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Sample records for model descriptor consistent

  1. Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets

    Science.gov (United States)

    2013-01-01

    Background While a large body of work exists on comparing and benchmarking descriptors of molecular structures, a similar comparison of protein descriptor sets is lacking. Hence, in the current work a total of 13 amino acid descriptor sets have been benchmarked with respect to their ability of establishing bioactivity models. The descriptor sets included in the study are Z-scales (3 variants), VHSE, T-scales, ST-scales, MS-WHIM, FASGAI, BLOSUM, a novel protein descriptor set (termed ProtFP (4 variants)), and in addition we created and benchmarked three pairs of descriptor combinations. Prediction performance was evaluated in seven structure-activity benchmarks which comprise Angiotensin Converting Enzyme (ACE) dipeptidic inhibitor data, and three proteochemometric data sets, namely (1) GPCR ligands modeled against a GPCR panel, (2) enzyme inhibitors (NNRTIs) with associated bioactivities against a set of HIV enzyme mutants, and (3) enzyme inhibitors (PIs) with associated bioactivities on a large set of HIV enzyme mutants. Results The amino acid descriptor sets compared here show similar performance (set differences ( > 0.3 log units RMSE difference and >0.7 difference in MCC). Combining different descriptor sets generally leads to better modeling performance than utilizing individual sets. The best performers were Z-scales (3) combined with ProtFP (Feature), or Z-Scales (3) combined with an average Z-Scale value for each target, while ProtFP (PCA8), ST-Scales, and ProtFP (Feature) rank last. Conclusions While amino acid descriptor sets capture different aspects of amino acids their ability to be used for bioactivity modeling is still – on average – surprisingly similar. Still, combining sets describing complementary information consistently leads to small but consistent improvement in modeling performance (average MCC 0.01 better, average RMSE 0.01 log units lower). Finally, performance differences exist between the targets compared thereby underlining that

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

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    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.

  3. Discretizing LTI Descriptor (Regular Differential Input Systems with Consistent Initial Conditions

    Directory of Open Access Journals (Sweden)

    Athanasios D. Karageorgos

    2010-01-01

    Full Text Available A technique for discretizing efficiently the solution of a Linear descriptor (regular differential input system with consistent initial conditions, and Time-Invariant coefficients (LTI is introduced and fully discussed. Additionally, an upper bound for the error ‖x¯(kT−x¯k‖ that derives from the procedure of discretization is also provided. Practically speaking, we are interested in such kind of systems, since they are inherent in many physical, economical and engineering phenomena.

  4. 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.

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

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    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.

  6. 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.

  7. Systems biological approach of molecular descriptors connectivity: optimal descriptors for oral bioavailability prediction.

    Science.gov (United States)

    Ahmed, Shiek S S J; Ramakrishnan, V

    2012-01-01

    Poor oral bioavailability is an important parameter accounting for the failure of the drug candidates. Approximately, 50% of developing drugs fail because of unfavorable oral bioavailability. In silico prediction of oral bioavailability (%F) based on physiochemical properties are highly needed. Although many computational models have been developed to predict oral bioavailability, their accuracy remains low with a significant number of false positives. In this study, we present an oral bioavailability model based on systems biological approach, using a machine learning algorithm coupled with an optimal discriminative set of physiochemical properties. The models were developed based on computationally derived 247 physicochemical descriptors from 2279 molecules, among which 969, 605 and 705 molecules were corresponds to oral bioavailability, intestinal absorption (HIA) and caco-2 permeability data set, respectively. The partial least squares discriminate analysis showed 49 descriptors of HIA and 50 descriptors of caco-2 are the major contributing descriptors in classifying into groups. Of these descriptors, 47 descriptors were commonly associated to HIA and caco-2, which suggests to play a vital role in classifying oral bioavailability. To determine the best machine learning algorithm, 21 classifiers were compared using a bioavailability data set of 969 molecules with 47 descriptors. Each molecule in the data set was represented by a set of 47 physiochemical properties with the functional relevance labeled as (+bioavailability/-bioavailability) to indicate good-bioavailability/poor-bioavailability molecules. The best-performing algorithm was the logistic algorithm. The correlation based feature selection (CFS) algorithm was implemented, which confirms that these 47 descriptors are the fundamental descriptors for oral bioavailability prediction. The logistic algorithm with 47 selected descriptors correctly predicted the oral bioavailability, with a predictive accuracy

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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.

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

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    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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

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

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    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.

  2. 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

  3. 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.

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

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    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.

  5. 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

  6. 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

  7. 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.

  8. 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...

  9. 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.

  10. 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...

  11. 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.

  12. 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...

  13. Module descriptor

    DEFF Research Database (Denmark)

    Vincenti, Gordon; Klausen, Bodil; Kjær Jensen, Jesper

    2016-01-01

    The Module Descriptor including a Teacher’s Guide explains and describes how to work innovatively and co-creatively with wicked problems and young people. The descriptor shows how interested educators and lecturers in Europe can copy the lessons of the Erasmus+ project HIP when teaching their own...

  14. Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates

    Science.gov (United States)

    Crivori, Patrizia; Zamora, Ismael; Speed, Bill; Orrenius, Christian; Poggesi, Italo

    2004-03-01

    A number of computational approaches are being proposed for an early optimization of ADME (absorption, distribution, metabolism and excretion) properties to increase the success rate in drug discovery. The present study describes the development of an in silico model able to estimate, from the three-dimensional structure of a molecule, the stability of a compound with respect to the human cytochrome P450 (CYP) 3A4 enzyme activity. Stability data were obtained by measuring the amount of unchanged compound remaining after a standardized incubation with human cDNA-expressed CYP3A4. The computational method transforms the three-dimensional molecular interaction fields (MIFs) generated from the molecular structure into descriptors (VolSurf and Almond procedures). The descriptors were correlated to the experimental metabolic stability classes by a partial least squares discriminant procedure. The model was trained using a set of 1800 compounds from the Pharmacia collection and was validated using two test sets: the first one including 825 compounds from the Pharmacia collection and the second one consisting of 20 known drugs. This model correctly predicted 75% of the first and 85% of the second test set and showed a precision above 86% to correctly select metabolically stable compounds. The model appears a valuable tool in the design of virtual libraries to bias the selection toward more stable compounds. Abbreviations: ADME - absorption, distribution, metabolism and excretion; CYP - cytochrome P450; MIFs - molecular interaction fields; HTS - high throughput screening; DDI - drug-drug interactions; 3D - three-dimensional; PCA - principal components analysis; CPCA - consensus principal components analysis; PLS - partial least squares; PLSD - partial least squares discriminant; GRIND - grid independent descriptors; GRID - software originally created and developed by Professor Peter Goodford.

  15. Stereo matching based on SIFT descriptor with illumination and camera invariance

    Science.gov (United States)

    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

  16. QSAR modeling of toxicity of diverse organic chemicals to Daphnia magna using 2D and 3D descriptors

    International Nuclear Information System (INIS)

    Kar, Supratik; Roy, Kunal

    2010-01-01

    One of the major economic alternatives to experimental toxicity testing is the use of quantitative structure-activity relationships (QSARs) which are used in formulating regulatory decisions of environmental protection agencies. In this background, we have modeled a large diverse group of 297 chemicals for their toxicity to Daphnia magna using mechanistically interpretable descriptors. Three-dimensional (3D) (electronic and spatial) and two-dimensional (2D) (topological and information content indices) descriptors along with physicochemical parameter log K o/w (n-octanol/water partition coefficient) and structural descriptors were used as predictor variables. The QSAR models were developed by stepwise multiple linear regression (MLR), partial least squares (PLS), genetic function approximation (GFA), and genetic PLS (G/PLS). All the models were validated internally and externally. Among several models developed using different chemometric tools, the best model based on both internal and external validation characteristics was a PLS equation with 7 descriptors and three latent variables explaining 67.8% leave-one-out predicted variance and 74.1% external predicted variance. The PLS model suggests that higher lipophilicity and electrophilicity, less negative charge surface area and presence of ether linkage, hydrogen bond donor groups and acetylenic carbons are responsible for greater toxicity of chemicals. The developed model may be used for prediction of toxicity, safety and risk assessment of chemicals to achieve better ecotoxicological management and prevent adverse health consequences.

  17. QSAR modeling of toxicity of diverse organic chemicals to Daphnia magna using 2D and 3D descriptors

    Energy Technology Data Exchange (ETDEWEB)

    Kar, Supratik [Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Raja S C Mullick Road, Kolkata 700032 (India); Roy, Kunal, E-mail: kunalroy_in@yahoo.com [Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Raja S C Mullick Road, Kolkata 700032 (India)

    2010-05-15

    One of the major economic alternatives to experimental toxicity testing is the use of quantitative structure-activity relationships (QSARs) which are used in formulating regulatory decisions of environmental protection agencies. In this background, we have modeled a large diverse group of 297 chemicals for their toxicity to Daphnia magna using mechanistically interpretable descriptors. Three-dimensional (3D) (electronic and spatial) and two-dimensional (2D) (topological and information content indices) descriptors along with physicochemical parameter log K{sub o/w} (n-octanol/water partition coefficient) and structural descriptors were used as predictor variables. The QSAR models were developed by stepwise multiple linear regression (MLR), partial least squares (PLS), genetic function approximation (GFA), and genetic PLS (G/PLS). All the models were validated internally and externally. Among several models developed using different chemometric tools, the best model based on both internal and external validation characteristics was a PLS equation with 7 descriptors and three latent variables explaining 67.8% leave-one-out predicted variance and 74.1% external predicted variance. The PLS model suggests that higher lipophilicity and electrophilicity, less negative charge surface area and presence of ether linkage, hydrogen bond donor groups and acetylenic carbons are responsible for greater toxicity of chemicals. The developed model may be used for prediction of toxicity, safety and risk assessment of chemicals to achieve better ecotoxicological management and prevent adverse health consequences.

  18. 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 ...

  19. 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...

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

    Science.gov (United States)

    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.

  1. 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.

  2. 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.

  3. 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.

  4. Improved nucleic acid descriptors for siRNA efficacy prediction.

    Science.gov (United States)

    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.

  5. Stargate GTM: Bridging Descriptor and Activity Spaces.

    Science.gov (United States)

    Gaspar, Héléna A; Baskin, Igor I; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

    2015-11-23

    Predicting the activity profile of a molecule or discovering structures possessing a specific activity profile are two important goals in chemoinformatics, which could be achieved by bridging activity and molecular descriptor spaces. In this paper, we introduce the "Stargate" version of the Generative Topographic Mapping approach (S-GTM) in which two different multidimensional spaces (e.g., structural descriptor space and activity space) are linked through a common 2D latent space. In the S-GTM algorithm, the manifolds are trained simultaneously in two initial spaces using the probabilities in the 2D latent space calculated as a weighted geometric mean of probability distributions in both spaces. S-GTM has the following interesting features: (1) activities are involved during the training procedure; therefore, the method is supervised, unlike conventional GTM; (2) using molecular descriptors of a given compound as input, the model predicts a whole activity profile, and (3) using an activity profile as input, areas populated by relevant chemical structures can be detected. To assess the performance of S-GTM prediction models, a descriptor space (ISIDA descriptors) of a set of 1325 GPCR ligands was related to a B-dimensional (B = 1 or 8) activity space corresponding to pKi values for eight different targets. S-GTM outperforms conventional GTM for individual activities and performs similarly to the Lasso multitask learning algorithm, although it is still slightly less accurate than the Random Forest method.

  6. 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.

  7. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  9. 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.

  10. 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...

  11. In silico modelling of permeation enhancement potency in Caco-2 monolayers based on molecular descriptors and random forest

    DEFF Research Database (Denmark)

    Welling, Søren Havelund; Clemmensen, Line Katrine Harder; Buckley, Stephen T.

    2015-01-01

    has been developed.The random forest-QSAR model was based upon Caco-2 data for 41 surfactant-like permeation enhancers from Whitehead et al. (2008) and molecular descriptors calculated from their structure.The QSAR model was validated by two test-sets: (i) an eleven compound experimental set with Caco......-2 data and (ii) nine compounds with Caco-2 data from literature. Feature contributions, a recent developed diagnostic tool, was applied to elucidate the contribution of individual molecular descriptors to the predicted potency. Feature contributions provided easy interpretable suggestions...

  12. 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…

  13. FEATURE DESCRIPTOR BY CONVOLUTION AND POOLING AUTOENCODERS

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  15. The discussion of descriptors for the QSAR model and molecular dynamics simulation of benzimidazole derivatives as corrosion inhibitors

    International Nuclear Information System (INIS)

    Li, Lu; Zhang, Xiuhui; Gong, Shida; Zhao, Hongxia; Bai, Yang; Li, Qianshu; Ji, Lin

    2015-01-01

    Graphical abstract: - Highlights: • Aromaticity is used as a descriptor in QSAR model to describe corrosion inhibition. • Improved calculation of I and A is correlated well with inhibition efficiencies. • Binding energies were calculated using a realistic corrosion environment. • Nonlinear QSAR model was built by support vector machine with radial basis function. • Six designed benzimidazole molecules are predicted with high inhibition efficiencies. - Abstract: The corrosion inhibition performances of 20 protonated benzimidazole derivatives were studied using theoretical methods. Nuclear Independent Chemical Shift (NICS), the measurement of aromaticity, demonstrated good correlation with inhibition efficiencies and was used as a descriptor. Binding energies were calculated on the basis of molecular dynamics simulations using a realistic corrosive environment. Some improved descriptors correlate well with experimental inhibition efficiencies. A reliable nonlinear quantitative structure–activity relationship model was constructed by a support vector machine approach. The correlation coefficient and root-mean-square error were 0.96 and 6.79%, respectively. Additionally, six new benzimidazole molecules were designed, and their inhibition efficiencies were predicted.

  16. Functional Constructivism: In Search of Formal Descriptors.

    Science.gov (United States)

    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.'

  17. hERG classification model based on a combination of support vector machine method and GRIND descriptors

    DEFF Research Database (Denmark)

    Li, Qiyuan; Jorgensen, Flemming Steen; Oprea, Tudor

    2008-01-01

    and diverse library of 495 compounds. The models combine pharmacophore-based GRIND descriptors with a support vector machine (SVM) classifier in order to discriminate between hERG blockers and nonblockers. Our models were applied at different thresholds from 1 to 40 mu m and achieved an overall accuracy up...

  18. 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.

  19. A Spherical Model Based Keypoint Descriptor and Matching Algorithm for Omnidirectional Images

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available Omnidirectional images generally have nonlinear distortion in radial direction. Unfortunately, traditional algorithms such as scale-invariant feature transform (SIFT and Descriptor-Nets (D-Nets do not work well in matching omnidirectional images just because they are incapable of dealing with the distortion. In order to solve this problem, a new voting algorithm is proposed based on the spherical model and the D-Nets algorithm. Because the spherical-based keypoint descriptor contains the distortion information of omnidirectional images, the proposed matching algorithm is invariant to distortion. Keypoint matching experiments are performed on three pairs of omnidirectional images, and comparison is made among the proposed algorithm, the SIFT and the D-Nets. The result shows that the proposed algorithm is more robust and more precise than the SIFT, and the D-Nets in matching omnidirectional images. Comparing with the SIFT and the D-Nets, the proposed algorithm has two main advantages: (a there are more real matching keypoints; (b the coverage range of the matching keypoints is wider, including the seriously distorted areas.

  20. 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.

  1. Human Activity-Understanding: A Multilayer Approach Combining Body Movements and Contextual Descriptors Analysis

    Directory of Open Access Journals (Sweden)

    Consuelo Granata

    2015-07-01

    Full Text Available A deep understanding of human activity is key to successful human-robot interaction (HRI. The translation of sensed human behavioural signals/cues and context descriptors into an encoded human activity remains a challenge because of the complex nature of human actions. In this paper, we propose a multilayer framework for the understanding of human activity to be implemented in a mobile robot. It consists of a perception layer which exploits a D-RGB-based skeleton tracking output used to simulate a physical model of virtual human dynamics in order to compensate for the inaccuracy and inconsistency of the raw data. A multi-support vector machine (MSVM model trained with features describing the human motor coordination through temporal segments in combination with environment descriptors (object affordance is used to recognize each sub-activity (classification layer. The interpretation of sequences of classified elementary actions is based on discrete hidden Markov models (DHMMs (interpretation layer. The framework assessment was performed on the Cornell Activity Dataset (CAD-120 [1]. The performances of our method are comparable with those presented in [2] and clearly show the relevance of this model-based approach.

  2. 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.

  3. TreeBASIS Feature Descriptor and Its Hardware Implementation

    Directory of Open Access Journals (Sweden)

    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.

  4. Quantitative structure-retention relationships of pesticides in reversed-phase high-performance liquid chromatography based on WHIM and GETAWAY molecular 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; Maggi, Maria Anna; Mazzeo, Pietro; Ruggieri, Fabrizio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)

    2008-11-03

    The ability of the Weighted Holistic Invariant Molecular (WHIM) and GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) descriptors to represent the effect of molecular structure on the retention of pesticides in reversed-phase high-performance liquid chromatography (RP-HPLC) is investigated. To this end, two retention data sets previously collected in water-acetonitrile mobile phase are re-examined. The first data set (data-set-1) consists of retention data of 26 neutral compounds belonging to widely used pesticide classes, collected within the mobile phase composition range 40-65% (v/v) acetonitrile. The second data set (data-set-2) describes retention of phenoxy acid herbicides and structurally related compounds (benzoic acid and phenylacetic acid derivatives), as a whole covering the pK{sub a} range 2.3-4.3, as a function of mobile phase composition, ranging between 30 and 70% (v/v) acetonitrile, and pH, ranging between 2 and 5. For each data set, the mobile phase attributes are combined with WHIM or GETAWAY descriptors into 'mixed' predictive models in order to attempt retention modelling within the whole mobile phase composition range of analytical interest. Six- or seven-dimensional multilinear models, preliminarily selected using a genetic algorithm, were improved using a multi-layer artificial neural network (ANN) learned by back propagation. ANN performance was tested on three molecules not used in the learning stage and by leave-more-out cross validation. The results reveal that while WHIM descriptors seem not adequate to model retention of solutes of data-set-1, GETAWAY descriptors provide a satisfactory retention model. On the other hand WHIM and GETAWAY descriptors applied to data-set-2 provide a similar performance, even if slightly worse as compared with the above case. Accuracy of retention modelling in these cases is comparable or slightly poorer as compared with the results previously obtained by combining quantum chemical

  5. Quantitative structure-retention relationships of pesticides in reversed-phase high-performance liquid chromatography based on WHIM and GETAWAY molecular descriptors

    International Nuclear Information System (INIS)

    D'Archivio, Angelo Antonio; Maggi, Maria Anna; Mazzeo, Pietro; Ruggieri, Fabrizio

    2008-01-01

    The ability of the Weighted Holistic Invariant Molecular (WHIM) and GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) descriptors to represent the effect of molecular structure on the retention of pesticides in reversed-phase high-performance liquid chromatography (RP-HPLC) is investigated. To this end, two retention data sets previously collected in water-acetonitrile mobile phase are re-examined. The first data set (data-set-1) consists of retention data of 26 neutral compounds belonging to widely used pesticide classes, collected within the mobile phase composition range 40-65% (v/v) acetonitrile. The second data set (data-set-2) describes retention of phenoxy acid herbicides and structurally related compounds (benzoic acid and phenylacetic acid derivatives), as a whole covering the pK a range 2.3-4.3, as a function of mobile phase composition, ranging between 30 and 70% (v/v) acetonitrile, and pH, ranging between 2 and 5. For each data set, the mobile phase attributes are combined with WHIM or GETAWAY descriptors into 'mixed' predictive models in order to attempt retention modelling within the whole mobile phase composition range of analytical interest. Six- or seven-dimensional multilinear models, preliminarily selected using a genetic algorithm, were improved using a multi-layer artificial neural network (ANN) learned by back propagation. ANN performance was tested on three molecules not used in the learning stage and by leave-more-out cross validation. The results reveal that while WHIM descriptors seem not adequate to model retention of solutes of data-set-1, GETAWAY descriptors provide a satisfactory retention model. On the other hand WHIM and GETAWAY descriptors applied to data-set-2 provide a similar performance, even if slightly worse as compared with the above case. Accuracy of retention modelling in these cases is comparable or slightly poorer as compared with the results previously obtained by combining quantum chemical descriptors or usual

  6. Covariance descriptor fusion for target detection

    Science.gov (United States)

    Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

    2016-05-01

    Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.

  7. Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

    Science.gov (United States)

    Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

    2008-06-01

    In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

  8. 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.

  9. MPEG-7 low level image descriptors for modeling users' web pages visual appeal opinion

    OpenAIRE

    Uribe Mayoral, Silvia; Alvarez Garcia, Federico; Menendez Garcia, Jose Manuel

    2015-01-01

    The study of the users' web pages first impression is an important factor for interface designers, due to its influence over the final opinion about a site. In this regard, the analysis of web aesthetics can be considered as an interesting tool for evaluating this early impression, and the use of low level image descriptors for modeling it in an objective way represents an innovative research field. According to this, in this paper we present a new model for website aesthetics evaluation and ...

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. Replenishing data descriptors in a DMA injection FIFO buffer

    Science.gov (United States)

    Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Cernohous, Bob R [Rochester, MN; Heidelberger, Philip [Cortlandt Manor, NY; Kumar, Sameer [White Plains, NY; Parker, Jeffrey J [Rochester, MN

    2011-10-11

    Methods, apparatus, and products are disclosed for replenishing data descriptors in a Direct Memory Access (`DMA`) injection first-in-first-out (`FIFO`) buffer that include: determining, by a messaging module on an origin compute node, whether a number of data descriptors in a DMA injection FIFO buffer exceeds a predetermined threshold, each data descriptor specifying an application message for transmission to a target compute node; queuing, by the messaging module, a plurality of new data descriptors in a pending descriptor queue if the number of the data descriptors in the DMA injection FIFO buffer exceeds the predetermined threshold; establishing, by the messaging module, interrupt criteria that specify when to replenish the injection FIFO buffer with the plurality of new data descriptors in the pending descriptor queue; and injecting, by the messaging module, the plurality of new data descriptors into the injection FIFO buffer in dependence upon the interrupt criteria.

  15. 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.

  16. 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 ...

  17. Evaluating color descriptors for object and scene recognition.

    Science.gov (United States)

    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.

  18. 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...

  19. 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.

  20. 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.

  1. Estimation of the volume of distribution of some pharmacologically important compounds from their structural descriptor

    Directory of Open Access Journals (Sweden)

    MOHAMMAD H. FATEMI

    2011-07-01

    Full Text Available Quantitative structure–activity relationship (QSAR approaches were used to estimate the volume of distribution (Vd using an artificial neural network (ANN. The data set consisted of the volume of distribution of 129 pharmacologically important compounds, i.e., benzodiazepines, barbiturates, nonsteroidal anti-inflammatory drugs (NSAIDs, tricyclic anti-depressants and some antibiotics, such as betalactams, tetracyclines and quinolones. The descriptors, which were selected by stepwise variable selection methods, were: the Moriguchi octanol–water partition coefficient; the 3D-MoRSE-signal 30, weighted by atomic van der Waals volumes; the fragment-based polar surface area; the d COMMA2 value, weighted by atomic masses; the Geary autocorrelation, weighted by the atomic Sanderson electronegativities; the 3D-MoRSE – signal 02, weighted by atomic masses, and the Geary autocorrelation – lag 5, weighted by the atomic van der Waals volumes. These descriptors were used as inputs for developing multiple linear regressions (MLR and artificial neural network models as linear and non-linear feature mapping techniques, respectively. The standard errors in the estimation of Vd by the MLR model were: 0.104, 0.103 and 0.076 and for the ANN model: 0.029, 0.087 and 0.082 for the training, internal and external validation test, respectively. The robustness of these models were also evaluated by the leave-5-out cross validation procedure, that gives the statistics Q2 = 0.72 for the MLR model and Q2 = 0.82 for the ANN model. Moreover, the results of the Y-randomization test revealed that there were no chance correlations among the data matrix. In conclusion, the results of this study indicate the applicability of the estimation of the Vd value of drugs from their structural molecular descriptors. Furthermore, the statistics of the developed models indicate the superiority of the ANN over the MLR model.

  2. 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.

  3. Shape model of the maxillary dental arch using Fourier descriptors with an application in the rehabilitation for edentulous patient.

    Science.gov (United States)

    Rijal, Omar M; Abdullah, Norli A; Isa, Zakiah M; Noor, Norliza M; Tawfiq, Omar F

    2013-01-01

    The knowledge of teeth positions on the maxillary arch is useful in the rehabilitation of the edentulous patient. A combination of angular (θ), and linear (l) variables representing position of four teeth were initially proposed as the shape descriptor of the maxillary dental arch. Three categories of shape were established, each having a multivariate normal distribution. It may be argued that 4 selected teeth on the standardized digital images of the dental casts could be considered as insufficient with respect to representing shape. However, increasing the number of points would create problems with dimensions and proof of existence of the multivariate normal distribution is extremely difficult. This study investigates the ability of Fourier descriptors (FD) using all maxillary teeth to find alternative shape models. Eight FD terms were sufficient to represent 21 points on the arch. Using these 8 FD terms as an alternative shape descriptor, three categories of shape were verified, each category having the complex normal distribution.

  4. 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.

  5. Evaluating Learner Autonomy: A Dynamic Model with Descriptors

    Directory of Open Access Journals (Sweden)

    Maria Giovanna Tassinari

    2012-03-01

    Full Text Available Every autonomous learning process should entail an evaluation of the learner’s competencies for autonomy. The dynamic model of learner autonomy described in this paper is a tool designed in order to support the self-assessment and evaluation of learning competencies and to help both learners and advisors to focus on relevant aspects of the learning process. The dynamic model accounts for cognitive, metacognitive, action-oriented and affective components of learner autonomy and provides descriptors of learners’ attitudes, competencies and behaviors. It is dynamic in order to allow learners to focus on their own needs and goals.The model (http://www.sprachenzentrum.fuberlin.de/v/autonomiemodell/index.html has been validated in several workshops with experts at the Université Nancy 2, France and at the Freie Universität Berlin, Germany and tested by students, advisors and teachers. It is currently used at the Centre for Independent Language Learning at the Freie Universität Berlin for language advising. Learners can freely choose the components they would like to assess themselves in. Their assessment is then discussed in an advising session, where the learner and the advisor can compare their perspectives, focus on single aspects of the leaning process and set goals for further learning. The students’ feedback gathered in my PhD investigation shows that they are able to benefit from this evaluation; their awareness, self-reflection and decision-making in the autonomous learning process improved.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. Quantitative structure-activity relationship study of antioxidative peptide by using different sets of amino acids descriptors

    Science.gov (United States)

    Li, Yao-Wang; Li, Bo; He, Jiguo; Qian, Ping

    2011-07-01

    A database consisting of 214 tripeptides which contain either His or Tyr residue was applied to study quantitative structure-activity relationships (QSAR) of antioxidative tripeptides. Partial Least-Squares Regression analysis (PLSR) was conducted using parameters individually of each amino acid descriptor, including Divided Physico-chemical Property Scores (DPPS), Hydrophobic, Electronic, Steric, and Hydrogen (HESH), Vectors of Hydrophobic, Steric, and Electronic properties (VHSE), Molecular Surface-Weighted Holistic Invariant Molecular (MS-WHIM), isotropic surface area-electronic charge index (ISA-ECI) and Z-scale, to describe antioxidative tripeptides as X-variables and antioxidant activities measured with ferric thiocyanate methods were as Y-variable. After elimination of outliers by Hotelling's T 2 method and residual analysis, six significant models were obtained describing the entire data set. According to cumulative squared multiple correlation coefficients ( R2), cumulative cross-validation coefficients ( Q2) and relative standard deviation for calibration set (RSD c), the qualities of models using DPPS, HESH, ISA-ECI, and VHSE descriptors are better ( R2 > 0.6, Q2 > 0.5, RSD c 0.44). Furthermore, the predictive ability of models using DPPS descriptor is best among the six descriptors systems (cumulative multiple correlation coefficient for predict set ( Rext2) > 0.7). It was concluded that the DPPS is better to describe the amino acid of antioxidative tripeptides. The results of DPPS descriptor reveal that the importance of the center amino acid and the N-terminal amino acid are far more than the importance of the C-terminal amino acid for antioxidative tripeptides. The hydrophobic (positively to activity) and electronic (negatively to activity) properties of the N-terminal amino acid are suggested to play the most important significance to activity, followed by the hydrogen bond (positively to activity) of the center amino acid. The N-terminal amino acid

  11. DEVELOPING CEFR ILLUSTRATIVE DESCRIPTORS OF ASPECTS OF MEDIATION

    Directory of Open Access Journals (Sweden)

    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.

  12. 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.

  13. Consistent model driven architecture

    Science.gov (United States)

    Niepostyn, Stanisław J.

    2015-09-01

    The goal of the MDA is to produce software systems from abstract models in a way where human interaction is restricted to a minimum. These abstract models are based on the UML language. However, the semantics of UML models is defined in a natural language. Subsequently the verification of consistency of these diagrams is needed in order to identify errors in requirements at the early stage of the development process. The verification of consistency is difficult due to a semi-formal nature of UML diagrams. We propose automatic verification of consistency of the series of UML diagrams originating from abstract models implemented with our consistency rules. This Consistent Model Driven Architecture approach enables us to generate automatically complete workflow applications from consistent and complete models developed from abstract models (e.g. Business Context Diagram). Therefore, our method can be used to check practicability (feasibility) of software architecture models.

  14. 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

  15. Delay-Dependent Finite-Time H∞ Controller Design for a Kind of Nonlinear Descriptor Systems via a T-S Fuzzy Model

    Directory of Open Access Journals (Sweden)

    Baoyan Zhu

    2015-01-01

    Full Text Available Delay-dependent finite-time H∞ controller design problems are investigated for a kind of nonlinear descriptor system via a T-S fuzzy model in this paper. The solvable conditions of finite-time H∞ controller are given to guarantee that the loop-closed system is impulse-free and finite-time bounded and holds the H∞ performance to a prescribed disturbance attenuation level γ. The method given is the ability to eliminate the impulsive behavior caused by descriptor systems in a finite-time interval, which confirms the existence and uniqueness of solutions in the interval. By constructing a nonsingular matrix, we overcome the difficulty that results in an infeasible linear matrix inequality (LMI. Using the FEASP solver and GEVP solver of the LMI toolbox, we perform simulations to validate the proposed methods for a nonlinear descriptor system via the T-S fuzzy model, which shows the application of the T-S fuzzy method in studying the finite-time control problem of a nonlinear system. Meanwhile the method was also applied to the biological economy system to eliminate impulsive behavior at the bifurcation value, stabilize the loop-closed system in a finite-time interval, and achieve a H∞ performance level.

  16. 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

  17. Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

    Directory of Open Access Journals (Sweden)

    Yuan Xu

    2015-01-01

    Full Text Available Very high resolution (VHR image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened, while they ignore the change pattern description (i.e., how the changes changed, which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique.

  18. 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.

  19. 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.

  20. QSPR modeling of octanol/water partition coefficient for vitamins by optimal descriptors calculated with SMILES.

    Science.gov (United States)

    Toropov, A A; Toropova, A P; Raska, I

    2008-04-01

    Simplified molecular input line entry system (SMILES) has been utilized in constructing quantitative structure-property relationships (QSPR) for octanol/water partition coefficient of vitamins and organic compounds of different classes by optimal descriptors. Statistical characteristics of the best model (vitamins) are the following: n=17, R(2)=0.9841, s=0.634, F=931 (training set); n=7, R(2)=0.9928, s=0.773, F=690 (test set). Using this approach for modeling octanol/water partition coefficient for a set of organic compounds gives a model that is statistically characterized by n=69, R(2)=0.9872, s=0.156, F=5184 (training set) and n=70, R(2)=0.9841, s=0.179, F=4195 (test set).

  1. 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.

  2. 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.

  3. 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...

  4. Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors.

    Science.gov (United States)

    Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

    2010-06-01

    The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood-brain partitioning, expressed in terms of logBB values. The models are based on computationally derived physicochemical descriptors, namely the octanol/water partition coefficient (logP), the topological polar surface area (TPSA) and the total number of acidic and basic atoms, and were obtained using a homogeneous training set of 307 compounds, for all of which the published experimental logBB data had been determined in vivo. In particular, since molecules with logBB>0.3 cross the blood-brain barrier (BBB) readily while molecules with logBB<-1 are poorly distributed to the brain, on the basis of these thresholds we derived two distinct models, both of which show a percentage of good classification of about 80%. Notably, the predictive power of our models was confirmed by the analysis of a large external dataset of compounds with reported activity on the central nervous system (CNS) or lack thereof. The calculation of straightforward physicochemical descriptors is the only requirement for the prediction of the logBB of novel compounds through our models, which can be conveniently applied in conjunction with drug design and virtual screenings. Published by Elsevier Inc.

  5. 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.)

  6. Visual feature discrimination versus compression ratio for polygonal shape descriptors

    Science.gov (United States)

    Heuer, Joerg; Sanahuja, Francesc; Kaup, Andre

    2000-10-01

    In the last decade several methods for low level indexing of visual features appeared. Most often these were evaluated with respect to their discrimination power using measures like precision and recall. Accordingly, the targeted application was indexing of visual data within databases. During the standardization process of MPEG-7 the view on indexing of visual data changed, taking also communication aspects into account where coding efficiency is important. Even if the descriptors used for indexing are small compared to the size of images, it is recognized that there can be several descriptors linked to an image, characterizing different features and regions. Beside the importance of a small memory footprint for the transmission of the descriptor and the memory footprint in a database, eventually the search and filtering can be sped up by reducing the dimensionality of the descriptor if the metric of the matching can be adjusted. Based on a polygon shape descriptor presented for MPEG-7 this paper compares the discrimination power versus memory consumption of the descriptor. Different methods based on quantization are presented and their effect on the retrieval performance are measured. Finally an optimized computation of the descriptor is presented.

  7. 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.

  8. 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

  9. 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.

  10. 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 ...

  11. 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.

  12. 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

  13. 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.

  14. 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.

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

    Science.gov (United States)

    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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

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

    Science.gov (United States)

    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.

  4. Fast human pose estimation using 3D Zernike descriptors

    Science.gov (United States)

    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.

  5. 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.

  6. 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.)

  7. 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.

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. 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....

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

    Directory of Open Access Journals (Sweden)

    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.

  12. [The use of Cantonese pain descriptors among healthy young adults in Hong Kong].

    Science.gov (United States)

    Chung, W Y; Wong, C H; Yang, J C; Tan, P P

    1998-12-01

    The interpretation and expression of pain are closely related to an individual's social and cultural background. To convey messages on pain, language and words (pain descriptors) is particularly significant in assessment and evaluation of pain severity and its management. Therefore, the study of pain descriptors is crucial in clinical practice. It was of exploratory-descriptive design. Samples were recruited by convenience. Data were collected by structured self-administered questionnaire. Data obtained included demographic information and pain descriptors used by the subjects in various pain conditions. Data were analyzed by descriptive statistics. Pain descriptors were categorized according to nature, process, intensity, aggravating factors, accompanying symptoms and behavioral manifestation. Total number of pain descriptors (in Cantonese) based on real pain experience was 3017, mean was 3 (n = 986). The commonest used descriptors was the nature of pain (41%). The intensity of pain constituted 20%. There was no significant difference in the number of pain descriptors between male and female. However, there was a significant difference between the type of pain descriptors used (Mfemale = 526, Mmale = 453, Z = -2.9729, p = 0.0029). There were also significant differences in the use of pain descriptors among the various age groups (X2 = 15.0157, df = 4, P = 0.0047) and educational levels (X2 = 11.2443, df = 4, P = 0.0240). The types of descriptors used increased with an increase in age and education levels. This exploratory-descriptive study explores the use of pain descriptors among Chinese young adults in Hong Kong. The result shows that female use more pain descriptors than male. The pain descriptors that female used are mostly of nature type. The similarities and differences in findings with those of the Ho's (1991) are compared.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  15. 3D molecular descriptors important for clinical success.

    Science.gov (United States)

    Kombo, David C; Tallapragada, Kartik; Jain, Rachit; Chewning, Joseph; Mazurov, Anatoly A; Speake, Jason D; Hauser, Terry A; Toler, Steve

    2013-02-25

    The pharmacokinetic and safety profiles of clinical drug candidates are greatly influenced by their requisite physicochemical properties. In particular, it has been shown that 2D molecular descriptors such as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers correlate with clinical success. Using the proteomic off-target hit rate of nicotinic ligands, we found that shape-based 3D descriptors such as the radius of gyration and shadow indices discriminate off-target promiscuity better than do Fsp3 and the number of stereo centers. We have deduced the relevant descriptor values required for a ligand to be nonpromiscuous. Investigating the MDL Drug Data Report (MDDR) database as compounds move from the preclinical stage toward the market, we have found that these shape-based 3D descriptors predict clinical success of compounds at preclinical and phase1 stages vs compounds withdrawn from the market better than do Fsp3 and LogD. Further, these computed 3D molecular descriptors correlate well with experimentally observed solubility, which is among well-known physicochemical properties that drive clinical success. We also found that about 84% of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas withdrawn and discontinued compounds fail to meet the same criteria. Our studies suggest that spherical compounds (rather than their elongated counterparts) with a minimal number of aromatic rings may exhibit a high propensity to advance from clinical trials to market.

  16. Prioritization of in silico models and molecular descriptors for the assessment of ready biodegradability

    International Nuclear Information System (INIS)

    Fernández, Alberto; Rallo, Robert; Giralt, Francesc

    2015-01-01

    Ready biodegradability is a key property for evaluating the long-term effects of chemicals on the environment and human health. As such, it is used as a screening test for the assessment of persistent, bioaccumulative and toxic substances. Regulators encourage the use of non-testing methods, such as in silico models, to save money and time. A dataset of 757 chemicals was collected to assess the performance of four freely available in silico models that predict ready biodegradability. They were applied to develop a new consensus method that prioritizes the use of each individual model according to its performance on chemical subsets driven by the presence or absence of different molecular descriptors. This consensus method was capable of almost eliminating unpredictable chemicals, while the performance of combined models was substantially improved with respect to that of the individual models. - Highlights: • Consensus method to predict ready biodegradability by prioritizing multiple QSARs. • Consensus reduced the amount of unpredictable chemicals to less than 2%. • Performance increased with the number of QSAR models considered. • The absence of 2D atom pairs contributed significantly to the consensus model.

  17. Prioritization of in silico models and molecular descriptors for the assessment of ready biodegradability

    Energy Technology Data Exchange (ETDEWEB)

    Fernández, Alberto [Departament d’Enginyeria Quimica, Universitat Rovira i Virgili, Tarragona, Catalonia (Spain); Rallo, Robert [Departament d’Enginyeria Informatica i Matematiques, Universitat Rovira i Virgili, Tarragona, Catalonia (Spain); Giralt, Francesc [Departament d’Enginyeria Quimica, Universitat Rovira i Virgili, Tarragona, Catalonia (Spain)

    2015-10-15

    Ready biodegradability is a key property for evaluating the long-term effects of chemicals on the environment and human health. As such, it is used as a screening test for the assessment of persistent, bioaccumulative and toxic substances. Regulators encourage the use of non-testing methods, such as in silico models, to save money and time. A dataset of 757 chemicals was collected to assess the performance of four freely available in silico models that predict ready biodegradability. They were applied to develop a new consensus method that prioritizes the use of each individual model according to its performance on chemical subsets driven by the presence or absence of different molecular descriptors. This consensus method was capable of almost eliminating unpredictable chemicals, while the performance of combined models was substantially improved with respect to that of the individual models. - Highlights: • Consensus method to predict ready biodegradability by prioritizing multiple QSARs. • Consensus reduced the amount of unpredictable chemicals to less than 2%. • Performance increased with the number of QSAR models considered. • The absence of 2D atom pairs contributed significantly to the consensus model.

  18. 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.

  19. Local Descriptors of Dynamic and Nondynamic Correlation.

    Science.gov (United States)

    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.

  20. 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

  1. 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.

  2. On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors Towards Materials Quantitative Structure Property Relationships

    Science.gov (United States)

    Krein, Michael

    ZINC data set, a qHTS PubChem bioassay, as well as the protein binding sites from the PDB. The characteristics of these networks are compared and contrasted with those of the bioassay Structure Activity Landscape Index (SALI) subnetwork, which maps discontinuities or cliffs in the structure activity landscape. Mapping this newly generated information over underlying chemistry space networks generated using different descriptors demonstrates local modeling capacity and can guide the choice of better local representations of chemistry space. Chapter 2 introduces and demonstrates this novel concept, which also enables future work in visualization and interpretation of chemical spaces. Initially, it was discovered that there were no community-available tools to leverage best-practice ideas to comprehensively build, compare, and interpret QSPRs. The Yet Another Modeling System (YAMS) tool performs a series of balanced, rational decisions in dataset preprocessing and parameter/feature selection over a choice of modeling methods. To date, YAMS is the only community-available informatics tool that performs such decisions consistently between methods while also providing multiple model performance comparisons and detailed descriptor importance information. The focus of the tool is thus to convey rich information about model quality and predictions that help to "close the loop" between modeling and experimental efforts, for example, in tailoring nanocomposite properties. Polymer nanocomposites (PNC) are complex material systems encompassing many potential structures, chemistries, and self assembled morphologies that could significantly impact commercial and military applications. There is a strong desire to characterize and understand the tradespace of nanocomposites, to identify the important factors relating nanostructure to materials properties and determine an effective way to control materials properties at the manufacturing scale. Due to the complexity of the systems

  3. Molecular Descriptors Family on Structure Activity Relationships 3. Antituberculotic Activity of some Polyhydroxyxanthones

    Directory of Open Access Journals (Sweden)

    Sorana BOLBOACĂ

    2005-06-01

    Full Text Available The antituberculotic activity of some polyhydroxyxanthones was estimated using the Molecular Descriptors Family on Structure Activity Relationships methodology. From a total number of 298110 real and distinct calculated descriptors, 94843 were significantly different and entered into multiple linear regression analysis. The best performing bi-varied model was obtained by use of all polyhydroxyxanthones. The MDF SAR model was validated splitting the molecules into training and test sets. A correlated correlations analysis was applied in other to compare the MDF SAR models with the previous SAR model. The prediction ability of antituberculotic activity of polyhydroxyxanthones with MDF SAR methodology is sustained by three arguments: leave-one-out procedure, training vs. test procedure, and the correlated correlations analysis. Looking at the bi-varied MDF SAR model, we can conclude that the antituberculotic activity of polyhydroxyxanthones is almost of geometrical nature (99% and is strongly dependent on partial atomic charge and group electronegativity.

  4. Gun bore flaw image matching based on improved SIFT descriptor

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  6. 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.

  7. Probabilistic models for 2D active shape recognition using Fourier descriptors and mutual information

    CSIR Research Space (South Africa)

    Govender, N

    2014-08-01

    Full Text Available information to improve the initial shape recognition results. We propose an initial system which performs shape recognition using the euclidean distances of Fourier descriptors. To improve upon these results we build multinomial and Gaussian probabilistic...

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

    Science.gov (United States)

    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%).

  9. 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

  10. Color Independent Components Based SIFT Descriptors for Object/Scene Classification

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  12. Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

    Science.gov (United States)

    Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

    2014-01-27

    The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W

  13. 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.

  14. 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...

  15. Prediction of radical scavenging activities of anthocyanins applying adaptive neuro-fuzzy inference system (ANFIS) with quantum chemical descriptors.

    Science.gov (United States)

    Jhin, Changho; Hwang, Keum Taek

    2014-08-22

    Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively.

  16. Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS with Quantum Chemical Descriptors

    Directory of Open Access Journals (Sweden)

    Changho Jhin

    2014-08-01

    Full Text Available Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A and electronegativity (χ of flavylium cation, and ionization potential (I of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively.

  17. Comparison of combinatorial clustering methods on pharmacological data sets represented by machine learning-selected real molecular descriptors.

    Science.gov (United States)

    Rivera-Borroto, Oscar Miguel; Marrero-Ponce, Yovani; García-de la Vega, José Manuel; Grau-Ábalo, Ricardo del Corazón

    2011-12-27

    Cluster algorithms play an important role in diversity related tasks of modern chemoinformatics, with the widest applications being in pharmaceutical industry drug discovery programs. The performance of these grouping strategies depends on various factors such as molecular representation, mathematical method, algorithmical technique, and statistical distribution of data. For this reason, introduction and comparison of new methods are necessary in order to find the model that best fits the problem at hand. Earlier comparative studies report on Ward's algorithm using fingerprints for molecular description as generally superior in this field. However, problems still remain, i.e., other types of numerical descriptions have been little exploited, current descriptors selection strategy is trial and error-driven, and no previous comparative studies considering a broader domain of the combinatorial methods in grouping chemoinformatic data sets have been conducted. In this work, a comparison between combinatorial methods is performed,with five of them being novel in cheminformatics. The experiments are carried out using eight data sets that are well established and validated in the medical chemistry literature. Each drug data set was represented by real molecular descriptors selected by machine learning techniques, which are consistent with the neighborhood principle. Statistical analysis of the results demonstrates that pharmacological activities of the eight data sets can be modeled with a few of families with 2D and 3D molecular descriptors, avoiding classification problems associated with the presence of nonrelevant features. Three out of five of the proposed cluster algorithms show superior performance over most classical algorithms and are similar (or slightly superior in the most optimistic sense) to Ward's algorithm. The usefulness of these algorithms is also assessed in a comparative experiment to potent QSAR and machine learning classifiers, where they perform

  18. Complex Correlation Measure: a novel descriptor for Poincaré plot

    Directory of Open Access Journals (Sweden)

    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

  19. Fourier Descriptor Analysis and Unification of Voice Range Profile Contours: Method and Applications

    Science.gov (United States)

    Pabon, Peter; Ternstrom, Sten; Lamarche, Anick

    2011-01-01

    Purpose: To describe a method for unified description, statistical modeling, and comparison of voice range profile (VRP) contours, even from diverse sources. Method: A morphologic modeling technique, which is based on Fourier descriptors (FDs), is applied to the VRP contour. The technique, which essentially involves resampling of the curve of the…

  20. Novel topological descriptors for analyzing biological networks

    Directory of Open Access Journals (Sweden)

    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.

  1. Identification of Electronic and Structural Descriptors of Adenosine Analogues Related to Inhibition of Leishmanial Glyceraldehyde-3-Phosphate Dehydrogenase

    Directory of Open Access Journals (Sweden)

    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.

  2. QSPR study of absorption maxima of organic dyes for dye-sensitized solar cells based on 3D descriptors

    Science.gov (United States)

    Xu, Jie; Zhang, Hui; Wang, Lei; Liang, Guijie; Wang, Luoxin; Shen, Xiaolin; Xu, Weilin

    2010-07-01

    A quantitative structure-property relationship (QSPR) study was performed for the prediction of the absorption maxima ( λmax) of organic dyes for dye-sensitized solar cells (DSSCs). The entire set of 70 dyes was divided into a training set of 53 dyes and a test set of 17 dyes according to Kennard and Stones algorithm. Three-dimensional (3D) descriptors were calculated to represent the dye molecules. A ten-descriptor model, with a squared correlation coefficient ( R2) of 0.9543 and a standard error of estimation ( s) of 14.7 nm, was produced by using the stepwise multilinear regression analysis (MLRA) on the training set. The reliability of the proposed model was further illustrated using various evaluation techniques: leave-one-out cross-validation procedure, randomization tests, and validation through the external test set. All descriptors involved in the model were derived solely from the chemical structure of the dye molecules, which makes the model very useful to estimate the λmax of dyes before they are actually synthesized.

  3. 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.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. 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.

  7. 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

  8. New polynomial-based molecular descriptors with low degeneracy.

    Directory of Open Access Journals (Sweden)

    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.

  9. 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)

  10. 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.

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

    Science.gov (United States)

    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.

  12. Generic Traffic Descriptors in Managing Service Quality in BISDN/ATM Network

    Directory of Open Access Journals (Sweden)

    Ivan Bošnjak

    2002-03-01

    Full Text Available Traffic models for multiservice broadband networks differsignificantly regarding simple analytic models applicable intelephone traffic and circuit-switch network. The paper presentsa clear analysis of standardised traffic descriptors andquality parameters of the main services in BISDNIATM. Trafficdescriptors have been associated with the basic values andconcepts developed within generic traffic theory. Part systematisationof traffic parameters has been performed as basis for formalisedgeneralised description of parameters and effectivequality management of A TM services.

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

    Directory of Open Access Journals (Sweden)

    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.

  14. 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. .

  15. Detecting reactive islands using Lagrangian descriptors and the relevance to transition path sampling.

    Science.gov (United States)

    Patra, Sarbani; Keshavamurthy, Srihari

    2018-02-14

    It has been known for sometime now that isomerization reactions, classically, are mediated by phase space structures called reactive islands (RI). RIs provide one possible route to correct for the nonstatistical effects in the reaction dynamics. In this work, we map out the reactive islands for the two dimensional Müller-Brown model potential and show that the reactive islands are intimately linked to the issue of rare event sampling. In particular, we establish the sensitivity of the so called committor probabilities, useful quantities in the transition path sampling technique, to the hierarchical RI structures. Mapping out the RI structure for high dimensional systems, however, is a challenging task. Here, we show that the technique of Lagrangian descriptors is able to effectively identify the RI hierarchy in the model system. Based on our results, we suggest that the Lagrangian descriptors can be useful for detecting RIs in high dimensional systems.

  16. Self-consistent asset pricing models

    Science.gov (United States)

    Malevergne, Y.; Sornette, D.

    2007-08-01

    We discuss the foundations of factor or regression models in the light of the self-consistency condition that the market portfolio (and more generally the risk factors) is (are) constituted of the assets whose returns it is (they are) supposed to explain. As already reported in several articles, self-consistency implies correlations between the return disturbances. As a consequence, the alphas and betas of the factor model are unobservable. Self-consistency leads to renormalized betas with zero effective alphas, which are observable with standard OLS regressions. When the conditions derived from internal consistency are not met, the model is necessarily incomplete, which means that some sources of risk cannot be replicated (or hedged) by a portfolio of stocks traded on the market, even for infinite economies. Analytical derivations and numerical simulations show that, for arbitrary choices of the proxy which are different from the true market portfolio, a modified linear regression holds with a non-zero value αi at the origin between an asset i's return and the proxy's return. Self-consistency also introduces “orthogonality” and “normality” conditions linking the betas, alphas (as well as the residuals) and the weights of the proxy portfolio. Two diagnostics based on these orthogonality and normality conditions are implemented on a basket of 323 assets which have been components of the S&P500 in the period from January 1990 to February 2005. These two diagnostics show interesting departures from dynamical self-consistency starting about 2 years before the end of the Internet bubble. Assuming that the CAPM holds with the self-consistency condition, the OLS method automatically obeys the resulting orthogonality and normality conditions and therefore provides a simple way to self-consistently assess the parameters of the model by using proxy portfolios made only of the assets which are used in the CAPM regressions. Finally, the factor decomposition with the

  17. Automatic summarization of soccer highlights using audio-visual descriptors.

    Science.gov (United States)

    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.

  18. 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...

  19. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

    Science.gov (United States)

    Jhin, Changho; Hwang, Keum Taek

    2015-01-01

    One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

  20. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

    Directory of Open Access Journals (Sweden)

    Changho Jhin

    Full Text Available One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS applied quantitative structure-activity relationship models (QSAR were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

  1. 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

  2. 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.

  3. Prediction of retention in micellar electrokinetic chromatography based on molecular structural descriptors by using the heuristic method

    International Nuclear Information System (INIS)

    Liu Huanxiang; Yao Xiaojun; Liu Mancang; Hu Zhide; Fan Botao

    2006-01-01

    Based on calculated molecular descriptors from the solutes' structure alone, the micelle-water partition coefficients of 103 solutes in micellar electrokinetic chromatography (MEKC) were predicted using the heuristic method (HM). At the same time, in order to show the influence of different molecular descriptors on the micelle-water partition of solute and to well understand the retention mechanism in MEKC, HM was used to build several multivariable linear models using different numbers of molecular descriptors. The best 6-parameter model gave the following results: the square of correlation coefficient R 2 was 0.958 and the mean relative error was 3.98%, which proved that the predictive values were in good agreement with the experimental results. From the built model, it can be concluded that the hydrophobic, H-bond, polar interactions of solutes with the micellar and aqueous phases are the main factors that determine their partitioning behavior. In addition, this paper provided a simple, fast and effective method for predicting the retention of the solutes in MEKC from their structures and gave some insight into structural features related to the retention of the solutes

  4. 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...

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. Random Forest Approach to QSPR Study of Fluorescence Properties Combining Quantum Chemical Descriptors and Solvent Conditions.

    Science.gov (United States)

    Chen, Chia-Hsiu; Tanaka, Kenichi; Funatsu, Kimito

    2018-04-22

    The Quantitative Structure - Property Relationship (QSPR) approach was performed to study the fluorescence absorption wavelengths and emission wavelengths of 413 fluorescent dyes in different solvent conditions. The dyes included the chromophore derivatives of cyanine, xanthene, coumarin, pyrene, naphthalene, anthracene and etc., with the wavelength ranging from 250 nm to 800 nm. An ensemble method, random forest (RF), was employed to construct nonlinear prediction models compared with the results of linear partial least squares and nonlinear support vector machine regression models. Quantum chemical descriptors derived from density functional theory method and solvent information were also used by constructing models. The best prediction results were obtained from RF model, with the squared correlation coefficients [Formula: see text] of 0.940 and 0.905 for λ abs and λ em , respectively. The descriptors used in the models were discussed in detail in this report by comparing the feature importance of RF.

  8. Breast density pattern characterization by histogram features and texture descriptors

    Directory of Open Access Journals (Sweden)

    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.

  9. 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

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

    Science.gov (United States)

    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.

  11. 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.

  12. 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.

  13. An Analysis of Descriptors of Volatile Organic Compounds and Their Impact on Rate Constant for Reaction with Hydroxyl Radicals

    Science.gov (United States)

    2018-05-01

    5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Excet, Inc.; 2108 Emmorton Park Road , Suite 201...SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) Defense Threat Reduction Agency, 8725 John J. Kingman Road , MSC 6201, Fort Belvoir, VA 22060...bond descriptors may be useful for the construction of predictive modeling. 15. SUBJECT TERMS Volatile organic compound (VOC) Chemical descriptors

  14. Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

    Science.gov (United States)

    Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

    2008-06-01

    A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

  15. 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...

  16. BioGPS descriptors for rational engineering of enzyme promiscuity and structure based bioinformatic analysis.

    Directory of Open Access Journals (Sweden)

    Valerio Ferrario

    Full Text Available A new bioinformatic methodology was developed founded on the Unsupervised Pattern Cognition Analysis of GRID-based BioGPS descriptors (Global Positioning System in Biological Space. The procedure relies entirely on three-dimensional structure analysis of enzymes and does not stem from sequence or structure alignment. The BioGPS descriptors account for chemical, geometrical and physical-chemical features of enzymes and are able to describe comprehensively the active site of enzymes in terms of "pre-organized environment" able to stabilize the transition state of a given reaction. The efficiency of this new bioinformatic strategy was demonstrated by the consistent clustering of four different Ser hydrolases classes, which are characterized by the same active site organization but able to catalyze different reactions. The method was validated by considering, as a case study, the engineering of amidase activity into the scaffold of a lipase. The BioGPS tool predicted correctly the properties of lipase variants, as demonstrated by the projection of mutants inside the BioGPS "roadmap".

  17. 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.

  18. 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.

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

    Science.gov (United States)

    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.

  20. High-performance speech recognition using consistency modeling

    Science.gov (United States)

    Digalakis, Vassilios; Murveit, Hy; Monaco, Peter; Neumeyer, Leo; Sankar, Ananth

    1994-12-01

    The goal of SRI's consistency modeling project is to improve the raw acoustic modeling component of SRI's DECIPHER speech recognition system and develop consistency modeling technology. Consistency modeling aims to reduce the number of improper independence assumptions used in traditional speech recognition algorithms so that the resulting speech recognition hypotheses are more self-consistent and, therefore, more accurate. At the initial stages of this effort, SRI focused on developing the appropriate base technologies for consistency modeling. We first developed the Progressive Search technology that allowed us to perform large-vocabulary continuous speech recognition (LVCSR) experiments. Since its conception and development at SRI, this technique has been adopted by most laboratories, including other ARPA contracting sites, doing research on LVSR. Another goal of the consistency modeling project is to attack difficult modeling problems, when there is a mismatch between the training and testing phases. Such mismatches may include outlier speakers, different microphones and additive noise. We were able to either develop new, or transfer and evaluate existing, technologies that adapted our baseline genonic HMM recognizer to such difficult conditions.

  1. Modeling and Testing Legacy Data Consistency Requirements

    DEFF Research Database (Denmark)

    Nytun, J. P.; Jensen, Christian Søndergaard

    2003-01-01

    An increasing number of data sources are available on the Internet, many of which offer semantically overlapping data, but based on different schemas, or models. While it is often of interest to integrate such data sources, the lack of consistency among them makes this integration difficult....... This paper addresses the need for new techniques that enable the modeling and consistency checking for legacy data sources. Specifically, the paper contributes to the development of a framework that enables consistency testing of data coming from different types of data sources. The vehicle is UML and its...... accompanying XMI. The paper presents techniques for modeling consistency requirements using OCL and other UML modeling elements: it studies how models that describe the required consistencies among instances of legacy models can be designed in standard UML tools that support XMI. The paper also considers...

  2. 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

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

    Directory of Open Access Journals (Sweden)

    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

  4. 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.)

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

    Science.gov (United States)

    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.

  6. 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.

  7. Region descriptors for automatic classification of small sea targets in infrared video

    NARCIS (Netherlands)

    Mouthaan, M.M.; Broek, S.P. van den; Hendriks, E.A.; Schwering, P.B.W.

    2011-01-01

    We evaluate the performance of different key-point detectors and region descriptors when used for automatic classification of small sea targets in infrared video. In our earlier research performed on this subject as well as in other literature, many different region descriptors have been proposed.

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

    Science.gov (United States)

    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.

  9. 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.

  10. 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.

  11. 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...

  12. 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...

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

    Science.gov (United States)

    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.

  14. 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

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

    Science.gov (United States)

    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.

  16. Calculation of Quantitative Structure-Activity Relationship Descriptors of Artemisinin Derivatives

    Directory of Open Access Journals (Sweden)

    Jambalsuren Bayarmaa

    2008-06-01

    Full Text Available Quantitative structure-activity relationships are based on the construction of predictive models using a set of known molecules and associated activity value. This accurate methodology, developed with adequate mathematical and computational tools, leads to a faster, cheaper and more comprehensive design of new products, reducing the experimental synthesis and testing on animals. Preparation of the QSAR models of artemisinin derivatives was carried out by the genetic function algorithm (GFA method for 91 molecules. The results show some relationships to the observed antimalarial activities of the artemisinin derivatives. The most statistically signi fi cant regression equation obtained from the fi nal GFA relates to two molecular descriptors.

  17. Análisis de Detectores y Descriptores de Características Visuales en SLAM en Entornos Interiores y Exteriores

    Directory of Open Access Journals (Sweden)

    M. Ballesta

    2010-04-01

    Full Text Available Resumen: El objetivo de este artículo es encontrar un extractor de características visuales que pueda ser utilizado en un proceso de SLAM (Simultaneous Localization and Mapping. Este extractor de características consiste en la combinación de un detector que extrae puntos significativos del entorno, y un descriptor local que caracteriza dichos puntos. Este artículo presenta la comparación de un conjunto de detectores de puntos de interés y de descriptores locales que se utilizan como marcas visuales en un proceso de SLAM. El análisis comparativo se divide en dos fases diferenciadas: detección y descripción. Se evalúa la repetibilidad de los detectores, así como la invariabilidad de los descriptores ante cambios de vista, escala e iluminación. Los experimentos se han realizado a partir de un conjunto de secuencias de imágenes tanto interiores (entorno de oficinas como exteriores, con diversas variaciones en la imagen (iluminación y posición, representando así de una forma bastante general los entornos típicos de un robot. Se considera que los resultados de este trabajo pueden ser útiles a la hora de seleccionar una marca adecuada en SLAM visual, tanto para entornos interiores como exteriores. Palabras clave: SLAM visual, marcas visuales, detectores de puntos de interés, descriptores locales

  18. 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.

  19. 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.

  20. 3D Shape Modeling Using High Level Descriptors

    DEFF Research Database (Denmark)

    Andersen, Vedrana

    features like thorns, bark and scales. Presented here is a simple method for easy modeling, transferring and editing that kind of texture. The method is an extension of the height-field texture, but incorporates an additional tilt of the height field. Related to modeling non-heightfield textures, a part...... of my work involved developing feature-aware resizing of models with complex surfaces consisting of underlying shape and a distinctive texture detail. The aim was to deform an object while preserving the shape and size of the features.......The goal of this Ph.D. project is to investigate and improve the methods for describing the surface of 3D objects, with focus on modeling geometric texture on surfaces. Surface modeling being a large field of research, the work done during this project concentrated around a few smaller areas...

  1. Locator-Checker-Scaler Object Tracking Using Spatially Ordered and Weighted Patch Descriptor.

    Science.gov (United States)

    Kim, Han-Ul; Kim, Chang-Su

    2017-08-01

    In this paper, we propose a simple yet effective object descriptor and a novel tracking algorithm to track a target object accurately. For the object description, we divide the bounding box of a target object into multiple patches and describe them with color and gradient histograms. Then, we determine the foreground weight of each patch to alleviate the impacts of background information in the bounding box. To this end, we perform random walk with restart (RWR) simulation. We then concatenate the weighted patch descriptors to yield the spatially ordered and weighted patch (SOWP) descriptor. For the object tracking, we incorporate the proposed SOWP descriptor into a novel tracking algorithm, which has three components: locator, checker, and scaler (LCS). The locator and the scaler estimate the center location and the size of a target, respectively. The checker determines whether it is safe to adjust the target scale in a current frame. These three components cooperate with one another to achieve robust tracking. Experimental results demonstrate that the proposed LCS tracker achieves excellent performance on recent benchmarks.

  2. Screening for High Conductivity/Low Viscosity Ionic Liquids Using Product Descriptors.

    Science.gov (United States)

    Martin, Shawn; Pratt, Harry D; Anderson, Travis M

    2017-07-01

    We seek to optimize Ionic liquids (ILs) for application to redox flow batteries. As part of this effort, we have developed a computational method for suggesting ILs with high conductivity and low viscosity. Since ILs consist of cation-anion pairs, we consider a method for treating ILs as pairs using product descriptors for QSPRs, a concept borrowed from the prediction of protein-protein interactions in bioinformatics. We demonstrate the method by predicting electrical conductivity, viscosity, and melting point on a dataset taken from the ILThermo database on June 18 th , 2014. The dataset consists of 4,329 measurements taken from 165 ILs made up of 72 cations and 34 anions. We benchmark our QSPRs on the known values in the dataset then extend our predictions to screen all 2,448 possible cation-anion pairs in the dataset. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Predicting highly-connected hubs in protein interaction networks by QSAR and biological data descriptors

    Science.gov (United States)

    Hsing, Michael; Byler, Kendall; Cherkasov, Artem

    2009-01-01

    Hub proteins (those engaged in most physical interactions in a protein interaction network (PIN) have recently gained much research interest due to their essential role in mediating cellular processes and their potential therapeutic value. It is straightforward to identify hubs if the underlying PIN is experimentally determined; however, theoretical hub prediction remains a very challenging task, as physicochemical properties that differentiate hubs from less connected proteins remain mostly uncharacterized. To adequately distinguish hubs from non-hub proteins we have utilized over 1300 protein descriptors, some of which represent QSAR (quantitative structure-activity relationship) parameters, and some reflect sequence-derived characteristics of proteins including domain composition and functional annotations. Those protein descriptors, together with available protein interaction data have been processed by a machine learning method (boosting trees) and resulted in the development of hub classifiers that are capable of predicting highly interacting proteins for four model organisms: Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens. More importantly, through the analyses of the most relevant protein descriptors, we are able to demonstrate that hub proteins not only share certain common physicochemical and structural characteristics that make them different from non-hub counterparts, but they also exhibit species-specific characteristics that should be taken into account when analyzing different PINs. The developed prediction models can be used for determining highly interacting proteins in the four studied species to assist future proteomics experiments and PIN analyses. Availability The source code and executable program of the hub classifier are available for download at: http://www.cnbi2.ca/hub-analysis/ PMID:20198194

  4. 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...

  5. 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...

  6. Proposal for standardised ultrasound descriptors of abnormally invasive placenta (AIP)

    DEFF Research Database (Denmark)

    Collins, Sally L; Ashcroft, Anna; Braun, Thorsten

    2016-01-01

    on subjective interpretation of imaging signs. There is no accepted consensus on the definition of the commonly used ultrasound markers for AIP. The studies included in a recently published systematic review of antenatal sonographic diagnosis of AIP were analysed for the ultrasound descriptors. Different...... were examined for wording used to describe AIP signs. These were extracted and grouped by ultrasound modality, and synonymous or identical terms identified. The group agreed on six unified descriptors for 2D greyscale signs, four for 2D colour Doppler and one for 3D power Doppler. Four papers included...

  7. Alignment-independent comparison of binding sites based on DrugScore potential fields encoded by 3D Zernike descriptors.

    Science.gov (United States)

    Nisius, Britta; Gohlke, Holger

    2012-09-24

    Analyzing protein binding sites provides detailed insights into the biological processes proteins are involved in, e.g., into drug-target interactions, and so is of crucial importance in drug discovery. Herein, we present novel alignment-independent binding site descriptors based on DrugScore potential fields. The potential fields are transformed to a set of information-rich descriptors using a series expansion in 3D Zernike polynomials. The resulting Zernike descriptors show a promising performance in detecting similarities among proteins with low pairwise sequence identities that bind identical ligands, as well as within subfamilies of one target class. Furthermore, the Zernike descriptors are robust against structural variations among protein binding sites. Finally, the Zernike descriptors show a high data compression power, and computing similarities between binding sites based on these descriptors is highly efficient. Consequently, the Zernike descriptors are a useful tool for computational binding site analysis, e.g., to predict the function of novel proteins, off-targets for drug candidates, or novel targets for known drugs.

  8. 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

  9. Consistency of the MLE under mixture models

    OpenAIRE

    Chen, Jiahua

    2016-01-01

    The large-sample properties of likelihood-based statistical inference under mixture models have received much attention from statisticians. Although the consistency of the nonparametric MLE is regarded as a standard conclusion, many researchers ignore the precise conditions required on the mixture model. An incorrect claim of consistency can lead to false conclusions even if the mixture model under investigation seems well behaved. Under a finite normal mixture model, for instance, the consis...

  10. 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.

  11. Externally predictive single-descriptor based QSPRs for physico-chemical properties of polychlorinated-naphthalenes: Exploring relationships of log SW, log KOA, and log KOW with electron-correlation

    International Nuclear Information System (INIS)

    Chayawan; Vikas

    2015-01-01

    Highlights: • Aqueous solubility and partition coefficient are modelled using single-parameter. • Electron-correlation observed as a vital predictorof physico-chemical properties. • For octanol-air partition coefficient, energy and polarizability yield best models. • Dipole-moment is found to be worst single-descriptor for the properties analysed. - Abstract: Quantitative structure–property relationships (QSPRs), based only on a single-parameter, are proposed for the prediction of physico-chemical properties, namely, aqueous solubility (log S W ), octanol–water partition coefficient (log K OW ) and octanol–air partition coefficient (log K OA ) of polychloronaphthalenes (PCNs) including all the 75 chloronaphthalene congeners. The QSPR models are developed using molecular descriptors computed through quantum mechanical methods including ab-initio as well as advanced semi-empirical methods. The predictivity of the developed models is tested through state-of-the-art external validation procedures employing an external prediction set of compounds. To analyse the role of instantaneous interactions between electrons (the electron-correlation), the models are also compared with those developed using only the electron-correlation contribution of the quantum chemical descriptor. The electron-correlation contribution towards the chemical hardness and the LUMO energy are observed to be the best predictors for octanol–water partition coefficient, whereas for the octanol–air partition coefficient, the total electronic energy and electron-correlation energy are found to be reliable descriptors, in fact, even better than the polarisability. For aqueous solubility of PCNs, the absolute electronegativity is observed to be the best predictor. This work suggests that the electron-correlation contribution of a quantum-chemical descriptor can be used as a reliable indicator for physico-chemical properties, particularly the partition coefficients

  12. Rate constants of hydroxyl radical oxidation of polychlorinated biphenyls in the gas phase: A single−descriptor based QSAR and DFT study

    International Nuclear Information System (INIS)

    Yang, Zhihui; Luo, Shuang; Wei, Zongsu; Ye, Tiantian; Spinney, Richard; Chen, Dong; Xiao, Ruiyang

    2016-01-01

    The second‒order rate constants (k) of hydroxyl radical (·OH) with polychlorinated biphenyls (PCBs) in the gas phase are of scientific and regulatory importance for assessing their global distribution and fate in the atmosphere. Due to the limited number of measured k values, there is a need to model the k values for unknown PCBs congeners. In the present study, we developed a quantitative structure–activity relationship (QSAR) model with quantum chemical descriptors using a sequential approach, including correlation analysis, principal component analysis, multi−linear regression, validation, and estimation of applicability domain. The result indicates that the single descriptor, polarizability (α), plays an important role in determining the reactivity with a global standardized function of lnk = −0.054 × α ‒ 19.49 at 298 K. In order to validate the QSAR predicted k values and expand the current k value database for PCBs congeners, an independent method, density functional theory (DFT), was employed to calculate the kinetics and thermodynamics of the gas‒phase ·OH oxidation of 2,4′,5-trichlorobiphenyl (PCB31), 2,2′,4,4′-tetrachlorobiphenyl (PCB47), 2,3,4,5,6-pentachlorobiphenyl (PCB116), 3,3′,4,4′,5,5′-hexachlorobiphenyl (PCB169), and 2,3,3′,4,5,5′,6-heptachlorobiphenyl (PCB192) at 298 K at B3LYP/6–311++G**//B3LYP/6–31 + G** level of theory. The QSAR predicted and DFT calculated k values for ·OH oxidation of these PCB congeners exhibit excellent agreement with the experimental k values, indicating the robustness and predictive power of the single–descriptor based QSAR model we developed. - Highlights: • We developed a single−descriptor based QSAR model for ·OH oxidation of PCBs. • We independently validated the QSAR predicted k values of five PCB congeners with the DFT method. • The QSAR predicted and DFT calculated k for the five PCB congeners exhibit excellent agreement. - We developed a single−descriptor

  13. 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.

  14. 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).

  15. Position Estimation and Local Mapping Using Omnidirectional Images and Global Appearance Descriptors

    Directory of Open Access Journals (Sweden)

    Yerai Berenguer

    2015-10-01

    Full Text Available This work presents some methods to create local maps and to estimate the position of a mobile robot, using the global appearance of omnidirectional images. We use a robot that carries an omnidirectional vision system on it. Every omnidirectional image acquired by the robot is described only with one global appearance descriptor, based on the Radon transform. In the work presented in this paper, two different possibilities have been considered. In the first one, we assume the existence of a map previously built composed of omnidirectional images that have been captured from previously-known positions. The purpose in this case consists of estimating the nearest position of the map to the current position of the robot, making use of the visual information acquired by the robot from its current (unknown position. In the second one, we assume that we have a model of the environment composed of omnidirectional images, but with no information about the location of where the images were acquired. The purpose in this case consists of building a local map and estimating the position of the robot within this map. Both methods are tested with different databases (including virtual and real images taking into consideration the changes of the position of different objects in the environment, different lighting conditions and occlusions. The results show the effectiveness and the robustness of both methods.

  16. Modeling a Consistent Behavior of PLC-Sensors

    Directory of Open Access Journals (Sweden)

    E. V. Kuzmin

    2014-01-01

    Full Text Available The article extends the cycle of papers dedicated to programming and verificatoin of PLC-programs by LTL-specification. This approach provides the availability of correctness analysis of PLC-programs by the model checking method.The model checking method needs to construct a finite model of a PLC program. For successful verification of required properties it is important to take into consideration that not all combinations of input signals from the sensors can occur while PLC works with a control object. This fact requires more advertence to the construction of the PLC-program model.In this paper we propose to describe a consistent behavior of sensors by three groups of LTL-formulas. They will affect the program model, approximating it to the actual behavior of the PLC program. The idea of LTL-requirements is shown by an example.A PLC program is a description of reactions on input signals from sensors, switches and buttons. In constructing a PLC-program model, the approach to modeling a consistent behavior of PLC sensors allows to focus on modeling precisely these reactions without an extension of the program model by additional structures for realization of a realistic behavior of sensors. The consistent behavior of sensors is taken into account only at the stage of checking a conformity of the programming model to required properties, i. e. a property satisfaction proof for the constructed model occurs with the condition that the model contains only such executions of the program that comply with the consistent behavior of sensors.

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

    Science.gov (United States)

    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

  18. Scene text recognition in mobile applications by character descriptor and structure configuration.

    Science.gov (United States)

    Yi, Chucai; Tian, Yingli

    2014-07-01

    Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

  19. Collision cross section prediction of deprotonated phenolics in a travelling-wave ion mobility spectrometer using molecular descriptors and chemometrics

    Energy Technology Data Exchange (ETDEWEB)

    Gonzales, Gerard Bryan, E-mail: gerard.gonzales@ugent.be [Food Chemistry and Human Nutrition (NutriFOODChem), Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University (Belgium); Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University (Belgium); Department of Applied Biological Science, Faculty of Bioscience Engineering, Ghent University (Belgium); Smagghe, Guy [Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University (Belgium); Coelus, Sofie; Adriaenssens, Dieter [Food Chemistry and Human Nutrition (NutriFOODChem), Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University (Belgium); De Winter, Karel; Desmet, Tom [Center for Industrial Biotechnology and Biocatalysis, Faculty of Bioscience Engineering, Ghent University (Belgium); Raes, Katleen [Department of Applied Biological Science, Faculty of Bioscience Engineering, Ghent University (Belgium); Van Camp, John, E-mail: john.vancamp@ugent.be [Food Chemistry and Human Nutrition (NutriFOODChem), Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University (Belgium)

    2016-06-14

    The combination of ion mobility and mass spectrometry (MS) affords significant improvements over conventional MS/MS, especially in the characterization of isomeric metabolites due to the differences in their collision cross sections (CCS). Experimentally obtained CCS values are typically matched with theoretical CCS values from Trajectory Method (TM) and/or Projection Approximation (PA) calculations. In this paper, predictive models for CCS of deprotonated phenolics were developed using molecular descriptors and chemometric tools, stepwise multiple linear regression (SMLR), principal components regression (PCR), and partial least squares regression (PLS). A total of 102 molecular descriptors were generated and reduced to 28 after employing a feature selection tool, composed of mass, topological descriptors, Jurs descriptors and shadow indices. Therefore, the generated models considered the effects of mass, 3D conformation and partial charge distribution on CCS, which are the main parameters for either TM or PA (only 3D conformation) calculations. All three techniques yielded highly predictive models for both the training (R{sup 2}{sub SMLR} = 0.9911; R{sup 2}{sub PCR} = 0.9917; R{sup 2}{sub PLS} = 0.9918) and validation datasets (R{sup 2}{sub SMLR} = 0.9489; R{sup 2}{sub PCR} = 0.9761; R{sup 2}{sub PLS} = 0.9760). Also, the high cross validated R{sup 2} values indicate that the generated models are robust and highly predictive (Q{sup 2}{sub SMLR} = 0.9859; Q{sup 2}{sub PCR} = 0.9748; Q{sup 2}{sub PLS} = 0.9760). The predictions were also very comparable to the results from TM calculations using modified mobcal (N2). Most importantly, this method offered a rapid (<10 min) alternative to TM calculations without compromising predictive ability. These methods could therefore be used in routine analysis and could be easily integrated to metabolite identification platforms. - Highlights: • CCS for deprotonated phenolics were measured using TWIMS.

  20. Collision cross section prediction of deprotonated phenolics in a travelling-wave ion mobility spectrometer using molecular descriptors and chemometrics

    International Nuclear Information System (INIS)

    Gonzales, Gerard Bryan; Smagghe, Guy; Coelus, Sofie; Adriaenssens, Dieter; De Winter, Karel; Desmet, Tom; Raes, Katleen; Van Camp, John

    2016-01-01

    The combination of ion mobility and mass spectrometry (MS) affords significant improvements over conventional MS/MS, especially in the characterization of isomeric metabolites due to the differences in their collision cross sections (CCS). Experimentally obtained CCS values are typically matched with theoretical CCS values from Trajectory Method (TM) and/or Projection Approximation (PA) calculations. In this paper, predictive models for CCS of deprotonated phenolics were developed using molecular descriptors and chemometric tools, stepwise multiple linear regression (SMLR), principal components regression (PCR), and partial least squares regression (PLS). A total of 102 molecular descriptors were generated and reduced to 28 after employing a feature selection tool, composed of mass, topological descriptors, Jurs descriptors and shadow indices. Therefore, the generated models considered the effects of mass, 3D conformation and partial charge distribution on CCS, which are the main parameters for either TM or PA (only 3D conformation) calculations. All three techniques yielded highly predictive models for both the training (R"2_S_M_L_R = 0.9911; R"2_P_C_R = 0.9917; R"2_P_L_S = 0.9918) and validation datasets (R"2_S_M_L_R = 0.9489; R"2_P_C_R = 0.9761; R"2_P_L_S = 0.9760). Also, the high cross validated R"2 values indicate that the generated models are robust and highly predictive (Q"2_S_M_L_R = 0.9859; Q"2_P_C_R = 0.9748; Q"2_P_L_S = 0.9760). The predictions were also very comparable to the results from TM calculations using modified mobcal (N2). Most importantly, this method offered a rapid (<10 min) alternative to TM calculations without compromising predictive ability. These methods could therefore be used in routine analysis and could be easily integrated to metabolite identification platforms. - Highlights: • CCS for deprotonated phenolics were measured using TWIMS. • Isomeric phenolics were separated in the IMS based on their CCS. • SMLR

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

    Science.gov (United States)

    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.

  2. The model of the long-range effect in solids: Evolution of structure, clusters of internal boundaries, and their statistical descriptors

    Science.gov (United States)

    Herega, Alexander; Sukhanov, Volodymyr; Vyrovoy, Valery

    2017-12-01

    It is known that the multifocal mechanism of genesis of structure of heterogeneous materials provokes intensive formation of internal boundaries. In the present papers, the dependence of the structure and properties of material on the characteristic size and shape, the number and size distribution, and the character of interaction of individual internal boundaries and their clusters is studied. The limitation on the applicability of the material damage coefficient is established; the effective information descriptor of internal boundaries is proposed. An idea of the effect of long-range interaction in irradiated solids on the realization of the second-order phase transition is introduced; a phenomenological percolation model of the effect is proposed.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Consistent Estimation of Partition Markov Models

    Directory of Open Access Journals (Sweden)

    Jesús E. García

    2017-04-01

    Full Text Available The Partition Markov Model characterizes the process by a partition L of the state space, where the elements in each part of L share the same transition probability to an arbitrary element in the alphabet. This model aims to answer the following questions: what is the minimal number of parameters needed to specify a Markov chain and how to estimate these parameters. In order to answer these questions, we build a consistent strategy for model selection which consist of: giving a size n realization of the process, finding a model within the Partition Markov class, with a minimal number of parts to represent the process law. From the strategy, we derive a measure that establishes a metric in the state space. In addition, we show that if the law of the process is Markovian, then, eventually, when n goes to infinity, L will be retrieved. We show an application to model internet navigation patterns.

  6. QSAR, QSPR and QSRR in Terms of 3-D-MoRSE Descriptors for In Silico Screening of Clofibric Acid Analogues.

    Science.gov (United States)

    Di Tullio, Maurizio; Maccallini, Cristina; Ammazzalorso, Alessandra; Giampietro, Letizia; Amoroso, Rosa; De Filippis, Barbara; Fantacuzzi, Marialuigia; Wiczling, Paweł; Kaliszan, Roman

    2012-07-01

    A series of 27 analogues of clofibric acid, mostly heteroarylalkanoic derivatives, have been analyzed by a novel high-throughput reversed-phase HPLC method employing combined gradient of eluent's pH and organic modifier content. The such determined hydrophobicity (lipophilicity) parameters, log kw , and acidity constants, pKa , were subjected to multiple regression analysis to get a QSRR (Quantitative StructureRetention Relationships) and a QSPR (Quantitative Structure-Property Relationships) equation, respectively, describing these pharmacokinetics-determining physicochemical parameters in terms of the calculation chemistry derived structural descriptors. The previously determined in vitro log EC50 values - transactivation activity towards PPARα (human Peroxisome Proliferator-Activated Receptor α) - have also been described in a QSAR (Quantitative StructureActivity Relationships) equation in terms of the 3-D-MoRSE descriptors (3D-Molecule Representation of Structures based on Electron diffraction descriptors). The QSAR model derived can serve for an a priori prediction of bioactivity in vitro of any designed analogue, whereas the QSRR and the QSPR models can be used to evaluate lipophilicity and acidity, respectively, of the compounds, and hence to rational guide selection of structures of proper pharmacokinetics. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Prediction of monomer reactivity in radical copolymerizations from transition state quantum chemical descriptors

    Directory of Open Access Journals (Sweden)

    Zhengde Tan

    2013-01-01

    Full Text Available In comparison with the Q-e scheme, the Revised Patterns Scheme: the U, V Version (the U-V scheme has greatly improved both its accessibility and its accuracy in interpreting and predicting the reactivity of a monomer in free-radical copolymerizations. Quantitative structure-activity relationship (QSAR models were developed to predict the reactivity parameters u and v of the U-V scheme, by applying genetic algorithm (GA and support vector machine (SVM techniques. Quantum chemical descriptors used for QSAR models were calculated from transition state species with structures C¹H3 - C²HR³• or •C¹H2 - C²H2R³ (formed from vinyl monomers C¹H²=C²HR³ + H•, using density functional theory (DFT, at the UB3LYP level of theory with 6-31G(d basis set. The optimum support vector regression (SVR model of the reactivity parameter u based on Gaussian radial basis function (RBF kernel (C = 10, ε = 10- 5 and γ = 1.0 produced root-mean-square (rms errors for the training, validation and prediction sets being 0.220, 0.326 and 0.345, respectively. The optimal SVR model for v with the RBF kernel (C = 20, ε = 10- 4 and γ = 1.2 produced rms errors for the training set of 0.123, the validation set of 0.206 and the prediction set of 0.238. The feasibility of applying the transition state quantum chemical descriptors to develop SVM models for reactivity parameters u and v in the U-V scheme has been demonstrated.

  8. 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.

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

    Science.gov (United States)

    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.

  10. ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins.

    Science.gov (United States)

    Ruiz-Blanco, Yasser B; Paz, Waldo; Green, James; Marrero-Ponce, Yovani

    2015-05-16

    The exponential growth of protein structural and sequence databases is enabling multifaceted approaches to understanding the long sought sequence-structure-function relationship. Advances in computation now make it possible to apply well-established data mining and pattern recognition techniques to these data to learn models that effectively relate structure and function. However, extracting meaningful numerical descriptors of protein sequence and structure is a key issue that requires an efficient and widely available solution. We here introduce ProtDCal, a new computational software suite capable of generating tens of thousands of features considering both sequence-based and 3D-structural descriptors. We demonstrate, by means of principle component analysis and Shannon entropy tests, how ProtDCal's sequence-based descriptors provide new and more relevant information not encoded by currently available servers for sequence-based protein feature generation. The wide diversity of the 3D-structure-based features generated by ProtDCal is shown to provide additional complementary information and effectively completes its general protein encoding capability. As demonstration of the utility of ProtDCal's features, prediction models of N-linked glycosylation sites are trained and evaluated. Classification performance compares favourably with that of contemporary predictors of N-linked glycosylation sites, in spite of not using domain-specific features as input information. ProtDCal provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http://bioinf.sce.carleton.ca/ProtDCal/ . ProtDCal introduces local and group-based encoding which enhances the diversity of the information captured by the computed features. Furthermore, we have shown that adding structure-based descriptors contributes non-redundant additional information to the features-based characterization of polypeptide systems. This

  11. 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 ...

  12. Evaluating descriptors for the lateral translocation of membrane proteins.

    Science.gov (United States)

    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.

  13. Financial model calibration using consistency hints.

    Science.gov (United States)

    Abu-Mostafa, Y S

    2001-01-01

    We introduce a technique for forcing the calibration of a financial model to produce valid parameters. The technique is based on learning from hints. It converts simple curve fitting into genuine calibration, where broad conclusions can be inferred from parameter values. The technique augments the error function of curve fitting with consistency hint error functions based on the Kullback-Leibler distance. We introduce an efficient EM-type optimization algorithm tailored to this technique. We also introduce other consistency hints, and balance their weights using canonical errors. We calibrate the correlated multifactor Vasicek model of interest rates, and apply it successfully to Japanese Yen swaps market and US dollar yield market.

  14. Multi Voxel Descriptor for 3D Texture Retrieval

    Directory of Open Access Journals (Sweden)

    Hero Yudo Martono

    2016-08-01

    Full Text Available In this paper, we present a new feature descriptors  which exploit voxels for 3D textured retrieval system when models vary either by geometric shape or texture or both. First, we perform pose normalisation to modify arbitrary 3D models  in order to have same orientation. We then map the structure of 3D models into voxels. This purposes to make all the 3D models have the same dimensions. Through this voxels, we can capture information from a number of ways.  First, we build biner voxel histogram and color voxel histogram.  Second, we compute distance from centre voxel into other voxels and generate histogram. Then we also compute fourier transform in spectral space.  For capturing texture feature, we apply voxel tetra pattern. Finally, we merge all features by linear combination. For experiment, we use standard evaluation measures such as Nearest Neighbor (NN, First Tier (FT, Second Tier (ST, Average Dynamic Recall (ADR. Dataset in SHREC 2014  and its evaluation program is used to verify the proposed method. Experiment result show that the proposed method  is more accurate when compared with some methods of state-of-the-art.

  15. 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...

  16. 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.

  17. 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.

  18. 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 ...

  19. Self-organizing maps of molecular descriptors for sesquiterpene lactones and their application to the chemotaxonomy of the Asteraceae family.

    Science.gov (United States)

    Scotti, Marcus T; Emerenciano, Vicente; Ferreira, Marcelo J P; Scotti, Luciana; Stefani, Ricardo; da Silva, Marcelo S; Mendonça Junior, Francisco Jaime B

    2012-04-20

    The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

  20. Objective scoring of transformed foci in BALB/c 3T3 cell transformation assay by statistical image descriptors.

    Science.gov (United States)

    Urani, C; Corvi, R; Callegaro, G; Stefanini, F M

    2013-09-01

    In vitro cell transformation assays (CTAs) have been shown to model important stages of in vivo carcinogenesis and have the potential to predict carcinogenicity in humans. Advantages of CTAs are their ability of revealing both genotoxic and non-genotoxic carcinogens while reducing both experimental costs and the number of animals used. The endpoint of the CTA is foci formation, and requires classification under light microscopy based on morphology. Thus current limitations for the wide adoption of the assay partially depend on a fair degree of subjectivity in foci scoring. An objective evaluation may be obtained after separating foci from background monolayer in the digital image, and quantifying values of statistical descriptors which are selected to capture eye-scored morphological features. The aim of this study was to develop statistical descriptors to be applied to transformed foci of BALB/c 3T3, which cover foci size, multilayering and invasive cell growth into the background monolayer. Proposed descriptors were applied to a database of 407 foci images to explore the numerical features, and to illustrate open problems and potential solutions. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

    Science.gov (United States)

    Nelson, N.; Munoz-Carpena, R.; Neale, P.; Tzortziou, M.; Megonigal, P.

    2017-12-01

    Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically-regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer - early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

  2. 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...

  3. Universal fragment descriptors for predicting properties of inorganic crystals

    Science.gov (United States)

    Isayev, Olexandr; Oses, Corey; Toher, Cormac; Gossett, Eric; Curtarolo, Stefano; Tropsha, Alexander

    2017-06-01

    Although historically materials discovery has been driven by a laborious trial-and-error process, knowledge-driven materials design can now be enabled by the rational combination of Machine Learning methods and materials databases. Here, data from the AFLOW repository for ab initio calculations is combined with Quantitative Materials Structure-Property Relationship models to predict important properties: metal/insulator classification, band gap energy, bulk/shear moduli, Debye temperature and heat capacities. The prediction's accuracy compares well with the quality of the training data for virtually any stoichiometric inorganic crystalline material, reciprocating the available thermomechanical experimental data. The universality of the approach is attributed to the construction of the descriptors: Property-Labelled Materials Fragments. The representations require only minimal structural input allowing straightforward implementations of simple heuristic design rules.

  4. Grading system to categorize breast MRI using BI-RADS 5th edition: a statistical study of non-mass enhancement descriptors in terms of probability of malignancy.

    Science.gov (United States)

    Asada, Tatsunori; Yamada, Takayuki; Kanemaki, Yoshihide; Fujiwara, Keishi; Okamoto, Satoko; Nakajima, Yasuo

    2018-03-01

    To analyze the association of breast non-mass enhancement descriptors in the BI-RADS 5th edition with malignancy, and to establish a grading system and categorization of descriptors. This study was approved by our institutional review board. A total of 213 patients were enrolled. Breast MRI was performed with a 1.5-T MRI scanner using a 16-channel breast radiofrequency coil. Two radiologists determined internal enhancement and distribution of non-mass enhancement by consensus. Corresponding pathologic diagnoses were obtained by either biopsy or surgery. The probability of malignancy by descriptor was analyzed using Fisher's exact test and multivariate logistic regression analysis. The probability of malignancy by category was analyzed using Fisher's exact and multi-group comparison tests. One hundred seventy-eight lesions were malignant. Multivariate model analysis showed that internal enhancement (homogeneous vs others, p probability of malignancy (p < 0.0001). The three-grade criteria and categorization by sum-up grades of descriptors appear valid for non-mass enhancement.

  5. Self-consistent model of confinement

    International Nuclear Information System (INIS)

    Swift, A.R.

    1988-01-01

    A model of the large-spatial-distance, zero--three-momentum, limit of QCD is developed from the hypothesis that there is an infrared singularity. Single quarks and gluons do not propagate because they have infinite energy after renormalization. The Hamiltonian formulation of the path integral is used to quantize QCD with physical, nonpropagating fields. Perturbation theory in the infrared limit is simplified by the absence of self-energy insertions and by the suppression of large classes of diagrams due to vanishing propagators. Remaining terms in the perturbation series are resummed to produce a set of nonlinear, renormalizable integral equations which fix both the confining interaction and the physical propagators. Solutions demonstrate the self-consistency of the concepts of an infrared singularity and nonpropagating fields. The Wilson loop is calculated to provide a general proof of confinement. Bethe-Salpeter equations for quark-antiquark pairs and for two gluons have finite-energy solutions in the color-singlet channel. The choice of gauge is addressed in detail. Large classes of corrections to the model are discussed and shown to support self-consistency

  6. 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

  7. PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences.

    Science.gov (United States)

    Wang, Yanbin; You, Zhuhong; Li, Xiao; Chen, Xing; Jiang, Tonghai; Zhang, Jingting

    2017-05-11

    Protein-protein interactions (PPIs) are essential for most living organisms' process. Thus, detecting PPIs is extremely important to understand the molecular mechanisms of biological systems. Although many PPIs data have been generated by high-throughput technologies for a variety of organisms, the whole interatom is still far from complete. In addition, the high-throughput technologies for detecting PPIs has some unavoidable defects, including time consumption, high cost, and high error rate. In recent years, with the development of machine learning, computational methods have been broadly used to predict PPIs, and can achieve good prediction rate. In this paper, we present here PCVMZM, a computational method based on a Probabilistic Classification Vector Machines (PCVM) model and Zernike moments (ZM) descriptor for predicting the PPIs from protein amino acids sequences. Specifically, a Zernike moments (ZM) descriptor is used to extract protein evolutionary information from Position-Specific Scoring Matrix (PSSM) generated by Position-Specific Iterated Basic Local Alignment Search Tool (PSI-BLAST). Then, PCVM classifier is used to infer the interactions among protein. When performed on PPIs datasets of Yeast and H. Pylori , the proposed method can achieve the average prediction accuracy of 94.48% and 91.25%, respectively. In order to further evaluate the performance of the proposed method, the state-of-the-art support vector machines (SVM) classifier is used and compares with the PCVM model. Experimental results on the Yeast dataset show that the performance of PCVM classifier is better than that of SVM classifier. The experimental results indicate that our proposed method is robust, powerful and feasible, which can be used as a helpful tool for proteomics research.

  8. 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...

  9. Sci-Thur AM: YIS – 06: A Monte Carlo study of macro- and microscopic dose descriptors and the microdosimetric spread using detailed cellular models

    Energy Technology Data Exchange (ETDEWEB)

    Oliver, Patricia; Thomson, Rowan [Carleton University (Canada)

    2016-08-15

    Purpose: To develop Monte Carlo models of cell clusters to investigate the relationships between macro- and microscopic dose descriptors, quantify the microdosimetric spread in energy deposition for subcellular targets, and determine how these results depend on the computational model. Methods: Microscopic tissue structure is modelled as clusters of 13 to 150 cells, with cell (nuclear) radii between 5 and 10 microns (2 and 9 microns). Energy imparted per unit mass (specific energy or dose) is scored in the nucleus (D{sub nuc}) and cytoplasm (D{sub cyt}) for incident photon energies from 20 to 370 keV. Dose-to-water (D{sub w,m}) and dose-to-medium (D{sub m,m}) are compared to D{sub nuc} and D{sub cyt}. Single cells and single nuclear cavities are also simulated. Results: D{sub nuc} and D{sub cyt} are sensitive to the surrounding environment with deviations of up to 13% for a single nucleus/cell compared with a multicellular cluster. These dose descriptors vary with cell and nucleus size by up to 10%. D{sub nuc} and D{sub cyt} differ from D{sub w,m} and D{sub m,m} by up to 32%. The microdosimetric spread is sensitive to whether cells are arranged randomly or in a hexagonal lattice, and whether subcellular compartment sizes are sampled from a normal distribution or are constant throughout the cluster. Conclusions: D{sub nuc} and D{sub cyt} are sensitive to cell morphology, elemental composition and the presence of surrounding cells. The microdosimetric spread was investigated using realistic elemental compositions for the nucleus and cytoplasm, and depends strongly on subcellular compartment size, source energy and dose.

  10. Recognizing stationary and locomotion activities using combinational of spectral analysis with statistical descriptors features

    Science.gov (United States)

    Zainudin, M. N. Shah; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran

    2017-10-01

    Prior knowledge in pervasive computing recently garnered a lot of attention due to its high demand in various application domains. Human activity recognition (HAR) considered as the applications that are widely explored by the expertise that provides valuable information to the human. Accelerometer sensor-based approach is utilized as devices to undergo the research in HAR since their small in size and this sensor already build-in in the various type of smartphones. However, the existence of high inter-class similarities among the class tends to degrade the recognition performance. Hence, this work presents the method for activity recognition using our proposed features from combinational of spectral analysis with statistical descriptors that able to tackle the issue of differentiating stationary and locomotion activities. The noise signal is filtered using Fourier Transform before it will be extracted using two different groups of features, spectral frequency analysis, and statistical descriptors. Extracted signal later will be classified using random forest ensemble classifier models. The recognition results show the good accuracy performance for stationary and locomotion activities based on USC HAD datasets.

  11. 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.

  12. 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.

  13. Consistent spectroscopy for a extended gauge model

    International Nuclear Information System (INIS)

    Oliveira Neto, G. de.

    1990-11-01

    The consistent spectroscopy was obtained with a Lagrangian constructed with vector fields with a U(1) group extended symmetry. As consistent spectroscopy is understood the determination of quantum physical properties described by the model in an manner independent from the possible parametrizations adopted in their description. (L.C.J.A.)

  14. 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.

  15. CONSISTENCY UNDER SAMPLING OF EXPONENTIAL RANDOM GRAPH MODELS.

    Science.gov (United States)

    Shalizi, Cosma Rohilla; Rinaldo, Alessandro

    2013-04-01

    The growing availability of network data and of scientific interest in distributed systems has led to the rapid development of statistical models of network structure. Typically, however, these are models for the entire network, while the data consists only of a sampled sub-network. Parameters for the whole network, which is what is of interest, are estimated by applying the model to the sub-network. This assumes that the model is consistent under sampling , or, in terms of the theory of stochastic processes, that it defines a projective family. Focusing on the popular class of exponential random graph models (ERGMs), we show that this apparently trivial condition is in fact violated by many popular and scientifically appealing models, and that satisfying it drastically limits ERGM's expressive power. These results are actually special cases of more general results about exponential families of dependent random variables, which we also prove. Using such results, we offer easily checked conditions for the consistency of maximum likelihood estimation in ERGMs, and discuss some possible constructive responses.

  16. Consistent Stochastic Modelling of Meteocean Design Parameters

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Sterndorff, M. J.

    2000-01-01

    Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...

  17. Consistency and Reconciliation Model In Regional Development Planning

    Directory of Open Access Journals (Sweden)

    Dina Suryawati

    2016-10-01

    Full Text Available The aim of this study was to identify the problems and determine the conceptual model of regional development planning. Regional development planning is a systemic, complex and unstructured process. Therefore, this study used soft systems methodology to outline unstructured issues with a structured approach. The conceptual models that were successfully constructed in this study are a model of consistency and a model of reconciliation. Regional development planning is a process that is well-integrated with central planning and inter-regional planning documents. Integration and consistency of regional planning documents are very important in order to achieve the development goals that have been set. On the other hand, the process of development planning in the region involves technocratic system, that is, both top-down and bottom-up system of participation. Both must be balanced, do not overlap and do not dominate each other. regional, development, planning, consistency, reconciliation

  18. Consistent three-equation model for thin films

    Science.gov (United States)

    Richard, Gael; Gisclon, Marguerite; Ruyer-Quil, Christian; Vila, Jean-Paul

    2017-11-01

    Numerical simulations of thin films of newtonian fluids down an inclined plane use reduced models for computational cost reasons. These models are usually derived by averaging over the fluid depth the physical equations of fluid mechanics with an asymptotic method in the long-wave limit. Two-equation models are based on the mass conservation equation and either on the momentum balance equation or on the work-energy theorem. We show that there is no two-equation model that is both consistent and theoretically coherent and that a third variable and a three-equation model are required to solve all theoretical contradictions. The linear and nonlinear properties of two and three-equation models are tested on various practical problems. We present a new consistent three-equation model with a simple mathematical structure which allows an easy and reliable numerical resolution. The numerical calculations agree fairly well with experimental measurements or with direct numerical resolutions for neutral stability curves, speed of kinematic waves and of solitary waves and depth profiles of wavy films. The model can also predict the flow reversal at the first capillary trough ahead of the main wave hump.

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

    Science.gov (United States)

    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

  20. Multimodal image registration based on binary gradient angle descriptor.

    Science.gov (United States)

    Jiang, Dongsheng; Shi, Yonghong; Yao, Demin; Fan, Yifeng; Wang, Manning; Song, Zhijian

    2017-12-01

    Multimodal image registration plays an important role in image-guided interventions/therapy and atlas building, and it is still a challenging task due to the complex intensity variations in different modalities. The paper addresses the problem and proposes a simple, compact, fast and generally applicable modality-independent binary gradient angle descriptor (BGA) based on the rationale of gradient orientation alignment. The BGA can be easily calculated at each voxel by coding the quadrant in which a local gradient vector falls, and it has an extremely low computational complexity, requiring only three convolutions, two multiplication operations and two comparison operations. Meanwhile, the binarized encoding of the gradient orientation makes the BGA more resistant to image degradations compared with conventional gradient orientation methods. The BGA can extract similar feature descriptors for different modalities and enable the use of simple similarity measures, which makes it applicable within a wide range of optimization frameworks. The results for pairwise multimodal and monomodal registrations between various images (T1, T2, PD, T1c, Flair) consistently show that the BGA significantly outperforms localized mutual information. The experimental results also confirm that the BGA can be a reliable alternative to the sum of absolute difference in monomodal image registration. The BGA can also achieve an accuracy of [Formula: see text], similar to that of the SSC, for the deformable registration of inhale and exhale CT scans. Specifically, for the highly challenging deformable registration of preoperative MRI and 3D intraoperative ultrasound images, the BGA achieves a similar registration accuracy of [Formula: see text] compared with state-of-the-art approaches, with a computation time of 18.3 s per case. The BGA improves the registration performance in terms of both accuracy and time efficiency. With further acceleration, the framework has the potential for

  1. The use of reproductive vigor descriptors in studying genetic ...

    African Journals Online (AJOL)

    The use of reproductive vigor descriptors in studying genetic variability in nine Tunisian faba bean ( Vicia faba L.) populations. ... The dendrogram based on Nei's genetic distance of the 9 populations using UPGMA method, show some genetic drift between populations. Key words: Faba bean, agromorphological traits, ...

  2. 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

  3. 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

  4. Fourier-based quantification of renal glomeruli size using Hough transform and shape descriptors.

    Science.gov (United States)

    Najafian, Sohrab; Beigzadeh, Borhan; Riahi, Mohammad; Khadir Chamazkoti, Fatemeh; Pouramir, Mahdi

    2017-11-01

    Analysis of glomeruli geometry is important in histopathological evaluation of renal microscopic images. Due to the shape and size disparity of even glomeruli of same kidney, automatic detection of these renal objects is not an easy task. Although manual measurements are time consuming and at times are not very accurate, it is commonly used in medical centers. In this paper, a new method based on Fourier transform following usage of some shape descriptors is proposed to detect these objects and their geometrical parameters. Reaching the goal, a database of 400 regions are selected randomly. 200 regions of which are part of glomeruli and the other 200 regions are not belong to renal corpuscles. ROC curve is used to decide which descriptor could classify two groups better. f_measure, which is a combination of both tpr (true positive rate) and fpr (false positive rate), is also proposed to select optimal threshold for descriptors. Combination of three parameters (solidity, eccentricity, and also mean squared error of fitted ellipse) provided better result in terms of f_measure to distinguish desired regions. Then, Fourier transform of outer edges is calculated to form a complete curve out of separated region(s). The generality of proposed model is verified by use of cross validation method, which resulted tpr of 94%, and fpr of 5%. Calculation of glomerulus' and Bowman's space with use of the algorithm are also compared with a non-automatic measurement done by a renal pathologist, and errors of 5.9%, 5.4%, and 6.26% are resulted in calculation of Capsule area, Bowman space, and glomeruli area, respectively. Having tested different glomeruli with various shapes, the experimental consequences show robustness and reliability of our method. Therefore, it could be used to illustrate renal diseases and glomerular disorders by measuring the morphological changes accurately and expeditiously. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Externally predictive single-descriptor based QSPRs for physico-chemical properties of polychlorinated-naphthalenes: Exploring relationships of log S{sub W}, log K{sub OA}, and log K{sub OW} with electron-correlation

    Energy Technology Data Exchange (ETDEWEB)

    Chayawan; Vikas, E-mail: qlabspu@pu.ac.in

    2015-10-15

    Highlights: • Aqueous solubility and partition coefficient are modelled using single-parameter. • Electron-correlation observed as a vital predictorof physico-chemical properties. • For octanol-air partition coefficient, energy and polarizability yield best models. • Dipole-moment is found to be worst single-descriptor for the properties analysed. - Abstract: Quantitative structure–property relationships (QSPRs), based only on a single-parameter, are proposed for the prediction of physico-chemical properties, namely, aqueous solubility (log S{sub W}), octanol–water partition coefficient (log K{sub OW}) and octanol–air partition coefficient (log K{sub OA}) of polychloronaphthalenes (PCNs) including all the 75 chloronaphthalene congeners. The QSPR models are developed using molecular descriptors computed through quantum mechanical methods including ab-initio as well as advanced semi-empirical methods. The predictivity of the developed models is tested through state-of-the-art external validation procedures employing an external prediction set of compounds. To analyse the role of instantaneous interactions between electrons (the electron-correlation), the models are also compared with those developed using only the electron-correlation contribution of the quantum chemical descriptor. The electron-correlation contribution towards the chemical hardness and the LUMO energy are observed to be the best predictors for octanol–water partition coefficient, whereas for the octanol–air partition coefficient, the total electronic energy and electron-correlation energy are found to be reliable descriptors, in fact, even better than the polarisability. For aqueous solubility of PCNs, the absolute electronegativity is observed to be the best predictor. This work suggests that the electron-correlation contribution of a quantum-chemical descriptor can be used as a reliable indicator for physico-chemical properties, particularly the partition coefficients.

  6. Uncovering the Geometry of Barrierless Reactions Using Lagrangian Descriptors.

    Science.gov (United States)

    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.

  7. Consistent biokinetic models for the actinide elements

    International Nuclear Information System (INIS)

    Leggett, R.W.

    2001-01-01

    The biokinetic models for Th, Np, Pu, Am and Cm currently recommended by the International Commission on Radiological Protection (ICRP) were developed within a generic framework that depicts gradual burial of skeletal activity in bone volume, depicts recycling of activity released to blood and links excretion to retention and translocation of activity. For other actinide elements such as Ac, Pa, Bk, Cf and Es, the ICRP still uses simplistic retention models that assign all skeletal activity to bone surface and depicts one-directional flow of activity from blood to long-term depositories to excreta. This mixture of updated and older models in ICRP documents has led to inconsistencies in dose estimates and interpretation of bioassay for radionuclides with reasonably similar biokinetics. This paper proposes new biokinetic models for Ac, Pa, Bk, Cf and Es that are consistent with the updated models for Th, Np, Pu, Am and Cm. The proposed models are developed within the ICRP's generic model framework for bone-surface-seeking radionuclides, and an effort has been made to develop parameter values that are consistent with results of comparative biokinetic data on the different actinide elements. (author)

  8. Standard Model Vacuum Stability and Weyl Consistency Conditions

    DEFF Research Database (Denmark)

    Antipin, Oleg; Gillioz, Marc; Krog, Jens

    2013-01-01

    At high energy the standard model possesses conformal symmetry at the classical level. This is reflected at the quantum level by relations between the different beta functions of the model. These relations are known as the Weyl consistency conditions. We show that it is possible to satisfy them...... order by order in perturbation theory, provided that a suitable coupling constant counting scheme is used. As a direct phenomenological application, we study the stability of the standard model vacuum at high energies and compare with previous computations violating the Weyl consistency conditions....

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

    Directory of Open Access Journals (Sweden)

    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.

  10. 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.

  11. Fourth meeting entitled “Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data”

    CERN Document Server

    Vilanova, Anna; Burgeth, Bernhard; Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data

    2014-01-01

    Arising from the fourth Dagstuhl conference entitled Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data (2011), this book offers a broad and vivid view of current work in this emerging field. Topics covered range from applications of the analysis of tensor fields to research on their mathematical and analytical properties. Part I, Tensor Data Visualization, surveys techniques for visualization of tensors and tensor fields in engineering, discusses the current state of the art and challenges, and examines tensor invariants and glyph design, including an overview of common glyphs. The second Part, Representation and Processing of Higher-order Descriptors, describes a matrix representation of local phase, outlines mathematical morphological operations techniques, extended for use in vector images, and generalizes erosion to the space of diffusion weighted MRI. Part III, Higher Order Tensors and Riemannian-Finsler Geometry, offers powerful mathematical language to model and...

  12. Attributes and descriptors for building performance evaluation

    Directory of Open Access Journals (Sweden)

    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.

  13. Obscure phenomena in statistical analysis of quantitative structure-activity relationships. Part 1: Multicollinearity of physicochemical descriptors.

    Science.gov (United States)

    Mager, P P; Rothe, H

    1990-10-01

    Multicollinearity of physicochemical descriptors leads to serious consequences in quantitative structure-activity relationship (QSAR) analysis, such as incorrect estimators and test statistics of regression coefficients of the ordinary least-squares (OLS) model applied usually to QSARs. Beside the diagnosis of the known simple collinearity, principal component regression analysis (PCRA) also allows the diagnosis of various types of multicollinearity. Only if the absolute values of PCRA estimators are order statistics that decrease monotonically, the effects of multicollinearity can be circumvented. Otherwise, obscure phenomena may be observed, such as good data recognition but low predictive model power of a QSAR model.

  14. 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.

  15. 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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  18. A QSPR STUDY OF NORMAL BOILING POINT OF ORGANIC COMPOUNDS (ALIPHATIC ALKANES USING MOLECULAR DESCRIPTORS

    Directory of Open Access Journals (Sweden)

    B. Souyei

    2013-12-01

    Full Text Available A quantitative structure–property relationship (QSPR study is carried out to develop correlations that relate the molecular structures of organic compounds (Aliphatic Alkanes to their normal boiling point (NBP and two correlations were proposed for constitutionals and connectivity indices Models. The correlations are simple in application with good accuracy, which provide an easy, direct and relatively accurate way to calculate NBP. Such calculation gives us a model that gives results in remarkable correlations with the descriptors of blokes constitutionals (CON, and connectivity indices (CI (R2 = 0.950, δ = 0.766 (R2 = 0.969, δ = 0.782 respectively.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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%.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  3. Consistent Partial Least Squares Path Modeling via Regularization.

    Science.gov (United States)

    Jung, Sunho; Park, JaeHong

    2018-01-01

    Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

  4. Consistent Partial Least Squares Path Modeling via Regularization

    Directory of Open Access Journals (Sweden)

    Sunho Jung

    2018-02-01

    Full Text Available Partial least squares (PLS path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc, designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

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

    Science.gov (United States)

    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.

  6. Ship detection based on rotation-invariant HOG descriptors for airborne infrared images

    Science.gov (United States)

    Xu, Guojing; Wang, Jinyan; Qi, Shengxiang

    2018-03-01

    Infrared thermal imagery is widely used in various kinds of aircraft because of its all-time application. Meanwhile, detecting ships from infrared images attract lots of research interests in recent years. In the case of downward-looking infrared imagery, in order to overcome the uncertainty of target imaging attitude due to the unknown position relationship between the aircraft and the target, we propose a new infrared ship detection method which integrates rotation invariant gradient direction histogram (Circle Histogram of Oriented Gradient, C-HOG) descriptors and the support vector machine (SVM) classifier. In details, the proposed method uses HOG descriptors to express the local feature of infrared images to adapt to changes in illumination and to overcome sea clutter effects. Different from traditional computation of HOG descriptor, we subdivide the image into annular spatial bins instead of rectangle sub-regions, and then Radial Gradient Transform (RGT) on the gradient is applied to achieve rotation invariant histogram information. Considering the engineering application of airborne and real-time requirements, we use SVM for training ship target and non-target background infrared sample images to discriminate real ships from false targets. Experimental results show that the proposed method has good performance in both the robustness and run-time for infrared ship target detection with different rotation angles.

  7. Universal Fragment Descriptors for Predicting Electronic and Mechanical Properties of Inorganic Crystals

    Science.gov (United States)

    Oses, Corey; Isayev, Olexandr; Toher, Cormac; Curtarolo, Stefano; Tropsha, Alexander

    Historically, materials discovery is driven by a laborious trial-and-error process. The growth of materials databases and emerging informatics approaches finally offer the opportunity to transform this practice into data- and knowledge-driven rational design-accelerating discovery of novel materials exhibiting desired properties. By using data from the AFLOW repository for high-throughput, ab-initio calculations, we have generated Quantitative Materials Structure-Property Relationship (QMSPR) models to predict critical materials properties, including the metal/insulator classification, band gap energy, and bulk modulus. The prediction accuracy obtained with these QMSPR models approaches training data for virtually any stoichiometric inorganic crystalline material. We attribute the success and universality of these models to the construction of new materials descriptors-referred to as the universal Property-Labeled Material Fragments (PLMF). This representation affords straightforward model interpretation in terms of simple heuristic design rules that could guide rational materials design. This proof-of-concept study demonstrates the power of materials informatics to dramatically accelerate the search for new materials.

  8. How daylight influences high-order chromatic descriptors in natural images.

    Science.gov (United States)

    Ojeda, Juan; Nieves, Juan Luis; Romero, Javier

    2017-07-01

    Despite the global and local daylight changes naturally occurring in natural scenes, the human visual system usually adapts quite well to those changes, developing a stable color perception. Nevertheless, the influence of daylight in modeling natural image statistics is not fully understood and has received little attention. The aim of this work was to analyze the influence of daylight changes in different high-order chromatic descriptors (i.e., color volume, color gamut, and number of discernible colors) derived from 350 color images, which were rendered under 108 natural illuminants with Correlated Color Temperatures (CCT) from 2735 to 25,889 K. Results suggest that chromatic and luminance information is almost constant and does not depend on the CCT of the illuminant for values above 14,000 K. Nevertheless, differences between the red-green and blue-yellow image components were found below that CCT, with most of the statistical descriptors analyzed showing local extremes in the range 2950 K-6300 K. Uniform regions and areas of the images attracting observers' attention were also considered in this analysis and were characterized by their patchiness index and their saliency maps. Meanwhile, the results of the patchiness index do not show a clear dependence on CCT, and it is remarkable that a significant reduction in the number of discernible colors (58% on average) was found when the images were masked with their corresponding saliency maps. Our results suggest that chromatic diversity, as defined in terms of the discernible colors, can be strongly reduced when an observer scans a natural scene. These findings support the idea that a reduction in the number of discernible colors will guide visual saliency and attention. Whatever the modeling is mediating the neural representation of natural images, natural image statistics, it is clear that natural image statistics should take into account those local maxima and minima depending on the daylight illumination and

  9. Towards reporting standards for neuropsychological study results: A proposal to minimize communication errors with standardized qualitative descriptors for normalized test scores.

    Science.gov (United States)

    Schoenberg, Mike R; Rum, Ruba S

    2017-11-01

    Rapid, clear and efficient communication of neuropsychological results is essential to benefit patient care. Errors in communication are a lead cause of medical errors; nevertheless, there remains a lack of consistency in how neuropsychological scores are communicated. A major limitation in the communication of neuropsychological results is the inconsistent use of qualitative descriptors for standardized test scores and the use of vague terminology. PubMed search from 1 Jan 2007 to 1 Aug 2016 to identify guidelines or consensus statements for the description and reporting of qualitative terms to communicate neuropsychological test scores was conducted. The review found the use of confusing and overlapping terms to describe various ranges of percentile standardized test scores. In response, we propose a simplified set of qualitative descriptors for normalized test scores (Q-Simple) as a means to reduce errors in communicating test results. The Q-Simple qualitative terms are: 'very superior', 'superior', 'high average', 'average', 'low average', 'borderline' and 'abnormal/impaired'. A case example illustrates the proposed Q-Simple qualitative classification system to communicate neuropsychological results for neurosurgical planning. The Q-Simple qualitative descriptor system is aimed as a means to improve and standardize communication of standardized neuropsychological test scores. Research are needed to further evaluate neuropsychological communication errors. Conveying the clinical implications of neuropsychological results in a manner that minimizes risk for communication errors is a quintessential component of evidence-based practice. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    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

  11. Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: Automated measurement development for full field digital mammography

    International Nuclear Information System (INIS)

    Fowler, E. E.; Sellers, T. A.; Lu, B.; Heine, J. J.

    2013-01-01

    Purpose: The Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors are used for standardized mammographic reporting and are assessed visually. This reporting is clinically relevant because breast composition can impact mammographic sensitivity and is a breast cancer risk factor. New techniques are presented and evaluated for generating automated BI-RADS breast composition descriptors using both raw and calibrated full field digital mammography (FFDM) image data.Methods: A matched case-control dataset with FFDM images was used to develop three automated measures for the BI-RADS breast composition descriptors. Histograms of each calibrated mammogram in the percent glandular (pg) representation were processed to create the new BR pg measure. Two previously validated measures of breast density derived from calibrated and raw mammograms were converted to the new BR vc and BR vr measures, respectively. These three measures were compared with the radiologist-reported BI-RADS compositions assessments from the patient records. The authors used two optimization strategies with differential evolution to create these measures: method-1 used breast cancer status; and method-2 matched the reported BI-RADS descriptors. Weighted kappa (κ) analysis was used to assess the agreement between the new measures and the reported measures. Each measure's association with breast cancer was evaluated with odds ratios (ORs) adjusted for body mass index, breast area, and menopausal status. ORs were estimated as per unit increase with 95% confidence intervals.Results: The three BI-RADS measures generated by method-1 had κ between 0.25–0.34. These measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.87 (1.34, 2.59) for BR pg ; (b) OR = 1.93 (1.36, 2.74) for BR vc ; and (c) OR = 1.37 (1.05, 1.80) for BR vr . The measures generated by method-2 had κ between 0.42–0.45. Two of these measures were significantly

  12. Diagnosing a Strong-Fault Model by Conflict and Consistency.

    Science.gov (United States)

    Zhang, Wenfeng; Zhao, Qi; Zhao, Hongbo; Zhou, Gan; Feng, Wenquan

    2018-03-29

    The diagnosis method for a weak-fault model with only normal behaviors of each component has evolved over decades. However, many systems now demand a strong-fault models, the fault modes of which have specific behaviors as well. It is difficult to diagnose a strong-fault model due to its non-monotonicity. Currently, diagnosis methods usually employ conflicts to isolate possible fault and the process can be expedited when some observed output is consistent with the model's prediction where the consistency indicates probably normal components. This paper solves the problem of efficiently diagnosing a strong-fault model by proposing a novel Logic-based Truth Maintenance System (LTMS) with two search approaches based on conflict and consistency. At the beginning, the original a strong-fault model is encoded by Boolean variables and converted into Conjunctive Normal Form (CNF). Then the proposed LTMS is employed to reason over CNF and find multiple minimal conflicts and maximal consistencies when there exists fault. The search approaches offer the best candidate efficiency based on the reasoning result until the diagnosis results are obtained. The completeness, coverage, correctness and complexity of the proposals are analyzed theoretically to show their strength and weakness. Finally, the proposed approaches are demonstrated by applying them to a real-world domain-the heat control unit of a spacecraft-where the proposed methods are significantly better than best first and conflict directly with A* search methods.

  13. Self-consistent one-gluon exchange in soliton bag models

    International Nuclear Information System (INIS)

    Dodd, L.R.; Adelaide Univ.; Williams, A.G.

    1988-01-01

    The treatment of soliton bag models as two-point boundary value problems is extended to include self-consistent one-gluon exchange interactions. The colour-magnetic contribution to the nucleon-delta mass splitting is calculated self-consistently in the mean-field, one-gluon-exchange approximation for the Friedberg-Lee and Nielsen-Patkos models. Small glueball mass parameters (m GB ∝ 500 MeV) are favoured. Comparisons with previous calculations are made. (orig.)

  14. 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…

  15. 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.

  16. 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

  17. Diagnosing a Strong-Fault Model by Conflict and Consistency

    Directory of Open Access Journals (Sweden)

    Wenfeng Zhang

    2018-03-01

    Full Text Available The diagnosis method for a weak-fault model with only normal behaviors of each component has evolved over decades. However, many systems now demand a strong-fault models, the fault modes of which have specific behaviors as well. It is difficult to diagnose a strong-fault model due to its non-monotonicity. Currently, diagnosis methods usually employ conflicts to isolate possible fault and the process can be expedited when some observed output is consistent with the model’s prediction where the consistency indicates probably normal components. This paper solves the problem of efficiently diagnosing a strong-fault model by proposing a novel Logic-based Truth Maintenance System (LTMS with two search approaches based on conflict and consistency. At the beginning, the original a strong-fault model is encoded by Boolean variables and converted into Conjunctive Normal Form (CNF. Then the proposed LTMS is employed to reason over CNF and find multiple minimal conflicts and maximal consistencies when there exists fault. The search approaches offer the best candidate efficiency based on the reasoning result until the diagnosis results are obtained. The completeness, coverage, correctness and complexity of the proposals are analyzed theoretically to show their strength and weakness. Finally, the proposed approaches are demonstrated by applying them to a real-world domain—the heat control unit of a spacecraft—where the proposed methods are significantly better than best first and conflict directly with A* search methods.

  18. Consistent model reduction of polymer chains in solution in dissipative particle dynamics: Model description

    KAUST Repository

    Moreno Chaparro, Nicolas; Nunes, Suzana Pereira; Calo, Victor M.

    2015-01-01

    considerations we explicitly account for the correlation between beads in fine-grained DPD models and consistently represent the effect of these correlations in a reduced model, in a practical and simple fashion via power laws and the consistent scaling

  19. 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.

  20. 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.

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

    Science.gov (United States)

    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.

  2. 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.

  3. Density functional theory fragment descriptors to quantify the reactivity of a molecular family: application to amino acids.

    Science.gov (United States)

    Senet, P; Aparicio, F

    2007-04-14

    By using the exact density functional theory, one demonstrates that the value of the local electronic softness of a molecular fragment is directly related to the polarization charge (Coulomb hole) induced by a test electron removed (or added) from (at) the fragment. Our finding generalizes to a chemical group a formal relation between these molecular descriptors recently obtained for an atom in a molecule using an approximate atomistic model [P. Senet and M. Yang, J. Chem. Sci. 117, 411 (2005)]. In addition, a practical ab initio computational scheme of the Coulomb hole and related local descriptors of reactivity of a molecular family having in common a similar fragment is presented. As a blind test, the method is applied to the lateral chains of the 20 isolated amino acids. One demonstrates that the local softness of the lateral chain is a quantitative measure of the similarity of the amino acids. It predicts the separation of amino acids in different biochemical groups (aliphatic, basic, acidic, sulfur contained, and aromatic). The present approach may find applications in quantitative structure activity relationship methodology.

  4. A new k-epsilon model consistent with Monin-Obukhov similarity theory

    DEFF Research Database (Denmark)

    van der Laan, Paul; Kelly, Mark C.; Sørensen, Niels N.

    2017-01-01

    A new k-" model is introduced that is consistent with Monin–Obukhov similarity theory (MOST). The proposed k-" model is compared with another k-" model that was developed in an attempt to maintain inlet profiles compatible with MOST. It is shown that the previous k-" model is not consistent with ...

  5. Probabilistic Elastic Part Model: A Pose-Invariant Representation for Real-World Face Verification.

    Science.gov (United States)

    Li, Haoxiang; Hua, Gang

    2018-04-01

    Pose variation remains to be a major challenge for real-world face recognition. We approach this problem through a probabilistic elastic part model. We extract local descriptors (e.g., LBP or SIFT) from densely sampled multi-scale image patches. By augmenting each descriptor with its location, a Gaussian mixture model (GMM) is trained to capture the spatial-appearance distribution of the face parts of all face images in the training corpus, namely the probabilistic elastic part (PEP) model. Each mixture component of the GMM is confined to be a spherical Gaussian to balance the influence of the appearance and the location terms, which naturally defines a part. Given one or multiple face images of the same subject, the PEP-model builds its PEP representation by sequentially concatenating descriptors identified by each Gaussian component in a maximum likelihood sense. We further propose a joint Bayesian adaptation algorithm to adapt the universally trained GMM to better model the pose variations between the target pair of faces/face tracks, which consistently improves face verification accuracy. Our experiments show that we achieve state-of-the-art face verification accuracy with the proposed representations on the Labeled Face in the Wild (LFW) dataset, the YouTube video face database, and the CMU MultiPIE dataset.

  6. Thermodynamically consistent model calibration in chemical kinetics

    Directory of Open Access Journals (Sweden)

    Goutsias John

    2011-05-01

    Full Text Available Abstract Background The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. Results We introduce a thermodynamically consistent model calibration (TCMC method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. Conclusions TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new

  7. 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

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

    OpenAIRE

    Morteza Atabati; Kobra Zarei; Azam Borhani

    2016-01-01

    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 des...

  9. 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

  10. Genetic dissimilarity among sweet potato genotypes using morphological and molecular descriptors

    Directory of Open Access Journals (Sweden)

    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.

  11. Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.

    Science.gov (United States)

    Murrell, Daniel S; Cortes-Ciriano, Isidro; van Westen, Gerard J P; Stott, Ian P; Bender, Andreas; Malliavin, Thérèse E; Glen, Robert C

    2015-01-01

    In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2). Overall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.Graphical abstractFrom compounds and data to models: a complete model building workflow in one package.

  12. 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...

  13. Stroke subtype classification by geometrical descriptors of lesion shape.

    Directory of Open Access Journals (Sweden)

    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.

  14. Consistent Conformal Extensions of the Standard Model arXiv

    CERN Document Server

    Loebbert, Florian; Plefka, Jan

    The question of whether classically conformal modifications of the standard model are consistent with experimental obervations has recently been subject to renewed interest. The method of Gildener and Weinberg provides a natural framework for the study of the effective potential of the resulting multi-scalar standard model extensions. This approach relies on the assumption of the ordinary loop hierarchy $\\lambda_\\text{s} \\sim g^2_\\text{g}$ of scalar and gauge couplings. On the other hand, Andreassen, Frost and Schwartz recently argued that in the (single-scalar) standard model, gauge invariant results require the consistent scaling $\\lambda_\\text{s} \\sim g^4_\\text{g}$. In the present paper we contrast these two hierarchy assumptions and illustrate the differences in the phenomenological predictions of minimal conformal extensions of the standard model.

  15. Modeling self-consistent multi-class dynamic traffic flow

    Science.gov (United States)

    Cho, Hsun-Jung; Lo, Shih-Ching

    2002-09-01

    In this study, we present a systematic self-consistent multiclass multilane traffic model derived from the vehicular Boltzmann equation and the traffic dispersion model. The multilane domain is considered as a two-dimensional space and the interaction among vehicles in the domain is described by a dispersion model. The reason we consider a multilane domain as a two-dimensional space is that the driving behavior of road users may not be restricted by lanes, especially motorcyclists. The dispersion model, which is a nonlinear Poisson equation, is derived from the car-following theory and the equilibrium assumption. Under the concept that all kinds of users share the finite section, the density is distributed on a road by the dispersion model. In addition, the dynamic evolution of the traffic flow is determined by the systematic gas-kinetic model derived from the Boltzmann equation. Multiplying Boltzmann equation by the zeroth, first- and second-order moment functions, integrating both side of the equation and using chain rules, we can derive continuity, motion and variance equation, respectively. However, the second-order moment function, which is the square of the individual velocity, is employed by previous researches does not have physical meaning in traffic flow. Although the second-order expansion results in the velocity variance equation, additional terms may be generated. The velocity variance equation we propose is derived from multiplying Boltzmann equation by the individual velocity variance. It modifies the previous model and presents a new gas-kinetic traffic flow model. By coupling the gas-kinetic model and the dispersion model, a self-consistent system is presented.

  16. 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.

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

    Science.gov (United States)

    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

  18. Kompensasi Kesalahan Sensor Berbasis Descriptor dengan Performa H_inf pada Winding Machine

    Directory of Open Access Journals (Sweden)

    Hendra Antomy

    2015-12-01

    Full Text Available Kesalahan pada sensor dapat terjadi pada sistem kontrol dengan umpan balik sehingga mengakibatkan sistem mengalami penurunan stabilitas dan performa. Fault Tolerant Control (FTC adalah metode untuk mengkompensasi kesalahan pada komponen sistem, salah satunya adalah kesalahan sensor. FTC dapat disusun dengan cara mendesain estimator untuk mengestimasi besarnya kesalahan sensor yang terjadi. Kompensasi dilakukan dengan cara mengurangkan estimasi kesalahan sensor dengan keluaran sistem. Pada makalah ini, FTC untuk kesalahan sensor diterapkan pada sistem winding machine. Estimator dirancang menggunakan pendekatan sistem descriptor dan didesain memenuhi performa H_inf. Permasalahan dalam desain estimator dirumuskan dalam bentuk Linear Matrix Inequality (LMI. Untuk merancang kontroler nominal, sistem winding machine direpresentasikan sebagai model fuzzy Takagi-Sugeno (T-S. Berdasarkan model tersebut, aturan kontroler disusun menggunakan konsep Parallel Distributed Compensation (PDC dengan struktur kontrol servo tipe 1. Hasil simulasi menunjukkan bahwa kompensasi yang diberikan dapat menjaga performa dan stabilitas sistem saat terjadi kesalahan sensor. Selain itu, estimator memenuhi performa H_inf dengan L2-Gain kurang dari tingkat pelemahan yang ditentukan.

  19. Topologically Consistent Models for Efficient Big Geo-Spatio Data Distribution

    Science.gov (United States)

    Jahn, M. W.; Bradley, P. E.; Doori, M. Al; Breunig, M.

    2017-10-01

    Geo-spatio-temporal topology models are likely to become a key concept to check the consistency of 3D (spatial space) and 4D (spatial + temporal space) models for emerging GIS applications such as subsurface reservoir modelling or the simulation of energy and water supply of mega or smart cities. Furthermore, the data management for complex models consisting of big geo-spatial data is a challenge for GIS and geo-database research. General challenges, concepts, and techniques of big geo-spatial data management are presented. In this paper we introduce a sound mathematical approach for a topologically consistent geo-spatio-temporal model based on the concept of the incidence graph. We redesign DB4GeO, our service-based geo-spatio-temporal database architecture, on the way to the parallel management of massive geo-spatial data. Approaches for a new geo-spatio-temporal and object model of DB4GeO meeting the requirements of big geo-spatial data are discussed in detail. Finally, a conclusion and outlook on our future research are given on the way to support the processing of geo-analytics and -simulations in a parallel and distributed system environment.

  20. 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...

  1. Development and Trialling of a Graduated Descriptors Tool for Australian Pharmacy Students

    Science.gov (United States)

    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…

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

    Directory of Open Access Journals (Sweden)

    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

  3. Electronic forces as descriptors of nucleophilic and electrophilic regioselectivity and stereoselectivity.

    Science.gov (United States)

    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.

  4. Toward a consistent model for glass dissolution

    International Nuclear Information System (INIS)

    Strachan, D.M.; McGrail, B.P.; Bourcier, W.L.

    1994-01-01

    Understanding the process of glass dissolution in aqueous media has advanced significantly over the last 10 years through the efforts of many scientists around the world. Mathematical models describing the glass dissolution process have also advanced from simple empirical functions to structured models based on fundamental principles of physics, chemistry, and thermodynamics. Although borosilicate glass has been selected as the waste form for disposal of high-level wastes in at least 5 countries, there is no international consensus on the fundamental methodology for modeling glass dissolution that could be used in assessing the long term performance of waste glasses in a geologic repository setting. Each repository program is developing their own model and supporting experimental data. In this paper, we critically evaluate a selected set of these structured models and show that a consistent methodology for modeling glass dissolution processes is available. We also propose a strategy for a future coordinated effort to obtain the model input parameters that are needed for long-term performance assessments of glass in a geologic repository. (author) 4 figs., tabs., 75 refs

  5. Augmented Topological Descriptors of Pore Networks for Material Science.

    Science.gov (United States)

    Ushizima, D; Morozov, D; Weber, G H; Bianchi, A G C; Sethian, J A; Bethel, E W

    2012-12-01

    One potential solution to reduce the concentration of carbon dioxide in the atmosphere is the geologic storage of captured CO2 in underground rock formations, also known as carbon sequestration. There is ongoing research to guarantee that this process is both efficient and safe. We describe tools that provide measurements of media porosity, and permeability estimates, including visualization of pore structures. Existing standard algorithms make limited use of geometric information in calculating permeability of complex microstructures. This quantity is important for the analysis of biomineralization, a subsurface process that can affect physical properties of porous media. This paper introduces geometric and topological descriptors that enhance the estimation of material permeability. Our analysis framework includes the processing of experimental data, segmentation, and feature extraction and making novel use of multiscale topological analysis to quantify maximum flow through porous networks. We illustrate our results using synchrotron-based X-ray computed microtomography of glass beads during biomineralization. We also benchmark the proposed algorithms using simulated data sets modeling jammed packed bead beds of a monodispersive material.

  6. Descriptor Learning via Supervised Manifold Regularization for Multioutput Regression.

    Science.gov (United States)

    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.

  7. Adjoint-consistent formulations of slip models for coupled electroosmotic flow systems

    KAUST Repository

    Garg, Vikram V

    2014-09-27

    Background Models based on the Helmholtz `slip\\' approximation are often used for the simulation of electroosmotic flows. The objectives of this paper are to construct adjoint-consistent formulations of such models, and to develop adjoint-based numerical tools for adaptive mesh refinement and parameter sensitivity analysis. Methods We show that the direct formulation of the `slip\\' model is adjoint inconsistent, and leads to an ill-posed adjoint problem. We propose a modified formulation of the coupled `slip\\' model, which is shown to be well-posed, and therefore automatically adjoint-consistent. Results Numerical examples are presented to illustrate the computation and use of the adjoint solution in two-dimensional microfluidics problems. Conclusions An adjoint-consistent formulation for Helmholtz `slip\\' models of electroosmotic flows has been proposed. This formulation provides adjoint solutions that can be reliably used for mesh refinement and sensitivity analysis.

  8. Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

    Science.gov (United States)

    Fang, Xingang; Bagui, Sikha; Bagui, Subhash

    2017-08-01

    The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Consistency in Estimation and Model Selection of Dynamic Panel Data Models with Fixed Effects

    Directory of Open Access Journals (Sweden)

    Guangjie Li

    2015-07-01

    Full Text Available We examine the relationship between consistent parameter estimation and model selection for autoregressive panel data models with fixed effects. We find that the transformation of fixed effects proposed by Lancaster (2002 does not necessarily lead to consistent estimation of common parameters when some true exogenous regressors are excluded. We propose a data dependent way to specify the prior of the autoregressive coefficient and argue for comparing different model specifications before parameter estimation. Model selection properties of Bayes factors and Bayesian information criterion (BIC are investigated. When model uncertainty is substantial, we recommend the use of Bayesian Model Averaging to obtain point estimators with lower root mean squared errors (RMSE. We also study the implications of different levels of inclusion probabilities by simulations.

  10. A descriptor list of Silybum marianum (L. Gaertner – morphological and biological characters

    Directory of Open Access Journals (Sweden)

    Dušková, Elena

    2016-07-01

    Full Text Available Silybum marianum (L. Gaertn (Milk thistle is an important medicinal plant which fruits are used for treatment of various liver diseases. In an effort to utilize the genetic potential of cultivated plants in the best way, the breeding of new high-performance cultivars is underway all over the world. Genetic improvement in Silybum can only be, as with all other plants, achieved through a clear understanding of the plant´s behaviour and the amount of variability presented in wild populations. Surprisingly no descriptor list has been compiled up to now, which would permit an objective and easily repeatable description an evaluation of the different Silybum genotypes. The first part of such a descriptor list, which is intended mainly for evaluation of genotypes perspective for fruit production, is presented here and it contains both the morphological and biological characters.

  11. Self-consistent mean-field models for nuclear structure

    International Nuclear Information System (INIS)

    Bender, Michael; Heenen, Paul-Henri; Reinhard, Paul-Gerhard

    2003-01-01

    The authors review the present status of self-consistent mean-field (SCMF) models for describing nuclear structure and low-energy dynamics. These models are presented as effective energy-density functionals. The three most widely used variants of SCMF's based on a Skyrme energy functional, a Gogny force, and a relativistic mean-field Lagrangian are considered side by side. The crucial role of the treatment of pairing correlations is pointed out in each case. The authors discuss other related nuclear structure models and present several extensions beyond the mean-field model which are currently used. Phenomenological adjustment of the model parameters is discussed in detail. The performance quality of the SCMF model is demonstrated for a broad range of typical applications

  12. Thermodynamically Consistent Algorithms for the Solution of Phase-Field Models

    KAUST Repository

    Vignal, Philippe

    2016-01-01

    of thermodynamically consistent algorithms for time integration of phase-field models. The first part of this thesis focuses on an energy-stable numerical strategy developed for the phase-field crystal equation. This model was put forward to model microstructure

  13. Prostate malignancy grading using gland-related shape descriptors

    Science.gov (United States)

    Braumann, Ulf-Dietrich; Scheibe, Patrick; Loeffler, Markus; Kristiansen, Glen; Wernert, Nicolas

    2014-03-01

    A proof-of-principle study was accomplished assessing the descriptive potential of two simple geometric measures (shape descriptors) applied to sets of segmented glands within images of 125 prostate cancer tissue sections. Respective measures addressing glandular shapes were (i) inverse solidity and (ii) inverse compactness. Using a classifier based on logistic regression, Gleason grades 3 and 4/5 could be differentiated with an accuracy of approx. 95%. Results suggest not only good discriminatory properties, but also robustness against gland segmentation variations. False classifications in part were caused by inadvertent Gleason grade assignments, as a-posteriori re-inspections had turned out.

  14. Aggregated wind power plant models consisting of IEC wind turbine models

    DEFF Research Database (Denmark)

    Altin, Müfit; Göksu, Ömer; Hansen, Anca Daniela

    2015-01-01

    The common practice regarding the modelling of large generation components has been to make use of models representing the performance of the individual components with a required level of accuracy and details. Owing to the rapid increase of wind power plants comprising large number of wind...... turbines, parameters and models to represent each individual wind turbine in detail makes it necessary to develop aggregated wind power plant models considering the simulation time for power system stability studies. In this paper, aggregated wind power plant models consisting of the IEC 61400-27 variable...... speed wind turbine models (type 3 and type 4) with a power plant controller is presented. The performance of the detailed benchmark wind power plant model and the aggregated model are compared by means of simulations for the specified test cases. Consequently, the results are summarized and discussed...

  15. Reduced density gradient as a novel approach for estimating QSAR descriptors, and its application to 1, 4-dihydropyridine derivatives with potential antihypertensive effects.

    Science.gov (United States)

    Jardínez, Christiaan; Vela, Alberto; Cruz-Borbolla, Julián; Alvarez-Mendez, Rodrigo J; Alvarado-Rodríguez, José G

    2016-12-01

    The relationship between the chemical structure and biological activity (log IC 50 ) of 40 derivatives of 1,4-dihydropyridines (DHPs) was studied using density functional theory (DFT) and multiple linear regression analysis methods. With the aim of improving the quantitative structure-activity relationship (QSAR) model, the reduced density gradient s( r) of the optimized equilibrium geometries was used as a descriptor to include weak non-covalent interactions. The QSAR model highlights the correlation between the log IC 50 with highest molecular orbital energy (E HOMO ), molecular volume (V), partition coefficient (log P), non-covalent interactions NCI(H4-G) and the dual descriptor [Δf(r)]. The model yielded values of R 2 =79.57 and Q 2 =69.67 that were validated with the next four internal analytical validations DK=0.076, DQ=-0.006, R P =0.056, and R N =0.000, and the external validation Q 2 boot =64.26. The QSAR model found can be used to estimate biological activity with high reliability in new compounds based on a DHP series. Graphical abstract The good correlation between the log IC 50 with the NCI (H4-G) estimated by the reduced density gradient approach of the DHP derivatives.

  16. Quantitative structure-activity relationships of selective antagonists of glucagon receptor using QuaSAR descriptors.

    Science.gov (United States)

    Manoj Kumar, Palanivelu; Karthikeyan, Chandrabose; Hari Narayana Moorthy, Narayana Subbiah; Trivedi, Piyush

    2006-11-01

    In the present paper, quantitative structure activity relationship (QSAR) approach was applied to understand the affinity and selectivity of a novel series of triaryl imidazole derivatives towards glucagon receptor. Statistically significant and highly predictive QSARs were derived for glucagon receptor inhibition by triaryl imidazoles using QuaSAR descriptors of molecular operating environment (MOE) employing computer-assisted multiple regression procedure. The generated QSAR models revealed that factors related to hydrophobicity, molecular shape and geometry predominantly influences glucagon receptor binding affinity of the triaryl imidazoles indicating the relevance of shape specific steric interactions between the molecule and the receptor. Further, QSAR models formulated for selective inhibition of glucagon receptor over p38 mitogen activated protein (MAP) kinase of the compounds in the series highlights that the same structural features, which influence the glucagon receptor affinity, also contribute to their selective inhibition.

  17. Estimating long-term volatility parameters for market-consistent models

    African Journals Online (AJOL)

    Contemporary actuarial and accounting practices (APN 110 in the South African context) require the use of market-consistent models for the valuation of embedded investment derivatives. These models have to be calibrated with accurate and up-to-date market data. Arguably, the most important variable in the valuation of ...

  18. A novel 3D shape descriptor for automatic retrieval of anatomical structures from medical images

    Science.gov (United States)

    Nunes, Fátima L. S.; Bergamasco, Leila C. C.; Delmondes, Pedro H.; Valverde, Miguel A. G.; Jackowski, Marcel P.

    2017-03-01

    Content-based image retrieval (CBIR) aims at retrieving from a database objects that are similar to an object provided by a query, by taking into consideration a set of extracted features. While CBIR has been widely applied in the two-dimensional image domain, the retrieval of3D objects from medical image datasets using CBIR remains to be explored. In this context, the development of descriptors that can capture information specific to organs or structures is desirable. In this work, we focus on the retrieval of two anatomical structures commonly imaged by Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) techniques, the left ventricle of the heart and blood vessels. Towards this aim, we developed the Area-Distance Local Descriptor (ADLD), a novel 3D local shape descriptor that employs mesh geometry information, namely facet area and distance from centroid to surface, to identify shape changes. Because ADLD only considers surface meshes extracted from volumetric medical images, it substantially diminishes the amount of data to be analyzed. A 90% precision rate was obtained when retrieving both convex (left ventricle) and non-convex structures (blood vessels), allowing for detection of abnormalities associated with changes in shape. Thus, ADLD has the potential to aid in the diagnosis of a wide range of vascular and cardiac diseases.

  19. Airborne sound insulation descriptors in the Nordic building regulations - Overview special rules and benefits of changing descriptors

    DEFF Research Database (Denmark)

    Helimäki, Heikki; Rasmussen, Birgit

    2010-01-01

    All Nordic countries have sound insulation requirements specified in the building regulations or in sound classification schemes, Class C, referred to in the regulations and published as national standards, which all originate from a common Nordic INSTA-B proposal from the 90’s, thus having a lot...... insulation requirements and is related to an equivalent paper about impact sound insulation requirements. The papers also describe the major benefits of reducing the number of special rules and of changing descriptors to those which best support protection of the residents and development of the building....... These national rules are not easy to find, unless all details of standards and other documents are known and studied carefully, and they cause problems since the building industry is not national anymore. This paper gives an overview of special national rules in the Nordic countries regarding airborne sound...

  20. Discrete-Time Sliding-Mode Control of Uncertain Systems with Time-Varying Delays via Descriptor Approach

    Directory of Open Access Journals (Sweden)

    Maode Yan

    2008-01-01

    Full Text Available This paper considers the problem of robust discrete-time sliding-mode control (DT-SMC design for a class of uncertain linear systems with time-varying delays. By applying a descriptor model transformation and Moon's inequality for bounding cross terms, a delay-dependent sufficient condition for the existence of stable sliding surface is given in terms of linear matrix inequalities (LMIs. Based on this existence condition, the synthesized sliding mode controller can guarantee the sliding-mode reaching condition of the specified discrete-time sliding surface for all admissible uncertainties and time-varying delays. An illustrative example verifies the effectiveness of the proposed method.

  1. A semi-nonparametric mixture model for selecting functionally consistent proteins.

    Science.gov (United States)

    Yu, Lianbo; Doerge, Rw

    2010-09-28

    High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

  2. OPERA models for predicting physicochemical properties and environmental fate endpoints.

    Science.gov (United States)

    Mansouri, Kamel; Grulke, Chris M; Judson, Richard S; Williams, Antony J

    2018-03-08

    The collection of chemical structure information and associated experimental data for quantitative structure-activity/property relationship (QSAR/QSPR) modeling is facilitated by an increasing number of public databases containing large amounts of useful data. However, the performance of QSAR models highly depends on the quality of the data and modeling methodology used. This study aims to develop robust QSAR/QSPR models for chemical properties of environmental interest that can be used for regulatory purposes. This study primarily uses data from the publicly available PHYSPROP database consisting of a set of 13 common physicochemical and environmental fate properties. These datasets have undergone extensive curation using an automated workflow to select only high-quality data, and the chemical structures were standardized prior to calculation of the molecular descriptors. The modeling procedure was developed based on the five Organization for Economic Cooperation and Development (OECD) principles for QSAR models. A weighted k-nearest neighbor approach was adopted using a minimum number of required descriptors calculated using PaDEL, an open-source software. The genetic algorithms selected only the most pertinent and mechanistically interpretable descriptors (2-15, with an average of 11 descriptors). The sizes of the modeled datasets varied from 150 chemicals for biodegradability half-life to 14,050 chemicals for logP, with an average of 3222 chemicals across all endpoints. The optimal models were built on randomly selected training sets (75%) and validated using fivefold cross-validation (CV) and test sets (25%). The CV Q 2 of the models varied from 0.72 to 0.95, with an average of 0.86 and an R 2 test value from 0.71 to 0.96, with an average of 0.82. Modeling and performance details are described in QSAR model reporting format and were validated by the European Commission's Joint Research Center to be OECD compliant. All models are freely available as an open

  3. A Hybrid FPGA/Coarse Parallel Processing Architecture for Multi-modal Visual Feature Descriptors

    DEFF Research Database (Denmark)

    Jensen, Lars Baunegaard With; Kjær-Nielsen, Anders; Alonso, Javier Díaz

    2008-01-01

    This paper describes the hybrid architecture developed for speeding up the processing of so-called multi-modal visual primitives which are sparse image descriptors extracted along contours. In the system, the first stages of visual processing are implemented on FPGAs due to their highly parallel...

  4. Automated Clustering Analysis of Immunoglobulin Sequences in Chronic Lymphocytic Leukemia Based on 3D Structural Descriptors

    DEFF Research Database (Denmark)

    Marcatili, Paolo; Mochament, Konstantinos; Agathangelidis, Andreas

    2016-01-01

    study, we used the structure prediction tools PIGS and I-TASSER for creating the 3D models and the TM-align algorithm to superpose them. The innovation of the current methodology resides in the usage of methods adapted from 3D content-based search methodologies to determine the local structural...... determine it are extremely laborious and demanding. Hence, the ability to gain insight into the structure of Igs at large relies on the availability of tools and algorithms for producing accurate Ig structural models based on their primary sequence alone. These models can then be used to determine...... to achieve an optimal solution to this task yet their results were hindered mainly due to the lack of efficient clustering methods based on the similarity of 3D structure descriptors. Here, we present a novel workflow for robust Ig 3D modeling and automated clustering. We validated our protocol in chronic...

  5. Using machine learning and quantum chemistry descriptors to predict the toxicity of ionic liquids.

    Science.gov (United States)

    Cao, Lingdi; Zhu, Peng; Zhao, Yongsheng; Zhao, Jihong

    2018-06-15

    Large-scale application of ionic liquids (ILs) hinges on the advancement of designable and eco-friendly nature. Research of the potential toxicity of ILs towards different organisms and trophic levels is insufficient. Quantitative structure-activity relationships (QSAR) model is applied to evaluate the toxicity of ILs towards the leukemia rat cell line (ICP-81). The structures of 57 cations and 21 anions were optimized by quantum chemistry. The electrostatic potential surface area (S EP ) and charge distribution area (S σ-profile ) descriptors are calculated and used to predict the toxicity of ILs. The performance and predictive aptitude of extreme learning machine (ELM) model are analyzed and compared with those of multiple linear regression (MLR) and support vector machine (SVM) models. The highest R 2 and the lowest AARD% and RMSE of the training set, test set and total set for the ELM are observed, which validates the superior performance of the ELM than that of obtained by the MLR and SVM. The applicability domain of the model is assessed by the Williams plot. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

    Directory of Open Access Journals (Sweden)

    Carlos E. Galván-Tejada

    2017-02-01

    Full Text Available Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

  7. Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis.

    Science.gov (United States)

    Galván-Tejada, Carlos E; Zanella-Calzada, Laura A; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L

    2017-02-14

    Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

  8. Combination of image descriptors for the exploration of cultural photographic collections

    Science.gov (United States)

    Bhowmik, Neelanjan; Gouet-Brunet, Valérie; Bloch, Gabriel; Besson, Sylvain

    2017-01-01

    The rapid growth of image digitization and collections in recent years makes it challenging and burdensome to organize, categorize, and retrieve similar images from voluminous collections. Content-based image retrieval (CBIR) is immensely convenient in this context. A considerable number of local feature detectors and descriptors are present in the literature of CBIR. We propose a model to anticipate the best feature combinations for image retrieval-related applications. Several spatial complementarity criteria of local feature detectors are analyzed and then engaged in a regression framework to find the optimal combination of detectors for a given dataset and are better adapted for each given image; the proposed model is also useful to optimally fix some other parameters, such as the k in k-nearest neighbor retrieval. Three public datasets of various contents and sizes are employed to evaluate the proposal, which is legitimized by improving the quality of retrieval notably facing classical approaches. Finally, the proposed image search engine is applied to the cultural photographic collections of a French museum, where it demonstrates its added value for the exploration and promotion of these contents at different levels from their archiving up to their exhibition in or ex situ.

  9. Consistency checks in beam emission modeling for neutral beam injectors

    International Nuclear Information System (INIS)

    Punyapu, Bharathi; Vattipalle, Prahlad; Sharma, Sanjeev Kumar; Baruah, Ujjwal Kumar; Crowley, Brendan

    2015-01-01

    In positive neutral beam systems, the beam parameters such as ion species fractions, power fractions and beam divergence are routinely measured using Doppler shifted beam emission spectrum. The accuracy with which these parameters are estimated depend on the accuracy of the atomic modeling involved in these estimations. In this work, an effective procedure to check the consistency of the beam emission modeling in neutral beam injectors is proposed. As a first consistency check, at a constant beam voltage and current, the intensity of the beam emission spectrum is measured by varying the pressure in the neutralizer. Then, the scaling of measured intensity of un-shifted (target) and Doppler shifted intensities (projectile) of the beam emission spectrum at these pressure values are studied. If the un-shifted component scales with pressure, then the intensity of this component will be used as a second consistency check on the beam emission modeling. As a further check, the modeled beam fractions and emission cross sections of projectile and target are used to predict the intensity of the un-shifted component and then compared with the value of measured target intensity. An agreement between the predicted and measured target intensities provide the degree of discrepancy in the beam emission modeling. In order to test this methodology, a systematic analysis of Doppler shift spectroscopy data obtained on the JET neutral beam test stand data was carried out

  10. Learned Compact Local Feature Descriptor for Tls-Based Geodetic Monitoring of Natural Outdoor Scenes

    Science.gov (United States)

    Gojcic, Z.; Zhou, C.; Wieser, A.

    2018-05-01

    The advantages of terrestrial laser scanning (TLS) for geodetic monitoring of man-made and natural objects are not yet fully exploited. Herein we address one of the open challenges by proposing feature-based methods for identification of corresponding points in point clouds of two or more epochs. We propose a learned compact feature descriptor tailored for point clouds of natural outdoor scenes obtained using TLS. We evaluate our method both on a benchmark data set and on a specially acquired outdoor dataset resembling a simplified monitoring scenario where we successfully estimate 3D displacement vectors of a rock that has been displaced between the scans. We show that the proposed descriptor has the capacity to generalize to unseen data and achieves state-of-the-art performance while being time efficient at the matching step due the low dimension.

  11. Computational prediction of the pKas of small peptides through Conceptual DFT descriptors

    Science.gov (United States)

    Frau, Juan; Hernández-Haro, Noemí; Glossman-Mitnik, Daniel

    2017-03-01

    The experimental pKa of a group of simple amines have been plotted against several Conceptual DFT descriptors calculated by means of different density functionals, basis sets and solvation schemes. It was found that the best fits are those that relate the pKa of the amines with the global hardness η through the MN12SX density functional in connection with the Def2TZVP basis set and the SMD solvation model, using water as a solvent. The parameterized equation resulting from the linear regression analysis has then been used for the prediction of the pKa of small peptides of interest in the study of diabetes and Alzheimer disease. The accuracy of the results is relatively good, with a MAD of 0.36 units of pKa.

  12. Self-consistent modeling of amorphous silicon devices

    International Nuclear Information System (INIS)

    Hack, M.

    1987-01-01

    The authors developed a computer model to describe the steady-state behaviour of a range of amorphous silicon devices. It is based on the complete set of transport equations and takes into account the important role played by the continuous distribution of localized states in the mobility gap of amorphous silicon. Using one set of parameters they have been able to self-consistently simulate the current-voltage characteristics of p-i-n (or n-i-p) solar cells under illumination, the dark behaviour of field-effect transistors, p-i-n diodes and n-i-n diodes in both the ohmic and space charge limited regimes. This model also describes the steady-state photoconductivity of amorphous silicon, in particular, its dependence on temperature, doping and illumination intensity

  13. Comparative study of dose descriptor in pediatric computed tomography exams

    International Nuclear Information System (INIS)

    Finatto, Jerusa Dalbosco; Silva, Ana Maria Marques da; Froner, Ana Paula Pastre; Pimentel, Juliana

    2014-01-01

    This work aims to investigate the dose descriptor, volumetric Computed Tomography Dose Index (CTDI), a pediatric patients sample undergoing to skull CT, comparing the results with the diagnostic reference levels of the literature. Were collected volumetric CTDI values of all skull CT exams performed retrospectively in children of 0-10 years of age in a period of 12 months in a large hospital size. Patients, in a total of 103, were divided into four groups, where the criterion of separation used was age, trying to use the same division used in international references dose descriptors. In all acquisitions we used the pediatric protocol and the Automatic Exposure Control (AEC) available on the equipment. The CDTI values, with and without the use of AEC for pediatric studies, were compared. There was a reduction of approximately 100% in the absorbed dose value due to the use of the AEC. From the data collected and analyzed in this work, it is concluded that the use of dose reduction systems is relevant, such as the Care Dose, to maintain volumetric CTDI values within the reference levels. Also it is important the observation of range of children age to the appropriate choice of parameters used in the test protocol. The values obtained are according to the diagnostic reference levels from the literature

  14. Breast density pattern characterization by histogram features and texture descriptors

    OpenAIRE

    Carneiro,Pedro Cunha; Franco,Marcelo Lemos Nunes; Thomaz,Ricardo de Lima; Patrocinio,Ana Claudia

    2017-01-01

    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 mammo...

  15. Impact sound insulation descriptors in the Nordic building regulations – Overview special rules and benefits of changing descriptors

    DEFF Research Database (Denmark)

    Hagberg, Klas; Rasmussen, Birgit

    2010-01-01

    All Nordic countries have sound insulation requirements specified in the building regulations or in sound classification schemes, Class C, referred to in the regulations and published as national standards, which all originate from a common Nordic INSTA-B proposal from the 90’s, thus having a lot...... insulation requirements and is related to an equivalent paper about airborne sound insulation requirements. The papers also describe the major benefits of reducing the number of special rules and of changing descriptors to those which best support protection of the residents and development of the building....... These national rules are not easy to find, unless all details of standards and other documents are known and studied carefully, and they cause problems since the building industry is not national anymore. This paper gives an overview of special national rules in the Nordic countries regarding impact sound...

  16. Molecular Descriptors Family on Vertex Cutting: Relationships between Acelazolamide Structures and their Inhibitory Activity

    Directory of Open Access Journals (Sweden)

    Sorana D. BOLBOACĂ

    2009-12-01

    Full Text Available Aim: To investigate the relationship between the structural information of acetazolamides and their inhibitory activity on carbonic anhydrase II. Material and Method: A sample of previously reported acetazolamides was studied. A pool of descriptors was calculated based on matrix representation and vertex cut in order to be included in the multiple linear regression analysis. The best performing model in terms of goodness-of-fit was analysed in order to assess its validity and reliability. The model was compared with previously reported models using a series of information and prediction criteria besides the Steiger’s Z test. Results: A model with a 99.77% determination coefficient proved to be the best performing model. The obtained model proved to have a less than 5% average of the absolute difference between the observed and the estimated inhibitory activity. The information and prediction criteria showed that the obtained model was better than the previously reported models. This conclusion is also sustained by the results of Steiger’s Z test (7.78; p = 3.66·10-15. Conclusion: The inhibitory activity on carbonic anhydrase II of acetazolamides proved to be of geometric and topologic nature and depended on the compounds’ melting point, relative atomic mass and atomic electronegativity.

  17. Symbol recognition via statistical integration of pixel-level constraint histograms: a new descriptor.

    Science.gov (United States)

    Yang, Su

    2005-02-01

    A new descriptor for symbol recognition is proposed. 1) A histogram is constructed for every pixel to figure out the distribution of the constraints among the other pixels. 2) All the histograms are statistically integrated to form a feature vector with fixed dimension. The robustness and invariance were experimentally confirmed.

  18. Consistency Across Standards or Standards in a New Business Model

    Science.gov (United States)

    Russo, Dane M.

    2010-01-01

    Presentation topics include: standards in a changing business model, the new National Space Policy is driving change, a new paradigm for human spaceflight, consistency across standards, the purpose of standards, danger of over-prescriptive standards, a balance is needed (between prescriptive and general standards), enabling versus inhibiting, characteristics of success-oriented standards, characteristics of success-oriented standards, and conclusions. Additional slides include NASA Procedural Requirements 8705.2B identifies human rating standards and requirements, draft health and medical standards for human rating, what's been done, government oversight models, examples of consistency from anthropometry, examples of inconsistency from air quality and appendices of government and non-governmental human factors standards.

  19. Dissecting molecular descriptors into atomic contributions in density functional reactivity theory

    International Nuclear Information System (INIS)

    Rong, Chunying; Lu, Tian; Liu, Shubin

    2014-01-01

    Density functional reactivity theory (DFRT) employs the electron density of a molecule and its related quantities such as gradient and Laplacian to describe its structure and reactivity properties. Proper descriptions at both molecular (global) and atomic (local) levels are equally important and illuminating. In this work, we make use of Bader's zero-flux partition scheme and consider atomic contributions for a few global reactivity descriptors in DFRT, including the density-based quantification of steric effect and related indices. Earlier, we proved that these quantities are intrinsically correlated for atomic and molecular systems [S. B. Liu, J. Chem. Phys. 126, 191107 (2007); ibid. 126, 244103 (2007)]. In this work, a new basin-based integration algorithm has been implemented, whose reliability and effectiveness have been extensively examined. We also investigated a list of simple hydrocarbon systems and different scenarios of bonding processes, including stretching, bending, and rotating. Interesting changing patterns for the atomic and molecular values of these quantities have been revealed for different systems. This work not only confirms the strong correlation between these global reactivity descriptors for molecular systems, as theoretically proven earlier by us, it also provides new and unexpected changing patterns for their atomic values, which can be employed to understand the origin and nature of chemical phenomena

  20. Dissecting molecular descriptors into atomic contributions in density functional reactivity theory

    Energy Technology Data Exchange (ETDEWEB)

    Rong, Chunying [Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China) and Key Laboratory of Resource Fine-Processing and Advanced Materials of Hunan Province, College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan 410081 (China); Lu, Tian [School of Chemical and Biological Engineering, University of Science and Technology Beijing, Beijing (China); Liu, Shubin, E-mail: shubin@email.unc.edu [Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China) and Key Laboratory of Resource Fine-Processing and Advanced Materials of Hunan Province, College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan 410081 (China); Research Computing Center, University of North Carolina, Chapel Hill, North Carolina 27599-3420 (United States)

    2014-01-14

    Density functional reactivity theory (DFRT) employs the electron density of a molecule and its related quantities such as gradient and Laplacian to describe its structure and reactivity properties. Proper descriptions at both molecular (global) and atomic (local) levels are equally important and illuminating. In this work, we make use of Bader's zero-flux partition scheme and consider atomic contributions for a few global reactivity descriptors in DFRT, including the density-based quantification of steric effect and related indices. Earlier, we proved that these quantities are intrinsically correlated for atomic and molecular systems [S. B. Liu, J. Chem. Phys. 126, 191107 (2007); ibid. 126, 244103 (2007)]. In this work, a new basin-based integration algorithm has been implemented, whose reliability and effectiveness have been extensively examined. We also investigated a list of simple hydrocarbon systems and different scenarios of bonding processes, including stretching, bending, and rotating. Interesting changing patterns for the atomic and molecular values of these quantities have been revealed for different systems. This work not only confirms the strong correlation between these global reactivity descriptors for molecular systems, as theoretically proven earlier by us, it also provides new and unexpected changing patterns for their atomic values, which can be employed to understand the origin and nature of chemical phenomena.

  1. Drug-like and non drug-like pattern classification based on simple topology descriptor using hybrid neural network.

    Science.gov (United States)

    Wan-Mamat, Wan Mohd Fahmi; Isa, Nor Ashidi Mat; Wahab, Habibah A; Wan-Mamat, Wan Mohd Fairuz

    2009-01-01

    An intelligent prediction system has been developed to discriminate drug-like and non drug-like molecules pattern. The system is constructed by using the application of advanced version of standard multilayer perceptron (MLP) neural network called Hybrid Multilayer Perceptron (HMLP) neural network and trained using Modified Recursive Prediction Error (MRPE) training algorithm. In this work, a well understood and easy excess Rule of Five + Veber filter properties are selected as the topological descriptor. The main idea behind the selection of this simple descriptor is to assure that the system could be used widely, beneficial and more advantageous regardless at all user level within a drug discovery organization.

  2. Prediction of solid oxide fuel cell cathode activity with first-principles descriptors

    DEFF Research Database (Denmark)

    Lee, Yueh-Lin; Kleis, Jesper; Rossmeisl, Jan

    2011-01-01

    In this work we demonstrate that the experimentally measured area specific resistance and oxygen surface exchange of solid oxide fuel cell cathode perovskites are strongly correlated with the first-principles calculated oxygen p-band center and vacancy formation energy. These quantities...... are therefore descriptors of catalytic activity that can be used in the first-principles design of new SOFC cathodes....

  3. Detection and quantification of flow consistency in business process models.

    Science.gov (United States)

    Burattin, Andrea; Bernstein, Vered; Neurauter, Manuel; Soffer, Pnina; Weber, Barbara

    2018-01-01

    Business process models abstract complex business processes by representing them as graphical models. Their layout, as determined by the modeler, may have an effect when these models are used. However, this effect is currently not fully understood. In order to systematically study this effect, a basic set of measurable key visual features is proposed, depicting the layout properties that are meaningful to the human user. The aim of this research is thus twofold: first, to empirically identify key visual features of business process models which are perceived as meaningful to the user and second, to show how such features can be quantified into computational metrics, which are applicable to business process models. We focus on one particular feature, consistency of flow direction, and show the challenges that arise when transforming it into a precise metric. We propose three different metrics addressing these challenges, each following a different view of flow consistency. We then report the results of an empirical evaluation, which indicates which metric is more effective in predicting the human perception of this feature. Moreover, two other automatic evaluations describing the performance and the computational capabilities of our metrics are reported as well.

  4. Consistency of the tachyon warm inflationary universe models

    International Nuclear Information System (INIS)

    Zhang, Xiao-Min; Zhu, Jian-Yang

    2014-01-01

    This study concerns the consistency of the tachyon warm inflationary models. A linear stability analysis is performed to find the slow-roll conditions, characterized by the potential slow-roll (PSR) parameters, for the existence of a tachyon warm inflationary attractor in the system. The PSR parameters in the tachyon warm inflationary models are redefined. Two cases, an exponential potential and an inverse power-law potential, are studied, when the dissipative coefficient Γ = Γ 0 and Γ = Γ(φ), respectively. A crucial condition is obtained for a tachyon warm inflationary model characterized by the Hubble slow-roll (HSR) parameter ε H , and the condition is extendable to some other inflationary models as well. A proper number of e-folds is obtained in both cases of the tachyon warm inflation, in contrast to existing works. It is also found that a constant dissipative coefficient (Γ = Γ 0 ) is usually not a suitable assumption for a warm inflationary model

  5. Consistency, Verification, and Validation of Turbulence Models for Reynolds-Averaged Navier-Stokes Applications

    Science.gov (United States)

    Rumsey, Christopher L.

    2009-01-01

    In current practice, it is often difficult to draw firm conclusions about turbulence model accuracy when performing multi-code CFD studies ostensibly using the same model because of inconsistencies in model formulation or implementation in different codes. This paper describes an effort to improve the consistency, verification, and validation of turbulence models within the aerospace community through a website database of verification and validation cases. Some of the variants of two widely-used turbulence models are described, and two independent computer codes (one structured and one unstructured) are used in conjunction with two specific versions of these models to demonstrate consistency with grid refinement for several representative problems. Naming conventions, implementation consistency, and thorough grid resolution studies are key factors necessary for success.

  6. Delay-dependent asymptotic stability of mobile ad-hoc networks: A descriptor system approach

    International Nuclear Information System (INIS)

    Yang Juan; Yang Dan; Zhang Xiao-Hong; Huang Bin; Luo Jian-Lu

    2014-01-01

    In order to analyze the capacity stability of the time-varying-propagation and delay-dependent of mobile ad-hoc networks (MANETs), in this paper, a novel approach is proposed to explore the capacity asymptotic stability for the delay-dependent of MANETs based on non-cooperative game theory, where the delay-dependent conditions are explicitly taken into consideration. This approach is based on the Lyapunov—Krasovskii stability theory for functional differential equations and the linear matrix inequality (LMI) technique. A corresponding Lyapunov—Krasovskii functional is introduced for the stability analysis of this system with use of the descriptor and “neutral-type” model transformation without producing any additional dynamics. The delay-dependent stability criteria are derived for this system. Conditions are given in terms of linear matrix inequalities, and for the first time referred to neutral systems with the time-varying propagation and delay-dependent stability for capacity analysis of MANETs. The proposed criteria are less conservative since they are based on an equivalent model transformation. Furthermore, we also provide an effective and efficient iterative algorithm to solve the constrained stability control model. Simulation experiments have verified the effectiveness and efficiency of our algorithm. (general)

  7. Simple Ligand–Receptor Interaction Descriptor (SILIRID for alignment-free binding site comparison

    Directory of Open Access Journals (Sweden)

    Vladimir Chupakhin

    2014-06-01

    Full Text Available We describe SILIRID (Simple Ligand–Receptor Interaction Descriptor, a novel fixed size descriptor characterizing protein–ligand interactions. SILIRID can be obtained from the binary interaction fingerprints (IFPs by summing up the bits corresponding to identical amino acids. This results in a vector of 168 integer numbers corresponding to the product of the number of entries (20 amino acids and one cofactor and 8 interaction types per amino acid (hydrophobic, aromatic face to face, aromatic edge to face, H-bond donated by the protein, H-bond donated by the ligand, ionic bond with protein cation and protein anion, and interaction with metal ion. Efficiency of SILIRID to distinguish different protein binding sites has been examined in similarity search in sc-PDB database, a druggable portion of the Protein Data Bank, using various protein–ligand complexes as queries. The performance of retrieval of structurally and evolutionary related classes of proteins was comparable to that of state-of-the-art approaches (ROC AUC ≈ 0.91. SILIRID can efficiently be used to visualize chemogenomic space covered by sc-PDB using Generative Topographic Mapping (GTM: sc-PDB SILIRID data form clusters corresponding to different protein types.

  8. Simple Ligand-Receptor Interaction Descriptor (SILIRID) for alignment-free binding site comparison.

    Science.gov (United States)

    Chupakhin, Vladimir; Marcou, Gilles; Gaspar, Helena; Varnek, Alexandre

    2014-06-01

    We describe SILIRID (Simple Ligand-Receptor Interaction Descriptor), a novel fixed size descriptor characterizing protein-ligand interactions. SILIRID can be obtained from the binary interaction fingerprints (IFPs) by summing up the bits corresponding to identical amino acids. This results in a vector of 168 integer numbers corresponding to the product of the number of entries (20 amino acids and one cofactor) and 8 interaction types per amino acid (hydrophobic, aromatic face to face, aromatic edge to face, H-bond donated by the protein, H-bond donated by the ligand, ionic bond with protein cation and protein anion, and interaction with metal ion). Efficiency of SILIRID to distinguish different protein binding sites has been examined in similarity search in sc-PDB database, a druggable portion of the Protein Data Bank, using various protein-ligand complexes as queries. The performance of retrieval of structurally and evolutionary related classes of proteins was comparable to that of state-of-the-art approaches (ROC AUC ≈ 0.91). SILIRID can efficiently be used to visualize chemogenomic space covered by sc-PDB using Generative Topographic Mapping (GTM): sc-PDB SILIRID data form clusters corresponding to different protein types.

  9. Phenotypic characterization of glioblastoma identified through shape descriptors

    Science.gov (United States)

    Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

    2016-03-01

    This paper proposes quantitatively describing the shape of glioblastoma (GBM) tissue phenotypes as a set of shape features derived from segmentations, for the purposes of discriminating between GBM phenotypes and monitoring tumor progression. GBM patients were identified from the Cancer Genome Atlas, and quantitative MR imaging data were obtained from the Cancer Imaging Archive. Three GBM tissue phenotypes are considered including necrosis, active tumor and edema/invasion. Volumetric tissue segmentations are obtained from registered T1˗weighted (T1˗WI) postcontrast and fluid-attenuated inversion recovery (FLAIR) MRI modalities. Shape features are computed from respective tissue phenotype segmentations, and a Kruskal-Wallis test was employed to select features capable of classification with a significance level of p < 0.05. Several classifier models are employed to distinguish phenotypes, where a leave-one-out cross-validation was performed. Eight features were found statistically significant for classifying GBM phenotypes with p <0.05, orientation is uninformative. Quantitative evaluations show the SVM results in the highest classification accuracy of 87.50%, sensitivity of 94.59% and specificity of 92.77%. In summary, the shape descriptors proposed in this work show high performance in predicting GBM tissue phenotypes. They are thus closely linked to morphological characteristics of GBM phenotypes and could potentially be used in a computer assisted labeling system.

  10. Self-consistent assessment of Englert-Schwinger model on atomic properties

    Science.gov (United States)

    Lehtomäki, Jouko; Lopez-Acevedo, Olga

    2017-12-01

    Our manuscript investigates a self-consistent solution of the statistical atom model proposed by Berthold-Georg Englert and Julian Schwinger (the ES model) and benchmarks it against atomic Kohn-Sham and two orbital-free models of the Thomas-Fermi-Dirac (TFD)-λvW family. Results show that the ES model generally offers the same accuracy as the well-known TFD-1/5 vW model; however, the ES model corrects the failure in the Pauli potential near-nucleus region. We also point to the inability of describing low-Z atoms as the foremost concern in improving the present model.

  11. Full self-consistency versus quasiparticle self-consistency in diagrammatic approaches: exactly solvable two-site Hubbard model.

    Science.gov (United States)

    Kutepov, A L

    2015-08-12

    Self-consistent solutions of Hedin's equations (HE) for the two-site Hubbard model (HM) have been studied. They have been found for three-point vertices of increasing complexity (Γ = 1 (GW approximation), Γ1 from the first-order perturbation theory, and the exact vertex Γ(E)). Comparison is made between the cases when an additional quasiparticle (QP) approximation for Green's functions is applied during the self-consistent iterative solving of HE and when QP approximation is not applied. The results obtained with the exact vertex are directly related to the present open question-which approximation is more advantageous for future implementations, GW + DMFT or QPGW + DMFT. It is shown that in a regime of strong correlations only the originally proposed GW + DMFT scheme is able to provide reliable results. Vertex corrections based on perturbation theory (PT) systematically improve the GW results when full self-consistency is applied. The application of QP self-consistency combined with PT vertex corrections shows similar problems to the case when the exact vertex is applied combined with QP sc. An analysis of Ward Identity violation is performed for all studied in this work's approximations and its relation to the general accuracy of the schemes used is provided.

  12. Electrodermal responses to words in chronic low back pain patients: a comparison between pain descriptors, other emotional words, and neutral words.

    Science.gov (United States)

    Bonnet, Adeline; Naveteur, Janick

    2006-10-01

    This study examines the electrodermal reactivity of chronic sufferers to emotional words. The hypothesis that patients are over-sensitive to pain descriptors is tested. Electrodermal activity was recorded in 12 chronic low back pain patients and 12 healthy controls during passive viewing of words on a video monitor. These words were pain descriptors, other emotional words, and neutral words, in a pseudo-randomized order. A jingle was associated with the word occurrence. In chronic low back pain patients, skin conductance responses (SCRs) induced by pain descriptors or other emotional words were larger than SCRs induced by neutral words but they did not differ from each other. Patients presented SCRs, which were both larger and faster than those of controls, including following neutral words. There was no significant effect of word type in controls. Skin conductance level and the number of nonspecific fluctuations were larger in patients as compared with controls. The present electrodermal study suggests that chronic pain is linked to an increased reactivity to a wide range of stimuli. Emotional load amplifies the effect. This leads to recommend broad therapeutic management in chronic sufferers. Contrary to expectation derived from classical conditioning, patients did not prove over-sensitive to pain descriptors. This negative finding is discussed at methodologic, physiologic, and psychologic levels.

  13. Analytic Intermodel Consistent Modeling of Volumetric Human Lung Dynamics.

    Science.gov (United States)

    Ilegbusi, Olusegun; Seyfi, Behnaz; Neylon, John; Santhanam, Anand P

    2015-10-01

    Human lung undergoes breathing-induced deformation in the form of inhalation and exhalation. Modeling the dynamics is numerically complicated by the lack of information on lung elastic behavior and fluid-structure interactions between air and the tissue. A mathematical method is developed to integrate deformation results from a deformable image registration (DIR) and physics-based modeling approaches in order to represent consistent volumetric lung dynamics. The computational fluid dynamics (CFD) simulation assumes the lung is a poro-elastic medium with spatially distributed elastic property. Simulation is performed on a 3D lung geometry reconstructed from four-dimensional computed tomography (4DCT) dataset of a human subject. The heterogeneous Young's modulus (YM) is estimated from a linear elastic deformation model with the same lung geometry and 4D lung DIR. The deformation obtained from the CFD is then coupled with the displacement obtained from the 4D lung DIR by means of the Tikhonov regularization (TR) algorithm. The numerical results include 4DCT registration, CFD, and optimal displacement data which collectively provide consistent estimate of the volumetric lung dynamics. The fusion method is validated by comparing the optimal displacement with the results obtained from the 4DCT registration.

  14. Adjoint-consistent formulations of slip models for coupled electroosmotic flow systems

    KAUST Repository

    Garg, Vikram V; Prudhomme, Serge; van der Zee, Kris G; Carey, Graham F

    2014-01-01

    Models based on the Helmholtz `slip' approximation are often used for the simulation of electroosmotic flows. The objectives of this paper are to construct adjoint-consistent formulations of such models, and to develop adjoint

  15. Toward a consistent modeling framework to assess multi-sectoral climate impacts.

    Science.gov (United States)

    Monier, Erwan; Paltsev, Sergey; Sokolov, Andrei; Chen, Y-H Henry; Gao, Xiang; Ejaz, Qudsia; Couzo, Evan; Schlosser, C Adam; Dutkiewicz, Stephanie; Fant, Charles; Scott, Jeffery; Kicklighter, David; Morris, Jennifer; Jacoby, Henry; Prinn, Ronald; Haigh, Martin

    2018-02-13

    Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

  16. Simplified models for dark matter face their consistent completions

    Energy Technology Data Exchange (ETDEWEB)

    Gonçalves, Dorival; Machado, Pedro A. N.; No, Jose Miguel

    2017-03-01

    Simplified dark matter models have been recently advocated as a powerful tool to exploit the complementarity between dark matter direct detection, indirect detection and LHC experimental probes. Focusing on pseudoscalar mediators between the dark and visible sectors, we show that the simplified dark matter model phenomenology departs significantly from that of consistent ${SU(2)_{\\mathrm{L}} \\times U(1)_{\\mathrm{Y}}}$ gauge invariant completions. We discuss the key physics simplified models fail to capture, and its impact on LHC searches. Notably, we show that resonant mono-Z searches provide competitive sensitivities to standard mono-jet analyses at $13$ TeV LHC.

  17. Consistent model reduction of polymer chains in solution in dissipative particle dynamics: Model description

    KAUST Repository

    Moreno Chaparro, Nicolas

    2015-06-30

    We introduce a framework for model reduction of polymer chain models for dissipative particle dynamics (DPD) simulations, where the properties governing the phase equilibria such as the characteristic size of the chain, compressibility, density, and temperature are preserved. The proposed methodology reduces the number of degrees of freedom required in traditional DPD representations to model equilibrium properties of systems with complex molecules (e.g., linear polymers). Based on geometrical considerations we explicitly account for the correlation between beads in fine-grained DPD models and consistently represent the effect of these correlations in a reduced model, in a practical and simple fashion via power laws and the consistent scaling of the simulation parameters. In order to satisfy the geometrical constraints in the reduced model we introduce bond-angle potentials that account for the changes in the chain free energy after the model reduction. Following this coarse-graining process we represent high molecular weight DPD chains (i.e., ≥200≥200 beads per chain) with a significant reduction in the number of particles required (i.e., ≥20≥20 times the original system). We show that our methodology has potential applications modeling systems of high molecular weight molecules at large scales, such as diblock copolymer and DNA.

  18. Prediction of protein binding sites using physical and chemical descriptors and the support vector machine regression method

    International Nuclear Information System (INIS)

    Sun Zhong-Hua; Jiang Fan

    2010-01-01

    In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression (SVR) method than by the support vector classification method. (rapid communication)

  19. A self-consistent upward leader propagation model

    International Nuclear Information System (INIS)

    Becerra, Marley; Cooray, Vernon

    2006-01-01

    The knowledge of the initiation and propagation of an upward moving connecting leader in the presence of a downward moving lightning stepped leader is a must in the determination of the lateral attraction distance of a lightning flash by any grounded structure. Even though different models that simulate this phenomenon are available in the literature, they do not take into account the latest developments in the physics of leader discharges. The leader model proposed here simulates the advancement of positive upward leaders by appealing to the presently understood physics of that process. The model properly simulates the upward continuous progression of the positive connecting leaders from its inception to the final connection with the downward stepped leader (final jump). Thus, the main physical properties of upward leaders, namely the charge per unit length, the injected current, the channel gradient and the leader velocity are self-consistently obtained. The obtained results are compared with an altitude triggered lightning experiment and there is good agreement between the model predictions and the measured leader current and the experimentally inferred spatial and temporal location of the final jump. It is also found that the usual assumption of constant charge per unit length, based on laboratory experiments, is not valid for lightning upward connecting leaders

  20. Self-consistent atmosphere modeling with cloud formation for low-mass stars and exoplanets

    Science.gov (United States)

    Juncher, Diana; Jørgensen, Uffe G.; Helling, Christiane

    2017-12-01

    Context. Low-mass stars and extrasolar planets have ultra-cool atmospheres where a rich chemistry occurs and clouds form. The increasing amount of spectroscopic observations for extrasolar planets requires self-consistent model atmosphere simulations to consistently include the formation processes that determine cloud formation and their feedback onto the atmosphere. Aims: Our aim is to complement the MARCS model atmosphere suit with simulations applicable to low-mass stars and exoplanets in preparation of E-ELT, JWST, PLATO and other upcoming facilities. Methods: The MARCS code calculates stellar atmosphere models, providing self-consistent solutions of the radiative transfer and the atmospheric structure and chemistry. We combine MARCS with a kinetic model that describes cloud formation in ultra-cool atmospheres (seed formation, growth/evaporation, gravitational settling, convective mixing, element depletion). Results: We present a small grid of self-consistently calculated atmosphere models for Teff = 2000-3000 K with solar initial abundances and log (g) = 4.5. Cloud formation in stellar and sub-stellar atmospheres appears for Teff day-night energy transport and no temperature inversion.

  1. Development of a Consistent and Reproducible Porcine Scald Burn Model

    Science.gov (United States)

    Kempf, Margit; Kimble, Roy; Cuttle, Leila

    2016-01-01

    There are very few porcine burn models that replicate scald injuries similar to those encountered by children. We have developed a robust porcine burn model capable of creating reproducible scald burns for a wide range of burn conditions. The study was conducted with juvenile Large White pigs, creating replicates of burn combinations; 50°C for 1, 2, 5 and 10 minutes and 60°C, 70°C, 80°C and 90°C for 5 seconds. Visual wound examination, biopsies and Laser Doppler Imaging were performed at 1, 24 hours and at 3 and 7 days post-burn. A consistent water temperature was maintained within the scald device for long durations (49.8 ± 0.1°C when set at 50°C). The macroscopic and histologic appearance was consistent between replicates of burn conditions. For 50°C water, 10 minute duration burns showed significantly deeper tissue injury than all shorter durations at 24 hours post-burn (p ≤ 0.0001), with damage seen to increase until day 3 post-burn. For 5 second duration burns, by day 7 post-burn the 80°C and 90°C scalds had damage detected significantly deeper in the tissue than the 70°C scalds (p ≤ 0.001). A reliable and safe model of porcine scald burn injury has been successfully developed. The novel apparatus with continually refreshed water improves consistency of scald creation for long exposure times. This model allows the pathophysiology of scald burn wound creation and progression to be examined. PMID:27612153

  2. Perceived size and perceived direction: The interplay of the two descriptors of visual space

    Czech Academy of Sciences Publication Activity Database

    Šikl, Radovan; Šimeček, Michal

    2011-01-01

    Roč. 40, č. 8 (2011), s. 953-961 ISSN 0301-0066 R&D Projects: GA ČR GPP407/10/P566 Institutional research plan: CEZ:AV0Z70250504 Keywords : visual space * spatial descriptors * size judgments * direction judgments * parameterization Subject RIV: AN - Psychology Impact factor: 1.313, year: 2011

  3. Structure based descriptors for the estimation of colloidal interactions and protein aggregation propensities.

    Directory of Open Access Journals (Sweden)

    Michael Brunsteiner

    Full Text Available The control of protein aggregation is an important requirement in the development of bio-pharmaceutical formulations. Here a simple protein model is proposed that was used in molecular dynamics simulations to obtain a quantitative assessment of the relative contributions of proteins' net-charges, dipole-moments, and the size of hydrophobic or charged surface patches to their colloidal interactions. The results demonstrate that the strength of these interactions correlate with net-charge and dipole moment. Variation of both these descriptors within ranges typical for globular proteins have a comparable effect. By comparison no clear trends can be observed upon varying the size of hydrophobic or charged patches while keeping the other parameters constant. The results are discussed in the context of experimental literature data on protein aggregation. They provide a clear guide line for the development of improved algorithms for the prediction of aggregation propensities.

  4. Microstructural descriptors and cellular automata simulation of the effects of non-random nuclei location on recrystallization in two dimensions

    Directory of Open Access Journals (Sweden)

    Paulo Rangel Rios

    2006-06-01

    Full Text Available The effect of non-random nuclei location and the efficiency of microstructural descriptors in assessing such a situation are studied. Cellular automata simulation of recrystallization in two dimensions is carried out to simulate microstrutural evolution for nuclei distribution ranging from a periodic arrangement to clusters of nuclei. The simulation results are compared in detail with microstrutural descriptors normally used to follow transformation evolution. It is shown that the contiguity is particularly relevant to detect microstructural deviations from randomness. This work focuses on recrystallization but its results are applicable to any nucleation and growth transformation.

  5. Modeling the Dispersibility of Single Walled Carbon Nanotubes in Organic Solvents by Quantitative Structure-Activity Relationship Approach

    Science.gov (United States)

    Yilmaz, Hayriye; Rasulev, Bakhtiyor; Leszczynski, Jerzy

    2015-01-01

    The knowledge of physico-chemical properties of carbon nanotubes, including behavior in organic solvents is very important for design, manufacturing and utilizing of their counterparts with improved properties. In the present study a quantitative structure-activity/property relationship (QSAR/QSPR) approach was applied to predict the dispersibility of single walled carbon nanotubes (SWNTs) in various organic solvents. A number of additive descriptors and quantum-chemical descriptors were calculated and utilized to build QSAR models. The best predictability is shown by a 4-variable model. The model showed statistically good results (R2training = 0.797, Q2 = 0.665, R2test = 0.807), with high internal and external correlation coefficients. Presence of the X0Av descriptor and its negative term suggest that small size solvents have better SWCNTs solubility. Mass weighted descriptor ATS6m also indicates that heavier solvents (and small in size) most probably are better solvents for SWCNTs. The presence of the Dipole Z descriptor indicates that higher polarizability of the solvent molecule increases the solubility. The developed model and contributed descriptors can help to understand the mechanism of the dispersion process and predictorganic solvents that improve the dispersibility of SWNTs. PMID:28347035

  6. Modeling the Dispersibility of Single Walled Carbon Nanotubes in Organic Solvents by Quantitative Structure-Activity Relationship Approach

    Directory of Open Access Journals (Sweden)

    Hayriye Yilmaz

    2015-05-01

    Full Text Available The knowledge of physico-chemical properties of carbon nanotubes, including behavior in organic solvents is very important for design, manufacturing and utilizing of their counterparts with improved properties. In the present study a quantitative structure-activity/property relationship (QSAR/QSPR approach was applied to predict the dispersibility of single walled carbon nanotubes (SWNTs in various organic solvents. A number of additive descriptors and quantum-chemical descriptors were calculated and utilized to build QSAR models. The best predictability is shown by a 4-variable model. The model showed statistically good results (R2training = 0.797, Q2 = 0.665, R2test = 0.807, with high internal and external correlation coefficients. Presence of the X0Av descriptor and its negative term suggest that small size solvents have better SWCNTs solubility. Mass weighted descriptor ATS6m also indicates that heavier solvents (and small in size most probably are better solvents for SWCNTs. The presence of the Dipole Z descriptor indicates that higher polarizability of the solvent molecule increases the solubility. The developed model and contributed descriptors can help to understand the mechanism of the dispersion process and predictorganic solvents that improve the dispersibility of SWNTs.

  7. Performance Evaluation of State-of-the-Art Local Feature Detectors and Descriptors in the Context of Longitudinal Registration of Retinal Images.

    Science.gov (United States)

    Saha, Sajib K; Xiao, Di; Frost, Shaun; Kanagasingam, Yogesan

    2018-02-17

    In this paper we systematically evaluate the performance of several state-of-the-art local feature detectors and descriptors in the context of longitudinal registration of retinal images. Longitudinal (temporal) registration facilitates to track the changes in the retina that has happened over time. A wide number of local feature detectors and descriptors exist and many of them have already applied for retinal image registration, however, no comparative evaluation has been made so far to analyse their respective performance. In this manuscript we evaluate the performance of the widely known and commonly used detectors such as Harris, SIFT, SURF, BRISK, and bifurcation and cross-over points. As of descriptors SIFT, SURF, ALOHA, BRIEF, BRISK and PIIFD are used. Longitudinal retinal image datasets containing a total of 244 images are used for the experiment. The evaluation reveals some potential findings including more robustness of SURF and SIFT keypoints than the commonly used bifurcation and cross-over points, when detected on the vessels. SIFT keypoints can be detected with a reliability of 59% for without pathology images and 45% for with pathology images. For SURF keypoints these values are respectively 58% and 47%. ALOHA descriptor is best suited to describe SURF keypoints, which ensures an overall matching accuracy, distinguishability of 83%, 93% and 78%, 83% for without pathology and with pathology images respectively.

  8. Circular blurred shape model for multiclass symbol recognition.

    Science.gov (United States)

    Escalera, Sergio; Fornés, Alicia; Pujol, Oriol; Lladós, Josep; Radeva, Petia

    2011-04-01

    In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.

  9. Number of outer electrons as descriptor for adsorption processes on transition metals and their oxides

    DEFF Research Database (Denmark)

    Calle-Vallejo, Federico; Inoglu, Nilay G.; Su, Hai-Yan

    2013-01-01

    The trends in adsorption energies of the intermediates of the oxygen reduction and evolution reactions on transition metals and their oxides are smoothly captured by the number of outer electrons. This unique descriptor permits the construction of predictive adsorption-energy grids and explains t...

  10. Associations among descriptors of herd management and phenotypic and genetic levels of health and fertility

    NARCIS (Netherlands)

    Calus, M.P.L.; Windig, J.J.; Veerkamp, R.F.

    2005-01-01

    The objective of this paper was to investigate the association of descriptors of herd environment with phenotypic levels and breeding values of fertility and health traits. Analyses were performed for 82,080 first-lactation heifers and 173,787 multiparous cows. Fourteen environmental parameters were

  11. Important clinical descriptors to include in the examination and assessment of patients with femoroacetabular impingement syndrome

    DEFF Research Database (Denmark)

    Reiman, M P; Thorborg, K; Covington, K

    2017-01-01

    PURPOSE: Determine which examination findings are key clinical descriptors of femoroacetabular impingement syndrome (FAIS) through use of an international, multi-disciplinary expert panel. METHODS: A three-round Delphi survey utilizing an international, multi-disciplinary expert panel operationally...

  12. Consistent partnership formation: application to a sexually transmitted disease model.

    Science.gov (United States)

    Artzrouni, Marc; Deuchert, Eva

    2012-02-01

    We apply a consistent sexual partnership formation model which hinges on the assumption that one gender's choices drives the process (male or female dominant model). The other gender's behavior is imputed. The model is fitted to UK sexual behavior data and applied to a simple incidence model of HSV-2. With a male dominant model (which assumes accurate male reports on numbers of partners) the modeled incidences of HSV-2 are 77% higher for men and 50% higher for women than with a female dominant model (which assumes accurate female reports). Although highly stylized, our simple incidence model sheds light on the inconsistent results one can obtain with misreported data on sexual activity and age preferences. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. Self-consistent approach for neutral community models with speciation

    Science.gov (United States)

    Haegeman, Bart; Etienne, Rampal S.

    2010-03-01

    Hubbell’s neutral model provides a rich theoretical framework to study ecological communities. By incorporating both ecological and evolutionary time scales, it allows us to investigate how communities are shaped by speciation processes. The speciation model in the basic neutral model is particularly simple, describing speciation as a point-mutation event in a birth of a single individual. The stationary species abundance distribution of the basic model, which can be solved exactly, fits empirical data of distributions of species’ abundances surprisingly well. More realistic speciation models have been proposed such as the random-fission model in which new species appear by splitting up existing species. However, no analytical solution is available for these models, impeding quantitative comparison with data. Here, we present a self-consistent approximation method for neutral community models with various speciation modes, including random fission. We derive explicit formulas for the stationary species abundance distribution, which agree very well with simulations. We expect that our approximation method will be useful to study other speciation processes in neutral community models as well.

  14. Self-consistent modeling of electron cyclotron resonance ion sources

    International Nuclear Information System (INIS)

    Girard, A.; Hitz, D.; Melin, G.; Serebrennikov, K.; Lecot, C.

    2004-01-01

    In order to predict the performances of electron cyclotron resonance ion source (ECRIS), it is necessary to perfectly model the different parts of these sources: (i) magnetic configuration; (ii) plasma characteristics; (iii) extraction system. The magnetic configuration is easily calculated via commercial codes; different codes also simulate the ion extraction, either in two dimension, or even in three dimension (to take into account the shape of the plasma at the extraction influenced by the hexapole). However the characteristics of the plasma are not always mastered. This article describes the self-consistent modeling of ECRIS: we have developed a code which takes into account the most important construction parameters: the size of the plasma (length, diameter), the mirror ratio and axial magnetic profile, whether a biased probe is installed or not. These input parameters are used to feed a self-consistent code, which calculates the characteristics of the plasma: electron density and energy, charge state distribution, plasma potential. The code is briefly described, and some of its most interesting results are presented. Comparisons are made between the calculations and the results obtained experimentally

  15. Self-consistent modeling of electron cyclotron resonance ion sources

    Science.gov (United States)

    Girard, A.; Hitz, D.; Melin, G.; Serebrennikov, K.; Lécot, C.

    2004-05-01

    In order to predict the performances of electron cyclotron resonance ion source (ECRIS), it is necessary to perfectly model the different parts of these sources: (i) magnetic configuration; (ii) plasma characteristics; (iii) extraction system. The magnetic configuration is easily calculated via commercial codes; different codes also simulate the ion extraction, either in two dimension, or even in three dimension (to take into account the shape of the plasma at the extraction influenced by the hexapole). However the characteristics of the plasma are not always mastered. This article describes the self-consistent modeling of ECRIS: we have developed a code which takes into account the most important construction parameters: the size of the plasma (length, diameter), the mirror ratio and axial magnetic profile, whether a biased probe is installed or not. These input parameters are used to feed a self-consistent code, which calculates the characteristics of the plasma: electron density and energy, charge state distribution, plasma potential. The code is briefly described, and some of its most interesting results are presented. Comparisons are made between the calculations and the results obtained experimentally.

  16. Application of morphological associative memories and Fourier descriptors for classification of noisy subsurface signatures

    Science.gov (United States)

    Ortiz, Jorge L.; Parsiani, Hamed; Tolstoy, Leonid

    2004-02-01

    This paper presents a method for recognition of Noisy Subsurface Images using Morphological Associative Memories (MAM). MAM are type of associative memories that use a new kind of neural networks based in the algebra system known as semi-ring. The operations performed in this algebraic system are highly nonlinear providing additional strength when compared to other transformations. Morphological associative memories are a new kind of neural networks that provide a robust performance with noisy inputs. Two representations of morphological associative memories are used called M and W matrices. M associative memory provides a robust association with input patterns corrupted by dilative random noise, while the W associative matrix performs a robust recognition in patterns corrupted with erosive random noise. The robust performance of MAM is used in combination of the Fourier descriptors for the recognition of underground objects in Ground Penetrating Radar (GPR) images. Multiple 2-D GPR images of a site are made available by NASA-SSC center. The buried objects in these images appear in the form of hyperbolas which are the results of radar backscatter from the artifacts or objects. The Fourier descriptors of the prototype hyperbola-like and shapes from non-hyperbola shapes in the sub-surface images are used to make these shapes scale-, shift-, and rotation-invariant. Typical hyperbola-like and non-hyperbola shapes are used to calculate the morphological associative memories. The trained MAMs are used to process other noisy images to detect the presence of these underground objects. The outputs from the MAM using the noisy patterns may be equal to the training prototypes, providing a positive identification of the artifacts. The results are images with recognized hyperbolas which indicate the presence of buried artifacts. A model using MATLAB has been developed and results are presented.

  17. Unsupervised selection of informative descriptors in QSAR study of anti-HIV activities of HEPT derivatives

    DEFF Research Database (Denmark)

    Bagheri, Saeed; Omidikia, Nematollah; Kompany-Zareh, Mohsen

    2013-01-01

    features of HEPT derivatives. The aims of this procedure are generating a subset of descriptors from a data set with the relevant variables, eliminating redundancy, and reducing multicollinearity. The core of this methodology is based on jack-knife resampling method. In this paper, using jack-knife led...

  18. T-scale as a novel vector of topological descriptors for amino acids and its application in QSARs of peptides

    Science.gov (United States)

    Tian, Feifei; Zhou, Peng; Li, Zhiliang

    2007-03-01

    In this paper, a new topological descriptor T-scale is derived from principal component analysis (PCA) on the collected 67 kinds of structural and topological variables of 135 amino acids. Applying T-scale to three peptide panels as 58 angiotensin-converting enzyme (ACE) inhibitors, 20 thromboplastin inhibitors (TI) and 28 bovine lactoferricin-(17-31)-pentadecapeptides (LFB), the resulting QSAR models, constructed by partial least squares (PLS), are all superior to reference reports, with correlative coefficient r2 and cross-validated q2 of 0.845, 0.786; 0.996, 0.782 (0.988, 0.961); 0.760, 0.627, respectively.

  19. Mean-field theory and self-consistent dynamo modeling

    International Nuclear Information System (INIS)

    Yoshizawa, Akira; Yokoi, Nobumitsu

    2001-12-01

    Mean-field theory of dynamo is discussed with emphasis on the statistical formulation of turbulence effects on the magnetohydrodynamic equations and the construction of a self-consistent dynamo model. The dynamo mechanism is sought in the combination of the turbulent residual-helicity and cross-helicity effects. On the basis of this mechanism, discussions are made on the generation of planetary magnetic fields such as geomagnetic field and sunspots and on the occurrence of flow by magnetic fields in planetary and fusion phenomena. (author)

  20. Assessing diversity among traditional Greek and foreign eggplant cultivars using molecular markers and morphometrical descriptors

    International Nuclear Information System (INIS)

    Augustinos, A.A.; Petropoulos, C.; Karasoulou, V.; Bletsos, F.; Papasotiropoulos, V.

    2016-01-01

    Eggplant is a widely cultivated vegetable crop of great economic importance. Its long lasting history of domestication, selection and breeding has led to the development of numerous cultivars with variable traits. In the present study, we assessed the diversity levels within and among eleven Greek and foreign cultivars, using 22 morphological descriptors and two different classes of molecular markers (retrotransposon microsatellite amplified polymorphism-REMAP markers and nuclear microsatellites). Our results, in accordance with other studies in the field showed: a) the limited levels of genetic polymorphism within the cultivars; b) the high morphological and genetic divergence existing among them as indicated by the genetic distance values calculated, which could be attributed to selection, inbreeding and bottleneck effects; and c) the lack of concordance among morphological descriptors and molecular markers. Despite these, our analysis showed that the utilization of combinations of markers is an effective method for the characterization of plant material providing also useful diagnostic tools for the identification and authentication of the selected Greek cultivars.

  1. Assessing diversity among traditional Greek and foreign eggplant cultivars using molecular markers and morphometrical descriptors

    Energy Technology Data Exchange (ETDEWEB)

    Augustinos, A.A.; Petropoulos, C.; Karasoulou, V.; Bletsos, F.; Papasotiropoulos, V.

    2016-07-01

    Eggplant is a widely cultivated vegetable crop of great economic importance. Its long lasting history of domestication, selection and breeding has led to the development of numerous cultivars with variable traits. In the present study, we assessed the diversity levels within and among eleven Greek and foreign cultivars, using 22 morphological descriptors and two different classes of molecular markers (retrotransposon microsatellite amplified polymorphism-REMAP markers and nuclear microsatellites). Our results, in accordance with other studies in the field showed: a) the limited levels of genetic polymorphism within the cultivars; b) the high morphological and genetic divergence existing among them as indicated by the genetic distance values calculated, which could be attributed to selection, inbreeding and bottleneck effects; and c) the lack of concordance among morphological descriptors and molecular markers. Despite these, our analysis showed that the utilization of combinations of markers is an effective method for the characterization of plant material providing also useful diagnostic tools for the identification and authentication of the selected Greek cultivars.

  2. Classical and Quantum Consistency of the DGP Model

    CERN Document Server

    Nicolis, A; Nicolis, Alberto; Rattazzi, Riccardo

    2004-01-01

    We study the Dvali-Gabadadze-Porrati model by the method of the boundary effective action. The truncation of this action to the bending mode \\pi consistently describes physics in a wide range of regimes both at the classical and at the quantum level. The Vainshtein effect, which restores agreement with precise tests of general relativity, follows straightforwardly. We give a simple and general proof of stability, i.e. absence of ghosts in the fluctuations, valid for most of the relevant cases, like for instance the spherical source in asymptotically flat space. However we confirm that around certain interesting self-accelerating cosmological solutions there is a ghost. We consider the issue of quantum corrections. Around flat space \\pi becomes strongly coupled below a macroscopic length of 1000 km, thus impairing the predictivity of the model. Indeed the tower of higher dimensional operators which is expected by a generic UV completion of the model limits predictivity at even larger length scales. We outline ...

  3. Novel dimer based descriptors with solvational computation for QSAR study of oxadiazoylbenzoyl-ureas as novel insect-growth regulators.

    Science.gov (United States)

    Fan, Feng; Cheng, Jiagao; Li, Zhong; Xu, Xiaoyong; Qian, Xuhong

    2010-02-01

    Molecular aggregation state of bioactive compounds plays a key role in its bio-interactive procedure. In this article, based on the structure information of dimers, the simplest model of molecular aggregation state, and combined with solvational computation, total four descriptors (DeltaV, MR2, DeltaE(1), and DeltaE(2)) were calculated for QSAR study of a novel insect-growth regulator, N-(5-phenyl-1,3,4-oxadiazol-2-yl)-N'-benzoyl urea. Two QSAR models were constructed with r(2) = 0.671, q(2) = 0.516 and r(2) = 0.816, q(2) = 0.695, respectively. It implicates that the bioactivity may strongly depend on the characters of molecular aggregation state, especially on the dimeric transport ability from oil phase to water phase. Copyright 2009 Wiley Periodicals, Inc.

  4. A CVAR scenario for a standard monetary model using theory-consistent expectations

    DEFF Research Database (Denmark)

    Juselius, Katarina

    2017-01-01

    A theory-consistent CVAR scenario describes a set of testable regularities capturing basic assumptions of the theoretical model. Using this concept, the paper considers a standard model for exchange rate determination and shows that all assumptions about the model's shock structure and steady...

  5. Consistency maintenance for constraint in role-based access control model

    Institute of Scientific and Technical Information of China (English)

    韩伟力; 陈刚; 尹建伟; 董金祥

    2002-01-01

    Constraint is an important aspect of role-based access control and is sometimes argued to be the principal motivation for role-based access control (RBAC). But so far few authors have discussed consistency maintenance for constraint in RBAC model. Based on researches of constraints among roles and types of inconsistency among constraints, this paper introduces corresponding formal rules, rule-based reasoning and corresponding methods to detect, avoid and resolve these inconsistencies. Finally, the paper introduces briefly the application of consistency maintenance in ZD-PDM, an enterprise-oriented product data management (PDM) system.

  6. Consistency maintenance for constraint in role-based access control model

    Institute of Scientific and Technical Information of China (English)

    韩伟力; 陈刚; 尹建伟; 董金祥

    2002-01-01

    Constraint is an important aspect of role-based access control and is sometimes argued to be the principal motivation for role-based access control (RBAC). But so far'few authors have discussed consistency maintenance for constraint in RBAC model. Based on researches of constraints among roles and types of inconsistency among constraints, this paper introduces correaponding formal rules, rulebased reasoning and corresponding methods to detect, avoid and resolve these inconsistencies. Finally,the paper introduces briefly the application of consistency maintenance in ZD-PDM, an enterprise-ori-ented product data management (PDM) system.

  7. Variational 3D-PIV with sparse descriptors

    Science.gov (United States)

    Lasinger, Katrin; Vogel, Christoph; Pock, Thomas; Schindler, Konrad

    2018-06-01

    3D particle imaging velocimetry (3D-PIV) aims to recover the flow field in a volume of fluid, which has been seeded with tracer particles and observed from multiple camera viewpoints. The first step of 3D-PIV is to reconstruct the 3D locations of the tracer particles from synchronous views of the volume. We propose a new method for iterative particle reconstruction, in which the locations and intensities of all particles are inferred in one joint energy minimization. The energy function is designed to penalize deviations between the reconstructed 3D particles and the image evidence, while at the same time aiming for a sparse set of particles. We find that the new method, without any post-processing, achieves significantly cleaner particle volumes than a conventional, tomographic MART reconstruction, and can handle a wide range of particle densities. The second step of 3D-PIV is to then recover the dense motion field from two consecutive particle reconstructions. We propose a variational model, which makes it possible to directly include physical properties, such as incompressibility and viscosity, in the estimation of the motion field. To further exploit the sparse nature of the input data, we propose a novel, compact descriptor of the local particle layout. Hence, we avoid the memory-intensive storage of high-resolution intensity volumes. Our framework is generic and allows for a variety of different data costs (correlation measures) and regularizers. We quantitatively evaluate it with both the sum of squared differences and the normalized cross-correlation, respectively with both a hard and a soft version of the incompressibility constraint.

  8. A Theoretically Consistent Framework for Modelling Lagrangian Particle Deposition in Plant Canopies

    Science.gov (United States)

    Bailey, Brian N.; Stoll, Rob; Pardyjak, Eric R.

    2018-06-01

    We present a theoretically consistent framework for modelling Lagrangian particle deposition in plant canopies. The primary focus is on describing the probability of particles encountering canopy elements (i.e., potential deposition), and provides a consistent means for including the effects of imperfect deposition through any appropriate sub-model for deposition efficiency. Some aspects of the framework draw upon an analogy to radiation propagation through a turbid medium with which to develop model theory. The present method is compared against one of the most commonly used heuristic Lagrangian frameworks, namely that originally developed by Legg and Powell (Agricultural Meteorology, 1979, Vol. 20, 47-67), which is shown to be theoretically inconsistent. A recommendation is made to discontinue the use of this heuristic approach in favour of the theoretically consistent framework developed herein, which is no more difficult to apply under equivalent assumptions. The proposed framework has the additional advantage that it can be applied to arbitrary canopy geometries given readily measurable parameters describing vegetation structure.

  9. Wavelet neural network modeling in QSPR for prediction of solubility of 25 anthraquinone dyes at different temperatures and pressures in supercritical carbon dioxide.

    Science.gov (United States)

    Tabaraki, R; Khayamian, T; Ensafi, A A

    2006-09-01

    A wavelet neural network (WNN) model in quantitative structure property relationship (QSPR) was developed for predicting solubility of 25 anthraquinone dyes in supercritical carbon dioxide over a wide range of pressures (70-770 bar) and temperatures (291-423 K). A large number of descriptors were calculated with Dragon software and a subset of calculated descriptors was selected from 18 classes of Dragon descriptors with a stepwise multiple linear regression (MLR) as a feature selection technique. Six calculated and two experimental descriptors, pressure and temperature, were selected as the most feasible descriptors. The selected descriptors were used as input nodes in a wavelet neural network (WNN) model. The wavelet neural network architecture and its parameters were optimized simultaneously. The data was randomly divided to the training, prediction and validation sets. The predictive ability of the model was evaluated using validation data set. The root mean squares error (RMSE) and mean absolute errors were 0.339 and 0.221, respectively, for the validation data set. The performance of the WNN model was also compared with artificial neural network (ANN) model and the results showed the superiority of the WNN over ANN model.

  10. Demonstration of SST value as EBVs descriptor in the Mediterranean Sea

    Science.gov (United States)

    Valentini, E.; Filipponi, F.; Nguyen Xuan, A.; Taramelli, A.

    2017-12-01

    Sea Surface Temperature is an Essential Climate and Ocean Variable (ECV - EOV) able to capture critical scales in the seascape warming patterns and to highlight the exceeding of thresholds. This presentation addresses the changes of the SST in the last three decades over the Mediterranean Sea, a "Large Marine Ecosystem (LME)", in order to speculate the value of such powerful variable, as proxy for the assessment of ecosystem state in terms of ecosystem structures, functions and composition key descriptor. Time series of daily SST for the period 1982-2016, estimated from multi-sensor satellite data and provided by Copernicus Marine Environment Monitoring Service (CMEMS-EU) are used to perform different statistical analysis on common fish species. Results highlight the critical conditions, the general trends as well as the spatial and temporal patterns, in terms of thermal growth, vitality and stress influence on selected fish species. Results confirm a constant increasing trend in SST with an average rise of 1.4° C in the past thirty years. The variance associated to the average trend is not constant across the entire Mediterranean Sea opening the way to multiple scenarios for fish growth and vitality in the diverse sub-basins. A major effort is oriented in addressing the cross-scale ecological interactions to assess the feasibility of using SST as descriptor for Essential Biodiversity Variables, able to prioritize areas and to feed operational tools for planning and management in the Mediterranean LME.

  11. Final Report Fermionic Symmetries and Self consistent Shell Model

    International Nuclear Information System (INIS)

    Zamick, Larry

    2008-01-01

    In this final report in the field of theoretical nuclear physics we note important accomplishments.We were confronted with 'anomoulous' magnetic moments by the experimetalists and were able to expain them. We found unexpected partial dynamical symmetries--completely unknown before, and were able to a large extent to expain them. The importance of a self consistent shell model was emphasized.

  12. 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)

  13. Fitting multimeric protein complexes into electron microscopy maps using 3D Zernike descriptors.

    Science.gov (United States)

    Esquivel-Rodríguez, Juan; Kihara, Daisuke

    2012-06-14

    A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three-dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root-mean-square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.

  14. A self-consistent spin-diffusion model for micromagnetics

    KAUST Repository

    Abert, Claas; Ruggeri, Michele; Bruckner, Florian; Vogler, Christoph; Manchon, Aurelien; Praetorius, Dirk; Suess, Dieter

    2016-01-01

    We propose a three-dimensional micromagnetic model that dynamically solves the Landau-Lifshitz-Gilbert equation coupled to the full spin-diffusion equation. In contrast to previous methods, we solve for the magnetization dynamics and the electric potential in a self-consistent fashion. This treatment allows for an accurate description of magnetization dependent resistance changes. Moreover, the presented algorithm describes both spin accumulation due to smooth magnetization transitions and due to material interfaces as in multilayer structures. The model and its finite-element implementation are validated by current driven motion of a magnetic vortex structure. In a second experiment, the resistivity of a magnetic multilayer structure in dependence of the tilting angle of the magnetization in the different layers is investigated. Both examples show good agreement with reference simulations and experiments respectively.

  15. A self-consistent spin-diffusion model for micromagnetics

    KAUST Repository

    Abert, Claas

    2016-12-17

    We propose a three-dimensional micromagnetic model that dynamically solves the Landau-Lifshitz-Gilbert equation coupled to the full spin-diffusion equation. In contrast to previous methods, we solve for the magnetization dynamics and the electric potential in a self-consistent fashion. This treatment allows for an accurate description of magnetization dependent resistance changes. Moreover, the presented algorithm describes both spin accumulation due to smooth magnetization transitions and due to material interfaces as in multilayer structures. The model and its finite-element implementation are validated by current driven motion of a magnetic vortex structure. In a second experiment, the resistivity of a magnetic multilayer structure in dependence of the tilting angle of the magnetization in the different layers is investigated. Both examples show good agreement with reference simulations and experiments respectively.

  16. Discrimination Power of Polynomial-Based Descriptors for Graphs by Using Functional Matrices.

    Science.gov (United States)

    Dehmer, Matthias; Emmert-Streib, Frank; Shi, Yongtang; Stefu, Monica; Tripathi, Shailesh

    2015-01-01

    In this paper, we study the discrimination power of graph measures that are based on graph-theoretical matrices. The paper generalizes the work of [M. Dehmer, M. Moosbrugger. Y. Shi, Encoding structural information uniquely with polynomial-based descriptors by employing the Randić matrix, Applied Mathematics and Computation, 268(2015), 164-168]. We demonstrate that by using the new functional matrix approach, exhaustively generated graphs can be discriminated more uniquely than shown in the mentioned previous work.

  17. Optimal descriptor as a translator of eclectic data into endpoint prediction: mutagenicity of fullerene as a mathematical function of conditions.

    Science.gov (United States)

    Toropov, Andrey A; Toropova, Alla P

    2014-06-01

    The experimental data on the bacterial reverse mutation test on C60 nanoparticles (TA100) is examined as an endpoint. By means of the optimal descriptors calculated with the Monte Carlo method a mathematical model of the endpoint has been built up. The model is the mathematical function of (i) dose (g/plate); (ii) metabolic activation (i.e. with S9 mix or without S9 mix); and (iii) illumination (i.e. dark or irradiation). The statistical quality of the model is the following: n=10, r(2)=0.7549, q(2)=0.5709, s=7.67, F=25 (Training set); n=5, r(2)=0.8987, s=18.4 (Calibration set); and n=5, r(2)=0.6968, s=10.9 (Validation set). Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Descriptor Fingerprints and Their Application to Red Wine Clustering and Discrimination

    Science.gov (United States)

    Bangov, I. P.; Moskovkina, M.; Stojanov, B. P.

    2017-03-01

    The investigation was performed to test the potentials of the fingerprint clustering algorithm for a set of 1599 red wines in relation to some wine properties, comprised in the notion "wine quality". We have obtained a distribution of the wines into different clusters as a result. Each cluster was composed of wine-objects with similar values of laboratory parameters and with a wine quality certificate. A correlation between the. quality of wines (a sensory taste factor) and the phisicochemical descriptors (laboratory analytical test results data) was observed and analyzed.

  19. Descriptor Fingerprints and Their Application to Red Wine Clustering and Discrimination

    Directory of Open Access Journals (Sweden)

    Bangov I.P.

    2017-03-01

    Full Text Available The investigation was performed to test the potentials of the fingerprint clustering algorithm for a set of 1599 red wines in relation to some wine properties, comprised in the notion “wine quality”. We have obtained a distribution of the wines into different clusters as a result. Each cluster was composed of wine-objects with similar values of laboratory parameters and with a wine quality certificate. A correlation between the. quality of wines (a sensory taste factor and the phisicochemical descriptors (laboratory analytical test results data was observed and analyzed.

  20. Sign languages and the Common European Framework of Reference for Languages : Descriptors and approaches to assessment

    NARCIS (Netherlands)

    L. Leeson; Dr. Beppie van den Bogaerde; Tobias Haug; C. Rathmann

    2015-01-01

    This resource establishes European standards for sign languages for professional purposes in line with the Common European Framework of Reference for Languages (CEFR) and provides an overview of assessment descriptors and approaches. Drawing on preliminary work undertaken in adapting the CEFR to

  1. Imprecise Frequency Descriptors and the Miscomprehension of Prescription Drug Advertising: Public Policy and Regulatory Implications.

    Science.gov (United States)

    Davis, Joel J.

    1999-01-01

    Explores the communicative effectiveness of imprecise frequency descriptors within the context of consumer prescription drug advertising. Conducts two separate studies using a total sample of 147 adults. Finds that consumers are unable to accurately estimate the relative likelihood of side effect occurrence when a list of side effects are preceded…

  2. A Time consistent model for monetary value of man-sievert

    International Nuclear Information System (INIS)

    Na, S.H.; Kim, Sun G.

    2008-01-01

    Full text: Performing a cost-benefit analysis to establish optimum levels of radiation protection under the ALARA principle, we introduce a discrete stepwise model to evaluate man-sievert monetary value of Korea. The model formula, which is unique and country-specific, is composed of GDP, the nominal risk coefficient for cancer and hereditary effects, the aversion factor against radiation exposure, and the average life expectancy. Unlike previous researches on alpha-value assessment, we showed different alpha values optimized with respect to various ranges of individual dose, which would be more realistic and applicable to the radiation protection area. Employing economically constant term of GDP we showed the real values of man-sievert by year, which should be consistent in time series comparison even under price level fluctuation. GDP deflators of an economy have to be applied to measure one's own consistent value of radiation protection by year. In addition, we recommend that the concept of purchasing power parity should be adopted if it needs international comparison of alpha values in real terms. Finally, we explain the way that this stepwise model can be generalized simply to other countries without normalizing any country-specific factors. (author)

  3. A model for cytoplasmic rheology consistent with magnetic twisting cytometry.

    Science.gov (United States)

    Butler, J P; Kelly, S M

    1998-01-01

    Magnetic twisting cytometry is gaining wide applicability as a tool for the investigation of the rheological properties of cells and the mechanical properties of receptor-cytoskeletal interactions. Current technology involves the application and release of magnetically induced torques on small magnetic particles bound to or inside cells, with measurements of the resulting angular rotation of the particles. The properties of purely elastic or purely viscous materials can be determined by the angular strain and strain rate, respectively. However, the cytoskeleton and its linkage to cell surface receptors display elastic, viscous, and even plastic deformation, and the simultaneous characterization of these properties using only elastic or viscous models is internally inconsistent. Data interpretation is complicated by the fact that in current technology, the applied torques are not constant in time, but decrease as the particles rotate. This paper describes an internally consistent model consisting of a parallel viscoelastic element in series with a parallel viscoelastic element, and one approach to quantitative parameter evaluation. The unified model reproduces all essential features seen in data obtained from a wide variety of cell populations, and contains the pure elastic, viscoelastic, and viscous cases as subsets.

  4. Contrast-enhanced spectral mammography: Impact of the qualitative morphology descriptors on the diagnosis of breast lesions.

    Science.gov (United States)

    Mohamed Kamal, Rasha; Hussien Helal, Maha; Wessam, Rasha; Mahmoud Mansour, Sahar; Godda, Iman; Alieldin, Nelly

    2015-06-01

    To analyze the morphology and enhancement characteristics of breast lesions on contrast-enhanced spectral mammography (CESM) and to assess their impact on the differentiation between benign and malignant lesions. This ethics committee approved study included 168 consecutive patients with 211 breast lesions over 18 months. Lesions classified as non-enhancing and enhancing and then the latter group was subdivided into mass and non-mass. Mass lesions descriptors included: shape, margins, pattern and degree of internal enhancement. Non-mass lesions descriptors included: distribution, pattern and degree of internal enhancement. The impact of each descriptor on diagnosis individually assessed using Chi test and the validity compared in both benign and malignant lesions. The overall performance of CESM were also calculated. The study included 102 benign (48.3%) and 109 malignant (51.7%) lesions. Enhancement was encountered in 145/211 (68.7%) lesions. They further classified into enhancing mass (99/145, 68.3%) and non-mass lesions (46/145, 31.7%). Contrast uptake was significantly more frequent in malignant breast lesions (p value ≤ 0.001). Irregular mass lesions with intense and heterogeneous enhancement patterns correlated with a malignant pathology (p value ≤ 0.001). CESM showed an overall sensitivity of 88.99% and specificity of 83.33%. The positive and negative likelihood ratios were 5.34 and 0.13 respectively. The assessment of the morphology and enhancement characteristics of breast lesions on CESM enhances the performance of digital mammography in the differentiation between benign and malignant breast lesions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  5. New geometric design consistency model based on operating speed profiles for road safety evaluation.

    Science.gov (United States)

    Camacho-Torregrosa, Francisco J; Pérez-Zuriaga, Ana M; Campoy-Ungría, J Manuel; García-García, Alfredo

    2013-12-01

    To assist in the on-going effort to reduce road fatalities as much as possible, this paper presents a new methodology to evaluate road safety in both the design and redesign stages of two-lane rural highways. This methodology is based on the analysis of road geometric design consistency, a value which will be a surrogate measure of the safety level of the two-lane rural road segment. The consistency model presented in this paper is based on the consideration of continuous operating speed profiles. The models used for their construction were obtained by using an innovative GPS-data collection method that is based on continuous operating speed profiles recorded from individual drivers. This new methodology allowed the researchers to observe the actual behavior of drivers and to develop more accurate operating speed models than was previously possible with spot-speed data collection, thereby enabling a more accurate approximation to the real phenomenon and thus a better consistency measurement. Operating speed profiles were built for 33 Spanish two-lane rural road segments, and several consistency measurements based on the global and local operating speed were checked. The final consistency model takes into account not only the global dispersion of the operating speed, but also some indexes that consider both local speed decelerations and speeds over posted speeds as well. For the development of the consistency model, the crash frequency for each study site was considered, which allowed estimating the number of crashes on a road segment by means of the calculation of its geometric design consistency. Consequently, the presented consistency evaluation method is a promising innovative tool that can be used as a surrogate measure to estimate the safety of a road segment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. MODELLING THE INHIBITORY ACTIVITY ON CARBONIC ANHYDRASE IV OF SUBSTITUTED THIADIAZOLE - AND THIADIAZOLINE - DISULFONAMIDES: INTEGRATION OF STRUCTURE INFORMATION

    Directory of Open Access Journals (Sweden)

    Sorana Daniela Bolboaca

    2006-07-01

    Full Text Available ABSTRACT:Purpose: To analyze the relationships between inhibitory activities on carbonic anhydrase IV and structures of substituted 1,3,4-thiadiazole and 1,3,4-thiadiazoline disulfonamide through integration of compounds complex structure information by the use of Molecular Descriptors Family.Method: A number of forty compounds were used to generate and compute the molecular descriptors family and to build structure-activity relationships models. The obtained multi-varied models (the models with two, respectively with four descriptors were validated by computing the cross-validation leave-one-out score (r2cv-loo, and analyzed through assessment of the squared correlation coefficients (r2, and the models stability (r2 - r2cv-loo. The estimation abilities of the multi-varied MDF-SAR model with four descriptors were analyzed in training and test sets.Results: Analysis of the obtained models shows that the best results was obtained by the multi-varied model with four molecular descriptors (r2 = 0.920. The prediction abilities of this model is sustained by the cross validation leave-one-out score (r2cv-loo = 0.903, the model stability (r2 - r2cv-loo = 0.017, and the results on training versus test analysis (no significant differences between correlation coefficients in training and test sets, p > 0.05. The multi-varied model which used four descriptors proved to render higher value of correlation coefficient comparing with previous reported models (p 0.05. El modelo multivariante que utilizó cuatro descriptores mostró un valor más alto del coeficiente de correlación en comparación con los modelos divulgados anteriormente (p < 0.01.Conclusión: El modelo multivariante con cuatro descriptores es sólido y fiable e indica que la actividad de la inhibición en la carboanhidrasa IV producida por las sufonamidas sustituidas del 1,3,4-tiadiazol- y de la 1,3,4-tiadiazolina- dependen de la naturaleza de la geometría y de la topología del compuesto

  7. Towards Global QSAR Model Building for Acute Toxicity: Munro Database Case Study

    Directory of Open Access Journals (Sweden)

    Swapnil Chavan

    2014-10-01

    Full Text Available A series of 436 Munro database chemicals were studied with respect to their corresponding experimental LD50 values to investigate the possibility of establishing a global QSAR model for acute toxicity. Dragon molecular descriptors were used for the QSAR model development and genetic algorithms were used to select descriptors better correlated with toxicity data. Toxic values were discretized in a qualitative class on the basis of the Globally Harmonized Scheme: the 436 chemicals were divided into 3 classes based on their experimental LD50 values: highly toxic, intermediate toxic and low to non-toxic. The k-nearest neighbor (k-NN classification method was calibrated on 25 molecular descriptors and gave a non-error rate (NER equal to 0.66 and 0.57 for internal and external prediction sets, respectively. Even if the classification performances are not optimal, the subsequent analysis of the selected descriptors and their relationship with toxicity levels constitute a step towards the development of a global QSAR model for acute toxicity.

  8. Behavioral Consistency of C and Verilog Programs Using Bounded Model Checking

    National Research Council Canada - National Science Library

    Clarke, Edmund; Kroening, Daniel; Yorav, Karen

    2003-01-01

    .... We describe experimental results on various reactive present an algorithm that checks behavioral consistency between an ANSI-C program and a circuit given in Verilog using Bounded Model Checking...

  9. Theories of quantum dissipation and nonlinear coupling bath descriptors

    Science.gov (United States)

    Xu, Rui-Xue; Liu, Yang; Zhang, Hou-Dao; Yan, YiJing

    2018-03-01

    The quest of an exact and nonperturbative treatment of quantum dissipation in nonlinear coupling environments remains in general an intractable task. In this work, we address the key issues toward the solutions to the lowest nonlinear environment, a harmonic bath coupled both linearly and quadratically with an arbitrary system. To determine the bath coupling descriptors, we propose a physical mapping scheme, together with the prescription reference invariance requirement. We then adopt a recently developed dissipaton equation of motion theory [R. X. Xu et al., Chin. J. Chem. Phys. 30, 395 (2017)], with the underlying statistical quasi-particle ("dissipaton") algebra being extended to the quadratic bath coupling. We report the numerical results on a two-level system dynamics and absorption and emission line shapes.

  10. QSPR models based on molecular mechanics and quantum chemical calculations. 2. Thermodynamic properties of alkanes, alcohols, polyols, and ethers

    DEFF Research Database (Denmark)

    Dyekjær, Jane Dannow; Jonsdottir, Svava Osk

    2003-01-01

    Quantitative Structure-Property Relationship (QSPR) models for prediction of various thermodynamic properties of simple organic compounds have been developed. A number of new descriptors are proposed and used alongside with descriptors available within the Codessa program. An important feature...... for alkanes, alcohols, diols, ethers, and oxyalcohols, including cyclic alkanes and alcohols. Several good models, having good predictability, have been developed. To enhance the applicability of the QSPR models, simpler expressions for each descriptor have also been developed. This allows for the prediction...

  11. Robust optimal control design using a differential game approach for open-loop linear quadratic descriptor systems

    NARCIS (Netherlands)

    Musthofa, M.W.; Salmah, S.; Engwerda, Jacob; Suparwanto, A.

    This paper studies the robust optimal control problem for descriptor systems. We applied differential game theory to solve the disturbance attenuation problem. The robust control problem was converted into a reduced ordinary zero-sum game. Within a linear quadratic setting, we solved the problem for

  12. Comparing Local Descriptors and Bags of Visual Words to Deep Convolutional Neural Networks for Plant Recognition

    NARCIS (Netherlands)

    Pawara, Pornntiwa; Okafor, Emmanuel; Surinta, Olarik; Schomaker, Lambertus; Wiering, Marco

    2017-01-01

    The use of machine learning and computer vision methods for recognizing different plants from images has attracted lots of attention from the community. This paper aims at comparing local feature descriptors and bags of visual words with different classifiers to deep convolutional neural networks

  13. A consistency assessment of coupled cohesive zone models for mixed-mode debonding problems

    Directory of Open Access Journals (Sweden)

    R. Dimitri

    2014-07-01

    Full Text Available Due to their simplicity, cohesive zone models (CZMs are very attractive to describe mixed-mode failure and debonding processes of materials and interfaces. Although a large number of coupled CZMs have been proposed, and despite the extensive related literature, little attention has been devoted to ensuring the consistency of these models for mixed-mode conditions, primarily in a thermodynamical sense. A lack of consistency may affect the local or global response of a mechanical system. This contribution deals with the consistency check for some widely used exponential and bilinear mixed-mode CZMs. The coupling effect on stresses and energy dissipation is first investigated and the path-dependance of the mixed-mode debonding work of separation is analitically evaluated. Analytical predictions are also compared with results from numerical implementations, where the interface is described with zero-thickness contact elements. A node-to-segment strategy is here adopted, which incorporates decohesion and contact within a unified framework. A new thermodynamically consistent mixed-mode CZ model based on a reformulation of the Xu-Needleman model as modified by van den Bosch et al. is finally proposed and derived by applying the Coleman and Noll procedure in accordance with the second law of thermodynamics. The model holds monolithically for loading and unloading processes, as well as for decohesion and contact, and its performance is demonstrated through suitable examples.

  14. A new self-consistent model for thermodynamics of binary solutions

    Czech Academy of Sciences Publication Activity Database

    Svoboda, Jiří; Shan, Y. V.; Fischer, F. D.

    2015-01-01

    Roč. 108, NOV (2015), s. 27-30 ISSN 1359-6462 R&D Projects: GA ČR(CZ) GA14-24252S Institutional support: RVO:68081723 Keywords : Thermodynamics * Analytical methods * CALPHAD * Phase diagram * Self-consistent model Subject RIV: BJ - Thermodynamics Impact factor: 3.305, year: 2015

  15. An information retrieval system using weighted descriptors generated by automatic frequency counting

    International Nuclear Information System (INIS)

    Komatsubara, Yasutoshi

    1979-01-01

    An information retrieval system with improved relevance is described, in which a weighted descriptor file, generated by feedback of requester's relevance judgement on pretest results, is used. This method does not need modification of search formulas, and works better by only setting weight thresholds, and can alleviate searcher duties, as examples show. Index word weighting and retrieval word weighting are compared and some problems to be encountered when retrieval word weighting is combined to operational systems are pointed out. (author)

  16. Genetic algorithm as a variable selection procedure for the simulation of 13C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression.

    Science.gov (United States)

    Ghavami, Raoof; Najafi, Amir; Sajadi, Mohammad; Djannaty, Farhad

    2008-09-01

    In order to accurately simulate (13)C NMR spectra of hydroxy, polyhydroxy and methoxy substituted flavonoid a quantitative structure-property relationship (QSPR) model, relating atom-based calculated descriptors to (13)C NMR chemical shifts (ppm, TMS=0), is developed. A dataset consisting of 50 flavonoid derivatives was employed for the present analysis. A set of 417 topological, geometrical, and electronic descriptors representing various structural characteristics was calculated and separate multilinear QSPR models were developed between each carbon atom of flavonoid and the calculated descriptors. Genetic algorithm (GA) and multiple linear regression analysis (MLRA) were used to select the descriptors and to generate the correlation models. Analysis of the results revealed a correlation coefficient and root mean square error (RMSE) of 0.994 and 2.53ppm, respectively, for the prediction set.

  17. Self-consistent nonlinearly polarizable shell-model dynamics for ferroelectric materials

    International Nuclear Information System (INIS)

    Mkam Tchouobiap, S.E.; Kofane, T.C.; Ngabireng, C.M.

    2002-11-01

    We investigate the dynamical properties of the polarizable shellmodel with a symmetric double Morse-type electron-ion interaction in one ionic species. A variational calculation based on the Self-Consistent Einstein Model (SCEM) shows that a theoretical ferroelectric (FE) transition temperature can be derive which demonstrates the presence of a first-order phase transition for the potassium selenate (K 2 SeO 4 ) crystal around Tc 91.5 K. Comparison of the model calculation with the experimental critical temperature yields satisfactory agreement. (author)

  18. A consistent modelling methodology for secondary settling tanks in wastewater treatment.

    Science.gov (United States)

    Bürger, Raimund; Diehl, Stefan; Nopens, Ingmar

    2011-03-01

    The aim of this contribution is partly to build consensus on a consistent modelling methodology (CMM) of complex real processes in wastewater treatment by combining classical concepts with results from applied mathematics, and partly to apply it to the clarification-thickening process in the secondary settling tank. In the CMM, the real process should be approximated by a mathematical model (process model; ordinary or partial differential equation (ODE or PDE)), which in turn is approximated by a simulation model (numerical method) implemented on a computer. These steps have often not been carried out in a correct way. The secondary settling tank was chosen as a case since this is one of the most complex processes in a wastewater treatment plant and simulation models developed decades ago have no guarantee of satisfying fundamental mathematical and physical properties. Nevertheless, such methods are still used in commercial tools to date. This particularly becomes of interest as the state-of-the-art practice is moving towards plant-wide modelling. Then all submodels interact and errors propagate through the model and severely hamper any calibration effort and, hence, the predictive purpose of the model. The CMM is described by applying it first to a simple conversion process in the biological reactor yielding an ODE solver, and then to the solid-liquid separation in the secondary settling tank, yielding a PDE solver. Time has come to incorporate established mathematical techniques into environmental engineering, and wastewater treatment modelling in particular, and to use proven reliable and consistent simulation models. Copyright © 2011 Elsevier Ltd. All rights reserved.

  19. Detecting consistent patterns of directional adaptation using differential selection codon models.

    Science.gov (United States)

    Parto, Sahar; Lartillot, Nicolas

    2017-06-23

    Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

  20. Detection and quantification of flow consistency in business process models

    DEFF Research Database (Denmark)

    Burattin, Andrea; Bernstein, Vered; Neurauter, Manuel

    2017-01-01

    , to show how such features can be quantified into computational metrics, which are applicable to business process models. We focus on one particular feature, consistency of flow direction, and show the challenges that arise when transforming it into a precise metric. We propose three different metrics......Business process models abstract complex business processes by representing them as graphical models. Their layout, as determined by the modeler, may have an effect when these models are used. However, this effect is currently not fully understood. In order to systematically study this effect......, a basic set of measurable key visual features is proposed, depicting the layout properties that are meaningful to the human user. The aim of this research is thus twofold: first, to empirically identify key visual features of business process models which are perceived as meaningful to the user and second...

  1. Impact of the removal of light and mild descriptors from cigarette packages in Ontario, Canada: switching to "light replacement" brand variants.

    Science.gov (United States)

    Cohen, Joanna E; Yang, Jingyan; Donaldson, Elisabeth A

    2014-12-01

    This study assessed cessation and brand switching among smokers in Ontario, Canada after tobacco companies' voluntary removal of 'light' and 'mild' descriptors from cigarette packages. We analyzed longitudinal data on brand preference and cessation from a cohort of smokers (n=632) in the Ontario Tobacco Survey in Canada from 2006 to 2008 with a longitudinal regression model. While cessation differed by brand variant prior to the ban (7% light vs. 3% regular; Pbrand variant after the ban was implemented. In 2008, when light cigarette brand variants were no longer available, 33% of the sample still reported smoking lights and 31% smoked light replacement brand variants. During each subsequent follow-up, light brand smokers had 2 times the odds of smoking regular brand variants (Adjusted OR: 2.03, 95% CI 1.80,2.29), and almost 5 times the odds of using light replacement brand variants (Adjusted OR: 4.87, 95% CI 4.07,5.84), respectively, compared to continuing to smoke lights. Even after removing misleading descriptors from cigarette packs, smokers continued to report using light brand variants, and many switched to newly introduced light replacement brand variants. After full implementation of the ban, cessation did not vary by brand variant. Copyright © 2014. Published by Elsevier Inc.

  2. Descriptors used to define running-related musculoskeletal injury: a systematic review.

    Science.gov (United States)

    Yamato, Tiê Parma; Saragiotto, Bruno Tirotti; Hespanhol Junior, Luiz Carlos; Yeung, Simon S; Lopes, Alexandre Dias

    2015-05-01

    Systematic review. To systematically review the descriptors used to define running-related musculoskeletal injury and to analyze the implications of different definitions on the results of studies. Studies have developed their own definitions of running-related musculoskeletal injuries based on different criteria. This may affect the rates of injury, which can be overestimated or underestimated due to the lack of a standard definition. Searches were conducted in the Embase, PubMed, CINAHL, SPORTDiscus, LILACS, and SciELO databases, without limits on date of publication and language. Only articles that reported a definition of running-related injury were included. The definitions were classified according to 3 domains and subcategories: (1) presence of physical complaint (symptom, body system involved, region), (2) interruption of training or competition (primary sports involved, extent of injury, extent of limitation, interruption, period of injury), and (3) need for medical assistance. Spearman rank correlation was performed to evaluate the correlation between the completeness of definitions and the rates of injury reported in the studies. A total of 48 articles were included. Most studies described more than half of the subcategories, but with no standardization between the terms used within each category, showing that there is no consensus for a definition. The injury rates ranged between 3% and 85%, and tended to increase with less specific definitions. The descriptors commonly used by researchers to define a running-related injury vary between studies and may affect the rates of injuries. The lack of a standardized definition hinders comparison between studies and rates of injuries.

  3. Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure

    Directory of Open Access Journals (Sweden)

    Yong-Hong Zhang

    2015-05-01

    Full Text Available Assessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfusion is the most widely used method. In this study, the partial least squares (PLS variable selection and modeling procedure was used to pick out optimal descriptors from a pool of 620 descriptors of 65 compounds and to simultaneously develop a QSAR model between the descriptors and the placental barrier permeability expressed by the clearance indices (CI. The model was subjected to internal validation by cross-validation and y-randomization and to external validation by predicting CI values of 19 compounds. It was shown that the model developed is robust and has a good predictive potential (r2 = 0.9064, RMSE = 0.09, q2 = 0.7323, rp2 = 0.7656, RMSP = 0.14. The mechanistic interpretation of the final model was given by the high variable importance in projection values of descriptors. Using PLS procedure, we can rapidly and effectively select optimal descriptors and thus construct a model with good stability and predictability. This analysis can provide an effective tool for the high-throughput screening of the placental barrier permeability of drugs.

  4. Self-consistent collisional-radiative model for hydrogen atoms: Atom–atom interaction and radiation transport

    International Nuclear Information System (INIS)

    Colonna, G.; Pietanza, L.D.; D’Ammando, G.

    2012-01-01

    Graphical abstract: Self-consistent coupling between radiation, state-to-state kinetics, electron kinetics and fluid dynamics. Highlight: ► A CR model of shock-wave in hydrogen plasma has been presented. ► All equations have been coupled self-consistently. ► Non-equilibrium electron and level distributions are obtained. ► The results show non-local effects and non-equilibrium radiation. - Abstract: A collisional-radiative model for hydrogen atom, coupled self-consistently with the Boltzmann equation for free electrons, has been applied to model a shock tube. The kinetic model has been completed considering atom–atom collisions and the vibrational kinetics of the ground state of hydrogen molecules. The atomic level kinetics has been also coupled with a radiative transport equation to determine the effective adsorption and emission coefficients and non-local energy transfer.

  5. Requirements for UML and OWL Integration Tool for User Data Consistency Modeling and Testing

    DEFF Research Database (Denmark)

    Nytun, J. P.; Jensen, Christian Søndergaard; Oleshchuk, V. A.

    2003-01-01

    The amount of data available on the Internet is continuously increasing, consequentially there is a growing need for tools that help to analyse the data. Testing of consistency among data received from different sources is made difficult by the number of different languages and schemas being used....... In this paper we analyze requirements for a tool that support integration of UML models and ontologies written in languages like the W3C Web Ontology Language (OWL). The tool can be used in the following way: after loading two legacy models into the tool, the tool user connects them by inserting modeling......, an important part of this technique is attaching of OCL expressions to special boolean class attributes that we call consistency attributes. The resulting integration model can be used for automatic consistency testing of two instances of the legacy models by automatically instantiate the whole integration...

  6. Composite multi-lobe descriptor for cross spectral face recognition: matching active IR to visible light images

    Science.gov (United States)

    Cao, Zhicheng; Schmid, Natalia A.

    2015-05-01

    Matching facial images across electromagnetic spectrum presents a challenging problem in the field of biometrics and identity management. An example of this problem includes cross spectral matching of active infrared (IR) face images or thermal IR face images against a dataset of visible light images. This paper describes a new operator named Composite Multi-Lobe Descriptor (CMLD) for facial feature extraction in cross spectral matching of near-infrared (NIR) or short-wave infrared (SWIR) against visible light images. The new operator is inspired by the design of ordinal measures. The operator combines Gaussian-based multi-lobe kernel functions, Local Binary Pattern (LBP), generalized LBP (GLBP) and Weber Local Descriptor (WLD) and modifies them into multi-lobe functions with smoothed neighborhoods. The new operator encodes both the magnitude and phase responses of Gabor filters. The combining of LBP and WLD utilizes both the orientation and intensity information of edges. Introduction of multi-lobe functions with smoothed neighborhoods further makes the proposed operator robust against noise and poor image quality. Output templates are transformed into histograms and then compared by means of a symmetric Kullback-Leibler metric resulting in a matching score. The performance of the multi-lobe descriptor is compared with that of other operators such as LBP, Histogram of Oriented Gradients (HOG), ordinal measures, and their combinations. The experimental results show that in many cases the proposed method, CMLD, outperforms the other operators and their combinations. In addition to different infrared spectra, various standoff distances from close-up (1.5 m) to intermediate (50 m) and long (106 m) are also investigated in this paper. Performance of CMLD is evaluated for of each of the three cases of distances.

  7. A Consistent Pricing Model for Index Options and Volatility Derivatives

    DEFF Research Database (Denmark)

    Kokholm, Thomas

    to be priced consistently, while allowing for jumps in volatility and returns. An affine specification using Lévy processes as building blocks leads to analytically tractable pricing formulas for volatility derivatives, such as VIX options, as well as efficient numerical methods for pricing of European options...... on the underlying asset. The model has the convenient feature of decoupling the vanilla skews from spot/volatility correlations and allowing for different conditional correlations in large and small spot/volatility moves. We show that our model can simultaneously fit prices of European options on S&P 500 across...

  8. A Consistent Pricing Model for Index Options and Volatility Derivatives

    DEFF Research Database (Denmark)

    Cont, Rama; Kokholm, Thomas

    2013-01-01

    to be priced consistently, while allowing for jumps in volatility and returns. An affine specification using Lévy processes as building blocks leads to analytically tractable pricing formulas for volatility derivatives, such as VIX options, as well as efficient numerical methods for pricing of European options...... on the underlying asset. The model has the convenient feature of decoupling the vanilla skews from spot/volatility correlations and allowing for different conditional correlations in large and small spot/volatility moves. We show that our model can simultaneously fit prices of European options on S&P 500 across...

  9. Development of a Model for Dynamic Recrystallization Consistent with the Second Derivative Criterion

    Directory of Open Access Journals (Sweden)

    Muhammad Imran

    2017-11-01

    Full Text Available Dynamic recrystallization (DRX processes are widely used in industrial hot working operations, not only to keep the forming forces low but also to control the microstructure and final properties of the workpiece. According to the second derivative criterion (SDC by Poliak and Jonas, the onset of DRX can be detected from an inflection point in the strain-hardening rate as a function of flow stress. Various models are available that can predict the evolution of flow stress from incipient plastic flow up to steady-state deformation in the presence of DRX. Some of these models have been implemented into finite element codes and are widely used for the design of metal forming processes, but their consistency with the SDC has not been investigated. This work identifies three sources of inconsistencies that models for DRX may exhibit. For a consistent modeling of the DRX kinetics, a new strain-hardening model for the hardening stages III to IV is proposed and combined with consistent recrystallization kinetics. The model is devised in the Kocks-Mecking space based on characteristic transition in the strain-hardening rate. A linear variation of the transition and inflection points is observed for alloy 800H at all tested temperatures and strain rates. The comparison of experimental and model results shows that the model is able to follow the course of the strain-hardening rate very precisely, such that highly accurate flow stress predictions are obtained.

  10. Self-consistent model calculations of the ordered S-matrix and the cylinder correction

    International Nuclear Information System (INIS)

    Millan, J.

    1977-11-01

    The multiperipheral ordered bootstrap of Rosenzweig and Veneziano is studied by using dual triple Regge couplings exhibiting the required threshold behavior. In the interval -0.5 less than or equal to t less than or equal to 0.8 GeV 2 self-consistent reggeon couplings and propagators are obtained for values of Regge slopes and intercepts consistent with the physical values for the leading natural-parity Regge trajectories. Cylinder effects on planar pole positions and couplings are calculated. By use of an unsymmetrical planar π--rho reggeon loop model, self-consistent solutions are obtained for the unnatural-parity mesons in the interval -0.5 less than or equal to t less than or equal to 0.6 GeV 2 . The effects of other Regge poles being neglected, the model gives a value of the π--eta splitting consistent with experiment. 24 figures, 1 table, 25 references

  11. EVALUATION OF PHOTOGRAMMETRIC BLOCK ORIENTATION USING QUALITY DESCRIPTORS FROM STATISTICALLY FILTERED TIE POINTS

    Directory of Open Access Journals (Sweden)

    A. Calantropio

    2018-05-01

    Full Text Available Due to the increasing number of low-cost sensors, widely accessible on the market, and because of the supposed granted correctness of the semi-automatic workflow for 3D reconstruction, highly implemented in the recent commercial software, more and more users operate nowadays without following the rigorousness of classical photogrammetric methods. This behaviour often naively leads to 3D products that lacks metric quality assessment. This paper proposes and analyses an approach that gives the users the possibility to preserve the trustworthiness of the metric information inherent in the 3D model, without sacrificing the automation offered by modern photogrammetry software. At the beginning, the importance of Data Quality Assessment is outlined, together with some recall of photogrammetry best practices. With the purpose of guiding the user through a correct pipeline for a certified 3D model reconstruction, an operative workflow is proposed, focusing on the first part of the object reconstruction steps (tie-points extraction, camera calibration, and relative orientation. A new GUI (Graphical User Interface developed for the open source MicMac suite is then presented, and a sample dataset is used for the evaluation of the photogrammetric block orientation using statistically obtained quality descriptors. The results and the future directions are then presented and discussed.

  12. Thermodynamically consistent model of brittle oil shales under overpressure

    Science.gov (United States)

    Izvekov, Oleg

    2016-04-01

    The concept of dual porosity is a common way for simulation of oil shale production. In the frame of this concept the porous fractured media is considered as superposition of two permeable continua with mass exchange. As a rule the concept doesn't take into account such as the well-known phenomenon as slip along natural fractures, overpressure in low permeability matrix and so on. Overpressure can lead to development of secondary fractures in low permeability matrix in the process of drilling and pressure reduction during production. In this work a new thermodynamically consistent model which generalizes the model of dual porosity is proposed. Particularities of the model are as follows. The set of natural fractures is considered as permeable continuum. Damage mechanics is applied to simulation of secondary fractures development in low permeability matrix. Slip along natural fractures is simulated in the frame of plasticity theory with Drucker-Prager criterion.

  13. A consistent modelling methodology for secondary settling tanks: a reliable numerical method.

    Science.gov (United States)

    Bürger, Raimund; Diehl, Stefan; Farås, Sebastian; Nopens, Ingmar; Torfs, Elena

    2013-01-01

    The consistent modelling methodology for secondary settling tanks (SSTs) leads to a partial differential equation (PDE) of nonlinear convection-diffusion type as a one-dimensional model for the solids concentration as a function of depth and time. This PDE includes a flux that depends discontinuously on spatial position modelling hindered settling and bulk flows, a singular source term describing the feed mechanism, a degenerating term accounting for sediment compressibility, and a dispersion term for turbulence. In addition, the solution itself is discontinuous. A consistent, reliable and robust numerical method that properly handles these difficulties is presented. Many constitutive relations for hindered settling, compression and dispersion can be used within the model, allowing the user to switch on and off effects of interest depending on the modelling goal as well as investigate the suitability of certain constitutive expressions. Simulations show the effect of the dispersion term on effluent suspended solids and total sludge mass in the SST. The focus is on correct implementation whereas calibration and validation are not pursued.

  14. Signature molecular descriptor : advanced applications.

    Energy Technology Data Exchange (ETDEWEB)

    Visco, Donald Patrick, Jr. (Tennessee Technological University, Cookeville, TN)

    2010-04-01

    In this work we report on the development of the Signature Molecular Descriptor (or Signature) for use in the solution of inverse design problems as well as in highthroughput screening applications. The ultimate goal of using Signature is to identify novel and non-intuitive chemical structures with optimal predicted properties for a given application. We demonstrate this in three studies: green solvent design, glucocorticoid receptor ligand design and the design of inhibitors for Factor XIa. In many areas of engineering, compounds are designed and/or modified in incremental ways which rely upon heuristics or institutional knowledge. Often multiple experiments are performed and the optimal compound is identified in this brute-force fashion. Perhaps a traditional chemical scaffold is identified and movement of a substituent group around a ring constitutes the whole of the design process. Also notably, a chemical being evaluated in one area might demonstrate properties very attractive in another area and serendipity was the mechanism for solution. In contrast to such approaches, computer-aided molecular design (CAMD) looks to encompass both experimental and heuristic-based knowledge into a strategy that will design a molecule on a computer to meet a given target. Depending on the algorithm employed, the molecule which is designed might be quite novel (re: no CAS registration number) and/or non-intuitive relative to what is known about the problem at hand. While CAMD is a fairly recent strategy (dating to the early 1980s), it contains a variety of bottlenecks and limitations which have prevented the technique from garnering more attention in the academic, governmental and industrial institutions. A main reason for this is how the molecules are described in the computer. This step can control how models are developed for the properties of interest on a given problem as well as how to go from an output of the algorithm to an actual chemical structure. This report

  15. Creation of Consistent Burn Wounds: A Rat Model

    Directory of Open Access Journals (Sweden)

    Elijah Zhengyang Cai

    2014-07-01

    Full Text Available Background Burn infliction techniques are poorly described in rat models. An accurate study can only be achieved with wounds that are uniform in size and depth. We describe a simple reproducible method for creating consistent burn wounds in rats. Methods Ten male Sprague-Dawley rats were anesthetized and dorsum shaved. A 100 g cylindrical stainless-steel rod (1 cm diameter was heated to 100℃ in boiling water. Temperature was monitored using a thermocouple. We performed two consecutive toe-pinch tests on different limbs to assess the depth of sedation. Burn infliction was limited to the loin. The skin was pulled upwards, away from the underlying viscera, creating a flat surface. The rod rested on its own weight for 5, 10, and 20 seconds at three different sites on each rat. Wounds were evaluated for size, morphology and depth. Results Average wound size was 0.9957 cm2 (standard deviation [SD] 0.1845 (n=30. Wounds created with duration of 5 seconds were pale, with an indistinct margin of erythema. Wounds of 10 and 20 seconds were well-defined, uniformly brown with a rim of erythema. Average depths of tissue damage were 1.30 mm (SD 0.424, 2.35 mm (SD 0.071, and 2.60 mm (SD 0.283 for duration of 5, 10, 20 seconds respectively. Burn duration of 5 seconds resulted in full-thickness damage. Burn duration of 10 seconds and 20 seconds resulted in full-thickness damage, involving subjacent skeletal muscle. Conclusions This is a simple reproducible method for creating burn wounds consistent in size and depth in a rat burn model.

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

    Directory of Open Access Journals (Sweden)

    Gutierrez J. A.

    2004-04-01

    Full Text Available Se cuantificó la variabilidad genética de una muestra de 116 accesiones de habichuela P. vulgaris, cultivadas en centros primarios y secundarios de domesticación. Se evaluaron 18 descriptores morfo-agronómicos asociados con características de la planta, vaina y semilla. Mediante el análisis de las faseolinas utilizando SDS-PAGE se encontraron patrones de bandas de origen andino (T, C y H1 y mesoamericano [S, Sb, CH y H(S+I]. También se evaluaron ocho sistemas isoenzimáticos polimórficos. En el germoplasma de habichuela hay importante contribución del acervo mesoamericano y las accesiones en algunos centros secundarios de domesticación tuvieron origen y procesos de dispersión diferentes de los del fríjol común en tales zonas. La mayor variabilidad morfológica y el mayor número de accesiones con características deseables para el mercado fresco se encontró en el grupo mesoamericano. Se detectó mayor número de genotipos híbridos entre acervos cuando se utilizaron simultáneamente los tres descriptores, lo cual indica una estructura genética compleja que podría deberse al efecto de los factores ambientales propios de la zona templada sobre sus patrones reproductivos. La diversidad total medida con los tres descriptores fue similar a la registrada en fríjol común. Sin embargo, la estructura poblacional encontrada por otros autores en el fríjol común es diferente de la observada en este estudio. Palabras claves: Variabilidad, descriptores morfológicos, isoenzimas, proteínas de semilla, acervos genéticos. ABSTRACT Genetic variability of 116 accesions of Phaseolus vulgaris showing snap beans characteristics coming from primary and secondary centers of domestication, were studied using eighteen morphological descriptors to characterize pods and seeds, SDS-PAGE analysis of seed phaseolins and eight isozyme systems. Higher morphological diversity and best pod marketing characteristics were found at Andean accessions

  17. A consistent transported PDF model for treating differential molecular diffusion

    Science.gov (United States)

    Wang, Haifeng; Zhang, Pei

    2016-11-01

    Differential molecular diffusion is a fundamentally significant phenomenon in all multi-component turbulent reacting or non-reacting flows caused by the different rates of molecular diffusion of energy and species concentrations. In the transported probability density function (PDF) method, the differential molecular diffusion can be treated by using a mean drift model developed by McDermott and Pope. This model correctly accounts for the differential molecular diffusion in the scalar mean transport and yields a correct DNS limit of the scalar variance production. The model, however, misses the molecular diffusion term in the scalar variance transport equation, which yields an inconsistent prediction of the scalar variance in the transported PDF method. In this work, a new model is introduced to remedy this problem that can yield a consistent scalar variance prediction. The model formulation along with its numerical implementation is discussed, and the model validation is conducted in a turbulent mixing layer problem.

  18. Comparison of Multi-shot Models for Short-term Re-identification of People using RGB-D Sensors

    DEFF Research Database (Denmark)

    Møgelmose, Andreas; Bahnsen, Chris; Moeslund, Thomas B.

    2015-01-01

    This work explores different types of multi-shot descriptors for re-identification in an on-the-fly enrolled environment using RGB-D sensors. We present a full re-identification pipeline complete with detection, segmentation, feature extraction, and re-identification, which expands on previous work...... by using multi-shot descriptors modeling people over a full camera pass instead of single frames with no temporal linking. We compare two different multi-shot models; mean histogram and histogram series, and test them each in 3 different color spaces. Both histogram descriptors are assisted by a depth...

  19. A self-consistent model of an isothermal tokamak

    Science.gov (United States)

    McNamara, Steven; Lilley, Matthew

    2014-10-01

    Continued progress in liquid lithium coating technologies have made the development of a beam driven tokamak with minimal edge recycling a feasibly possibility. Such devices are characterised by improved confinement due to their inherent stability and the suppression of thermal conduction. Particle and energy confinement become intrinsically linked and the plasma thermal energy content is governed by the injected beam. A self-consistent model of a purely beam fuelled isothermal tokamak is presented, including calculations of the density profile, bulk species temperature ratios and the fusion output. Stability considerations constrain the operating parameters and regions of stable operation are identified and their suitability to potential reactor applications discussed.

  20. Modelling of the effect of solute structure and mobile phase pH and composition on the retention of phenoxy acid herbicides in reversed-phase high-performance liquid chromatography

    International Nuclear Information System (INIS)

    Aschi, Massimiliano; D'Archivio, Angelo Antonio; Mazzeo, Pietro; Pierabella, Mirko; Ruggieri, Fabrizio

    2008-01-01

    A feed-forward artificial neural network (ANN) learned by error back-propagation is used to generate a retention predictive model for phenoxy acid herbicides in isocratic reversed-phase high-performance liquid chromatography. The investigated solutes (18 compounds), apart from the most common herbicides of this class, include some derivatives of benzoic acid and phenylacetic acid structurally related to phenoxy acids, as a whole covering a pK a range between 2.3 and 4.3. A mixed model in terms of both solute descriptors and eluent attributes is built with the aim of predicting retention in water-acetonitrile mobile phases within a large range of composition (acetonitrile from 30% to 70%, v/v) and acidity (pH of water before mixing with acetonitrile ranging between 2 and 5). The set of input variables consists of solute pK a and quantum chemical molecular descriptors of both the neutral and dissociated form, %v/v of acetonitrile in the mobile phase and pH of aqueous phase before mixing with acetonitrile. After elimination of redundant variables, a nine-dimensional model is identified and its prediction ability is evaluated by external validation based on three solutes not involved in model generation and by cross-validation. A multilinear counterpart in terms of the same descriptors is seen to provide a noticeably poorer retention prediction

  1. Modelling of the effect of solute structure and mobile phase pH and composition on the retention of phenoxy acid herbicides in reversed-phase high-performance liquid chromatography

    Energy Technology Data Exchange (ETDEWEB)

    Aschi, Massimiliano [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy); 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; Mazzeo, Pietro; Pierabella, Mirko; Ruggieri, Fabrizio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)

    2008-06-02

    A feed-forward artificial neural network (ANN) learned by error back-propagation is used to generate a retention predictive model for phenoxy acid herbicides in isocratic reversed-phase high-performance liquid chromatography. The investigated solutes (18 compounds), apart from the most common herbicides of this class, include some derivatives of benzoic acid and phenylacetic acid structurally related to phenoxy acids, as a whole covering a pK{sub a} range between 2.3 and 4.3. A mixed model in terms of both solute descriptors and eluent attributes is built with the aim of predicting retention in water-acetonitrile mobile phases within a large range of composition (acetonitrile from 30% to 70%, v/v) and acidity (pH of water before mixing with acetonitrile ranging between 2 and 5). The set of input variables consists of solute pK{sub a} and quantum chemical molecular descriptors of both the neutral and dissociated form, %v/v of acetonitrile in the mobile phase and pH of aqueous phase before mixing with acetonitrile. After elimination of redundant variables, a nine-dimensional model is identified and its prediction ability is evaluated by external validation based on three solutes not involved in model generation and by cross-validation. A multilinear counterpart in terms of the same descriptors is seen to provide a noticeably poorer retention prediction.

  2. QSPR Models for Predicting Log Pliver Values for Volatile Organic Compounds Combining Statistical Methods and Domain Knowledge

    Directory of Open Access Journals (Sweden)

    Mónica F. Díaz

    2012-12-01

    Full Text Available Volatile organic compounds (VOCs are contained in a variety of chemicals that can be found in household products and may have undesirable effects on health. Thereby, it is important to model blood-to-liver partition coefficients (log Pliver for VOCs in a fast and inexpensive way. In this paper, we present two new quantitative structure-property relationship (QSPR models for the prediction of log Pliver, where we also propose a hybrid approach for the selection of the descriptors. This hybrid methodology combines a machine learning method with a manual selection based on expert knowledge. This allows obtaining a set of descriptors that is interpretable in physicochemical terms. Our regression models were trained using decision trees and neural networks and validated using an external test set. Results show high prediction accuracy compared to previous log Pliver models, and the descriptor selection approach provides a means to get a small set of descriptors that is in agreement with theoretical understanding of the target property.

  3. Scale Invariant Gabor Descriptor-Based Noncooperative Iris Recognition

    Directory of Open Access Journals (Sweden)

    Du Yingzi

    2010-01-01

    Full Text Available Abstract A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and low-resolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT for feature extraction to better extract the iris features. Both the phase and magnitude of the Gabor wavelet outputs were used in a novel way for local feature point description. Two feature region maps were designed to locally and globally register the feature points and each subregion in the map is locally adjusted to the dilation/contraction/deformation. We also developed a video-based non-cooperative iris recognition system by integrating video-based non-cooperative segmentation, segmentation evaluation, and score fusion units. The proposed method shows good performance for frontal and off-angle iris matching. Video-based recognition methods can improve non-cooperative iris recognition accuracy.

  4. Scale Invariant Gabor Descriptor-based Noncooperative Iris Recognition

    Directory of Open Access Journals (Sweden)

    Zhi Zhou

    2010-01-01

    Full Text Available A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and low-resolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT for feature extraction to better extract the iris features. Both the phase and magnitude of the Gabor wavelet outputs were used in a novel way for local feature point description. Two feature region maps were designed to locally and globally register the feature points and each subregion in the map is locally adjusted to the dilation/contraction/deformation. We also developed a video-based non-cooperative iris recognition system by integrating video-based non-cooperative segmentation, segmentation evaluation, and score fusion units. The proposed method shows good performance for frontal and off-angle iris matching. Video-based recognition methods can improve non-cooperative iris recognition accuracy.

  5. Relations between water physico-chemistry and benthic algal communities in a northern Canadian watershed: defining reference conditions using multiple descriptors of community structure.

    Science.gov (United States)

    Thomas, Kathryn E; Hall, Roland I; Scrimgeour, Garry J

    2015-09-01

    Defining reference conditions is central to identifying environmental effects of anthropogenic activities. Using a watershed approach, we quantified reference conditions for benthic algal communities and their relations to physico-chemical conditions in rivers in the South Nahanni River watershed, NWT, Canada, in 2008 and 2009. We also compared the ability of three descriptors that vary in terms of analytical costs to define algal community structure based on relative abundances of (i) all algal taxa, (ii) only diatom taxa, and (iii) photosynthetic pigments. Ordination analyses showed that variance in algal community structure was strongly related to gradients in environmental variables describing water physico-chemistry, stream habitats, and sub-watershed structure. Water physico-chemistry and local watershed-scale descriptors differed significantly between algal communities from sites in the Selwyn Mountain ecoregion compared to sites in the Nahanni-Hyland ecoregions. Distinct differences in algal community types between ecoregions were apparent irrespective of whether algal community structure was defined using all algal taxa, diatom taxa, or photosynthetic pigments. Two algal community types were highly predictable using environmental variables, a core consideration in the development of Reference Condition Approach (RCA) models. These results suggest that assessments of environmental impacts could be completed using RCA models for each ecoregion. We suggest that use of algal pigments, a high through-put analysis, is a promising alternative compared to more labor-intensive and costly taxonomic approaches for defining algal community structure.

  6. Texture Retrieval from VHR Optical Remote Sensed Images Using the Local Extrema Descriptor with Application to Vineyard Parcel Detection

    Directory of Open Access Journals (Sweden)

    Minh-Tan Pham

    2016-04-01

    Full Text Available In this article, we develop a novel method for the detection of vineyard parcels in agricultural landscapes based on very high resolution (VHR optical remote sensing images. Our objective is to perform texture-based image retrieval and supervised classification algorithms. To do that, the local textural and structural features inside each image are taken into account to measure its similarity to other images. In fact, VHR images usually involve a variety of local textures and structures that may verify a weak stationarity hypothesis. Hence, an approach only based on characteristic points, not on all pixels of the image, is supposed to be relevant. This work proposes to construct the local extrema-based descriptor (LED by using the local maximum and local minimum pixels extracted from the image. The LED descriptor is formed based on the radiometric, geometric and gradient features from these local extrema. We first exploit the proposed LED descriptor for the retrieval task to evaluate its performance on texture discrimination. Then, it is embedded into a supervised classification framework to detect vine parcels using VHR satellite images. Experiments performed on VHR panchromatic PLEIADES image data prove the effectiveness of the proposed strategy. Compared to state-of-the-art methods, an enhancement of about 7% in retrieval rate is achieved. For the detection task, about 90% of vineyards are correctly detected.

  7. Replacement method and enhanced replacement method versus the genetic algorithm approach for the selection of molecular descriptors in QSPR/QSAR theories.

    Science.gov (United States)

    Mercader, Andrew G; Duchowicz, Pablo R; Fernández, Francisco M; Castro, Eduardo A

    2010-09-27

    We compare three methods for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. On the one hand is our enhanced replacement method (ERM) and on the other is the simpler replacement method (RM) and the genetic algorithm (GA). These methods avoid the impracticable full search for optimal variables in large sets of molecular descriptors. Present results for 10 different experimental databases suggest that the ERM is clearly preferable to the GA that is slightly better than the RM. However, the latter approach requires the smallest amount of linear regressions and, consequently, the lowest computation time.

  8. Towards an Information Model of Consistency Maintenance in Distributed Interactive Applications

    Directory of Open Access Journals (Sweden)

    Xin Zhang

    2008-01-01

    Full Text Available A novel framework to model and explore predictive contract mechanisms in distributed interactive applications (DIAs using information theory is proposed. In our model, the entity state update scheme is modelled as an information generation, encoding, and reconstruction process. Such a perspective facilitates a quantitative measurement of state fidelity loss as a result of the distribution protocol. Results from an experimental study on a first-person shooter game are used to illustrate the utility of this measurement process. We contend that our proposed model is a starting point to reframe and analyse consistency maintenance in DIAs as a problem in distributed interactive media compression.

  9. A Consistent Pricing Model for Index Options and Volatility Derivatives

    DEFF Research Database (Denmark)

    Cont, Rama; Kokholm, Thomas

    observed properties of variance swap dynamics and allows for jumps in volatility and returns. An affine specification using L´evy processes as building blocks leads to analytically tractable pricing formulas for options on variance swaps as well as efficient numerical methods for pricing of European......We propose and study a flexible modeling framework for the joint dynamics of an index and a set of forward variance swap rates written on this index, allowing options on forward variance swaps and options on the underlying index to be priced consistently. Our model reproduces various empirically...... options on the underlying asset. The model has the convenient feature of decoupling the vanilla skews from spot/volatility correlations and allowing for different conditional correlations in large and small spot/volatility moves. We show that our model can simultaneously fit prices of European options...

  10. A non-parametric consistency test of the ΛCDM model with Planck CMB data

    Energy Technology Data Exchange (ETDEWEB)

    Aghamousa, Amir; Shafieloo, Arman [Korea Astronomy and Space Science Institute, Daejeon 305-348 (Korea, Republic of); Hamann, Jan, E-mail: amir@aghamousa.com, E-mail: jan.hamann@unsw.edu.au, E-mail: shafieloo@kasi.re.kr [School of Physics, The University of New South Wales, Sydney NSW 2052 (Australia)

    2017-09-01

    Non-parametric reconstruction methods, such as Gaussian process (GP) regression, provide a model-independent way of estimating an underlying function and its uncertainty from noisy data. We demonstrate how GP-reconstruction can be used as a consistency test between a given data set and a specific model by looking for structures in the residuals of the data with respect to the model's best-fit. Applying this formalism to the Planck temperature and polarisation power spectrum measurements, we test their global consistency with the predictions of the base ΛCDM model. Our results do not show any serious inconsistencies, lending further support to the interpretation of the base ΛCDM model as cosmology's gold standard.

  11. High resolution MRI of the breast at 3 T: which BI-RADS registered descriptors are most strongly associated with the diagnosis of breast cancer?

    International Nuclear Information System (INIS)

    Pinker-Domenig, K.; Helbich, T.H.; Bogner, W.; Gruber, S.; Bickel, H.; Duffy, S.; Schernthaner, M.; Dubsky, P.; Pluschnig, U.; Rudas, M.; Trattnig, S.

    2012-01-01

    To identify which breast lesion descriptors in the ACR BI-RADS registered MRI lexicon are most strongly associated with the diagnosis of breast cancer when performing breast MR imaging at 3 T. 150 patients underwent breast MR imaging at 3 T. Lesion size, morphology and enhancement kinetics were assessed according to the BI-RADS registered classification. Sensitivity, specificity and diagnostic accuracy were assessed. The effects of the BI-RADS registered descriptors on sensitivity and specificity were evaluated. Data were analysed using logistic regression. Histopathological diagnoses were used as the standard of reference. The sensitivity, specificity and diagnostic accuracy of breast MRI at 3 T was 99%, 81% and 93%, respectively. In univariate analysis, the final diagnosis of malignancy was positively associated with irregular shape (p registered breast lesion descriptors that are mostly strongly associated with breast cancer in breast MR imaging at 3 T are lesion shape, lesion margin, internal enhancement pattern and Type 3 enhancement kinetics. (orig.)

  12. Modelos teóricos de gestión del conocimiento: descriptores, conceptualizaciones y enfoques

    Directory of Open Access Journals (Sweden)

    Víctor Avendaño Pérez

    2016-01-01

    Full Text Available Uno de los desafíos que enfrentan las organizaciones en la actualidad, consiste en transformar el conocimiento que cada individuo dispone en un conocimiento organizacional, y, a su vez, crear una cultura organizacional colaborativa que favorezca este proceso, para incrementar el patrimonio intelectual de la empresa. En este contexto, la gestión del conocimiento aparece como campo de estudio y estrategia organizacional: permite abordar estos retos; sin embargo, por su reciente aparición, aún los estudios y ensayos especializados son heterogéneos al respecto, en cuanto a sus conteni - dos. En este trabajo analizamos algunos modelos teóricos en función de descriptores y sus principales orientaciones; analizamos las definiciones de “conocimiento” y de “gestión de conocimiento”, ubicándolos en sus respectivos enfoques epistemológicos. Como principales resultados, se deduce que en los autores analizados predomina el enfoque objetivista del conocimiento, el enfoque organizacional de la gestión del conocimiento y la importancia de complementar el uso de las tecnologías de información y comunicación con la creación de un clima organizacional colaborativo para gestionar de forma óptima el conocimiento en las organizaciones.

  13. Contrast-enhanced spectral mammography: Impact of the qualitative morphology descriptors on the diagnosis of breast lesions

    International Nuclear Information System (INIS)

    Mohamed Kamal, Rasha; Hussien Helal, Maha; Wessam, Rasha; Mahmoud Mansour, Sahar; Godda, Iman; Alieldin, Nelly

    2015-01-01

    Highlights: • We studied interpretation criteria for enhancing lesions on CESM. • We evaluated the enhancement patterns of 211 breast lesions. • Our results proved that CESM minimized positive and negative falsies in DM. • The proposed CESM lexicon helped in characterization and categorization. - Abstract: Objective: To analyze the morphology and enhancement characteristics of breast lesions on contrast-enhanced spectral mammography (CESM) and to assess their impact on the differentiation between benign and malignant lesions. Materials and method: This ethics committee approved study included 168 consecutive patients with 211 breast lesions over 18 months. Lesions classified as non-enhancing and enhancing and then the latter group was subdivided into mass and non-mass. Mass lesions descriptors included: shape, margins, pattern and degree of internal enhancement. Non-mass lesions descriptors included: distribution, pattern and degree of internal enhancement. The impact of each descriptor on diagnosis individually assessed using Chi test and the validity compared in both benign and malignant lesions. The overall performance of CESM were also calculated. Results: The study included 102 benign (48.3%) and 109 malignant (51.7%) lesions. Enhancement was encountered in 145/211 (68.7%) lesions. They further classified into enhancing mass (99/145, 68.3%) and non-mass lesions (46/145, 31.7%). Contrast uptake was significantly more frequent in malignant breast lesions (p value ≤0.001). Irregular mass lesions with intense and heterogeneous enhancement patterns correlated with a malignant pathology (p value ≤0.001). CESM showed an overall sensitivity of 88.99% and specificity of 83.33%. The positive and negative likelihood ratios were 5.34 and 0.13 respectively. Conclusion: The assessment of the morphology and enhancement characteristics of breast lesions on CESM enhances the performance of digital mammography in the differentiation between benign and malignant

  14. Contrast-enhanced spectral mammography: Impact of the qualitative morphology descriptors on the diagnosis of breast lesions

    Energy Technology Data Exchange (ETDEWEB)

    Mohamed Kamal, Rasha [Radiology Department (Women' s Imaging unit), Kasr ElAiny Hospital, Cairo University (Egypt); Hussien Helal, Maha [Radiology Department (Breast Imaging unit), National Cancer Institute, Cairo University (Egypt); Wessam, Rasha [Radiology Department (Women' s Imaging unit), Kasr ElAiny Hospital, Cairo University (Egypt); Mahmoud Mansour, Sahar, E-mail: sahar_mnsr@yahoo.com [Radiology Department (Breast Imaging unit), National Cancer Institute, Cairo University (Egypt); Godda, Iman [Pathology Department, National Cancer Institute, Cairo University (Egypt); Alieldin, Nelly [Statistics Department, National Cancer Institute, Cairo University (Egypt)

    2015-06-15

    Highlights: • We studied interpretation criteria for enhancing lesions on CESM. • We evaluated the enhancement patterns of 211 breast lesions. • Our results proved that CESM minimized positive and negative falsies in DM. • The proposed CESM lexicon helped in characterization and categorization. - Abstract: Objective: To analyze the morphology and enhancement characteristics of breast lesions on contrast-enhanced spectral mammography (CESM) and to assess their impact on the differentiation between benign and malignant lesions. Materials and method: This ethics committee approved study included 168 consecutive patients with 211 breast lesions over 18 months. Lesions classified as non-enhancing and enhancing and then the latter group was subdivided into mass and non-mass. Mass lesions descriptors included: shape, margins, pattern and degree of internal enhancement. Non-mass lesions descriptors included: distribution, pattern and degree of internal enhancement. The impact of each descriptor on diagnosis individually assessed using Chi test and the validity compared in both benign and malignant lesions. The overall performance of CESM were also calculated. Results: The study included 102 benign (48.3%) and 109 malignant (51.7%) lesions. Enhancement was encountered in 145/211 (68.7%) lesions. They further classified into enhancing mass (99/145, 68.3%) and non-mass lesions (46/145, 31.7%). Contrast uptake was significantly more frequent in malignant breast lesions (p value ≤0.001). Irregular mass lesions with intense and heterogeneous enhancement patterns correlated with a malignant pathology (p value ≤0.001). CESM showed an overall sensitivity of 88.99% and specificity of 83.33%. The positive and negative likelihood ratios were 5.34 and 0.13 respectively. Conclusion: The assessment of the morphology and enhancement characteristics of breast lesions on CESM enhances the performance of digital mammography in the differentiation between benign and malignant

  15. QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computations.

    Science.gov (United States)

    Valdés-Martiní, José R; Marrero-Ponce, Yovani; García-Jacas, César R; Martinez-Mayorga, Karina; Barigye, Stephen J; Vaz d'Almeida, Yasser Silveira; Pham-The, Hai; Pérez-Giménez, Facundo; Morell, Carlos A

    2017-06-07

    In previous reports, Marrero-Ponce et al. proposed algebraic formalisms for characterizing topological (2D) and chiral (2.5D) molecular features through atom- and bond-based ToMoCoMD-CARDD (acronym for Topological Molecular Computational Design-Computer Aided Rational Drug Design) molecular descriptors. These MDs codify molecular information based on the bilinear, quadratic and linear algebraic forms and the graph-theoretical electronic-density and edge-adjacency matrices in order to consider atom- and bond-based relations, respectively. These MDs have been successfully applied in the screening of chemical compounds of different therapeutic applications ranging from antimalarials, antibacterials, tyrosinase inhibitors and so on. To compute these MDs, a computational program with the same name was initially developed. However, this in house software barely offered the functionalities required in contemporary molecular modeling tasks, in addition to the inherent limitations that made its usability impractical. Therefore, the present manuscript introduces the QuBiLS-MAS (acronym for Quadratic, Bilinear and N-Linear mapS based on graph-theoretic electronic-density Matrices and Atomic weightingS) software designed to compute topological (0-2.5D) molecular descriptors based on bilinear, quadratic and linear algebraic forms for atom- and bond-based relations. The QuBiLS-MAS module was designed as standalone software, in which extensions and generalizations of the former ToMoCoMD-CARDD 2D-algebraic indices are implemented, considering the following aspects: (a) two new matrix normalization approaches based on double-stochastic and mutual probability formalisms; (b) topological constraints (cut-offs) to take into account particular inter-atomic relations; (c) six additional atomic properties to be used as weighting schemes in the calculation of the molecular vectors; (d) four new local-fragments to consider molecular regions of interest; (e) number of lone-pair electrons in

  16. Descriptors of Modular Formation of Accounting and Analytical Cluster in Innovation Development of Agricultural Holdings

    Directory of Open Access Journals (Sweden)

    Zhanna Degaltseva

    2015-11-01

    Full Text Available In the context of the division of accounting into financial accounting, taxation accounting, management accounting and statistical accounting a problem of improving their relationship arises. The accounting and analytical cluster plays the role of the correlating factor of the relationship between the subdivisions of the agricultural holding property. To improve its work a modular principle of its building based on information technology was introduced. Practical implementation of modular accounting and analytical cluster revealed its shortcomings. They were as follows: each type of account and each production unit used its own natural and cost parameters. The number and nature of these parameters were different. To eliminate the shortcomings in the information security of managers and specialists of the agricultural holding, we attempt to develop a methodology for establishing a rational number of descriptors (binding parameters for each module. The proposed descriptors are designed on the basis of validity of the methodological approach to their calculations and legal support. The proposed method allowed to limit the asymmetric information in all kinds of records, to improve its quality and to bring a synergistic effect from the scale and structure of the use of the agricultural holdings property complex.

  17. Possible world based consistency learning model for clustering and classifying uncertain data.

    Science.gov (United States)

    Liu, Han; Zhang, Xianchao; Zhang, Xiaotong

    2018-06-01

    Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good. In this paper, we propose a novel possible world based consistency learning model for uncertain data, which can be extended both for clustering and classifying uncertain data. This model utilizes the consistency principle to learn a consensus affinity matrix for uncertain data, which can make full use of the information across different possible worlds and then improve the clustering and classification performance. Meanwhile, this model imposes a new rank constraint on the Laplacian matrix of the consensus affinity matrix, thereby ensuring that the number of connected components in the consensus affinity matrix is exactly equal to the number of classes. This also means that the clustering and classification results can be directly obtained without any post-processing procedure. Furthermore, for the clustering and classification tasks, we respectively derive the efficient optimization methods to solve the proposed model. Experimental results on real benchmark datasets and real world uncertain datasets show that the proposed model outperforms the state-of-the-art uncertain data clustering and classification algorithms in effectiveness and performs competitively in efficiency. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. Spectral descriptors for bulk metallic glasses based on the thermodynamics of competing crystalline phases

    OpenAIRE

    Perim, Eric; Lee, Dongwoo; Liu, Yanhui; Toher, Cormac; Gong, Pan; Li, Yanglin; Simmons, W. Neal; Levy, Ohad; Vlassak, Joost J.; Schroers, Jan; Curtarolo, Stefano

    2016-01-01

    Metallic glasses have attracted considerable interest in recent years due to their unique combination of superb properties and processability. Predicting bulk metallic glass formers from known parameters remains a challenge and the search for new systems is still performed by trial and error. It has been speculated that some sort of "confusion" during crystallization of the crystalline phases competing with glass formation could play a key role. Here, we propose a heuristic descriptor quantif...

  19. Are tags from Mars and descriptors from Venus? A study on the ecology of educational resource metadata

    NARCIS (Netherlands)

    Vuorikari, Riina; Sillaots, Martin; Panzavolta, Silvia; Koper, Rob

    2009-01-01

    Vuorikari, R., Sillaots, M., Panzavolta, S. & Koper, R. (2009). Are tags from Mars and descriptors from Venus? A study on the ecology of educational resource metadata. In M. Spaniol, Q. Li, R. Klamma & R. W. H. Lau (Eds.), Proceedings of the 8th International Conference Advances in Web Based

  20. Limits with modeling data and modeling data with limits

    Directory of Open Access Journals (Sweden)

    Lionello Pogliani

    2006-01-01

    Full Text Available Modeling of the solubility of amino acids and purine and pyrimidine bases with a set of sixteen molecular descriptors has been thoroughly analyzed to detect and understand the reasons for anomalies in the description of this property for these two classes of compounds. Unsatisfactory modeling can be ascribed to incomplete collateral data, i.e, to the fact that there is insufficient data known about the behavior of these compounds in solution. This is usually because intermolecular forces cannot be modeled. The anomalous modeling can be detected from the rather large values of the standard deviation of the estimates of the whole set of compounds, and from the unsatisfactory modeling of some of the subsets of these compounds. Thus the detected abnormalities can be used (i to get an idea about weak intermolecular interactions such as hydration, self-association, the hydrogen-bond phenomena in solution, and (ii to reshape the molecular descriptors with the introduction of parameters that allow better modeling. This last procedure should be used with care, bearing in mind that the solubility phenomena is rather complex.