can be characterized as aphasic confabulations which stem from a memory gap. Thus, although KB’s language impairment is severe, his responses across time indicate that step-by-step a breakthrough is being made.

An ERP investigation of visual word recognition in syllabary scripts.

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Okano, Kana; Grainger, Jonathan; Holcomb, Phillip J

2013-06-01

The bimodal interactive-activation model has been successfully applied to understanding the neurocognitive processes involved in reading words in alphabetic scripts, as reflected in the modulation of ERP components in masked repetition priming. In order to test the generalizability of this approach, in the present study we examined word recognition in a different writing system, the Japanese syllabary scripts hiragana and katakana. Native Japanese participants were presented with repeated or unrelated pairs of Japanese words in which the prime and target words were both in the same script (within-script priming, Exp. 1) or were in the opposite script (cross-script priming, Exp. 2). As in previous studies with alphabetic scripts, in both experiments the N250 (sublexical processing) and N400 (lexical-semantic processing) components were modulated by priming, although the time course was somewhat delayed. The earlier N/P150 effect (visual feature processing) was present only in "Experiment 1: Within-script priming", in which the prime and target words shared visual features. Overall, the results provide support for the hypothesis that visual word recognition involves a generalizable set of neurocognitive processes that operate in similar manners across different writing systems and languages, as well as pointing to the viability of the bimodal interactive-activation framework for modeling such processes.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

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Mingzhe Su

Full Text Available The traditional scale invariant feature transform (SIFT method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

Science.gov (United States)

Su, Mingzhe; Ma, Yan; Zhang, Xiangfen; Wang, Yan; Zhang, Yuping

2017-01-01

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

Determination of descriptors for polycyclic aromatic hydrocarbons and related compounds by chromatographic methods and liquid-liquid partition in totally organic biphasic systems.

Science.gov (United States)

Ariyasena, Thiloka C; Poole, Colin F

2014-09-26

Retention factors on several columns and at various temperatures using gas chromatography and from reversed-phase liquid chromatography on a SunFire C18 column with various mobile phase compositions containing acetonitrile, methanol and tetrahydrofuran as strength adjusting solvents are combined with liquid-liquid partition coefficients in totally organic biphasic systems to calculate descriptors for 23 polycyclic aromatic hydrocarbons and eighteen related compounds of environmental interest. The use of a consistent protocol for the above measurements provides descriptors that are more self consistent for the estimation of physicochemical properties (octanol-water, air-octanol, air-water, aqueous solubility, and subcooled liquid vapor pressure). The descriptor in this report tend to have smaller values for the L and E descriptors and random differences in the B and S descriptors compared with literature sources. A simple atom fragment constant model is proposed for the estimation of descriptors from structure for polycyclic aromatic hydrocarbons. The new descriptors show no bias in the prediction of the air-water partition coefficient for polycyclic aromatic hydrocarbons unlike the literature values. Copyright © 2014 Elsevier B.V. All rights reserved.

Word Domain Disambiguation via Word Sense Disambiguation

Energy Technology Data Exchange (ETDEWEB)

Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.

2006-06-04

Word subject domains have been widely used to improve the perform-ance of word sense disambiguation al-gorithms. However, comparatively little effort has been devoted so far to the disambiguation of word subject do-mains. The few existing approaches have focused on the development of al-gorithms specific to word domain dis-ambiguation. In this paper we explore an alternative approach where word domain disambiguation is achieved via word sense disambiguation. Our study shows that this approach yields very strong results, suggesting that word domain disambiguation can be ad-dressed in terms of word sense disam-biguation with no need for special purpose algorithms.

CALCULATION OF COEFFICIENT OF SHARING OCTANOL-WATER OF ORGANIC COMPOUNDS USING MOLECULAR DESCRIPTORS

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B. Souyei

2010-12-01

Full Text Available A quantitative structure-property relationship (QSPR study is carried out to develop correlations that relate the molecular structures of organic compounds to their Octanol- Water partition coefficients, Kow , using molecular descriptors. The correlations are simple in application with good accuracy, which provide an easy, direct and relatively accurate way to calculate Kow. Such calculation gives us a model that gives results in remarkable correlation with the descriptors of blocks fragments of the atom-centered and functional groups (R2 = 0.949, δ = 0477 (R2 = 0.926,δ = 0,548 respectively.

Cognitive Predictors of Spoken Word Recognition in Children With and Without Developmental Language Disorders.

Science.gov (United States)

Evans, Julia L; Gillam, Ronald B; Montgomery, James W

2018-05-10

This study examined the influence of cognitive factors on spoken word recognition in children with developmental language disorder (DLD) and typically developing (TD) children. Participants included 234 children (aged 7;0-11;11 years;months), 117 with DLD and 117 TD children, propensity matched for age, gender, socioeconomic status, and maternal education. Children completed a series of standardized assessment measures, a forward gating task, a rapid automatic naming task, and a series of tasks designed to examine cognitive factors hypothesized to influence spoken word recognition including phonological working memory, updating, attention shifting, and interference inhibition. Spoken word recognition for both initial and final accept gate points did not differ for children with DLD and TD controls after controlling target word knowledge in both groups. The 2 groups also did not differ on measures of updating, attention switching, and interference inhibition. Despite the lack of difference on these measures, for children with DLD, attention shifting and interference inhibition were significant predictors of spoken word recognition, whereas updating and receptive vocabulary were significant predictors of speed of spoken word recognition for the children in the TD group. Contrary to expectations, after controlling for target word knowledge, spoken word recognition did not differ for children with DLD and TD controls; however, the cognitive processing factors that influenced children's ability to recognize the target word in a stream of speech differed qualitatively for children with and without DLDs.

Cross-situational statistically based word learning intervention for late-talking toddlers.

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Alt, Mary; Meyers, Christina; Oglivie, Trianna; Nicholas, Katrina; Arizmendi, Genesis

2014-01-01

To explore the efficacy of a word learning intervention for late-talking toddlers that is based on principles of cross-situational statistical learning. Four late-talking toddlers were individually provided with 7-10 weeks of bi-weekly word learning intervention that incorporated principles of cross-situational statistical learning. Treatment was input-based meaning that, aside from initial probes, children were not asked to produce any language during the sessions. Pre-intervention data included parent-reported measures of productive vocabulary and language samples. Data collected during intervention included production on probes, spontaneous production during treatment, and parent report of words used spontaneously at home. Data were analyzed for number of target words learned relative to control words, effect sizes, and pre-post treatment vocabulary measures. All children learned more target words than control words and, on average, showed a large treatment effect size. Children made pre-post vocabulary gains, increasing their percentile scores on the MCDI, and demonstrated a rate of word learning that was faster than rates found in the literature. Cross-situational statistically based word learning intervention has the potential to improve vocabulary learning in late-talking toddlers. Limitations on interpretation are also discussed. Readers will describe what cross-situational learning is and how it might apply to treatment. They will identify how including lexical and contextual variability in a word learning intervention for toddlers affected treatment outcomes. They will also recognize evidence of improved rate of vocabulary learning following treatment. Copyright © 2014 Elsevier Inc. All rights reserved.

Control Configuration Selection for Multivariable Descriptor Systems

DEFF Research Database (Denmark)

Shaker, Hamid Reza; Stoustrup, Jakob

2012-01-01

Control configuration selection is the procedure of choosing the appropriate input and output pairs for the design of SISO (or block) controllers. This step is an important prerequisite for a successful industrial control strategy. In industrial practices it is often the case that the system, whi...... is that it can be used to propose a richer sparse or block diagonal controller structure. The interaction measure is used for control configuration selection of the linearized CSTR model with descriptor from....

Attributes and descriptors for building performance evaluation

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S. Gopikrishnan

2017-12-01

In order to obtain the right feedback in levels of satisfaction with respect to these attributes, there is a need to have appropriate descriptors for incorporation in a survey instrument. This paper identifies attributes that indicate building performance and provides simple description of these attributes based on which items can be generated for a questionnaire. Such items can enable any user/occupant to easily understand the characteristics of these attributes and offer an objective feedback during questionnaire survey.

Static sign language recognition using 1D descriptors and neural networks

Science.gov (United States)

Solís, José F.; Toxqui, Carina; Padilla, Alfonso; Santiago, César

2012-10-01

A frame work for static sign language recognition using descriptors which represents 2D images in 1D data and artificial neural networks is presented in this work. The 1D descriptors were computed by two methods, first one consists in a correlation rotational operator.1 and second is based on contour analysis of hand shape. One of the main problems in sign language recognition is segmentation; most of papers report a special color in gloves or background for hand shape analysis. In order to avoid the use of gloves or special clothing, a thermal imaging camera was used to capture images. Static signs were picked up from 1 to 9 digits of American Sign Language, a multilayer perceptron reached 100% recognition with cross-validation.

Forehearing words: Pre-activation of word endings at word onset.

Science.gov (United States)

Roll, Mikael; Söderström, Pelle; Frid, Johan; Mannfolk, Peter; Horne, Merle

2017-09-29

Occurring at rates up to 6-7 syllables per second, speech perception and understanding involves rapid identification of speech sounds and pre-activation of morphemes and words. Using event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI), we investigated the time-course and neural sources of pre-activation of word endings as participants heard the beginning of unfolding words. ERPs showed a pre-activation negativity (PrAN) for word beginnings (first two segmental phonemes) with few possible completions. PrAN increased gradually as the number of possible completions of word onsets decreased and the lexical frequency of the completions increased. The early brain potential effect for few possible word completions was associated with a blood-oxygen-level-dependent (BOLD) contrast increase in Broca's area (pars opercularis of the left inferior frontal gyrus) and angular gyrus of the left parietal lobe. We suggest early involvement of the left prefrontal cortex in inhibiting irrelevant left parietal activation during lexical selection. The results further our understanding of the importance of Broca's area in rapid online pre-activation of words. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Cross-Cultural Evidence for Multimodal Motherese: Asian-Indian Mothers’ Adaptive Use of Synchronous Words and Gestures

Science.gov (United States)

Maganti, Madhavilatha; Bahrick, Lorraine E.

2014-01-01

In a quasi-experimental study, twenty-four Asian-Indian mothers were asked to teach novel (target) names for two objects and two actions to their children of three different levels of lexical-mapping development, pre-lexical (5–8 months), early-lexical (9–17 months), and advanced-lexical (20–43 months). Target (N = 1482) and non-target (other, N = 2411) naming was coded for synchronous spoken words and object motion (multimodal motherese) and other naming styles. Indian mothers abundantly used multimodal motherese with target words to highlight novel word-referent relations, paralleling earlier findings from American mothers (Gogate, Bahrick, & Watson, 2000). They used it with target words more often for pre-lexical infants than advanced-lexical children, and to name target actions later into children’s development. Unlike American mothers, Indian mothers also abundantly used multimodal motherese to name target objects later into children’s development. Finally, monolingual mothers who spoke a verb-dominant Indian language used multimodal motherese more often than bilingual mothers who also spoke noun-dominant English to their child. The findings suggest that within a dynamic and reciprocal mother-infant communication system, multimodal motherese adapts to unify novel words and referents across cultures. It adapts to children’s level of lexical development and to ambient language-specific lexical-dominance hierarchies. PMID:25285369

Cations in Octahedral Sites: A Descriptor for Oxygen Electrocatalysis on Transition-Metal Spinels

Energy Technology Data Exchange (ETDEWEB)

Wei, Chao; Feng, Zhenxing; Scherer, Günther G.; Barber, James; Shao-Horn, Yang; Xu, Zhichuan J. (Nanyang); (ICL); (Oregon State U.); (TUM-CREATE); (MIT)

2017-04-10

Exploring efficient and low-cost electrocatalysts for the oxygen-reduction reaction (ORR) and oxygen-evolution reaction (OER) is critical for developing renewable energy technologies such as fuel cells, metal–air batteries, and water electrolyzers. A rational design of a catalyst can be guided by identifying descriptors that determine its activity. Here, a descriptor study on the ORR/OER of spinel oxides is presented. With a series of MnCo2O4, the Mn in octahedral sites is identified as an active site. This finding is then applied to successfully explain the ORR/OER activities of other transition-metal spinels, including MnxCo3-xO4 (x = 2, 2.5, 3), LixMn2O4 (x = 0.7, 1), XCo2O4 (X = Co, Ni, Zn), and XFe2O4 (X = Mn, Co, Ni). A general principle is concluded that the eg occupancy of the active cation in the octahedral site is the activity descriptor for the ORR/OER of spinels, consolidating the role of electron orbital filling in metal oxide catalysis.

Finding Chemical Structures Corresponding to a Set of Coordinates in Chemical Descriptor Space.

Science.gov (United States)

Miyao, Tomoyuki; Funatsu, Kimito

2017-08-01

When chemical structures are searched based on descriptor values, or descriptors are interpreted based on values, it is important that corresponding chemical structures actually exist. In order to consider the existence of chemical structures located in a specific region in the chemical space, we propose to search them inside training data domains (TDDs), which are dense areas of a training dataset in the chemical space. We investigated TDDs' features using diverse and local datasets, assuming that GDB11 is the chemical universe. These two analyses showed that considering TDDs gives higher chance of finding chemical structures than a random search-based method, and that novel chemical structures actually exist inside TDDs. In addition to those findings, we tested the hypothesis that chemical structures were distributed on the limited areas of chemical space. This hypothesis was confirmed by the fact that distances among chemical structures in several descriptor spaces were much shorter than those among randomly generated coordinates in the training data range. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America

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Arismendi, Ivan; Johnson, Sherri L.; Dunham, Jason B.; Haggerty, Roy

2013-01-01

1. Temperature is a major driver of ecological processes in stream ecosystems, yet the dynamics of thermal regimes remain poorly described. Most work has focused on relatively simple descriptors that fail to capture the full range of conditions that characterise thermal regimes of streams across seasons or throughout the year. 2. To more completely describe thermal regimes, we developed several descriptors of magnitude, variability, frequency, duration and timing of thermal events throughout a year. We evaluated how these descriptors change over time using long-term (1979–2009), continuous temperature data from five relatively undisturbed cold-water streams in western Oregon, U.S.A. In addition to trends for each descriptor, we evaluated similarities among them, as well as patterns of spatial coherence, and temporal synchrony. 3. Using different groups of descriptors, we were able to more fully capture distinct aspects of the full range of variability in thermal regimes across space and time. A subset of descriptors showed both higher coherence and synchrony and, thus, an appropriate level of responsiveness to examine evidence of regional climatic influences on thermal regimes. Most notably, daily minimum values during winter–spring were the most responsive descriptors to potential climatic influences. 4. Overall, thermal regimes in streams we studied showed high frequency and low variability of cold temperatures during the cold-water period in winter and spring, and high frequency and high variability of warm temperatures during the warm-water period in summer and autumn. The cold and warm periods differed in the distribution of events with a higher frequency and longer duration of warm events in summer than cold events in winter. The cold period exhibited lower variability in the duration of events, but showed more variability in timing. 5. In conclusion, our results highlight the importance of a year-round perspective in identifying the most responsive

New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

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Franco-Pérez, Marco; Polanco-Ramírez, Carlos-A; Ayers, Paul W; Gázquez, José L; Vela, Alberto

2017-06-21

We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.

The Functions Of Taboo Words And Their Translation In Subtitling: A Case Study In “The Help”

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Agus Darma Yoga Pratama

2016-10-01

Full Text Available Translating taboo words in subtitling especially translating them into Indonesian is quite difficult since most of the Indonesian people are not used to uttering taboo or offensive words publicly. In addition, watching movie is more of social activity compared to reading and that is why reading taboo expressions while watching might be embarrassing. This study tries to explore the functions of taboo words found in “The Help” movie and tries to find out how the translator translate the taboo words into the target language in order to produce the closest functions to the source language without ignoring the technical aspects of subtitling. This study also deals with the strategy used by the translator to translate the taboo words. The main theories applied here in are from Karamitroglou (1998, Ljung (2011, Toury (1995, and Gottlieb (1992. There are 70 taboo words found in the raw data and the functions of those taboo words are to express sympathy, surprise, disappointment, disbelief, fear, annoyance, metaphorical interpretation, reaction to mishap, to emphasize the associated item, function as adjectival intensifier, name-calling, anaphoric use of epithet, oath, curse, unfriendly suggestion, and four of the taboo words show non-swearing word or in dysphemism form. The strategies applied are omission (16, transfer (27, and euphemism (26. In terms of the technical aspect in subtitling, all of the subtitles in the target language are presented at the maximum of two lines at once. However, there are three lines of the subtitles which exceed the maximum numbers of characters being proposed. Since taboo word is not only used to offend someone, it is important for the translator to get the closest equivalence in the target language in order to maintain its function. The translator may choose whether he/she wants to follow the source language norms to produce adequate target text or follow the target language norms in order to produce acceptable

An efficient descriptor model for designing materials for solar cells

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Alharbi, Fahhad H.; Rashkeev, Sergey N.; El-Mellouhi, Fedwa; Lüthi, Hans P.; Tabet, Nouar; Kais, Sabre

2015-11-01

An efficient descriptor model for fast screening of potential materials for solar cell applications is presented. It works for both excitonic and non-excitonic solar cells materials, and in addition to the energy gap it includes the absorption spectrum (α(E)) of the material. The charge transport properties of the explored materials are modelled using the characteristic diffusion length (Ld) determined for the respective family of compounds. The presented model surpasses the widely used Scharber model developed for bulk heterojunction solar cells. Using published experimental data, we show that the presented model is more accurate in predicting the achievable efficiencies. To model both excitonic and non-excitonic systems, two different sets of parameters are used to account for the different modes of operation. The analysis of the presented descriptor model clearly shows the benefit of including α(E) and Ld in view of improved screening results.

Periodic words connected with the Fibonacci words

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G. M. Barabash

2016-06-01

Full Text Available In this paper we introduce two families of periodic words (FLP-words of type 1 and FLP-words of type 2 that are connected with the Fibonacci words and investigated their properties.

A 3D visualization of the substituent effect : A brief analysis of two components of the operational formula of dual descriptor for open-shell systems.

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Martínez-Araya, Jorge I; Yepes, Diana; Jaque, Pablo

2017-12-27

Six organometallic compounds coming from a basic Mo-based complex were analyzed from the perspective of the dual descriptor in order to detect subtle influences that a substituent group could exert on the reactive core at a long range. Since the aforementioned complexes are open-shell systems, the used operational formula for the dual descriptor is that one defined for those aforementioned systems, which was then compared with spin density. In addition, dual descriptor was decomposed into two terms, each of which was also applied on every molecular system. The obtained results indicated that components of dual descriptor could become more useful than the operational formula of dual descriptor because differences exerted by the substituents at the para position were better detected by components of dual descriptor rather than the dual descriptor by itself.

Neural correlates of an early attentional capture by positive distractor words

OpenAIRE

Hinojosa, Jos? A.; Mercado, Francisco; Albert, Jacobo; Barjola, Paloma; Pel?ez, Irene; Villalba-Garc?a, Cristina; Carreti?, Luis

2015-01-01

Exogenous or automatic attention to emotional distractors has been observed for emotional scenes and faces. In the language domain, however, automatic attention capture by emotional words has been scarcely investigated. In the current event-related potentials study we explored distractor effects elicited by positive, negative and neutral words in a concurrent but distinct target distractor paradigm. Specifically, participants performed a digit categorization task in which task-irrelevant words...

Protein-protein docking using region-based 3D Zernike descriptors.

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Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

Qualitative spatial logic descriptors from 3D indoor scenes to generate explanations in natural language.

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Falomir, Zoe; Kluth, Thomas

2018-05-01

The challenge of describing 3D real scenes is tackled in this paper using qualitative spatial descriptors. A key point to study is which qualitative descriptors to use and how these qualitative descriptors must be organized to produce a suitable cognitive explanation. In order to find answers, a survey test was carried out with human participants which openly described a scene containing some pieces of furniture. The data obtained in this survey are analysed, and taking this into account, the QSn3D computational approach was developed which uses a XBox 360 Kinect to obtain 3D data from a real indoor scene. Object features are computed on these 3D data to identify objects in indoor scenes. The object orientation is computed, and qualitative spatial relations between the objects are extracted. These qualitative spatial relations are the input to a grammar which applies saliency rules obtained from the survey study and generates cognitive natural language descriptions of scenes. Moreover, these qualitative descriptors can be expressed as first-order logical facts in Prolog for further reasoning. Finally, a validation study is carried out to test whether the descriptions provided by QSn3D approach are human readable. The obtained results show that their acceptability is higher than 82%.

Neural network-based feature point descriptors for registration of optical and SAR images

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Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

2018-04-01

Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

RESEARCH ON FEATURE POINTS EXTRACTION METHOD FOR BINARY MULTISCALE AND ROTATION INVARIANT LOCAL FEATURE DESCRIPTOR

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Hongwei Ying

2014-08-01

Full Text Available An extreme point of scale space extraction method for binary multiscale and rotation invariant local feature descriptor is studied in this paper in order to obtain a robust and fast method for local image feature descriptor. Classic local feature description algorithms often select neighborhood information of feature points which are extremes of image scale space, obtained by constructing the image pyramid using certain signal transform method. But build the image pyramid always consumes a large amount of computing and storage resources, is not conducive to the actual applications development. This paper presents a dual multiscale FAST algorithm, it does not need to build the image pyramid, but can extract feature points of scale extreme quickly. Feature points extracted by proposed method have the characteristic of multiscale and rotation Invariant and are fit to construct the local feature descriptor.

Determination of polyparameter linear free energy relationship (pp-LFER) substance descriptors for established and alternative flame retardants.

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Stenzel, Angelika; Goss, Kai-Uwe; Endo, Satoshi

2013-02-05

Polyparameter linear free energy relationships (pp-LFERs) can predict partition coefficients for a multitude of environmental and biological phases with high accuracy. In this work, the pp-LFER substance descriptors of 40 established and alternative flame retardants (e.g., polybrominated diphenyl ethers, hexabromocyclododecane, bromobenzenes, trialkyl phosphates) were determined experimentally. In total, 251 data for gas-chromatographic (GC) retention times and liquid/liquid partition coefficients (K) were measured and used to calibrate the pp-LFER substance descriptors. Substance descriptors were validated through a comparison between predicted and experimental log K for the systems octanol/water (K(ow)), water/air (K(wa)), organic carbon/water (K(oc)) and liposome/water (K(lipw)), revealing a high reliability of pp-LFER predictions based on our descriptors. For instance, the difference between predicted and experimental log K(ow) was <0.3 log units for 17 out of 21 compounds for which experimental values were available. Moreover, we found an indication that the H-bond acceptor value (B) depends on the solvent for some compounds. Thus, for predicting environmentally relevant partition coefficients it is important to determine B values using measurements in aqueous systems. The pp-LFER descriptors calibrated in this study can be used to predict partition coefficients for which experimental data are unavailable, and the predicted values can serve as references for further experimental measurements.

Diminutives facilitate word segmentation in natural speech: cross-linguistic evidence.

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Kempe, Vera; Brooks, Patricia J; Gillis, Steven; Samson, Graham

2007-06-01

Final-syllable invariance is characteristic of diminutives (e.g., doggie), which are a pervasive feature of the child-directed speech registers of many languages. Invariance in word endings has been shown to facilitate word segmentation (Kempe, Brooks, & Gillis, 2005) in an incidental-learning paradigm in which synthesized Dutch pseudonouns were used. To broaden the cross-linguistic evidence for this invariance effect and to increase its ecological validity, adult English speakers (n=276) were exposed to naturally spoken Dutch or Russian pseudonouns presented in sentence contexts. A forced choice test was given to assess target recognition, with foils comprising unfamiliar syllable combinations in Experiments 1 and 2 and syllable combinations straddling word boundaries in Experiment 3. A control group (n=210) received the recognition test with no prior exposure to targets. Recognition performance improved with increasing final-syllable rhyme invariance, with larger increases for the experimental group. This confirms that word ending invariance is a valid segmentation cue in artificial, as well as naturalistic, speech and that diminutives may aid segmentation in a number of languages.

Shuffling cross-validation-bee algorithm as a new descriptor selection method for retention studies of pesticides in biopartitioning micellar chromatography.

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Zarei, Kobra; Atabati, Morteza; Ahmadi, Monire

2017-05-04

Bee algorithm (BA) is an optimization algorithm inspired by the natural foraging behaviour of honey bees to find the optimal solution which can be proposed to feature selection. In this paper, shuffling cross-validation-BA (CV-BA) was applied to select the best descriptors that could describe the retention factor (log k) in the biopartitioning micellar chromatography (BMC) of 79 heterogeneous pesticides. Six descriptors were obtained using BA and then the selected descriptors were applied for model development using multiple linear regression (MLR). The descriptor selection was also performed using stepwise, genetic algorithm and simulated annealing methods and MLR was applied to model development and then the results were compared with those obtained from shuffling CV-BA. The results showed that shuffling CV-BA can be applied as a powerful descriptor selection method. Support vector machine (SVM) was also applied for model development using six selected descriptors by BA. The obtained statistical results using SVM were better than those obtained using MLR, as the root mean square error (RMSE) and correlation coefficient (R) for whole data set (training and test), using shuffling CV-BA-MLR, were obtained as 0.1863 and 0.9426, respectively, while these amounts for the shuffling CV-BA-SVM method were obtained as 0.0704 and 0.9922, respectively.

Acquiring concepts and features of novel words by two types of learning: direct mapping and inference.

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Chen, Shuang; Wang, Lin; Yang, Yufang

2014-04-01

This study examined the semantic representation of novel words learnt in two conditions: directly mapping a novel word to a concept (Direct mapping: DM) and inferring the concept from provided features (Inferred learning: IF). A condition where no definite concept could be inferred (No basic-level meaning: NM) served as a baseline. The semantic representation of the novel word was assessed via a semantic-relatedness judgment task. In this task, the learned novel word served as a prime, while the corresponding concept, an unlearned feature of the concept, and an unrelated word served as targets. ERP responses to the targets, primed by the novel words in the three learning conditions, were compared. For the corresponding concept, smaller N400s were elicited in the DM and IF conditions than in the NM condition, indicating that the concept could be obtained in both learning conditions. However, for the unlearned feature, the targets in the IF condition produced an N400 effect while in the DM condition elicited an LPC effect relative to the NM learning condition. No ERP difference was observed among the three learning conditions for the unrelated words. The results indicate that conditions of learning affect the semantic representation of novel word, and that the unlearned feature was only activated by the novel word in the IF learning condition. Copyright © 2014 Elsevier Ltd. All rights reserved.

Local chemical potential, local hardness, and dual descriptors in temperature dependent chemical reactivity theory.

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Franco-Pérez, Marco; Ayers, Paul W; Gázquez, José L; Vela, Alberto

2017-05-31

In this work we establish a new temperature dependent procedure within the grand canonical ensemble, to avoid the Dirac delta function exhibited by some of the second order chemical reactivity descriptors based on density functional theory, at a temperature of 0 K. Through the definition of a local chemical potential designed to integrate to the global temperature dependent electronic chemical potential, the local chemical hardness is expressed in terms of the derivative of this local chemical potential with respect to the average number of electrons. For the three-ground-states ensemble model, this local hardness contains a term that is equal to the one intuitively proposed by Meneses, Tiznado, Contreras and Fuentealba, which integrates to the global hardness given by the difference in the first ionization potential, I, and the electron affinity, A, at any temperature. However, in the present approach one finds an additional temperature-dependent term that introduces changes at the local level and integrates to zero. Additionally, a τ-hard dual descriptor and a τ-soft dual descriptor given in terms of the product of the global hardness and the global softness multiplied by the dual descriptor, respectively, are derived. Since all these reactivity indices are given by expressions composed of terms that correspond to products of the global properties multiplied by the electrophilic or nucleophilic Fukui functions, they may be useful for studying and comparing equivalent sites in different chemical environments.

Predicting CT Image From MRI Data Through Feature Matching With Learned Nonlinear Local Descriptors.

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Yang, Wei; Zhong, Liming; Chen, Yang; Lin, Liyan; Lu, Zhentai; Liu, Shupeng; Wu, Yao; Feng, Qianjin; Chen, Wufan

2018-04-01

Attenuation correction for positron-emission tomography (PET)/magnetic resonance (MR) hybrid imaging systems and dose planning for MR-based radiation therapy remain challenging due to insufficient high-energy photon attenuation information. We present a novel approach that uses the learned nonlinear local descriptors and feature matching to predict pseudo computed tomography (pCT) images from T1-weighted and T2-weighted magnetic resonance imaging (MRI) data. The nonlinear local descriptors are obtained by projecting the linear descriptors into the nonlinear high-dimensional space using an explicit feature map and low-rank approximation with supervised manifold regularization. The nearest neighbors of each local descriptor in the input MR images are searched in a constrained spatial range of the MR images among the training dataset. Then the pCT patches are estimated through k-nearest neighbor regression. The proposed method for pCT prediction is quantitatively analyzed on a dataset consisting of paired brain MRI and CT images from 13 subjects. Our method generates pCT images with a mean absolute error (MAE) of 75.25 ± 18.05 Hounsfield units, a peak signal-to-noise ratio of 30.87 ± 1.15 dB, a relative MAE of 1.56 ± 0.5% in PET attenuation correction, and a dose relative structure volume difference of 0.055 ± 0.107% in , as compared with true CT. The experimental results also show that our method outperforms four state-of-the-art methods.

The Neural Correlates of Abstract and Concrete Words: Evidence from Brain-Damaged Patients

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Giorgia Martello

2013-08-01

Full Text Available Neuropsychological and activation studies on the neural correlates of abstract and concrete words have produced contrasting results. The present study explores the anatomical substrates of abstract/concrete words in 22 brain-damaged patients with a single vascular lesion either in the right or left hemisphere. One hundred and twenty (60 concrete and 60 abstract noun triplets were used for a semantic similarity judgment task. We found a significant interaction in word type × group since left temporal brain-damaged patients performed significantly better with concrete than abstract words. Lesion mapping of patients with predominant temporal damage showed that the left superior and middle temporal gyri and the insula were the areas of major overlapping, while the anterior portion of the left temporal lobe was generally spared. Errors on abstract words mainly concerned (although at a non-significant level semantically associate targets, while in the case of concrete words, coordinate targets were significantly more impaired than associate ones. Our results suggest that the left superior and middle temporal gyri and the insula are crucial regions in processing abstract words. They also confirm the hypothesis of a semantic similarity vs. associative organization of concrete and abstract concepts.

Tobacco Products Sold by Internet Vendors Following Restrictions on Flavors and Light Descriptors

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Williams, Rebecca S.; Ribisl, Kurt M.

2015-01-01

Introduction: The 2009 Family Smoking Prevention and Tobacco Control Act bans characterizing flavors (e.g., grape, strawberry) in cigarettes, excluding tobacco and menthol, and prohibits companies from using misleading descriptors (e.g., light, low) that imply reduced health risks without submitting scientific data to support the claim and obtaining a marketing authorization from the U.S. Food and Drug Administration. This observational study examines tobacco products offered by Internet cigarette vendors (ICV) pre- and postimplementation of the ban on characterizing flavors in cigarettes and the restriction on misleading descriptors. Methods: Cross-sectional samples of the 200 most popular ICVs in 2009, 2010, and 2011 were identified. Data were analyzed in 2012 and 2013. Results: In 2011 the odds for selling cigarettes with banned flavors or misleading descriptors were 0.40 times that for selling the products in 2009 (95% confidence interval [CI] = 0.18, 0.88). However, 89% of vendors continued to sell the products, including 95.8% of international vendors. Following the ban on characterizing flavors, ICVs began selling potential alternative products. In 2010, the odds for selling flavored little cigars were 1.71 (95% CI = 1.09, 2.69) times that for selling the product in 2009 and, for clove cigars, were 5.50 (95% CI = 2.36, 12.80) times that for selling the product in 2009. Conclusions: Noncompliance with the ban on characterizing flavors and restriction on misleading descriptors has been high, especially among international vendors. Many vendors appear to be circumventing the intent of the flavors ban by selling unbanned flavored cigars, in some cases in lieu of flavored cigarettes. PMID:25173777

Novel word retention in bilingual and monolingual speakers

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Pui Fong eKan

2014-09-01

Full Text Available The goal of this research was to examine word retention in bilinguals and monolinguals. Long-term word retention is an essential part of vocabulary learning. Previous studies have documented that bilinguals outperform monolinguals in terms of retrieving newly-exposed words. Yet, little is known about whether or to what extent bilinguals are different from monolinguals in word retention. Participants were 30 English-speaking monolingual adults and 30 bilingual adults who speak Spanish as a home language and learned English as a second language during childhood. In a previous study (Kan, Sadagopan, Janich, & Andrade, 2014, the participants were exposed to the target novel words in English, Spanish, and Cantonese. In this current study, word retention was measured a week after the fast mapping task. No exposures were given during the one-week interval. Results showed that bilinguals and monolinguals retain a similar number of words. However, participants produced more words in English than in either Spanish or Cantonese. Correlation analyses revealed that language knowledge plays a role in the relationships between fast mapping and word retention. Specifically, within- and across-language relationships between bilinguals’ fast mapping and word retention were found in Spanish and English, by contrast, within-language relationships between monolinguals’ fast mapping and word retention were found in English and across-language relationships between their fast mapping and word retention performance in English and Cantonese. Similarly, bilinguals differed from monolinguals in the relationships among the word retention scores in three languages. Significant correlations were found among bilinguals’ retention scores. However, no such correlations were found among monolinguals’ retention scores. The overall findings suggest that bilinguals’ language experience and language knowledge most likely contribute to how they learn and retain new words.

Novel word retention in bilingual and monolingual speakers.

Science.gov (United States)

Kan, Pui Fong; Sadagopan, Neeraja

2014-01-01

The goal of this research was to examine word retention in bilinguals and monolinguals. Long-term word retention is an essential part of vocabulary learning. Previous studies have documented that bilinguals outperform monolinguals in terms of retrieving newly-exposed words. Yet, little is known about whether or to what extent bilinguals are different from monolinguals in word retention. Participants were 30 English-speaking monolingual adults and 30 bilingual adults who speak Spanish as a home language and learned English as a second language during childhood. In a previous study (Kan et al., 2014), the participants were exposed to the target novel words in English, Spanish, and Cantonese. In this current study, word retention was measured a week after the fast mapping task. No exposures were given during the one-week interval. Results showed that bilinguals and monolinguals retain a similar number of words. However, participants produced more words in English than in either Spanish or Cantonese. Correlation analyses revealed that language knowledge plays a role in the relationships between fast mapping and word retention. Specifically, within- and across-language relationships between bilinguals' fast mapping and word retention were found in Spanish and English, by contrast, within-language relationships between monolinguals' fast mapping and word retention were found in English and across-language relationships between their fast mapping and word retention performance in English and Cantonese. Similarly, bilinguals differed from monolinguals in the relationships among the word retention scores in three languages. Significant correlations were found among bilinguals' retention scores. However, no such correlations were found among monolinguals' retention scores. The overall findings suggest that bilinguals' language experience and language knowledge most likely contribute to how they learn and retain new words.

Performance of Global-Appearance Descriptors in Map Building and Localization Using Omnidirectional Vision

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Luis Payá

2014-02-01

Full Text Available Map building and localization are two crucial abilities that autonomous robots must develop. Vision sensors have become a widespread option to solve these problems. When using this kind of sensors, the robot must extract the necessary information from the scenes to build a representation of the environment where it has to move and to estimate its position and orientation with robustness. The techniques based on the global appearance of the scenes constitute one of the possible approaches to extract this information. They consist in representing each scene using only one descriptor which gathers global information from the scene. These techniques present some advantages comparing to other classical descriptors, based on the extraction of local features. However, it is important a good configuration of the parameters to reach a compromise between computational cost and accuracy. In this paper we make an exhaustive comparison among some global appearance descriptors to solve the mapping and localization problem. With this aim, we make use of several image sets captured in indoor environments under realistic working conditions. The datasets have been collected using an omnidirectional vision sensor mounted on the robot.

Excited-state properties from ground-state DFT descriptors: A QSPR approach for dyes.

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Fayet, Guillaume; Jacquemin, Denis; Wathelet, Valérie; Perpète, Eric A; Rotureau, Patricia; Adamo, Carlo

2010-02-26

This work presents a quantitative structure-property relationship (QSPR)-based approach allowing an accurate prediction of the excited-state properties of organic dyes (anthraquinones and azobenzenes) from ground-state molecular descriptors, obtained within the (conceptual) density functional theory (DFT) framework. The ab initio computation of the descriptors was achieved at several levels of theory, so that the influence of the basis set size as well as of the modeling of environmental effects could be statistically quantified. It turns out that, for the entire data set, a statistically-robust four-variable multiple linear regression based on PCM-PBE0/6-31G calculations delivers a R(adj)(2) of 0.93 associated to predictive errors allowing for rapid and efficient dye design. All the selected descriptors are independent of the dye's family, an advantage over previously designed QSPR schemes. On top of that, the obtained accuracy is comparable to the one of the today's reference methods while exceeding the one of hardness-based fittings. QSPR relationships specific to both families of dyes have also been built up. This work paves the way towards reliable and computationally affordable color design for organic dyes. Copyright 2009 Elsevier Inc. All rights reserved.

The time course of morphological processing during spoken word recognition in Chinese.

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Shen, Wei; Qu, Qingqing; Ni, Aiping; Zhou, Junyi; Li, Xingshan

2017-12-01

We investigated the time course of morphological processing during spoken word recognition using the printed-word paradigm. Chinese participants were asked to listen to a spoken disyllabic compound word while simultaneously viewing a printed-word display. Each visual display consisted of three printed words: a semantic associate of the first constituent of the compound word (morphemic competitor), a semantic associate of the whole compound word (whole-word competitor), and an unrelated word (distractor). Participants were directed to detect whether the spoken target word was on the visual display. Results indicated that both the morphemic and whole-word competitors attracted more fixations than the distractor. More importantly, the morphemic competitor began to diverge from the distractor immediately at the acoustic offset of the first constituent, which was earlier than the whole-word competitor. These results suggest that lexical access to the auditory word is incremental and morphological processing (i.e., semantic access to the first constituent) that occurs at an early processing stage before access to the representation of the whole word in Chinese.

Motion control of planar parallel robot using the fuzzy descriptor system approach.

Science.gov (United States)

Vermeiren, Laurent; Dequidt, Antoine; Afroun, Mohamed; Guerra, Thierry-Marie

2012-09-01

This work presents the control of a two-degree of freedom parallel robot manipulator. A quasi-LPV approach, through the so-called TS fuzzy model and LMI constraints problems is used. Moreover, in this context a way to derive interesting control laws is to keep the descriptor form of the mechanical system. Therefore, new LMI problems have to be defined that helps to reduce the conservatism of the usual results. Some relaxations are also proposed to leave the pure quadratic stability/stabilization framework. A comparison study between the classical control strategies from robotics and the control design using TS fuzzy descriptor models is carried out to show the interest of the proposed approach. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

The word-length effect and disyllabic words.

Science.gov (United States)

Lovatt, P; Avons, S E; Masterson, J

2000-02-01

Three experiments compared immediate serial recall of disyllabic words that differed on spoken duration. Two sets of long- and short-duration words were selected, in each case maximizing duration differences but matching for frequency, familiarity, phonological similarity, and number of phonemes, and controlling for semantic associations. Serial recall measures were obtained using auditory and visual presentation and spoken and picture-pointing recall. In Experiments 1a and 1b, using the first set of items, long words were better recalled than short words. In Experiments 2a and 2b, using the second set of items, no difference was found between long and short disyllabic words. Experiment 3 confirmed the large advantage for short-duration words in the word set originally selected by Baddeley, Thomson, and Buchanan (1975). These findings suggest that there is no reliable advantage for short-duration disyllables in span tasks, and that previous accounts of a word-length effect in disyllables are based on accidental differences between list items. The failure to find an effect of word duration casts doubt on theories that propose that the capacity of memory span is determined by the duration of list items or the decay rate of phonological information in short-term memory.

Do handwritten words magnify lexical effects in visual word recognition?

Science.gov (United States)

Perea, Manuel; Gil-López, Cristina; Beléndez, Victoria; Carreiras, Manuel

2016-01-01

An examination of how the word recognition system is able to process handwritten words is fundamental to formulate a comprehensive model of visual word recognition. Previous research has revealed that the magnitude of lexical effects (e.g., the word-frequency effect) is greater with handwritten words than with printed words. In the present lexical decision experiments, we examined whether the quality of handwritten words moderates the recruitment of top-down feedback, as reflected in word-frequency effects. Results showed a reading cost for difficult-to-read and easy-to-read handwritten words relative to printed words. But the critical finding was that difficult-to-read handwritten words, but not easy-to-read handwritten words, showed a greater word-frequency effect than printed words. Therefore, the inherent physical variability of handwritten words does not necessarily boost the magnitude of lexical effects.

Statistical Laws Governing Fluctuations in Word Use from Word Birth to Word Death

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Petersen, Alexander M.; Tenenbaum, Joel; Havlin, Shlomo; Stanley, H. Eugene

2012-03-01

We analyze the dynamic properties of 107 words recorded in English, Spanish and Hebrew over the period 1800-2008 in order to gain insight into the coevolution of language and culture. We report language independent patterns useful as benchmarks for theoretical models of language evolution. A significantly decreasing (increasing) trend in the birth (death) rate of words indicates a recent shift in the selection laws governing word use. For new words, we observe a peak in the growth-rate fluctuations around 40 years after introduction, consistent with the typical entry time into standard dictionaries and the human generational timescale. Pronounced changes in the dynamics of language during periods of war shows that word correlations, occurring across time and between words, are largely influenced by coevolutionary social, technological, and political factors. We quantify cultural memory by analyzing the long-term correlations in the use of individual words using detrended fluctuation analysis.

The Effects of Word Frequency and Context Variability in Cued Recall

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Criss, Amy H.; Aue, William R.; Smith, Larissa

2011-01-01

Normative word frequency and context variability affect memory in a range of episodic memory tasks and place constraints on theoretical development. In four experiments, we independently manipulated the word frequency and context variability of the targets (to-be-generated items) and cues in a cued recall paradigm. We found that high frequency…

Neural correlates of an early attentional capture by positive distractor words.

Science.gov (United States)

Hinojosa, José A; Mercado, Francisco; Albert, Jacobo; Barjola, Paloma; Peláez, Irene; Villalba-García, Cristina; Carretié, Luis

2015-01-01

Exogenous or automatic attention to emotional distractors has been observed for emotional scenes and faces. In the language domain, however, automatic attention capture by emotional words has been scarcely investigated. In the current event-related potentials study we explored distractor effects elicited by positive, negative and neutral words in a concurrent but distinct target distractor paradigm. Specifically, participants performed a digit categorization task in which task-irrelevant words were flanked by numbers. The results of both temporo-spatial principal component and source location analyses revealed the existence of early distractor effects that were specifically triggered by positive words. At the scalp level, task-irrelevant positive compared to neutral and negative words elicited larger amplitudes in an anterior negative component that peaked around 120 ms. Also, at the voxel level, positive distractor words increased activity in orbitofrontal regions compared to negative words. These results suggest that positive distractor words quickly and automatically capture attentional resources diverting them from the task where attention was voluntarily directed.

Neural correlates of an early attentional capture by positive distractor words

Directory of Open Access Journals (Sweden)

José Antonio Hinojosa

2015-01-01

Full Text Available Exogenous or automatic attention to emotional distractors has been observed for emotional scenes and faces. In the language domain, however, automatic attention capture by emotional words has been scarcely investigated. In the current event-related potentials study we explored distractor effects elicited by positive, negative and neutral words in a concurrent but distinct target distractor paradigm. Specifically, participants performed a digit categorization task in which task-irrelevant words were flanked by numbers. The results of both temporo-spatial principal component and source location analyses revealed the existence of early distractor effects that were specifically triggered by positive words. At the scalp level, task-irrelevant positive compared to neutral and negative words elicited larger amplitudes in an anterior negative component that peaked around 120 ms. Also, at the voxel level, positive distractor words increased activity in orbitofrontal regions compared to negative words. These results suggest that positive distractor words quickly and automatically capture attentional resources diverting them from the task where attention was voluntarily directed.

QSPR models based on molecular mechanics and quantum chemical calculations. 1. Construction of Boltzmann averaged descriptors for alkanes, alcohols, diols, ethers and cyclic compounds

DEFF Research Database (Denmark)

Dyekjær, Jane Dannow; Rasmussen, Kjeld; Jonsdottir, Svava Osk

2002-01-01

Values for nine descriptors for QSPR (quantitative structure-property relationships) modeling of physical properties of 96 alkanes, alcohols, ethers, diols, triols and cyclic alkanes and alcohols in conjunction with the program Codessa are presented. The descriptors are Boltzmann-averaged by sele......Values for nine descriptors for QSPR (quantitative structure-property relationships) modeling of physical properties of 96 alkanes, alcohols, ethers, diols, triols and cyclic alkanes and alcohols in conjunction with the program Codessa are presented. The descriptors are Boltzmann...

Retention of New Words: Quantity of Encounters, Quality of Task, and Degree of Knowledge

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Laufer, Batia; Rozovski-Roitblat, Bella

2015-01-01

We examined how learning new second language (L2) words was affected by three "task type" conditions (reading only, reading with a dictionary, reading and word focused exercises), three "number of encounters" conditions and their combinations. Three groups of L2 learners (n = 185) were exposed to 30 target words (one group in…

Periodic table-based descriptors to encode cytotoxicity profile of metal oxide nanoparticles: a mechanistic QSTR approach.

Science.gov (United States)

Kar, Supratik; Gajewicz, Agnieszka; Puzyn, Tomasz; Roy, Kunal; Leszczynski, Jerzy

2014-09-01

Nanotechnology has evolved as a frontrunner in the development of modern science. Current studies have established toxicity of some nanoparticles to human and environment. Lack of sufficient data and low adequacy of experimental protocols hinder comprehensive risk assessment of nanoparticles (NPs). In the present work, metal electronegativity (χ), the charge of the metal cation corresponding to a given oxide (χox), atomic number and valence electron number of the metal have been used as simple molecular descriptors to build up quantitative structure-toxicity relationship (QSTR) models for prediction of cytotoxicity of metal oxide NPs to bacteria Escherichia coli. These descriptors can be easily obtained from molecular formula and information acquired from periodic table in no time. It has been shown that a simple molecular descriptor χox can efficiently encode cytotoxicity of metal oxides leading to models with high statistical quality as well as interpretability. Based on this model and previously published experimental results, we have hypothesized the most probable mechanism of the cytotoxicity of metal oxide nanoparticles to E. coli. Moreover, the required information for descriptor calculation is independent of size range of NPs, nullifying a significant problem that various physical properties of NPs change for different size ranges. Copyright © 2014 Elsevier Inc. All rights reserved.

Feature extraction and descriptor calculation methods for automatic georeferencing of Philippines' first microsatellite imagery

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Tupas, M. E. A.; Dasallas, J. A.; Jiao, B. J. D.; Magallon, B. J. P.; Sempio, J. N. H.; Ramos, M. K. F.; Aranas, R. K. D.; Tamondong, A. M.

2017-10-01

The FAST-SIFT corner detector and descriptor extractor combination was used to automatically georeference DIWATA-1 Spaceborne Multispectral Imager images. Features from the Fast Accelerated Segment Test (FAST) algorithm detects corners or keypoints in an image, and these robustly detected keypoints have well-defined positions. Descriptors were computed using Scale-Invariant Feature Transform (SIFT) extractor. FAST-SIFT method effectively SMI same-subscene images detected by the NIR sensor. The method was also tested in stitching NIR images with varying subscene swept by the camera. The slave images were matched to the master image. The keypoints served as the ground control points. Random sample consensus was used to eliminate fall-out matches and ensure accuracy of the feature points from which the transformation parameters were derived. Keypoints are matched based on their descriptor vector. Nearest-neighbor matching is employed based on a metric distance between the descriptors. The metrics include Euclidean and city block, among others. Rough matching outputs not only the correct matches but also the faulty matches. A previous work in automatic georeferencing incorporates a geometric restriction. In this work, we applied a simplified version of the learning method. RANSAC was used to eliminate fall-out matches and ensure accuracy of the feature points. This method identifies if a point fits the transformation function and returns inlier matches. The transformation matrix was solved by Affine, Projective, and Polynomial models. The accuracy of the automatic georeferencing method were determined by calculating the RMSE of interest points, selected randomly, between the master image and transformed slave image.

Aquaculture Thesaurus: Descriptors Used in the National Aquaculture Information System.

Science.gov (United States)

Lanier, James A.; And Others

This document provides a listing of descriptors used in the National Aquaculture Information System (NAIS), a computer information storage and retrieval system on marine, brackish, and freshwater organisms. Included are an explanation of how to use the document, subject index terms, and a brief bibliography of the literature used in developing the…

Tobacco products sold by Internet vendors following restrictions on flavors and light descriptors.

Science.gov (United States)

Jo, Catherine L; Williams, Rebecca S; Ribisl, Kurt M

2015-03-01

The 2009 Family Smoking Prevention and Tobacco Control Act bans characterizing flavors (e.g., grape, strawberry) in cigarettes, excluding tobacco and menthol, and prohibits companies from using misleading descriptors (e.g., light, low) that imply reduced health risks without submitting scientific data to support the claim and obtaining a marketing authorization from the U.S. Food and Drug Administration. This observational study examines tobacco products offered by Internet cigarette vendors (ICV) pre- and postimplementation of the ban on characterizing flavors in cigarettes and the restriction on misleading descriptors. Cross-sectional samples of the 200 most popular ICVs in 2009, 2010, and 2011 were identified. Data were analyzed in 2012 and 2013. In 2011 the odds for selling cigarettes with banned flavors or misleading descriptors were 0.40 times that for selling the products in 2009 (95% confidence interval [CI] = 0.18, 0.88). However, 89% of vendors continued to sell the products, including 95.8% of international vendors. Following the ban on characterizing flavors, ICVs began selling potential alternative products. In 2010, the odds for selling flavored little cigars were 1.71 (95% CI = 1.09, 2.69) times that for selling the product in 2009 and, for clove cigars, were 5.50 (95% CI = 2.36, 12.80) times that for selling the product in 2009. Noncompliance with the ban on characterizing flavors and restriction on misleading descriptors has been high, especially among international vendors. Many vendors appear to be circumventing the intent of the flavors ban by selling unbanned flavored cigars, in some cases in lieu of flavored cigarettes. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

WORD LEVEL DISCRIMINATIVE TRAINING FOR HANDWRITTEN WORD RECOGNITION

NARCIS (Netherlands)

Chen, W.; Gader, P.

2004-01-01

Word level training refers to the process of learning the parameters of a word recognition system based on word level criteria functions. Previously, researchers trained lexicon­driven handwritten word recognition systems at the character level individually. These systems generally use statistical

Stability of neutral type descriptor system with mixed delays

International Nuclear Information System (INIS)

Li Hong; Li Houbiao; Zhong Shouming

2007-01-01

In this paper, the stability problems of general neutral type descriptor system with mixed delays are considered. Some new delay-independent stability and robust stability criteria, which are simpler and less conservative than existing results, are derived in terms of the stability of a new operator I and linear matrix inequalities (LMIs). Therefore, criteria can be easily checked by utilizing the Matlab LMI toolbox

Comparison of Word Intelligibility in Spoken and Sung Phrases

Directory of Open Access Journals (Sweden)

Lauren B. Collister

2008-09-01

Full Text Available Twenty listeners were exposed to spoken and sung passages in English produced by three trained vocalists. Passages included representative words extracted from a large database of vocal lyrics, including both popular and classical repertoires. Target words were set within spoken or sung carrier phrases. Sung carrier phrases were selected from classical vocal melodies. Roughly a quarter of all words sung by an unaccompanied soloist were misheard. Sung passages showed a seven-fold decrease in intelligibility compared with their spoken counterparts. The perceptual mistakes occurring with vowels replicate previous studies showing the centralization of vowels. Significant confusions are also evident for consonants, especially voiced stops and nasals.

The x-word and its usage : Taboo words and swearwords in general, and x-words in newspapers

OpenAIRE

Lindahl, Katarina

2008-01-01

All languages have words that are considered taboo – words that are not supposed to be said or used. Taboo words, or swearwords, can be used in many different ways and they can have different meanings depending on what context they appear in. Another aspect of taboo words is the euphemisms that are used in order to avoid obscene speech. This paper will focus on x-words, words like the f-word or the c-word, which replace the words fuck or cunt, but as the study will show they also have other m...

NMR spectrometers as "magnetic tongues": prediction of sensory descriptors in canned tomatoes

DEFF Research Database (Denmark)

Malmendal, Anders; Amoresano, Claudia; Trotta, Roberta

2011-01-01

The perception of odor and flavor of food is a complicated physiological and psychological process that cannot be explained by simple models. Quantitative descriptive analysis is a technique used to describe sensory features. Nevertheless, the availability of a number of instrumental techniques has...... opened up the possibility to calibrate the sensory perception. In this frame, we have tested the potentiality of nuclear magnetic resonance spectroscopy as a predictive tool to measure sensory descriptors. In particular, we have used an NMR metabolomic approach that allowed us to differentiate...... the analyzed samples based on their chemical composition. We were able to correlate the NMR metabolomic fingerprints recorded for canned tomato samples to the sensory descriptors bitterness, sweetness, sourness, saltiness, tomato and metal taste, redness, and density, suggesting that NMR might be a very useful...

Napping facilitates word learning in early lexical development.

Science.gov (United States)

Horváth, Klára; Myers, Kyle; Foster, Russell; Plunkett, Kim

2015-10-01

Little is known about the role that night-time sleep and daytime naps play in early cognitive development. Our aim was to investigate how napping affects word learning in 16-month-olds. Thirty-four typically developing infants were assigned randomly to nap and wake groups. After teaching two novel object-word pairs to infants, we tested their initial performance with an intermodal preferential looking task in which infants are expected to increase their target looking time compared to a distracter after hearing its auditory label. A second test session followed after approximately a 2-h delay. The delay contained sleep for the nap group or no sleep for the wake group. Looking behaviour was measured with an automatic eye-tracker. Vocabulary size was assessed using the Oxford Communicative Development Inventory. A significant interaction between group and session was found in preferential looking towards the target picture. The performance of the nap group increased after the nap, whereas that of the wake group did not change. The gain in performance correlated positively with the expressive vocabulary size in the nap group. These results indicate that daytime napping helps consolidate word learning in infancy. © 2015 European Sleep Research Society.

Time course of Chinese monosyllabic spoken word recognition: evidence from ERP analyses.

Science.gov (United States)

Zhao, Jingjing; Guo, Jingjing; Zhou, Fengying; Shu, Hua

2011-06-01

Evidence from event-related potential (ERP) analyses of English spoken words suggests that the time course of English word recognition in monosyllables is cumulative. Different types of phonological competitors (i.e., rhymes and cohorts) modulate the temporal grain of ERP components differentially (Desroches, Newman, & Joanisse, 2009). The time course of Chinese monosyllabic spoken word recognition could be different from that of English due to the differences in syllable structure between the two languages (e.g., lexical tones). The present study investigated the time course of Chinese monosyllabic spoken word recognition using ERPs to record brain responses online while subjects listened to spoken words. During the experiment, participants were asked to compare a target picture with a subsequent picture by judging whether or not these two pictures belonged to the same semantic category. The spoken word was presented between the two pictures, and participants were not required to respond during its presentation. We manipulated phonological competition by presenting spoken words that either matched or mismatched the target picture in one of the following four ways: onset mismatch, rime mismatch, tone mismatch, or syllable mismatch. In contrast to the English findings, our findings showed that the three partial mismatches (onset, rime, and tone mismatches) equally modulated the amplitudes and time courses of the N400 (a negative component that peaks about 400ms after the spoken word), whereas, the syllable mismatched words elicited an earlier and stronger N400 than the three partial mismatched words. The results shed light on the important role of syllable-level awareness in Chinese spoken word recognition and also imply that the recognition of Chinese monosyllabic words might rely more on global similarity of the whole syllable structure or syllable-based holistic processing rather than phonemic segment-based processing. We interpret the differences in spoken word

Classification of Word Levels with Usage Frequency, Expert Opinions and Machine Learning

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Sohsah, Gihad N.; Ünal, Muhammed Esad; Güzey, Onur

2015-01-01

Educational applications for language teaching can utilize the language levels of words to target proficiency levels of students. This paper and the accompanying data provide a methodology for making educational standard-aligned language-level predictions for all English words. The methodology involves expert opinions on language levels and…

Some words on Word

NARCIS (Netherlands)

Janssen, Maarten; Visser, A.

In many disciplines, the notion of a word is of central importance. For instance, morphology studies le mot comme tel, pris isol´ement (Mel’ˇcuk, 1993 [74]). In the philosophy of language the word was often considered to be the primary bearer of meaning. Lexicography has as its fundamental role

wACSF—Weighted atom-centered symmetry functions as descriptors in machine learning potentials

Science.gov (United States)

Gastegger, M.; Schwiedrzik, L.; Bittermann, M.; Berzsenyi, F.; Marquetand, P.

2018-06-01

We introduce weighted atom-centered symmetry functions (wACSFs) as descriptors of a chemical system's geometry for use in the prediction of chemical properties such as enthalpies or potential energies via machine learning. The wACSFs are based on conventional atom-centered symmetry functions (ACSFs) but overcome the undesirable scaling of the latter with an increasing number of different elements in a chemical system. The performance of these two descriptors is compared using them as inputs in high-dimensional neural network potentials (HDNNPs), employing the molecular structures and associated enthalpies of the 133 855 molecules containing up to five different elements reported in the QM9 database as reference data. A substantially smaller number of wACSFs than ACSFs is needed to obtain a comparable spatial resolution of the molecular structures. At the same time, this smaller set of wACSFs leads to a significantly better generalization performance in the machine learning potential than the large set of conventional ACSFs. Furthermore, we show that the intrinsic parameters of the descriptors can in principle be optimized with a genetic algorithm in a highly automated manner. For the wACSFs employed here, we find however that using a simple empirical parametrization scheme is sufficient in order to obtain HDNNPs with high accuracy.

An insight into morphometric descriptors of cell shape that pertain to regenerative medicine.

Science.gov (United States)

Lobo, Joana; See, Eugene Yong-Shun; Biggs, Manus; Pandit, Abhay

2016-07-01

Cellular morphology has recently been indicated as a powerful indicator of cellular function. The analysis of cell shape has evolved from rudimentary forms of microscopic visual inspection to more advanced methodologies that utilize high-resolution microscopy coupled with sophisticated computer hardware and software for data analysis. Despite this progress, there is still a lack of standardization in quantification of morphometric parameters. In addition, uncertainty remains as to which methodologies and parameters of cell morphology will yield meaningful data, which methods should be utilized to categorize cell shape, and the extent of reliability of measurements and the interpretation of the resulting analysis. A large range of descriptors has been employed to objectively assess the cellular morphology in two-dimensional and three-dimensional domains. Intuitively, simple and applicable morphometric descriptors are preferable and standardized protocols for cell shape analysis can be achieved with the help of computerized tools. In this review, cellular morphology is discussed as a descriptor of cellular function and the current morphometric parameters that are used quantitatively in two- and three-dimensional environments are described. Furthermore, the current problems associated with these morphometric measurements are addressed. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Validating Performance Level Descriptors (PLDs) for the AP® Environmental Science Exam

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Reshetar, Rosemary; Kaliski, Pamela; Chajewski, Michael; Lionberger, Karen

2012-01-01

This presentation summarizes a pilot study conducted after the May 2011 administration of the AP Environmental Science Exam. The study used analytical methods based on scaled anchoring as input to a Performance Level Descriptor validation process that solicited systematic input from subject matter experts.

Molecular surface representation using 3D Zernike descriptors for protein shape comparison and docking.

Science.gov (United States)

Kihara, Daisuke; Sael, Lee; Chikhi, Rayan; Esquivel-Rodriguez, Juan

2011-09-01

The tertiary structures of proteins have been solved in an increasing pace in recent years. To capitalize the enormous efforts paid for accumulating the structure data, efficient and effective computational methods need to be developed for comparing, searching, and investigating interactions of protein structures. We introduce the 3D Zernike descriptor (3DZD), an emerging technique to describe molecular surfaces. The 3DZD is a series expansion of mathematical three-dimensional function, and thus a tertiary structure is represented compactly by a vector of coefficients of terms in the series. A strong advantage of the 3DZD is that it is invariant to rotation of target object to be represented. These two characteristics of the 3DZD allow rapid comparison of surface shapes, which is sufficient for real-time structure database screening. In this article, we review various applications of the 3DZD, which have been recently proposed.

The facilitation effect of associative and semantic relatedness in word recognition

Directory of Open Access Journals (Sweden)

Jakić Milena

2011-01-01

Full Text Available In this study we addressed three issues concerning semantic and associative relatedness between two words and how they prime each other. The first issue is whether there is a priming effect of semantic relatedness over and above the effect of associative relatedness. The second issue is how difference in semantic overlap between two words affects priming. In order to specify the semantic overlap we introduce five relation types that differ in number of common semantic components. Three relation types (synonyms, antonyms and hyponyms represent semantic relatedness while two relation types represent associative relatedness, with negligible or no semantic relatedness. Finally, the third issue addressed in this study is whether there is a symmetric priming effect if we swap the position of prime and target, i.e. whether the direction of relatedness between two words affects priming. In two lexical decision experiments we presented five types of word pairs. In both experiments we obtained stronger facilitation for pairs that were both semantically and associatively related. Closer inspection showed that larger semantic overlap between words is paralleled by greater facilitation effect. The effects did not change when prime and target swap their position, indicating that the observed facilitation effects are symmetrical. This outcome complies with predictions of distributed models of memory.

Automatic evaluation of body-related words among young women: an experimental study

Directory of Open Access Journals (Sweden)

Cranney Jacquelyn

2010-06-01

Full Text Available Abstract Background Previous research has demonstrated that exposure to images depicting the thin female ideal has negative effects on some females' levels of body dissatisfaction. Much of this research, however, has utilised relatively long stimulus exposure times; thereby focusing on effortful and conscious processing of body-related stimuli. Relatively little is known about the nature of females' affective responses to the textual components of body-related stimuli, especially when these stimuli are only briefly encountered. The primary aim of the current research was to determine whether young women automatically evaluate body-related words and whether these responses are associated with body image concerns, including self-reported levels of appearance schematicity, thin internalisation, body dissatisfaction, and dietary restraint. Methods An affective priming task was used to investigate whether females automatically evaluate body-related words, and whether this is associated with self-reported body image concerns. In a within-participants experimental design, the valence congruence of the prime and target pairs was manipulated. Participants selected body words as primes in Experiment 1 (N = 27, while normatively selected body words were primes in Experiment 2 (N = 50. Each prime was presented briefly, followed by a target word which participants judged as "good" or "bad". The dependent variable was response latency to the target. Results Automatic evaluation was evident: responding to congruent pairs was faster than responding to incongruent pairs. Body image concerns were unrelated to automaticity. Conclusions The findings suggest that brief encounters with body words are likely to prompt automatic evaluation in all young women, and that this process proceeds unintentionally and efficiently, without conscious guidance.

Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

Science.gov (United States)

Liu, Zhi-Ping; Chen, Luonan

2016-01-01

Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

Linear and nonlinear relationships between biodegradation potential and molecular descriptors/fragments for organic pollutants and a theoretical interpretation

International Nuclear Information System (INIS)

He, Jia; Qin, Weichao; Zhang, Xujia; Wen, Yang; Su, Limin; Zhao, Yuanhui

2013-01-01

Prediction of the biodegradability of organic pollutants is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. In this paper, linear and nonlinear relationships between biological oxygen demand (BOD) and molecular descriptors/fragments have been investigated for 1130 organic chemicals. Significant relationships have been observed between the simple molecular descriptors and %BOD for some homologous compounds, but not for the whole set of compounds. Electronic parameters, such as E HOMO and E LUMO , are the dominant factors affecting the biodegradability for some homologous chemicals. However, other descriptors, such as molecular weight, acid dissociation constant and polarity still have a significant impact on the biodegradation. The best global model for %BOD prediction is that developed from a chain-based fragmentation scheme. At the same time, the theoretical relationship between %BOD and molecular descriptors/fragments has been investigated, based on a first-order kinetic process. The %BOD is nonlinearly, rather than linearly, related to the descriptors. The coefficients of determination can be significantly improved by using nonlinear models for the homologous compounds and the whole data set. After analysing 1130 ready and not ready biodegradable compounds using 23 simple descriptors and various fragmentation schemes, it was revealed that biodegradation could be well predicted from a chain-based fragmentation scheme, a decision tree and a %BOD model. The models were capable of separating NRB and RB with an overall accuracy of 87.2%, 83.0% and 82.5%, respectively. The best classification model developed was a chain-based model but it used 155 fragments. The simplest model was a decision tree which only used 10 structural fragments. The effect of structures on the biodegradation has been analysed and the biodegradation pathway and mechanisms have been discussed based on activating and inactivating

Reading in Developmental Prosopagnosia: Evidence for a Dissociation Between Word and Face Recognition

DEFF Research Database (Denmark)

Starrfelt, Randi; Klargaard, Solja; Petersen, Anders

2018-01-01

exposure durations (targeting the word superiority effect), and d) text reading. Results: Participants with developmental prosopagnosia performed strikingly similar to controls across the four reading tasks. Formal analysis revealed a significant dissociation between word and face recognition......, that is, impaired reading in developmental prosopagnosia. Method: We tested 10 adults with developmental prosopagnosia and 20 matched controls. All participants completed the Cambridge Face Memory Test, the Cambridge Face Perception test and a Face recognition questionnaire used to quantify everyday face...... recognition experience. Reading was measured in four experimental tasks, testing different levels of letter, word, and text reading: a) single word reading with words of varying length, b) vocal response times in single letter and short word naming, c) recognition of single letters and short words at brief...

Word segmentation by alternating colors facilitates eye guidance in Chinese reading.

Science.gov (United States)

Zhou, Wei; Wang, Aiping; Shu, Hua; Kliegl, Reinhold; Yan, Ming

2018-02-12

During sentence reading, low spatial frequency information afforded by spaces between words is the primary factor for eye guidance in spaced writing systems, whereas saccade generation for unspaced writing systems is less clear and under debate. In the present study, we investigated whether word-boundary information, provided by alternating colors (consistent or inconsistent with word-boundary information) influences saccade-target selection in Chinese. In Experiment 1, as compared to a baseline (i.e., uniform color) condition, word segmentation with alternating color shifted fixation location towards the center of words. In contrast, incorrect word segmentation shifted fixation location towards the beginning of words. In Experiment 2, we used a gaze-contingent paradigm to restrict the color manipulation only to the upcoming parafoveal words and replicated the results, including fixation location effects, as observed in Experiment 1. These results indicate that Chinese readers are capable of making use of parafoveal word-boundary knowledge for saccade generation, even if such information is unfamiliar to them. The present study provides novel support for the hypothesis that word segmentation is involved in the decision about where to fixate next during Chinese reading.

Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

Science.gov (United States)

Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

2015-10-06

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

American Spirit Pack Descriptors and Perceptions of Harm: A Crowdsourced Comparison of Modified Packs.

Science.gov (United States)

Pearson, Jennifer L; Richardson, Amanda; Feirman, Shari P; Villanti, Andrea C; Cantrell, Jennifer; Cohn, Amy; Tacelosky, Michael; Kirchner, Thomas R

2016-08-01

In 2015, the Food and Drug Administration issued warnings to three tobacco manufacturers who label their cigarettes as "additive-free" and/or "natural" on the grounds that they make unauthorized reduced risk claims. The goal of this study was to examine US adults' perceptions of three American Spirit (AS) pack descriptors ("Made with Organic Tobacco," "100% Additive-Free," and "100% US Grown Tobacco") to assess if they communicate reduced risk. In September 2012, three cross-sectional surveys were posted on Amazon Mechanical Turk. Adult participants evaluated the relative harm of a Marlboro Red pack versus three different AS packs with the descriptors "Made with Organic Tobacco," "100% Additive-Free," or "100% US Grown Tobacco" (Survey 1; n = 461); a Marlboro Red pack versus these AS packs modified to exclude descriptors (Survey 2; n = 857); and unmodified versus modified AS pack images (Survey 3; n = 1001). The majority of Survey 1 participants rated the unmodified AS packs as less harmful than the Marlboro Red pack; 35.4%-58.8% of Survey 2 participants also rated the modified (no claims) packs as less harmful than Marlboro Red. In these surveys, prior use of AS cigarettes was associated with reduced perceptions of risk (adjusted odds ratio [AOR] 1.59-2.40). "Made with Organic Tobacco" and "100% Additive-Free" were associated with reduced perceptions of risk when comparing the modified versus the unmodified AS packs (Survey 3). Data suggest that these AS pack descriptors communicate reduced harm messages to consumers. Findings have implications for regulatory actions related to product labeling and packaging. These findings provide additional evidence that the "Made with Organic Tobacco," "100% Additive-Free," and "100% US Grown" descriptors, as well as other aspects of the AS pack design, communicate reduced harm to non-, current, and former smokers. Additionally, they provide support for the importance of FDA's 2015 warning to Santa Fe Natural Tobacco Company on

Finding words in a language that allows words without vowels.

Science.gov (United States)

El Aissati, Abder; McQueen, James M; Cutler, Anne

2012-07-01

Across many languages from unrelated families, spoken-word recognition is subject to a constraint whereby potential word candidates must contain a vowel. This constraint minimizes competition from embedded words (e.g., in English, disfavoring win in twin because t cannot be a word). However, the constraint would be counter-productive in certain languages that allow stand-alone vowelless open-class words. One such language is Berber (where t is indeed a word). Berber listeners here detected words affixed to nonsense contexts with or without vowels. Length effects seen in other languages replicated in Berber, but in contrast to prior findings, word detection was not hindered by vowelless contexts. When words can be vowelless, otherwise universal constraints disfavoring vowelless words do not feature in spoken-word recognition. Copyright © 2012 Elsevier B.V. All rights reserved.

Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game

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Zai, Dawei; Li, Jonathan; Guo, Yulan; Cheng, Ming; Huang, Pengdi; Cao, Xiaofei; Wang, Cheng

2017-12-01

It is challenging to automatically register TLS point clouds with noise, outliers and varying overlap. In this paper, we propose a new method for pairwise registration of TLS point clouds. We first generate covariance matrix descriptors with an adaptive neighborhood size from point clouds to find candidate correspondences, we then construct a non-cooperative game to isolate mutual compatible correspondences, which are considered as true positives. The method was tested on three models acquired by two different TLS systems. Experimental results demonstrate that our proposed adaptive covariance (ACOV) descriptor is invariant to rigid transformation and robust to noise and varying resolutions. The average registration errors achieved on three models are 0.46 cm, 0.32 cm and 1.73 cm, respectively. The computational times cost on these models are about 288 s, 184 s and 903 s, respectively. Besides, our registration framework using ACOV descriptors and a game theoretic method is superior to the state-of-the-art methods in terms of both registration error and computational time. The experiment on a large outdoor scene further demonstrates the feasibility and effectiveness of our proposed pairwise registration framework.

A group of facial normal descriptors for recognizing 3D identical twins

KAUST Repository

Li, Huibin; Huang, Di; Chen, Liming; Wang, Yunhong; Morvan, Jean-Marie

2012-01-01

In this paper, to characterize and distinguish identical twins, three popular texture descriptors: i.e. local binary patterns (LBPs), gabor filters (GFs) and local gabor binary patterns (LGBPs) are employed to encode the normal components (x, y

Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

Science.gov (United States)

Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

2018-02-01

Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

Genetic dissimilarity among sweet potato genotypes using morphological and molecular descriptors

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Elisângela Knoblauch Viega de Andrade

2017-08-01

Full Text Available This study aimed to evaluate the genetic dissimilarity among sweet potato genotypes using morphological and molecular descriptors. The experiment was conducted in the Olericulture Sector at Federal University of Jequitinhonha and Mucuri Valleys (UFVJM and evaluated 60 sweet potato genotypes. For morphological characterization, 24 descriptors were used. For molecular characterization, 11 microsatellite primers specific for sweet potatoes were used, obtaining 210 polymorphic bands. Morphological and molecular diversity was obtained by dissimilarity matrices based on the coefficient of simple matching and the Jaccard index for morphological and molecular data, respectively. From these matrices, dendrograms were built. There is a large amount of genetic variability among sweet potato genotypes of the germplasm bank at UFVJM based on morphological and molecular characterizations. There was no duplicate suspicion or strong association between morphological and molecular analyses. Divergent accessions have been identified by molecular and morphological analyses, which can be used as parents in breeding programmes to produce progenies with high genetic variability.

Target matching based on multi-view tracking

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Liu, Yahui; Zhou, Changsheng

2011-01-01

A feature matching method is proposed based on Maximally Stable Extremal Regions (MSER) and Scale Invariant Feature Transform (SIFT) to solve the problem of the same target matching in multiple cameras. Target foreground is extracted by using frame difference twice and bounding box which is regarded as target regions is calculated. Extremal regions are got by MSER. After fitted into elliptical regions, those regions will be normalized into unity circles and represented with SIFT descriptors. Initial matching is obtained from the ratio of the closest distance to second distance less than some threshold and outlier points are eliminated in terms of RANSAC. Experimental results indicate the method can reduce computational complexity effectively and is also adapt to affine transformation, rotation, scale and illumination.

Social interaction facilitates word learning in preverbal infants: Word-object mapping and word segmentation.

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Hakuno, Yoko; Omori, Takahide; Yamamoto, Jun-Ichi; Minagawa, Yasuyo

2017-08-01

In natural settings, infants learn spoken language with the aid of a caregiver who explicitly provides social signals. Although previous studies have demonstrated that young infants are sensitive to these signals that facilitate language development, the impact of real-life interactions on early word segmentation and word-object mapping remains elusive. We tested whether infants aged 5-6 months and 9-10 months could segment a word from continuous speech and acquire a word-object relation in an ecologically valid setting. In Experiment 1, infants were exposed to a live tutor, while in Experiment 2, another group of infants were exposed to a televised tutor. Results indicate that both younger and older infants were capable of segmenting a word and learning a word-object association only when the stimuli were derived from a live tutor in a natural manner, suggesting that real-life interaction enhances the learning of spoken words in preverbal infants. Copyright © 2017 Elsevier Inc. All rights reserved.

Examining the Conditions of Using an On-Line Dictionary to Learn Words and Comprehend Texts

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Dilenschneider, Robert Francis

2018-01-01

This study investigated three look-up conditions for language learners to learn unknown target words and comprehend a reading passage when their attention is transferred away to an on-line dictionary. The research questions focused on how each look-up condition impacted the recall and recognition of word forms, word meanings, and passage…

The Influence of Concreteness of Concepts on the Integration of Novel Words into the Semantic Network.

Science.gov (United States)

Ding, Jinfeng; Liu, Wenjuan; Yang, Yufang

2017-01-01

On the basis of previous studies revealing a processing advantage of concrete words over abstract words, the current study aimed to further explore the influence of concreteness on the integration of novel words into semantic memory with the event related potential (ERP) technique. In the experiment during the learning phase participants read two-sentence contexts and inferred the meaning of novel words. The novel words were two-character non-words in Chinese language. Their meaning was either a concrete or abstract known concept which could be inferred from the contexts. During the testing phase participants performed a lexical decision task in which the learned novel words served as primes for either their corresponding concepts, semantically related or unrelated targets. For the concrete novel words, the semantically related words belonged to the same semantic categories with their corresponding concepts. For the abstract novel words, the semantically related words were synonyms of their corresponding concepts. The unrelated targets were real words which were concrete or abstract for the concrete or abstract novel words respectively. The ERP results showed that the corresponding concepts and the semantically related words elicited smaller N400s than the unrelated words. The N400 effect was not modulated by the concreteness of the concepts. In addition, the concrete corresponding concepts elicited a smaller late positive component (LPC) than the concrete unrelated words. This LPC effect was absent for the abstract words. The results indicate that although both concrete and abstract novel words can be acquired and linked to their related words in the semantic network after a short learning phase, the concrete novel words are learned better. Our findings support the (extended) dual coding theory and broaden our understanding of adult word learning and changes in concept organization.

The Influence of Concreteness of Concepts on the Integration of Novel Words into the Semantic Network

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Jinfeng Ding

2017-12-01

Full Text Available On the basis of previous studies revealing a processing advantage of concrete words over abstract words, the current study aimed to further explore the influence of concreteness on the integration of novel words into semantic memory with the event related potential (ERP technique. In the experiment during the learning phase participants read two-sentence contexts and inferred the meaning of novel words. The novel words were two-character non-words in Chinese language. Their meaning was either a concrete or abstract known concept which could be inferred from the contexts. During the testing phase participants performed a lexical decision task in which the learned novel words served as primes for either their corresponding concepts, semantically related or unrelated targets. For the concrete novel words, the semantically related words belonged to the same semantic categories with their corresponding concepts. For the abstract novel words, the semantically related words were synonyms of their corresponding concepts. The unrelated targets were real words which were concrete or abstract for the concrete or abstract novel words respectively. The ERP results showed that the corresponding concepts and the semantically related words elicited smaller N400s than the unrelated words. The N400 effect was not modulated by the concreteness of the concepts. In addition, the concrete corresponding concepts elicited a smaller late positive component (LPC than the concrete unrelated words. This LPC effect was absent for the abstract words. The results indicate that although both concrete and abstract novel words can be acquired and linked to their related words in the semantic network after a short learning phase, the concrete novel words are learned better. Our findings support the (extended dual coding theory and broaden our understanding of adult word learning and changes in concept organization.

Linguistic Context Versus Semantic Competition in Word Recognition by Younger and Older Adults With Cochlear Implants.

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Amichetti, Nicole M; Atagi, Eriko; Kong, Ying-Yee; Wingfield, Arthur

The increasing numbers of older adults now receiving cochlear implants raises the question of how the novel signal produced by cochlear implants may interact with cognitive aging in the recognition of words heard spoken within a linguistic context. The objective of this study was to pit the facilitative effects of a constraining linguistic context against a potential age-sensitive negative effect of response competition on effectiveness of word recognition. Younger (n = 8; mean age = 22.5 years) and older (n = 8; mean age = 67.5 years) adult implant recipients heard 20 target words as the final words in sentences that manipulated the target word's probability of occurrence within the sentence context. Data from published norms were also used to measure response entropy, calculated as the total number of different responses and the probability distribution of the responses suggested by the sentence context. Sentence-final words were presented to participants using a word-onset gating paradigm, in which a target word was presented with increasing amounts of its onset duration in 50 msec increments until the word was correctly identified. Results showed that for both younger and older adult implant users, the amount of word-onset information needed for correct recognition of sentence-final words was inversely proportional to their likelihood of occurrence within the sentence context, with older adults gaining differential advantage from the contextual constraints offered by a sentence context. On the negative side, older adults' word recognition was differentially hampered by high response entropy, with this effect being driven primarily by the number of competing responses that might also fit the sentence context. Consistent with previous research with normal-hearing younger and older adults, the present results showed older adult implant users' recognition of spoken words to be highly sensitive to linguistic context. This sensitivity, however, also resulted in a

Evidence for Separate Contributions of High and Low Spatial Frequencies during Visual Word Recognition.

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Winsler, Kurt; Holcomb, Phillip J; Midgley, Katherine J; Grainger, Jonathan

2017-01-01

Previous studies have shown that different spatial frequency information processing streams interact during the recognition of visual stimuli. However, it is a matter of debate as to the contributions of high and low spatial frequency (HSF and LSF) information for visual word recognition. This study examined the role of different spatial frequencies in visual word recognition using event-related potential (ERP) masked priming. EEG was recorded from 32 scalp sites in 30 English-speaking adults in a go/no-go semantic categorization task. Stimuli were white characters on a neutral gray background. Targets were uppercase five letter words preceded by a forward-mask (#######) and a 50 ms lowercase prime. Primes were either the same word (repeated) or a different word (un-repeated) than the subsequent target and either contained only high, only low, or full spatial frequency information. Additionally within each condition, half of the prime-target pairs were high lexical frequency, and half were low. In the full spatial frequency condition, typical ERP masked priming effects were found with an attenuated N250 (sub-lexical) and N400 (lexical-semantic) for repeated compared to un-repeated primes. For HSF primes there was a weaker N250 effect which interacted with lexical frequency, a significant reversal of the effect around 300 ms, and an N400-like effect for only high lexical frequency word pairs. LSF primes did not produce any of the classic ERP repetition priming effects, however they did elicit a distinct early effect around 200 ms in the opposite direction of typical repetition effects. HSF information accounted for many of the masked repetition priming ERP effects and therefore suggests that HSFs are more crucial for word recognition. However, LSFs did produce their own pattern of priming effects indicating that larger scale information may still play a role in word recognition.

Metal Oxide Nanomaterial QNAR Models: Available Structural Descriptors and Understanding of Toxicity Mechanisms

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Jiali Ying

2015-10-01

Full Text Available Metal oxide nanomaterials are widely used in various areas; however, the divergent published toxicology data makes it difficult to determine whether there is a risk associated with exposure to metal oxide nanomaterials. The application of quantitative structure activity relationship (QSAR modeling in metal oxide nanomaterials toxicity studies can reduce the need for time-consuming and resource-intensive nanotoxicity tests. The nanostructure and inorganic composition of metal oxide nanomaterials makes this approach different from classical QSAR study; this review lists and classifies some structural descriptors, such as size, cation charge, and band gap energy, in recent metal oxide nanomaterials quantitative nanostructure activity relationship (QNAR studies and discusses the mechanism of metal oxide nanomaterials toxicity based on these descriptors and traditional nanotoxicity tests.

Attention Blinks for Selection, Not Perception or Memory: Reading Sentences and Reporting Targets

Science.gov (United States)

Potter, Mary C.; Wyble, Brad; Olejarczyk, Jennifer

2011-01-01

In whole report, a sentence presented sequentially at the rate of about 10 words/s can be recalled accurately, whereas if the task is to report only two target words (e.g., red words), the second target suffers an attentional blink if it appears shortly after the first target. If these two tasks are carried out simultaneously, is there an…

A comparison of feature detectors and descriptors for object class matching

DEFF Research Database (Denmark)

Hietanen, Antti; Lankinen, Jukka; Kämäräinen, Joni-Kristian

2016-01-01

appearance variation can be large. We extend the benchmarks to the class matching setting and evaluate state-of-the-art detectors and descriptors with Caltech and ImageNet classes. Our experiments provide important findings with regard to object class matching: (1) the original SIFT is still the best...

Stroke subtype classification by geometrical descriptors of lesion shape.

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Bastian Cheng

Full Text Available Inference of etiology from lesion pattern in acute magnetic resonance imaging is valuable for management and prognosis of acute stroke patients. This study aims to assess the value of three-dimensional geometrical lesion-shape descriptors for stroke-subtype classification, specifically regarding stroke of cardioembolic origin.Stroke Etiology was classified according to ASCOD in retrospectively selected patients with acute stroke. Lesions were segmented on diffusion-weighed datasets, and descriptors of lesion shape quantified: surface area, sphericity, bounding box volume, and ratio between bounding box and lesion volume. Morphological measures were compared between stroke subtypes classified by ASCOD and between patients with embolic stroke of cardiac and non-cardiac source.150 patients (mean age 77 years; 95% CI, 65-80 years; median NIHSS 6, range 0-22 were included. Group comparison of lesion shape measures demonstrated that lesions caused by small-vessel disease were smaller and more spherical compared to other stroke subtypes. No significant differences of morphological measures were detected between patients with cardioembolic and non-cardioembolic stroke.Stroke lesions caused by small vessel disease can be distinguished from other stroke lesions based on distinctive morphological properties. However, within the group of embolic strokes, etiology could not be inferred from the morphology measures studied in our analysis.

A Few Words about Words | Poster

Science.gov (United States)

By Ken Michaels, Guest Writer In Shakepeare’s play “Hamlet,” Polonius inquires of the prince, “What do you read, my lord?” Not at all pleased with what he’s reading, Hamlet replies, “Words, words, words.”1 I have previously described the communication model in which a sender encodes a message and then sends it via some channel (or medium) to a receiver, who decodes the message

Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

Science.gov (United States)

Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

2013-10-30

In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.

Tracing the time course of picture--word processing.

Science.gov (United States)

Smith, M C; Magee, L E

1980-12-01

A number of independent lines of research have suggested that semantic and articulatory information become available differentially from pictures and words. The first of the experiments reported here sought to clarify the time course by which information about pictures and words becomes available by considering the pattern of interference generated when incongruent pictures and words are presented simultaneously in a Stroop-like situation. Previous investigators report that picture naming is easily disrupted by the presence of a distracting word but that word naming is relatively immune to interference from an incongruent picture. Under the assumption that information available from a completed process may disrupt an ongoing process, these results suggest that words access articulatory information more rapidly than do pictures. Experiment 1 extended this paradigm by requiring subjects to verify the category of the target stimulus. In accordance with the hypothesis that picture access the semantic code more rapidly than words, there was a reversal in the interference pattern: Word categorization suffered considerable disruption, whereas picture categorization was minimally affected by the presence of an incongruent word. Experiment 2 sought to further test the hypothesis that access to semantic and articulatory codes is different for pictures and words by examining memory for those items following naming or categorization. Categorized words were better recognized than named words, whereas the reverse was true for pictures, a result which suggests that picture naming involves more extensive processing than picture categorization. Experiment 3 replicated this result under conditions in which viewing time was held constant. The last experiment extended the investigation of memory differences to a situation in which subjects were required to generate the superordinate category name. Here, memory for categorized pictures was as good as memory for named pictures. Category

Words and possible words in early language acquisition.

Science.gov (United States)

Marchetto, Erika; Bonatti, Luca L

2013-11-01

In order to acquire language, infants must extract its building blocks-words-and master the rules governing their legal combinations from speech. These two problems are not independent, however: words also have internal structure. Thus, infants must extract two kinds of information from the same speech input. They must find the actual words of their language. Furthermore, they must identify its possible words, that is, the sequences of sounds that, being morphologically well formed, could be words. Here, we show that infants' sensitivity to possible words appears to be more primitive and fundamental than their ability to find actual words. We expose 12- and 18-month-old infants to an artificial language containing a conflict between statistically coherent and structurally coherent items. We show that 18-month-olds can extract possible words when the familiarization stream contains marks of segmentation, but cannot do so when the stream is continuous. Yet, they can find actual words from a continuous stream by computing statistical relationships among syllables. By contrast, 12-month-olds can find possible words when familiarized with a segmented stream, but seem unable to extract statistically coherent items from a continuous stream that contains minimal conflicts between statistical and structural information. These results suggest that sensitivity to word structure is in place earlier than the ability to analyze distributional information. The ability to compute nontrivial statistical relationships becomes fully effective relatively late in development, when infants have already acquired a considerable amount of linguistic knowledge. Thus, mechanisms for structure extraction that do not rely on extensive sampling of the input are likely to have a much larger role in language acquisition than general-purpose statistical abilities. Copyright © 2013. Published by Elsevier Inc.

Extraction of Linguistic Information from Successive Words during Reading: Evidence for Spatially Distributed Lexical Processing

Science.gov (United States)

Wang, Chin-An; Inhoff, Albrecht W.

2013-01-01

Two experiments examined whether word recognition progressed from one word to the next during reading, as maintained by sequential attention shift models such as the E-Z Reader model. The boundary technique was used to control the visibility of to-be-identified short target words, so that they were either previewed in the parafovea or masked. The…

Acquiring L2 Sentence Comprehension: A Longitudinal Study of Word Monitoring in Noise

Science.gov (United States)

Oliver, Georgina; Gullberg, Marianne; Hellwig, Frauke; Mitterer, Holger; Indefrey, Peter

2012-01-01

This study investigated the development of second language online auditory processing with ab initio German learners of Dutch. We assessed the influence of different levels of background noise and different levels of semantic and syntactic target word predictability on word-monitoring latencies. There was evidence of syntactic, but not…

Lexical association and false memory for words in two cultures.

Science.gov (United States)

Lee, Yuh-shiow; Chiang, Wen-Chi; Hung, Hsu-Ching

2008-01-01

This study examined the relationship between language experience and false memory produced by the DRM paradigm. The word lists used in Stadler, et al. (Memory & Cognition, 27, 494-500, 1999) were first translated into Chinese. False recall and false recognition for critical non-presented targets were then tested on a group of Chinese users. The average co-occurrence rate of the list word and the critical word was calculated based on two large Chinese corpuses. List-level analyses revealed that the correlation between the American and Taiwanese participants was significant only in false recognition. More importantly, the co-occurrence rate was significantly correlated with false recall and recognition of Taiwanese participants, and not of American participants. In addition, the backward association strength based on Nelson et al. (The University of South Florida word association, rhyme and word fragment norms, 1999) was significantly correlated with false recall of American participants and not of Taiwanese participants. Results are discussed in terms of the relationship between language experiences and lexical association in creating false memory for word lists.

Looking and touching: what extant approaches reveal about the structure of early word knowledge.

Science.gov (United States)

Hendrickson, Kristi; Mitsven, Samantha; Poulin-Dubois, Diane; Zesiger, Pascal; Friend, Margaret

2015-09-01

The goal of the current study is to assess the temporal dynamics of vision and action to evaluate the underlying word representations that guide infants' responses. Sixteen-month-old infants participated in a two-alternative forced-choice word-picture matching task. We conducted a moment-by-moment analysis of looking and reaching behaviors as they occurred in tandem to assess the speed with which a prompted word was processed (visual reaction time) as a function of the type of haptic response: Target, Distractor, or No Touch. Visual reaction times (visual RTs) were significantly slower during No Touches compared to Distractor and Target Touches, which were statistically indistinguishable. The finding that visual RTs were significantly faster during Distractor Touches compared to No Touches suggests that incorrect and absent haptic responses appear to index distinct knowledge states: incorrect responses are associated with partial knowledge whereas absent responses appear to reflect a true failure to map lexical items to their target referents. Further, we found that those children who were faster at processing words were also those children who exhibited better haptic performance. This research provides a methodological clarification on knowledge measured by the visual and haptic modalities and new evidence for a continuum of word knowledge in the second year of life. © 2014 The Authors Developmental Science Published by John Wiley & Sons Ltd.

The Effects of Lexical Pitch Accent on Infant Word Recognition in Japanese

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Mitsuhiko Ota

2018-01-01

Full Text Available Learners of lexical tone languages (e.g., Mandarin develop sensitivity to tonal contrasts and recognize pitch-matched, but not pitch-mismatched, familiar words by 11 months. Learners of non-tone languages (e.g., English also show a tendency to treat pitch patterns as lexically contrastive up to about 18 months. In this study, we examined if this early-developing capacity to lexically encode pitch variations enables infants to acquire a pitch accent system, in which pitch-based lexical contrasts are obscured by the interaction of lexical and non-lexical (i.e., intonational features. Eighteen 17-month-olds learning Tokyo Japanese were tested on their recognition of familiar words with the expected pitch or the lexically opposite pitch pattern. In early trials, infants were faster in shifting their eyegaze from the distractor object to the target object than in shifting from the target to distractor in the pitch-matched condition. In later trials, however, infants showed faster distractor-to-target than target-to-distractor shifts in both the pitch-matched and pitch-mismatched conditions. We interpret these results to mean that, in a pitch-accent system, the ability to use pitch variations to recognize words is still in a nascent state at 17 months.

Predicting English Word Reading Skills for Spanish-Speaking Students in First Grade.

Science.gov (United States)

Páez, Mariela; Rinaldi, Claudia

2006-10-01

This article describes the word reading skills in English and Spanish for a sample of 244 Spanish-speaking, English-learning (hence, bilingual) students in first grade and presents a predictive model for English word reading skills. The children in the study were assessed at the end of kindergarten and first grade, respectively. Data were gathered with 3 subtests of the Woodcock Language Proficiency Battery and a researcher-developed phonological awareness task. Results showed that, on average, children's English word reading skills were similar to monolingual norms whereas their Spanish word reading skills averaged 1 SD below the mean. English vocabulary, English phonological awareness, and Spanish word reading skills in kindergarten were found to be significant predictors of English word reading skills in first grade. Educational implications for screening language and reading skills and promising areas for targeted instruction for this population are discussed.

Search for descriptors that characterize an emerging discipline in WoS and SCOPUS: the case of mathematics education

Directory of Open Access Journals (Sweden)

Natividad Adamuz-Povedano

2013-03-01

Full Text Available Some social sciences become very complex due to de links and specific connexions with some others disciplines. This fact explains the necessity of identifying which are the main descriptors or keywords that characterize unequivocally their scientific production. One example of this is the case of mathematics education. This case is also special due to the existing ambiguity in the identification of validated keywords for it. Thus, it becomes necessary to establish a list of descriptors that characterize a research article as a Mathematics Education one. We present a methodology to obtain a core descriptors list for accessing to the Mathematic Education articles published in journals indexed by both the Web of Sciences (WoS and SCOPUS databases during a period of time of 30 years, since 1980 up to 2009.

A “loop” shape descriptor and its application to automated segmentation of airways from CT scans

Energy Technology Data Exchange (ETDEWEB)

Pu, Jiantao [Department of Radiology, First Affiliated Hospital of Medical College, Xi’an Jiaotong University, Shaanxi 710061, People’s Republic of China, and Departments of Radiology and Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15213 (United States); Jin, Chenwang, E-mail: jcw76@163.com; Yu, Nan; Qian, Yongqiang; Guo, Youmin [Department of Radiology, First Affiliated Hospital of Medical College, Xi’an Jiaotong University, Shaanxi 710061 (China); Wang, Xiaohua [Third Affiliated Hospital, Peking University, Beijing, People’s Republic of China, 100029 (China); Meng, Xin [Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania 15213 (United States)

2015-06-15

Purpose: A novel shape descriptor is presented to aid an automated identification of the airways depicted on computed tomography (CT) images. Methods: Instead of simplifying the tubular characteristic of the airways as an ideal mathematical cylindrical or circular shape, the proposed “loop” shape descriptor exploits the fact that the cross sections of any tubular structure (regardless of its regularity) always appear as a loop. In implementation, the authors first reconstruct the anatomical structures in volumetric CT as a three-dimensional surface model using the classical marching cubes algorithm. Then, the loop descriptor is applied to locate the airways with a concave loop cross section. To deal with the variation of the airway walls in density as depicted on CT images, a multiple threshold strategy is proposed. A publicly available chest CT database consisting of 20 CT scans, which was designed specifically for evaluating an airway segmentation algorithm, was used for quantitative performance assessment. Measures, including length, branch count, and generations, were computed under the aid of a skeletonization operation. Results: For the test dataset, the airway length ranged from 64.6 to 429.8 cm, the generation ranged from 7 to 11, and the branch number ranged from 48 to 312. These results were comparable to the performance of the state-of-the-art algorithms validated on the same dataset. Conclusions: The authors’ quantitative experiment demonstrated the feasibility and reliability of the developed shape descriptor in identifying lung airways.

Working Memory Load Affects Processing Time in Spoken Word Recognition: Evidence from Eye-Movements

Science.gov (United States)

Hadar, Britt; Skrzypek, Joshua E.; Wingfield, Arthur; Ben-David, Boaz M.

2016-01-01

In daily life, speech perception is usually accompanied by other tasks that tap into working memory capacity. However, the role of working memory on speech processing is not clear. The goal of this study was to examine how working memory load affects the timeline for spoken word recognition in ideal listening conditions. We used the “visual world” eye-tracking paradigm. The task consisted of spoken instructions referring to one of four objects depicted on a computer monitor (e.g., “point at the candle”). Half of the trials presented a phonological competitor to the target word that either overlapped in the initial syllable (onset) or at the last syllable (offset). Eye movements captured listeners' ability to differentiate the target noun from its depicted phonological competitor (e.g., candy or sandal). We manipulated working memory load by using a digit pre-load task, where participants had to retain either one (low-load) or four (high-load) spoken digits for the duration of a spoken word recognition trial. The data show that the high-load condition delayed real-time target discrimination. Specifically, a four-digit load was sufficient to delay the point of discrimination between the spoken target word and its phonological competitor. Our results emphasize the important role working memory plays in speech perception, even when performed by young adults in ideal listening conditions. PMID:27242424

Physician Preferences to Communicate Neuropsychological Results: Comparison of Qualitative Descriptors and a Proposal to Reduce Communication Errors.

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Schoenberg, Mike R; Osborn, Katie E; Mahone, E Mark; Feigon, Maia; Roth, Robert M; Pliskin, Neil H

2017-11-08

Errors in communication are a leading cause of medical errors. A potential source of error in communicating neuropsychological results is confusion in the qualitative descriptors used to describe standardized neuropsychological data. This study sought to evaluate the extent to which medical consumers of neuropsychological assessments believed that results/findings were not clearly communicated. In addition, preference data for a variety of qualitative descriptors commonly used to communicate normative neuropsychological test scores were obtained. Preference data were obtained for five qualitative descriptor systems as part of a larger 36-item internet-based survey of physician satisfaction with neuropsychological services. A new qualitative descriptor system termed the Simplified Qualitative Classification System (Q-Simple) was proposed to reduce the potential for communication errors using seven terms: very superior, superior, high average, average, low average, borderline, and abnormal/impaired. A non-random convenience sample of 605 clinicians identified from four United States academic medical centers from January 1, 2015 through January 7, 2016 were invited to participate. A total of 182 surveys were completed. A minority of clinicians (12.5%) indicated that neuropsychological study results were not clearly communicated. When communicating neuropsychological standardized scores, the two most preferred qualitative descriptor systems were by Heaton and colleagues (26%) and a newly proposed Q-simple system (22%). Comprehensive norms for an extended Halstead-Reitan battery: Demographic corrections, research findings, and clinical applications. Odessa, TX: Psychological Assessment Resources) (26%) and the newly proposed Q-Simple system (22%). Initial findings highlight the need to improve and standardize communication of neuropsychological results. These data offer initial guidance for preferred terms to communicate test results and form a foundation for more

QSAR analysis of salicylamide isosteres with the use of quantum chemical molecular descriptors.

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Dolezal, R; Van Damme, S; Bultinck, P; Waisser, K

2009-02-01

Quantitative relationships between the molecular structure and the biological activity of 49 isosteric salicylamide derivatives as potential antituberculotics with a new mechanism of action against three Mycobacterial strains were investigated. The molecular structures were represented by quantum chemical B3LYP/6-31G( *) based molecular descriptors. A resulting set of 220 molecular descriptors, including especially electronic properties, was statistically analyzed using multiple linear regression, resulting in acceptable and robust QSAR models. The best QSAR model was found for Mycobacterium tuberculosis (r(2)=0.92; q(2)=0.89), and somewhat less good QSAR models were found for Mycobacterium avium (r(2)=0.84; q(2)=0.78) and Mycobacterium kansasii (r(2)=0.80; q(2)=0.56). All QSAR models were cross-validated using the leave-10-out procedure.

Early language development in children with profound hearing loss fitted with a device at a young age: part I--the time period taken to acquire first words and first word combinations.

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Nott, Pauline; Cowan, Robert; Brown, P Margaret; Wigglesworth, Gillian

2009-10-01

Increasing numbers of infants and young children are now presenting to implantation centers and early intervention programs as the impact of universal newborn hearing screening programs is felt worldwide. Although results of a number of studies have highlighted the benefit of early identification and early fitting of hearing devices, there is relatively little research on the impact of early fitting of these devices on first language milestones. The aim of this study was to investigate the early spoken language milestones of young children with hearing loss (HL) from two perspectives: first, the acquisition of the first lexicon (i.e., the first 100 words) and second, the emergence of the first word combinations. Two groups of participants, one comprising 24 participants with profound HL and a second comprising 16 participants with normal hearing, were compared. Twenty-three participants in the HL group were fitted with a cochlear implant and one with bilateral hearing aids. All of these were "switched-on" or fitted before 30 months of age and half at words and any word combinations produced while reaching this single-word target. Acquisition of single words was compared by using the time period (in days) taken to reach several single-word targets (e.g., 50 words, 100 words) from the date of production of the first word. The emergence of word combinations was analyzed from two perspectives: first, the time (in days) from the date of production of the first word to the emergence of the first word combinations and second, the size of the single-word lexicon when word combinations emerged. The normal-hearing group required a significantly shorter time period to acquire the first 50 (mean words than the HL group. Although both groups demonstrated acceleration in lexical acquisition, the hearing group took significantly fewer days to reach the second 50 words relative to the first 50 words than did the HL group. Finally, the hearing group produced word combinations

Recurrent Partial Words

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Francine Blanchet-Sadri

2011-08-01

Full Text Available Partial words are sequences over a finite alphabet that may contain wildcard symbols, called holes, which match or are compatible with all letters; partial words without holes are said to be full words (or simply words. Given an infinite partial word w, the number of distinct full words over the alphabet that are compatible with factors of w of length n, called subwords of w, refers to a measure of complexity of infinite partial words so-called subword complexity. This measure is of particular interest because we can construct partial words with subword complexities not achievable by full words. In this paper, we consider the notion of recurrence over infinite partial words, that is, we study whether all of the finite subwords of a given infinite partial word appear infinitely often, and we establish connections between subword complexity and recurrence in this more general framework.

Effects of Word Width and Word Length on Optimal Character Size for Reading of Horizontally Scrolling Japanese Words.

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Teramoto, Wataru; Nakazaki, Takuyuki; Sekiyama, Kaoru; Mori, Shuji

2016-01-01

The present study investigated, whether word width and length affect the optimal character size for reading of horizontally scrolling Japanese words, using reading speed as a measure. In Experiment 1, three Japanese words, each consisting of four Hiragana characters, sequentially scrolled on a display screen from right to left. Participants, all Japanese native speakers, were instructed to read the words aloud as accurately as possible, irrespective of their order within the sequence. To quantitatively measure their reading performance, we used rapid serial visual presentation paradigm, where the scrolling rate was increased until the participants began to make mistakes. Thus, the highest scrolling rate at which the participants' performance exceeded 88.9% correct rate was calculated for each character size (0.3°, 0.6°, 1.0°, and 3.0°) and scroll window size (5 or 10 character spaces). Results showed that the reading performance was highest in the range of 0.6° to 1.0°, irrespective of the scroll window size. Experiment 2 investigated whether the optimal character size observed in Experiment 1 was applicable for any word width and word length (i.e., the number of characters in a word). Results showed that reading speeds were slower for longer than shorter words and the word width of 3.6° was optimal among the word lengths tested (three, four, and six character words). Considering that character size varied depending on word width and word length in the present study, this means that the optimal character size can be changed by word width and word length in scrolling Japanese words.

Abelian primitive words

OpenAIRE

Domaratzki, Michael; Rampersad, Narad

2011-01-01

We investigate Abelian primitive words, which are words that are not Abelian powers. We show that unlike classical primitive words, the set of Abelian primitive words is not context-free. We can determine whether a word is Abelian primitive in linear time. Also different from classical primitive words, we find that a word may have more than one Abelian root. We also consider enumeration problems and the relation to the theory of codes. Peer reviewed

Visual words assignment via information-theoretic manifold embedding.

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Deng, Yue; Li, Yipeng; Qian, Yanjun; Ji, Xiangyang; Dai, Qionghai

2014-10-01

Codebook-based learning provides a flexible way to extract the contents of an image in a data-driven manner for visual recognition. One central task in such frameworks is codeword assignment, which allocates local image descriptors to the most similar codewords in the dictionary to generate histogram for categorization. Nevertheless, existing assignment approaches, e.g., nearest neighbors strategy (hard assignment) and Gaussian similarity (soft assignment), suffer from two problems: 1) too strong Euclidean assumption and 2) neglecting the label information of the local descriptors. To address the aforementioned two challenges, we propose a graph assignment method with maximal mutual information (GAMI) regularization. GAMI takes the power of manifold structure to better reveal the relationship of massive number of local features by nonlinear graph metric. Meanwhile, the mutual information of descriptor-label pairs is ultimately optimized in the embedding space for the sake of enhancing the discriminant property of the selected codewords. According to such objective, two optimization models, i.e., inexact-GAMI and exact-GAMI, are respectively proposed in this paper. The inexact model can be efficiently solved with a closed-from solution. The stricter exact-GAMI nonparametrically estimates the entropy of descriptor-label pairs in the embedding space and thus leads to a relatively complicated but still trackable optimization. The effectiveness of GAMI models are verified on both the public and our own datasets.

Effects of word width and word length on optimal character size for reading of horizontally scrolling Japanese words

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Wataru eTeramoto

2016-02-01

Full Text Available The present study investigated whether word width and length affect the optimal character size for reading of horizontally scrolling Japanese words, using reading speed as a measure. In Experiment 1, three Japanese words, each consisting of 4 Hiragana characters, sequentially scrolled on a display screen from right to left. Participants, all Japanese native speakers, were instructed to read the words aloud as accurately as possible, irrespective of their order within the sequence. To quantitatively measure their reading performance, we used rapid serial visual presentation paradigm, where the scrolling rate was increased until the participants began to make mistakes. Thus, the highest scrolling rate at which the participants’ performance exceeded 88.9% correct rate was calculated for each character size (0.3, 0.6, 1.0, and 3.0° and scroll window size (5 or 10 character spaces. Results showed that the reading performance was highest in the range of 0.6° to 1.0°, irrespective of the scroll window size. Experiment 2 investigated whether the optimal character size observed in Experiment 1 was applicable for any word width and word length (i.e., the number of characters in a word. Results showed that reading speeds were slower for longer than shorter words and the word width of 3.6° was optimal among the word lengths tested (3, 4, and 6 character words. Considering that character size varied depending on word width and word length in the present study, this means that the optimal character size can be changed by word width and word length.

P2-13: Location word Cues' Effect on Location Discrimination Task: Cross-Modal Study

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Satoko Ohtsuka

2012-10-01

Full Text Available As is well known, participants are slower and make more errors in responding to the display color of an incongruent color word than a congruent one. This traditional stroop effect is often accounted for with relatively automatic and dominant word processing. Although the word dominance account has been widely supported, it is not clear in what extent of perceptual tasks it is valid. Here we aimed to examine whether the word dominance effect is observed in location stroop tasks and in audio-visual situations. The participants were required to press a key according to the location of visual (Experiment 1 and audio (Experiment 2 targets, left or right, as soon as possible. A cue of written (Experiments 1a and 2a or spoken (Experiments 1b and 2b location words, “left” or “right”, was presented on the left or right side of the fixation with cue lead times (CLT of 200 ms and 1200 ms. Reaction time from target presentation to key press was recorded as a dependent variable. The results were that the location validity effect was marked in within-modality but less so in cross-modality trials. The word validity effect was strong in within- but not in cross-modality trials. The CLT gave some effect of inhibition of return. So the word dominance could be less effective in location tasks and in cross-modal situations. The spatial correspondence seems to overcome the word effect.

The use of molecular descriptors in the development of co-amorphous formulations

DEFF Research Database (Denmark)

Meng-Lund, Helena Marie Lindholm; Korgaard, Georgia Kasten; Jensen, Katrine Birgitte Tarp

2018-01-01

-amorphisation between amino acid and drug. The predictions are thought to be used in an early screening phase to identify potential drug-amino acid combinations for further studies. A large variety of molecular descriptors was calculated for six drugs (carvedilol, mebendazole, carbamazepine, furosemide, indomethacin...

Development and Trialling of a Graduated Descriptors Tool for Australian Pharmacy Students

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Stupans, Ieva; Owen, Susanne; McKauge, Leigh; Pont, Lisa; Ryan, Greg; Woulfe, Jim

2012-01-01

Profession-derived competency standards are key determinants for curriculum and assessment in many professional university programmes. An Australian Learning and Teaching Council funded project used a participatory action research approach to enable the collaborative development of a graduated (or incremental) descriptors tool related to…

Evaluating the Performance of a Visually Guided Hearing Aid Using a Dynamic Auditory-Visual Word Congruence Task.

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Roverud, Elin; Best, Virginia; Mason, Christine R; Streeter, Timothy; Kidd, Gerald

2017-12-15

The "visually guided hearing aid" (VGHA), consisting of a beamforming microphone array steered by eye gaze, is an experimental device being tested for effectiveness in laboratory settings. Previous studies have found that beamforming without visual steering can provide significant benefits (relative to natural binaural listening) for speech identification in spatialized speech or noise maskers when sound sources are fixed in location. The aim of the present study was to evaluate the performance of the VGHA in listening conditions in which target speech could switch locations unpredictably, requiring visual steering of the beamforming. To address this aim, the present study tested an experimental simulation of the VGHA in a newly designed dynamic auditory-visual word congruence task. Ten young normal-hearing (NH) and 11 young hearing-impaired (HI) adults participated. On each trial, three simultaneous spoken words were presented from three source positions (-30, 0, and 30 azimuth). An auditory-visual word congruence task was used in which participants indicated whether there was a match between the word printed on a screen at a location corresponding to the target source and the spoken target word presented acoustically from that location. Performance was compared for a natural binaural condition (stimuli presented using impulse responses measured on KEMAR), a simulated VGHA condition (BEAM), and a hybrid condition that combined lowpass-filtered KEMAR and highpass-filtered BEAM information (BEAMAR). In some blocks, the target remained fixed at one location across trials, and in other blocks, the target could transition in location between one trial and the next with a fixed but low probability. Large individual variability in performance was observed. There were significant benefits for the hybrid BEAMAR condition relative to the KEMAR condition on average for both NH and HI groups when the targets were fixed. Although not apparent in the averaged data, some

Protein-protein docking using region-based 3D Zernike descriptors

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Sael Lee

2009-12-01

Full Text Available Abstract Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for

Primary phonological planning units in spoken word production are language-specific: Evidence from an ERP study.

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Wang, Jie; Wong, Andus Wing-Kuen; Wang, Suiping; Chen, Hsuan-Chih

2017-07-19

It is widely acknowledged in Germanic languages that segments are the primary planning units at the phonological encoding stage of spoken word production. Mixed results, however, have been found in Chinese, and it is still unclear what roles syllables and segments play in planning Chinese spoken word production. In the current study, participants were asked to first prepare and later produce disyllabic Mandarin words upon picture prompts and a response cue while electroencephalogram (EEG) signals were recorded. Each two consecutive pictures implicitly formed a pair of prime and target, whose names shared the same word-initial atonal syllable or the same word-initial segments, or were unrelated in the control conditions. Only syllable repetition induced significant effects on event-related brain potentials (ERPs) after target onset: a widely distributed positivity in the 200- to 400-ms interval and an anterior positivity in the 400- to 600-ms interval. We interpret these to reflect syllable-size representations at the phonological encoding and phonetic encoding stages. Our results provide the first electrophysiological evidence for the distinct role of syllables in producing Mandarin spoken words, supporting a language specificity hypothesis about the primary phonological units in spoken word production.

Not all reading is alike: Task modulation of magnetic evoked response to visual word

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Pavlova A. A.

2017-09-01

Full Text Available Background. Previous studies have shown that brain response to a written word depends on the task: whether the word is a target in a version of lexical decision task or should be read silently. Although this effect has been interpreted as an evidence for an interaction between word recognition processes and task demands, it also may be caused by greater attention allocation to the target word. Objective. We aimed to examine the task effect on brain response evoked by non- target written words. Design. Using MEG and magnetic source imaging, we compared spatial-temporal pattern of brain response elicited by a noun cue when it was read silently either without additional task (SR or with a requirement to produce an associated verb (VG. Results.The task demands penetrated into early (200-300 ms and late (500-800 ms stages of a word processing by enhancing brain response under VG versus SR condition. The cortical sources of the early response were localized to bilateral inferior occipitotemporal and anterior temporal cortex suggesting that more demanding VG task required elaborated lexical-semantic analysis. The late effect was observed in the associative auditory areas in middle and superior temporal gyri and in motor representation of articulators. Our results suggest that a remote goal plays a pivotal role in enhanced recruitment of cortical structures underlying orthographic, semantic and sensorimotor dimensions of written word perception from the early processing stages. Surprisingly, we found that to fulfil a more challenging goal the brain progressively engaged resources of the right hemisphere throughout all stages of silent reading. Conclusion. Our study demonstrates that a deeper processing of linguistic input amplifies activation of brain areas involved in integration of speech perception and production. This is consistent with theories that emphasize the role of sensorimotor integration in speech understanding.

Electronic forces as descriptors of nucleophilic and electrophilic regioselectivity and stereoselectivity.

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Liu, Shubin; Rong, Chunying; Lu, Tian

2017-01-04

One of the main tasks of theoretical chemistry is to rationalize computational results with chemical insights. Key concepts of such nature include nucleophilicity, electrophilicity, regioselectivity, and stereoselectivity. While computational tools are available to predict barrier heights and other reactivity properties with acceptable accuracy, a conceptual framework to appreciate above quantities is still lacking. In this work, we introduce the electronic force as the fundamental driving force of chemical processes to understand and predict molecular reactivity. It has three components but only two are independent. These forces, electrostatic and steric, can be employed as reliable descriptors for nucleophilic and electrophilic regioselectivity and stereoselectivity. The advantages of using these forces to evaluate molecular reactivity are that electrophilic and nucleophilic attacks are featured by distinct characteristics in the electrostatic force and no knowledge of quantum effects included in the kinetic and exchange-correlation energies is required. Examples are provided to highlight the validity and general applicability of these reactivity descriptors. Possible applications in ambident reactivity, σ and π holes, frustrated Lewis pairs, and stereoselective reactions are also included in this work.

Word categorization from distributional information: frames confer more than the sum of their (Bigram) parts.

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Mintz, Toben H; Wang, Felix Hao; Li, Jia

2014-12-01

Grammatical categories, such as noun and verb, are the building blocks of syntactic structure and the components that govern the grammatical patterns of language. However, in many languages words are not explicitly marked with their category information, hence a critical part of acquiring a language is categorizing the words. Computational analyses of child-directed speech have shown that distributional information-information about how words pattern with one another in sentences-could be a useful source of initial category information. Yet questions remain as to whether learners use this kind of information, and if so, what kinds of distributional patterns facilitate categorization. In this paper we investigated how adults exposed to an artificial language use distributional information to categorize words. We compared training situations in which target words occurred in frames (i.e., surrounded by two words that frequently co-occur) against situations in which target words occurred in simpler bigram contexts (where an immediately adjacent word provides the context for categorization). We found that learners categorized words together when they occurred in similar frame contexts, but not when they occurred in similar bigram contexts. These findings are particularly relevant because they accord with computational investigations showing that frame contexts provide accurate category information cross-linguistically. We discuss these findings in the context of prior research on distribution-based categorization and the broader implications for the role of distributional categorization in language acquisition. Copyright © 2014 Elsevier Inc. All rights reserved.

Neural correlates of an early attentional capture by positive distractor words

OpenAIRE

José Antonio Hinojosa; Francisco eMercado; Jacobo eAlbert; Jacobo eAlbert; Paloma eBarjola; Irene ePeláez; Cristina eVillalba-García; Luis eCarretié

2015-01-01

Exogenous or automatic attention to emotional distractors has been observed for emotional scenes and faces. In the language domain, however, automatic attention capture by emotional words has been scarcely investigated. In the current event-related potentials study we explored distractor effects elicited by positive, negative and neutral words in a concurrent but distinct target distractor paradigm. Specifically, participants performed a digit categorization task in which task-irrelevant wor...

Identification of Electronic and Structural Descriptors of Adenosine Analogues Related to Inhibition of Leishmanial Glyceraldehyde-3-Phosphate Dehydrogenase

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Norka B. H. Lozano

2013-04-01

Full Text Available Quantitative structure–activity relationship (QSAR studies were performed in order to identify molecular features responsible for the antileishmanial activity of 61 adenosine analogues acting as inhibitors of the enzyme glyceraldehyde 3-phosphate dehydrogenase of Leishmania mexicana (LmGAPDH. Density functional theory (DFT was employed to calculate quantum-chemical descriptors, while several structural descriptors were generated with Dragon 5.4. Variable selection was undertaken with the ordered predictor selection (OPS algorithm, which provided a set with the most relevant descriptors to perform PLS, PCR and MLR regressions. Reliable and predictive models were obtained, as attested by their high correlation coefficients, as well as the agreement between predicted and experimental values for an external test set. Additional validation procedures were carried out, demonstrating that robust models were developed, providing helpful tools for the optimization of the antileishmanial activity of adenosine compounds.