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Sample records for getaway molecular descriptors

  1. Structure/response correlations and similarity/diversity analysis by GETAWAY descriptors. 2. Application of the novel 3D molecular descriptors to QSAR/QSPR studies.

    Science.gov (United States)

    Consonni, Viviana; Todeschini, Roberto; Pavan, Manuela; Gramatica, Paola

    2002-01-01

    In a previous paper the theory of the new molecular descriptors called GETAWAY (GEometry, Topology, and Atom-Weights AssemblY) was explained. These descriptors have been proposed with the aim of matching 3D-molecular geometry, atom relatedness, and chemical information. In this paper prediction ability in structure-property correlations of GETAWAY descriptors has been tested extensively by analyzing the regressions of these descriptors for selected properties of some reference compound classes. Moreover, the general performance of the new descriptors in QSAR/QSPR has been evaluated with respect to other well-known sets of molecular descriptors.

  2. Molecular Descriptors

    Science.gov (United States)

    Consonni, Viviana; Todeschini, Roberto

    In the last decades, several scientific researches have been focused on studying how to encompass and convert - by a theoretical pathway - the information encoded in the molecular structure into one or more numbers used to establish quantitative relationships between structures and properties, biological activities, or other experimental properties. Molecular descriptors are formally mathematical representations of a molecule obtained by a well-specified algorithm applied to a defined molecular representation or a well-specified experimental procedure. They play a fundamental role in chemistry, pharmaceutical sciences, environmental protection policy, toxicology, ecotoxicology, health research, and quality control. Evidence of the interest of the scientific community in the molecular descriptors is provided by the huge number of descriptors proposed up today: more than 5000 descriptors derived from different theories and approaches are defined in the literature and most of them can be calculated by means of dedicated software applications. Molecular descriptors are of outstanding importance in the research fields of quantitative structure-activity relationships (QSARs) and quantitative structure-property relationships (QSPRs), where they are the independent chemical information used to predict the properties of interest. Along with the definition of appropriate molecular descriptors, the molecular structure representation and the mathematical tools for deriving and assessing models are other fundamental components of the QSAR/QSPR approach. The remarkable progress during the last few years in chemometrics and chemoinformatics has led to new strategies for finding mathematical meaningful relationships between the molecular structure and biological activities, physico-chemical, toxicological, and environmental properties of chemicals. Different approaches for deriving molecular descriptors here reviewed and some of the most relevant descriptors are presented in

  3. 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.

  4. Molecular descriptors of benzenoid systems

    Directory of Open Access Journals (Sweden)

    Nazeran Idrees

    Full Text Available Molecular descriptors are being widely used in QSAR/QSPR studies in chemistry and drug designing as well as modeling of compounds. Different topological descriptors have been formulated to investigate the physio chemical properties and chemical reactivity of compounds. In this article we gave exact relations for first and second Zagreb index, hyper Zagreb index, multiplicative Zagreb indices as well as first and second Zagreb polynomials for some benzenoid systems.

  5. 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

  6. Molecular quantum similarity using conceptual DFT descriptors

    Indian Academy of Sciences (India)

    This paper reports a Molecular Quantum Similarity study for a set of congeneric steroid molecules, using as basic similarity descriptors electron density ρ (r), shape ... Department of Inorganic and Physical Chemistry, Ghent University, Krijgslaan 281, B-9000 Gent, Belgium; Institute of Computational Chemistry, University of ...

  7. PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints.

    Science.gov (United States)

    Yap, Chun Wei

    2011-05-01

    PaDEL-Descriptor is a software for calculating molecular descriptors and fingerprints. The software currently calculates 797 descriptors (663 1D, 2D descriptors, and 134 3D descriptors) and 10 types of fingerprints. These descriptors and fingerprints are calculated mainly using The Chemistry Development Kit. Some additional descriptors and fingerprints were added, which include atom type electrotopological state descriptors, McGowan volume, molecular linear free energy relation descriptors, ring counts, count of chemical substructures identified by Laggner, and binary fingerprints and count of chemical substructures identified by Klekota and Roth. PaDEL-Descriptor was developed using the Java language and consists of a library component and an interface component. The library component allows it to be easily integrated into quantitative structure activity relationship software to provide the descriptor calculation feature while the interface component allows it to be used as a standalone software. The software uses a Master/Worker pattern to take advantage of the multiple CPU cores that are present in most modern computers to speed up calculations of molecular descriptors. The software has several advantages over existing standalone molecular descriptor calculation software. It is free and open source, has both graphical user interface and command line interfaces, can work on all major platforms (Windows, Linux, MacOS), supports more than 90 different molecular file formats, and is multithreaded. PaDEL-Descriptor is a useful addition to the currently available molecular descriptor calculation software. The software can be downloaded at http://padel.nus.edu.sg/software/padeldescriptor. Copyright © 2010 Wiley Periodicals, Inc.

  8. QSAR of Chalcones Utilizing Theoretical Molecular Descriptors.

    Science.gov (United States)

    Nandi, Sisir; Bagchi, Manish C

    2015-01-01

    The paper is an attempt for QSAR modeling based on topological, electrostatic, quantum chemical, constitutional, geometrical and physicochemical indices computed from the structures of 59 set of synthesized chalcone derivatives tested for the cell cycle inhibition of mitotic G2/M phase using multiple linear regression method. Impact of such computed structural descriptors towards antimitotic and antiproliferative activities was analysed by ridge regression (RR) studies. The RR model explained that the topological indices alone can produce significant influence upon the pharmacological responses while combination of topological, electrostatic and quantum chemical descriptors can enhance the degree of impact towards antimitotic and antiproliferative activities of these compounds. Furthermore, QSAR models were formulated utilizing only topological and the combination of topological, electrostatic and quantum chemical descriptors respectively by multiple linear regression method and the validation of the model was performed by searching the predictability of the QSAR models. Satisfactory results were obtained in terms of model quality expressed as R(2) = 0.826, QLoo(2) = 0.710, Rpred(2) = 0.771 respectively for the topological indices. Combination of topological, electrostatic and quantum chemical descriptors resulted in an increase of R(2) = 0.965, QLoo 2 = 0.891, Rpred(2) = 0.849. The generated model predicted that BCUT descriptors (Charge) using modified partial equalization of orbital electronegativity (MPEOE), autocorrelation descriptors, information content descriptor and HOMO descriptor are very much crucial for modeling highly active chalcone compounds. Quantitative structure-activity relationships modeling of 59 set of synthesized chalcone derivatives were tested for the inhibition of mitotic G2/M phase using ridge regression and multiple linear regression methodologies. The generated model predicted that BCUT descriptors (Charge) using modified partial

  9. 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

    of more than 71%. Overall, the method captures the fundamental molecular descriptors, that can be used as an entity to facilitate prediction of oral bioavailability.

  10. 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.

  11. 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.

  12. ChemDes: an integrated web-based platform for molecular descriptor and fingerprint computation.

    Science.gov (United States)

    Dong, Jie; Cao, Dong-Sheng; Miao, Hong-Yu; Liu, Shao; Deng, Bai-Chuan; Yun, Yong-Huan; Wang, Ning-Ning; Lu, Ai-Ping; Zeng, Wen-Bin; Chen, Alex F

    2015-01-01

    Molecular descriptors and fingerprints have been routinely used in QSAR/SAR analysis, virtual drug screening, compound search/ranking, drug ADME/T prediction and other drug discovery processes. Since the calculation of such quantitative representations of molecules may require substantial computational skills and efforts, several tools have been previously developed to make an attempt to ease the process. However, there are still several hurdles for users to overcome to fully harness the power of these tools. First, most of the tools are distributed as standalone software or packages that require necessary configuration or programming efforts of users. Second, many of the tools can only calculate a subset of molecular descriptors, and the results from multiple tools need to be manually merged to generate a comprehensive set of descriptors. Third, some packages only provide application programming interfaces and are implemented in different computer languages, which pose additional challenges to the integration of these tools. A freely available web-based platform, named ChemDes, is developed in this study. It integrates multiple state-of-the-art packages (i.e., Pybel, CDK, RDKit, BlueDesc, Chemopy, PaDEL and jCompoundMapper) for computing molecular descriptors and fingerprints. ChemDes not only provides friendly web interfaces to relieve users from burdensome programming work, but also offers three useful and convenient auxiliary tools for format converting, MOPAC optimization and fingerprint similarity calculation. Currently, ChemDes has the capability of computing 3679 molecular descriptors and 59 types of molecular fingerprints. ChemDes provides users an integrated and friendly tool to calculate various molecular descriptors and fingerprints. It is freely available at http://www.scbdd.com/chemdes. The source code of the project is also available as a supplementary file. Graphical abstract:An overview of ChemDes. A platform for computing various molecular

  13. QSAR modeling of datasets with enantioselective compounds using chirality sensitive molecular descriptors.

    Science.gov (United States)

    Kovatcheva, A; Golbraikh, A; Oloff, S; Feng, J; Zheng, W; Tropsha, A

    2005-01-01

    Shape descriptors used in 3D QSAR studies naturally take into account chirality; however, for flexible and structurally diverse molecules such studies require extensive conformational searching and alignment. QSAR modeling studies of two datasets of fragrance compounds with complex stereochemistry using simple alignment-free chirality sensitive descriptors developed in our laboratories are presented. In the first investigation, 44 alpha-campholenic derivatives with sandalwood odor were represented as derivatives of several common structural templates with substituents numbered according to their relative spatial positions in the molecules. Both molecular and substituent descriptors were used as independent variables in MLR calculations, and the best model was characterized by the training set q2 of 0.79 and external test set r2 of 0.95. In the second study, several types of chirality descriptors were employed in combinatorial QSAR modeling of 98 ambergris fragrance compounds. Among 28 possible combinations of seven types of descriptors and four statistical modeling techniques, k nearest neighbor classification with CoMFA descriptors was initially found to generate the best models with the internal and external accuracies of 76 and 89%, respectively. The same dataset was then studied using novel atom pair chirality descriptors (cAP). The cAP are based on a modified definition of the atomic chirality, in which the seniority of the substituents is defined by their relative partial charge values: higher values correspond to higher seniorities. The resulting models were found to have higher predictive power than those developed with CoMFA descriptors; the best model was characterized by the internal and external accuracies of 82 and 94%, respectively. The success of modeling studies using simple alignment free chirality descriptors discussed in this paper suggests that they should be applied broadly to QSAR studies of many datasets when compound stereochemistry plays an

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. Correlation between calculated molecular descriptors of excipient amino acids and experimentally observed thermal stability of lysozyme

    DEFF Research Database (Denmark)

    Meng-Lund, Helena; Friis, Natascha; van de Weert, Marco

    2017-01-01

    analysis was applied to correlate the descriptors with the experimental results. It was possible to identify descriptors, i.e. amino acids properties, with a positive influence on either transition temperature or aggregation onset time, or both. A high number of hydrogen bond acceptor moieties was the most......A quantitative structure-property relationship (QSPR) between protein stability and the physicochemical properties of excipients was investigated to enable a more rational choice of stabilizing excipients than prior knowledge. The thermal transition temperature and aggregation time were determined...... for lysozyme in combination with 13 different amino acids using high throughput fluorescence spectroscopy and kinetic static light scattering measurements. On the theoretical side, around 200 2D and 3D molecular descriptors were calculated based on the amino acids' chemical structure. Multivariate data...

  19. 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.

  20. Correlation between calculated molecular descriptors of excipient amino acids and experimentally observed thermal stability of lysozyme.

    Science.gov (United States)

    Meng-Lund, Helena; Friis, Natascha; van de Weert, Marco; Rantanen, Jukka; Poso, Antti; Grohganz, Holger; Jorgensen, Lene

    2017-05-15

    A quantitative structure-property relationship (QSPR) between protein stability and the physicochemical properties of excipients was investigated to enable a more rational choice of stabilizing excipients than prior knowledge. The thermal transition temperature and aggregation time were determined for lysozyme in combination with 13 different amino acids using high throughput fluorescence spectroscopy and kinetic static light scattering measurements. On the theoretical side, around 200 2D and 3D molecular descriptors were calculated based on the amino acids' chemical structure. Multivariate data analysis was applied to correlate the descriptors with the experimental results. It was possible to identify descriptors, i.e. amino acids properties, with a positive influence on either transition temperature or aggregation onset time, or both. A high number of hydrogen bond acceptor moieties was the most prominent stabilizing factor for both responses, whereas hydrophilic surface properties and high molecular mass density mostly had a positive influence on the unfolding temperature. A high partition coefficient (logP(o/w)) was identified as the most prominent destabilizing factor for both responses. The QSPR shows good correlation between calculated molecular descriptors and the measured stabilizing effect of amino acids on lysozyme. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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    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.

  2. ChemDes: an integrated web-based platform for molecular descriptor and fingerprint computation

    OpenAIRE

    Dong, Jie; Cao, Dong-Sheng; Miao, Hong-Yu; Liu, Shao; Deng, Bai-Chuan; Yun, Yong-Huan; Wang, Ning-Ning; Lu, Ai-Ping; Zeng, Wen-Bin; Chen, Alex F.

    2015-01-01

    Background Molecular descriptors and fingerprints have been routinely used in QSAR/SAR analysis, virtual drug screening, compound search/ranking, drug ADME/T prediction and other drug discovery processes. Since the calculation of such quantitative representations of molecules may require substantial computational skills and efforts, several tools have been previously developed to make an attempt to ease the process. However, there are still several hurdles for users to overcome to fully harne...

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

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    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. 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.

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Antonios A. Augustinos

    2016-12-01

    Full Text Available 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.

  7. Chemical and Molecular Descriptors for the Reactivity of Amines with CO{sub 2}

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Anita S.; Kitchin, John R.

    2012-10-24

    Amine-based solvents are likely to play an important role in CO{sub 2} capture applications in the future, and the identification of amines with superior performance will facilitate their use in CO{sub 2} capture. While some improvements in performance will be achieved through process modifications, modifying the CO{sub 2} capture performance of an amine also implies in part an ability to modify the reactions between the amine and CO{sub 2} through development of new functionalized amines. We present a computational study of trends in the reactions between CO{sub 2} and functionalized amines with a focus on identifying molecular descriptors that determine trends in reactivity. We examine the formation of bicarbonate and carbamate species on three classes of functionalized amines: alkylamines, alkanolamines, and fluorinated alkylamines including primary, secondary and tertiary amines in each class. These functional groups span electron-withdrawing to donating behavior, hydrogen-bonding, extent of functionalization, and proximity effects of the functional groups. Electron withdrawing groups tend to destabilize CO{sub 2} reaction products, whereas electron-donating groups tend to stabilize CO{sub 2} reaction products. Hydrogen bonding stabilizes CO{sub 2} reaction products. Electronic structure descriptors based on electronegativity were found to describe trends in the bicarbonate formation energy. A chemical correlation was observed between the carbamate formation energy and the carbamic acid formation energy. The local softness on the reacting N in the amine was found to partially explain trends carbamic acid formation energy.

  8. Quantitative structure-activity relationship modeling of polycyclic aromatic hydrocarbon mutagenicity by classification methods based on holistic theoretical molecular descriptors.

    Science.gov (United States)

    Gramatica, Paola; Papa, Ester; Marrocchi, Assunta; Minuti, Lucio; Taticchi, Aldo

    2007-03-01

    Various polycyclic aromatic hydrocarbons (PAHs), ubiquitous environmental pollutants, are recognized mutagens and carcinogens. A homogeneous set of mutagenicity data (TA98 and TA100,+S9) for 32 benzocyclopentaphenanthrenes/chrysenes was modeled by the quantitative structure-activity relationship classification methods k-nearest neighbor and classification and regression tree, using theoretical holistic molecular descriptors. Genetic algorithm provided the selection of the best subset of variables for modeling mutagenicity. The models were validated by leave-one-out and leave-50%-out approaches and have good performance, with sensitivity and specificity ranges of 90-100%. Mutagenicity assessment for these PAHs requires only a few theoretical descriptors of their molecular structure.

  9. 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...

  10. Morphological descriptors and ISSR molecular markers in the evaluation of genetic variability of Tectona grandis genotypes.

    Science.gov (United States)

    Chimello, A M; Jesus, J G; Teodoro, P E; Rossi, A A B; Araújo, K L; Marostega, T N; Neves, L G; Barelli, M A A

    2017-05-25

    This study aimed to evaluate the genetic variability of the teak germplasm bank, using morphological traits and inter-simple sequence repeat molecular markers. Thirty clones were evaluated in a randomized complete block design with three replicates, and each plot was composed of three plants. A joint analysis of quantitative and qualitative variables was performed using the Gower algorithm. Quantitative, qualitative, and molecular variables were analyzed simultaneously using the Ward-MLM procedure. There is genetic variability among the 30 teak genotypes studied, considering the quantitative, qualitative, and molecular variables by the Ward-MLM statistical procedure. Morphological traits used proved to be efficient for the study of genetic variability; however, it was not possible to compose a descriptor table for clonal teak genotypes based on the traits evaluated. The Gower method was efficient in discriminating the groups, demonstrating that the simultaneous analysis of qualitative and quantitative data is feasible and can allow greater efficiency in the knowledge of the variability among teak genotypes. The genotype 22 showed to be the most divergent compared to the other genotypes, except for the cluster of genotypes by the UPGMA method based on the Gower distance obtained by the Ward-MLM procedure, which formed a group with genotypes 9 and 30, in the morphological and molecular analyses and was grouped alone.

  11. Morphological and Molecular Descriptors of the Developmental Cycle of Babesia divergens Parasites in Human Erythrocytes.

    Science.gov (United States)

    Rossouw, Ingrid; Maritz-Olivier, Christine; Niemand, Jandeli; van Biljon, Riette; Smit, Annel; Olivier, Nicholas A; Birkholtz, Lyn-Marie

    2015-05-01

    Human babesiosis, especially caused by the cattle derived Babesia divergens parasite, is on the increase, resulting in renewed attentiveness to this potentially life threatening emerging zoonotic disease. The molecular mechanisms underlying the pathophysiology and intra-erythrocytic development of these parasites are poorly understood. This impedes concerted efforts aimed at the discovery of novel anti-babesiacidal agents. By applying sensitive cell biological and molecular functional genomics tools, we describe the intra-erythrocytic development cycle of B. divergens parasites from immature, mono-nucleated ring forms to bi-nucleated paired piriforms and ultimately multi-nucleated tetrads that characterizes zoonotic Babesia spp. This is further correlated for the first time to nuclear content increases during intra-erythrocytic development progression, providing insight into the part of the life cycle that occurs during human infection. High-content temporal evaluation elucidated the contribution of the different stages to life cycle progression. Moreover, molecular descriptors indicate that B. divergens parasites employ physiological adaptation to in vitro cultivation. Additionally, differential expression is observed as the parasite equilibrates its developmental stages during its life cycle. Together, this information provides the first temporal evaluation of the functional transcriptome of B. divergens parasites, information that could be useful in identifying biological processes essential to parasite survival for future anti-babesiacidal discoveries.

  12. Morphological and Molecular Descriptors of the Developmental Cycle of Babesia divergens Parasites in Human Erythrocytes.

    Directory of Open Access Journals (Sweden)

    Ingrid Rossouw

    2015-05-01

    Full Text Available Human babesiosis, especially caused by the cattle derived Babesia divergens parasite, is on the increase, resulting in renewed attentiveness to this potentially life threatening emerging zoonotic disease. The molecular mechanisms underlying the pathophysiology and intra-erythrocytic development of these parasites are poorly understood. This impedes concerted efforts aimed at the discovery of novel anti-babesiacidal agents. By applying sensitive cell biological and molecular functional genomics tools, we describe the intra-erythrocytic development cycle of B. divergens parasites from immature, mono-nucleated ring forms to bi-nucleated paired piriforms and ultimately multi-nucleated tetrads that characterizes zoonotic Babesia spp. This is further correlated for the first time to nuclear content increases during intra-erythrocytic development progression, providing insight into the part of the life cycle that occurs during human infection. High-content temporal evaluation elucidated the contribution of the different stages to life cycle progression. Moreover, molecular descriptors indicate that B. divergens parasites employ physiological adaptation to in vitro cultivation. Additionally, differential expression is observed as the parasite equilibrates its developmental stages during its life cycle. Together, this information provides the first temporal evaluation of the functional transcriptome of B. divergens parasites, information that could be useful in identifying biological processes essential to parasite survival for future anti-babesiacidal discoveries.

  13. 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

    -averaged by selection of the most relevant conformers out of a set of possible molecular conformers generated by a systematic scheme presented in this paper. Six of these descriptors are calculated with molecular mechanics and three with quantum chemical methods. Especially interesting descriptors are the relative van...

  14. 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.

  15. Molecular dynamics simulations and structural descriptors of radioisotope glass vectors for in situ radiotherapy.

    Science.gov (United States)

    Christie, Jamieson K; Tilocca, Antonio

    2012-10-18

    The low solubility (high durability) of yttrium aluminosilicate (YAS) glass is one of its most important properties for use in in situ radiotherapy. Simple parameters, such as silica or yttria content or network connectivity, are not sufficient to rationalize the dependence of the solubility on the glass composition observed experimentally. We performed classical molecular dynamics (MD) simulations of eight different YAS glasses of known solubility and analyzed the MD trajectories to identify specific structural features that are correlated and can be used to predict the solubility. We show that the (Si-)O-Si coordination number CN(SiOSi), the yttrium-yttrium clustering ratio R(YY), and the number of intratetrahedral O-Si-O bonds per yttrium atom N(intra) can be combined into a single structural descriptor s = f(CN(SiOSi),R(YY),N(intra)) with a high correlation with the solubility. The parameter s can thus be calculated from MD simulations and used to predict the solubility of YAS compositions, allowing one to adjust them to the range required by radiotherapy applications. For instance, its trend shows that high-silica- and low-yttria-content YAS glasses should be sufficiently durable for the radiotherapy application, although additional clinical considerations may set a lower limit to the yttria content.

  16. Molecular docking using the molecular lipophilicity potential as hydrophobic descriptor: impact on GOLD docking performance.

    Science.gov (United States)

    Nurisso, Alessandra; Bravo, Juan; Carrupt, Pierre-Alain; Daina, Antoine

    2012-05-25

    GOLD is a molecular docking software widely used in drug design. In the initial steps of docking, it creates a list of hydrophobic fitting points inside protein cavities that steer the positioning of ligand hydrophobic moieties. These points are generated based on the Lennard-Jones potential between a carbon probe and each atom of the residues delimitating the binding site. To thoroughly describe hydrophobic regions in protein pockets and properly guide ligand hydrophobic moieties toward favorable areas, an in-house tool, the MLP filter, was developed and herein applied. This strategy only retains GOLD hydrophobic fitting points that match the rigorous definition of hydrophobicity given by the molecular lipophilicity potential (MLP), a molecular interaction field that relies on an atomic fragmental system based on 1-octanol/water experimental partition coefficients (log P(oct)). MLP computations in the binding sites of crystallographic protein structures revealed that a significant number of points considered hydrophobic by GOLD were actually polar according to the MLP definition of hydrophobicity. To examine the impact of this new tool, ligand-protein complexes from the Astex Diverse Set and the PDB bind core database were redocked with and without the use of the MLP filter. Reliable docking results were obtained by using the MLP filter that increased the quality of docking in nonpolar cavities and outperformed the standard GOLD docking approach.

  17. Molecular electrostatic potential on the proton-donating atom as a theoretical descriptor of excited state acidity.

    Science.gov (United States)

    Wang, Yu-Fu; Cheng, Yuan-Chung

    2018-02-07

    Organic photoacids with enhanced acidities in the excited states have received much attention both experimentally and theoretically because of their applications in nanotechnology and chemistry. In this study, we investigate the excited-state acidities of 14 hydroxyl-substituted aromatic photoacids, with a focus on using theoretical molecular electrostatic potential (MEP) as an effective descriptor for photoacidity. For these model photoacids, we applied time-dependent density functional theory (TDDFT) at the ωB97X-D/6-31G(d) level to calculate the molecular electrostatic potentials of S 1 excited states and show that the molecular electrostatic potential on the proton-donating atom exhibits a linear relationship with the observed excited-state logarithmic acid dissociation constant (pK a *). As a result, the molecular electrostatic potential on the proton-donating atom can be used to estimate the pK a * values based on simple TDDFT calculations for a broad range of hydroxyl-substituted aromatic compounds. Furthermore, we explore the molecular electrostatic potential as a quantum descriptor for the photoacidities of cationic photoacids, and show a universal behavior of the pK a *-MEP dependence. We also investigate the solvent effects on the photoacidity using TDDFT calculations with implicit solvent models. Finally, we discuss the physical insights implicated by the molecular electrostatic potential as a successful measure for photoacidity on the mechanism of proton transfer in the molecular excited states. This pK a * descriptor provides an effective means to quantify the tendency of excited-state proton transfer with a relatively small computational cost, which is expected to be useful in the design of functional photoacids.

  18. Three-Dimensional Biologically Relevant Spectrum (BRS-3D: Shape Similarity Profile Based on PDB Ligands as Molecular Descriptors

    Directory of Open Access Journals (Sweden)

    Ben Hu

    2016-11-01

    Full Text Available The crystallized ligands in the Protein Data Bank (PDB can be treated as the inverse shapes of the active sites of corresponding proteins. Therefore, the shape similarity between a molecule and PDB ligands indicated the possibility of the molecule to bind with the targets. In this paper, we proposed a shape similarity profile that can be used as a molecular descriptor for ligand-based virtual screening. First, through three-dimensional (3D structural clustering, 300 diverse ligands were extracted from the druggable protein–ligand database, sc-PDB. Then, each of the molecules under scrutiny was flexibly superimposed onto the 300 ligands. Superimpositions were scored by shape overlap and property similarity, producing a 300 dimensional similarity array termed the “Three-Dimensional Biologically Relevant Spectrum (BRS-3D”. Finally, quantitative or discriminant models were developed with the 300 dimensional descriptor using machine learning methods (support vector machine. The effectiveness of this approach was evaluated using 42 benchmark data sets from the G protein-coupled receptor (GPCR ligand library and the GPCR decoy database (GLL/GDD. We compared the performance of BRS-3D with other 2D and 3D state-of-the-art molecular descriptors. The results showed that models built with BRS-3D performed best for most GLL/GDD data sets. We also applied BRS-3D in histone deacetylase 1 inhibitors screening and GPCR subtype selectivity prediction. The advantages and disadvantages of this approach are discussed.

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

    Science.gov (United States)

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

    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(2)SMLR = 0.9911; R(2)PCR = 0.9917; R(2)PLS = 0.9918) and validation datasets (R(2)SMLR = 0.9489; R(2)PCR = 0.9761; R(2)PLS = 0.9760). Also, the high cross validated R(2) values indicate that the generated models are robust and highly predictive (Q(2)SMLR = 0.9859; Q(2)PCR = 0.9748; Q(2)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 (predictive ability. These methods could therefore be used in routine analysis and could be easily integrated to metabolite identification platforms. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Determination of LFER descriptors of 30 cations of ionic liquids--progress in understanding their molecular interaction potentials.

    Science.gov (United States)

    Cho, Chul-Woong; Jungnickel, Christian; Stolte, Stefan; Preiss, Ulrich; Arning, Jürgen; Ranke, Johannes; Krossing, Ingo; Thöming, Jorg

    2012-02-01

    In order to understand molecular interaction potentials of 30 cations of ionic liquids (ILs), the well-known linear free energy relationship concept (LFER) was applied. The LFER descriptors for the excess molar refractivity and the molar volume were calculated in silico and for hydrogen-bonding acidity and basicity, and the polarizability/dipolarity of IL cations were experimentally determined through high performance liquid chromatography (HPLC) measurements. For the study, three different columns (RP-select B, Cyan, and Diol) and buffered mobile phases, based on two organic solvents acetonitrile (ACN) and methanol (MeOH), were selectively combined to the HPLC separation systems RP-select B-ACN, RP-select B-MeOH, Cyan-MeOH, Diol-ACN, and Diol-MeOH. By measuring the retention factors of 45 neutral calibration compounds and calculating LFER descriptors of three cations in the HPLC systems, the system parameters, including an ionic z coefficient, were determined. Conversely, the LFER descriptors of 30 ionic liquid cations were determined, based on the parameters of five systems and their retention factors in the HPLC systems. The results showed that the type of head group, alkyl chain length and further substituents of the cation have a significant influence on the dipolarity/polarizability and the hydrogen-bonding acidity, and functionalized groups (hydroxyl, ether, and dimethylamino) lead to hydrogen-bonding basicity of the cation. The characterization of cationic LFER descriptors opens up the chance for a more quantitative understanding of molecular interaction potentials and physicochemical properties of ILs. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. 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

  2. Anabolic and androgenic activities of 19-nor-testosterone steroids: QSAR study using quantum and physicochemical molecular descriptors.

    Science.gov (United States)

    Alvarez-Ginarte, Yoanna María; Montero-Cabrera, Luis Alberto; de la Vega, José Manuel García; Noheda-Marín, Pedro; Marrero-Ponce, Yovani; Ruíz-García, José Alberto

    2011-08-01

    Quantitative structure-activity relationship (QSAR) study of 19-nor-testosterone steroids family was performed using quantum and physicochemical molecular descriptors. The quantum-chemical descriptors were calculated using semiempirical calculations. The descriptor values were statistically correlated using multi-linear regression analysis. The QSAR study indicated that the electronic properties of these derivatives have significant relationship with observed biological activities. The found QSAR equations explain that the energy difference between the LUMO and HOMO, the total dipole moment, the chemical potential and the value of the net charge of different carbon atoms in the steroid nucleus showed key interaction of these steroids with their anabolic-androgenic receptor binding site. The calculated values predict that the 17α-cyclopropyl-17β, 3β-hydroxy-4-estrene compound presents the highest anabolic-androgenic ratio (AAR) and the 7α-methyl-17β-acetoxy-estr-4-en-3-one compound the lowest AAR. This study might be helpful in the future successful identification of "real" or "virtual" anabolic-androgenic steroids. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. 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

  4. 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...

  5. 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 SMLR  = 0.9911; R 2 PCR  = 0.9917; R 2 PLS  = 0.9918) and validation datasets (R 2 SMLR  = 0.9489; R 2 PCR  = 0.9761; R 2 PLS  = 0.9760). Also, the high cross validated R 2 values indicate that the generated models are robust and highly predictive (Q 2 SMLR  = 0.9859; Q 2 PCR  = 0.9748; Q 2 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. • Isomeric phenolics were separated in the IMS based on their CCS. • SMLR, PLS and

  6. 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.

  7. Use of self-organizing maps and molecular descriptors to predict the cytotoxic activity of sesquiterpene lactones.

    Science.gov (United States)

    Fernandes, Mariane B; Scotti, Marcus T; Ferreira, Marcelo J P; Emerenciano, Vicente P

    2008-10-01

    Some sesquiterpene lactones (SLs) are the active compounds of a great number of traditionally medicinal plants from the Asteraceae family and possess considerable cytotoxic activity. Several studies in vitro have shown the inhibitory activity against cells derived from human carcinoma of the nasopharynx (KB). Chemical studies showed that the cytotoxic activity is due to the reaction of alpha,beta-unsaturated carbonyl structures of the SLs with thiols, such as cysteine. These studies support the view that SLs inhibit tumour growth by selective alkylation of growth-regulatory biological macromolecules, such as key enzymes, which control cell division, thereby inhibiting a variety of cellular functions, which directs the cells into apoptosis. In this study we investigated a set of 55 different sesquiterpene lactones, represented by 5 skeletons (22 germacranolides, 6 elemanolides, 2 eudesmanolides, 16 guaianolides and nor-derivatives and 9 pseudoguaianolides), in respect to their cytotoxic properties. The experimental results and 3D molecular descriptors were submitted to Kohonen self-organizing map (SOM) to classify (training set) and predict (test set) the cytotoxic activity. From the obtained results, it was concluded that only the geometrical descriptors showed satisfactory values. The Kohonen map obtained after training set using 25 geometrical descriptors shows a very significant match, mainly among the inactive compounds (approximately 84%). Analyzing both groups, the percentage seen is high (83%). The test set shows the highest match, where 89% of the substances had their cytotoxic activity correctly predicted. From these results, important properties for the inhibition potency are discussed for the whole dataset and for subsets of the different structural skeletons.

  8. QuBiLS-MIDAS: a parallel free-software for molecular descriptors computation based on multilinear algebraic maps.

    Science.gov (United States)

    García-Jacas, César R; Marrero-Ponce, Yovani; Acevedo-Martínez, Liesner; Barigye, Stephen J; Valdés-Martiní, José R; Contreras-Torres, Ernesto

    2014-07-05

    The present report introduces the QuBiLS-MIDAS software belonging to the ToMoCoMD-CARDD suite for the calculation of three-dimensional molecular descriptors (MDs) based on the two-linear (bilinear), three-linear, and four-linear (multilinear or N-linear) algebraic forms. Thus, it is unique software that computes these tensor-based indices. These descriptors, establish relations for two, three, and four atoms by using several (dis-)similarity metrics or multimetrics, matrix transformations, cutoffs, local calculations and aggregation operators. The theoretical background of these N-linear indices is also presented. The QuBiLS-MIDAS software was developed in the Java programming language and employs the Chemical Development Kit library for the manipulation of the chemical structures and the calculation of the atomic properties. This software is composed by a desktop user-friendly interface and an Abstract Programming Interface library. The former was created to simplify the configuration of the different options of the MDs, whereas the library was designed to allow its easy integration to other software for chemoinformatics applications. This program provides functionalities for data cleaning tasks and for batch processing of the molecular indices. In addition, it offers parallel calculation of the MDs through the use of all available processors in current computers. The studies of complexity of the main algorithms demonstrate that these were efficiently implemented with respect to their trivial implementation. Lastly, the performance tests reveal that this software has a suitable behavior when the amount of processors is increased. Therefore, the QuBiLS-MIDAS software constitutes a useful application for the computation of the molecular indices based on N-linear algebraic maps and it can be used freely to perform chemoinformatics studies. Copyright © 2014 Wiley Periodicals, Inc.

  9. Poly(DL-lactide-co-glycolic acid) nanoparticle design and payload prediction: a molecular descriptor based study.

    Science.gov (United States)

    Das, Suvadra; Roy, Partha; Islam, Ataul; Saha, Achintya; Mukherjee, Arup

    2013-01-01

    Polymer nanoparticles are veritable tools for pharmacokinetic and therapeutic modifications of bioactive compounds. Nanoparticle technology development and scaling up are however often constrained due to poor payload and improper particle dissolution. This work was aimed to develop descriptor based computational models as prior art tools for optimal payload in polymeric nanoparticles. Loading optimization experiments were carried out both in vitro and in-silico. Molecular descriptors generated in three different platforms DRAGON, molecular operating environment (MOE) and VolSurf+ were used. Multiple linear regression analysis (MLR) provided computation models which were further validated based on goodness of fit statistics and correlation coefficients (DRAGON, R(2)=0.889, Q(2)=0.657, R(2)(pred)=0.616; MOE, R(2)=0.826, Q(2)=0.572, R(2)(pred)=0.601; and VolSurf+, R(2)=0.818, Q(2)=0.573, R(2)(pred)=0.653). Pharmacophore space modeling studies were carried out in order to understand the fundamental molecular interactions necessary for drug loading in poly(DL-lactide-co-glycolic acid). The space modeling study (R(2)=0.882, Q(2)=0.662, R(2)(pred)=0.725, Δ(cost)=108.931) indicated that hydrogen bond acceptors and ring aromatic features are of primary significance for nanoparticle drug loading. Results of in vitro experiments have also confirmed the fact as a viable prognosis in case of nanoparticle payload. Polymeric nanoparticles payload prediction can therefore be a useful tool for wider benefits at the preformulation stages itself.

  10. 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.

  11. Morphological and Molecular Descriptors of the Developmental Cycle of Babesia divergens Parasites in Human Erythrocytes

    OpenAIRE

    Rossouw, Ingrid; Maritz-Olivier, Christine; Niemand, Jandeli; van Biljon, Riette; Smit, Annel; Olivier, Nicholas A.; Birkholtz, Lyn-Marie

    2015-01-01

    Human babesiosis, especially caused by the cattle derived Babesia divergens parasite, is on the increase, resulting in renewed attentiveness to this potentially life threatening emerging zoonotic disease. The molecular mechanisms underlying the pathophysiology and intra-erythrocytic development of these parasites are poorly understood. This impedes concerted efforts aimed at the discovery of novel anti-babesiacidal agents. By applying sensitive cell biological and molecular functional genomic...

  12. Molecular descriptor data explain market prices of a large commercial chemical compound library

    Science.gov (United States)

    Polanski, Jaroslaw; Kucia, Urszula; Duszkiewicz, Roksana; Kurczyk, Agata; Magdziarz, Tomasz; Gasteiger, Johann

    2016-06-01

    The relationship between the structure and a property of a chemical compound is an essential concept in chemistry guiding, for example, drug design. Actually, however, we need economic considerations to fully understand the fate of drugs on the market. We are performing here for the first time the exploration of quantitative structure-economy relationships (QSER) for a large dataset of a commercial building block library of over 2.2 million chemicals. This investigation provided molecular statistics that shows that on average what we are paying for is the quantity of matter. On the other side, the influence of synthetic availability scores is also revealed. Finally, we are buying substances by looking at the molecular graphs or molecular formulas. Thus, those molecules that have a higher number of atoms look more attractive and are, on average, also more expensive. Our study shows how data binning could be used as an informative method when analyzing big data in chemistry.

  13. Descriptors for antimicrobial peptides

    DEFF Research Database (Denmark)

    Jenssen, Håvard

    2011-01-01

    Introduction: A frightening increase in the number of isolated multidrug resistant bacterial strains linked to the decline in novel antimicrobial drugs entering the market is a great cause for concern. Cationic antimicrobial peptides (AMPs) have lately been introduced as a potential new class...... of antimicrobial drugs, and computational methods utilizing molecular descriptors can significantly accelerate the development of new peptide drug candidates. Areas covered: This paper gives a broad overview of peptide and amino-acid scale descriptors available for AMP modeling and highlights which...

  14. Topological Substituent Descriptors

    Directory of Open Access Journals (Sweden)

    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.

  15. Prediction of Anticancer Activity of 2-phenylindoles: Comparative Molecular Field Analysis Versus Ridge Regression using Mathematical Molecular Descriptors.

    Science.gov (United States)

    Basak, Subhash C; Zhu, Qianhong; Mills, Denise

    2010-09-01

    Topological indices (TIs) and atom pairs (APs) were used to develop quantitative structure-activity relationships (QSARs) for anticancer activity for a set of 43 derivatives of 2-phenylindole. Results show that QSARs formulated using TI+AP outperform those using either TI or AP alone. The q2 of the ridge regression model using TI+AP was 0.867 as compared to 0.705 reported in the literature using the comparative molecular field analysis (CoMFA) method.

  16. Relationships Between MRI Breast Imaging-Reporting and Data System (BI-RADS) Lexicon Descriptors and Breast Cancer Molecular Subtypes: Internal Enhancement is Associated with Luminal B Subtype.

    Science.gov (United States)

    Grimm, Lars J; Zhang, Jing; Baker, Jay A; Soo, Mary S; Johnson, Karen S; Mazurowski, Maciej A

    2017-09-01

    The aim of this study was to determine the associations between breast MRI findings using the Breast Imaging-Reporting and Data System (BI-RADS) lexicon descriptors and breast cancer molecular subtypes. In this retrospective, IRB-approved, single institution study MRIs from 278 women with breast cancer were reviewed by one of six fellowship-trained breast imagers. Readers reported BI-RADS descriptors for breast masses (shape, margin, internal enhancement) and non-mass enhancement (distribution, internal enhancement). Pathology reports were reviewed for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2). Surrogates were used to categorize tumors by molecular subtype: ER/PR+, HER2- (luminal A); ER/PR+, HER2+ (luminal B); ER/PR-, HER2+ (HER2); ER/PR/HER2- (basal). A univariate logistic regression model was developed to identify associations between BI-RADS descriptors and molecular subtypes. Internal enhancement for mass and non-mass enhancement was combined for analysis. There was an association between mass shape and basal subtype (p = 0.039), which was more frequently round (17.1%) than other subtypes (range: 0-8.3%). In addition, there was an association between mass margin and HER2 subtype (p = 0.040), as HER2 cancers more frequently had a smooth margin (33.3%) than other subtypes (range: 4.2-17.1%). Finally, there was an association between internal enhancement and luminal B subtype (p = 0.003), with no cases of luminal B cancer demonstrating homogeneous internal enhancement versus a range of 10.9-23.5% for other subtypes. There are associations between breast cancer molecular subtypes and lesion appearance on MRI using the BI-RADS lexicon. © 2017 Wiley Periodicals, Inc.

  17. Maximum Topological Distances Based Indices as Molecular Descriptors for QSPR. 4. Modeling the Enthalpy of Formation of Hydrocarbons from Elements

    Directory of Open Access Journals (Sweden)

    Andrey A. Toropov

    2001-06-01

    Full Text Available The enthalpy of formation of a set of 60 hydroarbons is calculated on the basis of topological descriptors defined from the distance and detour matrices within the realm of the QSAR/QSPR theory. Linear and non-linear polynomials fittings are made and results show the need to resort to higher-order regression equations in order to get better concordances between theoretical results and experimental available data. Besides, topological indices computed from maximum order distances seems to yield rather satisfactory predictions of heats of formation for hydrocarbons.

  18. Benchmarking of protein descriptor sets in proteochemometric modeling (part 1) : comparative study of 13 amino acid descriptor sets.

    NARCIS (Netherlands)

    Westen, van G.J.P.; Swier, R.F.; Wegner, J.K.; IJzerman, A.P.; Vlijmen, van H.; Bender, A.

    2013-01-01

    Background While a large body of work exists on comparing and benchmarking of descriptors of molecular structures, a similar comparison of protein descriptor sets is lacking. Hence, in the current work a total of 13 different protein descriptor sets have been compared with respect to their behavior

  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. 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.

  1. Topological and quantum molecular descriptors as effective tools for analyzing cytotoxic activity achieved by a series of (diselanediyldibenzene-4,1-diylnide)biscarbamate derivatives.

    Science.gov (United States)

    Font, María; Plano, Daniel; Sanmartín, Carmen; Palop, Juan Antonio

    2017-05-01

    A molecular modeling study has been carried out on a previously reported series of (diselanediyldibenzene-4,1-diylnide)biscarbamate derivatives that show cytotoxic and antiproliferative in vitro activity against MCF-7 human cell line; radical scavenging properties were also confirmed when these compounds were tested for their ability to scavenge DPPH and ABTS radicals. The data obtained allowed us to classify the compounds into two different groups: (a) aliphatic carbamates for which the activity could be related with a first nucleophilic attack (mediated by H 2 O, for example) on the selenium atoms of the central scaffold, followed by the release of the alkyl N-(4-selanylphenyl) and N-(4-selenenophenyl)carbamate moieties. Then, a second nucleophilic attack on the carbamate moiety, to yield 4-aminobenzeneselenol and 4-selenenoaniline respectively, which can ultimately be responsible for the activity of the compounds; (b) aromatic carbamates, for which we propose a preferred nucleophilic attack on the carbamate moiety, yielding 4-[(4-aminophenyl)diselanyl]aniline, the common structural fragment for this series, for which we have previously demonstrated its cytotoxic profile. Then, selenium atoms of the central fragment may later undergo a new nucleophilic attack, to yield 4-selenenoaniline and 4-aminobenzeneselenol. The phenolic moieties released in this process may also have a synergistic cytotoxic and redox activity. The data that support this connection include the conformational behavior and the molecular topography of the derivatives which can influence the accessibility of the hydrolysis points, and some quantum descriptors (bond order, atomic charges, total valences, ionization potential, electron affinity, HOMO 0 and LUMO 0 location, etc.) that have been related to the biological activity of the compounds. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Derivatives in discrete mathematics: a novel graph-theoretical invariant for generating new 2/3D molecular descriptors. I. Theory and QSPR application.

    Science.gov (United States)

    Marrero-Ponce, Yovani; Santiago, Oscar Martínez; López, Yoan Martínez; Barigye, Stephen J; Torrens, Francisco

    2012-11-01

    In this report, we present a new mathematical approach for describing chemical structures of organic molecules at atomic-molecular level, proposing for the first time the use of the concept of the derivative ([Formula: see text]) of a molecular graph (MG) with respect to a given event (E), to obtain a new family of molecular descriptors (MDs). With this purpose, a new matrix representation of the MG, which generalizes graph's theory's traditional incidence matrix, is introduced. This matrix, denominated the generalized incidence matrix, Q, arises from the Boolean representation of molecular sub-graphs that participate in the formation of the graph molecular skeleton MG and could be complete (representing all possible connected sub-graphs) or constitute sub-graphs of determined orders or types as well as a combination of these. The Q matrix is a non-quadratic and unsymmetrical in nature, its columns (n) and rows (m) are conditions (letters) and collection of conditions (words) with which the event occurs. This non-quadratic and unsymmetrical matrix is transformed, by algebraic manipulation, to a quadratic and symmetric matrix known as relations frequency matrix, F, which characterizes the participation intensity of the conditions (letters) in the events (words). With F, we calculate the derivative over a pair of atomic nuclei. The local index for the atomic nuclei i, Δ(i), can therefore be obtained as a linear combination of all the pair derivatives of the atomic nuclei i with all the rest of the j's atomic nuclei. Here, we also define new strategies that generalize the present form of obtaining global or local (group or atom-type) invariants from atomic contributions (local vertex invariants, LOVIs). In respect to this, metric (norms), means and statistical invariants are introduced. These invariants are applied to a vector whose components are the values Δ(i) for the atomic nuclei of the molecule or its fragments. Moreover, with the purpose of differentiating

  3. Robust Affine Invariant Descriptors

    Directory of Open Access Journals (Sweden)

    Jianwei Yang

    2011-01-01

    Full Text Available An approach is developed for the extraction of affine invariant descriptors by cutting object into slices. Gray values associated with every pixel in each slice are summed up to construct affine invariant descriptors. As a result, these descriptors are very robust to additive noise. In order to establish slices of correspondence between an object and its affine transformed version, general contour (GC of the object is constructed by performing projection along lines with different polar angles. Consequently, affine in-variant division curves are derived. A slice is formed by points fall in the region enclosed by two adjacent division curves. To test and evaluate the proposed method, several experiments have been conducted. Experimental results show that the proposed method is very robust to noise.

  4. 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...... to the Common European Framework of Reference for Languages, specifying in detail and structuring its rationale on intercultural and plurilingual competences. The FREPA tools consist of (a) a comprehensive list of descriptors operationalizing intercultural and plurilingual competences in terms of knowledge...... that the FREPA project bridges theory and practice by equipping teachers with practical tools, which suit the needs of various contexts....

  5. Interpretable correlation descriptors for quantitativestructure-activity relationships

    Directory of Open Access Journals (Sweden)

    Spowage Benson M

    2009-12-01

    Full Text Available Abstract Background The topological maximum cross correlation (TMACC descriptors are alignment-independent 2D descriptors for the derivation of QSARs. TMACC descriptors are generated using atomic properties determined by molecular topology. Previous validation (J Chem Inf Model 2007, 47: 626-634 of the TMACC descriptor suggests it is competitive with the current state of the art. Results Here, we illustrate the interpretability of the TMACC descriptors, through the analysis of the QSARs of inhibitors of angiotensin converting enzyme (ACE and dihydrofolate reductase (DHFR. In the case of the ACE inhibitors, the TMACC interpretation shows features specific to C-domain inhibition, which have not been explicitly identified in previous QSAR studies. Conclusions The TMACC interpretation can provide new insight into the structure-activity relationships studied. Freely available, open source software for generating the TMACC descriptors can be downloaded from http://comp.chem.nottingham.ac.uk.

  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. Quantitative morphological descriptors confirm traditionally ...

    African Journals Online (AJOL)

    SARAH

    2015-09-30

    Sep 30, 2015 ... J. Appl. Biosci. 2015 Quantitative morphological descriptors confirm traditionally classified morphotypes of Pentadesma butyracea Sabine (clusiaceae). 8736. Quantitative morphological descriptors ...... Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis. A, 2004. The WorldClim interpolated global.

  8. 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.

  9. Alternative methods for estimating common descriptors for QSAR studies of dyes and fluorescent probes using molecular modeling software. 2. Correlations between log P and the hydrophilic/lipophilic index, and new methods for estimating degrees of amphiphilicity.

    Science.gov (United States)

    Dapson, Richard W; Horobin, Richard W

    2013-11-01

    The log P descriptor, despite its usefulness, can be difficult to use, especially for researchers lacking skills in physical chemistry. Moreover this classic measure has been determined in numerous ways, which can result in inconsistant estimates of log P values, especially for relatively complex molecules such as fluorescent probes. Novel measures of hydrophilicity/lipophilicity (the Hydrophilic/Lipophilic Index, HLI) and amphiphilicity (hydrophilic/lipophilic indices for the head group and tail, HLIT and HLIHG, respectively) therefore have been devised. We compare these descriptors with measures based on log P, the standard method for quantitative structure activity relationships (QSAR) studies. HLI can be determined using widely available molecular modeling software, coupled with simple arithmetic calculations. It is based on partial atomic charges and is intended to be a stand-alone measure of hydrophilicity/lipophilicity. Given the wide application of log P, however, we investigated the correlation between HLI and log P using a test set of 56 fluorescent probes of widely different physicochemical character. Overall correlation was poor; however, correlation of HLI and log P for probes of narrowly specified charge types, i.e., non-ionic compounds, anions, conjugated cations, or zwitterions, was excellent. Values for probes with additional nonconjugated quaternary cations, however, were less well correlated. The newly devised HLI can be divided into domain-specific descriptors, HLIT and HLIHG in amphiphilic probes. Determinations of amphiphilicity, made independently by the authors using their respective methods, showed excellent agreement. Quantifying amphiphilicity from partial log P values of the head group (head group hydrophilicity; HGH) and tail (amphiphilicity index; AI) has proved useful for understanding fluorescent probe action. The same limitations of log P apply to HGH and AI, however. The novel descriptors, HLIT and HLIHG, offer analogous advantages

  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......The paper discusses a set of tools that have been developed within the FREPA research project, supported since 2004 by the Council of Europe’s European Centre for Modern Languages. The Framework of Reference for Pluralistic Approaches to Languages and Cultures (FREPA) represents a complement...... to the Common European Framework of Reference for Languages, specifying in detail and structuring its rationale on intercultural and plurilingual competences. The FREPA tools consist of (a) a comprehensive list of descriptors operationalizing intercultural and plurilingual competences in terms of knowledge...

  11. 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

  12. Complementing ultrafast shape recognition with an optical isomerism descriptor.

    Science.gov (United States)

    Zhou, Ting; Lafleur, Karine; Caflisch, Amedeo

    2010-11-01

    We introduce the mixed product of three vectors spanning four molecular locations as a descriptor of optical isomerism. This descriptor is very efficient as it does not require molecular superposition, and is very robust in discriminating between a given isomer and its mirror image. In particular, conformational isomers that are mirror images of each other, as well as optical isomers have opposite sign of the descriptor value. For efficient database searches, the optical isomerism descriptor can be used to complement an available ultrafast shape recognition (USR) method based solely on distances, which is not able to distinguish enantiomers. By an extensive comparison of the USR-based similarity score with an approach based on Gaussian molecular volume overlap, the accuracy and completeness of the former are discussed. Copyright © 2010 Elsevier Inc. All rights reserved.

  13. Prediction of compounds activity in nuclear receptor signaling and stress pathway assays using machine learning algorithms and low dimensional molecular descriptors

    Directory of Open Access Journals (Sweden)

    Filip eStefaniak

    2015-12-01

    Full Text Available Toxicity evaluation of newly synthesized or used compounds is one of the main challenges during product development in many areas of industry. For example, toxicity is the second reason - after lack of efficacy - for failure in preclinical and clinical studies of drug candidates. To avoid attrition at the late stage of the drug development process, the toxicity analyses are employed at the early stages of a discovery pipeline, along with activity and selectivity enhancing. Although many assays for screening in vitro toxicity are available, their massive application is not always time and cost effective. Thus the need for fast and reliable in silico tools, which can be used not only for toxicity prediction of existing compounds, but also for prioritization of compounds planned for synthesis or acquisition. Here I present the benchmark results of the combination of various attribute selection methods and machine learning algorithms and their application to the data sets of the Tox21 Data Challenge. The best performing method: Best First for attribute selection with the Rotation Forest/ADTree classifier offers good accuracy for most tested cases. For 11 out of 12 targets, the AUROC value for the final evaluation set was ≥0.72, while for three targets the AUROC value was ≥ 0.80, with the average AUROC being 0.784±0.069. The use of two-dimensional descriptors sets enables fast screening and compound prioritization even for a very large database. Open source tools used in this project make the presented approach widely available and encourage the community to further improve the presented scheme.

  14. 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.

  15. 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 ...

  16. Understanding the Polar Character Trend in a Series of Diels-Alder Reactions Using Molecular Quantum Similarity and Chemical Reactivity Descriptors

    Directory of Open Access Journals (Sweden)

    Alejandro Morales-Bayuelo

    2014-01-01

    Full Text Available In molecular similarity there is a premise “similar molecules tend to behave similarly”; however in the actual quantum similarity field there is no clear methodology to describe the similarity in chemical reactivity, and with this end an analysis of charge-transfer (CT processes in a series of Diels-Alder (DA reactions between cyclopentadiene (Cp and cyano substitutions on ethylene has been studied. The CT analysis is performed in the reagent assuming a grand canonical ensemble and the considerations for an electrophilic system using B3LYP/6-31G(d and M06-2X/6-311 + G(d,p methods. An analysis for CT was performed in agreement with the experimental results with a good statistical correlation (R2=0.9118 relating the polar character to the bond force constants in DA reactions. The quantum distortion analysis on the transition states (TS was performed using molecular quantum similarity indexes of overlap and coulomb showing good correlation (R2=0.8330 between the rate constants and quantum similarity indexes. In this sense, an electronic reorganization based on molecular polarization in terms of CT is proposed; therefore, new interpretations on the electronic systematization of the DA reactions are presented, taking into account that today such electronic systematization is an open problem in organic physical chemistry. Additionally, one way to quantify the similarity in chemical reactivity was shown, taking into account the dependence of the molecular alignment on properties when their position changes; in this sense a possible way to quantify the similarity of the CT in systematic form on these DA cycloadditions was shown.

  17. Molecular descriptors calculation as a tool in the analysis of the antileishmanial activity achieved by two series of diselenide derivatives. An insight into its potential action mechanism.

    Science.gov (United States)

    Font, María; Baquedano, Ylenia; Plano, Daniel; Moreno, Esther; Espuelas, Socorro; Sanmartín, Carmen; Palop, Juan Antonio

    2015-07-01

    A molecular modeling study has been carried out on two previously reported series of symmetric diselenide derivatives that show remarkable antileishmanial in vitro activity against Leishmania infantum intracellular amastigotes and in infected macrophages (THP-1 cells), in addition to showing favorable selectivity indices. Series 1 consists of compounds that can be considered as central scaffold constructed with a diaryl/dialkylaryl diselenide central nucleus, decorated with different substituents located on the aryl rings. Series 2 consists of compounds constructed over a diaryl diselenide central nucleus, decorated in 4 and 4' positions with an aryl or heteroaryl sulfonamide fragment, thus forming the diselenosulfonamide derivatives. With regard to the diselenosulfonamide derivatives (2 series), the activity can be related, as a first approximation, with (a) the ability to release bis(4-aminophenyl) diselenide, the common fragment which can be ultimately responsible for the activity of the compounds. (b) the anti-parasitic activity achieved by the sulfonamide pharmacophore present in the analyzed derivatives. The data that support this connection include the topography of the molecules, the conformational behavior of the compounds, which influences the bond order, as well as the accessibility of the hydrolysis point, and possibly the hydrophobicity and polarizability of the compounds. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Separability of local reactivity descriptors

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Chemical Sciences; Volume 117; Issue 5. Separability of local ... We derive analytic results of these descriptors calculated using finite difference approximation. In particular, we studied ... Tanwar1 Sourav Pal1. Physical Chemistry Division, National Chemical Laboratory, Pune 411 008, India ...

  19. A 2D-QSAR and Grid-Independent Molecular Descriptor (GRIND) Analysis of Quinoline-Type Inhibitors of Akt2: Exploration of the Binding Mode in the Pleckstrin Homology (PH) Domain

    Science.gov (United States)

    Akhtar, Noreen; Jabeen, Ishrat

    2016-01-01

    Protein kinase B-β (PKBβ/Akt2) is a serine/threonine-specific protein kinase that has emerged as one of the most important regulators of cell growth, differentiation, and division. Upregulation of Akt2 in various human carcinomas, including ovarian, breast, and pancreatic, is a well-known tumorigenesis phenomenon. Early on, the concept of the simultaneous administration of anticancer drugs with inhibitors of Akt2 was advocated to overcome cell proliferation in the chemotherapeutic treatment of cancer. However, clinical studies have not lived up to the high expectations, and several phase II and phase III clinical studies have been terminated prematurely because of severe side effects related to the non-selective isomeric inhibition of Akt2. The notion that the sequence identity of pleckstrin homology (PH) domains within Akt-isoforms is less than 30% might indicate the possibility of the development of selective antagonists against the Akt2 PH domain. Therefore, in this study, various in silico tools were utilized to explore the hypothesis that quinoline-type inhibitors bind in the Akt2 PH domain. A Grid-Independent Molecular Descriptor (GRIND) analysis indicated that two hydrogen bond acceptors, two hydrogen bond donors and one hydrophobic feature at a certain distance from each other were important for the selective inhibition of Akt2. Our docking results delineated the importance of Lys30 as an anchor point for mapping the distances of important amino acid residues in the binding pocket, including Lys14, Glu17, Arg25, Asn53, Asn54 and Arg86. The binding regions identified complement the GRIND-based pharmacophoric features. PMID:28036396

  20. 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

  1. Molecular quantum similarity using conceptual DFT descriptors

    Indian Academy of Sciences (India)

    Unknown

    RCD ex- presses his acknowledgement to the Ministerio de. Ciencia y Tecnología for a grant that partially spon- sored this work and also for a Salvador de Madariaga fellowship permitting his stay at Gent University. References. 1. Rouvray D H 1995 Top. Curr. Chem. 173 1. 2. Herndon W C and Bertz S H 1987 J. Comput.

  2. Molecular quantum similarity using conceptual DFT descriptors

    Indian Academy of Sciences (India)

    Unknown

    Cortisol. Cortisone. H. H. H. HO. CH3. O. CH3. 9. O. H. H. H. CH2OH. O. CH3. CH3. 10. Dehydroepiandrosterone. 11-Deoxycorticosterone molecules included in the present set are shown in table 1. The 3-D structures of all molecules were gener- ated using AM157,58 geometry optimizations. Elec- tron densities were then ...

  3. Robust control of linear descriptor systems

    CERN Document Server

    Feng, Yu

    2017-01-01

    This book develops original results regarding singular dynamic systems following two different paths. The first consists of generalizing results from classical state-space cases to linear descriptor systems, such as dilated linear matrix inequality (LMI) characterizations for descriptor systems and performance control under regulation constraints. The second is a new path, which considers descriptor systems as a powerful tool for conceiving new control laws, understanding and deciphering some controller’s architecture and even homogenizing different—existing—ways of obtaining some new and/or known results for state-space systems. The book also highlights the comprehensive control problem for descriptor systems as an example of using the descriptor framework in order to transform a non-standard control problem into a classic stabilization control problem. In another section, an accurate solution is derived for the sensitivity constrained linear optimal control also using the descriptor framework. The boo...

  4. In Silico Design in Homogeneous Catalysis Using Descriptor Modelling

    Directory of Open Access Journals (Sweden)

    Gadi Rothenberg

    2006-09-01

    Full Text Available This review summarises the state-of-the-art methodologies used for designinghomogeneous catalysts and optimising reaction conditions (e.g. choosing the right solvent.We focus on computational techniques that can complement the current advances in high-throughput experimentation, covering the literature in the period 1996-2006. The reviewassesses the use of molecular modelling tools, from descriptor models based onsemiempirical and molecular mechanics calculations, to 2D topological descriptors andgraph theory methods. Different techniques are compared based on their computational andtime cost, output level, problem relevance and viability. We also review the application ofvarious data mining tools, including artificial neural networks, linear regression, andclassification trees. The future of homogeneous catalysis discovery and optimisation isdiscussed in the light of these developments.

  5. Multivariate analysis of hydrophobic descriptors

    Directory of Open Access Journals (Sweden)

    Stefan Dove

    2014-04-01

    Full Text Available Multivariate approaches like principal component analysis (PCA are powerful tools to investigate hydrophobic descriptors and to discriminate between intrinsic hydrophobicity and polar contributions as hydrogen bonds and other electronic effects. PCA of log P values measured for 37 solutes in eight solvent-water systems and of hydrophobic octanol-water substituent constants p for 25 meta- and para-substituents from seven phenyl series were performed (re-analysis of previous work. In both cases, the descriptors are repro­duced within experimental errors by two principal components, an intrinsic hydrophobic component and a second component accounting for differences between the systems due to electronic interactions. Underlying effects were identified by multiple linear regression analysis. Log P values depend on the water solubility of the solvents and hydrogen bonding capabilities of both the solute and the solvents. Results indicate different impacts of hydrogen bonds in nonpolar and polar solvent-water systems on log P and their dependence on isotropic and hydrated surface areas. In case of the p-values, the second component (loadings and scores correlates with electronic substituent constants. More detailed analysis of the data as p-values of disubstituted benzenes XPhY has led to extended symmetric bilinear Hammett-type models relating interaction increments to cross products pX sY, pY sX and sX sY which are mainly due to mutual effects on hydrogen-bonds with octanol.

  6. Descriptors of server capabilities in China

    DEFF Research Database (Denmark)

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

    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...... 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...

  7. Structural similarity and descriptor spaces for clustering and development of QSAR models.

    Science.gov (United States)

    Ruiz, Irene Luque; García, Gonzalo Cerruela; Gómez-Nieto, Miguel Angel

    2013-06-01

    In this paper we study and analyze the behavior of different representational spaces for the clustering and building of QSAR models. Representational spaces based on fingerprint similarity, structural similarity using maximum common subgraphs (MCS) and all maximum common subgraphs (AMCS) approaches are compared against representational spaces based on structural fragments and non-isomorphic fragments (NIF), built using different molecular descriptors. Algorithms for extraction of MCS, AMCS and NIF are described and support vector machine is used for the classification of a dataset corresponding with 74 compounds of 1,4-benzoquinone derivatives. Molecular descriptors are tested in order to build QSAR models for the prediction of the antifungal activity of the dataset. Descriptors based on the consideration of graph connectivity and distances are the most appropriate for building QSAR models. Moreover, models based on approximate similarity improve the statistical of the equations thanks to combining structural similarity, nonisomorphic fragments and descriptors approaches for the creation of more robust and finer prediction equations.

  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. Correlation of lipophilicity descriptors with pharmacokinetic ...

    African Journals Online (AJOL)

    The validity of lipophilicity determination based on different descriptors was evaluated using 4 model compounds of the benzodiazepine class; bromazepam, clonazepam, diazepam and lorazepam. Lipophilicity descriptors describing the retention behaviours of the model compounds were obtained from three approaches, ...

  10. Compact and tractable descriptors for information discovery

    NARCIS (Netherlands)

    Wondergem, B.C.M.

    2000-01-01

    The effectiveness and efficiency of searches for relevant documents strongly depend on key features of the descriptor language supported by the retrieval system. Effectiveness, for instance, is limited by the expressiveness of the descriptors. In addition, system efficiency is proportional to

  11. LDAHash: Improved Matching with Smaller Descriptors.

    Science.gov (United States)

    Strecha, C; Bronstein, A M; Bronstein, M M; Fua, P

    2012-01-01

    SIFT-like local feature descriptors are ubiquitously employed in computer vision applications such as content-based retrieval, video analysis, copy detection, object recognition, photo tourism, and 3D reconstruction. Feature descriptors can be designed to be invariant to certain classes of photometric and geometric transformations, in particular, affine and intensity scale transformations. However, real transformations that an image can undergo can only be approximately modeled in this way, and thus most descriptors are only approximately invariant in practice. Second, descriptors are usually high dimensional (e.g., SIFT is represented as a 128-dimensional vector). In large-scale retrieval and matching problems, this can pose challenges in storing and retrieving descriptor data. We map the descriptor vectors into the Hamming space in which the Hamming metric is used to compare the resulting representations. This way, we reduce the size of the descriptors by representing them as short binary strings and learn descriptor invariance from examples. We show extensive experimental validation, demonstrating the advantage of the proposed approach.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Separability of local reactivity descriptors

    Indian Academy of Sciences (India)

    Unknown

    their suggestions that improved the manuscript. References. 1. (a) Hanna M W and Lippert J L 1973 In Molecular complexes (ed.) R Foester (London: Eleck) vol 1; (b). Scheiner S (ed.) 1997 Molecular interactions: From van der Waals to strongly bound complexes (New. York: John-Wiley & Sons). 2. (a) Mayer I 1983 Chem.

  17. 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, which...... is needed to be controlled, is either in the descriptor form or can be represented in the descriptor form. Singular systems and the differential algebraic equation (DAE) systems are among these systems. Descriptor systems appear in the variety of fields to describe the practical processes ranging from power...... systems, hydraulic systems to heat transfer, and chemical processes. The focus of this paper is on the problem of control configuration selection for multivariable descriptor systems. A gramian-based interaction measure for control configuration selection of such processes is described in this paper...

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

    Science.gov (United States)

    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

  19. On atom-bond connectivity molecule structure descriptors

    Directory of Open Access Journals (Sweden)

    Furtula Boris

    2016-01-01

    Full Text Available The atom-bond connectivity index (ABC is a degree-based molecular structure descriptor with well-documented chemical applications. In 2010 a distance-based new variant of this index (ABCGG has been proposed. Until now, the relation between ABC and ABCGG has not been analyzed. In this paper, we establish the basic characteristics of this relation. In particular, ABC and ABCGG are not correlated and both cases ABC > ABCGG and ABC < ABCGG may occur in the case of (structurally similar molecules. However, in the case of benzenoid hydrocarbons, ABC always exceeds ABCGG. [Projekat Ministarstva nauke Republike Srbije, br. 174033

  20. Separability of local reactivity descriptors

    Indian Academy of Sciences (India)

    Unknown

    which are ratios of electrophilic to nucleophilic FF and vice-versa respectively, have been identified as more reliable criteria for intra-molecular reactivity.16. More recently, Parr and co-workers have defined a new concept of global philicity21 from which Chatta- raj and co-workers have defined local philicity indices,22 which ...

  1. Marcadores moleculares RAPD e descritores morfológicos na avaliação da diversidade genética de goiabeiras (Psidium guajava L. = RAPD molecular markers and morphological descriptors in the evaluation of genetic diversity of guava (Psidium guajava L.

    Directory of Open Access Journals (Sweden)

    Aroldo Gomes Filho

    2010-10-01

    Full Text Available O conhecimento da variabilidade genética e fenotípica entre diferentes acessos de goiabeiras é importante para se apoiar programas de melhoramento dessa espécie na região Norte Fluminense que carece de novas culturas capazes de gerar renda aos produtores locais. O objetivo deste trabalho foi avaliar a divergência genética entre seis cultivares e 19 acessos de goiabeiras, por meio de marcadores moleculares RAPD e características morfoagronômicas. Foram obtidas 117 marcas polimórficas, utilizando-se 28 iniciadores. Os resultados mostraram uma concordância parcial entre os métodos de agrupamentos estudados, com a formação de 12 grupos. O acesso Vita 3 e o acesso 6 foram os mais divergentes, apresentando distância genética de 0,663. A análise comparativa dos agrupamentos revelou que os marcadores RAPD e os descritores morfológicos foram eficientes para discriminação dos acessos e que houve variabilidade genética potencial para uso em Programa de Melhoramento Genético.The knowledge of the genetic and phenotypic variability among different accessions of guava is important for supporting improvement programs of this specie in northern Rio de Janeiro state, which needs new cultivars able to generate income for local farmers. This work aimed to evaluate the genetic divergence among six cultivars and 19 accessions of guava via RAPD molecular markers and morphologicalcharacteristics. One hundred and seventeen polymorphic markers were obtained from 28 primers. The results showed a partial agreement between the methods of studied groupings, with the formation of 12 groups. The accessions ‘Vita 3’and ‘6’ were the most divergent, showing genetic distance of 0.663. The comparative analysis of groupings showed that RAPD markers and morphological descriptors were effective in discriminating the accessions and to show potentialgenetic variability useful in genetic improvement programs.

  2. 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.

  3. Estudio teórico de la reactividad de las conformaciones y configuraciones de los ácidos grasos omega-3 a través de descriptores moleculares de reactividad utilizando la Teoría del Funcional de la Densidad (DFT

    Directory of Open Access Journals (Sweden)

    Jhon Zapata.

    2009-04-01

    Full Text Available La reactividad y estabilidad estructural de los ácidos omega-3, alfa-linolénico (ALA, estearidónico (SDA, eicosapentaenoico (EPA y docosahexaenoico (DHA, fue estudiada desde el punto de vista teórico haciendo uso de una serie de cálculos mecánico-cuánticos tipo DFT, usando la funcional B3LYP junto con la base de cálculo 6-31G. A través de descriptores de la reactividad química tales como, el potencial electrostático molecular (MEP, la función de Fukui, la dureza global, la suavidad global y local, energía de los orbitales HOMO-LUMO, se estudiaron algunas propiedades moleculares de los ácidos grasos omega-3, que permitió obtener información molecular valiosa acerca de los sitios reactivos y de la estabilidad estructural de este tipo de ácidos grasos.

  4. 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.

  5. Local Pyramidal Descriptors for Image Recognition.

    Science.gov (United States)

    Seidenari, Lorenzo; Serra, Giuseppe; Bagdanov, Andrew D; Del Bimbo, Alberto

    2014-05-01

    In this paper, we present a novel method to improve the flexibility of descriptor matching for image recognition by using local multiresolution pyramids in feature space. We propose that image patches be represented at multiple levels of descriptor detail and that these levels be defined in terms of local spatial pooling resolution. Preserving multiple levels of detail in local descriptors is a way of hedging one's bets on which levels will most relevant for matching during learning and recognition. We introduce the Pyramid SIFT (P-SIFT) descriptor and show that its use in four state-of-the-art image recognition pipelines improves accuracy and yields state-of-the-art results. Our technique is applicable independently of spatial pyramid matching and we show that spatial pyramids can be combined with local pyramids to obtain further improvement. We achieve state-of-the-art results on Caltech-101 (80.1%) and Caltech-256 (52.6%) when compared to other approaches based on SIFT features over intensity images. Our technique is efficient and is extremely easy to integrate into image recognition pipelines.

  6. Correlation of Lipophilicity Descriptors with Pharmacokinetic

    African Journals Online (AJOL)

    Dr Olaleye

    Correlation of Lipophilicity Descriptors with Pharmacokinetic. Parameters of Selected Benzodiazepines. Adeyemo M.A1 and Idowu S.O1*. 1Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Ibadan, Ibadan, Nigeria. ABSTRACT. In early-stage drug discovery science, it is often important to reliably ...

  7. 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.'

  8. Tracking image features with PCA-SURF descriptors

    CSIR Research Space (South Africa)

    Pancham, A

    2015-05-01

    Full Text Available , Principal Component Analysis (PCA) is applied to the 64-Dimension (D) Speeded Up Robust Features (SURF) descriptor to reduce the descriptor dimensionality and computational time, and suggest the minimum number of dimensions needed for reliable tracking...

  9. 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

  10. Shape Descriptors for Scanning Probe Recognition Microscopy

    Science.gov (United States)

    Chen, Qian; Ayres, Virginia; Udpa, Lalita

    2003-03-01

    Direct investigation of, and interaction with, biological objects at the macromolecular level will provide insight into multiple physical regulatory processes. Scanning probe microscopy (SPM) techniques have the potential to provide a direct interaction with living specimens at the macromolecular scale. A key enabling capability is to replace the current x-y raster scan with site-specific direct investigation. In the present research we will discuss the site-specific recognition techniques that are appropriate for tubular and globular biological features. The SPM image will be input to an image segmentation and boundary detection algorithm to extract closed boundaries of features in the image. The boundary information will be parameterized using Fourier descriptors, which are rotation invariant descriptors to be used for recognizing the segmented shape.

  11. Study of Fourier descriptors statistical features

    Science.gov (United States)

    Darwish, Ahmed M.; Mohamed, Emad-Eldin H.

    1993-12-01

    In this paper we present a new approach to reduce the computations involved in recognition applications. Fourier descriptors are treated as a occurrence of a complex random variable. Statistical function measures are then used to characterize the behavior of the complex variable. A study of pattern regeneration based on these statistical features was carried out. Some of these statistical measures were found to comprehend most of the object global features. Thus, they could be used for classification and recognition purposes.

  12. Local Radon Descriptors for Image Search

    OpenAIRE

    Babaie, Morteza; Tizhoosh, H. R.; Khatami, Amin; Shiri, M. E.

    2017-01-01

    Radon transform and its inverse operation are important techniques in medical imaging tasks. Recently, there has been renewed interest in Radon transform for applications such as content-based medical image retrieval. However, all studies so far have used Radon transform as a global or quasi-global image descriptor by extracting projections of the whole image or large sub-images. This paper attempts to show that the dense sampling to generate the histogram of local Radon projections has a muc...

  13. 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.

  14. 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.

  15. 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.

  16. Fingerprint identification using SIFT-based minutia descriptors and improved all descriptor-pair matching.

    Science.gov (United States)

    Zhou, Ru; Zhong, Dexing; Han, Jiuqiang

    2013-03-06

    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.

  17. 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.

  18. 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.

  19. 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.)

  20. Consensus approach for modeling HTS assays using in silico descriptors

    Directory of Open Access Journals (Sweden)

    Ahmed eAbdelaziz Sayed

    2016-02-01

    Full Text Available The need for filling information gaps while reducing toxicity testing in animals is becoming more predominant in risk assessment. Recent legislations are accepting in silico approaches for predicting toxicological outcomes. This article describes the results of Quantitative Structure Activity Relationship (QSAR modeling efforts within Tox21 Data Challenge 2014, which calculated the best balanced accuracy across all molecular pathway endpoints as well as the highest scores for ATAD5 and mitochondrial membrane potential disruption. Automated QSPR workflow systems, OCHEM (http://ochem.eu, the analytics platform, KNIME and the statistics software, CRAN R, were used to conduct the analysis and develop consensus models using ten different descriptor sets. A detailed analysis of QSAR models for all 12 molecular pathways and the effect of underlying models’ accuracy on the quality of the consensus model are provided. The resulting consensus models yielded a balanced accuracy as high as 88.1%±0.6 for mitochondrial membrane disruptors. Such high balanced accuracy and use of the applicability domain show a promising potential for in silico modeling to complement design HTS screening experiments. The summary statistics of all models are publicly available online at https://github.com/amaziz/Tox21-Challenge-Publication while the developed consensus models can be accessed at http://ochem.eu/article/98009.

  1. 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

  2. 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.

  3. 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.

  4. Web-4D-QSAR: A web-based application to generate 4D-QSAR descriptors.

    Science.gov (United States)

    Ataide Martins, João Paulo; Rougeth de Oliveira, Marco Antônio; Oliveira de Queiroz, Mário Sérgio

    2018-02-05

    A web-based application is developed to generate 4D-QSAR descriptors using the LQTA-QSAR methodology, based on molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. The LQTAGrid module calculates the intermolecular interaction energies at each grid point, considering probes and all aligned conformations resulting from MD simulations. These interaction energies are the independent variables or descriptors employed in a QSAR analysis. A friendly front end web interface, built using the Django framework and Python programming language, integrates all steps of the LQTA-QSAR methodology in a way that is transparent to the user, and in the backend, GROMACS and LQTAGrid are executed to generate 4D-QSAR descriptors to be used later in the process of QSAR model building. © 2018 Wiley Periodicals, Inc.

  5. 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.

  6. Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors.

    Science.gov (United States)

    Ding, Feng; Yang, Xianhai; Chen, Guosong; Liu, Jining; Shi, Lili; Chen, Jingwen

    2017-10-01

    The partition coefficients between bovine serum albumin (BSA) and water (K BSA/w ) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logK BSA/w . However, it was found that the conventional descriptors are inappropriate for modeling logK BSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K BSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logK BSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (V s-adj - ), the chemical form adjusted molecular dipole moment (dipolemoment adj ), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logK BSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. 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.

  8. 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.

  9. Feature Detector and Descriptor for Medical Images

    Science.gov (United States)

    Sargent, Dusty; Chen, Chao-I.; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Daniel

    2009-02-01

    The ability to detect and match features across multiple views of a scene is a crucial first step in many computer vision algorithms for dynamic scene analysis. State-of-the-art methods such as SIFT and SURF perform successfully when applied to typical images taken by a digital camera or camcorder. However, these methods often fail to generate an acceptable number of features when applied to medical images, because such images usually contain large homogeneous regions with little color and intensity variation. As a result, tasks like image registration and 3D structure recovery become difficult or impossible in the medical domain. This paper presents a scale, rotation and color/illumination invariant feature detector and descriptor for medical applications. The method incorporates elements of SIFT and SURF while optimizing their performance on medical data. Based on experiments with various types of medical images, we combined, adjusted, and built on methods and parameter settings employed in both algorithms. An approximate Hessian based detector is used to locate scale invariant keypoints and a dominant orientation is assigned to each keypoint using a gradient orientation histogram, providing rotation invariance. Finally, keypoints are described with an orientation-normalized distribution of gradient responses at the assigned scale, and the feature vector is normalized for contrast invariance. Experiments show that the algorithm detects and matches far more features than SIFT and SURF on medical images, with similar error levels.

  10. 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.

  11. In-silico Comparative Study and Quantitative Structure-activity Relationship Analysis of Some Structural and Physiochemical Descriptors of Elvitegravir Analogs.

    Science.gov (United States)

    Satpathy, R; Ghosh, S

    2011-07-01

    Elvitegravir is a new-generation drug which acts as an integrase inhibitor of the HIV virus. The potential inhibition has been tested from the clinical trial data. Here the work basically deals with the quantitative structure-activity relationship (QSAR) analysis by considering some of the physiochemical descriptors like molecular weight, logP, molar volume, and structural descriptors like Winers index, and molecular topological index of the drug analogs. The descriptors were calculated from the E-Dragon server and the multiple linear regression equation models were built by using Minitab tools. The different combinations of structural and physiochemical descriptors were considered for model derivation. The best three models were chosen by observing high R-Sq value, high F-value and low residual errors. The P values (regression) for the three models indicates the significance of the considered descriptors.The overall results obtained with these model suggest that for this perticular drug the activity is dependent on physiochemical descriptors.

  12. Fingerprint descriptors in tailoring new drugs using GUHA method

    Czech Academy of Sciences Publication Activity Database

    Hálová, Jaroslava; Žák, Přemysl

    2000-01-01

    Roč. 94, č. 9 (2000), s. 817 ISSN 0009-2770 Institutional research plan: CEZ:AV0Z4032918 Keywords : descriptor * fingerprint * guha Subject RIV: CA - Inorganic Chemistry Impact factor: 0.278, year: 2000

  13. 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.)

  14. Dimensionality reduction of medical image descriptors for multimodal image registration

    Directory of Open Access Journals (Sweden)

    Degen Johanna

    2015-09-01

    Full Text Available Defining similarity forms a challenging and relevant research topic in multimodal image registration. The frequently used mutual information disregards contextual information, which is shared across modalities. A recent popular approach, called modality independent neigh-bourhood descriptor, is based on local self-similarities of image patches and is therefore able to capture spatial information. This image descriptor generates vectorial representations, i.e. it is multidimensional, which results in a disadvantage in terms of computation time. In this work, we present a problem-adapted solution for dimensionality reduction, by using principal component analysis and Horn’s parallel analysis. Furthermore, the influence of dimensionality reduction in global rigid image registration is investigated. It is shown that the registration results obtained from the reduced descriptor have the same high quality in comparison to those found for the original descriptor.

  15. 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.

  16. 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...... Analysis (KPCA) that only keeps features contributing mostly to image reconstruction, KECA selects the CKD that contribute mostly to the Rényi entropy of the image. These CKD are discriminative as they relate to the density distribution of the histogram of image attributes. We report superior performance...

  17. 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.

  18. Correlation between Virtual Screening Performance and Binding Site Descriptors of Protein Targets.

    Science.gov (United States)

    Shamsara, Jamal

    2018-01-01

    Rescoring is a simple approach that theoretically could improve the original docking results. In this study AutoDock Vina was used as a docked engine and three other scoring functions besides the original scoring function, Vina, as well as their combinations as consensus scoring functions were employed to explore the effect of rescoring on virtual screenings that had been done on diverse targets. Rescoring by DrugScore produces the most number of cases with significant changes in screening power. Thus, the DrugScore results were used to build a simple model based on two binding site descriptors that could predict possible improvement by DrugScore rescoring. Furthermore, generally the screening power of all rescoring approach as well as original AutoDock Vina docking results correlated with the Maximum Theoretical Shape Complementarity (MTSC) and Maximum Distance from Center of Mass and all Alpha spheres (MDCMA). Therefore, it was suggested that, with a more complete set of binding site descriptors, it could be possible to find robust relationship between binding site descriptors and response to certain molecular docking programs and scoring functions. The results could be helpful for future researches aiming to do a virtual screening using AutoDock Vina and/or rescoring using DrugScore.

  19. Correlation between Virtual Screening Performance and Binding Site Descriptors of Protein Targets

    Directory of Open Access Journals (Sweden)

    Jamal Shamsara

    2018-01-01

    Full Text Available Rescoring is a simple approach that theoretically could improve the original docking results. In this study AutoDock Vina was used as a docked engine and three other scoring functions besides the original scoring function, Vina, as well as their combinations as consensus scoring functions were employed to explore the effect of rescoring on virtual screenings that had been done on diverse targets. Rescoring by DrugScore produces the most number of cases with significant changes in screening power. Thus, the DrugScore results were used to build a simple model based on two binding site descriptors that could predict possible improvement by DrugScore rescoring. Furthermore, generally the screening power of all rescoring approach as well as original AutoDock Vina docking results correlated with the Maximum Theoretical Shape Complementarity (MTSC and Maximum Distance from Center of Mass and all Alpha spheres (MDCMA. Therefore, it was suggested that, with a more complete set of binding site descriptors, it could be possible to find robust relationship between binding site descriptors and response to certain molecular docking programs and scoring functions. The results could be helpful for future researches aiming to do a virtual screening using AutoDock Vina and/or rescoring using DrugScore.

  20. The application of new HARD-descriptor available from the CORAL software to building up NOAEL models.

    Science.gov (United States)

    Toropova, Alla P; Toropov, Andrey A; Marzo, Marco; Escher, Sylvia E; Dorne, Jean Lou; Georgiadis, Nikolaos; Benfenati, Emilio

    2018-02-01

    Continuous QSAR models have been developed and validated for the prediction of no-observed-adverse-effect (NOAEL) in rats, using training and test sets from the Fraunhofer RepDose® database and EFSA's Chemical Hazards Database: OpenFoodTox. This paper demonstrates that the HARD index, as an integrated attribute of SMILES, improves the prediction power of NOAEL values using the continuous QSAR models and Monte Carlo simulations. The HARD-index is a line of eleven symbols, which represents the presence, or absence of eight chemical elements (nitrogen, oxygen, sulfur, phosphorus, fluorine, chlorine, bromine, and iodine) and different kinds of chemical bonds (double bond, triple bond, and stereo chemical bond). Optimal molecular descriptors calculated with the Monte Carlo technique (maximization of correlation coefficient between the descriptor and endpoint) give satisfactory predictive models for NOAEL. Optimal molecular descriptors calculated in this way with the Monte Carlo technique (maximization of correlation coefficient between the descriptor and endpoint) give amongst the best results available in the literature. The models are built up in accordance with OECD principles. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Application of Group-Based QSAR and Molecular Docking in the ...

    African Journals Online (AJOL)

    Selection of training and test sets. Fragment-based molecular descriptor calculations resulted in a pool of 325 different two-dimensional descriptors divided into 110,. 100, and 115 descriptors for fragment R1, R2, and R3, respectively. The sphere exclusion method with a dissimilarity value of +1 resulted in a training set of ...

  2. How strong is it? The interpretation of force and compliance constants as bond strength descriptors.

    Science.gov (United States)

    Brandhorst, Kai; Grunenberg, Jörg

    2008-08-01

    Knowledge about individual covalent or non-covalent bond strengths is the Holy Grail of many modern molecular sciences. Recent developments of new descriptors for such interaction strengths based on potential constants are summarised in this tutorial review. Several publications for and against the use of compliance matrices (inverse force constants matrix) have appeared in the literature in the last few years. However the mathematical basis for understanding, and therefore interpreting, compliance constants is still not well developed. We therefore summarise the theoretical foundations and point to the advantages and disadvantages of the use of force constants versus compliance constants for the description of both non-covalent and covalent interactions.

  3. 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.

  4. 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...

  5. Interframe coding of feature descriptors for mobile augmented reality.

    Science.gov (United States)

    Makar, Mina; Chandrasekhar, Vijay; Tsai, Sam S; Chen, David; Girod, Bernd

    2014-08-01

    Streaming mobile augmented reality applications require both real-time recognition and tracking of objects of interest in a video sequence. Typically, local features are calculated from the gradients of a canonical patch around a keypoint in individual video frames. In this paper, we propose a temporally coherent keypoint detector and design efficient interframe predictive coding techniques for canonical patches, feature descriptors, and keypoint locations. In the proposed system, we strive to transmit each patch or its equivalent feature descriptor with as few bits as possible by modifying a previously transmitted patch or descriptor. Our solution enables server-based mobile augmented reality where a continuous stream of salient information, sufficient for image-based retrieval, and object localization, is sent at a bit-rate that is practical for today's wireless links and less than one-tenth of the bit-rate needed to stream the compressed video to the server.

  6. Real-Time Traffic Sign Recognition using SURF Descriptor

    Directory of Open Access Journals (Sweden)

    Htet Wai Kyu

    2015-08-01

    Full Text Available For road safety traffic sign is essential for drivers by giving valuable safety and navigation information pedestrians and even for the development of autonomous driver assistance system. Traffic sign can be classified by two methods can be approached. First approach is color base segmentation which is the region of traffic sign by using HSV color space Hue Saturation and Value and the next approach is shape base segmentation using Hough Circle Detection. In thissystem we use circle shape base detection for every traffic sign. At first keypoints descriptor is extracted from each standard traffic sign image in database and then keypoints descriptor is taken from region of traffic sign extracted from Hough circle detection. After that the nearest distance is matched keypoints descriptor between in each standard traffic sign image in database and extracted traffic sign image.

  7. 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

  8. 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.

  9. Comparative performance of descriptors in a multiple linear and Kriging models: a case study on the acute toxicity of organic chemicals to algae.

    Science.gov (United States)

    Tugcu, Gulcin; Yilmaz, H Birkan; Saçan, Melek Türker

    2014-10-01

    This study presents quantitative structure-toxicity relationship (QSTR) models on the toxicity of 91 organic compounds to Chlorella vulgaris using multiple linear regression (MLR) and Kriging techniques. The molecular descriptors were calculated using SPARTAN and DRAGON programs, and descriptor selection was made by "all subset" method available in the QSARINS software. MLR and Kriging models developed with the same descriptors were compared. In addition to these models, Kriging method was used for descriptor selection, and model development. The selected descriptors showed the importance of hydrophobicity, molecular weight and atomic ionization state in describing the toxicity of a diverse set of chemicals to C. vulgaris. A QSTR model should be associated with appropriate measures of goodness-of-fit, robustness, and predictivity in order to be used for regulatory purpose. Therefore, while the internal performances (goodness-of-fit and robustness) of the models were determined by using a training set, the predictive abilities of the models were determined by using a test set. The results of the study showed that while MLR method is easier to apply, the Kriging method was more successful in predicting toxicity.

  10. 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. .

  11. Accumulation of different visual feature descriptors in a coherent framework

    DEFF Research Database (Denmark)

    Jessen, Jeppe Barsøe; Pilz, Florian; 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...

  12. Novel texture-based descriptors for tool wear condition monitoring

    Science.gov (United States)

    Antić, Aco; Popović, Branislav; Krstanović, Lidija; Obradović, Ratko; Milošević, Mijodrag

    2018-01-01

    All state-of-the-art tool condition monitoring systems (TCM) in the tool wear recognition task, especially those that use vibration sensors, heavily depend on the choice of descriptors containing information about the tool wear state which are extracted from the particular sensor signals. All other post-processing techniques do not manage to increase the recognition precision if those descriptors are not discriminative enough. In this work, we propose a tool wear monitoring strategy which relies on the novel texture based descriptors. We consider the module of the Short Term Discrete Fourier Transform (STDFT) spectra obtained from the particular vibration sensors signal utterance as the 2D textured image. This is done by identifying the time scale of STDFT as the first dimension, and the frequency scale as the second dimension of the particular textured image. The obtained textured image is then divided into particular 2D texture patches, covering a part of the frequency range of interest. After applying the appropriate filter bank, 2D textons are extracted for each predefined frequency band. By averaging in time, we extract from the textons for each band of interest the information regarding the Probability Density Function (PDF) in the form of lower order moments, thus obtaining robust tool wear state descriptors. We validate the proposed features by the experiments conducted on the real TCM system, obtaining the high recognition accuracy.

  13. Finding the Best Feature Detector-Descriptor Combination

    DEFF Research Database (Denmark)

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

    2011-01-01

    matching. The size of the dataset implies that we can also reasonably make deductions about the statistical significance of our results. We conclude, that the MSER and Difference of Gaussian (DoG) detectors with a SIFT or DAISY descriptor are the top performers. This performance is, however...

  14. 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

  15. 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

  16. 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.

  17. 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, ...

  18. 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.

  19. 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…

  20. 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 ...

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    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...

  2. Reactivity descriptors and electron density analysis for ligand ...

    Indian Academy of Sciences (India)

    We discuss evaluation of local descriptors using relaxed as well as frozen approximation and characterize the / acceptance/donor characteristics of the above ligands. The intermolecular reactivity sequence for the same systems is examined by the global and local philicity index. In addition, electron density analysis has ...

  3. 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 ...

  4. 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.

  5. A Comparative Study of Two Quantum Chemical Descriptors in Predicting Toxicity of Aliphatic Compounds towards Tetrahymena pyriformis

    Directory of Open Access Journals (Sweden)

    Altaf Hussain Pandith

    2010-01-01

    Full Text Available Quantum chemical parameters such as LUMO energy, HOMO energy, ionization energy (I, electron affinity (A, chemical potential (μ, hardness (η electronegativity (χ, philicity (ωα, and electrophilicity (ω of a series of aliphatic compounds are calculated at the B3LYP/6-31G(d level of theory. Quantitative structure-activity relationship (QSAR models are developed for predicting the toxicity (pIGC50 of 13 classes of aliphatic compounds, including 171 electron acceptors and 81 electron donors, towards Tetrahymena pyriformis. The multiple linear regression modeling of toxicity of these compounds is performed by using the molecular descriptor log P (1-octanol/water partition coefficient in conjunction with two other quantum chemical descriptors, electrophilicity (ω and energy of the lowest unoccupied molecular orbital (ELUMO. A comparison is made towards the toxicity predicting the ability of electrophilicity (ω versus ELUMO as a global chemical reactivity descriptor in addition to log P. The former works marginally better in most cases. There is a slight improvement in the quality of regression by changing the unit of IGC50 from mg/L to molarity and by removing the racemates and the diastereoisomers from the data set.

  6. Statistically validated QSARs, based on theoretical descriptors, for modeling aquatic toxicity of organic chemicals in Pimephales promelas (fathead minnow).

    Science.gov (United States)

    Papa, Ester; Villa, Fulvio; Gramatica, Paola

    2005-01-01

    The use of Quantitative Structure-Activity Relationships in assessing the potential negative effects of chemicals plays an important role in ecotoxicology. (LC50)(96h) in Pimephales promelas (Duluth database) is widely modeled as an aquatic toxicity end-point. The object of this study was to compare different molecular descriptors in the development of new statistically validated QSAR models to predict the aquatic toxicity of chemicals classified according to their MOA and in a unique general model. The applied multiple linear regression approach (ordinary least squares) is based on theoretical molecular descriptor variety (1D, 2D, and 3D, from DRAGON package, and some calculated logP). The best combination of modeling descriptors was selected by the Genetic Algorithm-Variable Subset Selection procedure. The robustness and the predictive performance of the proposed models was verified using both internal (cross-validation by LOO, bootstrap, Y-scrambling) and external statistical validations (by splitting the original data set into training and validation sets by Kohonen-artificial neural networks (K-ANN)). The model applicability domain (AD) was checked by the leverage approach to verify prediction reliability.

  7. Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor.

    Science.gov (United States)

    Prasanna, Prateek; Tiwari, Pallavi; Madabhushi, Anant

    2016-11-22

    In this paper, we introduce a new radiomic descriptor, Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe) for capturing subtle differences between benign and pathologic phenotypes which may be visually indistinguishable on routine anatomic imaging. CoLlAGe seeks to capture and exploit local anisotropic differences in voxel-level gradient orientations to distinguish similar appearing phenotypes. CoLlAGe involves assigning every image voxel an entropy value associated with the co-occurrence matrix of gradient orientations computed around every voxel. The hypothesis behind CoLlAGe is that benign and pathologic phenotypes even though they may appear similar on anatomic imaging, will differ in their local entropy patterns, in turn reflecting subtle local differences in tissue microarchitecture. We demonstrate CoLlAGe's utility in three clinically challenging classification problems: distinguishing (1) radiation necrosis, a benign yet confounding effect of radiation treatment, from recurrent tumors on T1-w MRI in 42 brain tumor patients, (2) different molecular sub-types of breast cancer on DCE-MRI in 65 studies and (3) non-small cell lung cancer (adenocarcinomas) from benign fungal infection (granulomas) on 120 non-contrast CT studies. For each of these classification problems, CoLlAGE in conjunction with a random forest classifier outperformed state of the art radiomic descriptors (Haralick, Gabor, Histogram of Gradient Orientations).

  8. Multimodal Algorithm for Iris Recognition with Local Topological Descriptors

    Science.gov (United States)

    Campos, Sergio; Salas, Rodrigo; Allende, Hector; Castro, Carlos

    This work presents a new method for feature extraction of iris images to improve the identification process. The valuable information of the iris is intrinsically located in its natural texture, and preserving and extracting the most relevant features is of paramount importance. The technique consists in several steps from adquisition up to the person identification. Our contribution consists in a multimodal algorithm where a fragmentation of the normalized iris image is performed and, afterwards, regional statistical descriptors with Self-Organizing-Maps are extracted. By means of a biometric fusion of the resulting descriptors, the features of the iris are compared and classified. The results with the iris data set obtained from the Bath University repository show an excellent accuracy reaching up to 99.867%.

  9. Learning linear discriminant projections for dimensionality reduction of image descriptors.

    Science.gov (United States)

    Cai, Hongping; Mikolajczyk, Krystian; Matas, Jiri

    2011-02-01

    In this paper, we present Linear Discriminant Projections (LDP) for reducing dimensionality and improving discriminability of local image descriptors. We place LDP into the context of state-of-the-art discriminant projections and analyze its properties. LDP requires a large set of training data with point-to-point correspondence ground truth. We demonstrate that training data produced by a simulation of image transformations leads to nearly the same results as the real data with correspondence ground truth. This makes it possible to apply LDP as well as other discriminant projection approaches to the problems where the correspondence ground truth is not available, such as image categorization. We perform an extensive experimental evaluation on standard data sets in the context of image matching and categorization. We demonstrate that LDP enables significant dimensionality reduction of local descriptors and performance increases in different applications. The results improve upon the state-of-the-art recognition performance with simultaneous dimensionality reduction from 128 to 30.

  10. Learning image descriptors for matching based on Haar features

    Science.gov (United States)

    Chen, L.; Rottensteiner, F.; Heipke, C.

    2014-08-01

    This paper presents a new and fast binary descriptor for image matching learned from Haar features. The training uses AdaBoost; the weak learner is built on response function for Haar features, instead of histogram-type features. The weak classifier is selected from a large weak feature pool. The selected features have different feature type, scale and position within the patch, having correspond threshold value for weak classifiers. Besides, to cope with the fact in real matching that dissimilar matches are encountered much more often than similar matches, cascaded classifiers are trained to motivate training algorithms see a large number of dissimilar patch pairs. The final trained output are binary value vectors, namely descriptors, with corresponding weight and perceptron threshold for a strong classifier in every stage. We present preliminary results which serve as a proof-of-concept of the work.

  11. 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...

  12. 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

  13. Automated detection of microaneurysms using robust blob descriptors

    OpenAIRE

    Adal, Kedir; Ali, Sharib; Sidibé, Désiré; Karnowski, T.P.; Chaum, Edward; Mériaudeau, Fabrice

    2013-01-01

    International audience; 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 a...

  14. Calculation of Five Thermodynamic Molecular Descriptors by Means of a General Computer Algorithm Based on the Group-Additivity Method: Standard Enthalpies of Vaporization, Sublimation and Solvation, and Entropy of Fusion of Ordinary Organic Molecules and Total Phase-Change Entropy of Liquid Crystals.

    Science.gov (United States)

    Naef, Rudolf; Acree, William E

    2017-06-25

    The calculation of the standard enthalpies of vaporization, sublimation and solvation of organic molecules is presented using a common computer algorithm on the basis of a group-additivity method. The same algorithm is also shown to enable the calculation of their entropy of fusion as well as the total phase-change entropy of liquid crystals. The present method is based on the complete breakdown of the molecules into their constituting atoms and their immediate neighbourhood; the respective calculations of the contribution of the atomic groups by means of the Gauss-Seidel fitting method is based on experimental data collected from literature. The feasibility of the calculations for each of the mentioned descriptors was verified by means of a 10-fold cross-validation procedure proving the good to high quality of the predicted values for the three mentioned enthalpies and for the entropy of fusion, whereas the predictive quality for the total phase-change entropy of liquid crystals was poor. The goodness of fit ( Q ²) and the standard deviation (σ) of the cross-validation calculations for the five descriptors was as follows: 0.9641 and 4.56 kJ/mol ( N = 3386 test molecules) for the enthalpy of vaporization, 0.8657 and 11.39 kJ/mol ( N = 1791) for the enthalpy of sublimation, 0.9546 and 4.34 kJ/mol ( N = 373) for the enthalpy of solvation, 0.8727 and 17.93 J/mol/K ( N = 2637) for the entropy of fusion and 0.5804 and 32.79 J/mol/K ( N = 2643) for the total phase-change entropy of liquid crystals. The large discrepancy between the results of the two closely related entropies is discussed in detail. Molecules for which both the standard enthalpies of vaporization and sublimation were calculable, enabled the estimation of their standard enthalpy of fusion by simple subtraction of the former from the latter enthalpy. For 990 of them the experimental enthalpy-of-fusion values are also known, allowing their comparison with predictions, yielding a correlation coefficient R

  15. Development of Theoretical Descriptors for Cytotoxicity Evaluation of Metallic Nanoparticles.

    Science.gov (United States)

    Boukhvalov, D W; Yoon, T H

    2017-08-21

    Motivated by the recent development of quantitative structure-activity relationship (QSAR) methods in the area of nanotoxicology, we proposed an approach to develop additional descriptors based on results of first-principles calculations. For the evaluation of the biochemical activity of metallic nanoparticles, we consider two processes: ion extraction from the surface of a specimen to aqueous media and water dissociation on the surface. We performed calculations for a set of metals (Al, Fe, Cu, Ag, Au, and Pt). Taking into account the diversity of atomic structures of real metallic nanoparticles, we performed calculations for different models such as (001) and (111) surfaces, nanorods, and two different cubic nanoparticles of 0.6 and 0.3 nm size. Significant energy dependence of the processes from the selected model of nanoparticle suggests that for the correct description we should combine the calculations for several representative models. In addition to the descriptors of chemical activity of the metallic nanoparticles for the two studied processes, we propose descriptors for taking into account the dependence of chemical activity from the size and shape of nanoparticles. Routes to minimization of computational costs for these calculations are also discussed.

  16. 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.

  17. 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.

  18. 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

    With the increasing ease of measuring and calculating multiple descriptors per molecule in quantitative structure-activity relationship, the importance of variable selection for data reduction and improving interpretability is gaining importance. While variable selection has been extensively...... to selection of 48 out of 160 initial descriptors, so that the data information was preserved. Lastly, using influence effect on prediction resulted in eight descriptors as representative of the 160 descriptors. Constructed model with final 8 descriptors has Q(IN)(2) = 0.67, R-2 = 0.74, Q(EXT)(2) = 0...

  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. 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.

  1. 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.

  2. CARACTERIZACIÓN DEL TALLO ACEPTOR DEL tRNA MEDIANTE DESCRIPTORES LOCALES BASADOS EN CARGAS PARCIALES

    Directory of Open Access Journals (Sweden)

    Ray Marín

    2009-04-01

    Full Text Available En este trabajo se caracteriza la distribución de carga del tallo aceptor del tRNA, considerando todas las posibles combinaciones de pares Watson-Crick. El estudio se realizó con 256 fragmentos moleculares de 10 nucleótidos que modelan los tres primeros pares del tallo aceptor, la base diferenciadora y el extremo CCA. Para caracterizar los nucleótidos se proponen dos descriptores locales basados en la distribución de carga de las base nitrogenada de cada nucleótido, los cuales se calculan a partir de las cargas parciales de Mulliken obtenidas de cálculos HF/6-31G. La caracterización y clasificación de los tallos según estos descriptores mostró como la base diferenciadora tiene un comportamiento particular respecto a los demás nucleótidos del tallo y una fuerte influencia sobre el extremo CCA. La clasificación de nueve variaciones del tallo aceptor del tRNAAla mostró una buena relación estructura-actividad que pone en evidencia la bondad de los descriptores propuestos para caracterizar de manera local la distribución de carga de estas biomoléculas. 

  3. 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.

  4. Anomaly Detection Based on Local Nearest Neighbor Distance Descriptor in Crowded Scenes

    Directory of Open Access Journals (Sweden)

    Xing Hu

    2014-01-01

    Full Text Available We propose a novel local nearest neighbor distance (LNND descriptor for anomaly detection in crowded scenes. Comparing with the commonly used low-level feature descriptors in previous works, LNND descriptor has two major advantages. First, LNND descriptor efficiently incorporates spatial and temporal contextual information around the video event that is important for detecting anomalous interaction among multiple events, while most existing feature descriptors only contain the information of single event. Second, LNND descriptor is a compact representation and its dimensionality is typically much lower than the low-level feature descriptor. Therefore, not only the computation time and storage requirement can be accordingly saved by using LNND descriptor for the anomaly detection method with offline training fashion, but also the negative aspects caused by using high-dimensional feature descriptor can be avoided. We validate the effectiveness of LNND descriptor by conducting extensive experiments on different benchmark datasets. Experimental results show the promising performance of LNND-based method against the state-of-the-art methods. It is worthwhile to notice that the LNND-based approach requires less intermediate processing steps without any subsequent processing such as smoothing but achieves comparable event better performance.

  5. Descriptor Based Analysis of Digital 3D Shapes

    DEFF Research Database (Denmark)

    Welnicka, Katarzyna

    Analysis and processing of 3D digital shapes is a significant research area with numerous medical, industrial, and entertainment applications which has gained enormously in importance as optical scanning modalities have started to make acquired 3D geometry commonplace. The area holds many...... challenges. One such challenge, which is addressed in this thesis, is to develop computational methods for classifying shapes which are in agreement with the human way of understanding and classifying shapes. In this dissertation we first present a shape descriptor based on the process of diffusion...

  6. 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.

  7. Factor Analytic Approach to Transitive Text Mining using Medline Descriptors

    Science.gov (United States)

    Stegmann, J.; Grohmann, G.

    Matrix decomposition methods were applied to examples of noninteractive literature sets sharing implicit relations. Document-by-term matrices were created from downloaded PubMed literature sets, the terms being the Medical Subject Headings (MeSH descriptors) assigned to the documents. The loadings of the factors derived from singular value or eigenvalue matrix decomposition were sorted according to absolute values and subsequently inspected for positions of terms relevant to the discovery of hidden connections. It was found that only a small number of factors had to be screened to find key terms in close neighbourhood, being separated by a small number of terms only.

  8. 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

  9. 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.

  10. 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

  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. 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.

  13. Models for anti-tumor activity of bisphosphonates using refined topochemical descriptors

    Science.gov (United States)

    Goyal, Rakesh K.; Singh, G.; Madan, A. K.

    2011-10-01

    An in silico approach comprising of decision tree (DT), random forest (RF) and moving average analysis (MAA) was successfully employed for development of models for prediction of anti-tumor activity of bisphosphonates. A dataset consisting of 65 analogues of both nitrogen-containing and non-nitrogen-containing bisphosphonates was selected for the present study. Four refinements of eccentric distance sum topochemical index termed as augmented eccentric distance sum topochemical indices 1-4 ( {ξ_{{1c}}^{{ADS}},ξ_{{2c}}^{{ADS}},ξ_{{3c}}^{{ADS}},ξ_{{4c}}^{{ADS}}} ) have been proposed so as to significantly augment discriminating power. Proposed topological indices (TIs) along with the exiting TIs (>1,400) were subsequently utilized for development of models for prediction of anti-tumor activity of bisphosphonates. A total of 43 descriptors of diverse nature, from a large pool of molecular descriptors, calculated through E-Dragon software (version 1.0) and an in-house computer program were selected for development of suitable models by employing DT, RF and MAA. DT identified two TIs as most important and classified the analogues of the dataset with an accuracy of 97% in training set and 90.7% in tenfold cross-validated set. Random forest correctly classified the analogues with an accuracy of 89.2%. Four independent models developed through MAA predicted the activity of analogues of the dataset with an accuracy of 87.6% to 89%. The statistical significance of proposed models was assessed through intercorrelation analysis, specificity, sensitivity and Matthew's correlation coefficient. The proposed models offer a vast potential for providing lead structures for development of potent anti-tumor agents for treatment of cancer that has spread to the bone.

  14. Selection of morphoagronomic descriptors for the characterization of accessions of cassava of the Eastern Brazilian Amazon.

    Science.gov (United States)

    Silva, R S; Moura, E F; Farias-Neto, J T; Ledo, C A S; Sampaio, J E

    2017-04-13

    The aim of this study was to select morphoagronomic descriptors to characterize cassava accessions representative of Eastern Brazilian Amazonia. It was characterized 262 accessions using 21 qualitative descriptors. The multiple-correspondence analysis (MCA) technique was applied using the criteria: contribution of the descriptor in the last factorial axis of analysis in successive cycles (SMCA); reverse order of the descriptor's contribution in the last factorial axis of analysis with all descriptors ('O'´p') of Jolliffe's method; mean of the contribution orders of the descriptor in the first three factorial axes in the analysis with all descriptors ('Os') together with ('O'´p'); and order of contribution of weighted mean in the first three factorial axes in the analysis of all descriptors ('Oz'). The dissimilarity coefficient was measured by the method of multicategorical variables. The correlation among the matrix generated with all descriptors and matrices based on each criteria varied (r = 0.21, r = 0.97, r = 0.98, r = 0.13 for SMCA, 'Os', 'Oz' and 'O'´p', respectively). The least informative descriptors were discarded independently and according to both 'Os' and 'Oz' criteria. Thirteen descriptors were capable to discriminate the accessions and to represent the morphological variability of accessions sampled in Brazilian Eastern Amazonia: color of apical leaves, petiole color, color of stem exterior, external color of storage root, color of stem cortex, color of root pulp, texture of root epidermis, color of leaf vein, color of stem epidermis, color of end branches of adult plant, branching habit, root shape, and constriction of root.

  15. Application of 3D Zernike descriptors to shape-based ligand similarity searching

    Directory of Open Access Journals (Sweden)

    Venkatraman Vishwesh

    2009-12-01

    Full Text Available Abstract Background The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. Conclusion The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

  16. Uterus segmentation in dynamic MRI using LBP texture descriptors

    Science.gov (United States)

    Namias, R.; Bellemare, M.-E.; Rahim, M.; Pirró, N.

    2014-03-01

    Pelvic floor disorders cover pathologies of which physiopathology is not well understood. However cases get prevalent with an ageing population. Within the context of a project aiming at modelization of the dynamics of pelvic organs, we have developed an efficient segmentation process. It aims at alleviating the radiologist with a tedious one by one image analysis. From a first contour delineating the uterus-vagina set, the organ border is tracked along a dynamic mri sequence. The process combines movement prediction, local intensity and texture analysis and active contour geometry control. Movement prediction allows a contour intitialization for next image in the sequence. Intensity analysis provides image-based local contour detection enhanced by local binary pattern (lbp) texture descriptors. Geometry control prohibits self intersections and smoothes the contour. Results show the efficiency of the method with images produced in clinical routine.

  17. Retrieval of Remote Sensing Images with Pattern Spectra Descriptors

    Directory of Open Access Journals (Sweden)

    Petra Bosilj

    2016-12-01

    Full Text Available The rapidly increasing volume of visual Earth Observation data calls for effective content based image retrieval solutions, specifically tailored for their high spatial resolution and heterogeneous content. In this paper, we address this issue with a novel local implementation of the well-known morphological descriptors called pattern spectra. They are computationally efficient histogram-like structures describing the global distribution of arbitrarily defined attributes of connected image components. Besides employing pattern spectra for the first time in this context, our main contribution lies in their dense calculation, at a local scale, thus enabling their combination with sophisticated visual vocabulary strategies. The Merced Landuse/Landcover dataset has been used for comparing the proposed strategy against alternative global and local content description methods, where the introduced approach is shown to yield promising performances.

  18. Planetary and Solar Data Labeled with IVOA Unified Content Descriptors

    Science.gov (United States)

    Louys, Mireille; Cecconi, Baptiste; Derriere, Sébastien; Erard, S.; André, N.; Preite-Martinez, A.; Ochsenbein, F.; Jacquey, C.; Génot, V.; Henry, F.; Bonnin, X.; Le Sidaner, P.; Chauvin, C.; Fuller, N.; Braga, V. F.; Aboudarham, J.

    2015-09-01

    Astronomical data collections are widely using tabular formats to expose their data to the community and especially in the Virtual Observatory. In order to label the content of physical quantities stored in table columns, The Unified Content Descriptors (UCDs) [Preite Martinez et al. (2011)] labels have been standardized and attached as semantic tags to a wide range of measurements and metadata. This unifies the content description across multiple data collections and archive centers. The Planetary and Solar science communities proposed, together with the IVOA Semantics Working group, to extend this bank of semantic labels for the distribution of their own collections and to adopt compatible standards such as VOTable, TAP, etc. This work shows the new UCD set proposed and how it is made available in the Virtual Observatory framework. A reference vocabulary is set up, UCD assigning tools and tests are presented.

  19. Ensemble of texture descriptors and classifiers for face recognition

    Directory of Open Access Journals (Sweden)

    Alessandra Lumini

    2017-01-01

    Full Text Available Presented in this paper is a novel system for face recognition that works well in the wild and that is based on ensembles of descriptors that utilize different preprocessing techniques. The power of our proposed approach is demonstrated on two datasets: the FERET dataset and the Labeled Faces in the Wild (LFW dataset. In the FERET datasets, where the aim is identification, we use the angle distance. In the LFW dataset, where the aim is to verify a given match, we use the Support Vector Machine and Similarity Metric Learning. Our proposed system performs well on both datasets, obtaining, to the best of our knowledge, one of the highest performance rates published in the literature on the FERET datasets. Particularly noteworthy is the fact that these good results on both datasets are obtained without using additional training patterns. The MATLAB source of our best ensemble approach will be freely available at https://www.dei.unipd.it/node/2357.

  20. Novel signal shape descriptors through wavelet transforms and dimensionality reduction

    Science.gov (United States)

    Hughes, Nicholas P.; Tarassenko, Lionel

    2003-11-01

    The wavelet transform is a powerful tool for capturing the joint time-frequency characteristics of a signal. However, the resulting wavelet coefficients are typically high-dimensional, since at each time sample the wavelet transform is evaluated at a number of distinct scales. Unfortunately, modelling these coefficients can be problematic because of the large number of parameters needed to capture the dependencies between different scales. In this paper we investigate the use of algorithms from the field of dimensionality reduction to extract informative and compact descriptions of shape from wavelet coefficients. These low-dimensional shape descriptors lead to models that are governed by only a small number of parameters and can be learnt successfully from limited amounts of data. The validity of our approach is demonstrated on the task of automatically segmenting an electrocardiogram signal into its constituent waveform features.

  1. Learning physical descriptors for materials science by compressed sensing

    Science.gov (United States)

    Ghiringhelli, Luca M.; Vybiral, Jan; Ahmetcik, Emre; Ouyang, Runhai; Levchenko, Sergey V.; Draxl, Claudia; Scheffler, Matthias

    2017-02-01

    The availability of big data in materials science offers new routes for analyzing materials properties and functions and achieving scientific understanding. Finding structure in these data that is not directly visible by standard tools and exploitation of the scientific information requires new and dedicated methodology based on approaches from statistical learning, compressed sensing, and other recent methods from applied mathematics, computer science, statistics, signal processing, and information science. In this paper, we explain and demonstrate a compressed-sensing based methodology for feature selection, specifically for discovering physical descriptors, i.e., physical parameters that describe the material and its properties of interest, and associated equations that explicitly and quantitatively describe those relevant properties. As showcase application and proof of concept, we describe how to build a physical model for the quantitative prediction of the crystal structure of binary compound semiconductors.

  2. Reactivity descriptors for direct methanol fuel cell anode catalysts

    DEFF Research Database (Denmark)

    Ferrin, Peter; Nilekar, Anand Udaykumar; Greeley, Jeff

    2008-01-01

    We have investigated the anode reaction in direct methanol fuel cells using a database of adsorption free energies for 16 intermediates on 12 close-packed transition metal surfaces calculated with periodic, self-consistent, density functional theory (DFT-GGA). This database, combined with a simple...... electrokinetic model of the methanol electrooxidation reaction, yields mechanistic insights that are consistent with previous experimental and theoretical studies on Pt, and extends these insights to a broad spectrum of other transition metals. In addition, by using linear scaling relations between...... the adsorption free energies of various intermediates in the reaction network, we find that the results determined with the full database of adsorption energies can be estimated by knowing only two key descriptors for each metal surface: the free energies of OH and CO on the surface. Two mechanisms for methanol...

  3. 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.

  4. 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.

  5. 32 CFR 256.10 - Air installations compatible use zone noise descriptors.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 2 2010-07-01 2010-07-01 false Air installations compatible use zone noise descriptors. 256.10 Section 256.10 National Defense Department of Defense (Continued) OFFICE OF THE SECRETARY OF DEFENSE (CONTINUED) MISCELLANEOUS AIR INSTALLATIONS COMPATIBLE USE ZONES § 256.10 Air installations compatible use zone noise descriptors. (...

  6. 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 ban...

  7. 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

  8. 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.

  9. 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...... and of course correlate well with subjective evaluation. More noise sources - including neighbours' activities - and an increased demand for high quality and comfort, together with a trend towards light-weight constructions, are contradictory and challenging. This calls for exchange of data and experience...

  10. 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....... 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...... 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...

  11. 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....... 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...... 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...

  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. 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.

  14. 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.

  15. On the information content of 2D and 3D descriptors for QSAR

    Directory of Open Access Journals (Sweden)

    Oprea Tudor I.

    2002-01-01

    Full Text Available To gain better understanding on the information content of two-dimensional (2D vs. three-dimensional (3D descriptor systems, we analyzed principal component analysis scores derived from 87 2D descriptors and 798 3D (ALMOND variables on a set of 5998 compounds of medicinal chemistry interest. The information overlap between ALMOND and 2D-based descriptors, as modeled by the fraction of explained variance (r² and by seven-groups cross-validation (q² in a two PLS components model was 40%. Individual component analysis indicates that the first and second principal components from the 2D-descriptors are related to the first and third dimensions from the ALMOND PCA model. The first ALMOND component is explained (61% by size-related descriptors, whereas the third component is marginally explained (25% by hydrophobicity-related descriptors. Surprisingly, 2D-based hydrogen-bonding descriptors did not contribute significantly in this analysis. These results do not a priori justify the choice of one methodology over the other, when performing QSAR studies.

  16. Spherical harmonics based descriptor for neural network potentials: Structure and dynamics of Au147 nanocluster

    Science.gov (United States)

    Jindal, Shweta; Chiriki, Siva; Bulusu, Satya S.

    2017-05-01

    We propose a highly efficient method for fitting the potential energy surface of a nanocluster using a spherical harmonics based descriptor integrated with an artificial neural network. Our method achieves the accuracy of quantum mechanics and speed of empirical potentials. For large sized gold clusters (Au147), the computational time for accurate calculation of energy and forces is about 1.7 s, which is faster by several orders of magnitude compared to density functional theory (DFT). This method is used to perform the global minimum optimizations and molecular dynamics simulations for Au147, and it is found that its global minimum is not an icosahedron. The isomer that can be regarded as the global minimum is found to be 4 eV lower in energy than the icosahedron and is confirmed from DFT. The geometry of the obtained global minimum contains 105 atoms on the surface and 42 atoms in the core. A brief study on the fluxionality in Au147 is performed, and it is concluded that Au147 has a dynamic surface, thus opening a new window for studying its reaction dynamics.

  17. Spherical harmonics based descriptor for neural network potentials: Structure and dynamics of Au147nanocluster.

    Science.gov (United States)

    Jindal, Shweta; Chiriki, Siva; Bulusu, Satya S

    2017-05-28

    We propose a highly efficient method for fitting the potential energy surface of a nanocluster using a spherical harmonics based descriptor integrated with an artificial neural network. Our method achieves the accuracy of quantum mechanics and speed of empirical potentials. For large sized gold clusters (Au 147 ), the computational time for accurate calculation of energy and forces is about 1.7 s, which is faster by several orders of magnitude compared to density functional theory (DFT). This method is used to perform the global minimum optimizations and molecular dynamics simulations for Au 147 , and it is found that its global minimum is not an icosahedron. The isomer that can be regarded as the global minimum is found to be 4 eV lower in energy than the icosahedron and is confirmed from DFT. The geometry of the obtained global minimum contains 105 atoms on the surface and 42 atoms in the core. A brief study on the fluxionality in Au 147 is performed, and it is concluded that Au 147 has a dynamic surface, thus opening a new window for studying its reaction dynamics.

  18. Sensory and affective pain descriptors respond differentially to pharmacological interventions in neuropathic conditions.

    Science.gov (United States)

    Gilron, Ian; Tu, Dongsheng; Holden, Ronald R

    2013-02-01

    Pain management is limited by inability to match a patient's condition-and pain mechanisms-to optimal treatment(s). Much is known about pain treatment from animal investigations, but antinociceptive mechanisms cannot be readily explored in clinical studies. Evidence suggests that self-report verbal pain descriptors characterize important pain dimensions and may reflect diverse underlying mechanisms. This exploratory analysis of data from a trial of a gabapentin-morphine combination evaluated effects of treatment on short-form McGill Pain Questionnaire sensory and affective descriptor profiles and prediction of treatment response by these descriptors. Severity of "throbbing," "shooting," and "aching" improved preferentially with morphine over gabapentin, whereas "tiring-exhausting" and "sickening" improved preferentially with gabapentin over morphine. Improvement in descriptor severity with gabapentin-morphine combination was superior to active placebo for 12 of 15 short-form McGill Pain Questionnaire descriptors, whereas morphine and gabapentin were superior to active placebo for only 7 and 6 descriptors, respectively. Baseline moderate-severe "throbbing" and "hot-burning" predicted poor outcomes with gabapentin, whereas moderate-severe "aching" and "punishing-cruel" predicted favorable outcomes with gabapentin. Baseline "throbbing" severity also predicted poor outcomes with morphine. Baseline allodynia predicted superior reduction of "stabbing" with morphine but not with gabapentin alone. These results point to the hypothesis that sensory and affective pain descriptor profiles exhibit a treatment-specific response. Larger, more definitive, investigations to evaluate treatment-specific effects on multiple sensory and affective pain descriptors, and prediction of treatment response by these descriptors, will advance efforts toward developing and implementing more effective individualized pain therapies.

  19. Automated selection of BI-RADS lesion descriptors for reporting calcifications in mammograms

    Science.gov (United States)

    Paquerault, Sophie; Jiang, Yulei; Nishikawa, Robert M.; Schmidt, Robert A.; D'Orsi, Carl J.; Vyborny, Carl J.; Newstead, Gillian M.

    2003-05-01

    We are developing an automated computer technique to describe calcifications in mammograms according to the BI-RADS lexicon. We evaluated this technique by its agreement with radiologists' description of the same lesions. Three expert mammographers reviewed our database of 90 cases of digitized mammograms containing clustered microcalcifications and described the calcifications according to BI-RADS. In our study, the radiologists used only 4 of the 5 calcification distribution descriptors and 5 of the 14 calcification morphology descriptors contained in BI-RADS. Our computer technique was therefore designed specifically for these 4 calcification distribution descriptors and 5 calcification morphology descriptors. For calcification distribution, 4 linear discriminant analysis (LDA) classifiers were developed using 5 computer-extracted features to produce scores of how well each descriptor describes a cluster. Similarly, for calcification morphology, 5 LDAs were designed using 10 computer-extracted features. We trained the LDAs using only the BI-RADS data reported by the first radiologist and compared the computer output to the descriptor data reported by all 3 radiologists (for the first radiologist, the leave-one-out method was used). The computer output consisted of the best calcification distribution descriptor and the best 2 calcification morphology descriptors. The results of the comparison with the data from each radiologist, respectively, were: for calcification distribution, percent agreement, 74%, 66%, and 73%, kappa value, 0.44, 0.36, and 0.46; for calcification morphology, percent agreement, 83%, 77%, and 57%, kappa value, 0.78, 0.70, and 0.44. These results indicate that the proposed computer technique can select BI-RADS descriptors in good agreement with radiologists.

  20. 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.

  1. Pollen Image Recognition Based on DGDB-LBP Descriptor

    Science.gov (United States)

    Han, L. P.; Xie, Y. H.

    2018-01-01

    In this paper, we propose DGDB-LBP, a local binary pattern descriptor based on the pixel blocks in the dominant gradient direction. Differing from traditional LBP and its variants, DGDB-LBP encodes by comparing the main gradient magnitude of each block rather than the single pixel value or the average of pixel blocks, in doing so, it reduces the influence of noise on pollen images and eliminates redundant and non-informative features. In order to fully describe the texture features of pollen images and analyze it under multi-scales, we propose a new sampling strategy, which uses three types of operators to extract the radial, angular and multiple texture features under different scales. Considering that the pollen images have some degree of rotation under the microscope, we propose the adaptive encoding direction, which is determined by the texture distribution of local region. Experimental results on the Pollenmonitor dataset show that the average correct recognition rate of our method is superior to other pollen recognition methods in recent years.

  2. Improved SIFT descriptor applied to stereo image matching

    Science.gov (United States)

    Zeng, Luan; Zhai, You; Xiong, Wei

    2015-02-01

    Scale Invariant Feature Transform (SIFT) has been proven to perform better on the distinctiveness and robustness than other features. But it cannot satisfy the needs of low contrast images matching and the matching results are sensitive to 3D viewpoint change of camera. In order to improve the performance of SIFT to low contrast images and images with large 3D viewpoint change, a new matching method based on improved SIFT is proposed. First, an adaptive contrast threshold is computed for each initial key point in low contrast image region, which uses pixels in its 9×9 local neighborhood, and then using it to eliminate initial key points in low contrast image region. Second, a new SIFT descriptor with 48 dimensions is computed for each key point. Third, a hierarchical matching method based on epipolar line and differences of key points' dominate orientation is presented. The experimental results prove that the method can greatly enhance the performance of SIFT to low contrast image matching. Besides, when applying it to stereo images matching with the hierarchical matching method, the correct matches and matching efficiency are greatly enhanced.

  3. Robustness of shape descriptors to incomplete contour representations.

    Science.gov (United States)

    Ghosh, Anarta; Petkov, Nicolai

    2005-11-01

    With inspiration from psychophysical researches of the human visual system, we propose a novel aspect and a method for performance evaluation of contour-based shape recognition algorithms regarding their robustness to incompleteness of contours. We use complete contour representations of objects as a reference (training) set. Incomplete contour representations of the same objects are used as a test set. The performance of an algorithm is reported using the recognition rate as a function of the percentage of contour retained. We call this evaluation procedure the ICR test. We consider three types of contour incompleteness, viz. segment-wise contour deletion, occlusion, and random pixel depletion. As an illustration, the robustness of two shape recognition algorithms to contour incompleteness is evaluated. These algorithms use a shape context and a distance multiset as local shape descriptors. Qualitatively, both algorithms mimic human visual perception in the sense that recognition performance monotonously increases with the degree of completeness and that they perform best in the case of random depletion and worst in the case of occluded contours. The distance multiset method performs better than the shape context method in this test framework.

  4. Unevenness Point Descriptor for Terrain Analysis in Mobile Robot Applications

    Directory of Open Access Journals (Sweden)

    Mauro Bellone

    2013-07-01

    Full Text Available In recent years, the use of imaging sensors that produce a three-dimensional representation of the environment has become an efficient solution to increase the degree of perception of autonomous mobile robots. Accurate and dense 3D point clouds can be generated from traditional stereo systems and laser scanners or from the new generation of RGB-D cameras, representing a versatile, reliable and cost-effective solution that is rapidly gaining interest within the robotics community. For autonomous mobile robots, it is critical to assess the traversability of the surrounding environment, especially when driving across natural terrain. In this paper, a novel approach to detect traversable and non-traversable regions of the environment from a depth image is presented that could enhance mobility and safety through integration with localization, control and planning methods. The proposed algorithm is based on the analysis of the normal vector of a surface obtained through Principal Component Analysis and it leads to the definition of a novel, so defined, Unevenness Point Descriptor. Experimental results, obtained with vehicles operating in indoor and outdoor environments, are presented to validate this approach.

  5. 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.

  6. Controlled Invariant Polyhedral Sets for Constrained Discrete-Time Descriptor Systems

    Science.gov (United States)

    Araújo, José Mario; Dórea, Carlos Eduardo Trabuco

    This paper addresses the problem of constructing controlled invariant polyhedral sets for linear discrete-time descriptor systems subject to state and control constraints and persistent disturbances. Regardless the large number of contributions on set invariance for linear systems in the standard form, there are few works dealing with set invariance properties in the case of descriptor systems. Here, assuming regularity and causality of the descriptor system, the state equations are written in such way that standard algorithms can be directly applied. Moreover, state and control constraints can be enforced through a piecewise linear delayed state feedback. A numerical example is presented to illustrate these ideas.

  7. 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

    descriptor; (2) dense sampling outperforms interest point detectors with a clear margin; (3) detectors perform moderately well, but descriptors׳ performance collapses; (4) using multiple, even a few, best matches instead of the single best has significant effect on the performance; (5) object pose variation...... degrades dense sampling performance while the best detector (Hessian-affine) is unaffected. The performance of the best detector-descriptor pair is verified in the application of unsupervised visual class alignment where state-of-the-art results are achieved. The findings help to improve the existing...

  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 atom from the closest end of a branch or the molecule. The end of a branch and the end of a molecule, as well as the selection of the fragments, are made by an algorithm that uses only the distance matrix of the molecule. The novel descriptors are applied to a small set of biotransformation rules...

  9. 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....... Contrary to existing methods that rely on a dominant orientation estimate to achieve rotation invariance, we utilize the orientation information in the Gabor bank to achieve rotation invariance during the matching stage. Compared to SIFT and a recent also projective distortion compensating descriptor...

  10. 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.

  11. 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...

  12. 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.

  13. 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...

  14. 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...... plane and the depth direction, is developed to take full advantage of the available depth information. By embedding DCKD and JSDP into the standard object classification pipeline, we achieve superior performance to state-of-the-art methods on RGB-D benchmarks for object classification and scene...

  15. GENETIC DIVERSITY IN ACCESSIONS OF Stylosanthes spp. USING MORPHOAGRONOMIC DESCRIPTORS

    Directory of Open Access Journals (Sweden)

    RONALDO SIMÃO DE OLIVEIRA

    2016-01-01

    Full Text Available The great diversity of plants in the Brazilian Semiarid environment represents a vital natural resource for the human populations of these areas. Many of these plants have been subject to extractivism and among these, the species of the genus Stylosanthes , which have occurrence in this region, show great potential, however, studies on this topic are limited, and little is known about the existing variability among these plants. Therefore, further study is necessary, to facilitate the development of cultivars. This might reduce the scarcity of fodder supply in this region, but to commence a plant breeding programme, it is essential to identify genetic variability. Therefore, this study evaluated 25 accessions of Stylosanthes spp., to identify the most suitable candidates to be parents in a plant breeding programme for the semiarid region of the state of Bahia. Two experiments were carried out in different sites in an experimental design of randomized blocks with four replicates, with a spacing of 3.0 × 8.0 m. A large amount of genetic diversity was observed among accessions and the genotypes BGF 08 - 007, BGF 08 - 016, BGF 08 - 015 and BGF 08 - 021 were the most divergent in the overall evaluation. For the structuring of segregating populations, it is recommended to combine the genotypes BGF 08 - 016, BGF 08 - 015, BGF 08 - 007 and BGF 08 - 006, and for the interspecific crosses, a hybrid from the accession BGF - 024 with the accessions BGF 08 - 016 or BGF 08 - 015. This might generate superior individuals for mass descriptors, which are the most important for animal forage breeding.

  16. Quantitative structure-activity relationship (QSAR) analysis of plant-derived compounds with larvicidal activity against Zika Aedes aegypti (Diptera: Culicidae) vector using freely available descriptors.

    Science.gov (United States)

    Saavedra, Laura M; Romanelli, Gustavo P; Duchowicz, Pablo R

    2018-01-04

    We have developed a quantitative structure-activity relationship (QSAR) model for predicting the larvicidal activity of 60 plant-derived molecules against Aedes aegypti L. (Diptera: Culicidae), a vector of several diseases such as dengue, yellow fever, chikungunya and Zika. The balanced subsets method (BSM) based on k-means cluster analysis (k-MCA) was employed to split the data set. The replacement method (RM) variable subset selection technique coupled with multivariable linear regression (MLR) proved to be successful for exploring 18 326 molecular descriptors and fingerprints calculated with PaDEL, Mold 2 and EPI Suite open-source softwares. A robust QSAR model (Rtrain2=0.84, S train  = 0.20 and Rtest2=0.92, S test  = 0.23) involving five non-conformational descriptors was established. The model was validated and tested through the use of an external test set of compounds, the leave-one-out (LOO) and leave-more-out (LMO) cross-validation methods, Y-randomization and applicability domain (AD) analysis. The QSAR model surpasses previously published models based on geometrical descriptors, thereby representing a suitable tool for predicting larvicidal activity against the vector A. aegypti using a conformation-independent approach. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

  17. Soundscape descriptors and a conceptual framework for developing predictive soundscape models

    OpenAIRE

    Aletta, F.; Kang, J.; Axelsson, O.

    2016-01-01

    Soundscape exists through human perception of the acoustic environment. This paper investigates how soundscape currently is assessed and measured. It reviews and analyzes the main soundscape descriptors in the soundscape literature, and provides a conceptual framework for developing predictive models in soundscape studies. A predictive soundscape model provides a means of predicting the value of a soundscape descriptor, and the blueprint for how to design soundscape. It is the key for impleme...

  18. 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

  19. Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection.

    Science.gov (United States)

    Gottschlich, Carsten

    2016-01-01

    We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification.

  20. Fast Matching of Binary Descriptors for Large-Scale Applications in Robot Vision

    Directory of Open Access Journals (Sweden)

    Andreas Persson

    2016-03-01

    Full Text Available The introduction of computationally efficient binary feature descriptors has raised new opportunities for real-world robot vision applications. However, brute force feature matching of binary descriptors is only practical for smaller datasets. In the literature, there has therefore been an increasing interest in representing and matching binary descriptors more efficiently. In this article, we follow this trend and present a method for efficiently and dynamically quantizing binary descriptors through a summarized frequency count into compact representations (called fsum for improved feature matching of binary point-features. With the motivation that real-world robot applications must adapt to a changing environment, we further present an overview of the field of algorithms, which concerns the efficient matching of binary descriptors and which are able to incorporate changes over time, such as clustered search trees and bag-of-features improved by vocabulary adaptation. The focus for this article is on evaluation, particularly large scale evaluation, compared to alternatives that exist within the field. Throughout this evaluation it is shown that the fsum approach is both efficient in terms of computational cost and memory requirements, while retaining adequate retrieval accuracy. It is further shown that the presented algorithm is equally suited to binary descriptors of arbitrary type and that the algorithm is therefore a valid option for several types of vision applications.

  1. Effective structural descriptors for natural and engineered radioactive waste confinement barriers

    Science.gov (United States)

    Lemmens, Laurent; Rogiers, Bart; De Craen, Mieke; Laloy, Eric; Jacques, Diederik; Huysmans, Marijke; Swennen, Rudy; Urai, Janos L.; Desbois, Guillaume

    2017-04-01

    The microstructure of a radioactive waste confinement barrier strongly influences its flow and transport properties. Numerical flow and transport simulations for these porous media at the pore scale therefore require input data that describe the microstructure as accurately as possible. To date, no imaging method can resolve all heterogeneities within important radioactive waste confinement barrier materials as hardened cement paste and natural clays at the micro scale (nm-cm). Therefore, it is necessary to merge information from different 2D and 3D imaging methods using porous media reconstruction techniques. To qualitatively compare the results of different reconstruction techniques, visual inspection might suffice. To quantitatively compare training-image based algorithms, Tan et al. (2014) proposed an algorithm using an analysis of distance. However, the ranking of the algorithm depends on the choice of the structural descriptor, in their case multiple-point or cluster-based histograms. We present here preliminary work in which we will review different structural descriptors and test their effectiveness, for capturing the main structural characteristics of radioactive waste confinement barrier materials, to determine the descriptors to use in the analysis of distance. The investigated descriptors are particle size distributions, surface area distributions, two point probability functions, multiple point histograms, linear functions and two point cluster functions. The descriptor testing consists of stochastically generating realizations from a reference image using the simulated annealing optimization procedure introduced by Karsanina et al. (2015). This procedure basically minimizes the differences between pre-specified descriptor values associated with the training image and the image being produced. The most efficient descriptor set can therefore be identified by comparing the image generation quality among the tested descriptor combinations. The assessment

  2. 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

  3. Preference for different anchor descriptors on visual analogue scales among Japanese patients with chronic pain.

    Directory of Open Access Journals (Sweden)

    Junya Yokobe

    Full Text Available CONTEXT: Although many previous studies have examined the preference of patients for different pain measurement scales, preference for anchor descriptors has not been thoroughly discussed. OBJECTIVES: To examine (1 the preferred end-phrases used in the VAS as anchor labels for Japanese patients with chronic pain, and (2 whether the preference differs according to factors such as age, sex, educational level, duration of pain, and pain intensity. METHODS: We performed an observational study in patients suffering from non-cancer chronic pain for more than 3 months at a pain center in Japan. The patients were asked to rate their pain intensity using four types of VAS that used the following different anchor descriptors: "worst pain" ("Worst", "worst pain bearable" ("Bearable", "worst pain imaginable" ("Imaginable", and "worst pain you have ever experienced" ("Experienced". They were also asked to rank the four scales according to ease of responding, and asked which descriptor best reflected their perceived pain. RESULTS: In total, 183 patients participated in the study. They consisted of 119 (65.0% women and 64 (35.0% men aged 18-84 years with the mean age of 56.9 years. "Experienced" was most preferred (69.8%, followed by "Bearable" (66.3%, "Worst" (48.8%, and "Imaginable" (16.9%. Factors such as age, sex, educational background, duration of pain, and pain intensity did not significantly affect the results. In 83.1% of patients, the preferred descriptor corresponded to the descriptor that best reflected patients' perceived pain. CONCLUSION: The frequently used expression "worst pain imaginable" is considered to be difficult to understand for most patients. Widely preferred descriptors, such as "worst pain you have ever experienced" and "worst pain bearable", should be used when evaluating perceived pain. The preference of anchor descriptors was not significantly affected by the factors such as age, sex, educational level, duration of pain, and pain

  4. The utilisation of structural descriptors to predict metabolic constants of xenobiotics in mammals.

    Science.gov (United States)

    Pirovano, Alessandra; Brandmaier, Stefan; Huijbregts, Mark A J; Ragas, Ad M J; Veltman, Karin; Hendriks, A Jan

    2015-01-01

    Quantitative structure-activity relationships (QSARs) were developed to predict the Michaelis-Menten constant (Km) and the maximum reaction rate (Vmax) of xenobiotics metabolised by four enzyme classes in mammalian livers: alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO), and cytochrome P450 (CYP). Metabolic constants were gathered from the literature and a genetic algorithm was employed to select at most six predictors from a pool of over 2000 potential molecular descriptors using two-thirds of the xenobiotics in each enzyme class. The resulting multiple linear models were cross-validated using the remaining one-third of the compounds. The explained variances (R(2)adj) of the QSARs were between 50% and 80% and the predictive abilities (R(2)ext) between 50% and 60%, except for the Vmax QSAR of FMO with both R(2)adj and R(2)ext less than 30%. The Vmax values of FMO were independent of substrate chemical structure because the rate-limiting step of its catalytic cycle occurs before compound oxidation. For the other enzymes, Vmax was predominantly determined by functional groups or fragments and electronic properties because of the strong and chemical-specific interactions involved in the metabolic reactions. The most relevant predictors for Km were functional groups or fragments for the enzymes metabolising specific compounds (ADH, ALDH and FMO) and size and shape properties for CYP, likely because of the broad substrate specificity of CYP enzymes. The present study can be helpful to predict the Km and Vmax of four important oxidising enzymes in mammals and better understand the underlying principles of chemical transformation by liver enzymes. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Molecular Descriptors Family on Structure Activity Relationships 2. Insecticidal Activity of Neonicotinoid Compounds

    Directory of Open Access Journals (Sweden)

    Sorana BOLBOACĂ

    2005-01-01

    Full Text Available The neonicotinoids are the newest major class of insecticides modeled after the basic nicotine molecule having improved insecticide activity and generally low toxicity. The insecticidal activities of neonicotinoids were previous studied using 3D and standard partial least squares regression models. The paper describes the ability of the MDF SAR methodology in prediction of insecticidal activities of neonicotinoid compounds. The best MDF SAR bi-varied model was validated on training and test sets and its ability on prediction of insecticidal activity was compared with previous reported models. Even if the MDF SAR methodology is complex and time consuming the results worth the effort because they are statistical significant better then previous reported results.

  6. Testing the quality of molecular structure descriptors. Vertex-degree-based topological indices

    Directory of Open Access Journals (Sweden)

    Gutman Ivan

    2013-01-01

    Full Text Available The correlation ability of 20 vertex-degree-based topological indices, occurring in the chemical literature, is tested for the case of standard heats of formation and normal boiling points of octane isomers. It is found that the correlation ability of many of these indices is either rather weak or nil. The augmented Zagreb index and the atom-bond connectivity index yield the best results. [Projekat Ministarstva nauke Republike Srbije, br. 174033

  7. Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review

    Science.gov (United States)

    Mamy, Laure; Patureau, Dominique; Barriuso, Enrique; Bedos, Carole; Bessac, Fabienne; Louchart, Xavier; Martin-laurent, Fabrice; Miege, Cecile; Benoit, Pierre

    2015-01-01

    A comprehensive review of quantitative structure-activity relationships (QSAR) allowing the prediction of the fate of organic compounds in the environment from their molecular properties was done. The considered processes were water dissolution, dissociation, volatilization, retention on soils and sediments (mainly adsorption and desorption), degradation (biotic and abiotic), and absorption by plants. A total of 790 equations involving 686 structural molecular descriptors are reported to estimate 90 environmental parameters related to these processes. A significant number of equations was found for dissociation process (pKa), water dissolution or hydrophobic behavior (especially through the KOW parameter), adsorption to soils and biodegradation. A lack of QSAR was observed to estimate desorption or potential of transfer to water. Among the 686 molecular descriptors, five were found to be dominant in the 790 collected equations and the most generic ones: four quantum-chemical descriptors, the energy of the highest occupied molecular orbital (EHOMO) and the energy of the lowest unoccupied molecular orbital (ELUMO), polarizability (α) and dipole moment (μ), and one constitutional descriptor, the molecular weight. Keeping in mind that the combination of descriptors belonging to different categories (constitutional, topological, quantum-chemical) led to improve QSAR performances, these descriptors should be considered for the development of new QSAR, for further predictions of environmental parameters. This review also allows finding of the relevant QSAR equations to predict the fate of a wide diversity of compounds in the environment. PMID:25866458

  8. Descriptor Selection via Log-Sum Regularization for the Biological Activities of Chemical Structure.

    Science.gov (United States)

    Xia, Liang-Yong; Wang, Yu-Wei; Meng, De-Yu; Yao, Xiao-Jun; Chai, Hua; Liang, Yong

    2017-12-22

    The quantitative structure-activity relationship (QSAR) model searches for a reliable relationship between the chemical structure and biological activities in the field of drug design and discovery. (1) Background: In the study of QSAR, the chemical structures of compounds are encoded by a substantial number of descriptors. Some redundant, noisy and irrelevant descriptors result in a side-effect for the QSAR model. Meanwhile, too many descriptors can result in overfitting or low correlation between chemical structure and biological bioactivity. (2) Methods: We use novel log-sum regularization to select quite a few descriptors that are relevant to biological activities. In addition, a coordinate descent algorithm, which uses novel univariate log-sum thresholding for updating the estimated coefficients, has been developed for the QSAR model. (3) Results: Experimental results on artificial and four QSAR datasets demonstrate that our proposed log-sum method has good performance among state-of-the-art methods. (4) Conclusions: Our proposed multiple linear regression with log-sum penalty is an effective technique for both descriptor selection and prediction of biological activity.

  9. Shape Signatures: New Descriptors for Predicting Cardiotoxicity In Silico

    OpenAIRE

    Chekmarev, Dmitriy S.; Kholodovych, Vladyslav; Balakin, Konstantin V.; Ivanenkov, Yan; Ekins, Sean; Welsh, William J.

    2008-01-01

    Shape Signatures is a new computational tool that is being evaluated for applications in computational toxicology and drug discovery. The method employs a customized ray-tracing algorithm to explore the volume enclosed by the surface of a molecule and then uses the output to construct compact histograms (i.e., signatures) that encode for molecular shape and polarity. In the present study, we extend the application of the Shape Signatures methodology to the domain of computational models for c...

  10. 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.

  11. 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

  12. 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...... on clinically relevant descriptors. RESULTS: It is proposed that identification of a dominance of central sensitization pain is based on descriptors derived from the subjective assessment and the physical examination. In the former, clinicians are recommended to inquire about intensity and duration of pain...

  13. 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.

  14. Texture analysis by fractal descriptors over the wavelet domain using a best basis decomposition

    Science.gov (United States)

    Florindo, J. B.; Bruno, O. M.

    2016-02-01

    This work proposes the development and study of a novel set of fractal descriptors for texture analysis. These descriptors are obtained by exploring the fractal-like relation among the coefficients and magnitudes of a particular type of wavelet decomposition, to know, the best basis selection. The proposed method is tested in the classification of three sets of textures from the literature: Brodatz, Vistex and USPTex. The method is also applied to a challenging real-world problem, which is the identification of species of plants from the Brazilian flora. The results are compared with other classical and state-of-the-art texture descriptors and demonstrate the efficiency of the proposed technique in this task.

  15. 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...

  16. 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.

  17. 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.

  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. Topological Model on the Inductive Effect in Alkyl Halides Using Local Quantum Similarity and Reactivity Descriptors in the Density Functional Theory

    Directory of Open Access Journals (Sweden)

    Alejandro Morales-Bayuelo

    2014-01-01

    Full Text Available We present a topological analysis to the inductive effect through steric and electrostatic scales of quantitative convergence. Using the molecular similarity field based in the local guantum similarity (LQS with the Topo-Geometrical Superposition Algorithm (TGSA alignment method and the chemical reactivity in the density function theory (DFT context, all calculations were carried out with Amsterdam Density Functional (ADF code, using the gradient generalized approximation (GGA and local exchange correlations PW91, in order to characterize the electronic effect by atomic size in the halogens group using a standard Slater-type-orbital basis set. In addition, in this study we introduced news molecular bonding relationships in the inductive effect and the nature of the polar character in the C–H bond taking into account the global and local reactivity descriptors such as chemical potential, hardness, electrophilicity, and Fukui functions, respectively. These descriptors are used to find new alternative considerations on the inductive effect, unlike to the binding energy and dipole moment performed in the traditional organic chemical.

  20. 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.

  1. Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

    Science.gov (United States)

    Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

    2012-01-01

    Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

  2. 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

  3. Does true Gleason pattern 3 merit its cancer descriptor?

    Science.gov (United States)

    Miah, Saiful; Ahmed, Hashim U; Freeman, Alex; Emberton, Mark

    2016-09-01

    Nearly five decades following its conception, the Gleason grading system remains a cornerstone in the prognostication and management of patients with prostate cancer. In the past few years, a debate has been growing whether Gleason score 3 + 3 = 6 prostate cancer is a clinically significant disease. Clinical, molecular and genetic research is addressing the question whether well characterized Gleason score 3 + 3 = 6 disease has the ability to affect the morbidity and quality of life of an individual in whom it is diagnosed. The consequences of treatment of Gleason score 3 + 3 = 6 disease are considerable; few men get through their treatments without sustaining some harm. Further modification of the classification of prostate cancer and dropping the label cancer for Gleason score 3 + 3 = 6 disease might be warranted.

  4. Describing Performance Standards: Validity of the 1992 National Assessment of Educational Progress Achievement Level Descriptors as Characterizations of Mathematics Performance.

    Science.gov (United States)

    Burstein, Leigh; Koretz, Daniel; Linn, Robert; Sugrue, Brenda; Novak, John; Baker, Eva L.; Harris, Elizabeth Lewis

    1996-01-01

    Three studies evaluating the validity of the descriptors and exemplars of the National Assessment of Educational Progress (NAEP) as characterizations of the actual mathematics performance of students at achievement levels are reported. Serious inconsistencies were found between actual performance and descriptors and exemplars. Recommendations for…

  5. 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…

  6. 75 FR 2879 - Use of Tobacco Marketing Descriptors to Convey Modified Risk; Request for Comments

    Science.gov (United States)

    2010-01-19

    ... the agency's development of guidance on the meaning of the term ``similar descriptors.'' A copy of the... Product packaging plays a critical role in fostering brand loyalty and communicating messages to consumers... imply purification or healthfulness; Words used in brand names that have associations with potency, risk...

  7. 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.

  8. 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…

  9. 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.

  10. 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.

  11. 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...

  12. Human pol II promoter prediction: time series descriptors and machine learning.

    Science.gov (United States)

    Gangal, Rajeev; Sharma, Pankaj

    2005-01-01

    Although several in silico promoter prediction methods have been developed to date, they are still limited in predictive performance. The limitations are due to the challenge of selecting appropriate features of promoters that distinguish them from non-promoters and the generalization or predictive ability of the machine-learning algorithms. In this paper we attempt to define a novel approach by using unique descriptors and machine-learning methods for the recognition of eukaryotic polymerase II promoters. In this study, non-linear time series descriptors along with non-linear machine-learning algorithms, such as support vector machine (SVM), are used to discriminate between promoter and non-promoter regions. The basic idea here is to use descriptors that do not depend on the primary DNA sequence and provide a clear distinction between promoter and non-promoter regions. The classification model built on a set of 1000 promoter and 1500 non-promoter sequences, showed a 10-fold cross-validation accuracy of 87% and an independent test set had an accuracy >85% in both promoter and non-promoter identification. This approach correctly identified all 20 experimentally verified promoters of human chromosome 22. The high sensitivity and selectivity indicates that n-mer frequencies along with non-linear time series descriptors, such as Lyapunov component stability and Tsallis entropy, and supervised machine-learning methods, such as SVMs, can be useful in the identification of pol II promoters.

  13. High-order statistics of weber local descriptors for image representation.

    Science.gov (United States)

    Han, Xian-Hua; Chen, Yen-Wei; Xu, Gang

    2015-06-01

    Highly discriminant visual features play a key role in different image classification applications. This study aims to realize a method for extracting highly-discriminant features from images by exploring a robust local descriptor inspired by Weber's law. The investigated local descriptor is based on the fact that human perception for distinguishing a pattern depends not only on the absolute intensity of the stimulus but also on the relative variance of the stimulus. Therefore, we firstly transform the original stimulus (the images in our study) into a differential excitation-domain according to Weber's law, and then explore a local patch, called micro-Texton, in the transformed domain as Weber local descriptor (WLD). Furthermore, we propose to employ a parametric probability process to model the Weber local descriptors, and extract the higher-order statistics to the model parameters for image representation. The proposed strategy can adaptively characterize the WLD space using generative probability model, and then learn the parameters for better fitting the training space, which would lead to more discriminant representation for images. In order to validate the efficiency of the proposed strategy, we apply three different image classification applications including texture, food images and HEp-2 cell pattern recognition, which validates that our proposed strategy has advantages over the state-of-the-art approaches.

  14. 3D face recognition based on multiple keypoint descriptors and sparse representation.

    Directory of Open Access Journals (Sweden)

    Lin Zhang

    Full Text Available Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD and the sparse representation-based classification (SRC. We call the proposed method 3DMKDSRC for short. Specifically, with 3DMKDSRC, each 3D face scan is represented as a set of descriptor vectors extracted from keypoints by meshSIFT. Descriptor vectors of gallery samples form the gallery dictionary. Given a probe 3D face scan, its descriptors are extracted at first and then its identity can be determined by using a multitask SRC. The proposed 3DMKDSRC approach does not require the pre-alignment between two face scans and is quite robust to the problems of missing data, occlusions and expressions. Its superiority over the other leading 3D face recognition schemes has been corroborated by extensive experiments conducted on three benchmark databases, Bosphorus, GavabDB, and FRGC2.0. The Matlab source code for 3DMKDSRC and the related evaluation results are publicly available at http://sse.tongji.edu.cn/linzhang/3dmkdsrcface/3dmkdsrc.htm.

  15. 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

  16. Descriptors for unprofessional behaviours of medical students: a systematic review and categorisation.

    Science.gov (United States)

    Mak-van der Vossen, Marianne; van Mook, Walther; van der Burgt, Stéphanie; Kors, Joyce; Ket, Johannes C F; Croiset, Gerda; Kusurkar, Rashmi

    2017-09-15

    Developing professionalism is a core task in medical education. Unfortunately, it has remained difficult for educators to identify medical students' unprofessionalism, because, among other reasons, there are no commonly adopted descriptors that can be used to document students' unprofessional behaviour. This study aimed to generate an overview of descriptors for unprofessional behaviour based on research evidence of real-life unprofessional behaviours of medical students. A systematic review was conducted searching PubMed, Ebsco/ERIC, Ebsco/PsycINFO and Embase.com from inception to 2016. Articles were reviewed for admitted or witnessed unprofessional behaviours of undergraduate medical students. The search yielded 11,963 different studies, 46 met all inclusion criteria. We found 205 different descriptions of unprofessional behaviours, which were coded into 30 different descriptors, and subsequently classified in four behavioural themes: failure to engage, dishonest behaviour, disrespectful behaviour, and poor self-awareness. This overview provides a common language to describe medical students' unprofessional behaviour. The framework of descriptors is proposed as a tool for educators to denominate students' unprofessional behaviours. The found behaviours can have various causes, which should be explored in a discussion with the student about personal, interpersonal and/or institutional circumstances in which the behaviour occurred. Explicitly denominating unprofessional behaviour serves two goals: [i] creating a culture in which unprofessional behaviour is acknowledged, [ii] targeting students who need extra guidance. Both are important to avoid unprofessional behaviour among future doctors.

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

    Science.gov (United States)

    Falomir, Zoe; Kluth, Thomas

    2017-06-24

    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%.

  18. Developing and Validating Band Levels and Descriptors for Reporting Overall Examinee Performance

    Science.gov (United States)

    Papageorgiou, Spiros; Xi, Xiaoming; Morgan, Rick; So, Youngsoon

    2015-01-01

    This study presents the development and empirical validation of score levels and descriptors specifically designed for reporting purposes to provide test takers with more than just a number on a score scale. In the context of a test primarily intended for 11- to 15-year-old students learning English as a second/foreign language, the study examined…

  19. 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

  20. 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.

  1. Reactivity descriptor in solid acid catalysis : Predicting turnover frequencies for propene methylation in zeotypes

    NARCIS (Netherlands)

    Wang, Chuan Ming; Brogaard, Rasmus Y.; Weckhuysen, Bert M.|info:eu-repo/dai/nl/285484397; Nørskov, Jens K.; Studt, Felix

    2014-01-01

    Recent work has reported the discovery of metal surface catalysts by employing a descriptor-based approach, establishing a correlation between a few well-defined properties of a material and its catalytic activity. This theoretical work aims for a similar approach in solid acid catalysis, focusing

  2. 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

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

    Directory of Open Access Journals (Sweden)

    Seyyed Mohammad Ali Sajadi

    2017-03-01

    Full Text Available Introduction: 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. Method: 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. Results: 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. Conclusion: 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.  

  4. Has the tobacco industry evaded the FDA's ban on 'Light' cigarette descriptors?

    Science.gov (United States)

    Connolly, Gregory N; Alpert, Hillel R

    2014-03-01

    Under the Family Smoking Prevention and Tobacco Control Act (FSPTCA), the Food and Drug Administration (FDA) banned the use of "Lights" descriptors or similar terms on tobacco products that convey messages of reduced risk. Manufacturers eliminated terms explicitly stated and substituted colour name descriptors corresponding to the banned terms. This paper examines whether the tobacco industry complied with or circumvented the law and potential FDA regulatory actions. Philip Morris retailer manuals, manufacturers' annual reports filed with the Massachusetts Department of Public Health, a national public opinion survey, and market-wide cigarette sales data were examined. Manufacturers substituted "Gold" for "Light" and "Silver" for "Ultra-light" in the names of Marlboro sub-brands, and "Blue", "Gold", and "Silver" for banned descriptors in sub-brand names. Percent filter ventilation levels, used to generate the smoke yield ranges associated with "Lights" categories, appear to have been reassigned to the new colour brand name descriptors. Following the ban, 92% of smokers reported they could easily identify their usual brands, and 68% correctly named the package colour associated with their usual brand, while sales for "Lights" cigarettes remained unchanged. Tobacco manufacturers appear to have evaded a critical element of the FSPTCA, the ban on misleading descriptors that convey reduced health risk messages. The FPSTCA provides regulatory mechanisms, including banning these products as adulterated (Section 902). Manufacturers could then apply for pre-market approval as new products and produce evidence for FDA evaluation and determination whether or not sales of these products are in the public health interest.

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

    Science.gov (United States)

    Lluch, Enrique; Nijs, Jo; Courtney, Carol A; Rebbeck, Trudy; Wylde, Vikki; Baert, Isabel; Wideman, Timothy H; Howells, Nick; Skou, Søren T

    2017-08-02

    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. 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. A narrative review of original research papers was conducted by nine clinicians and researchers from seven different countries to reach agreement on clinically relevant descriptors. It is proposed that identification of a dominance of central sensitization pain is based on descriptors derived from the subjective assessment and the physical examination. In the former, clinicians are recommended to inquire about intensity and duration of pain and its association with structural joint changes, pain distribution, behavior of knee pain, presence of neuropathic-like or centrally mediated symptoms and responsiveness to previous treatment. The latter includes assessment of response to clinical test, mechanical hyperalgesia and allodynia, thermal hyperalgesia, hypoesthesia and reduced vibration sense. 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 in this review require experimental testing in future studies. Implications for Rehabilitation Laboratory evaluation of central sensitization for people with knee osteoarthritis is yet to be incorporated into clinical practice. A set of clinical indicators for the recognition of central sensitization in patients with knee osteoarthritis is proposed. Although based on research data, the clinical indicators proposed require further experimental testing of psychometric properties.

  6. 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

  7. 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

  8. 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.

  9. 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%).

  10. Comparing axial CT slices in quantized N-dimensional SURF descriptor space to estimate the visible body region.

    Science.gov (United States)

    Feulner, Johannes; Zhou, S Kevin; Angelopoulou, Elli; Seifert, Sascha; Cavallaro, Alexander; Hornegger, Joachim; Comaniciu, Dorin

    2011-04-01

    In this paper, a method is described to automatically estimate the visible body region of a computed tomography (CT) volume image. In order to quantify the body region, a body coordinate (BC) axis is used that runs in longitudinal direction. Its origin and unit length are patient-specific and depend on anatomical landmarks. The body region of a test volume is estimated by registering it only along the longitudinal axis to a set of reference CT volume images with known body coordinates. During these 1D registrations, an axial image slice of the test volume is compared to an axial slice of a reference volume by extracting a descriptor from both slices and measuring the similarity of the descriptors. A slice descriptor consists of histograms of visual words. Visual words are code words of a quantized feature space and can be thought of as classes of image patches with similar appearance. A slice descriptor is formed by sampling a slice on a regular 2D grid and extracting a Speeded Up Robust Features (SURF) descriptor at each sample point. The codebook, or visual vocabulary, is generated in a training step by clustering SURF descriptors. Each SURF descriptor extracted from a slice is classified into the closest visual word (or cluster center) and counted in a histogram. A slice is finally described by a spatial pyramid of such histograms. We introduce an extension of the SURF descriptors to an arbitrary number of dimensions (N-SURF). Here, we make use of 2-SURF and 3-SURF descriptors. Cross-validation on 84 datasets shows the robustness of the results. The body portion can be estimated with an average error of 15.5mm within 9s. Possible applications of this method are automatic labeling of medical image databases and initialization of subsequent image analysis algorithms. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. 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.

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

    Science.gov (United States)

    Malmendal, Anders; Amoresano, Claudia; Trotta, Roberta; Lauri, Ilaria; De Tito, Stefano; Novellino, Ettore; Randazzo, Antonio

    2011-10-26

    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 tool for the characterization of sensory features of tomatoes.

  13. 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.

  14. A comparative study of local descriptors for Arabic character recognition on mobile devices

    Science.gov (United States)

    Tounsi, Maroua; Moalla, Ikram; Alimi, Adel M.; Lebourgeois, Franck

    2015-02-01

    Nowadays, the number of mobile applications based on image registration and recognition is increasing. Most interesting applications include mobile translator which can read text characters in the real world and translates it into the native language instantaneously. In this context, we aim to recognize characters in natural scenes by computing significant points so called key points or features/interest points in the image. So, it will be important to compare and evaluate features descriptors in terms of matching accuracy and processing time in a particular context of natural scene images. In this paper, we were interested on comparing the efficiency of the binary features as alternatives to the traditional SIFT and SURF in matching Arabic characters descended from natural scenes. We demonstrate that the binary descriptor ORB yields not only to similar results in terms of matching characters performance that the famous SIFT but also to faster computation suitable for mobile applications.

  15. 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.

  16. A high capacity multiple watermarking scheme based on Fourier descriptor and Sudoku

    Science.gov (United States)

    Zhang, Li; Zheng, Huimin

    2015-12-01

    Digital watermark is a type of technology to hide some significant information which is mainly used to protect digital data. A high capacity multiple watermarking method is proposed, which adapts the Fourier descriptor to pre-process the watermarks, while a Sudoku puzzle is used as a reference matrix in embedding process and a key in extraction process. It can dramatically reduce the required capacity by applying Fourier descriptor. Meanwhile, the security of watermarks can be guaranteed due to the Sudoku puzzle. Unlike previous algorithms applying Sudoku puzzle in spatial domain, the proposed algorithm works in transformed domain by applying LWT2.In addition, the proposed algorithm can detect the temper location accurately. The experimental results demonstrated that the goals mentioned above have been achieved.

  17. GENOTYPIC VARIABILITY OF PEANUT LINES IN RESPONSE TO WATER STRESS, BASED ON BIOCHEMICAL DESCRIPTORS

    Directory of Open Access Journals (Sweden)

    GERCKSON MACIEL RODRIGUES ALVES

    2016-01-01

    Full Text Available Seven biochemical descriptors were used to estimate the genotypic variability of peanut in response to moderate water stress. Six genotypes, constituted by four lines and two cultivars, were grown in pots, each containing two plants. At 15 days after emergence (DAE, the treatment differentiation was carried out: Control-plants maintained with daily watering, and Stress-plants submitted to water stress by complete suspension of watering for 15 days. The experimental design was completely randomized with factorial scheme 6 x 2 (genotype x water treatments, with five replications. The biochemical variables evaluated were: catalase (CAT, ascorbate peroxidase (APX, guaiacol peroxidase (GPX, free proline, total carbohydrates, soluble proteins, and amino acids. Results obtained by biochemical analysis and estimation of genotypic variability indicated that proline is the most appropriate descriptor for selecting genotypes tolerant to water stress, which led to identification of L81V and L108V as promising lines for drought tolerance breeding program.

  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. Chemical structure of descriptors with an active hydrogen atom in certain bioregulators.

    Science.gov (United States)

    Kurchii, B A

    1996-01-01

    The chemical structure of descriptors (D) for some plant growth regulators (PGR), herbicides, pesticides and drugs is described. The presence of an active hydrogen atom in molecules is an essential factor determining biological activity of chemicals. The results obtained from the study of dependence existing between the structure of a certain substance and its biological activity may be used in designing of novel compounds which possess in biological activity.

  20. 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.

  1. 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.

  2. 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)

  3. 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 ...

  4. Joint efforts to harmonize sound insulation descriptors and classification schemes in Europe (COST TU0901)

    OpenAIRE

    Rasmussen, Birgit

    2010-01-01

    Sound insulation descriptors, regulatory requirements and classification schemes in Europe represent a high degree of diversity. One implication is very little exchange of experience of housing design and construction details for different levels of sound insulation; another is trade barriers for building systems and products. Unfortunately, there is evidence for a development in the "wrong" direction. For example, sound classification schemes for dwellings exist in nine countries. There is n...

  5. Localized heuristic inverse quantitative structure activity relationship with bulk descriptors using numerical gradients.

    Science.gov (United States)

    Stålring, Jonna; Almeida, Pedro R; Carlsson, Lars; Helgee Ahlberg, Ernst; Hasselgren, Catrin; Boyer, Scott

    2013-08-26

    State-of-the-art quantitative structure-activity relationship (QSAR) models are often based on nonlinear machine learning algorithms, which are difficult to interpret. From a pharmaceutical perspective, QSARs are used to enhance the chemical design process. Ultimately, they should not only provide a prediction but also contribute to a mechanistic understanding and guide modifications to the chemical structure, promoting compounds with desirable biological activity profiles. Global ranking of descriptor importance and inverse QSAR have been used for these purposes. This paper introduces localized heuristic inverse QSAR, which provides an assessment of the relative ability of the descriptors to influence the biological response in an area localized around the predicted compound. The method is based on numerical gradients with parameters optimized using data sets sampled from analytical functions. The heuristic character of the method reduces the computational requirements and makes it applicable not only to fragment based methods but also to QSARs based on bulk descriptors. The application of the method is illustrated on congeneric QSAR data sets, and it is shown that the predicted influential descriptors can be used to guide structural modifications that affect the biological response in the desired direction. The method is implemented into the AZOrange Open Source QSAR package. The current implementation of localized heuristic inverse QSAR is a step toward a generally applicable method for elucidating the structure activity relationship specifically for a congeneric region of chemical space when using QSARs based on bulk properties. Consequently, this method could contribute to accelerating the chemical design process in pharmaceutical projects, as well as provide information that could enhance the mechanistic understanding for individual scaffolds.

  6. 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.

  7. Descriptor-Based Analysis Applied to HCN Synthesis from NH3 and CH4

    Energy Technology Data Exchange (ETDEWEB)

    Grabow, L

    2011-08-18

    The design of solid metal catalysts using theoretical methods has been a long-standing goal in heterogeneous catalysis. Recent developments in methodology and computer technology as well as the establishment of a descriptor-based approach for the analysis of reaction mechanisms and trends across the periodic table allow for the fast screening for new catalytic materials and have lead to first examples of computational discoveries of new materials. The underlying principles of the descriptor-based approach are the existence of relations between the surface electronic structure, adsorption energies and activation barriers that result in volcano-shaped activity plots as function of simple descriptors, such as atomic binding energies or the d-band center. Linear scaling relations have been established between the adsorption energies of hydrogen-containing molecules such as CH{sub x}, NH{sub x}, OH{sub x} and SH{sub x} and the C, N O and S adsorption energies on transition-metal surfaces. Transition-state energies have also been shown to scale linearly with adsorption energies in a similar fashion. Recently, a single transition state scaling relation has been identified for a large number of C-C, C-O, C-N, N-O, N-N, and O-O coupling reactions. The scaling relations provide a powerful tool for the investigation of reaction mechanisms and the prediction of potential energy surfaces. They limit the number of independent variables to a few, typically adsorption energies of key atoms. Using this information as input to a microkinetic model provides an understanding of trends in catalytic activity across the transition metals. In most cases a volcano-shaped relation between activity and the key variables, the descriptors, is observed. In the present paper we will provide an example of the approach outlined above and show how one can obtain an understanding of activity/selectivity trends of a reaction with just a few new calculations.

  8. 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.

  9. 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

  10. 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.

  11. Morphological classification of odontogenic keratocysts using Bouligand-Minkowski fractal descriptors.

    Science.gov (United States)

    Florindo, Joao B; Bruno, Odemir M; Landini, Gabriel

    2017-02-01

    The Odontogenic keratocyst (OKC) is a cystic lesion of the jaws, which has high growth and recurrence rates compared to other cysts of the jaws (for instance, radicular cyst, which is the most common jaw cyst type). For this reason OKCs are considered by some to be benign neoplasms. There exist two sub-types of OKCs (sporadic and syndromic) and the ability to discriminate between these sub-types, as well as other jaw cysts, is an important task in terms of disease diagnosis and prognosis. With the development of digital pathology, computational algorithms have become central to addressing this type of problem. Considering that only basic feature-based methods have been investigated in this problem before, we propose to use a different approach (the Bouligand-Minkowski descriptors) to assess the success rates achieved on the classification of a database of histological images of the epithelial lining of these cysts. This does not require the level of abstraction necessary to extract histologically-relevant features and therefore has the potential of being more robust than previous approaches. The descriptors were obtained by mapping pixel intensities into a three dimensional cloud of points in discrete space and applying morphological dilations with spheres of increasing radii. The descriptors were computed from the volume of the dilated set and submitted to a machine learning algorithm to classify the samples into diagnostic groups. This approach was capable of discriminating between OKCs and radicular cysts in 98% of images (100% of cases) and between the two sub-types of OKCs in 68% of images (71% of cases). These results improve over previously reported classification rates reported elsewhere and suggest that Bouligand-Minkowski descriptors are useful features to be used in histopathological images of these cysts. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  12. Measuring the Conformational Distance of GPCR-related Proteins Using a Joint-based Descriptor.

    Science.gov (United States)

    Thangappan, Jayaraman; Madan, Bharat; Wu, Sangwook; Lee, Sun-Gu

    2017-11-09

    Joint-based descriptor is a new level of macroscopic descriptor for protein structure using joints of secondary structures as a basic element. Here, we propose how the joint-based descriptor can be applied to examine the conformational distances or differences of transmembrane (TM) proteins. Specifically, we performed three independent studies that measured the global and conformational distances between GPCR A family and its related structures. First, the conformational distances of GPCR A family and other 7TM proteins were evaluated. This provided the information on the distant and close families or superfamilies to GPCR A family and permitted the identification of conserved local conformations. Second, computational models of GPCR A family proteins were validated, which enabled us to estimate how much they reproduce the native conformation of GPCR A proteins at global and local conformational level. Finally, the conformational distances between active and inactive states of GPCR proteins were estimated, which identified the difference of local conformation. The proposed macroscopic joint-based approach is expected to allow us to investigate structural features, evolutionary relationships, computational models and conformational changes of TM proteins in a more simplistic manner.

  13. 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.

  14. 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.

  15. 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.

  16. Algorithm of sub-pixel image registration based on Harris corner and SIFT descriptor

    Science.gov (United States)

    Zhu, Jianguo; Fan, Guihua

    2014-09-01

    Since multi-cameras images involve much differences in spatial characteristics and spectral characteristics, so it is full of difficulties in the image registration. According to the different characteristics of the multi-cameras images, this paper proposed a new algorithm of sub-pixel image registration based on Harris corner and Scale Invariant Features Transform (SIFT) descriptor. The algorithm consists of three procedures: feature detection, pixel-level registration and sub-pixel-level registration. Firstly, the Harris algorithm was selected to extract the feature corners and determine the main direction of the Harris corners. Secondly, the SIFT descriptor was chose to describe the key points. Then, feature points acquired on matching by the two-way nearest neighbor algorithm. Finally, in the sub-pixel-level registration process, we carry out interpolation in the neighborhood of the pixel-level matching points. Then the pixel-level registration is taken once again. The experimental results show that, the proposed algorithm is accurate, efficient, and retains the rotational invariance of the SIFT descriptor. What's more, processing speed is significantly increased.

  17. 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.

  18. Linear dimensionality reduction applied to scale invariant feature transformation and speeded up robust feature descriptors

    Science.gov (United States)

    Valenzuela, Ricardo Eugenio González; Schwartz, William Robson; Pedrini, Helio

    2014-05-01

    Robust local descriptors usually consist of high-dimensional feature vectors to describe distinctive characteristics of images. The high dimensionality of a feature vector incurs considerable costs in terms of computational time and storage. It also results in the curse of dimensionality that affects the performance of several tasks that use feature vectors, such as matching, retrieval, and classification of images. To address these problems, it is possible to employ some dimensionality reduction techniques, leading frequently to information lost and, consequently, accuracy reduction. This work aims at applying linear dimensionality reduction to the scale invariant feature transformation and speeded up robust feature descriptors. The objective is to demonstrate that even risking the decrease of the accuracy of the feature vectors, it results in a satisfactory trade-off between computational time and storage requirements. We perform linear dimensionality reduction through random projections, principal component analysis, linear discriminant analysis, and partial least squares in order to create lower dimensional feature vectors. These new reduced descriptors lead us to less computational time and memory storage requirements, even improving accuracy in some cases. We evaluate reduced feature vectors in a matching application, as well as their distinctiveness in image retrieval. Finally, we assess the computational time and storage requirements by comparing the original and the reduced feature vectors.

  19. Perspective: Essential Study Quality Descriptors for Data from Nutritional Epidemiologic Research.

    Science.gov (United States)

    Yang, Chen; Pinart, Mariona; Kolsteren, Patrick; Van Camp, John; De Cock, Nathalie; Nimptsch, Katharina; Pischon, Tobias; Laird, Eamon; Perozzi, Giuditta; Canali, Raffaella; Hoge, Axelle; Stelmach-Mardas, Marta; Dragsted, Lars Ove; Palombi, Stéphanie Maria; Dobre, Irina; Bouwman, Jildau; Clarys, Peter; Minervini, Fabio; De Angelis, Maria; Gobbetti, Marco; Tafforeau, Jean; Coltell, Oscar; Corella, Dolores; De Ruyck, Hendrik; Walton, Janette; Kehoe, Laura; Matthys, Christophe; De Baets, Bernard; De Tré, Guy; Bronselaer, Antoon; Rivellese, Angela; Giacco, Rosalba; Lombardo, Rosario; De Clercq, Sofian; Hulstaert, Niels; Lachat, Carl

    2017-09-01

    Pooled analysis of secondary data increases the power of research and enables scientific discovery in nutritional epidemiology. Information on study characteristics that determine data quality is needed to enable correct reuse and interpretation of data. This study aims to define essential quality characteristics for data from observational studies in nutrition. First, a literature review was performed to get an insight on existing instruments that assess the quality of cohort, case-control, and cross-sectional studies and dietary measurement. Second, 2 face-to-face workshops were organized to determine the study characteristics that affect data quality. Third, consensus on the data descriptors and controlled vocabulary was obtained. From 4884 papers retrieved, 26 relevant instruments, containing 164 characteristics for study design and 93 characteristics for measurements, were selected. The workshop and consensus process resulted in 10 descriptors allocated to "study design" and 22 to "measurement" domains. Data descriptors were organized as an ordinal scale of items to facilitate the identification, storage, and querying of nutrition data. Further integration of an Ontology for Nutrition Studies will facilitate interoperability of data repositories. © 2017 American Society for Nutrition.

  20. Filtered local pattern descriptor for face recognition and infrared pedestrian detection

    Directory of Open Access Journals (Sweden)

    Ning Sun

    2017-03-01

    Full Text Available In recent decades, the local pattern descriptor has achieved tremendous success in the field of face recognition, pedestrian detection, and image texture analysis. This study presents a generic approach, called the filtered local pattern descriptor (FLPD, which expands the traditional local pattern descriptor (TLPD by using multi-scale and multi-type filter banks. The FLPD encodes the local information of an image based on the convolutional sum of the sub-image blocks and the filter banks, instead of the original pixel values in the TLPD. This design can effectively increase the diversity of the TLPD feature extraction, thereby enhancing the ability of feature representation and its reliability. Two FLPD-based feature representation methods are proposed for the face image and the pedestrian image. To evaluate the performance of the proposed FLPD, extensive experiments on face recognition and infrared pedestrian detection are conducted using several benchmark image datasets. The experimental results illustrate that the FLPD has a significant advantage in the discrimination and stability of feature extraction, and is able to achieve a satisfactory accuracy in comparison with state-of-the-art methods. It is demonstrated that the FLPD is a powerful and convenient extension of the TLPD by filter banks, and suitable to be implemented as feature extraction into approaches to solve the binary or multi-class image classification problems.

  1. 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.

  2. Leaf and fruit morphological descriptors for commercial nance selections (Byrsonima crassifolia (L. HBK in Nayarit, Mexico.

    Directory of Open Access Journals (Sweden)

    Medina-Torres, R.

    2016-01-01

    Full Text Available In order to identify the variability of quantitative and qualitative leaf and fruit descriptors, 41 commercial nance selections (Byrsonima crassifolia (L. HBK collected in six locations of the state of Nayarit were characterized. The main component analysis (MCA showed that 79.91 % of the total variance (TV was explained by seven main components (MC’s and from these three contributed 55.20 % to TV. MC1 explained 24.10 % of the variance, where the most relevant to the study of the nance genetic diversity were: fresh leaf weight, leaf area and the equatorial fruit diameter. MC2 contributed 19.18 % to TV, where the most important were fruit size and fresh weight, as well as leaf average length and width. MC3 contributed 11.92 % to TV, where fruit shape and fruit apex form were negatively correlated. Adaxial leaf pubescence correlated positively. The rest of the total variance had little importance to leaf and fruit phenotypic characterization. The three groupings obtained by principal components and hierarchical conglomerates had a high coincidence for discriminating selections based on leaf and fruit descriptors. However, the descriptors obtained showed no relationship with the geographical origin of the selections. This supposes an advanced degree of domestication and transit of plant material for commercial orchards.

  3. 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.

  4. 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

  5. Molecular Characterization of 36 Accessions of Two Genera of ...

    African Journals Online (AJOL)

    The present study aims to collect cocoyam germplasm from local agriculture systems in Edo state, Nigeria and characterize them using molecular marker techniques. Random stratified sampling method was used to collect the plant genetic resources based on IBPGR and IPGRI descriptors. Collecting cocoyam germplasm is ...

  6. 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.

  7. 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.

  8. 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: BI-RADS lexicon morphology descriptors can be applied in the characterization of enhancing lesions on CESM with a few exceptions. (2) Multiple bilateral intensely enhancing foci should not be included under the normal background parenchymal enhancement unless they are proved to be benign by biopsy. (3) Mass lesion features that indicated malignancy were irregular-shaped, spiculated and irregular margins and heterogeneous internal enhancement patterns. The rim enhancement pattern should not be considered as a descriptor of malignant lesions unless CESM is coupled with an ultrasound examination.

  9. FLORISTIC COMPARISON BETWEEN TWO TREE COMMUNITIES ASSOCIATED WITH HABITAT DESCRIPTOR VARIABLES

    Directory of Open Access Journals (Sweden)

    Jean Daniel Morel

    2015-12-01

    Full Text Available The knowledge about the influence of habitat variables is essential to understand the underlying ecological patterns in vegetation. This study compared the floristic composition of two forest communities located in different altitudes. Associated with this comparison, we used a methodology where habitat descriptor variables were scaled and interpreted by the biotic set sampled. We constructed one matrix with scores given to physical, biotic, vegetation, and anthropogenic variables in the field and one matrix with the species sampled and performed multivariate analyses. We found that the floristic communities differ between the different altitudes and that the methodology used showed significant variables for the ecological characterization of the sampled habitat.

  10. 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...

  11. Descriptors and Thermodynamic Limitations of Electrocatalytic Carbon Dioxide Reduction on Rutile Oxide Surfaces

    DEFF Research Database (Denmark)

    Bhowmik, Arghya; Vegge, Tejs; Hansen, Heine Anton

    2016-01-01

    A detailed understanding of the electrochemical reduction of CO2 into liquid fuels on rutile metal oxide surfaces is developed by using DFT calculations. We consider oxide overlayer structures on RuO2(1 1 0) surfaces as model catalysts to elucidate the trends and limitations in the CO2 reduction...... reaction (CO2RR) based on thermodynamic analysis. We aim to specify the requirements for CO2RR catalysts to establish adsorbate scaling relations and use these to derive activity volcanoes. Computational results show that the OH* binding free energy is a good descriptor of the thermodynamic limitations...

  12. 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.

  13. 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.

  14. Evaluating the Effectiveness of Various Blast Loading Descriptors as Occupant Injury Predictors for Underbody Blast Events

    Science.gov (United States)

    2014-01-09

    t:N , CFC # Pulse type Dec. g ion ms al ms m/s Sp. Pwr Eff. G G- ava @2ms @Oms @15ms 1000 @3ms @7ms @7ms @30ms @Oms 1 Triangular 44 40 2 8.6 376 27 22...Power, Blast, ROM, reduced order models, MADYMO, occupant, injury, pulse , loading, descriptor, calculator 16. SECURITY CLASSIFICATION OF: 17... pulse and occupant injury It has been shown before that there is no single input parameter which can be used to effectively assess occupant injury

  15. Computing distance-based topological descriptors of complex chemical networks: New theoretical techniques

    Science.gov (United States)

    Hayat, Sakander

    2017-11-01

    Structure-based topological descriptors/indices of complex chemical networks enable prediction of physico-chemical properties and the bioactivities of these compounds through QSAR/QSPR methods. In this paper, we have developed a rigorous computational and theoretical technique to compute various distance-based topological indices of complex chemical networks. A fullerene is called the IPR (Isolated-Pentagon-Rule) fullerene, if every pentagon in it is surrounded by hexagons only. To ensure the applicability of our technique, we compute certain distance-based indices of an infinite family of IPR fullerenes. Our results show that the proposed technique is more diverse and bears less algorithmic and combinatorial complexity.

  16. 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...... nature whereas the higher stages are implemented in a coarse parallel way on a multicore PC. A significant increase in processing speed could be achieved (factor 11.5) as well as in terms of latency (factor 3.3). These factors can be further increased by optimizing the processes implemented...... on the multicore PC....

  17. Improving predictions of protein-protein interfaces by combining amino acid-specific classifiers based on structural and physicochemical descriptors with their weighted neighbor averages.

    Science.gov (United States)

    de Moraes, Fábio R; Neshich, Izabella A P; Mazoni, Ivan; Yano, Inácio H; Pereira, José G C; Salim, José A; Jardine, José G; Neshich, Goran

    2014-01-01

    Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now

  18. Improving predictions of protein-protein interfaces by combining amino acid-specific classifiers based on structural and physicochemical descriptors with their weighted neighbor averages.

    Directory of Open Access Journals (Sweden)

    Fábio R de Moraes

    Full Text Available Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR from free surface residues (FSR. We formulated a linear discriminative analysis (LDA classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/ are suitable for such a task. Receiver operating characteristic (ROC analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study

  19. Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

    Science.gov (United States)

    de Moraes, Fábio R.; Neshich, Izabella A. P.; Mazoni, Ivan; Yano, Inácio H.; Pereira, José G. C.; Salim, José A.; Jardine, José G.; Neshich, Goran

    2014-01-01

    Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now

  20. 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

  1. 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.

  2. Evaluation of MPEG-7-Based Audio Descriptors for Animal Voice Recognition over Wireless Acoustic Sensor Networks

    Directory of Open Access Journals (Sweden)

    Joaquín Luque

    2016-05-01

    Full Text Available Environmental audio monitoring is a huge area of interest for biologists all over the world. This is why some audio monitoring system have been proposed in the literature, which can be classified into two different approaches: acquirement and compression of all audio patterns in order to send them as raw data to a main server; or specific recognition systems based on audio patterns. The first approach presents the drawback of a high amount of information to be stored in a main server. Moreover, this information requires a considerable amount of effort to be analyzed. The second approach has the drawback of its lack of scalability when new patterns need to be detected. To overcome these limitations, this paper proposes an environmental Wireless Acoustic Sensor Network architecture focused on use of generic descriptors based on an MPEG-7 standard. These descriptors demonstrate it to be suitable to be used in the recognition of different patterns, allowing a high scalability. The proposed parameters have been tested to recognize different behaviors of two anuran species that live in Spanish natural parks; the Epidalea calamita and the Alytes obstetricans toads, demonstrating to have a high classification performance.

  3. 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.

  4. A set of descriptors for identifying the protein-drug interaction in cellular networking.

    Science.gov (United States)

    Nanni, Loris; Lumini, Alessandra; Brahnam, Sheryl

    2014-10-21

    The study of protein-drug interactions is a significant issue for drug development. Unfortunately, it is both expensive and time-consuming to perform physical experiments to determine whether a drug and a protein are interacting with each other. Some previous attempts to design an automated system to perform this task were based on the knowledge of the 3D structure of a protein, which is not always available in practice. With the availability of protein sequences generated in the post-genomic age, however, a sequence-based solution to deal with this problem is necessary. Following other works in this area, we propose a new machine learning system based on several protein descriptors extracted from several protein representations, such as, variants of the position specific scoring matrix (PSSM) of proteins, the amino-acid sequence, and a matrix representation of a protein. The prediction engine is operated by an ensemble of support vector machines (SVMs), with each SVM trained on a specific descriptor and the results of each SVM combined by sum rule. The overall success rate achieved by our final ensemble is notably higher than previous results obtained on the same datasets using the same testing protocols reported in the literature. MATLAB code and the datasets used in our experiments are freely available for future comparison at http://www.dei.unipd.it/node/2357. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. 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.

  6. Cardiac Arrhythmias Classification Method Based on MUSIC, Morphological Descriptors, and Neural Network

    Science.gov (United States)

    Naghsh-Nilchi, Ahmad R.; Kadkhodamohammadi, A. Rahim

    2009-12-01

    An electrocardiogram (ECG) beat classification scheme based on multiple signal classification (MUSIC) algorithm, morphological descriptors, and neural networks is proposed for discriminating nine ECG beat types. These are normal, fusion of ventricular and normal, fusion of paced and normal, left bundle branch block, right bundle branch block, premature ventricular concentration, atrial premature contraction, paced beat, and ventricular flutter. ECG signal samples from MIT-BIH arrhythmia database are used to evaluate the scheme. MUSIC algorithm is used to calculate pseudospectrum of ECG signals. The low-frequency samples are picked to have the most valuable heartbeat information. These samples along with two morphological descriptors, which deliver the characteristics and features of all parts of the heart, form an input feature vector. This vector is used for the initial training of a classifier neural network. The neural network is designed to have nine sample outputs which constitute the nine beat types. Two neural network schemes, namely multilayered perceptron (MLP) neural network and a probabilistic neural network (PNN), are employed. The experimental results achieved a promising accuracy of 99.03% for classifying the beat types using MLP neural network. In addition, our scheme recognizes NORMAL class with 100% accuracy and never misclassifies any other classes as NORMAL.

  7. 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.

  8. Local Wavelet Pattern: A New Feature Descriptor for Image Retrieval in Medical CT Databases.

    Science.gov (United States)

    Dubey, Shiv Ram; Singh, Satish Kumar; Singh, Rajat Kumar

    2015-12-01

    A new image feature description based on the local wavelet pattern (LWP) is proposed in this paper to characterize the medical computer tomography (CT) images for content-based CT image retrieval. In the proposed work, the LWP is derived for each pixel of the CT image by utilizing the relationship of center pixel with the local neighboring information. In contrast to the local binary pattern that only considers the relationship between a center pixel and its neighboring pixels, the presented approach first utilizes the relationship among the neighboring pixels using local wavelet decomposition, and finally considers its relationship with the center pixel. A center pixel transformation scheme is introduced to match the range of center value with the range of local wavelet decomposed values. Moreover, the introduced local wavelet decomposition scheme is centrally symmetric and suitable for CT images. The novelty of this paper lies in the following two ways: 1) encoding local neighboring information with local wavelet decomposition and 2) computing LWP using local wavelet decomposed values and transformed center pixel values. We tested the performance of our method over three CT image databases in terms of the precision and recall. We also compared the proposed LWP descriptor with the other state-of-the-art local image descriptors, and the experimental results suggest that the proposed method outperforms other methods for CT image retrieval.

  9. 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.

  10. 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".

  11. The Impact of Urban Design Descriptors on Outdoor Thermal Environment: A Literature Review

    Directory of Open Access Journals (Sweden)

    Pingying Lin

    2017-12-01

    Full Text Available This paper presents a literature review on urban design indicators addressing the impact of urban geometry and vegetation on the outdoor thermal environment at the pedestrian level, as urban geometry and vegetation have been regarded as the most influential urban design factors that affect outdoor microclimate. The thermal balance concept is first introduced to elaborate how each component of energy fluxes is affected by the urban built environment, which helps to explore the underlying thermophysical mechanisms of how urban design modifies the outdoor thermal environment. The literature on numerous urban design descriptors addressing urban geometric characteristics is categorized into five groups in this paper according to the design features that the parameters entail, including land use intensity, building form, canyon geometry, space enclosure and descriptive characteristics. The literature on urban vegetation descriptors is reviewed together, followed by the combined effect of urban geometry and vegetation. This paper identifies a series of important urban design parameters and shows that the impact of design parameters on thermal environment varies with time, season, local climate and urban contexts. Contradictory impacts often occur between daytime and nighttime, or different seasons, which requests trade-offs to be achieved when proposing design strategies.

  12. Smart imaging for power-efficient extraction of Viola-Jones local descriptors

    Science.gov (United States)

    Fernández-Berni, J.; Carmona-Galán, R. A.; del Río, R.; Leñero-Bardallo, Juan A.; Suárez-Cambre, M.; Rodríguez-Vázquez, Á.

    2014-03-01

    In computer vision, local descriptors permit to summarize relevant visual cues through feature vectors. These vectors constitute inputs for trained classifiers which in turn enable different high-level vision tasks. While local descriptors certainly alleviate the computation load of subsequent processing stages by preventing them from handling raw images, they still have to deal with individual pixels. Feature vector extraction can thus become a major limitation for conventional embedded vision hardware. In this paper, we present a power-efficient sensing processing array conceived to provide the computation of integral images at different scales. These images are intermediate representations that speed up feature extraction. In particular, the mixed-signal array operation is tailored for extraction of Haar-like features. These features feed the cascade of classifiers at the core of the Viola-Jones framework. The processing lattice has been designed for the standard UMC 0.18μm 1P6M CMOS process. In addition to integral image computation, the array can be reprogrammed to deliver other early vision tasks: concurrent rectangular area sum, block-wise HDR imaging, Gaussian pyramids and image pre-warping for subsequent reduced kernel filtering.

  13. Cardiac Arrhythmias Classification Method Based on MUSIC, Morphological Descriptors, and Neural Network

    Directory of Open Access Journals (Sweden)

    2009-03-01

    Full Text Available An electrocardiogram (ECG beat classification scheme based on multiple signal classification (MUSIC algorithm, morphological descriptors, and neural networks is proposed for discriminating nine ECG beat types. These are normal, fusion of ventricular and normal, fusion of paced and normal, left bundle branch block, right bundle branch block, premature ventricular concentration, atrial premature contraction, paced beat, and ventricular flutter. ECG signal samples from MIT-BIH arrhythmia database are used to evaluate the scheme. MUSIC algorithm is used to calculate pseudospectrum of ECG signals. The low-frequency samples are picked to have the most valuable heartbeat information. These samples along with two morphological descriptors, which deliver the characteristics and features of all parts of the heart, form an input feature vector. This vector is used for the initial training of a classifier neural network. The neural network is designed to have nine sample outputs which constitute the nine beat types. Two neural network schemes, namely multilayered perceptron (MLP neural network and a probabilistic neural network (PNN, are employed. The experimental results achieved a promising accuracy of 99.03% for classifying the beat types using MLP neural network. In addition, our scheme recognizes NORMAL class with 100% accuracy and never misclassifies any other classes as NORMAL.

  14. 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.

  15. 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.

  16. Driving the getaway car? Ireland, taxation and development

    OpenAIRE

    Killian, Sheila

    2011-01-01

    non-peer-reviewed Taxation is about far more than revenue-raising: it concerns power and impacts taxpayer behaviour. It is pivotal in enhancing accountability and participation in young states through the bargaining process between a government and its citizens. Very significantly, it often has unexpected consequences, and the tax system of one country can easily have an impact on economic or social behaviour in another. Since business is now international, it is important that taxes are d...

  17. Computational Study of AumSin (m+n=2-6) Nanoalloy Clusters Invoking Density Functional Based Descriptors

    International Nuclear Information System (INIS)

    Ranjan, P.; Kumar, A.; Chakraborty, T.

    2016-01-01

    In this study, electronic and optical properties of Au m Si n (m+n=2-6) nanoalloy clusters are systematically investigated in terms of the Density Functional Theory (DFT) with the generalized gradient approximation (GGA). Conceptual DFT based global theoretical descriptors have been used to reveal experimental properties qualitatively. In this venture, experimental properties of Au m Si n (m+n=2-6) nanoalloy clusters are correlated in terms of dFt based descriptors viz. HOMO-LUMO gap, Global Hardness (η), Global Softness (S), Electronegativity (χ) and Electrophilicity Index (ω). Our computed bond length of this silicon- gold cluster exhibits a close agreement with experimental bond length. Regression analysis has been done in terms of correlation between our computed descriptors and their experimental counterpart. (paper)

  18. Correlation between electronic parameters and corrosion inhibition of benzothiazole derivatives- NMR parameters as important and neglected descriptors

    Science.gov (United States)

    Behzadi, Hadi; Forghani, Ali

    2017-03-01

    The relation between electronic properties and corrosion inhibitive performance of three benzothiazole derivatives 1,3-benzothiazol-2-amine (BTA), 6-methyl-1,3-benzothiazol-2-amine (MBTA) and 2-amino-1,3-benzthiazole-6-thiol (TBTA) has been investigated by density functional theory. The electronic properties including EHOMO, ELUMO and related parameters were calculated at the B3LYP/6-311++G(d,p) level. The chemical shielding CS tensors were introduced as important and neglected descriptors to evaluate inhibitive efficiency of corrosion inhibitors. Nuclear independent chemical shift (NICS) components, as an aromaticity criterion, were also investigated as local descriptor. Polarizability and CS descriptors, as second rank tensors, show the best correlations with inhibition efficiencies of studied inhibitors.

  19. Classificação de genótipos de amendoim baseada nos descritores agromorfológicos e isoenzimáticos Classification of peanut genotypes based on agromorphological and isoenzimatic descriptors

    Directory of Open Access Journals (Sweden)

    Roseane Cavalcanti dos Santos

    2000-03-01

    Full Text Available Procedeu-se à classificação de genótipos intraespecíficos de amendoim quanto aos descritores agromorfológicos e isoenzimáticos com auxílio da análise dos componentes principais. Vinte e três descritores foram analisados, dentre esses, onze foram morfológicos, nove agronômicos e três protéico- enzimáticos. Baseado nas evidências da análise dos componentes principais, verificou-se que os principais descritores morfológicos foram o tipo botânico, pigmentação da haste principal, padrão de inflorescência, ponto de maturação da vagem, cor dos folíolos, tamanho da vagem, hábito de crescimento, cor da semente e pilosidade da planta. Nos agronômicos, as maiores cargas foram para o início da floração, peso de 100 sementes, número de vagens/planta, porcentagem de vagens chochas e rendimento em amêndoas. Na combinação desses caracteres, as maiores cargas foram observadas para os descritores porcentagem de vagens chochas, número de semente/vagem, número de vagens/planta, rendimento em amêndoas, tamanho da vagem e o tipo botânico. Na análise dos sistemas enzimáticos, verificou-se que nenhum dos sistemas apresentou qualquer relação entre os padrões de banda e os tipos botânicos; contudo, constatou-se que a similaridade baseada nos tipos agromorfológicos dos genótipos do tipo Valência deve corresponder com a encontrada na base dos sistemas protéico-enzimáticos.The agromorphological and isoenzimatic descriptors were used to classify peanut infraespecific genotypes by principal components analysis. Twenty three descriptors were utilized, among them, eleven were morphologic, nine agronomic and three molecular ones. Based on the results of principal components analysis, it was verified that the main morphological descriptors were botany type, pigmentation of main stem, inflorescence pattern, pod maturation, leaflets colour, growth habit, seed colour and hairiness; the main agronomic descriptors were blomming, 100

  20. 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.

  1. 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.

  2. Selecting an informative features vocabulary for recognition algorithms based on Fourier-descriptors

    Directory of Open Access Journals (Sweden)

    V. Ya. Kolyuchkin

    2014-01-01

    Full Text Available Working vocabulary of features include most informative features of objects to be recognized. The aim is to develop a method of forming a working vocabulary of features for recognition algorithms based on Fourier-descriptors of the object image contours.To solve this problem the paper offers to use the method of functional maximization that is the ratio of the distance between the classes to the spread of objects within each of the classes represented in the feature space, which is formed on the basis of Fourier-descriptors.To check the effectiveness of the proposed method to form a working vocabulary of features the numerical experiments have been carried out. The experiments used two databases of reference images consisting of 10 and 13 reference images. Test images obtained by rotating the reference images, by zooming, as well as by adding the noise using the normal law of distribution have been created from these images. The proposed by the author algorithm, which uses the Prewitt operator, threshold segmentation, and morphological processing has marked the contours of images. The original vocabulary of features derived from the Fourier-descriptors has dimension of 98. The vocabularies of working features having the dimensions, respectively, 3 and 4 have been formed on the basis of functional maximization for both reference images. In the course of numerical experiments the frequency of correct decisions to recognise the features of reference bases of images for the original and working vocabularies has been evaluated. It has been proved that the algorithm of recognition with the formed working vocabularies of features provides a great efficiency of automatic recognition of objects.There are known publications, which use a similar method to form a working vocabulary of features in algorithms of human recognition by the image. But there are no publications on choosing the vocabulary of features for recognition algorithms based on the

  3. Searching for global descriptors of engineered nanomaterial fate and transport in the environment.

    Science.gov (United States)

    Westerhoff, Paul; Nowack, Bernd

    2013-03-19

    Engineered nanomaterials (ENMs) are a new class of environmental pollutants. Researchers are beginning to debate whether new modeling paradigms and experimental tests to obtain model parameters are required for ENMs or if approaches for existing pollutants are robust enough to predict ENM distribution between environmental compartments. This Account outlines how experimental research can yield quantitative data for use in ENM fate and exposure models. We first review experimental testing approaches that are employed with ENMs. Then we compare and contrast ENMs against other pollutants. Finally, we summarize the findings and identify research needs that may yield global descriptors for ENMs that are suitable for use in fate and transport modeling. Over the past decade, researchers have made significant progress in understanding factors that influence the fate and transport of ENMs. In some cases, researchers have developed approaches toward global descriptor models (experimental, conceptual, and quantitative). We suggest the following global descriptors for ENMs: octanol-water partition coefficients, solid-water partition coefficients, attachment coefficients, and rate constants describing reactions such as dissolution, sedimentation, and degradation. ENMs appear to accumulate at the octanol-water interface and readily interact with other interfaces, such as lipid-water interfaces. Batch experiments to investigate factors that influence retention of ENMs on solid phases are very promising. However, ENMs probably do not behave in the same way as dissolved chemicals, and therefore, researchers need to use measurement techniques and concepts more commonly associated with colloids. Despite several years of research with ENMs in column studies, available summaries tend to discuss the effects of ionic strength, pH, organic matter, ENM type, packing media, or other parameters qualitatively rather than reporting quantitative values, such as attachment efficiencies, that

  4. Molecular moment similarity between several nucleoside analogs of thymidine and thymidine. sil@watson.ibm.com.

    Science.gov (United States)

    Silverman, B D; Pitman, M C; Platt, D E

    1999-06-01

    Molecular moment descriptors of the shape and charge distributions of twenty five nucleoside structures have been examined. The structures include thymidine as well as the difluorotoluene nucleoside analog which has been found to pair efficiently with adenine by polymerase catalysis. The remaining twenty three structures have been chosen to be as structurally similar to thymidine and to the difluorotoluene nucleoside analog as possible. The moment descriptors which include a description of the relationship of molecular charge to shape show the difluorotoluene nucleoside to be one of the most proximate molecules to thymidine in the space of the molecular moments. The calculations, therefore, suggest that polymerase specificity might be not only a consequence of molecular steric features alone but also of the molecular electrostatic environment and its registration with molecular shape.

  5. Robust Stabilization of T-S Fuzzy Stochastic Descriptor Systems via Integral Sliding Modes.

    Science.gov (United States)

    Li, Jinghao; Zhang, Qingling; Yan, Xing-Gang; Spurgeon, Sarah K

    2017-09-19

    This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi-Sugeno (T-S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T-S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.

  6. Iris Segmentation using Gradient Magnitude and Fourier Descriptor for Multimodal Biometric Authentication System

    Directory of Open Access Journals (Sweden)

    Defiana Sulaeman

    2016-12-01

    Full Text Available Perfectly segmenting the area of the iris is one of the most important steps in iris recognition. There are several problematic areas that affect the accuracy of the iris segmentation step, such as eyelids, eyelashes, glasses, pupil (due to less accurate iris segmentation, motion blur, and lighting and specular reflections. To solve these problems, gradient magnitude and Fourier descriptor are employed to do iris segmentation in the proposed Multimodal Biometric Authentication System (MBAS. This approach showed quite promising results, i.e. an accuracy rate of 97%. The result of the iris recognition system was combined with the result of an open-source fingerprint recognition system to develop a multimodal biometrics authentication system. The results of the fusion between iris and fingerprint authentication were 99% accurate. Data from Multimedia Malaysia University (MMUI and our own prepared database, the SGU-MB-1 dataset, were used to test the accuracy of the proposed system.

  7. Lagrangian descriptors and the assessment of the predictive capacity of oceanic data sets

    Science.gov (United States)

    Mendoza, C.; Mancho, A. M.; Wiggins, S.

    2014-06-01

    We use a recently developed Lagrangian transport tool, Lagrangian descriptors, to compare the transport properties of data distributed by AVISO and numerical simulations obtained from the HYCOM model in the Yucatán-Florida current system. Our data correspond to the months from June through August 2010. Structures obtained from HYCOM are noisier than those from AVISO; however, both AVISO and HYCOM succeed in identifying Lagrangian structures that influence the paths of drifters, such as eddies, currents, lobes, etc. We find evidence in which AVISO gives the positions of important hyperbolic trajectories in a manner that is inconsistent with the trajectories of the drifters, while for the same examples HYCOM succeeds to this end.

  8. Harmonization of sound insulation descriptors and classification schemes in Europe: COST Action TU0901

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    -in-Chief. Handbook of noise and vibration control, USA: Wiley and Son; 2007 [Ch. 114]. [4] COST Action TU0901 “Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions”, 2009-2013, www.cost.eu/index.php?id=240&action_number=tu0901 (public information at COST website) or http...... Sound Insulation Aspects in Sustainable Urban Housing Constructions" has been approved and runs for four years from November 2009. Until now (end 2010), 28 countries in Europe and 3 overseas countries have signed up for TU0901, and about 85 people have been nominated for the management committee...... of the inhabitants and the society. References [1] "Sound insulation between dwellings – Descriptors in building regulations in Europe" by Birgit Rasmussen & Jens Holger Rindel. Applied Acoustics, 2010, 71(3), 171-180. http://dx.doi.org/10.1016/j.apacoust.2009.05.002 [2] "Sound insulation between dwellings...

  9. A Java Chemical Structure Editor Supporting the Modular Chemical Descriptor Language (MCDL

    Directory of Open Access Journals (Sweden)

    Andrei A. Gakh

    2006-03-01

    Full Text Available A compact Modular Chemical Descriptor Language (MCDL chemical structure editor (Java applet is described. The small size (approximately 200 KB of the applet allows its use to display and edit chemical structures in various Internet applications. The editor supports the MCDL format, in which structures are presented in compact canonical form and is capable of restoring bond orders as well as of managing atom and bond drawing overlap. A small database of cage and large cyclic fragment is used for optimal representation of difficult-to-draw molecules. The improved algorithm of the structure diagram generation can be used for other chemical notations that lack atomic coordinates (SMILES, InChI.

  10. Cerebellum segmentation in MRI using atlas registration and local multi-scale image descriptors

    DEFF Research Database (Denmark)

    van der Lijn, F.; de Bruijne, M.; Hoogendam, Y.Y.

    2009-01-01

    We propose a novel cerebellum segmentation method for MRI, based on a combination of statistical models of the structure's expected location in the brain and its local appearance. The appearance model is obtained from a k-nearest-neighbor classifier, which uses a set of multi-scale local image...... descriptors as features. The spatial model is constructed by registering multiple manually annotated datasets to the unlabeled target image. The two components are then combined in a Bayesian framework. The method is quantitatively validated in a leave-one-out experiment using 18 MR images of elderly subjects....... The experiment showed that the method produces accurate segmentations. The mean Dice similarity index compared to the manual reference was 0.953 for left and right, and the mean surface distance was 0.49 mm for left and 0.50 mm for right. The combined atlas- and appearance-based method was found to be more...

  11. Categorical Dimensions of Human Odor Descriptor Space Revealed by Non-Negative Matrix Factorization

    Science.gov (United States)

    Castro, Jason B.; Ramanathan, Arvind; Chennubhotla, Chakra S.

    2013-01-01

    In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain unclear. Here, we use non-negative matrix factorization (NMF) – a dimensionality reduction technique – to uncover structure in a panel of odor profiles, with each odor defined as a point in multi-dimensional descriptor space. The properties of NMF are favorable for the analysis of such lexical and perceptual data, and lead to a high-dimensional account of odor space. We further provide evidence that odor dimensions apply categorically. That is, odor space is not occupied homogenously, but rather in a discrete and intrinsically clustered manner. We discuss the potential implications of these results for the neural coding of odors, as well as for developing classifiers on larger datasets that may be useful for predicting perceptual qualities from chemical structures. PMID:24058466

  12. Distance phenomena in high-dimensional chemical descriptor spaces: consequences for similarity-based approaches.

    Science.gov (United States)

    Rupp, Matthias; Schneider, Petra; Schneider, Gisbert

    2009-11-15

    Measuring the (dis)similarity of molecules is important for many cheminformatics applications like compound ranking, clustering, and property prediction. In this work, we focus on real-valued vector representations of molecules (as opposed to the binary spaces of fingerprints). We demonstrate the influence which the choice of (dis)similarity measure can have on results, and provide recommendations for such choices. We review the mathematical concepts used to measure (dis)similarity in vector spaces, namely norms, metrics, inner products, and, similarity coefficients, as well as the relationships between them, employing (dis)similarity measures commonly used in cheminformatics as examples. We present several phenomena (empty space phenomenon, sphere volume related phenomena, distance concentration) in high-dimensional descriptor spaces which are not encountered in two and three dimensions. These phenomena are theoretically characterized and illustrated on both artificial and real (bioactivity) data. 2009 Wiley Periodicals, Inc.

  13. 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.

  14. Categorical dimensions of human odor descriptor space revealed by non-negative matrix factorization

    Energy Technology Data Exchange (ETDEWEB)

    Chennubhotla, Chakra [University of Pittsburgh School of Medicine, Pittsburgh PA; Castro, Jason [Bates College

    2013-01-01

    In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain un- clear. Here, we use non-negative matrix factorization (NMF) - a dimensionality reduction technique - to uncover structure in a panel of odor profiles, with each odor defined as a point in multi-dimensional descriptor space. The properties of NMF are favorable for the analysis of such lexical and perceptual data, and lead to a high-dimensional account of odor space. We further provide evidence that odor di- mensions apply categorically. That is, odor space is not occupied homogenously, but rather in a discrete and intrinsically clustered manner. We discuss the potential implications of these results for the neural coding of odors, as well as for developing classifiers on larger datasets that may be useful for predicting perceptual qualities from chemical structures.

  15. Fractional Differential Texture Descriptors Based on the Machado Entropy for Image Splicing Detection

    Directory of Open Access Journals (Sweden)

    Rabha W. Ibrahim

    2015-07-01

    Full Text Available Image splicing is a common operation in image forgery. Different techniques of image splicing detection have been utilized to regain people’s trust. This study introduces a texture enhancement technique involving the use of fractional differential masks based on the Machado entropy. The masks slide over the tampered image, and each pixel of the tampered image is convolved with the fractional mask weight window on eight directions. Consequently, the fractional differential texture descriptors are extracted using the gray-level co-occurrence matrix for image splicing detection. The support vector machine is used as a classifier that distinguishes between authentic and spliced images. Results prove that the achieved improvements of the proposed algorithm are compatible with other splicing detection methods.

  16. Joint efforts to harmonize sound insulation descriptors and classification schemes in Europe (COST TU0901)

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2010-01-01

    Sound insulation descriptors, regulatory requirements and classification schemes in Europe represent a high degree of diversity. One implication is very little exchange of experience of housing design and construction details for different levels of sound insulation; another is trade barriers...... for building systems and products. Unfortunately, there is evidence for a development in the "wrong" direction. For example, sound classification schemes for dwellings exist in nine countries. There is no sign on increasing harmonization, rather the contrary, as more countries are preparing proposals with new......, new housing must meet the needs of the people and offer comfort. Also for existing housing, sound insulation aspects should be taken into account, when renovating housing; otherwise the renovation is not “sustainable”. A joint European Action, COST TU0901 "Integrating and Harmonizing Sound Insulation...

  17. Obtaining time-dependent multi-dimensional dividing surfaces using Lagrangian descriptors

    Science.gov (United States)

    Feldmaier, Matthias; Junginger, Andrej; Main, Jörg; Wunner, Günter; Hernandez, Rigoberto

    2017-11-01

    Dynamics between reactants and products are often mediated by a rate-determining barrier and an associated dividing surface leading to the transition state theory rate. This framework is challenged when the barrier is time-dependent because its motion can give rise to recrossings across the fixed dividing surface. A non-recrossing time-dependent dividing surface can nevertheless be attached to the TS trajectory resulting in recrossing-free dynamics. We extend the formalism-constructed using Lagrangian Descriptors-to systems with additional bath degrees of freedom. The propagation of reactant ensembles provides a numerical demonstration that our dividing surface is recrossing-free and leads to exact TST rates.

  18. 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.

  19. 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.

  20. Morphological analysis of the left ventricular endocardial surface using a bag-of-features descriptor.

    Science.gov (United States)

    Mukhopadhyay, Anirban; Qian, Zhen; Bhandarkar, Suchendra M; Liu, Tianming; Voros, Szilard; Rinehart, Sarah

    2015-07-01

    The limitations of conventional imaging techniques have hitherto precluded a thorough and formal investigation of the complex morphology of the left ventricular (LV) endocardial surface and its relation to the severity of coronary artery disease (CAD). However, recent developments in high-resolution multirow-detector computed tomography (MDCT) scanner technology have enabled the imaging of the complex LV endocardial surface morphology in a single heartbeat. Analysis of high-resolution computed tomography images from a 320-MDCT scanner allows for the noninvasive study of the relationship between the percent diameter stenosis (DS) values of the major coronary arteries and localization of the cardiac segments affected by coronary arterial stenosis. In this paper, a novel approach for the analysis of the nonrigid LV endocardial surface from MDCT images, using a combination of rigid body transformation-invariant shape descriptors and a more generalized isometry-invariant Bag-of-Features descriptor, is proposed and implemented. The proposed approach is shown to be successful in identifying, localizing, and quantifying the incidence and extent of CAD and, thus, is seen to have a potentially significant clinical impact. Specifically, the association between the incidence and extent of CAD, determined via the percent DS measurements of the major coronary arteries, and the alterations in the endocardial surface morphology is formally quantified. The results of the proposed approach on 16 normal datasets and 16 abnormal datasets exhibiting CAD with varying levels of severity are presented. A multivariable regression test is employed to test the effectiveness of the proposed morphological analysis approach. Experiments performed on a strictly leave-one-out basis are shown to exhibit a distinct and interesting pattern in terms of the correlation coefficient values within the cardiac segments, where the incidence of coronary arterial stenosis is localized.

  1. Molecular Vibration-Activity Relationship in the Agonism of Adenosine Receptors

    OpenAIRE

    Chee, Hyun Keun; Oh, S. June

    2013-01-01

    The molecular vibration-activity relationship in the receptor-ligand interaction of adenosine receptors was investigated by structure similarity, molecular vibration, and hierarchical clustering in a dataset of 46 ligands of adenosine receptors. The resulting dendrogram was compared with those of another kind of fingerprint or descriptor. The dendrogram result produced by corralled intensity of molecular vibrational frequency outperformed four other analyses in the current study of adenosine ...

  2. Partition coefficients of organics between water and carbon dioxide revisited: Correlation with solute molecular descriptors and solvent cohesive properties

    Czech Academy of Sciences Publication Activity Database

    Roth, Michal

    2016-01-01

    Roč. 50, č. 23 (2016), s. 12857-12863 ISSN 0013-936X R&D Projects: GA ČR(CZ) GA16-03749S Institutional support: RVO:68081715 Keywords : partitioning between water and supercritical CO2 * organic solutes * K-factor modeling * linear solvation energy relationship Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 6.198, year: 2016

  3. The implementation of aerial object recognition algorithm based on contour descriptor in FPGA-based on-board vision system

    Science.gov (United States)

    Babayan, Pavel; Smirnov, Sergey; Strotov, Valery

    2017-10-01

    This paper describes the aerial object recognition algorithm for on-board and stationary vision system. Suggested algorithm is intended to recognize the objects of a specific kind using the set of the reference objects defined by 3D models. The proposed algorithm based on the outer contour descriptor building. The algorithm consists of two stages: learning and recognition. Learning stage is devoted to the exploring of reference objects. Using 3D models we can build the database containing training images by rendering the 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the recognition stage of the algorithm. The recognition stage is focusing on estimating the similarity of the captured object and the reference objects by matching an observed image descriptor and the reference object descriptors. The experimental research was performed using a set of the models of the aircraft of the different types (airplanes, helicopters, UAVs). The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

  4. 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

  5. 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

  6. A Comparative Study of Personality Descriptors Attributed to the Deaf, the Blind, and Individuals with No Sensory Disability.

    Science.gov (United States)

    Cambra, Cristina

    1996-01-01

    University students (N=222) evaluated personality descriptors as applied to people with deafness, blindness, or no sensory disability. Two general stereotypes of the deaf emerged: that of general nonsociability and that of limited intelligence. However, students who already knew a deaf person assigned the deaf more positive personality…

  7. Hybrid in silico models for drug-induced liver injury using chemical descriptors and in vitro cell-imaging information.

    Science.gov (United States)

    Zhu, Xiang-Wei; Sedykh, Alexander; Liu, Shu-Shen

    2014-03-01

    Drug-induced liver injury (DILI) is a major adverse drug reaction that accounts for one-third of post-marketing drug withdrawals. Several classifiers for human hepatotoxicity using chemical descriptors with limited prediction accuracies have been published. In this study, we developed predictive in silico models based on a set of 156 DILI positive and 136 DILI negative compounds for DILI prediction. First, models based on a chemical descriptor (CDK, Dragon and MOE) and in vitro cell-imaging endpoints [human hepatocyte imaging assay technology (HIAT) descriptors] were built using random forest (RF) and five-fold cross-validation procedure. Then three hybrid models were built using HIAT and a single type of chemical descriptors. Generally, the models based only on chemical descriptors were poor, with a correct classification rate (CCR) around 0.60 when the default threshold value (i.e. threshold = 0.50) was used. The hybrid models afforded a CCR of 0.73 with a specificity of 0.74 and a better true positive rate (sensitivity of 0.71), which is crucial in drug toxicity screening for the purpose of patient safety. The benefit of hybrid models was even more drastic when stricter classification thresholds were employed (e.g. CCR would be 0.83 when double thresholds (non-toxic 0.60) were used for the hybrid model). We have developed rigorously validated hybrid models which can be used in virtual screening of lead compounds with potential hepatotoxicity. Our study also showed a chemical structure and in vitro biological data can be complementary in enhancing the prediction accuracy of human hepatotoxicity and can afford rational mechanistic interpretation. Copyright © 2013 John Wiley & Sons, Ltd.

  8. New Quantitative Structure-Activity Relationship Model for Angiotensin-Converting Enzyme Inhibitory Dipeptides Based on Integrated Descriptors.

    Science.gov (United States)

    Deng, Baichuan; Ni, Xiaojun; Zhai, Zhenya; Tang, Tianyue; Tan, Chengquan; Yan, Yijing; Deng, Jinping; Yin, Yulong

    2017-11-08

    Angiotensin-converting enzyme (ACE) inhibitory peptides derived from food proteins have been widely reported for hypertension treatment. In this paper, a benchmark data set containing 141 unique ACE inhibitory dipeptides was constructed through database mining, and a quantitative structure-activity relationships (QSAR) study was carried out to predict half-inhibitory concentration (IC 50 ) of ACE activity. Sixteen descriptors were tested and the model generated by G-scale descriptor showed the best predictive performance with the coefficient of determination (R 2 ) and cross-validated R 2 (Q 2 ) of 0.6692 and 0.6220, respectively. For most other descriptors, R 2 were ranging from 0.52 to 0.68 and Q 2 were ranging from 0.48 to 0.61. A complex model combining all 16 descriptors was carried out and variable selection was performed in order to further improve the prediction performance. The quality of model using integrated descriptors (R 2 0.7340 ± 0.0038, Q 2 0.7151 ± 0.0019) was better than that of G-scale. An in-depth study of variable importance showed that the most correlated properties to ACE inhibitory activity were hydrophobicity, steric, and electronic properties and C-terminal amino acids contribute more than N-terminal amino acids. Five novel predicted ACE-inhibitory peptides were synthesized, and their IC 50 values were validated through in vitro experiments. The results indicated that the constructed model could give a reliable prediction of ACE-inhibitory activity of peptides, and it may be useful in the design of novel ACE-inhibitory peptides.

  9. Long-term prediction of solar and geomagnetic activity daily time series using singular spectrum analysis and fuzzy descriptor models

    Science.gov (United States)

    Mirmomeni, M.; Kamaliha, E.; Shafiee, M.; Lucas, C.

    2009-09-01

    Of the various conditions that affect space weather, Sun-driven phenomena are the most dominant. Cyclic solar activity has a significant effect on the Earth, its climate, satellites, and space missions. In recent years, space weather hazards have become a major area of investigation, especially due to the advent of satellite technology. As such, the design of reliable alerting and warning systems is of utmost importance, and international collaboration is needed to develop accurate short-term and long-term prediction methodologies. Several methods have been proposed and implemented for the prediction of solar and geomagnetic activity indices, but problems in predicting the exact time and magnitude of such catastrophic events still remain. There are, however, descriptor systems that describe a wider class of systems, including physical models and non-dynamic constraints. It is well known that the descriptor system is much tighter than the state-space expression for representing real independent parametric perturbations. In addition, the fuzzy descriptor models as a generalization of the locally linear neurofuzzy models are general forms that can be trained by constructive intuitive learning algorithms. Here, we propose a combined model based on fuzzy descriptor models and singular spectrum analysis (SSA) (FD/SSA) to forecast a number of geomagnetic activity indices in a manner that optimizes a fuzzy descriptor model for each of the principal components obtained from singular spectrum analysis and recombines the predicted values so as to transform the geomagnetic activity time series into natural chaotic phenomena. The method has been applied to predict two solar and geomagnetic activity indices: geomagnetic aa and solar wind speed (SWS) of the solar wind index. The results demonstrate the higher power of the proposed method-- compared to other methods -- for predicting solar activity.

  10. 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

  11. 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

  12. Fighting high molecular weight in bioactive molecules with sub-pharmacophore-based virtual screening.

    Science.gov (United States)

    von Korff, Modest; Freyss, Joel; Sander, Thomas; Boss, Christoph; Ciana, Claire-Lise

    2012-02-27

    A new subpharmacophore-based virtual screening method is introduced. Subpharmacophores are derived from large active molecules to detect small bioactive molecules as seeds for starting points in medicinal chemistry programs. A large data set was assembled from the ChEMBL database to check the validity of this approach. Molecules for 133 targets with molecular weights between 450 and 850 were selected as queries. For the query molecules, the pharmacophore descriptors were calculated. Up to 56 000 subpharmacophore descriptors with five to seven pharmacophore points were derived from the query pharmacophores. The subpharmacophore descriptors were used as queries to screen 1079 test data sets, containing decoys and spike molecules. A maximum upper molecular weight limit of 400 Da was set for the test molecules. Three different chemical fingerprint descriptors were used for comparison purposes. The subpharmacophore approach detected active molecules for 85 out of 133 targets and outperformed the chemical fingerprints. This ligand-based virtual screening experiment was triggered by the needs of medicinal chemistry. Applying the subpharmacophore method in a medicinal chemistry program, where a lead molecule with a molecular weight of 800 Da was available, resulted in a new series of molecules with molecular weights below 400.

  13. Classification of cardiovascular tissues using LBP based descriptors and a cascade SVM.

    Science.gov (United States)

    Mazo, Claudia; Alegre, Enrique; Trujillo, Maria

    2017-08-01

    Histological images have characteristics, such as texture, shape, colour and spatial structure, that permit the differentiation of each fundamental tissue and organ. Texture is one of the most discriminative features. The automatic classification of tissues and organs based on histology images is an open problem, due to the lack of automatic solutions when treating tissues without pathologies. In this paper, we demonstrate that it is possible to automatically classify cardiovascular tissues using texture information and Support Vector Machines (SVM). Additionally, we realised that it is feasible to recognise several cardiovascular organs following the same process. The texture of histological images was described using Local Binary Patterns (LBP), LBP Rotation Invariant (LBPri), Haralick features and different concatenations between them, representing in this way its content. Using a SVM with linear kernel, we selected the more appropriate descriptor that, for this problem, was a concatenation of LBP and LBPri. Due to the small number of the images available, we could not follow an approach based on deep learning, but we selected the classifier who yielded the higher performance by comparing SVM with Random Forest and Linear Discriminant Analysis. Once SVM was selected as the classifier with a higher area under the curve that represents both higher recall and precision, we tuned it evaluating different kernels, finding that a linear SVM allowed us to accurately separate four classes of tissues: (i) cardiac muscle of the heart, (ii) smooth muscle of the muscular artery, (iii) loose connective tissue, and (iv) smooth muscle of the large vein and the elastic artery. The experimental validation was conducted using 3000 blocks of 100 × 100 sized pixels, with 600 blocks per class and the classification was assessed using a 10-fold cross-validation. using LBP as the descriptor, concatenated with LBPri and a SVM with linear kernel, the main four classes of tissues were

  14. Evaluation of vegetation post-fire resilience in the Alpine region using descriptors derived from MODIS spectral index time series

    Science.gov (United States)

    Di Mauro, Biagio; Fava, Francesco; Busetto, Lorenzo; Crosta, Giovanni Franco; Colombo, Roberto

    2013-04-01

    In this study a method based on the analysis of MODerate-resolution Imaging Spectroradiometer (MODIS) time series is proposed to estimate the post-fire resilience of mountain vegetation (broadleaf forest and prairies) in the Italian Alps. Resilience is defined herewith as the ability of a dynamical system to counteract disturbances. It can be quantified by the amount of time the disturbed system takes to resume, in statistical terms, an ecological functionality comparable with its undisturbed behavior. Satellite images of the Normalized Difference Vegetation Index (NDVI) and of the Enhanced Vegetation Index (EVI) with spatial resolution of 250m and temporal resolution of 16 days in the 2000-2012 time period were used. Wildfire affected areas in the Lombardy region between the years 2000 and 2010 were analysed. Only large fires (affected area >40ha) were selected. For each burned area, an undisturbed adjacent control site was located. Data pre-processing consisted in the smoothing of MODIS time series for noise removal and then a double logistic function was fitted. Land surface phenology descriptors (proxies for growing season start/end/length and green biomass) were extracted in order to characterize the time evolution of the vegetation. Descriptors from a burned area were compared to those extracted from the respective control site by means of the one-way analysis of variance. According to the number of subsequent years which exhibit statistically meaningful difference between burned and control site, five classes of resilience were identified and a set of thematic maps was created for each descriptor. The same method was applied to all 84 aggregated events and to events aggregated by main land cover. EVI index results more sensitive to fire impact than NDVI index. Analysis shows that fire causes both a reduction of the biomass and a variation in the phenology of the Alpine vegetation. Results suggest an average ecosystem resilience of 6-7 years. Moreover

  15. The Big Five Factor Marker Adjectives Are Not Especially Popular Words. Are They Superior Descriptors?

    Science.gov (United States)

    Roivainen, Eka

    2015-12-01

    Vocabularies of natural languages evolve over time. Useful words become more popular and useless concepts disappear. In this study, the frequency of the use of 295 English, 100 German, and 114 French personality adjectives in book texts and Twitter messages as qualifiers of the words person, woman, homme, femme, and Person was studied. Word frequency data were compared to factor loadings from previous factor analytic studies on personality terms. The correlation between the popularity of an adjective and its highest primary loading in five- and six-factor models was low (-0.12 to 0.17). The Big five (six) marker adjectives were not more popular than "blended" adjectives that had moderate loadings on several factors. This finding implies that laymen consider "blended" adjectives as equally useful descriptors compared to adjectives that represent core features of the five (six) factors. These results are compatible with three hypotheses: 1) laymen are not good at describing personality, 2) the five (six) factors are artifacts of research methods, 3) the interaction of the five (six) factors is not well understood.

  16. 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.

  17. Environmental quality of Italian marine water by means of marine strategy framework directive (MSFD descriptor 9.

    Directory of Open Access Journals (Sweden)

    Chiara Maggi

    Full Text Available ISPRA, on behalf of the Italian Ministry of Environment, carried out the initial assessment of environmental quality status of the 3 Italian subregions (Mediterranean Sea Region on Descriptor 9. The approach adopted to define the GES started to verify that contaminants in fish and other seafood for human consumption did not exceed levels established by Community legislation (Reg. 1881/2006 and further updates. As the Marine Strategy Framework Directive (MSFD requires to use health tools to assess the environment, Italy decided to adopt a statistical range of acceptance of thresholds identified by national (D.Lgs. 152/2006 concerning water quality required for mussel farms and international legislation (Reg. 1881/2006 and further updates, which allowed to use the health results and to employ them for the assessment of environmental quality. Italy proposed that Good Environmental Status (GES is achieved when concentrations are lower than statistical range of acceptance, estimated on samples of fish and fishery products coming from only national waters. GIS-based approach a to perform different integration levels for station, cell's grid and years, was used; the elaborations allowed to judge the environmental quality good.

  18. Microcalcification morphological descriptors and parenchyma fractal dimension hierarchically interact in breast cancer: A diagnostic perspective.

    Science.gov (United States)

    Verma, Garima; Luciani, Maria Laura; Palombo, Alessandro; Metaxa, Linda; Panzironi, Giovanna; Pediconi, Federica; Giuliani, Alessandro; Bizzarri, Mariano; Todde, Virginia

    2018-02-01

    Herein, we propose a Systems Biology approach aimed at identifying quantitative morphological parameters useful in discriminating benign from malignant breast microcalcifications at digital mammography. The study includes 31 patients in which microcalcifications had been detected during XR mammography and were further confirmed by stereotactic (XR-guided) biopsies. Patients were classified according to the BIRADS (Breast Imaging-Reporting and Data System), along with their parenchyma fractal dimension and biopsy size. A geometrical-topological characterization of microcalcifications was obtained as well. The 'size of biopsy' was the parameter endowed with the highest discriminant power between malignant and benign lesions thus confirming the reliability of surgeon judgment. The quantitative shape evaluation of both lesions and parenchyma allowed for a promising prediction of the BIRADS score. The area of lesions and parenchyma fractal dimension show a complex distribution for malignant breast calcifications that are consistent with their qualitative morphological pattern. Fractal dimension analysis enables the user to obtain reliable results as proved by its efficiency in the prediction of the morphology of breast cancer. By reconstructing a phase-space distribution of biophysical parameters, different patterns of aggregation are recognized corresponding to different calcium deposition patterns, while the combination of tissue and microcalcification morphological descriptors provide a statistically significant prediction of tumour grade. The development of an automated morphology evaluation system can help during clinical evaluation while also sketching mechanistic hypotheses of microcalcification generation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Hankel-norm approximation of FIR filters: a descriptor-systems based approach

    Science.gov (United States)

    Halikias, George; Tsoulkas, Vasilis; Pantelous, Athanasios; Milonidis, Efstathios

    2010-09-01

    We propose a new method for approximating a matrix finite impulse response (FIR) filter by an infinite impulse response (IIR) filter of lower McMillan degree. This is based on a technique for approximating discrete-time descriptor systems and requires only standard linear algebraic routines, while avoiding altogether the solution of two matrix Lyapunov equations which is computationally expensive. Both the optimal and the suboptimal cases are addressed using a unified treatment. A detailed solution is developed in state-space or polynomial form, using only the Markov parameters of the FIR filter which is approximated. The method is finally applied to the design of scalar IIR filters with specified magnitude frequency-response tolerances and approximately linear-phase characteristics. A priori bounds on the magnitude and phase errors are obtained which may be used to select the reduced-order IIR filter order which satisfies the specified design tolerances. The effectiveness of the method is illustrated with a numerical example. Additional applications of the method are also briefly discussed.

  20. Facial expression recognition based on weber local descriptor and sparse representation

    Science.gov (United States)

    Ouyang, Yan

    2018-03-01

    Automatic facial expression recognition has been one of the research hotspots in the area of computer vision for nearly ten years. During the decade, many state-of-the-art methods have been proposed which perform very high accurate rate based on the face images without any interference. Nowadays, many researchers begin to challenge the task of classifying the facial expression images with corruptions and occlusions and the Sparse Representation based Classification framework has been wildly used because it can robust to the corruptions and occlusions. Therefore, this paper proposed a novel facial expression recognition method based on Weber local descriptor (WLD) and Sparse representation. The method includes three parts: firstly the face images are divided into many local patches, and then the WLD histograms of each patch are extracted, finally all the WLD histograms features are composed into a vector and combined with SRC to classify the facial expressions. The experiment results on the Cohn-Kanade database show that the proposed method is robust to occlusions and corruptions.

  1. Comparison of efficiency of distance measurement methodologies in mango (Mangifera indica) progenies based on physicochemical descriptors.

    Science.gov (United States)

    Alves, E O S; Cerqueira-Silva, C B M; Souza, A M; Santos, C A F; Lima Neto, F P; Corrêa, R X

    2012-03-14

    We investigated seven distance measures in a set of observations of physicochemical variables of mango (Mangifera indica) submitted to multivariate analyses (distance, projection and grouping). To estimate the distance measurements, five mango progeny (total of 25 genotypes) were analyzed, using six fruit physicochemical descriptors (fruit weight, equatorial diameter, longitudinal diameter, total soluble solids in °Brix, total titratable acidity, and pH). The distance measurements were compared by the Spearman correlation test, projection in two-dimensional space and grouping efficiency. The Spearman correlation coefficients between the seven distance measurements were, except for the Mahalanobis' generalized distance (0.41 ≤ rs ≤ 0.63), high and significant (rs ≥ 0.91; P < 0.001). Regardless of the origin of the distance matrix, the unweighted pair group method with arithmetic mean grouping method proved to be the most adequate. The various distance measurements and grouping methods gave different values for distortion (-116.5 ≤ D ≤ 74.5), cophenetic correlation (0.26 ≤ rc ≤ 0.76) and stress (-1.9 ≤ S ≤ 58.9). Choice of distance measurement and analysis methods influence the.

  2. Exploring spatial patterns of vulnerability for diverse biodiversity descriptors in regional conservation planning.

    Science.gov (United States)

    Vimal, Ruppert; Pluvinet, Pascal; Sacca, Céline; Mazagol, Pierre-Olivier; Etlicher, Bernard; Thompson, John D

    2012-03-01

    In this study, we developed a multi-criteria assessment of spatial variability of the vulnerability of three different biodiversity descriptors: sites of high conservation interest by virtue of the presence of rare or remarkable species, extensive areas of high ecological integrity, and landscape diversity in grid cells across an entire region. We assessed vulnerability in relation to (a) direct threats in and around sites to a distance of 2 km associated with intensive agriculture, building and road infrastructure and (b) indirect effects of human population density on a wider scale (50 km). The different combinations of biodiversity and threat indicators allowed us to set differential priorities for biodiversity conservation and assess their spatial variation. For example, with this method we identified sites and grid cells which combined high biodiversity with either high threat values or low threat values for the three different biodiversity indicators. In these two classes the priorities for conservation planning will be different, reduce threat values in the former and restrain any increase in the latter. We also identified low priority sites (low biodiversity with either high or low threats). This procedure thus allows for the integration of a spatial ranking of vulnerability into priority setting for regional conservation planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. APPLICATION OF BINARY DESCRIPTORS TO MULTIPLE FACE TRACKING IN VIDEO SURVEILLANCE SYSTEMS

    Directory of Open Access Journals (Sweden)

    A. L. Oleinik

    2016-07-01

    Full Text Available Subject of Research. The paper deals with the problem of multiple face tracking in a video stream. The primary application of the implemented tracking system is the automatic video surveillance. The particular operating conditions of surveillance cameras are taken into account in order to increase the efficiency of the system in comparison to existing general-purpose analogs. Method. The developed system is comprised of two subsystems: detector and tracker. The tracking subsystem does not depend on the detector, and thus various face detection methods can be used. Furthermore, only a small portion of frames is processed by the detector in this structure, substantially improving the operation rate. The tracking algorithm is based on BRIEF binary descriptors that are computed very efficiently on modern processor architectures. Main Results. The system is implemented in C++ and the experiments on the processing rate and quality evaluation are carried out. MOTA and MOTP metrics are used for tracking quality measurement. The experiments demonstrated the four-fold processing rate gain in comparison to the baseline implementation that processes every video frame with the detector. The tracking quality is on the adequate level when compared to the baseline. Practical Relevance. The developed system can be used with various face detectors (including slow ones to create a fully functional high-speed multiple face tracking solution. The algorithm is easy to implement and optimize, so it may be applied not only in full-scale video surveillance systems, but also in embedded solutions integrated directly into cameras.

  4. Environmental quality of Italian marine water by means of marine strategy framework directive (MSFD) descriptor 9.

    Science.gov (United States)

    Maggi, Chiara; Lomiri, Serena; Di Lorenzo, Bianca; d'Antona, Marco; Berducci, Maria Teresa

    2014-01-01

    ISPRA, on behalf of the Italian Ministry of Environment, carried out the initial assessment of environmental quality status of the 3 Italian subregions (Mediterranean Sea Region) on Descriptor 9. The approach adopted to define the GES started to verify that contaminants in fish and other seafood for human consumption did not exceed levels established by Community legislation (Reg. 1881/2006 and further updates). As the Marine Strategy Framework Directive (MSFD) requires to use health tools to assess the environment, Italy decided to adopt a statistical range of acceptance of thresholds identified by national (D.Lgs. 152/2006 concerning water quality required for mussel farms) and international legislation (Reg. 1881/2006 and further updates), which allowed to use the health results and to employ them for the assessment of environmental quality. Italy proposed that Good Environmental Status (GES) is achieved when concentrations are lower than statistical range of acceptance, estimated on samples of fish and fishery products coming from only national waters. GIS-based approach a to perform different integration levels for station, cell's grid and years, was used; the elaborations allowed to judge the environmental quality good.

  5. Prediction of Apoptosis Protein's Subcellular Localization by Fusing Two Different Descriptors Based on Evolutionary Information.

    Science.gov (United States)

    Liang, Yunyun; Zhang, Shengli

    2018-03-12

    The apoptosis protein has a central role in the development and the homeostasis of an organism. Obtaining information about the subcellular localization of apoptosis protein is very helpful to understand the apoptosis mechanism and the function of this protein. Prediction of apoptosis protein's subcellular localization is a challenging task, and currently the existing feature extraction methods mainly rely on the protein's primary sequence. In this paper we develop a feature extraction model based on two different descriptors of evolutionary information, which contains the 192 frequencies of triplet codons (FTC) in the RNA sequence derived from the protein's primary sequence and the 190 features from a detrended forward moving-average cross-correlation analysis (DFMCA) based on a position-specific scoring matrix (PSSM) generated by the PSI-BLAST program. Hence, this model is called FTC-DFMCA-PSSM. A 382-dimensional (382D) feature vector is constructed on the ZD98, ZW225 and CL317 datasets. Then a support vector machine is adopted as classifier, and the jackknife cross-validation test method is used for evaluating the accuracy. The overall prediction accuracies are further improved by an objective and rigorous jackknife test. Our model not only broadens the source of the feature information, but also provides a more accurate and reliable automated calculation method for the prediction of apoptosis protein's subcellular localization.

  6. Experiments and improvements of ear recognition based on local texture descriptors

    Science.gov (United States)

    Benzaoui, Amir; Adjabi, Insaf; Boukrouche, Abdelhani

    2017-04-01

    The morphology of the human ear presents rich and stable information embedded on the curved 3-D surface and has as a result attracted considerable attention from forensic scientists and engineers as a biometric recognition modality. However, recognizing a person's identity from the morphology of the human ear in unconstrained environments, with insufficient and incomplete training data, strong person-specificity, and high within-range variance, can be very challenging. Following our previous work on ear recognition based on local texture descriptors, we propose to use anatomical and embryological information about the human ear in order to find the autonomous components and the locations where large interindividual variations can be detected. Embryology is particularly relevant to our approach as it provides information on the possible changes that can be observed in the external structure of the ear. We experimented with three publicly available databases, namely: IIT Delhi-1, IIT Delhi-2, and USTB-1, consisting of several ear benchmarks acquired under varying conditions and imaging qualities. The experiments show excellent results, beyond the state of the art.

  7. Cognitive organization of emotion: differences between labels and descriptors of emotion in jealousy situations.

    Science.gov (United States)

    Hupka, R B; Eshett, C

    1988-06-01

    The purpose of this study was to ascertain whether the cognitive organization of labels of emotion differs from descriptions of affective states. This was done in the context of determining whether the attributions of labels of emotion and descriptions of affective responses in jealousy situations differed according to the status of the interloper, presence of an audience to the untoward behavior, and sex of the respondent. The subjects, 300 male and female junior college students, read vignettes which placed them at a party where their mates passionately kissed interlopers of varying status, and whose transgressions were, or were not, observed by others. The subjects were required to indicate the likelihood that they would experience anger, disgust, fear, jealousy, sadness, and surprise, and 49 cognitive and physiological descriptions of the affective states referred to by the aforementioned labels of emotion. Different findings were obtained with the labels and descriptors of affective states. This was interpreted as support for the systems theory of G.E. Schwartz. The descriptions, but not the labels, indicated that men were most upset when the interloper was a best friend and least concerned when he was a stranger. In contrast, women were most upset when the interloper was someone of equal or lower status than themselves and least upset when the interloper was their best friend.

  8. On the Prognostic Efficiency of Topological Descriptors for Magnetograms of Active Regions

    Science.gov (United States)

    Knyazeva, I. S.; Urtiev, F. A.; Makarenko, N. G.

    2017-12-01

    Solar flare prediction remains an important practical task of space weather. An increase in the amount and quality of observational data and the development of machine-learning methods has led to an improvement in prediction techniques. Additional information has been retrieved from the vector magnetograms; these have been recently supplemented by traditional line-of-sight (LOS) magnetograms. In this work, the problem of the comparative prognostic efficiency of features obtained on the basis of vector data and LOS magnetograms is discussed. Invariants obtained from a topological analysis of LOS magnetograms are used as complexity characteristics of magnetic patterns. Alternatively, the so-called SHARP parameters were used; they were calculated by the data analysis group of the Stanford University Laboratory on the basis of HMI/SDO vector magnetograms and are available online at the website (http://jsoc.stanford.edu/) with the solar dynamics observatory (SDO) database for the entire history of SDO observations. It has been found that the efficiency of large-flare prediction based on topological descriptors of LOS magnetograms in epignosis mode is at least s no worse than the results of prognostic schemes based on vector features. The advantages of the use of topological invariants based on LOS data are discussed.

  9. 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.

    2017-01-01

    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. PMID:28216571

  10. 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.

  11. 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.

  12. 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.

  13. 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)

  14. 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...

  15. Simultaneous estimation of genotype by environment interaction accounting for discrete and continuous environmental descriptors in Irish dairy cattle.

    Science.gov (United States)

    Windig, J J; Mulder, H A; Bohthe-Wilhelmus, D I; Veerkamp, R F

    2011-06-01

    Genotype by environment interaction can be analyzed by using a multi-trait model in which a trait measured in different environments is considered as separate traits. Alternatively, it can be analyzed by using a reaction norm model, in which the trait is considered a function of an environmental descriptor. Here, a model is developed where the 2 approaches are combined such that the effect of a continuous environmental descriptor can be analyzed in 2 or more discrete environments. The model is applied to somatic cell score (SCS) in relation to average herd milk production in 2 production environments: spring calving and year-round calving in Ireland. Heritabilities and additive genetic variances for SCS increased somewhat with increasing milk production and were higher in year-round calving. Under the combined model, the genetic correlation between spring and year-round calving was estimated at 0.82 to 0.84, clearly lower than obtained in a bivariate analysis ignoring effects of herd milk production. Thus, when estimating the genetic correlation between environments, effects of one environmental descriptor may be obscured by another, but can be disentangled in an analysis combining the reaction norm and the multi-trait approach. Such models will be especially useful for analyzing questions such as whether the effect of increasing production or temperature is more severe in different production systems or geographic regions. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  16. 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

    2014-01-01

    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. PMID:25153627

  17. 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.

  18. Finding a Good Feature Detector-Descriptor Combination for the 2d Keypoint-Based Registration of Tls Point Clouds

    Science.gov (United States)

    Urban, S.; Weinmann, M.

    2015-08-01

    The automatic and accurate registration of terrestrial laser scanning (TLS) data is a topic of great interest in the domains of city modeling, construction surveying or cultural heritage. While numerous of the most recent approaches focus on keypoint-based point cloud registration relying on forward-projected 2D keypoints detected in panoramic intensity images, little attention has been paid to the selection of appropriate keypoint detector-descriptor combinations. Instead, keypoints are commonly detected and described by applying well-known methods such as the Scale Invariant Feature Transform (SIFT) or Speeded-Up Robust Features (SURF). In this paper, we present a framework for evaluating the influence of different keypoint detector-descriptor combinations on the results of point cloud registration. For this purpose, we involve five different approaches for extracting local features from the panoramic intensity images and exploit the range information of putative feature correspondences in order to define bearing vectors which, in turn, may be exploited to transfer the task of point cloud registration from the object space to the observation space. With an extensive evaluation of our framework on a standard benchmark TLS dataset, we clearly demonstrate that replacing SIFT and SURF detectors and descriptors by more recent approaches significantly alleviates point cloud registration in terms of accuracy, efficiency and robustness.

  19. Application of BI-RADS Descriptors in Contrast-Enhanced Dual-Energy Mammography: Comparison with MRI.

    Science.gov (United States)

    Knogler, Thomas; Homolka, Peter; Hoernig, Mathias; Leithner, Robert; Langs, Georg; Waitzbauer, Martin; Pinker, Katja; Leitner, Sabine; Helbich, Thomas H

    2017-09-01

    Contrast-enhanced (CE) magnetic resonance imaging (MRI) BI-RADS descriptors are used in the evaluation of contrast-enhanced dual-energy mammography (CEDEM) images of mass lesions and are assumed to be applicable. Patients with suspicious mass lesions on mammography (BI-RADS 4 or 5) were included. CEDEM examinations were performed using a modified prototype unit. CE-MRI was performed using a high temporal and high spatial resolution imaging protocol. 2 blinded breast radiologists evaluated all images using criteria related to contrast enhancement intensity and morphology according to the BI-RADS lexicon (5th edition) in 2 sessions. Histopathology was used as the standard of reference. 11 patients with 5 benign and 6 malignant index lesions were included. Enhancement characteristics were similar in the malignant cases. Enhancement of the benign lesions was moderate on CEDEM and strong on MRI. Discrepancies in the BI-RADS descriptors did not influence the final BI-RADS score. Overall, the BI-RADS assessment was almost identical in all cases. 1 malignant lesion was rated BI-RADS 4 with CEDEM and BI-RADS 5 with MRI, and 1 benign was rated BI-RADS 2 and BI-RADS 1, respectively. MRI BI-RADS descriptors of contrast-enhancing lesions can be applied for the morphologic analysis of mass lesions on CEDEM.

  20. Use of BI-RADS-MRI descriptors for differentiation between mucinous carcinoma and fibroadenoma.

    Science.gov (United States)

    Igarashi, Takao; Ashida, Hirokazu; Morikawa, Kazuhiko; Motohashi, Kenji; Fukuda, Kunihiko

    2016-06-01

    We evaluated the latest breast imaging reporting and data system (BI-RADS) magnetic resonance imaging (MRI) (5th edition) descriptors and non BI-RADS MRI factors that contribute to differentiation between mucinous carcinomas (MCs) and fibroadenomas (FAs). This retrospective study included 27 patients with P-MCs or M-MCs similar to P-MCs and 22 patients with FAs who underwent breast MRI between October 2008 and July 2014 at our institution. Definitive histopathological diagnoses were made for all of the MCs and FAs. The latest BI-RADS MRI descriptors for abnormal enhancement, including maximum diameter, shape (irregular or round/oval), margin (irregular or circumscribed), rim enhancement (present or absent), dark internal septation (absent or present), delayed internal enhancement (heterogeneous or homogeneous), and the time-intensity curve pattern (not persistent or persistent) were evaluated. As additional non BI-RADS MRI factors related to differentiation between MC and FA, age, signal intensity in the T2-weighted image (high or not high), extent of lobulation (strong or weak), enhancing internal septation (present or absent), and the apparent diffusion coefficient value were also evaluated. One radiologist retrospectively evaluated interpreted MR findings and analyzed the findings. Statistically significant findings were identified through univariate and multivariate analyses. Then, three blinded radiologists reviewed the MR images where MR findings had shown a significant association with outcomes during univariate analyses. Independently, the three blinded readers reviewed the MR images for the evaluation of inter-observer variability, and then arrived at a consensus for the evaluation of observer performance. Observer performance and inter-observer variability were determined via a receiver-operating-characteristic curve analysis and weighted k statistics. The sensitivity, specificity, and accuracy of each of the MR findings were calculated. Univariate

  1. A Monte Carlo study of macroscopic and microscopic dose descriptors for kilovoltage cellular dosimetry

    Science.gov (United States)

    Oliver, P. A. K.; Thomson, Rowan M.

    2017-02-01

    This work investigates how doses to cellular targets depend on cell morphology, as well as relations between cellular doses and doses to bulk tissues and water. Multicellular models of five healthy and cancerous soft tissues are developed based on typical values of cell compartment sizes, elemental compositions and number densities found in the literature. Cells are modelled as two concentric spheres with nucleus and cytoplasm compartments. Monte Carlo simulations are used to calculate the absorbed dose to the nucleus and cytoplasm for incident photon energies of 20-370 keV, relevant for brachytherapy, diagnostic radiology, and out-of-field radiation in higher-energy external beam radiotherapy. Simulations involving cell clusters, single cells and single nuclear cavities are carried out for cell radii between 5 and 10~μ m, and nuclear radii between 2 and 9~μ m. Seven nucleus and cytoplasm elemental compositions representative of animal cells are considered. The presence of a cytoplasm, extracellular matrix and surrounding cells can affect the nuclear dose by up to 13 % . Differences in cell and nucleus size can affect dose to the nucleus (cytoplasm) of the central cell in a cluster of 13 cells by up to 13 % (8 % ). Furthermore, the results of this study demonstrate that neither water nor bulk tissue are reliable substitutes for subcellular targets for incident photon energies  <50 keV: nuclear (cytoplasm) doses differ from dose-to-medium by up to 32 % (18 % ), and from dose-to-water by up to 21 % (8 % ). The largest differences between dose descriptors are seen for the lowest incident photon energies; differences are less than 3 % for energies ≥slant 90 keV. The sensitivity of results with regard to the parameters of the microscopic tissue structure model and cell model geometry, and the importance of the nucleus and cytoplasm as targets for radiation-induced cell death emphasize the importance of accurate models for cellular dosimetry studies.

  2. Indices, multispecies and synthesis descriptors in benthic assessments: Intertidal organic enrichment from oyster farming

    Science.gov (United States)

    Quintino, Victor; Azevedo, Ana; Magalhães, Luísa; Sampaio, Leandro; Freitas, Rosa; Rodrigues, Ana Maria; Elliott, Michael

    2012-09-01

    Intertidal off-bottom oyster culture is shown to cause organic enrichment of the shore and although there are two stressors of interest (the presence of a structure, the trestles, and also the sediment and organic waste from the oysters), these can be separated and their relative impacts determined using an appropriate nested experimental design and data treatments. Although no artificial food sources are involved, the oysters feeding activity and intensity of culture enhances biodeposition and significantly increases the sediment fines content and total organic matter. This in general impoverished the benthic community in culture areas rather than a species succession with the installation of opportunists or a resulting increase in the abundance and biomass of benthic species; the findings can be a direct consequence of the intertidal situation which is less-amenable recruitment of species more common to the subtidal environment. Thus the most appropriate biological descriptors to diagnose the effects associated with the organic enrichment were the multispecies abundance data as well as the primary biological variables species richness and abundance. The effects were however spatially and statistically significantly confined to the area located directly underneath the culture bags compared to the corridors located between the trestles, which do not show such enrichment effects. Synthesis biotic indices were much less effective to diagnose the benthic alterations associated with this organic enrichment. These results show that special attention must be paid when using indices in areas where the organic enrichment induces an impoverishment of the benthic community but not necessarily a species replacement with the installation of opportunists.

  3. Relationships between age and microarchitectural descriptors of iliac trabecular bone determined by microCT.

    Science.gov (United States)

    Deguette, C; Ramond-Roquin, A; Rougé-Maillart, C

    2017-06-01

    Estimation of age at death is a major issue in anthropology. The main anthropological histological methods propose studying the architecture of cortical bone. In bone histomorphometry, researches on metabolic bone diseases have provided normative tables for trabecular bone volume (BV/TV) according to age and gender of individuals on trans-iliac bone biopsies. We have used microCT, a non-destructive tool for measuring bone volume and trabecular descriptors to compare the French tables to a series of forensic anthropological population and if the two iliac bones could be used interchangeably. Coxal bone of a personal forensic collection whose age and gender were known (DNA identification) were used. Bone samples, centered on the same area than bone biopsy. MicroCT (pixel size: 36μm) was used to measure BV/TV and morphometric trabecular parameters of microarchitecture. An adjusted Z-score was calculated for BV/TV to compare with normative tables and a right/left comparison of trabecular parameters was provided. Twenty-seven iliac bones, which 20 forming 10 complete pelvises, aged between 24 and 73y.o. (average of 47.7 y.o.) were used. All adjusted Z-score were within normal values. There was a strong positive correlation between right and left sides for Tb.Th, Tb.N and Tb.Sp, but an insignificant correlation was obtained for BV/TV. Normative tables between age and BV/TV are valid and therefore usable in anthropology. They may represent an alternative to determine the age at death. Nevertheless, it requires a precise technique that could be a drawback in current practice. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  4. 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.

  5. Longitudinal analysis of serum oxylipin profile as a novel descriptor of the inflammatory response to surgery.

    Science.gov (United States)

    Wolfer, Arnaud M; Scott, Alasdair J; Rueb, Claudia; Gaudin, Mathieu; Darzi, Ara; Nicholson, Jeremy K; Holmes, Elaine; Kinross, James M

    2017-04-26

    reduced concentrations of anti-thrombotic mediators (9-HODE and 13-HODE) with increased concentration of their pro-thrombotic counterpart (TxB2). Serum oxylipin profile is modified by surgical intervention and may even be sensitive to the degree of surgical trauma and therefore represents a novel descriptor of the surgical systemic inflammatory response.

  6. Modeling clustered activity increase in amyloid-beta positron emission tomographic images with statistical descriptors

    Directory of Open Access Journals (Sweden)

    Shokouhi S

    2015-04-01

    correlated with the increase in mean SUVR but showed lower variance. The whole brain results showed a higher inverse correlation between the cerebrospinal Aβ and wS2 than between the cerebrospinal Aβ and SUVR mean/median. We did not observe any confounding of wS2 by region size or injected dose.Conclusion: The wS2 detects subtle changes and provides additional information about the binding characteristics of radiotracers and Aβ accumulation that are difficult to verify with mean SUVR alone.Keywords: amyloid-beta plaques, positron emission tomography, 11C-Pittsburgh compound B, statistical descriptors, two-point correlation function

  7. Concordance of computer-extracted image features with BI-RADS descriptors for mammographic mass margin

    Science.gov (United States)

    Sahiner, Berkman; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Paramagul, Chintana; Nees, Alexis; Helvie, Mark; Shi, Jiazheng

    2008-03-01

    values for the spiculation and the circumscribed margin features were 0.96+/-0.04 and 0.87+/-0.04, respectively. We conclude that the newly developed features had high accuracy for characterizing mass margins according to BI-RADS descriptors.

  8. Effect of the image resolution on the statistical descriptors of heterogeneous media

    Science.gov (United States)

    Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

    2018-02-01

    The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost

  9. Molecular vibration-activity relationship in the agonism of adenosine receptors.

    Science.gov (United States)

    Chee, Hyun Keun; Oh, S June

    2013-12-01

    The molecular vibration-activity relationship in the receptor-ligand interaction of adenosine receptors was investigated by structure similarity, molecular vibration, and hierarchical clustering in a dataset of 46 ligands of adenosine receptors. The resulting dendrogram was compared with those of another kind of fingerprint or descriptor. The dendrogram result produced by corralled intensity of molecular vibrational frequency outperformed four other analyses in the current study of adenosine receptor agonism and antagonism. The tree that was produced by clustering analysis of molecular vibration patterns showed its potential for the functional classification of adenosine receptor ligands.

  10. Molecular Vibration-Activity Relationship in the Agonism of Adenosine Receptors

    Directory of Open Access Journals (Sweden)

    Hyun Keun Chee

    2013-12-01

    Full Text Available The molecular vibration-activity relationship in the receptor-ligand interaction of adenosine receptors was investigated by structure similarity, molecular vibration, and hierarchical clustering in a dataset of 46 ligands of adenosine receptors. The resulting dendrogram was compared with those of another kind of fingerprint or descriptor. The dendrogram result produced by corralled intensity of molecular vibrational frequency outperformed four other analyses in the current study of adenosine receptor agonism and antagonism. The tree that was produced by clustering analysis of molecular vibration patterns showed its potential for the functional classification of adenosine receptor ligands.

  11. Evaluating frontier orbital energy and HOMO/LUMO gap with descriptors from density functional reactivity theory.

    Science.gov (United States)

    Huang, Ying; Rong, Chunying; Zhang, Ruiqin; Liu, Shubin

    2017-01-01

    Wave function theory (WFT) and density functional theory (DFT)-the two most popular solutions to electronic structure problems of atoms and molecules-share the same origin, dealing with the same subject yet using distinct methodologies. For example, molecular orbitals are artifacts in WFT, whereas in DFT, electron density plays the dominant role. One question that needs to be addressed when using these approaches to appreciate properties related to molecular structure and reactivity is if there is any link between the two. In this work, we present a piece of strong evidence addressing that very question. Using five polymeric systems as illustrative examples, we reveal that using quantities from DFT such as Shannon entropy, Fisher information, Ghosh-Berkowitz-Parr entropy, Onicescu information energy, Rényi entropy, etc., one is able to accurately evaluate orbital-related properties in WFT like frontier orbital energies and the HOMO (highest occupied molecular orbital)/LUMO (lowest unoccupied molecular orbital) gap. We verified these results at both the whole molecule level and the atoms-in-molecules level. These results provide compelling evidence suggesting that WFT and DFT are complementary to each other, both trying to comprehend the same properties of the electronic structure and molecular reactivity from different perspectives using their own characteristic vocabulary. Hence, there should be a bridge or bridges between the two approaches.

  12. Spectroscopic descriptors for dynamic changes of soluble microbial products from activated sludge at different biomass growth phases under prolonged starvation.

    Science.gov (United States)

    Maqbool, Tahir; Cho, Jinwoo; Hur, Jin

    2017-10-15

    In this study, the spectroscopic indices of soluble microbial products (SMP) were explored using absorption and fluorescence spectroscopy to identify different distinctive biomass growth phases (i.e., exponential phase, pseudo-endogenous phase, and endogenous phase) and to describe the microbial activity of activated sludge in a batch type bioreactor under prolonged starvation. The optical descriptors, including UV absorption at 254 nm (UVA254), spectral slope, absorbance slope index (ASI), biological index (BIX), humification index (HIX), and the ratio of tryptophan-like to humic-like components (C1/C2), were examined to describe the dynamic changes in SMP. These indices were mostly associated with dissolved organic carbon (DOC) of SMPs and specific oxygen uptake rate (SOUR). Among those, ASI was the most strongly correlated with the SOUR data for the pseudo-endogenous and the endogenous periods. Although the three microbial phases were well discriminated using the spectral slope, BIX, and the C1/C2 ratio, the C1/C2 ratio can be suggested as the most preferable indicator as it can also trace the changes of the relative abundance of proteins to humic-like substances in SMPs. The suggested spectroscopic descriptors were reasonably explained by the general trends of decreased large-sized biopolymer fractions (e.g., proteins) and increased humic substrates (HS) with starvation time, which were detected by size exclusion chromatography. This study provides a novel insight into the strong potential of using optical descriptors to easily probe microbial status in biological treatment systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. 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

  14. Inverse least-squares modeling of vapor descriptors using polymer-coated surface acoustic wave sensor array responses.

    Science.gov (United States)

    Grate, J W; Patrash, S J; Kaganovet, S N; Abraham, M H; Wise, B M; Gallagher, N B

    2001-11-01

    In previous work, it was shown that, in principle, vapor descriptors could be derived from the responses of an array of polymer-coated acoustic wave devices. This new chemometric classification approach was based on polymer/vapor interactions following the well-established linear solvation energy relationships (LSERs) and the surface acoustic wave (SAW) transducers being mass sensitive. Mathematical derivations were included and were supported by simulations. In this work, an experimental data set of polymer-coated SAW vapor sensors is investigated. The data set includes 20 diverse polymers tested against 18 diverse organic vapors. It is shown that interfacial adsorption can influence the response behavior of sensors with nonpolar polymers in response to hydrogen-bonding vapors; however, in general, most sensor responses are related to vapor interactions with the polymers. It is also shown that polymer-coated SAW sensor responses can be empirically modeled with LSERs, deriving an LSER for each individual sensor based on its responses to the 18 vapors. Inverse least-squares methods are used to develop models that correlate and predict vapor descriptors from sensor array responses. Successful correlations can be developed by multiple linear regression (MLR), principal components regression (PCR), and partial least-squares (PLS) regression. MLR yields the best fits to the training data, however cross-validation shows that prediction of vapor descriptors for vapors not in the training set is significantly more successful using PCR or PLS. In addition, the optimal dimension of the PCR and PLS models supports the dimensionality of the LSER formulation and SAW response models.

  15. Suspicious breast calcifications undergoing stereotactic biopsy in women ages 70 and over: Breast cancer incidence by BI-RADS descriptors.

    Science.gov (United States)

    Grimm, Lars J; Johnson, David Y; Johnson, Karen S; Baker, Jay A; Soo, Mary Scott; Hwang, E Shelley; Ghate, Sujata V

    2017-06-01

    To determine the malignancy rate overall and for specific BI-RADS descriptors in women ≥70 years who undergo stereotactic biopsy for calcifications. We retrospectively reviewed 14,577 consecutive mammogram reports in 6839 women ≥70 years to collect 231 stereotactic biopsies of calcifications in 215 women. Cases with missing images or histopathology and calcifications associated with masses, distortion, or asymmetries were excluded. Three breast radiologists determined BI-RADS descriptors by majority. Histology, hormone receptor status, and lymph node status were correlated with BI-RADS descriptors. There were 131 (57 %) benign, 22 (10 %) atypia/lobular carcinomas in situ, 55 (24 %) ductal carcinomas in situ (DCIS), and 23 (10 %) invasive diagnoses. Twenty-seven (51 %) DCIS cases were high-grade. Five (22 %) invasive cases were high-grade, two (9 %) were triple-negative, and three (12 %) were node-positive. Malignancy was found in 49 % (50/103) of fine pleomorphic, 50 % (14/28) of fine linear, 25 % (10/40) of amorphous, 20 % (3/15) of round, 3 % (1/36) of coarse heterogeneous, and 0 % (0/9) of dystrophic calcifications. Among women ≥70 years that underwent stereotactic biopsy for calcifications only, we observed a high rate of malignancy. Additionally, coarse heterogeneous calcifications may warrant a probable benign designation. • Cancer rates of biopsied calcifications in women ≥70 years are high • Radiologists should not dismiss suspicious calcifications in older women • Coarse heterogeneous calcifications may warrant a probable benign designation.

  16. 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.

  17. 2D-Qsar for 450 types of amino acid induction peptides with a novel substructure pair descriptor having wider scope

    Directory of Open Access Journals (Sweden)

    Osoda Tsutomu

    2011-11-01

    Full Text Available Abstract Background Quantitative structure-activity relationships (QSAR analysis of peptides is helpful for designing various types of drugs such as kinase inhibitor or antigen. Capturing various properties of peptides is essential for analyzing two-dimensional QSAR. A descriptor of peptides is an important element for capturing properties. The atom pair holographic (APH code is designed for the description of peptides and it represents peptides as the combination of thirty-six types of key atoms and their intermediate binding between two key atoms. Results The substructure pair descriptor (SPAD represents peptides as the combination of forty-nine types of key substructures and the sequence of amino acid residues between two substructures. The size of the key substructures is larger and the length of the sequence is longer than traditional descriptors. Similarity searches on C5a inhibitor data set and kinase inhibitor data set showed that order of inhibitors become three times higher by representing peptides with SPAD, respectively. Comparing scope of each descriptor shows that SPAD captures different properties from APH. Conclusion QSAR/QSPR for peptides is helpful for designing various types of drugs such as kinase inhibitor and antigen. SPAD is a novel and powerful descriptor for various types of peptides. Accuracy of QSAR/QSPR becomes higher by describing peptides with SPAD.

  18. 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 < 0.001, heterogeneous and clumped vs clustered ring, p = 0.003) and distribution (focal and linear vs segmental, p < 0.001) were the significant explanatory variables. The descriptors were classified into three grades of suspicion, and the categorization (3, 4A, 4B, 4C, and 5) by sum-up grades showed an incremental increase in the probability of malignancy (p < 0.0001). The three-grade criteria and categorization by sum-up grades of descriptors appear valid for non-mass enhancement.

  19. Fusion of iECO image descriptors for buried explosive hazard detection in forward-looking infrared imagery

    Science.gov (United States)

    Price, Stanton R.; Anderson, Derek T.; Havens, Timothy C.

    2015-05-01

    Data fusion is a powerful theory that often leads to significant performance gain and/or improved robustness of a given solution. In this article, we explore how fusion can be used to advance our previously established improved Evolutionary COnstructed (iECO) image descriptor framework. The goal of iECO is to learn a diverse set of individuals (variable length chromosome in a genetic algorithm). Each iECO individual encodes a unique composition of different low-level image transformations in the context of a high-level image descriptor. Herein, we investigate multiple kernel (MK) aggregation and MK learning (MKL) for "feature-level" fusion of iECO chromosomes. Specifically, we explore MKL group lasso (MKLGL) and we put forth a new way to directly assign kernel weights from a measure defined on the kernel matrices. The proposed work is presented in the context of buried explosive hazard detection (EHD) in forward looking (FL) imagery. Experiments are reported using receiver operating characteristic (ROC) curves on data from a U.S. Army test site that contains multiple target and clutter types, burial depths and times of day. We demonstrate that MK support vector machine (MKSVM) classification outperform single kernel SVM (SKSVM) classification and our weight assignment procedure generalizes well and outperforms MKLGL for EHD in FLIR.

  20. Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition.

    Science.gov (United States)

    Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

    2014-11-07

    Successful protein structure identification enables researchers to estimate the biological functions of proteins, yet it remains a challenging problem. The most common method for determining an unknown protein's structural class is to perform expensive and time-consuming manual experiments. Because of the availability of amino acid sequences generated in the post-genomic age, it is possible to predict an unknown protein's structural class using machine learning methods given a protein's amino-acid sequence and/or its secondary structural elements. Following recent research in this area, we propose a new machine learning system that is based on combining several protein descriptors extracted from different protein representations, such as position specific scoring matrix (PSSM), the amino-acid sequence, and secondary structural sequences. The prediction engine of our system is operated by an ensemble of support vector machines (SVMs), where each SVM is trained on a different descriptor. The results of each SVM are combined by sum rule. Our final ensemble produces a success rate that is substantially better than previously reported results on three well-established datasets. The MATLAB code and datasets used in our experiments are freely available for future comparison at http://www.dei.unipd.it/node/2357. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Red wine produced from the Isabella and Ives cultivar (Vitis Labrusca: profile of volatiles and aroma descriptors

    Directory of Open Access Journals (Sweden)

    Narciza Maria de Oliveira ARCANJO

    2018-03-01

    Full Text Available Abstract Considering the potential consumption and economic the importance that Isabella and Ives wines represent in the Brazilian consumer market as well as the scarcity of scientific data examining their quality, the objective of this study was to investigate the sensory quality and the volatiles profile of these wines. The volatile compounds were extracted by headspace solid-phase microextraction (HS-SPME and a total of 54 compounds were detected in red wine samples including esters (23, terpenes (12, alcohols (10, aldehydes and ketones (5 and amines (1 as well as 3 compounds belonging to other classes. Isabella and Ives red wines were sensorially characterized by 14 descriptors, through quantitative descriptive analysis (QDA. The PCAs fruity descriptors were the primary contributors to the aroma profile of the analyzed wines due to the presence of ethyl acetate and esters, especially in the wine coded as QM, which exhibited the highest variety of compounds. The differences observed in the principal components analysis, might have been influenced by the grape composition of each wine. Although the wines were from the same region, each came from a different winery and was subject to unique production processes.

  2. Application of a methodology for categorizing and differentiating urban soundscapes using acoustical descriptors and semantic-differential attributes.

    Science.gov (United States)

    Torija, Antonio J; Ruiz, Diego P; Ramos-Ridao, A F

    2013-07-01

    A subjective and physical categorization of an ambient sound is the first step to evaluate the soundscape and provides a basis for designing or adapting this ambient sound to match people's expectations. For this reason, the main goal of this work is to develop a categorization and differentiation analysis of soundscapes on the basis of acoustical and perceptual variables. A hierarchical cluster analysis, using 15 semantic-differential attributes and acoustical descriptors to include an equivalent sound-pressure level, maximum-minimum sound-pressure level, impulsiveness of the sound-pressure level, sound-pressure level time course, and spectral composition, was conducted to classify soundscapes into different typologies. This analysis identified 15 different soundscape typologies. Furthermore, based on a discriminant analysis the acoustical descriptors, the crest factor (impulsiveness of the sound-pressure level), and the sound level at 125 Hz were found to be the acoustical variables with the highest impact in the differentiation of the recognized types of soundscapes. Finally, to determine how the different soundscape typologies differed from each other, both subjectively and acoustically, a study was performed.

  3. Computational study of AuSi{sub n} (n=1-9) nanoalloy clusters invoking DFT based descriptors

    Energy Technology Data Exchange (ETDEWEB)

    Ranjan, Prabhat; Kumar, Ajay [Department of Mechatronics, Manipal University Jaipur Dehmi Kalan, Jaipur-303007 (India); Chakraborty, Tanmoy, E-mail: tanmoy.chakraborty@jaipur.manipal.edu, E-mail: tanmoychem@gmail.com [Department of Chemistry, Manipal University Jaipur Dehmi Kalan, Jaipur-303007 (India)

    2016-04-13

    Nanoalloy clusters formed between Au and Si are topics of great interest today from both scientific and technological point of view. Due to its remarkable catalytic, electronic, mechanical and magnetic properties Au-Si nanoalloy clusters have extensive applications in the field of microelectronics, catalysis, biomedicine, and jewelry industry. Density Functional Theory (DFT) is a new paradigm of quantum mechanics, which is very much popular to study the electronic properties of materials. Conceptual DFT based descriptors have been invoked to correlate the experimental properties of nanoalloy clusters. In this venture, we have systematically investigated AuSi{sub n} (n=1-9) nanoalloy clusters in the theoretical frame of the B3LYP exchange correlation. The experimental properties of AuSi{sub n} (n=1-9) nanoalloy clusters are correlated in terms of DFT based descriptors viz. HOMO-LUMO gap, Electronegativity (χ), Global Hardness (η), Global Softness (S) and Electrophilicity Index (ω). The calculated HOMO-LUMO gap exhibits interesting odd-even alteration behaviour, indicating that even numbered clusters possess higher stability as compare to their neighbour odd numbered clusters. This study also reflects a very well agreement between experimental bond length and computed data.

  4. Predictive performance of BI-RADS magnetic resonance imaging descriptors in the context of suspicious (category 4) findings.

    Science.gov (United States)

    de Almeida, João Ricardo Maltez; Gomes, André Boechat; Barros, Thomas Pitangueiras; Fahel, Paulo Eduardo; Rocha, Mário de Seixas

    2016-01-01

    To determine the positive predictive value (PPV) and likelihood ratio for magnetic resonance imaging (MRI) characteristics of category 4 lesions, as described in the Breast Imaging Reporting and Data System (BI-RADS(®)) lexicon, as well as to test the predictive performance of the descriptors using multivariate analysis and the area under the curve derived from a receiver operating characteristic (ROC) curve. This was a double-blind review study of 121 suspicious findings from 98 women examined between 2009 and 2013. The terminology was based on the 2013 edition of the BI-RADS. Of the 121 suspicious findings, 53 (43.8%) were proven to be malignant lesions, with no significant difference between mass and non-mass enhancement (p = 0.846). The PPVs were highest for masses with a spiculated margin (71%) and round shape (63%), whereas segmental distribution achieved a high PPV (80%) for non-mass enhancement. Kinetic analyses performed poorly, except for type 3 curves applied to masses (PPV of 73%). Logistic regression models were significant for both patterns, although the results were better for masses, particularly when kinetic assessments were included (p = 0.015; pseudo R(2) = 0.48; area under the curve = 90%). Some BI-RADS MRI descriptors have high PPV and good predictive performance-as demonstrated by ROC curve and multivariate analysis-when applied to BI-RADS category 4 findings. This may allow future stratification of this category.

  5. A theoretical analysis of bi-metallic (Cu–Agn = 1 − 7 nano alloy clusters invoking DFT based descriptors

    Directory of Open Access Journals (Sweden)

    Ranjan Prabhat

    2015-12-01

    Full Text Available Due to its large scale applications in the real field, the study of bi-metallic nano-alloy clusters is an active field of research. Though a number of experimental reports are available in this domain, a deep theoretical insight is yet to receive. Among several nano-clusters, the compound formed between Cu–Ag has gained a large importance due to its remarkable optical property. Density Functional Theory (DFT is one of the most popular approaches of quantum mechanics to study the electronic properties of materials. Conceptually, DFT based descriptors have turned to be indispensable tools for analyzing and correlating the experimental properties of compounds. In this venture, we have analyzed the experimental properties of the (Cu–Agn = 1 − 7 nano-alloy clusters invoking DFT methodology. A nice correlation has been found between optical properties of the aforesaid nano-clusters with our evaluated theoretical descriptors. The similar agreement between experimental bond length and computed data is also reflected in this analysis. Beside these, the effect of even-odd alternation behavior of nano compounds on the HOMO-LUMO gap is very important in our computation. It is probably the first attempt to establish such type of correlation.

  6. Predictive performance of BI-RADS magnetic resonance imaging descriptors in the context of suspicious (category 4 findings

    Directory of Open Access Journals (Sweden)

    João Ricardo Maltez de Almeida

    2016-06-01

    Full Text Available Abstract Objective: To determine the positive predictive value (PPV and likelihood ratio for magnetic resonance imaging (MRI characteristics of category 4 lesions, as described in the Breast Imaging Reporting and Data System (BI-RADS® lexicon, as well as to test the predictive performance of the descriptors using multivariate analysis and the area under the curve derived from a receiver operating characteristic (ROC curve. Materials and Methods: This was a double-blind review study of 121 suspicious findings from 98 women examined between 2009 and 2013. The terminology was based on the 2013 edition of the BI-RADS. Results: Of the 121 suspicious findings, 53 (43.8% were proven to be malignant lesions, with no significant difference between mass and non-mass enhancement (p = 0.846. The PPVs were highest for masses with a spiculated margin (71% and round shape (63%, whereas segmental distribution achieved a high PPV (80% for non-mass enhancement. Kinetic analyses performed poorly, except for type 3 curves applied to masses (PPV of 73%. Logistic regression models were significant for both patterns, although the results were better for masses, particularly when kinetic assessments were included (p = 0.015; pseudo R2 = 0.48; area under the curve = 90%. Conclusion: Some BI-RADS MRI descriptors have high PPV and good predictive performance-as demonstrated by ROC curve and multivariate analysis-when applied to BI-RADS category 4 findings. This may allow future stratification of this category.

  7. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Fowler, E. E.; Sellers, T. A.; Lu, B. [Department of Cancer Epidemiology, Division of Population Sciences, H. Lee Moffitt Cancer Center, Tampa, Florida 33612 (United States); Heine, J. J. [Department of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center, Tampa, Florida 33612 (United States)

    2013-11-15

    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{sub pg} measure. Two previously validated measures of breast density derived from calibrated and raw mammograms were converted to the new BR{sub vc} and BR{sub 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{sub pg}; (b) OR = 1.93 (1.36, 2.74) for BR{sub vc}; and (c) OR = 1.37 (1.05, 1.80) for BR{sub vr}. The measures generated by method-2 had κ between 0.42–0.45. Two of these

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

    Science.gov (United States)

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

    2013-11-01

    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. 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. 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 associated with breast cancer

  10. Detection of duplicates among repatriated Nordic spring barley (Hordeum vulgare L. s.l.) accessions using agronomic and morphological descriptors and microsatellite markers

    DEFF Research Database (Denmark)

    Lund, Birgitte; Ortiz, Rodomiro; von Bothmer, Roland

    2013-01-01

    Duplicate accessions in gene banks may be increasing while funding resources to maintain them are not always available. This research investigated the ability of agronomic and morphological descriptors for detecting duplicates among 138 repatriated putative Nordic barley germplasm and compared...... their use with results from previous research with microsatellite markers. These accessions were initially grouped into 36 potential duplicates according to passport data but further analysis with microsatellites reduce them to 22 genetically homogeneous groups. The analysis with 26 agronomic...... and morphological descriptors of putative Nordic spring barley accessions from nine gene banks was compared with a previous study with microsatellites. Each agronomic and morphological descriptor was weighed relative to its genetic determination with the aim of reducing the effect of environmental errors on genetic...

  11. Assessment of the relationship between the molecular properties of calcium channel blockers and plasma protein binding data

    Directory of Open Access Journals (Sweden)

    Odović Jadranka V.

    2017-01-01

    Full Text Available In this study we investigated the relationship between the calcium channel blockers (CCBs, amlodipine, felodipine, isradipine, nicardipine, nifedipine, nimodipine, nisoldipine, verapamil and diltiazem, and their calculated molecular descriptors: polar surface area (PSA, molecular weight (Mw, volume value (Vol, aqueous solubility data (logS, lipophilicity (logP, acidity (pKa values and plasma protein binding (PPB data, obtained from relevant literature. The relationships between the computed molecular properties of selected CCBs and their PPB data were investigated by simple linear regression analysis that revealed very low correlations (R2<0.35. When multiple linear regression (MLR analysis was applied to investigate reliable correlations between the CCBs’ calculated molecular descriptors and PPB data, the best correlations were found for the relationships between CCBs, and PPB data and lipophilicity, and with application of the molecular descriptor (Mw, Vol, or pKa data as additional independent variables (R2=0.623; R2=0.741; R2=0.657, respectively, with an acceptable probability value (P<0.05, confirming that lipophilicity, together with other molecular properties, are essential for the drugs’ PPB. We conclude that this could be considered as an additional in vitro approach for modeling CCBs. [Projekat Ministarstva nauke Republike Srbije, br. TR34031

  12. Diagnostic performance and reproducibility of T2w based and diffusion weighted imaging (DWI) based PI-RADSv2 lexicon descriptors for prostate MRI.

    Science.gov (United States)

    Benndorf, Matthias; Hahn, Felix; Krönig, Malte; Jilg, Cordula Annette; Krauss, Tobias; Langer, Mathias; Dovi-Akué, Philippe

    2017-08-01

    To examine the diagnostic performance of PI-RADSv2 T2w and diffusion weighted imaging (DWI) based lexicon descriptors, inter-observer agreement for descriptor assignment and diagnostic accuracy of the PI-RADSv2 assessment categories for multiparametric prostate MRI. 176 lesions in 79 consecutive patients are analyzed, lesions are histopathologically verified by MRI-ultrasound fusion biopsy. All lesions are rated according to the PI-RADSv2 lexicon, descriptors for T2w and DWI sequences and resulting assessment categories are assigned by two independent blinded radiologists. We perform receiver-operating-characteristic analysis using the assessment categories. To analyze inter-observer agreement, we calculate weighted kappa values for assessment category assignment and unweighted kappa values for descriptor assignment. PI-RADSv2 assessment categories yield an area under the curve of 0.76/0.74 (radiologist 1/radiologist 2), P >0.05. Weighted kappa for agreement is 0.601 in the peripheral zone and 0.580 in the transition zone. We detect a difference in the cancer rate for PI-RADSv2 category 3 between peripheral zone (32%) and transition zone (12%), P PI-RADSv2 lexicon is at most moderate in our study. Typical descriptors for benign and malignant lesions are validated, whereas the discriminatory power of some descriptors is challenged. The difference in the cancer rate for PI-RADSv2 category 3 between peripheral zone and transition zone should be considered when management recommendations are linked to assessment categories in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. SU-E-T-581: On the Value of LET as a Radiation Quality Descriptor for RBE

    Energy Technology Data Exchange (ETDEWEB)

    Pater, P; Backstrom, G; Enger, S; Seuntjens, J; Naqa, I El [McGill University, Montreal, Quebec (Canada); Villegas, F; Ahnesjo, A [Uppsala University, Uppsala (Sweden)

    2015-06-15

    Purpose: To investigate the relationship between linear energy transfer (LET) and relative biological effectiveness (RBE) for protons and light ions, and the corresponding role of LET as a descriptor of radiation quality of hadron therapy. Methods: Monte Carlo (MC) proton and light ion (He, Li, C) tracks with LET < 30 eV nm{sup -1} were generated in an event-by-event mode. They were overlaid on a cell nucleus model containing 6×10{sup 9} nucleotide base pairs using an isotropic irradiation procedure that provides electronic equilibrium. Strand breaks (sbs) were scored in the DNA sugar-phosphate groups and further sub-classified into single or double sbs (ssbs or dsbs). Distributions of ssbs and dsbs for 2 Gy fractions were calculated to estimate RBE for the induction of initial dsbs with reference to {sup 60}Co. Additionally, sbs were classified based on their complexity (i.e. the number of sbs in each cluster). Results: An increase in LET for light ions of the same atomic number or a decrease in atomic number for ions of the same LET resulted in a lower kinetic energy of emitted secondary electrons. The clustering of DNA damage was more pronounced as reflected by the increase in proton RBE from ∼ 1.75 to 4 for LET values of 7 to 28 eV nm{sup -1}. A significant RBE decrease between protons, He, Li and C ions of the same LET was also noticed as function of the atomic number. Significant differences in ssbs and dsbs complexities were also seen for particles with the same LET, potentially supporting a clustering-based radiation quality descriptor. Conclusion: The LET-RBE relationships were simulated for proton and light ions and exhibited expected trends, including different RBEs for particles with the same LET but different atomic numbers. A complexity based radiation quality descriptor may allow better differentiation of RBE between radiation fields of similar LET. We would like to acknowledge support from the Fonds de recherche du Quebec Sante (FRQS), from the

  14. PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions.

    Science.gov (United States)

    Dong, Jie; Yao, Zhi-Jiang; Zhang, Lin; Luo, Feijun; Lin, Qinlu; Lu, Ai-Ping; Chen, Alex F; Cao, Dong-Sheng

    2018-03-20

    With the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are accumulated in chemistry and biology fields, new tools that process and interpret large and complex interaction data are increasingly important. So far, there are no suitable toolkits that can effectively link the chemical and biological space in view of molecular representation. To further explore these complex data, an integrated toolkit for various molecular representation is urgently needed which could be easily integrated with data mining algorithms to start a full data analysis pipeline. Herein, the python library PyBioMed is presented, which comprises functionalities for online download for various molecular objects by providing different IDs, the pretreatment of molecular structures, the computation of various molecular descriptors for chemicals, proteins, DNAs and their interactions. PyBioMed is a feature-rich and highly customized python library used for the characterization of various complex chemical and biological molecules and interaction samples. The current version of PyBioMed could calculate 775 chemical descriptors and 19 kinds of chemical fingerprints, 9920 protein descriptors based on protein sequences, more than 6000 DNA descriptors from nucleotide sequences, and interaction descriptors from pairwise samples using three different combining strategies. Several examples and five real-life applications were provided to clearly guide the users how to use PyBioMed as an integral part of data analysis projects. By using PyBioMed, users are able to start a full pipelining from getting molecular data, pretreating molecules, molecular representation to constructing machine learning models conveniently. PyBioMed provides

  15. Magnetismo Molecular (Molecular Magentism)

    Energy Technology Data Exchange (ETDEWEB)

    Reis, Mario S [Universidade Federal Fluminense, Brasil; Moreira Dos Santos, Antonio F [ORNL

    2010-07-01

    The new synthesis processes in chemistry open a new world of research, new and surprising materials never before found in nature can now be synthesized and, as a wonderful result, observed a series of physical phenomena never before imagined. Among these are many new materials the molecular magnets, the subject of this book and magnetic properties that are often reflections of the quantum behavior of these materials. Aside from the wonderful experience of exploring something new, the theoretical models that describe the behavior these magnetic materials are, in most cases, soluble analytically, which allows us to know in detail the physical mechanisms governing these materials. Still, the academic interest in parallel this subject, these materials have a number of properties that are promising to be used in technological devices, such as in computers quantum magnetic recording, magnetocaloric effect, spintronics and many other devices. This volume will journey through the world of molecular magnets, from the structural description of these materials to state of the art research.

  16. Are Tags from Mars and Descriptors from Venus? A Study on the Ecology of Educational Resource Metadata

    Science.gov (United States)

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

    In this study, over a period of six months, we gathered empirical data from more than 200 users on a learning resource portal with a social bookmarking and tagging feature. Our aim was to study the interrelation of conventional metadata and social tags on the one hand, and their interaction with the environment, which can be understood as the repository, its resources and all stakeholders that included the managers, metadata indexers and the whole community of users. We found an interplay between tags and descriptors and showed how tags can enrich and add value to multilingual controlled vocabularies in various ways. We also showed that, even if many tags can be seen as redundant in terms of the existing LOM, some of them can become a useful source of metadata for repository owners, and help them better understand users’ needs and demands.

  17. Free Shape Context Descriptors Optimized with Genetic Algorithm for the Detection of Dead Tree Trunks in ALS Point Clouds

    Science.gov (United States)

    Polewski, P.; Yao, W.; Heurich, M.; Krzystek, P.; Stilla, U.

    2015-08-01

    In this paper, a new family of shape descriptors called Free Shape Contexts (FSC) is introduced to generalize the existing 3D Shape Contexts. The FSC introduces more degrees of freedom than its predecessor by allowing the level of complexity to vary between its parts. Also, each part of the FSC has an associated activity state which controls whether the part can contribute a feature value. We describe a method of evolving the FSC parameters for the purpose of creating highly discriminative features suitable for detecting specific objects in sparse point clouds. The evolutionary process is built on a genetic algorithm (GA) which optimizes the parameters with respect to cross-validated overall classification accuracy. The GA manipulates both the structure of the FSC and the activity flags, allowing it to perform an implicit feature selection alongside the structure optimization by turning off segments which do not augment the discriminative capabilities. We apply the proposed descriptor to the problem of detecting single standing dead tree trunks from ALS point clouds. The experiment, carried out on a set of 285 objects, reveals that an FSC optimized through a GA with manually tuned recombination parameters is able to attain a classification accuracy of 84.2%, yielding an increase of 4.2 pp compared to features derived from eigenvalues of the 3D covariance matrix. Also, we address the issue of automatically tuning the GA recombination metaparameters. For this purpose, a fuzzy logic controller (FLC) which dynamically adjusts the magnitude of the recombination effects is co-evolved with the FSC parameters in a two-tier evolution scheme. We find that it is possible to obtain an FLC which retains the classification accuracy of the manually tuned variant, thereby limiting the need for guessing the appropriate meta-parameter values.

  18. Gravitational self-organizing map-based seismic image classification with an adaptive spectral-textural descriptor

    Science.gov (United States)

    Hao, Yanling; Sun, Genyun

    2016-10-01

    Seismic image classification is of vital importance for extracting damage information and evaluating disaster losses. With the increasing availability of high resolution remote sensing images, automatic image classification offers a unique opportunity to accommodate the rapid damage mapping requirements. However, the diversity of disaster types and the lack of uniform statistical characteristics in seismic images increase the complexity of automated image classification. This paper presents a novel automatic seismic image classification approach by integrating an adaptive spectral-textural descriptor into gravitational self-organizing map (gSOM). In this approach, seismic image is first segmented into several objects based on mean shift (MS) method. These objects are then characterized explicitly by spectral and textural feature quantization histograms. To objectify the image object delineation adapt to various disaster types, an adaptive spectral-textural descriptor is developed by integrating the histograms automatically. Subsequently, these objects as classification units are represented by neurons in a self-organizing map and clustered by adjacency gravitation. By moving the neurons around the gravitational space and merging them according to the gravitation, the object-based gSOM is able to find arbitrary shape and determine the class number automatically. Taking advantage of the diversity of gSOM results, consensus function is then conducted to discover the most suitable classification result. To confirm the validity of the presented approach, three aerial seismic images in Wenchuan covering several disaster types are utilized. The obtained quantitative and qualitative experimental results demonstrated the feasibility and accuracy of the proposed seismic image classification method.

  19. Relationship between increasing concentrations of two carcinogens and statistical image descriptors of foci morphology in the cell transformation assay.

    Science.gov (United States)

    Callegaro, Giulia; Corvi, Raffaella; Salovaara, Susan; Urani, Chiara; Stefanini, Federico M

    2017-06-01

    Cell Transformation Assays (CTAs) have long been proposed for the identification of chemical carcinogenicity potential. The endpoint of these in vitro assays is represented by the phenotypic alterations in cultured cells, which are characterized by the change from the non-transformed to the transformed phenotype. Despite the wide fields of application and the numerous advantages of CTAs, their use in regulatory toxicology has been limited in part due to concerns about the subjective nature of visual scoring, i.e. the step in which transformed colonies or foci are evaluated through morphological features. An objective evaluation of morphological features has been previously obtained through automated digital processing of foci images to extract the value of three statistical image descriptors. In this study a further potential of the CTA using BALB/c 3T3 cells is addressed by analysing the effect of increasing concentrations of two known carcinogens, benzo[a]pyrene and NiCl 2 , with different modes of action on foci morphology. The main result of our quantitative evaluation shows that the concentration of the considered carcinogens has an effect on foci morphology that is statistically significant for the mean of two among the three selected descriptors. Statistical significance also corresponds to visual relevance. The statistical analysis of variations in foci morphology due to concentration allowed to quantify morphological changes that can be visually appreciated but not precisely determined. Therefore, it has the potential of providing new quantitative parameters in CTAs, and of exploiting all the information encoded in foci. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  20. Morphometric and Molecular Analysis of the Three Arbutus Species of Greece

    OpenAIRE

    Konstantinos Fotios BERTSOUKLIS; Maria PAPAFOTIOU

    2016-01-01

    Arbutus andrachne, Arbutus unedo and Arbutus × andrachnoides found in the Greek macchia are promising species for reforestations, ornamental use, as well as for medicinal use and the food industry. Μorphological traits and molecular markers (RAPD) were used to identify and distinguish these Arbutus species to facilitate their exploitation. Since there are no descriptors established for Arbutus spp., 23 qualitative morphological characteristics of crown, foliage, bark, flowering, fruiting, and...

  1. Quantitative relationships for the prediction of the vapor pressure of some hydrocarbons from the van der Waals molecular surface

    Directory of Open Access Journals (Sweden)

    Olariu Tudor

    2015-01-01

    Full Text Available A quantitative structure - property relationship (QSPR modeling of vapor pressure at 298.15 K, expressed as log (VP / Pa was performed for a series of 84 hydrocarbons (63 alkanes and 21 cycloalkanes using the van der Waals (vdW surface area, SW/Å2, calculated by the Monte Carlo method, as the molecular descriptor. The QSPR model developed from the subset of 63 alkanes (C1-C16, deemed as the training set, was successfully used for the prediction of the log (VP / Pa values of the 21 cycloalkanes, which was the external prediction (test subset. A QSPR model was also developed for a series composed of all 84 hydrocarbons. Both QSPR models were statistically tested for their ability to fit the data and for prediction. The results showed that the vdW molecular surface used as molecular descriptor (MD explains the variance of the majority of the log (VP / Pa values in this series of 84 hydrocarbons. This MD describes very well the intermolecular forces that hold neutral molecules together. The clear physical meaning of the molecular surface values, SW/Å2, could explain the success of the QSPR models obtained with a single structural molecular descriptor.

  2. 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.

  3. 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

  4. Molecular hematology

    National Research Council Canada - National Science Library

    Provan, Drew; Gribben, John

    2010-01-01

    ... The molecular basis of hemophilia, 219 Paul LF Giangrande 4 The genetics of acute myeloid leukemias, 42 Carolyn J Owen & Jude Fitzgibbon 19 The molecular basis of von Willebrand disease, 233 Luciano Baronc...

  5. Multimedia environmental chemical partitioning from molecular information

    International Nuclear Information System (INIS)

    Martinez, Izacar; Grifoll, Jordi; Giralt, Francesc; Rallo, Robert

    2010-01-01

    The prospect of assessing the environmental distribution of chemicals directly from their molecular information was analyzed. Multimedia chemical partitioning of 455 chemicals, expressed in dimensionless compartmental mass ratios, was predicted by SimpleBox 3, a Level III Fugacity model, together with the propagation of reported uncertainty for key physicochemical and transport properties, and degradation rates. Chemicals, some registered in priority lists, were selected according to the availability of experimental property data to minimize the influence of predicted information in model development. Chemicals were emitted in air or water in a fixed geographical scenario representing the Netherlands and characterized by five compartments (air, water, sediments, soil and vegetation). Quantitative structure-fate relationship (QSFR) models to predict mass ratios in different compartments were developed with support vector regression algorithms. A set of molecular descriptors, including the molecular weight and 38 counts of molecular constituents were adopted to characterize the chemical space. Out of the 455 chemicals, 375 were used for training and testing the QSFR models, while 80 were excluded from model development and were used as an external validation set. Training and test chemicals were selected and the domain of applicability (DOA) of the QSFRs established by means of self-organizing maps according to structural similarity. Best results were obtained with QSFR models developed for chemicals belonging to either the class [C] and [C; O], or the class with at least one heteroatom different than oxygen in the structure. These two class-specific models, with respectively 146 and 229 chemicals, showed a predictive squared coefficient of q 2 ≥ 0.90 both for air and water, which respectively dropped to q 2 ∼ 0.70 and 0.40 for outlying chemicals. Prediction errors were of the same order of magnitude as the deviations associated to the uncertainty of the

  6. Prediction of pesticide acute toxicity using two-dimensional chemical descriptors and target species classification.

    Science.gov (United States)

    Martin, T M; Lilavois, C R; Barron, M G

    2017-06-01

    Previous modelling of the median lethal dose (oral rat LD 50 ) has indicated that local class-based models yield better correlations than global models. We evaluated the hypothesis that dividing the dataset by pesticidal mechanisms would improve prediction accuracy. A linear discriminant analysis (LDA) based-approach was utilized to assign indicators such as the pesticide target species, mode of action, or target species - mode of action combination. LDA models were able to predict these indicators with about 87% accuracy. Toxicity is predicted utilizing the QSAR model fit to chemicals with that indicator. Toxicity was also predicted using a global hierarchical clustering (HC) approach which divides data set into clusters based on molecular similarity. At a comparable prediction coverage (~94%), the global HC method yielded slightly higher prediction accuracy (r 2 = 0.50) than the LDA method (r 2 ~ 0.47). A single model fit to the entire training set yielded the poorest results (r 2 = 0.38), indicating that there is an advantage to clustering the dataset to predict acute toxicity. Finally, this study shows that whilst dividing the training set into subsets (i.e. clusters) improves prediction accuracy, it may not matter which method (expert based or purely machine learning) is used to divide the dataset into subsets.

  7. An Effective Antifreeze Protein Predictor with Ensemble Classifiers and Comprehensive Sequence Descriptors

    Directory of Open Access Journals (Sweden)

    Runtao Yang

    2015-09-01

    Full Text Available Antifreeze proteins (AFPs play a pivotal role in the antifreeze effect of overwintering organisms. They have a wide range of applications in numerous fields, such as improving the production of crops and the quality of frozen foods. Accurate identification of AFPs may provide important clues to decipher the underlying mechanisms of AFPs in ice-binding and to facilitate the selection of the most appropriate AFPs for several applications. Based on an ensemble learning technique, this study proposes an AFP identification system called AFP-Ensemble. In this system, random forest classifiers are trained by different training subsets and then aggregated into a consensus classifier by majority voting. The resulting predictor yields a sensitivity of 0.892, a specificity of 0.940, an accuracy of 0.938 and a balanced accuracy of 0.916 on an independent dataset, which are far better than the results obtained by previous methods. These results reveal that AFP-Ensemble is an effective and promising predictor for large-scale determination of AFPs. The detailed feature analysis in this study may give useful insights into the molecular mechanisms of AFP-ice interactions and provide guidance for the related experimental validation. A web server has been designed to implement the proposed method.

  8. Synthesis and quantitative structure-activity relationship (QSAR) study of novel N-arylsulfonyl-3-acylindole arylcarbonyl hydrazone derivatives as nematicidal agents.

    Science.gov (United States)

    Che, Zhiping; Zhang, Shaoyong; Shao, Yonghua; Fan, Lingling; Xu, Hui; Yu, Xiang; Zhi, Xiaoyan; Yao, Xiaojun; Zhang, Rui

    2013-06-19

    In continuation of our program aimed at the discovery and development of natural-product-based pesticidal agents, 54 novel N-arylsulfonyl-3-acylindole arylcarbonyl hydrazone derivatives were prepared, and their structures were well characterized by ¹H NMR, ¹³C NMR, HRMS, ESI-MS, and mp. Their nematicidal activity was evaluated against that of the pine wood nematode, Bursaphelenchus xylophilus in vivo. Among all of the derivatives, especially V-12 and V-39 displayed the best promising nematicidal activity with LC₅₀ values of 1.0969 and 1.2632 mg/L, respectively. This suggested that introduction of R¹ and R² together as the electron-withdrawing substituents, R³ as the methyl group, and R⁴ as the phenyl with the electron-donating substituents could be taken into account for further preparation of these kinds of compounds as nematicidal agents. Six selected descriptors are a WHIM descriptor (E1m), two GETAWAY descriptors (R1m+ and R3m+), a Burden eigenvalues descriptor (BEHm8), and two edge-adjacency index descriptors (EEig05x and EEig13d). Quantitative structure-activity relationship (QSAR) studies demonstrated that the structural factors, such as molecular mass (a negative correlation with the bioactivity) and molecular polarity (a positive correlation with bioactivity), are likely to govern the nematicidal activities of these compounds. For this model, the correlation coefficient (R²(training set)), the leave-one-out cross-validation correlation coefficient (Q²(LOO)), and the 7-fold cross-validation correlation coefficient (Q²(7-fold)) were 0.791, 0.701, and 0.715, respectively. The external cross-validation correlation coefficient (Q²ext) and the root-mean-square error for the test set (RMSE(test set)) were 0.774 and 3.412, respectively. This study will pave the way for future design, structural modification, and development of indole derivatives as nematicidal agents.

  9. Molecular structure and elastic properties of thermotropic liquid crystals: Integrated molecular dynamics—Statistical mechanical theory vs molecular field approach

    Science.gov (United States)

    Capar, M. Ilk; Nar, A.; Ferrarini, A.; Frezza, E.; Greco, C.; Zakharov, A. V.; Vakulenko, A. A.

    2013-03-01

    The connection between the molecular structure of liquid crystals and their elastic properties, which control the director deformations relevant for electro-optic applications, remains a challenging objective for theories and computations. Here, we compare two methods that have been proposed to this purpose, both characterized by a detailed molecular level description. One is an integrated molecular dynamics-statistical mechanical approach, where the bulk elastic constants of nematics are calculated from the direct correlation function (DCFs) and the single molecule orientational distribution function [D. A. McQuarrie, Statistical Mechanics (Harper & Row, New York, 1973)]. The latter is obtained from atomistic molecular dynamics trajectories, together with the radial distribution function, from which the DCF is then determined by solving the Ornstein-Zernike equation. The other approach is based on a molecular field theory, where the potential of mean torque experienced by a mesogen in the liquid crystal phase is parameterized according to its molecular surface. In this case, the calculation of elastic constants is combined with the Monte Carlo sampling of single molecule conformations. Using these different approaches, but the same description, at the level of molecular geometry and torsional potentials, we have investigated the elastic properties of the nematic phase of two typical mesogens, 4'-n-pentyloxy-4-cyanobiphenyl and 4'-n-heptyloxy-4-cyanobiphenyl. Both methods yield K3(bend) >K1 (splay) >K2 (twist), although there are some discrepancies in the average elastic constants and in their anisotropy. These are interpreted in terms of the different approximations and the different ways of accounting for the structural properties of molecules in the two approaches. In general, the results point to the role of the molecular shape, which is modulated by the conformational freedom and cannot be fully accounted for by a single descriptor such as the aspect ratio.

  10. Do not hesitate to use Tversky-and other hints for successful active analogue searches with feature count descriptors.

    Science.gov (United States)

    Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre

    2013-07-22

    This study is an exhaustive analysis of the neighborhood behavior over a large coherent data set (ChEMBL target/ligand pairs of known Ki, for 165 targets with >50 associated ligands each). It focuses on similarity-based virtual screening (SVS) success defined by the ascertained optimality index. This is a weighted compromise between purity and retrieval rate of active hits in the neighborhood of an active query. One key issue addressed here is the impact of Tversky asymmetric weighing of query vs candidate features (represented as integer-value ISIDA colored fragment/pharmacophore triplet count descriptor vectors). The nearly a 3/4 million independent SVS runs showed that Tversky scores with a strong bias in favor of query-specific features are, by far, the most successful and the least failure-prone out of a set of nine other dissimilarity scores. These include classical Tanimoto, which failed to defend its privileged status in practical SVS applications. Tversky performance is not significantly conditioned by tuning of its bias parameter α. Both initial "guesses" of α = 0.9 and 0.7 were more successful than Tanimoto (at its turn, better than Euclid). Tversky was eventually tested in exhaustive similarity searching within the library of 1.6 M commercial + bioactive molecules at http://infochim.u-strasbg.fr/webserv/VSEngine.html , comparing favorably to Tanimoto in terms of "scaffold hopping" propensity. Therefore, it should be used at least as often as, perhaps in parallel to Tanimoto in SVS. Analysis with respect to query subclasses highlighted relationships of query complexity (simply expressed in terms of pharmacophore pattern counts) and/or target nature vs SVS success likelihood. SVS using more complex queries are more robust with respect to the choice of their operational premises (descriptors, metric). Yet, they are best handled by "pro-query" Tversky scores at α > 0.5. Among simpler queries, one may distinguish between "growable" (allowing for active

  11. Molecular beams

    International Nuclear Information System (INIS)

    Ramsey, N.F.

    1985-01-01

    This book is a timeless and rather complete theoretical and experimental treatment of electric and magnetic resonance molecular-beam experiments for studying the radio frequency spectra of atoms and molecules. The theory of interactions of the nucleus with atomic and molecular fields is extensively presented. Measurements of atomic and nuclear magnetic moments, electric multipole moments, and atomic fine and hyperfine structure are detailed. Useful but somewhat outdated chapters on gas kinetics, molecular beam design, and experimental techniques are also included

  12. Molecular pharmacognosy.

    Science.gov (United States)

    Huang, LuQi; Xiao, PeiGen; Guo, LanPing; Gao, WenYuan

    2010-06-01

    This article analyzes the background and significance of molecular pharmacognosy, including the molecular identification of medicinal raw materials, phylogenetic evolution of medicinal plants and animals, evaluation and preservation of germplasm resources for medicinal plants and animals, etiology of endangerment and protection of endangered medicinal plants and animals, biosynthesis and bioregulation of active components in medicinal plants, and characteristics and the molecular bases of top-geoherbs.

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

    Science.gov (United States)

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

    2016-01-01

    Pesticides generate transformation products (TPs) when they are released into the environment. These TPs may be of ecotoxicological importance. Past studies have demonstrated how difficult it is to predict the occurrence of pesticide TPs and their environmental risk. The monitoring approaches mostly used in current regulatory frameworks target only known ecotoxicologically relevant TPs. Here, we present a novel combined approach which identifies and categorizes known and unknown pesticide TPs in soil by combining suspect screening time-of-flight mass spectrometry with in silico molecular typology. We used an empirical and theoretical pesticide TP library for compound identification by both non-target and target time-of-flight (tandem) mass spectrometry, followed by structural proposition through a molecular structure correlation program. In silico molecular typology was then used to group TPs according to common molecular descriptors and to indirectly elucidate their environmental parameters by analogy to known pesticide compounds with similar molecular descriptors. This approach was evaluated via the identification of TPs of the triazole fungicide tebuconazole occurring in soil during a field dissipation study. Overall, 22 empirical and 12 yet unknown TPs were detected, and categorized into three groups with defined environmental properties. This approach combining suspect screening time-of-flight mass spectrometry with molecular typology could be extended to other organic pollutants and used to rationalize the choice of TPs to be investigated towards a more comprehensive environmental risk assessment scheme. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Euclidian embeddings of periodic nets: definition of a topologically induced complete set of geometric descriptors for crystal structures.

    Science.gov (United States)

    Eon, Jean-Guillaume

    2011-01-01

    Crystal-structure topologies, represented by periodic nets, are described by labelled quotient graphs (or voltage graphs). Because the edge space of a finite graph is the direct sum of its cycle and co-cycle spaces, a Euclidian representation of the derived periodic net is provided by mapping a basis of the cycle and co-cycle spaces to a set of real vectors. The mapping is consistent if every cycle of the basis is mapped on its own net voltage. The sum of all outgoing edges at every vertex may be chosen as a generating set of the co-cycle space. The embedding maps the cycle space onto the lattice L. By analogy, the concept of the co-lattice L* is defined as the image of the generators of the co-cycle space; a co-lattice vector is proportional to the distance vector between an atom and the centre of gravity of its neighbours. The pair (L, L*) forms a complete geometric descriptor of the embedding, generalizing the concept of barycentric embedding. An algebraic expression permits the direct calculation of fractional coordinates. Non-zero co-lattice vectors allow nets with collisions, displacive transitions etc. to be dealt with. The method applies to nets of any periodicity and dimension, be they crystallographic nets or not. Examples are analyzed: α-cristobalite, the seven unstable 3-periodic minimal nets etc.

  15. Relationship between Chinese adjective descriptors of personality and emotional symptoms in young Chinese patients with bipolar disorders.

    Science.gov (United States)

    Yu, Enyan; Li, Huihui; Fan, Hongying; Gao, Qianqian; Tan, Yunfei; Lou, Junyao; Zhang, Jie; Wang, Wei

    2015-12-01

    To investigate whether personality traits are related to emotional symptoms (mania, hypomania, and depression) in Chinese patients with bipolar disorders. Patients with bipolar I and II disorders, and healthy volunteers, were assessed using the Chinese Adjective Descriptors of Personality (CADP) questionnaire, Mood Disorder Questionnaire (MDQ), Hypomanic Checklist (HCL-32), and Plutchik-van Praag Depression Inventory (PVP). Seventy-three patients with bipolar I disorder, 35 with bipolar II disorder and 216 healthy controls were included. Bipolar I and II groups scored significantly higher on MDQ, HCL-32 and PVP scales than controls; the bipolar II group scored lower on the MDQ, but higher on the HCL-32 and PVP than bipolar I. In the bipolar I group, the CADP Intelligent trait (β, 0.25) predicted MDQ; Intelligent (β, -0.24), Agreeable (β, 0.22) and Emotional (β, 0.34) traits predicted PVP. In the bipolar II group, Intelligent (β, 0.22), Agreeable (β, -0.24) and Unsocial (β, 0.31) traits predicted MDQ; Intelligent (β, -0.20), Agreeable (β, -0.31) and Emotional (β, -0.26) traits predicted HCL-32. Four out of five Chinese personality traits were associated with emotional symptoms in patients with bipolar I or II disorder, but displayed different associations depending on disorder type. © The Author(s) 2015.

  16. Chemical dynamics between wells across a time-dependent barrier: Self-similarity in the Lagrangian descriptor and reactive basins

    Science.gov (United States)

    Junginger, Andrej; Duvenbeck, Lennart; Feldmaier, Matthias; Main, Jörg; Wunner, Günter; Hernandez, Rigoberto

    2017-08-01

    In chemical or physical reaction dynamics, it is essential to distinguish precisely between reactants and products for all times. This task is especially demanding in time-dependent or driven systems because therein the dividing surface (DS) between these states often exhibits a nontrivial time-dependence. The so-called transition state (TS) trajectory has been seen to define a DS which is free of recrossings in a large number of one-dimensional reactions across time-dependent barriers and thus, allows one to determine exact reaction rates. A fundamental challenge to applying this method is the construction of the TS trajectory itself. The minimization of Lagrangian descriptors (LDs) provides a general and powerful scheme to obtain that trajectory even when perturbation theory fails. Both approaches encounter possible breakdowns when the overall potential is bounded, admitting the possibility of returns to the barrier long after the trajectories have reached the product or reactant wells. Such global dynamics cannot be captured by perturbation theory. Meanwhile, in the LD-DS approach, it leads to the emergence of additional local minima which make it difficult to extract the optimal branch associated with the desired TS trajectory. In this work, we illustrate this behavior for a time-dependent double-well potential revealing a self-similar structure of the LD, and we demonstrate how the reflections and side-minima can be addressed by an appropriate modification of the LD associated with the direct rate across the barrier.

  17. Morphometric analysis of Passiflora leaves: the relationship between landmarks of the vasculature and elliptical Fourier descriptors of the blade.

    Science.gov (United States)

    Chitwood, Daniel H; Otoni, Wagner C

    2017-01-01

    Leaf shape among Passiflora species is spectacularly diverse. Underlying this diversity in leaf shape are profound changes in the patterning of the primary vasculature and laminar outgrowth. Each of these aspects of leaf morphology-vasculature and blade-provides different insights into leaf patterning. Here, we morphometrically analyze >3300 leaves from 40 different Passiflora species collected sequentially across the vine. Each leaf is measured in two different ways: using 1) 15 homologous Procrustes-adjusted landmarks of the vasculature, sinuses, and lobes; and 2) Elliptical Fourier Descriptors (EFDs), which quantify the outline of the leaf. The ability of landmarks, EFDs, and both datasets together are compared to determine their relative ability to predict species and node position within the vine. Pairwise correlation of x and y landmark coordinates and EFD harmonic coefficients reveals close associations between traits and insights into the relationship between vasculature and blade patterning. Landmarks, more reflective of the vasculature, and EFDs, more reflective of the blade contour, describe both similar and distinct features of leaf morphology. Landmarks and EFDs vary in ability to predict species identity and node position in the vine and exhibit a correlational structure (both within landmark or EFD traits and between the two data types) revealing constraints between vascular and blade patterning underlying natural variation in leaf morphology among Passiflora species. © The Author 2017. Published by Oxford University Press.

  18. Image copy-move forgery detection based on sped-up robust features descriptor and adaptive minimal-maximal suppression

    Science.gov (United States)

    Yang, Bin; Sun, Xingming; Xin, Xiangyang; Hu, Weifeng; Wu, Youxin

    2015-11-01

    Region duplication is a simple and effective operation to create digital image forgeries, where a continuous portion of pixels in an image is copied and pasted to a different location in the same image. Many prior copy-move forgery detection methods suffer from their inability to detect the duplicated region, which is subjected to various geometric transformations. A keypoint-based approach is proposed to detect the copy-move forgery in an image. Our method starts by extracting the keypoints through a fast Hessian detector. Then the adaptive minimal-maximal suppression (AMMS) strategy is developed for distributing the keypoints evenly throughout an image. By using AMMS and a sped-up robust feature descriptor, the proposed method is able to deal with the problem of insufficient keypoints in the almost uniform area. Finally, the geometric transformation performed in cloning is recovered by using the maximum likelihood estimation of the homography. Experimental results show the efficacy of this technique in detecting copy-move forgeries and estimating the geometric transformation parameters. Compared with the state of the art, our approach obtains a higher true positive rate and a lower false positive rate.

  19. Assessment of the genetic diversity of natural rubber tree clones of the SINCHI Institutes clone collection, using of morphological descriptors

    International Nuclear Information System (INIS)

    Quesada Mendez, Isaac; Quintero Barrera, Lorena; Aristizabal, Fabio A; Rodriguez Acuna, Olga

    2011-01-01

    Genetic diversity of natural rubber clones of the in SINCHI Institute’s clone collection was assessed. Clones of Hevea brasiliensis (Willd. ex Adr. De Juss.) Muell.Arg., Hevea spp. (H. brasiliensis x H. benthamiana), and three more species of Hevea genus are a part of the collection. Seventy-two materials were characterized with twenty-eight morphological descriptors. They were later used to generate a similarity matrix through the analysis of multi-categorical variables, and to obtain clusters based on the matrix. A low variability between clones of H. brasiliensis and H. spp. was observed, presumably because of the direct descendants of most of the materials from crosses of parental PB 80, PB 5/51, PB 49 and Tjir, exception made of clone GU 1410. Clustering between some materials product of exclusive cross of PB series, a group between clones descendants of parental clones PB 86, and clustering between descendants of parental clones PB 5/51, were observed. Clones from other species of Hevea differ from this big group.

  20. Use of BI-RADS lesion descriptors in computer-aided diagnosis of malignant and benign breast lesions

    Science.gov (United States)

    Jiang, Yulei; Schmidt, Robert A.; Nishikawa, Robert M.; D'Orsi, Carl J.; Vyborny, Carl J.; Newstead, Gillian M.

    2004-05-01

    The purpose of this study was to determine whether combining an automated computer technique that classifies calcifications in mammograms as malignant or benign with radiologist-provided BI-RADS lesion description improves classification performance. Three expert mammography radiologists who were MQSA certified and familiar with BI-RADS retrospectively interpreted 125 cases of mammograms containing calcifications and provided BI-RADS lesion descriptions. A computer technique was applied to the mammograms to extract eight image features that describe the size, shape, and uniformity of individual as well as groups of calcifications. We compared the performance of artificial neural networks that estimated the likelihood of malignancy based on input from either the computer-extracted image features alone, the BI-RADS lesion descriptors alone, or the combination of both. The leave-one-out method was used. Combining the BI-RADS lesion description provided by a single radiologist and computer-extracted image features resulted in improved performance. However, using two radiologists' BI-RADS lesion descriptions such that one radiologist's data was used to train and another radiologist's data was used to test the neural network diminished this improvement in performance. These results suggest that variability in radiologists' BI-RADS lesion description is large enough to offset a potential gain in performance from combining it with an automated computer technique.

  1. Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG

    Science.gov (United States)

    Bigdely-Shamlo, Nima; Cockfield, Jeremy; Makeig, Scott; Rognon, Thomas; La Valle, Chris; Miyakoshi, Makoto; Robbins, Kay A.

    2016-01-01

    Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies. PMID:27799907

  2. Buried Volume Analysis for Propene Polymerization Catalysis Promoted by Group 4 Metals: a Tool for Molecular Mass Prediction

    KAUST Repository

    Falivene, Laura

    2015-10-02

    A comparison of the steric properties of homogeneous single site catalysts for propene polymerization using the percentage of buried volume (%VBur) as molecular descriptor is reported. The %VBur calculated on the neutral precursors of the active species seems to be a reliable tool to explain several experimental data related to the propene insertion and to the monomer chain transfer. Interestingly, a linear correlation between the buried volume calculated for a large set of neutral precursors and the energetic difference between propagation and termination steps calculated by DFT methods is found for Group 4 metal catalysts. The “master curves” derived for Ti, Zr and Hf confirm not only that the %VBur is an appropriate molecular descriptor for the systems considered but also that it could be used as tool for a large computational screening of new ligands.

  3. ATS drugs molecular structure representation using refined 3D geometric moment invariants

    Czech Academy of Sciences Publication Activity Database

    Pratama, S. F.; Muda, A. K.; Choo, J. H.; Flusser, Jan; Abraham, A.

    2017-01-01

    Roč. 55, č. 10 (2017), s. 1951-1963 ISSN 0259-9791 R&D Projects: GA ČR GA15-16928S Institutional support: RVO:67985556 Keywords : 3D moment invariants * Geometric moment invariants * ATS drugs * Molecular similarity * Molecular descriptors Subject RIV: JD - Computer Applications, Robotics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 1.308, year: 2016 http://library.utia.cas.cz/separaty/2017/ZOI/flusser-0479217.pdf

  4. Molecular dynamics

    NARCIS (Netherlands)

    Bergstra, J.A.; Bethke, I.

    2002-01-01

    Molecular dynamics is a model for the structure and meaning of object based programming systems. In molecular dynamics the memory state of a system is modeled as a fluid consisting of a collection of molecules. Each molecule is a collection of atoms with bindings between them. A computation is

  5. Molecular Modeling

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 5. Molecular Modeling: A Powerful Tool for Drug Design and Molecular Docking. Rama Rao Nadendla. General Article Volume 9 Issue 5 May 2004 pp 51-60. Fulltext. Click here to view fulltext PDF. Permanent link:

  6. Molecular motors

    National Research Council Canada - National Science Library

    Schliwa, M

    2003-01-01

    ... and entitled Primitive Motile Systems in Cell Biology, the field has moved from the phenomenological to the mechanistic and from the largely structural to the primarily molecular. We have come to appreciate that at every level of complexity the cell operates through molecular machines. Some of these machines are single molecules that car...

  7. Application of ‘Inductive’ QSAR Descriptors for Quantification of Antibacterial Activity of Cationic Polypeptides

    Directory of Open Access Journals (Sweden)

    Bojana Jankovic

    2004-12-01

    Full Text Available On the basis of the inductive QSAR descriptors we have created a neural network-based solution enabling quantification of antibacterial activity in the series of 101 synthetic cationic polypeptides (CAMEL-s. The developed QSAR model allowed 80% correct categorical classification of antibacterial potencies of the CAMEL-s both in the training and the validation sets. The accuracy of the activity predictions demonstrates that a narrow set of 3D sensitive ‘inductive’ descriptors can adequately describe the aspects of intra- and intermolecular interactions that are relevant for antibacterial activity of the cationic polypeptides. The developed approach can be further expanded for the larger sets of biologically active peptides and can serve as a useful quantitative tool for rational antibiotic design and discovery.

  8. Alignment independent 3D-QSAR, quantum calculations and molecular docking of Mer specific tyrosine kinase inhibitors as anticancer drugs

    Directory of Open Access Journals (Sweden)

    Fereshteh Shiri

    2016-03-01

    Full Text Available Mer receptor tyrosine kinase is a promising novel cancer therapeutic target in many human cancers, because abnormal activation of Mer has been implicated in survival signaling and chemoresistance. 3D-QSAR analyses based on alignment independent descriptors were performed on a series of 81 Mer specific tyrosine kinase inhibitors. The fractional factorial design (FFD and the enhanced replacement method (ERM were applied and tested as variable selection algorithms for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. The data set was split into 65 molecules as the training set and 16 compounds as the test set. All descriptors were generated by using the GRid INdependent descriptors (GRIND approach. After variable selection, GRIND were correlated with activity values (pIC50 by PLS regression. Of the two applied variable selection methods, ERM had a noticeable improvement on the statistical parameters of PLS model, and yielded a q2 value of 0.77, an rpred2 of 0.94, and a low RMSEP value of 0.25. The GRIND information contents influencing the affinity on Mer specific tyrosine kinase were also confirmed by docking studies. In a quantum calculation study, the energy difference between HOMO and LUMO (gap implied the high interaction of the most active molecule in the active site of the protein. In addition, the molecular electrostatic potential energy at DFT level confirmed results obtained from the molecular docking. The identified key features obtained from the molecular modeling, enabled us to design novel kinase inhibitors.

  9. Alignment independent 3D-QSAR, quantum calculations and molecular docking of Mer specific tyrosine kinase inhibitors as anticancer drugs.

    Science.gov (United States)

    Shiri, Fereshteh; Pirhadi, Somayeh; Ghasemi, Jahan B

    2016-03-01

    Mer receptor tyrosine kinase is a promising novel cancer therapeutic target in many human cancers, because abnormal activation of Mer has been implicated in survival signaling and chemoresistance. 3D-QSAR analyses based on alignment independent descriptors were performed on a series of 81 Mer specific tyrosine kinase inhibitors. The fractional factorial design (FFD) and the enhanced replacement method (ERM) were applied and tested as variable selection algorithms for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. The data set was split into 65 molecules as the training set and 16 compounds as the test set. All descriptors were generated by using the GRid INdependent descriptors (GRIND) approach. After variable selection, GRIND were correlated with activity values (pIC50) by PLS regression. Of the two applied variable selection methods, ERM had a noticeable improvement on the statistical parameters of PLS model, and yielded a q (2) value of 0.77, an [Formula: see text] of 0.94, and a low RMSEP value of 0.25. The GRIND information contents influencing the affinity on Mer specific tyrosine kinase were also confirmed by docking studies. In a quantum calculation study, the energy difference between HOMO and LUMO (gap) implied the high interaction of the most active molecule in the active site of the protein. In addition, the molecular electrostatic potential energy at DFT level confirmed results obtained from the molecular docking. The identified key features obtained from the molecular modeling, enabled us to design novel kinase inhibitors.

  10. The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching

    OpenAIRE

    Willighagen, Egon L.; Mayfield, John W.; Alvarsson, Jonathan; Berg, Arvid; Carlsson, Lars; Jeliazkova, Nina; Kuhn, Stefan; Pluskal, Tom??; Rojas-Chert?, Miquel; Spjuth, Ola; Torrance, Gilleain; Evelo, Chris T.; Guha, Rajarshi; Steinbeck, Christoph

    2017-01-01

    Background The Chemistry Development Kit (CDK) is a widely used open source cheminformatics toolkit, providing data structures to represent chemical concepts along with methods to manipulate such structures and perform computations on them. The library implements a wide variety of cheminformatics algorithms ranging from chemical structure canonicalization to molecular descriptor calculations and pharmacophore perception. It is used in drug discovery, metabolomics, and toxicology. Over the las...

  11. Chemical Reactivity of Isoproturon, Diuron, Linuron, and Chlorotoluron Herbicides in Aqueous Phase: A Theoretical Quantum Study Employing Global and Local Reactivity Descriptors

    Directory of Open Access Journals (Sweden)

    Luis Humberto Mendoza-Huizar

    2015-01-01

    Full Text Available We have calculated global and local DFT reactivity descriptors for isoproturon, diuron, linuron, and chlorotoluron herbicides at the MP2/6-311++G(2d,2p level of theory. The results suggest that, in aqueous conditions, chlorotoluron, linuron, and diuron herbicides may be degraded by elimination of urea moiety through electrophilic attacks. On the other hand, electrophilic, nucleophilic, and free radical attacks on isoproturon may cause the elimination of isopropyl fragment.

  12. 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

  13. Towards 3D Face Recognition in the Real: A Registration-Free Approach Using Fine-Grained Matching of 3D Keypoint Descriptors

    KAUST Repository

    Li, Huibin

    2014-11-12

    Registration algorithms performed on point clouds or range images of face scans have been successfully used for automatic 3D face recognition under expression variations, but have rarely been investigated to solve pose changes and occlusions mainly since that the basic landmarks to initialize coarse alignment are not always available. Recently, local feature-based SIFT-like matching proves competent to handle all such variations without registration. In this paper, towards 3D face recognition for real-life biometric applications, we significantly extend the SIFT-like matching framework to mesh data and propose a novel approach using fine-grained matching of 3D keypoint descriptors. First, two principal curvature-based 3D keypoint detectors are provided, which can repeatedly identify complementary locations on a face scan where local curvatures are high. Then, a robust 3D local coordinate system is built at each keypoint, which allows extraction of pose-invariant features. Three keypoint descriptors, corresponding to three surface differential quantities, are designed, and their feature-level fusion is employed to comprehensively describe local shapes of detected keypoints. Finally, we propose a multi-task sparse representation based fine-grained matching algorithm, which accounts for the average reconstruction error of probe face descriptors sparsely represented by a large dictionary of gallery descriptors in identification. Our approach is evaluated on the Bosphorus database and achieves rank-one recognition rates of 96.56, 98.82, 91.14, and 99.21 % on the entire database, and the expression, pose, and occlusion subsets, respectively. To the best of our knowledge, these are the best results reported so far on this database. Additionally, good generalization ability is also exhibited by the experiments on the FRGC v2.0 database.

  14. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Pinker-Domenig, K.; Helbich, T.H. [Medical University Vienna, Dept. of Radiology, Division of Molecular and Gender Imaging, Vienna (Austria); Bogner, W.; Gruber, S. [Medical University Vienna, Dept. of Radiology, MR Centre of Excellence, Vienna (Austria); Medical University Vienna, Dept. of Radiology, Vienna (Austria); Bickel, H. [Medical University Vienna, Dept. of Radiology, Division of Molecular and Gender Imaging, Vienna (Austria); Medical University Vienna, Dept. of Radiology, Vienna (Austria); Duffy, S. [Queen Mary University of London, Cancer Research UK Centre for Epidemiology, Mathematics and Statistics, Wolfson Institute of Preventive Medicine, Barts and The London School of Medicine and Dentistry, London (United Kingdom); Schernthaner, M. [Medical University Vienna, Dept. of Radiology, Vienna (Austria); Dubsky, P. [Medical University Vienna, Dept. of Surgery, Vienna (Austria); Pluschnig, U. [Medical University Vienna, Dept. of Internal Medicine, Division of Oncology, Vienna (Austria); Rudas, M. [Medical University Vienna, Clinical Institute of Pathology, Vienna (Austria); Trattnig, S. [Medical University Vienna, Dept. of Radiology, MR Centre of Excellence, Vienna (Austria)

    2012-02-15

    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 {sup registered} classification. Sensitivity, specificity and diagnostic accuracy were assessed. The effects of the BI-RADS {sup 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 < 0.001), irregular margin (p < 0.001), heterogeneous enhancement (p < 0.001), Type 3 enhancement kinetics (p = 0.02), increasing patient age (p = 0.02) and larger lesion size (p < 0.001). In multivariate analysis, significant associations with malignancy remained for mass shape (p = 0.06), mass margin (p < 0.001), internal enhancement pattern (p = 0.03) and Type 3 enhancement kinetics (p = 0.06). The ACR BI-RADS {sup 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.)

  16. The Value of Lesion Size as an Adjunct to the BI-RADS-MRI 2013 Descriptors in the Diagnosis of Solitary Breast Masses.

    Science.gov (United States)

    Kawai, Makiko; Kataoka, Masako; Kanao, Shotaro; Iima, Mami; Onishi, Natsuko; Ohashi, Akane; Sakaguchi, Rena; Toi, Masakazu; Togashi, Kaori

    2017-12-07

    This study aimed to evaluate the MRI findings of breast solitary masses in diagnostic procedures to decide the appropriate category based on American College of Radiology (ACR) BI-RADS-MRI 2013, with the focus on lesion size. A retrospective review of 2,603 consecutive breast MRI reports identified 250 pathologically-proven solitary breast masses. Dynamic-contrast enhanced images and diffusion-weighted images were performed on a 3.0/1.5 Tesla Scanner with a 16/4 channel dedicated breast coil. MRI findings were re-evaluated according to ACR BI-RADS-MRI 2013. BI-RADS-MRI descriptors, lesion size and minimum apparent diffusion coefficient (ADC) value were statistically analyzed using univariate/multivariate logistic regression analysis and receiver operator characteristic (ROC) analysis. Based on the results, a diagnostic decision tree was constructed. Of the 250 lesions, 152 (61%) were malignant and 98 (39%) were benign. In univariate logistic regression analysis, most of the BI-RADS descriptors, lesion size, and ADC value were significant. Lesion size and ADC value were binarized with optimal cut-off values of 12 mm and 1.1 × 10 -3 mm 2 /s, respectively. Multivariate logistic regression analysis showed that lesion size (≥12 mm or not), margin (circumscribed or not), kinetics (washout or not) and internal enhancement characteristics (IEC) (rim enhancement present or absent) significantly contributed to the diagnosis (P BI-RADS-MRI 2013 descriptors will allow more detailed categorizations.

  17. Predicting the Metabolic Sites by Flavin-Containing Monooxygenase on Drug Molecules Using SVM Classification on Computed Quantum Mechanics and Circular Fingerprints Molecular Descriptors.

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    Chien-Wei Fu

    Full Text Available As an important enzyme in Phase I drug metabolism, the flavin-containing monooxygenase (FMO also metabolizes some xenobiotics with soft nucleophiles. The site of metabolism (SOM on a molecule is the site where the metabolic reaction is exerted by an enzyme. Accurate prediction of SOMs on drug molecules will assist the search for drug leads during the optimization process. Here, some quantum mechanics features such as the condensed Fukui function and attributes from circular fingerprints (called Molprint2D are computed and classified using the support vector machine (SVM for predicting some potential SOMs on a series of drugs that can be metabolized by FMO enzymes. The condensed Fukui function fA- representing the nucleophilicity of central atom A and the attributes from circular fingerprints accounting the influence of neighbors on the central atom. The total number of FMO substrates and non-substrates collected in the study is 85 and they are equally divided into the training and test sets with each carrying roughly the same number of potential SOMs. However, only N-oxidation and S-oxidation features were considered in the prediction since the available C-oxidation data was scarce. In the training process, the LibSVM package of WEKA package and the option of 10-fold cross validation are employed. The prediction performance on the test set evaluated by accuracy, Matthews correlation coefficient and area under ROC curve computed are 0.829, 0.659, and 0.877 respectively. This work reveals that the SVM model built can accurately predict the potential SOMs for drug molecules that are metabolizable by the FMO enzymes.

  18. Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties

    Energy Technology Data Exchange (ETDEWEB)

    von Lilienfeld, O. Anatole [Department of Chemistry, Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, University of Basel, Basel Switzerland; Argonne Leadership Computing Facility, Argonne National Laboratory, 9700 S. Cass Avenue Lemont Illinois 60439; Ramakrishnan, Raghunathan [Department of Chemistry, Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, University of Basel, Basel Switzerland; Rupp, Matthias [Department of Chemistry, Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, University of Basel, Basel Switzerland; Knoll, Aaron [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne Illinois 60439; Texas Advanced Computing Center, University of Texas, Austin Texas

    2015-04-20

    We introduce a fingerprint representation of molecules based on a Fourier series of atomic radial distribution functions. This fingerprint is unique (except for chirality), continuous, and differentiable with respect to atomic coordinates and nuclear charges. It is invariant with respect to translation, rotation, and nuclear permutation, and requires no preconceived knowledge about chemical bonding, topology, or electronic orbitals. As such, it meets many important criteria for a good molecular representation, suggesting its usefulness for machine learning models of molecular properties trained across chemical compound space. To assess the performance of this new descriptor, we have trained machine learning models of molecular enthalpies of atomization for training sets with up to 10 k organic molecules, drawn at random from a published set of 134 k organic molecules with an average atomization enthalpy of over 1770 kcal/mol. We validate the descriptor on all remaining molecules of the 134 k set. For a training set of 10 k molecules, the fingerprint descriptor achieves a mean absolute error of 8.0 kcal/mol. This is slightly worse than the performance attained using the Coulomb matrix, another popular alternative, reaching 6.2 kcal/mol for the same training and test sets. (c) 2015 Wiley Periodicals, Inc.

  19. Molecular geometry

    CERN Document Server

    Rodger, Alison

    1995-01-01

    Molecular Geometry discusses topics relevant to the arrangement of atoms. The book is comprised of seven chapters that tackle several areas of molecular geometry. Chapter 1 reviews the definition and determination of molecular geometry, while Chapter 2 discusses the unified view of stereochemistry and stereochemical changes. Chapter 3 covers the geometry of molecules of second row atoms, and Chapter 4 deals with the main group elements beyond the second row. The book also talks about the complexes of transition metals and f-block elements, and then covers the organometallic compounds and trans

  20. On the Relationship Between Global Land-Ocean Temperature and Various Descriptors of Solar-Geomagnetic Activity and Climate

    Science.gov (United States)

    Wilson, Robert M.

    2014-01-01

    Examined are sunspot cycle- (SC-) length averages of the annual January-December values of the Global Land-Ocean Temperature Index () in relation to SC-length averages of annual values of various descriptors of solar-geomagnetic activity and climate, incorporating lags of 0-5 yr. For the overall interval SC12-SC23, the is inferred to correlate best against the parameter incorporating lag = 5 yr, where the parameter refers to the resultant aa value having removed that portion of the annual aa average value due to the yearly variation of sunspot number (SSN). The inferred correlation between the and is statistically important at confidence level cl > 99.9%, having a coefficient of linear correlation r = 0.865 and standard error of estimate se = 0.149 degC. Excluding the most recent cycles SC22 and SC23, the inferred correlation is stronger, having r = 0.969 and se = 0.048 degC. With respect to the overall trend in the , which has been upwards towards warmer temperatures since SC12 (1878-1888), solar-geomagnetic activity parameters are now trending downwards (since SC19). For SC20-SC23, in contrast, comparison of the against SC-length averages of the annual value of the Mauna Loa carbon dioxide () index is found to be highly statistically important (cl >> 99.9%), having r = 0.9994 and se = 0.012 degC for lag = 2 yr. On the basis of the inferred preferential linear correlation between the and , the current ongoing SC24 is inferred to have warmer than was seen in SC23 (i.e., >0.526 degC), probably in excess of 0.68 degC (relative to the 1951-1980 base period).