DDC Descriptor Frequencies.

Science.gov (United States)

Klingbiel, Paul H.; Jacobs, Charles R.

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

Finding the Best Feature Detector-Descriptor Combination

DEFF Research Database (Denmark)

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

2011-01-01

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

A comparison between space-time video descriptors

Science.gov (United States)

Costantini, Luca; Capodiferro, Licia; Neri, Alessandro

2013-02-01

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

Topological Substituent Descriptors

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.

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.

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

Science.gov (United States)

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

2014-01-27

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

Covariance descriptor fusion for target detection

Science.gov (United States)

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

2016-05-01

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

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

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

Density-Based 3D Shape Descriptors

Directory of Open Access Journals (Sweden)

Schmitt Francis

2007-01-01

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

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

Directory of Open Access Journals (Sweden)

Jiuqiang Han

2013-03-01

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

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.

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

Determination of solute descriptors by chromatographic methods

International Nuclear Information System (INIS)

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

2009-01-01

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

Determination of solute descriptors by chromatographic methods.

Science.gov (United States)

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

2009-10-12

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

Descriptors of server capabilities in China

DEFF Research Database (Denmark)

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

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

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

Science.gov (United States)

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

2017-02-03

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

Surface Area Distribution Descriptor for object matching

Directory of Open Access Journals (Sweden)

Mohamed F. Gafar

2010-07-01

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

Descriptor revision belief change through direct choice

CERN Document Server

Hansson, Sven Ove

2017-01-01

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

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.

Learning discriminant face descriptor.

Science.gov (United States)

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

2014-02-01

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

Object classification and detection with context kernel descriptors

DEFF Research Database (Denmark)

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

2014-01-01

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

Color descriptors for object category recognition

NARCIS (Netherlands)

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

2008-01-01

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

DEVELOPING CEFR ILLUSTRATIVE DESCRIPTORS OF ASPECTS OF MEDIATION

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.

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

International Nuclear Information System (INIS)

Raevsky, Oleg A

1999-01-01

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

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

Ensembles of Novel Visual Keywords Descriptors for Image Categorization

NARCIS (Netherlands)

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

2010-01-01

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

Szeged Matrix Property Indices as Descriptors to Characterize Fullerenes

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Jäntschi Lorentz

2016-12-01

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

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

Science.gov (United States)

Vogt, Martin; Bajorath, Jürgen

2008-01-01

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

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

Science.gov (United States)

Davis, Joel J.

1999-01-01

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

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

KAUST Repository

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

2015-01-01

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

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

KAUST Repository

Khan, Naeemullah

2015-06-07

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

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

DEFF Research Database (Denmark)

Rasmussen, Birgit; Rindel, Jens Holger

2010-01-01

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

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...

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.)

Visual feature discrimination versus compression ratio for polygonal shape descriptors

Science.gov (United States)

Heuer, Joerg; Sanahuja, Francesc; Kaup, Andre

2000-10-01

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

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

Science.gov (United States)

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

2018-06-15

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

Learning to assign binary weights to binary descriptor

Science.gov (United States)

Huang, Zhoudi; Wei, Zhenzhong; Zhang, Guangjun

2016-10-01

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

Branch length similarity entropy-based descriptors for shape representation

Science.gov (United States)

Kwon, Ohsung; Lee, Sang-Hee

2017-11-01

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

Aggregating Local Descriptors for Epigraphs Recognition

OpenAIRE

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

2014-01-01

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

Stargate GTM: Bridging Descriptor and Activity Spaces.

Science.gov (United States)

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

2015-11-23

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

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.

RANZAR Body Systems Framework of diagnostic imaging examination descriptors

International Nuclear Information System (INIS)

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

2014-01-01

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

RANZCR Body Systems Framework of diagnostic imaging examination descriptors.

Science.gov (United States)

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

2014-08-01

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

Gabor Weber Local Descriptor for Bovine Iris Recognition

Directory of Open Access Journals (Sweden)

Shengnan Sun

2013-01-01

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

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

KAUST Repository

Li, Huibin

2012-09-01

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

RAID: a relation-augmented image descriptor

KAUST Repository

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

2016-01-01

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

RAID: a relation-augmented image descriptor

KAUST Repository

Guerrero, Paul

2016-07-11

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

Character context: a shape descriptor for Arabic handwriting recognition

Science.gov (United States)

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

2017-11-01

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

Three-Dimensional Model Retrieval Using Dynamic Multi-Descriptor Fusion

Institute of Scientific and Technical Information of China (English)

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

2017-01-01

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

Correspondence dictionary from free English term to INIS descriptors

International Nuclear Information System (INIS)

1991-12-01

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

Shape descriptors for mode-shape recognition and model updating

International Nuclear Information System (INIS)

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

2009-01-01

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

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.

3D molecular descriptors important for clinical success.

Science.gov (United States)

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

2013-02-25

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

Modular Chemical Descriptor Language (MCDL: Stereochemical modules

Directory of Open Access Journals (Sweden)

Gakh Andrei A

2011-01-01

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

Local Descriptors of Dynamic and Nondynamic Correlation.

Science.gov (United States)

Ramos-Cordoba, Eloy; Matito, Eduard

2017-06-13

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

Short local descriptors from 2D connected pattern spectra

NARCIS (Netherlands)

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

2015-01-01

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

Cooperative Control for Multiple Autonomous Vehicles Using Descriptor Functions

Directory of Open Access Journals (Sweden)

Marta Niccolini

2014-01-01

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

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

DEFF Research Database (Denmark)

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

2015-01-01

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

Lagrangian descriptors in dissipative systems.

Science.gov (United States)

Junginger, Andrej; Hernandez, Rigoberto

2016-11-09

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

Gun bore flaw image matching based on improved SIFT descriptor

Science.gov (United States)

Zeng, Luan; Xiong, Wei; Zhai, You

2013-01-01

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

Sparse B-spline polynomial descriptors for human activity recognition

NARCIS (Netherlands)

Oikonomopoulos, Antonios; Pantic, Maja; Patras, Ioannis

2009-01-01

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

Color Independent Components Based SIFT Descriptors for Object/Scene Classification

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.

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

Science.gov (United States)

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

2017-03-01

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

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.'

Gabor Weber Local Descriptor for Bovine Iris Recognition

OpenAIRE

Sun, Shengnan; Zhao, Lindu; Yang, Shicai

2013-01-01

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

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

Science.gov (United States)

Xiao, Qinhan; Li, Yanjun

2009-12-01

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

Complex Correlation Measure: a novel descriptor for Poincaré plot

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Gubbi Jayavardhana

2009-08-01

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

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

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Vladimir Chupakhin

2014-06-01

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

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

Science.gov (United States)

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

2014-06-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-15

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

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

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Mariusz Butkiewicz

2012-08-01

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

Ligand Electron Density Shape Recognition Using 3D Zernike Descriptors

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

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

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

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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.

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

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Trbojevic Jovana

2017-06-01

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

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

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Marilene Santos de Lima

2012-01-01

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

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

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Catana, Cornel

2009-03-01

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

New polynomial-based molecular descriptors with low degeneracy.

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Matthias Dehmer

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

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

International Nuclear Information System (INIS)

Ebinuma, Yukio; Takahashi, Satoko

1981-01-01

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

On the Alignment of Shapes Represented by Fourier Descriptors

DEFF Research Database (Denmark)

Sjöstrand, Karl; Ericsson, Anders; Larsen, Rasmus

2006-01-01

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

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

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Guo, Sheng; Huang, Weilin; Qiao, Yu

2017-01-01

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

Stereo matching based on SIFT descriptor with illumination and camera invariance

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

2010-10-01

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

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

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Huai Yu

2016-03-01

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

Image feature detectors and descriptors foundations and applications

CERN Document Server

Hassaballah, Mahmoud

2016-01-01

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

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

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Ashtawy, Hossam M; Mahapatra, Nihar R

2018-01-22

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

Automatic summarization of soccer highlights using audio-visual descriptors.

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

2015-01-01

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

Music Identification System Using MPEG-7 Audio Signature Descriptors

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

2013-01-01

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

Music Identification System Using MPEG-7 Audio Signature Descriptors

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Shingchern D. You

2013-01-01

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

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

CERN Document Server

Schultz, Thomas

2015-01-01

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

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

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Xiujie Qu

2014-01-01

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

Breast density pattern characterization by histogram features and texture descriptors

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Pedro Cunha Carneiro

2017-04-01

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

Discriminating Power of FISWG Characteristic Descriptors Under Different Forensic Use Cases

NARCIS (Netherlands)

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

2016-01-01

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

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.

Genetic divergence among Brazilian turmeric germplasm using morpho-agronomical descriptors

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Mário Sérgio Sigrist

2011-01-01

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

Innovative design method of automobile profile based on Fourier descriptor

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

2017-10-01

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

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

Science.gov (United States)

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

2011-01-01

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

From acoustic descriptors to evoked quality of car door sounds.

Science.gov (United States)

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

2014-07-01

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

Accumulation of different visual feature descriptors in a coherent framework

DEFF Research Database (Denmark)

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

2011-01-01

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

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

NARCIS (Netherlands)

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

2015-01-01

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

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

Science.gov (United States)

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

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

Deconstructing field-induced ketene isomerization through Lagrangian descriptors.

Science.gov (United States)

Craven, Galen T; Hernandez, Rigoberto

2016-02-07

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

GenMol trademark supramolecular descriptors predicting reliable sensitivity of energetic compounds

Energy Technology Data Exchange (ETDEWEB)

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

2009-04-15

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

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

Directory of Open Access Journals (Sweden)

Mengjuan Cao

2014-01-01

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

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.

Dense Descriptors for Optical Flow Estimation: A Comparative Study

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Ahmadreza Baghaie

2017-02-01

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

An Advanced Rotation Invariant Descriptor for SAR Image Registration

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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.

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

Science.gov (United States)

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

2004-01-01

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

Descriptors for antimicrobial peptides

DEFF Research Database (Denmark)

Jenssen, Håvard

2011-01-01

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

Tracking image features with PCA-SURF descriptors

CSIR Research Space (South Africa)

Pancham, A

2015-05-01

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

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

Science.gov (United States)

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

2008-08-14

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

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

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

Science.gov (United States)

Cao, Mengjuan; Liao, Fucheng

2015-04-01

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

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

Artificial intelligence systems based on texture descriptors for vaccine development.

Science.gov (United States)

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2011-02-01

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

Assigning Main Orientation to an EOH Descriptor on Multispectral Images.

Science.gov (United States)

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

2015-07-01

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

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

Science.gov (United States)

Kim, Han-Ul; Kim, Chang-Su

2017-08-01

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

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

Directory of Open Access Journals (Sweden)

Jadranka Odović

2014-03-01

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

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...

Automated detection of microaneurysms using robust blob descriptors

Science.gov (United States)

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

2013-03-01

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

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

DEFF Research Database (Denmark)

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

2016-01-01

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

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

Science.gov (United States)

Nisius, Britta; Gohlke, Holger

2012-09-24

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

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

Science.gov (United States)

Bonnet, Adeline; Naveteur, Janick

2006-10-01

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

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

Science.gov (United States)

Reenu; Vikas

2015-09-01

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

Propuesta de descriptores para Acca sellowiana (Berg. Burret

Directory of Open Access Journals (Sweden)

María Puppo

2014-12-01

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

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2013-01-28

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

Assigning Main Orientation to an EOH Descriptor on Multispectral Images

Directory of Open Access Journals (Sweden)

Yong Li

2015-07-01

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

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

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

2017-11-01

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

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.

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.

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.

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

Science.gov (United States)

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

2016-07-12

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

Fast human pose estimation using 3D Zernike descriptors

Science.gov (United States)

Berjón, Daniel; Morán, Francisco

2012-03-01

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

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.

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

Science.gov (United States)

Vikas; Chayawan

2014-01-01

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

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.

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

Science.gov (United States)

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

2015-05-01

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

Fourier descriptors analysis of anisotropy and preferred Orientation in geological samples

International Nuclear Information System (INIS)

Santiago Buey, C. de

2011-01-01

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

Morphological descriptors and micro satellite diversity among scarlet ...

African Journals Online (AJOL)

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

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.)

Evaluating descriptors for the lateral translocation of membrane proteins.

Science.gov (United States)

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

2011-01-01

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

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%).

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

International Nuclear Information System (INIS)

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

2007-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2007-06-19

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

2016-08-29

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

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

Unknown author

2016-01-01

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

morphological descriptors and micro satellite diversity among scarlet ...

African Journals Online (AJOL)

Prof. Adipala Ekwamu

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

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

Directory of Open Access Journals (Sweden)

Lorentz JÄNTSCHI

2005-01-01

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

Lagrangian descriptors of driven chemical reaction manifolds.

Science.gov (United States)

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

2017-08-01

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

Compositional descriptor-based recommender system for the materials discovery

Science.gov (United States)

Seko, Atsuto; Hayashi, Hiroyuki; Tanaka, Isao

2018-06-01

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

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

DEFF Research Database (Denmark)

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

2018-01-01

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

Partial solvation parameters and LSER molecular descriptors

International Nuclear Information System (INIS)

Panayiotou, Costas

2012-01-01

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

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

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Lei Qin

2014-05-01

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

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

Science.gov (United States)

Desai, Alok; Lee, Dah-Jye

2013-12-01

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

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...

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

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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.

Object tracking on mobile devices using binary descriptors

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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.

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

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

2017-12-05

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

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

Science.gov (United States)

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

2013-03-01

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

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

International Nuclear Information System (INIS)

Manzanas Lopez, J.; Santiago Buey, C.

2010-01-01

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

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

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Morteza Atabati

2016-09-01

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

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

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Lorentz JÄNTSCHI

2007-12-01

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

Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.

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Daberdaku, Sebastian; Ferrari, Carlo

2018-02-06

The correct determination of protein-protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task. In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein-Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI). The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction

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, ...

Feedback nash equilibria for linear quadratic descriptor differential games

NARCIS (Netherlands)

Engwerda, J.C.; Salmah, S.

2012-01-01

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

Feedback Nash Equilibria for Linear Quadratic Descriptor Differential Games

NARCIS (Netherlands)

Engwerda, J.C.; Salmah, Y.

2010-01-01

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

Uncovering the Geometry of Barrierless Reactions Using Lagrangian Descriptors.

Science.gov (United States)

Junginger, Andrej; Hernandez, Rigoberto

2016-03-03

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

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

Science.gov (United States)

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

2018-03-21

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

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

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Genyun Sun

2017-08-01

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

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

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Mingzhe Su

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

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

Ariyasena, Thiloka C; Poole, Colin F

2014-09-26

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

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

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B. Souyei

2010-12-01

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

Control Configuration Selection for Multivariable Descriptor Systems

DEFF Research Database (Denmark)

Shaker, Hamid Reza; Stoustrup, Jakob

2012-01-01

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

Attributes and descriptors for building performance evaluation

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S. Gopikrishnan

2017-12-01

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

Static sign language recognition using 1D descriptors and neural networks

Science.gov (United States)

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

2012-10-01

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

Comparing types of local public health agencies in North Carolina.

Science.gov (United States)

Markiewicz, Milissa; Moore, Jill; Foster, Johanna H; Berner, Maureen; Matthews, Gene; Wall, Aimee

2013-01-01

Some states are considering restructuring local public health agencies (LPHAs) in hopes of achieving long-term efficiencies. North Carolina's experience operating different types of LPHAs, such as county health departments, district health departments, public health authorities, and consolidated human services agencies, can provide valuable information to policy makers in other states who are examining how best to organize their local public health system. To identify stakeholders' perceptions of the benefits and challenges associated with different types of LPHAs in North Carolina and to compare LPHA types on selected financial, workforce, and service delivery measures. Focus groups and key informant interviews were conducted to identify stakeholders' perceptions of different LPHA types. To compare LPHA types on finance, workforce, and service delivery measures, descriptive statistical analyses were performed on publicly available quantitative data. North Carolina. Current and former state and local public health practitioners, county commissioners, county managers, assistant managers, state legislators, and others. In addition to identifying stakeholders' perceptions of LPHA types, proportion of total expenditures by funding source, expenditures per capita by funding source, full-time equivalents per 1000 population, and percentage of 127 tracked services offered were calculated. Stakeholders reported benefits and challenges of all LPHA types. LPHA types differ with regard to source of funding, with county health departments and consolidated human services agencies receiving a greater percentage of their funding from county appropriations than districts and authorities, which receive a comparatively larger percentage from other revenues. Types of LPHAs are not entirely distinct from one another, and LPHAs of the same type can vary greatly from one another. However, stakeholders noted differences between LPHA types-particularly with regard to district health

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-04-10

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

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

Science.gov (United States)

Miyao, Tomoyuki; Funatsu, Kimito

2017-08-01

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

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

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

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

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

2017-06-21

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

An efficient descriptor model for designing materials for solar cells

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

2015-11-01

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

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

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

2017-12-27

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

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

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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).

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

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

2009-12-09

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

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

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Falomir, Zoe; Kluth, Thomas

2018-05-01

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

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

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

2018-04-01

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

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

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Hongwei Ying

2014-08-01

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

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

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

2008-06-01

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

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

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

2013-02-05

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

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

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Zarei, Kobra; Atabati, Morteza; Ahmadi, Monire

2017-05-04

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

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

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Xu, Guojing; Wang, Jinyan; Qi, Shengxiang

2018-03-01

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

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

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

2017-05-31

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

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

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

2018-04-01

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

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

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Williams, Rebecca S.; Ribisl, Kurt M.

2015-01-01

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

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

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Luis Payá

2014-02-01

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

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

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

2010-02-26

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

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

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Mager, P P; Rothe, H

1990-10-01

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

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

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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.

Where the bugs are: analyzing distributions of bacterial phyla by descriptor keyword search in the nucleotide database.

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Squartini, Andrea

2011-07-26

The associations between bacteria and environment underlie their preferential interactions with given physical or chemical conditions. Microbial ecology aims at extracting conserved patterns of occurrence of bacterial taxa in relation to defined habitats and contexts. In the present report the NCBI nucleotide sequence database is used as dataset to extract information relative to the distribution of each of the 24 phyla of the bacteria superkingdom and of the Archaea. Over two and a half million records are filtered in their cross-association with each of 48 sets of keywords, defined to cover natural or artificial habitats, interactions with plant, animal or human hosts, and physical-chemical conditions. The results are processed showing: (a) how the different descriptors enrich or deplete the proportions at which the phyla occur in the total database; (b) in which order of abundance do the different keywords score for each phylum (preferred habitats or conditions), and to which extent are phyla clustered to few descriptors (specific) or spread across many (cosmopolitan); (c) which keywords individuate the communities ranking highest for diversity and evenness. A number of cues emerge from the results, contributing to sharpen the picture on the functional systematic diversity of prokaryotes. Suggestions are given for a future automated service dedicated to refining and updating such kind of analyses via public bioinformatic engines.

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

DEFF Research Database (Denmark)

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

2002-01-01

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

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

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

2014-09-01

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

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

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.

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

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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

Transformational Leadership Type in Public and Private Organizations

Directory of Open Access Journals (Sweden)

Mihaela Rus

2012-05-01

Full Text Available The issue concerning leadership is a very complex one, that is why taking into the account theplurity of styles already existent many times it was asked the questions: „What type of leadership isnecessary?”. By asking this question, we are thinking of a person responsible with organizing or coordinatingwork or the ones hired to do this, to think of what people want, to solve the management problems in group.This study is intended as a comparison of the two types of leadership (transformational vs. transactional interms of employee performance in public and private organizations. To measure performance and chose twoindicators: satisfaction and productivity. This study falls into the category of research studies the type ofdriving through subordinates with both theoretical and practical implications. The efficiency of this type ofleadership has been demonstrated by studies especially in the political and military and very few studies havebeen made in industrial .Type of transformational leadership is better than transactional perceived astransformational leaders are closer to the needs of employees and continuously investigate these necessities.This paper presents a practical validity as advising managers to develop a transformational type of leadership,both public and private organizations, leads to better performance. Also open new avenues of research,among which we can mention: study the impact of organizational culture on the adoption of transformationaltype vs transactional type; decision-making mechanisms in the type of transformational leadership; initiatetraining programs to develop a transformational type of leadership.

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

Science.gov (United States)

Lanier, James A.; And Others

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

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

Science.gov (United States)

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

2015-03-01

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

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

DEFF Research Database (Denmark)

Malmendal, Anders; Amoresano, Claudia; Trotta, Roberta

2011-01-01

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

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

Science.gov (United States)

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

2018-06-01

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

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

Science.gov (United States)

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

2016-07-01

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

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

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

2012-01-01

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

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

Science.gov (United States)

Liu, Zhi-Ping; Chen, Luonan

2016-01-01

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

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

International Nuclear Information System (INIS)

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

2013-01-01

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

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

Science.gov (United States)

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

2015-10-06

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

The public cancer radiology imaging collections of The Cancer Imaging Archive.

Science.gov (United States)

Prior, Fred; Smith, Kirk; Sharma, Ashish; Kirby, Justin; Tarbox, Lawrence; Clark, Ken; Bennett, William; Nolan, Tracy; Freymann, John

2017-09-19

The Cancer Imaging Archive (TCIA) is the U.S. National Cancer Institute's repository for cancer imaging and related information. TCIA contains 30.9 million radiology images representing data collected from approximately 37,568 subjects. This data is organized into collections by tumor-type with many collections also including analytic results or clinical data. TCIA staff carefully de-identify and curate all incoming collections prior to making the information available via web browser or programmatic interfaces. Each published collection within TCIA is assigned a Digital Object Identifier that references the collection. Additionally, researchers who use TCIA data may publish the subset of information used in their analysis by requesting a TCIA generated Digital Object Identifier. This data descriptor is a review of a selected subset of existing publicly available TCIA collections. It outlines the curation and publication methods employed by TCIA and makes available 15 collections of cancer imaging data.

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

Science.gov (United States)

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

2016-08-01

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

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.

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

KAUST Repository

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

2012-01-01

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

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

Science.gov (United States)

Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

2018-02-01

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

Genetic dissimilarity among sweet potato genotypes using morphological and molecular descriptors

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.

Most Common Publication Types in Radiology Journals:: What is the Level of Evidence?

Science.gov (United States)

Rosenkrantz, Andrew B; Pinnamaneni, Niveditha; Babb, James S; Doshi, Ankur M

2016-05-01

This study aimed to assess the most common publication types in radiology journals, as well as temporal trends and association with citation frequency. PubMed was searched to extract all published articles having the following "Publication Type" indices: "validation studies," "meta-analysis," "clinical trial," "comparative study," "evaluation study," "guideline," "multicenter study," "randomized study," "review," "editorial," "case report," and "technical report." The percentage of articles within each category published within clinical radiology journals was computed. Normalized percentages for each category were also computed on an annual basis. Citation counts within a 2-year window following publication were obtained using Web of Science. Overall trends were assessed. Publication types with the highest fraction in radiology journals were technical reports, evaluation studies, and case reports (4.8% to 5.8%). Publication types with the lowest fraction in radiology journals were randomized trials, multicenter studies, and meta-analyses (0.8% to 1.5%). Case reports showed a significant decrease since 1999, with accelerating decline since 2007 (P = 0.002). Publication types with highest citation counts were meta-analyses, guidelines, and multicenter studies (8.1 ± 10.7 to 12.9 ± 5.1). Publication types with lowest citation counts were case reports, editorials, and technical reports (1.4 ± 2.4 to 2.9 ± 4.3). The representation in radiology journals and citation frequency of the publication types showed weak inverse correlation (r = -0.372). Radiology journals have historically had relatively greater representation of less frequently cited publication types. Various strategies, including methodological training, multidisciplinary collaboration, national support networks, as well as encouragement of higher level of evidence by funding agencies and radiology journals themselves, are warranted to improve the impact of radiological research

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.

Analysis of Agromorphological Descriptors to Differentiate between Duke Cherry (Prunus x gondouinii (Poit. & TurpinRehd. and Its Progenitors: Sweet Cherry (Prunus avium L. and Sour Cherry (Prunus cerasus L. Análisis de Descriptores Agromorfológicos para Diferenciar entre Cerezo Duke (Prunus x gondouinii (Poit. & Turpin Rehd. y sus Progenitores: Cerezo (Prunus avium L. y Guindo (Prunus cerasus L.

Directory of Open Access Journals (Sweden)

Rodrigo Pérez

2010-03-01

Full Text Available The rapid identification of the hybrids between sweet cherry (Prunus avium L. and sour cherry (Prunus cerasus L. is not easy. In order to resolve this problem, 18 Spanish sweet, sour and duke cherry cultivars were surveyed and characterized using 43 agromorphological descriptors evaluated in flowers, leaves, dormant 1-yr-old shoots, fruits, and trees during 2005 and 2006. Based on quantitative parameters, ANOVA and stepwise discriminant analysis (SDA were carried out. For qualitative descriptors, statistical comparisons were done by means of the chi-square (χ2 test. As result of the study, two quantitative (titratable acidity and number of lenticels and six qualitative descriptors (shape of the central and lateral lobes in the internal bracts of the flower fascicles, leaf shape and margin, pubescence in the veins of the lower side of the leaf, and type of sulci of the seed coat were identified as differential parameters in P. avium, P. cerasus and P. x gondouinii(Poit. & Turpin Rehd. Also, another four qualitative descriptors (petal coloration at the end of blooming, leaf stipule type, and seed shape and viability were found to be useful for easy differentiation between sour and duke cherry. None of these parameters has been employed previously to discriminate among sweet, sour and duke cherry.Los híbridos de cerezo (Prunus avium L. y guindo (Prunus cerasus L. no son fáciles de identificar. Para resolver este problema, 18 cultivares de cerezo, guindo y sus híbridos fueron prospectados y caracterizados agromorfológicamente mediante el estudio de 43 descriptores evaluados en flores, hojas, frutos, ramas de 1 año y árbol durante los años 2005 y 2006. En base a los resultados obtenidos del estudio de los diferentes parámetros cuantitativos se realizaron un ANDEVA y un análisis discriminante escalonado (SDA. Los descriptores cualitativos fueron analizados mediante el test de Chi-cuadrado (χ². Como resultado del estudio se identificaron

A comparison of feature detectors and descriptors for object class matching

DEFF Research Database (Denmark)

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

2016-01-01

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

Stroke subtype classification by geometrical descriptors of lesion shape.

Directory of Open Access Journals (Sweden)

Bastian Cheng

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

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

Science.gov (United States)

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

2013-10-30

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

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

Directory of Open Access Journals (Sweden)

Gutierrez J. A.

2004-04-01

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

Combination of image descriptors for the exploration of cultural photographic collections

Science.gov (United States)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Natividad Adamuz-Povedano

2013-03-01

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

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.

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

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.

The use of molecular descriptors in the development of co-amorphous formulations

DEFF Research Database (Denmark)

Meng-Lund, Helena Marie Lindholm; Korgaard, Georgia Kasten; Jensen, Katrine Birgitte Tarp

2018-01-01

-amorphisation between amino acid and drug. The predictions are thought to be used in an early screening phase to identify potential drug-amino acid combinations for further studies. A large variety of molecular descriptors was calculated for six drugs (carvedilol, mebendazole, carbamazepine, furosemide, indomethacin...

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

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…

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

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

Science.gov (United States)

Liu, Shubin; Rong, Chunying; Lu, Tian

2017-01-04

One of the main tasks of theoretical chemistry is to rationalize computational results with chemical insights. Key concepts of such nature include nucleophilicity, electrophilicity, regioselectivity, and stereoselectivity. While computational tools are available to predict barrier heights and other reactivity properties with acceptable accuracy, a conceptual framework to appreciate above quantities is still lacking. In this work, we introduce the electronic force as the fundamental driving force of chemical processes to understand and predict molecular reactivity. It has three components but only two are independent. These forces, electrostatic and steric, can be employed as reliable descriptors for nucleophilic and electrophilic regioselectivity and stereoselectivity. The advantages of using these forces to evaluate molecular reactivity are that electrophilic and nucleophilic attacks are featured by distinct characteristics in the electrostatic force and no knowledge of quantum effects included in the kinetic and exchange-correlation energies is required. Examples are provided to highlight the validity and general applicability of these reactivity descriptors. Possible applications in ambident reactivity, σ and π holes, frustrated Lewis pairs, and stereoselective reactions are also included in this work.

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.

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.

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

Directory of Open Access Journals (Sweden)

Dušková, Elena

2016-07-01

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

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.

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.

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

Science.gov (United States)

2018-05-01

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

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

International Nuclear Information System (INIS)

Kar, Supratik; Roy, Kunal

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-05-15

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

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.

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

DEFF Research Database (Denmark)

Helimäki, Heikki; Rasmussen, Birgit

2010-01-01

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

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

Science.gov (United States)

Patra, Sarbani; Keshavamurthy, Srihari

2018-02-14

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

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

Science.gov (United States)

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

2011-07-01

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

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...

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

Energy Technology Data Exchange (ETDEWEB)

D' Archivio, Angelo Antonio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)], E-mail: darchivi@univaq.it; Maggi, Maria Anna; Mazzeo, Pietro; Ruggieri, Fabrizio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)

2008-11-03

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

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

International Nuclear Information System (INIS)

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

2008-01-01

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

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.

THE PROGNOSIS OF TOTAL PUBLIC EXPENDITURES AND TYPES OF EXPENDITURES IN ROMANIA

Directory of Open Access Journals (Sweden)

ANA-PETRINA STANCIU

2012-12-01

Full Text Available The purpose of the paper is to provide a prognosis of total public expenditure and types of expenditures, starting from the evolution in time of total public expenditure and spending on public services, defense, public order and safety, economic affairs, environmental protection, housing and community amenities, health, recreation, culture and religion, education and social protection.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Guofeng Tong

2014-04-01

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

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

Science.gov (United States)

Yi, Chucai; Tian, Yingli

2014-07-01

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

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...

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

Directory of Open Access Journals (Sweden)

Sorana BOLBOACĂ

2005-06-01

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

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

Science.gov (United States)

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

2018-05-01

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

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.

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.

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

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...

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...

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

DEFF Research Database (Denmark)

Hagberg, Klas; Rasmussen, Birgit

2010-01-01

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

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

Science.gov (United States)

Krein, Michael

After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright cheating in the form of explicitly removing data to fit models. These actions do not serve the community well, nor are they beneficial to future predictions based on established models. In practice, in order to select combinations of descriptors and machine learning methods that might work best, one must consider the nature and size of the training and test datasets, be aware of existing hypotheses about the data, and resist the temptation to bias structure representation and modeling to explicitly fit the hypotheses. The definition and application of these best practices is important for obtaining actionable modeling outcomes, and for setting user expectations of modeling accuracy when predicting the endpoint values of unknowns. A wide variety of statistical learning approaches, descriptor types, and model validation strategies are explored herein, with the goals of helping end users understand the factors involved in creating and using QSPR models effectively, and to better understand relationships within the data, especially by looking at the problem space from multiple perspectives. Molecular relationships are commonly envisioned in a continuous high-dimensional space of numerical descriptors, referred to as chemistry space. Descriptor and similarity metric choice influence the partitioning of this space into regions corresponding to local structural similarity. These regions, known as domains of applicability, are most likely to be successfully modeled by a QSPR. In Chapter 2, the network topology and scaling relationships of several chemistry spaces are thoroughly investigated. Chemistry spaces studied include the

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

Science.gov (United States)

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

2017-12-01

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

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

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

Science.gov (United States)

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

2013-01-01

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

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.

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…

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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.

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

Science.gov (United States)

Jhin, Changho; Hwang, Keum Taek

2014-08-22

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

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

Directory of Open Access Journals (Sweden)

Changho Jhin

2014-08-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Dissecting molecular descriptors into atomic contributions in density functional reactivity theory

International Nuclear Information System (INIS)

Rong, Chunying; Lu, Tian; Liu, Shubin

2014-01-01

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

Dissecting molecular descriptors into atomic contributions in density functional reactivity theory

Energy Technology Data Exchange (ETDEWEB)

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

2014-01-14

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

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.

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

DEFF Research Database (Denmark)

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

2011-01-01

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

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

Science.gov (United States)

Hsing, Michael; Byler, Kendall; Cherkasov, Artem

2009-01-01

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

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.

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

Science.gov (United States)

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

2015-09-01

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

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

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.

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

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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".

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)

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

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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.

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

Science.gov (United States)

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

2013-09-01

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

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

Science.gov (United States)

Jhin, Changho; Hwang, Keum Taek

2015-01-01

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

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

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Changho Jhin

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

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

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

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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.

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.

Fighting obesity or obese persons? Public perceptions of obesity-related health messages.

Science.gov (United States)

Puhl, R; Peterson, J L; Luedicke, J

2013-06-01

This study examined public perceptions of obesity-related public health media campaigns with specific emphasis on the extent to which campaign messages are perceived to be motivating or stigmatizing. In summer 2011, data were collected online from a nationally representative sample of 1014 adults. Participants viewed a random selection of 10 (from a total of 30) messages from major obesity public health campaigns from the United States, the United Kingdom and Australia, and rated each campaign message according to positive and negative descriptors, including whether it was stigmatizing or motivating. Participants also reported their familiarity with each message and their intentions to comply with the message content. Participants responded most favorably to messages involving themes of increased fruit and vegetable consumption, and general messages involving multiple health behaviors. Messages that have been publicly criticized for their stigmatizing content received the most negative ratings and the lowest intentions to comply with message content. Furthermore, messages that were perceived to be most positive and motivating made no mention of the word 'obesity' at all, and instead focused on making healthy behavioral changes without reference to body weight. These findings have important implications for framing messages in public health campaigns to address obesity, and suggest that certain types of messages may lead to increased motivation for behavior change among the public, whereas others may be perceived as stigmatizing and instill less motivation to improve health.

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

DEFF Research Database (Denmark)

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

2013-01-01

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

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

NARCIS (Netherlands)

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

2005-01-01

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

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

DEFF Research Database (Denmark)

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

2017-01-01

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

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

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

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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.

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

Science.gov (United States)

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

2018-03-01

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

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

DEFF Research Database (Denmark)

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

2013-01-01

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

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.

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.

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.

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2008-06-01

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

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.

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.

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

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.

Public humanization policies: integrative literature review.

Science.gov (United States)

Moreira, Márcia Adriana Dias Meirelles; Lustosa, Abdon Moreira; Dutra, Fernando; Barros, Eveline de Oliveira; Batista, Jaqueline Brito Vidal; Duarte, Marcella Costa Souto

2015-10-01

The study aimed to investigate the scientific literature on Public Humanization Policies, available in online periodicals, from 2009 to 2012, in the health field. This is an integrative literature review conducted in the Virtual Health Library databases: Latin-America and Caribbean Health Sciences (Lilacs) and the Scientific Electronic Library Online (SciELO) and Portal Capes. Data were collected in July 2013. To this end, the following Health Sciences Descriptors (DeCS) were used: "Humanization of Care," "Public Policies," "National Humanization Policy". The sample consisted of 27 articles about the investigated theme. From the publications selected for the research, three categories emerged according to their respective approaches: National Human-ization Policy: history and processes involved in its implementation; National Humanization Policy: health professionals contribution; Humanization and in the care process. The study showed that the National Humanization Policy is an important benchmark in the development of health practices. For this reason, there is a pressing multiplication of related reflections on ways to promote human-ization in health services.

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

Science.gov (United States)

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

2015-06-01

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

Calculation of Quantitative Structure-Activity Relationship Descriptors of Artemisinin Derivatives

Directory of Open Access Journals (Sweden)

Jambalsuren Bayarmaa

2008-06-01

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

Universal fragment descriptors for predicting properties of inorganic crystals

Science.gov (United States)

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

2017-06-01

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

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.

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

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

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)

Molecular-orbital and structural descriptors in theoretical investigation of electroreduction of nitrodiazoles

Directory of Open Access Journals (Sweden)

BRANKO KOLARIC

2005-07-01

Full Text Available It is shown how a simple theoretical approach can be used for the investigation of electro-organic reactions.Mononitroimidazoles and mononitropyrazoles were studied by the semiempirical MNDO-PM3 molecular orbital method. The electrochemical reduction potentials of diazoles have been correlated with the energy of the lowest unoccupied molecular orbital (LUMO. It was found that an admirable correlation could be obtained by the introduction of simple structural descriptors as a correction to the energy of the LUMO. The interaction of a molecule with its surrounding depends on electrostatic potential and on steric hindrance. Most of these steric effects are taken into account using two parameters having a very limited set of integer values. The first (b is the position of a ring substituent regarding ring nitrogens, which accounts for the different orientations of dipole moments and for the different shape of the electrostatic potential. The second (structural parameter (t is the type of the ring, which accounts mostly for different modes of electrode approach, and for different charge polarization patterns in two diazole rings. The extended correlation with ELUMO, b and t, is very good, having a regression coefficient r = 0.991. The intrinsic importance of b and t is exemplified by their high statistical weight.

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

Science.gov (United States)

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

2012-07-01

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

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.

Multimodal image registration based on binary gradient angle descriptor.

Science.gov (United States)

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

2017-12-01

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

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

DEFF Research Database (Denmark)

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

2008-01-01

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

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

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

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

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

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

Science.gov (United States)

Cao, Zhicheng; Schmid, Natalia A.

2015-05-01

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

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...

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Trends in Type of Original Psoriasis Publications by Decade, 1960 to 2010.

Science.gov (United States)

Sako, Eric; Famenini, Shannon; Wu, Jashin J

2016-01-01

Research investigating psoriasis has spanned decades, and as our understanding of the disease has evolved, the focus of publications has changed. We sought to characterize the trends in original psoriasis-related research from 1960 to 2010 chronologically by decade. A literature review was performed using the keyword psoriasis in the MEDLINE database. All original psoriasis-related articles published at the beginning of each decade were searched and categorized by study type and topic. Number of articles per topic. A total of 869 original psoriasis-related articles were found. The number of publications increased 18 fold over 5 decades. The immunology and pathogenesis of psoriasis was the most frequently researched topic (36%), and retrospective studies were the most common study type (37%). Recent highly published topics included biologic therapy, genetics, and psoriasis-associated cardiovascular disease. Original psoriasis-related publications have grown substantially since 1960. Basic science research into the immunology and pathogenesis has been and continues to be the mainstay of psoriasis research. Recent research trends suggest the focus has expanded to topics such as psoriasis-associated cardiovascular disease, genetics, and biologic therapy.

Scale Invariant Gabor Descriptor-Based Noncooperative Iris Recognition

Directory of Open Access Journals (Sweden)

Du Yingzi

2010-01-01

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

Scale Invariant Gabor Descriptor-based Noncooperative Iris Recognition

Directory of Open Access Journals (Sweden)

Zhi Zhou

2010-01-01

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

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

Directory of Open Access Journals (Sweden)

Baoyan Zhu

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Minh-Tan Pham

2016-04-01

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

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.

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

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

OpenAIRE

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

2016-01-01

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

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

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

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.

Towards a Holistic Cortical Thickness Descriptor: Heat Kernel-Based Grey Matter Morphology Signatures.

Science.gov (United States)

Wang, Gang; Wang, Yalin

2017-02-15

In this paper, we propose a heat kernel based regional shape descriptor that may be capable of better exploiting volumetric morphological information than other available methods, thereby improving statistical power on brain magnetic resonance imaging (MRI) analysis. The mechanism of our analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral meshes. In order to capture profound brain grey matter shape changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between white-grey matter and CSF-grey matter boundary surfaces by computing the streamlines in a tetrahedral mesh. Secondly, we propose multi-scale grey matter morphology signatures to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the grey matter morphology signatures and generate the internal structure features. With the sparse linear discriminant analysis, we select a concise morphology feature set with improved classification accuracies. In our experiments, the proposed work outperformed the cortical thickness features computed by FreeSurfer software in the classification of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, on publicly available data from the Alzheimer's Disease Neuroimaging Initiative. The multi-scale and physics based volumetric structure feature may bring stronger statistical power than some traditional methods for MRI-based grey matter morphology analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2017-07-01

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

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.

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

Science.gov (United States)

Senet, P; Aparicio, F

2007-04-14

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

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. �

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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 ...

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

Directory of Open Access Journals (Sweden)

Yuan Xu

2015-01-01

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

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.

DESCRIPTION OF THE BUDGET CONTROL TYPES IN MODERN CONDITIONS OF PUBLIC FINANCE MANAGEMENT

Directory of Open Access Journals (Sweden)

Nataliya Melnichuk

2016-11-01

Full Text Available The article highlights the essence of budgetary control. The features of control in the public sector performance are grounded as well as the relationship between verifiability and the controllability. It is proved that the achievement of public finance management needs its controllability. There is no alternative verifiability by ensuring controllability of budget resources. The classification criteria of budgetary control types according to the different classification criteria are developed. It has allowed to distinguish its following types: scheduled, unscheduled, previous, current, next, state, municipal, specialized, departmental, public, external, internal, solid, selective, comprehensive, effective, ineffective, centralized, decentralized, legislative, realizable, further, active, passive, available, projected, intermediate, final, mixed. The purpose of the article is to provide a classification criteria of budgetary control development, taking into account the role and functions of control in public finance management. The subject of the study is a set of financial relationships arising during the budgetary control due to appropriation of financial resources. Methodology. The following methods have been used in the process of writing: cognition, induction, deduction, analysis and synthesis. Results of the survey. Thus, the main directions of budgetary control implementation we can consider the following ones: monitoring compliance with procedures for preparation, review and approval of state and local budgets; the implementation of revenue and expenditure of the budget at the national and local levels control; detection of theft of public funds, as well as their misuse; accuracy of accounting control; increasing the revenue base of the state budget detection; preventive measures to combat corruption and bribery in the public sector. The author’s approach to classification criteria of budgetary control types, unlike existing ones

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.

Pattern and intensity of human impact on coral reefs depend on depth along the reef profile and on the descriptor adopted

Science.gov (United States)

Nepote, Ettore; Bianchi, Carlo Nike; Chiantore, Mariachiara; Morri, Carla; Montefalcone, Monica

2016-09-01

Coral reefs are threatened by multiple global and local disturbances. The Maldives, already heavily hit by the 1998 mass bleaching event, are currently affected also by growing tourism and coastal development that may add to global impacts. Most of the studies investigating effects of local disturbances on coral reefs assessed the response of communities along a horizontal distance from the impact source. This study investigated the status of a Maldivian coral reef around an island where an international touristic airport has been recently (2009-2011) built, at different depths along the reef profile (5-20 m depth) and considering the change in the percentage of cover of five different non-taxonomic descriptors assessed through underwater visual surveys: hard corals, soft corals, other invertebrates, macroalgae and abiotic attributes. Eight reefs in areas not affected by any coastal development were used as controls and showed a reduction of hard coral cover and an increase of abiotic attributes (i.e. sand, rock, coral rubble) at the impacted reef. However, hard coral cover, the most widely used descriptor of coral reef health, was not sufficient on its own to detect subtle indirect effects that occurred down the reef profile. Selecting an array of descriptors and considering different depths, where corals may find a refuge from climate impacts, could guide the efforts of minimising local human pressures on coral reefs.

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.

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

Science.gov (United States)

Magnusson, Jane E; Fennell, Joyce A

2011-01-21

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

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

Science.gov (United States)

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

2004-03-01

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

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.

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.

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.

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

Science.gov (United States)

Rabal, Obdulia; Oyarzabal, Julen

2012-05-25

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

Sex education in the pedagogical practice of public school teachers

Directory of Open Access Journals (Sweden)

Camila Borges Rufino

2013-12-01

Full Text Available This descriptive study was performed with 29 teachers from three public state schools in Goiânia, Goiás state. The teachers answered a semi-structured questionnaire that aimed at verifying the pedagogical practice in sex education, difficulties related to the theme, and the need for training. Most teachers were male (69% and aged between 25 and 35 years (74%. Half held a graduate degree (54% in human sciences (49%. Nearly all teachers find difficulties in working the topic (89% and need training (93%. Contents on sexuality were not addressed in the Political Pedagogical Projects (76% and the biology program aimed at teaching the theme (55%, a reality that disagrees with the National Curricular Standards, which is based on transversality. Partnerships between health and education must be established, particularly between the Family Health Strategy the higher education institutions, providing public school teachers with the necessary didactic-pedagogical support to address sexuality in the classroom. Descriptors: Sexuality; Schools; Nursing; Public Health.

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.

Augmented Topological Descriptors of Pore Networks for Material Science.

Science.gov (United States)

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

2012-12-01

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

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

Science.gov (United States)

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

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...

Oriented Edge-Based Feature Descriptor for Multi-Sensor Image Alignment and Enhancement

Directory of Open Access Journals (Sweden)

Myung-Ho Ju

2013-10-01

Full Text Available In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multi-sensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enables fast image alignment by identifying matching features in multi-sensor images. We enhance the aligned multi-sensor images through the fusion of the salient regions from each image. The results of stitching the multi-sensor images and their enhancement demonstrate that our proposed method can align and enhance multi-sensor images more efficiently than previous methods.

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

on agronomic and morphological discriminators to detect genetic heterogeneity, although with reduced sensitivity compared with microsatellite markers. These results also suggest that grouping ensuing from either approach could reflect distinct patterns of diversity (due to different mutation rates...... 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...

PSYCHO-LEGAL PUBLICATIONS ABOUT PARENTAL ALIENATION: AN INTEGRATIVE REVIEW OF LITERATURE IN PORTUGUESE

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Josimar Antônio de Alcântara Mendes

2016-07-01

Full Text Available After the enactment of Law No. 12,318 in 2010, awareness and discussion of Parental Alienation - AP increased not only in the psycho-legal context, but also social. This phenomenon also reflected in academic publications on the subject. This article analysed the publications on Parental Alienation, in Portuguese, between the years 2008 and 2014 in order to investigate the scientific quality of journals - based on the Qualis CAPES system, and the issues associated with the theme. 816 results were found with the descriptor "parental alienation" with a significant increase after 2010. Based on the inclusion and exclusion criteria, 29 articles followed for further analysis. Of these, 80% were publications of law, only 6.7% were empirical, 86% corroborated with the postulates of AP and ¾ were among the strata B4 and C. The most associated issues were slopes memories and / or sexual abuse allegations (42% and shared custody (12%. The study concluded that there are many publications on the subject, but there are also publications in Portuguese, a deficit in term structure, methodology and scientific rigor.

Uso de descritores de dispneia desenvolvidos no Brasil em pacientes com doenças cardiorrespiratórias ou obesidade Dyspnea descriptors developed in Brazil: application in obese patients and in patients with cardiorespiratory diseases

Directory of Open Access Journals (Sweden)

Christiane Aires Teixeira

2011-08-01

Full Text Available OBJETIVO: Desenvolver um conjunto de termos descritores de dispneia para uso no Brasil. Investigar a utilidade desses descritores em quatro condições distintas que cursam com dispneia. MÉTODOS: Um conjunto de 111 frases descritivas da sensação de falta de ar foi coletado a partir das informações de 67 pacientes e de 10 profissionais da saúde. Tais frases foram analisadas e reduzidas a 15 expressões, em função de sua frequência de citação, similaridade de significados e potencial importância fisiopatológica. O conjunto de expressões foi aplicado a 50 pacientes com asma, 50 com DPOC, 30 com insuficiência cardíaca e 50 com obesidade graus II ou III. Os três melhores termos selecionados pelos pacientes foram estudados por análise de agrupamentos. Também foram investigadas as possíveis associações entre os agrupamentos encontrados e as quatro condições clínicas incluídas. RESULTADOS: O emprego dessa lista de descritores levou a uma solução com sete agrupamentos, denominados sufoco, aperto, rápido, fadiga, abafado, trabalho/inspiração e falta de ar. Houve grande superposição no uso de descritores pelos pacientes com as quatro condições clínicas. A asma mostrou associações expressivas com sufoco e trabalho/inspiração, enquanto DPOC e insuficiência cardíaca, com sufoco, trabalho/inspiração e falta de ar; e obesidade, com falta de ar apenas. CONCLUSÕES: Pacientes no Brasil habituados a sentir dispneia utilizam diferentes termos para descrever seu sintoma, e tais descrições podem ser agrupadas em conjuntos por similaridade. Tais agrupamentos não mostraram utilidade na distinção diagnóstica entre os grupos avaliados neste estudo.OBJECTIVE: To develop a set of descriptive terms applied to the sensation of dyspnea (dyspnea descriptors for use in Brazil and to investigate the usefulness of these descriptors in four distinct clinical conditions that can be accompanied by dyspnea. METHODS: We collected 111

Ship recognition for improved persistent tracking with descriptor localization and compact representations

Science.gov (United States)

van den Broek, Sebastiaan P.; Bouma, Henri; den Hollander, Richard J. M.; Veerman, Henny E. T.; Benoist, Koen W.; Schwering, Piet B. W.

2014-10-01

For maritime situational awareness, it is important to identify currently observed ships as earlier encounters. For example, past location and behavior analysis are useful to determine whether a ship is of interest in case of piracy and smuggling. It is beneficial to verify this with cameras at a distance, to avoid the costs of bringing an own asset closer to the ship. The focus of this paper is on ship recognition from electro-optical imagery. The main contribution is an analysis of the effect of using the combination of descriptor localization and compact representations. An evaluation is performed to assess the usefulness in persistent tracking, especially for larger intervals (i.e. re-identification of ships). From the evaluation on recordings of imagery, it is estimated how well the system discriminates between different ships.

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-10-15

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

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.

Cellular automata rule characterization and classification using texture descriptors

Science.gov (United States)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes

DEFF Research Database (Denmark)

Bonàs-Guarch, Sílvia; Guindo-Martínez, Marta; Miguel-Escalada, Irene

2018-01-01

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel...... available data using novel genetic resources and analytical approaches....... associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly...

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

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...... 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...

How professionals perceive types of risk in public service innovation: Reports from Copenhagen municipality

DEFF Research Database (Denmark)

Timeus, Krista; Ricard, Lykke Margot

The paper addresses two questions; what do professionals working in the public administration understand by ‘risk’ in relation to their work on innovation?; and how do these professionals understand their own role in managing risks of innovation? The paper takes an inductive approach and focuses....... In the last five years, Copenhagen municipality has implemented programmes and partnerships for innovation, especially in social services, such as a new ‘innovation house’ to coordinate the municipality’s innovation strategy across all administrative departments. This context makes it a suitable case to study...... on individuals, namely, professionals in Copenhagen municipality working on public services innovation. Such innovation includes new services or new methods of service delivery. Although all types of innovation include some risk, in public services, risks are exacerbated by the vulnerability of many users...

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

Directory of Open Access Journals (Sweden)

B. Souyei

2013-12-01

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

A visual perceptual descriptor with depth feature for image retrieval

Science.gov (United States)

Wang, Tianyang; Qin, Zhengrui

2017-07-01

This paper proposes a visual perceptual descriptor (VPD) and a new approach to extract perceptual depth feature for 2D image retrieval. VPD mimics human visual system, which can easily distinguish regions that have different textures, whereas for regions which have similar textures, color features are needed for further differentiation. We apply VPD on the gradient direction map of an image, capture texture-similar regions to generate a VPD map. We then impose the VPD map on a quantized color map and extract color features only from the overlapped regions. To reflect the nature of perceptual distance in single 2D image, we propose and extract the perceptual depth feature by computing the nuclear norm of the sparse depth map of an image. Extracted color features and the perceptual depth feature are both incorporated to a feature vector, we utilize this vector to represent an image and measure similarity. We observe that the proposed VPD + depth method achieves a promising result, and extensive experiments prove that it outperforms other typical methods on 2D image retrieval.

Phenotypic characterization of glioblastoma identified through shape descriptors

Science.gov (United States)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

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

Quality descriptors of optical beams based on centred reduced moments I spot analysis

CERN Document Server

Castaneda, R; García-Sucerquia, J

2003-01-01

A method for analyzing beam spots is discussed. It is based on the central reduced moments of the spot and its associated density functions. These functions allow us to separately analyze specific spot fractions, in such a way that specific combinations of higher order moments can be interpreted as coordinates of their centre of mass and the length and orientations of their principal axis. So, the descriptors of the associated density functions deal with the quantitative estimation of spot features, such as coma-like and astigmatism-like distortions. To assure high accuracy, background noise suppression and an optimal match of the spot support onto the region [-1,1]x[- 1,1] are performed prior to the calculation of the moments. Simulations were performed for illustrating the method.

Is Electronegativity a Useful Descriptor for the 'Pseudo-Alkali-Metal' NH4?

International Nuclear Information System (INIS)

Whiteside, Alexander; Xantheas, Sotiris S.; Gutowski, Maciej S.

2011-01-01

Molecular ions in the form of 'pseudo-atoms' are common structural motifs in chemistry, with properties that are transferrable between different compounds. We have determined the electronegativity of the 'pseudo-alkali metal' ammonium (NH4) and evaluated its reliability as a descriptor in comparison to the electronegativities of the alkali metals. The computed properties of its binary complexes with astatine and of selected borohydrides confirm the similarity of NH4 to the alkali metal atoms, although the electronegativity of NH4 is relatively large in comparison to its cationic radius. We paid particular attention to the molecular properties of ammonium (angular anisotropy, geometric relaxation, and reactivity), which can cause deviations from the behaviour expected of a conceptual 'true alkali metal' with this electronegativity. These deviations allow for the discrimination of effects associated with the polyatomic nature of NH4.

Resistance and resilience of ecosystem descriptors and properties to dystrophic events: a study case in a Mediterranean lagoon

OpenAIRE

Basset, Alberto; Barbone, Enrico; Rosati, Ilaria; Vignes, Fabio; Breber, Paolo; Specchiulli, Antonietta; D'Adamo, Raffaele; Renzi, Monia; Focardi, Silvano; Ungaro, Nicola; Pinna, Maurizio

2013-01-01

Mediterranean lagoons are naturally exposed, during the dry season, to dystrophic and hypoxic events determining dis-equilibrium conditions along temporal and spatial scales, which are linked to metabolism and life cycle of the biotic components. In summer 2008, Lesina lagoon (SE Italian coastline) was interested by a geographically localized dystrophic crisis which affected up to 8% of the total lagoon surface. Temporal dynamics of principal descriptors of abiotic (water, sediment) and bioti...

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.

External validation of a publicly available computer assisted diagnostic tool for mammographic mass lesions with two high prevalence research datasets.

Science.gov (United States)

Benndorf, Matthias; Burnside, Elizabeth S; Herda, Christoph; Langer, Mathias; Kotter, Elmar

2015-08-01

Lesions detected at mammography are described with a highly standardized terminology: the breast imaging-reporting and data system (BI-RADS) lexicon. Up to now, no validated semantic computer assisted classification algorithm exists to interactively link combinations of morphological descriptors from the lexicon to a probabilistic risk estimate of malignancy. The authors therefore aim at the external validation of the mammographic mass diagnosis (MMassDx) algorithm. A classification algorithm like MMassDx must perform well in a variety of clinical circumstances and in datasets that were not used to generate the algorithm in order to ultimately become accepted in clinical routine. The MMassDx algorithm uses a naïve Bayes network and calculates post-test probabilities of malignancy based on two distinct sets of variables, (a) BI-RADS descriptors and age ("descriptor model") and (b) BI-RADS descriptors, age, and BI-RADS assessment categories ("inclusive model"). The authors evaluate both the MMassDx (descriptor) and MMassDx (inclusive) models using two large publicly available datasets of mammographic mass lesions: the digital database for screening mammography (DDSM) dataset, which contains two subsets from the same examinations-a medio-lateral oblique (MLO) view and cranio-caudal (CC) view dataset-and the mammographic mass (MM) dataset. The DDSM contains 1220 mass lesions and the MM dataset contains 961 mass lesions. The authors evaluate discriminative performance using area under the receiver-operating-characteristic curve (AUC) and compare this to the BI-RADS assessment categories alone (i.e., the clinical performance) using the DeLong method. The authors also evaluate whether assigned probabilistic risk estimates reflect the lesions' true risk of malignancy using calibration curves. The authors demonstrate that the MMassDx algorithms show good discriminatory performance. AUC for the MMassDx (descriptor) model in the DDSM data is 0.876/0.895 (MLO/CC view) and AUC

Statistical region based active contour using a fractional entropy descriptor: Application to nuclei cell segmentation in confocal \\ud microscopy images

OpenAIRE

Histace, A; Meziou, B J; Matuszewski, Bogdan; Precioso, F; Murphy, M F; Carreiras, F

2013-01-01

We propose an unsupervised statistical region based active contour approach integrating an original fractional entropy measure for image segmentation with a particular application to single channel actin tagged fluorescence confocal microscopy image segmentation. Following description of statistical based active contour segmentation and the mathematical definition of the proposed fractional entropy descriptor, we demonstrate comparative segmentation results between the proposed approach and s...

Shor-Preskill-type security proof for quantum key distribution without public announcement of bases

International Nuclear Information System (INIS)

Hwang, Won-Young; Wang Xiangbin; Matsumoto, Keiji; Kim, Jaewan; Lee, Hai-Woong

2003-01-01

We give a Shor-Preskill-type security proof to quantum key distribution without public announcement of bases [W.Y. Hwang et al., Phys. Lett. A 244, 489 (1998)]. First, we modify the Lo-Chau protocol once more so that it finally reduces to the quantum key distribution without public announcement of bases. Then we show how we can estimate the error rate in the code bits based on that in the checked bits in the proposed protocol, which is the central point of the proof. We discuss the problem of imperfect sources and that of large deviation in the error rate distributions. We discuss when the bases sequence must be discarded

Quality descriptors of optical beams based on centred reduced moments I: spot analysis

International Nuclear Information System (INIS)

Castaneda, Roman; Garcia-Sucerquia, Jorge; Brand, Frank

2003-03-01

A method for analyzing beam spots is discussed. It is based on the central reduced moments of the spot and its associated density functions. These functions allow us to separately analyze specific spot fractions, in such a way that specific combinations of higher order moments can be interpreted as coordinates of their centre of mass and the length and orientations of their principal axis. So, the descriptors of the associated density functions deal with the quantitative estimation of spot features, such as coma-like and astigmatism-like distortions. To assure high accuracy, background noise suppression and an optimal match of the spot support onto the region [-1,1]x[- 1,1] are performed prior to the calculation of the moments. Simulations were performed for illustrating the method. (author)

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.

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

Science.gov (United States)

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

2017-03-01

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

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.

Variational 3D-PIV with sparse descriptors

Science.gov (United States)

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

2018-06-01

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

Evaluating Learner Autonomy: A Dynamic Model with Descriptors

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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.

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

Science.gov (United States)

Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

2010-06-01

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

Racial Mismatch and School Type: Teacher Satisfaction and Retention in Charter and Traditional Public Schools

Science.gov (United States)

Renzulli, Linda A.; Parrott, Heather Macpherson; Beattie, Irenee R.

2011-01-01

Studies of teacher satisfaction suggest that satisfaction is related to both the racial composition and the organizational structure of the schools in which teachers work. In this article, the authors draw from theories of race and organizations to examine simultaneously the effects of school type (traditional public vs. charter) and racial…

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.

Quantification of the level descriptors for the standard EQ-5D three-level system and a five-level version according to two methods

NARCIS (Netherlands)

M.F. Janssen (Bas); E. Birnie (Erwin); G.J. Bonsel (Gouke)

2008-01-01

textabstractObjectives: Our aim was to compare the quantitative position of the level descriptors of the standard EQ-5D three-level system (3L) and a newly developed, experimental five-level version (5L) using a direct and a vignette-based indirect method. Methods: Eighty-two respondents took part

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

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

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

Kompensasi Kesalahan Sensor Berbasis Descriptor dengan Performa H_inf pada Winding Machine

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Hendra Antomy

2015-12-01

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

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

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

2008-04-01

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

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

OpenAIRE

Morteza Atabati; Kobra Zarei; Azam Borhani

2016-01-01

Quantitative structure–property relationship (QSPR) studies based on ant colony optimization (ACO) were carried out for the prediction of λmax of 9,10-anthraquinone derivatives. ACO is a meta-heuristic algorithm, which is derived from the observation of real ants and proposed to feature selection. After optimization of 3D geometry of structures by the semi-empirical quantum-chemical calculation at AM1 level, different descriptors were calculated by the HyperChem and Dragon softwares (1514 des...

Citation success of different publication types: a case study on all references in psychology publications from the German-speaking countries (D-A-CH-L-L) in 2009, 2010, and 2011.

Science.gov (United States)

Krampen, Günter; Weiland, Peter; Wiesenhütter, Jürgen

Scientometric data on the citation success of different publication types and publication genres in psychology publications are presented. Data refer to references that are cited in these scientific publications and that are documented in PSYNDEX, the exhaustive database of psychology publications from the German-speaking countries either published in German or in English language. Firstly, data analyses refer to the references that are cited in publications of 2009 versus 2010 versus 2011. With reference to all cited references, the portion of journal articles ranges from 57 to 61 %, of books from 22 to 24 %, and of book chapters from 14 to 15 %, with a rather high stability across the three publication years analysed. Secondly, data analyses refer to the numbers of cited references from the German-speaking countries, which are also documented in PSYNDEX. These compose about 11 % of all cited references indicating that nearly 90 % of the references cited are of international and/or interdisciplinary publications not stemming from the German-speaking countries. The subsample shows the proportion of journal articles, books, and chapters, and these are very similar to the percentages identified for all references that are cited. Thirdly, analyses refer to document type, scientific genre, and psychological sub-discipline of the most frequently cited references in the psychology publications. The frequency of top-cited references of books and book chapters is almost equal to that of journal articles; two-thirds of the top-cited references are non-empirical publications, only one-third are empirical publications. Top-cited references stem particularly from clinical psychology, experimental psychology, as well as tests, testing and psychometrics. In summary, the results point to the fact that citation analyses, which are limited to journal papers, tend to neglect very high portions of references that are cited in scientific publications.

Quantification of the level descriptors for the standard EQ-5D three-level system and a five-level version according to two methods

NARCIS (Netherlands)

Janssen, M. F.; Birnie, E.; Bonsel, G. J.

2008-01-01

OBJECTIVES: Our aim was to compare the quantitative position of the level descriptors of the standard EQ-5D three-level system (3L) and a newly developed, experimental five-level version (5L) using a direct and a vignette-based indirect method. METHODS: Eighty-two respondents took part in the study.

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

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

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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.

Development of an online, publicly accessible naive Bayesian decision support tool for mammographic mass lesions based on the American College of Radiology (ACR) BI-RADS lexicon

Energy Technology Data Exchange (ETDEWEB)

Benndorf, Matthias; Kotter, Elmar; Langer, Mathias [University Hospital Freiburg, Department of Radiology, Freiburg (Germany); Herda, Christoph [Kantonsspital Graubuenden, Chur (Switzerland); Wu, Yirong; Burnside, Elizabeth S. [University of Wisconsin-Madison School of Medicine and Public Health, Department of Radiology, Madison, WI (United States)

2015-06-01

To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. We used separate training data (1,276 lesions, 138 malignant) and validation data (1,177 lesions, 175 malignant). We created naive Bayes (NB) classifiers from the training data with tenfold cross-validation. Our ''inclusive model'' comprised BI-RADS categories, BI-RADS descriptors, and age as predictive variables; our ''descriptor model'' comprised BI-RADS descriptors and age. The resulting NB classifiers were applied to the validation data. We evaluated and compared classifier performance with ROC-analysis. In the training data, the inclusive model yields an AUC of 0.959; the descriptor model yields an AUC of 0.910 (P < 0.001). The inclusive model is superior to the clinical performance (BI-RADS categories alone, P < 0.001); the descriptor model performs similarly. When applied to the validation data, the inclusive model yields an AUC of 0.935; the descriptor model yields an AUC of 0.876 (P < 0.001). Again, the inclusive model is superior to the clinical performance (P < 0.001); the descriptor model performs similarly. We consider our classifier a step towards a more uniform interpretation of combinations of BI-RADS descriptors. We provide our classifier at www.ebm-radiology.com/nbmm/index.html. (orig.)

Development of an online, publicly accessible naive Bayesian decision support tool for mammographic mass lesions based on the American College of Radiology (ACR) BI-RADS lexicon

International Nuclear Information System (INIS)

Benndorf, Matthias; Kotter, Elmar; Langer, Mathias; Herda, Christoph; Wu, Yirong; Burnside, Elizabeth S.

2015-01-01

To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. We used separate training data (1,276 lesions, 138 malignant) and validation data (1,177 lesions, 175 malignant). We created naive Bayes (NB) classifiers from the training data with tenfold cross-validation. Our ''inclusive model'' comprised BI-RADS categories, BI-RADS descriptors, and age as predictive variables; our ''descriptor model'' comprised BI-RADS descriptors and age. The resulting NB classifiers were applied to the validation data. We evaluated and compared classifier performance with ROC-analysis. In the training data, the inclusive model yields an AUC of 0.959; the descriptor model yields an AUC of 0.910 (P < 0.001). The inclusive model is superior to the clinical performance (BI-RADS categories alone, P < 0.001); the descriptor model performs similarly. When applied to the validation data, the inclusive model yields an AUC of 0.935; the descriptor model yields an AUC of 0.876 (P < 0.001). Again, the inclusive model is superior to the clinical performance (P < 0.001); the descriptor model performs similarly. We consider our classifier a step towards a more uniform interpretation of combinations of BI-RADS descriptors. We provide our classifier at www.ebm-radiology.com/nbmm/index.html. (orig.)

A Generally Applicable Computer Algorithm Based on the Group Additivity Method for the Calculation of Seven Molecular Descriptors: Heat of Combustion, LogPO/W, LogS, Refractivity, Polarizability, Toxicity and LogBB of Organic Compounds; Scope and Limits of Applicability

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Rudolf Naef

2015-10-01

Full Text Available A generally applicable computer algorithm for the calculation of the seven molecular descriptors heat of combustion, logPoctanol/water, logS (water solubility, molar refractivity, molecular polarizability, aqueous toxicity (protozoan growth inhibition and logBB (log (cblood/cbrain is presented. The method, an extendable form of the group-additivity method, is based on the complete break-down of the molecules into their constituting atoms and their immediate neighbourhood. The contribution of the resulting atom groups to the descriptor values is calculated using the Gauss-Seidel fitting method, based on experimental data gathered from literature. The plausibility of the method was tested for each descriptor by means of a k-fold cross-validation procedure demonstrating good to excellent predictive power for the former six descriptors and low reliability of logBB predictions. The goodness of fit (Q2 and the standard deviation of the 10-fold cross-validation calculation was >0.9999 and 25.2 kJ/mol, respectively, (based on N = 1965 test compounds for the heat of combustion, 0.9451 and 0.51 (N = 2640 for logP, 0.8838 and 0.74 (N = 1419 for logS, 0.9987 and 0.74 (N = 4045 for the molar refractivity, 0.9897 and 0.77 (N = 308 for the molecular polarizability, 0.8404 and 0.42 (N = 810 for the toxicity and 0.4709 and 0.53 (N = 383 for logBB. The latter descriptor revealing a very low Q2 for the test molecules (R2 was 0.7068 and standard deviation 0.38 for N = 413 training molecules is included as an example to show the limits of the group-additivity method. An eighth molecular descriptor, the heat of formation, was indirectly calculated from the heat of combustion data and correlated with published experimental heat of formation data with a correlation coefficient R2 of 0.9974 (N = 2031.

[Bibliometric study of scientific output published by the Revista Panamericana de Salud Pública/Pan American Journal of Public Health from 1997-2012].

Science.gov (United States)

Sanz-Valero, Javier; Casterá, Vicente Tomás; Wanden-Berghe, Carmina

2014-02-01

To characterize the scientific output of the Revista Panamericana de Salud Pública/Pan American Journal of Public Health (RPSP) as a scientific publication of reference in the public health sector in the Americas. A descriptive cross-sectional study was conducted based on the articles published in the RPSP from 1997-2012. Bibliometric indicators of productivity (documents published, languages, authorship, and indices of productivity and collaboration); impact (impact factor according to the SciELO Network, Journal Citation Report and SCImago); key words; and bibliographic references, their structure (document type and main nucleus of Bradford) and degree of obsolescence (Burton and Kebler half-life, and Price index), were analyzed. A total of 2 815 articles with a median of 3 authors and 2 institutions per article were published. The percentage of original research articles increased in 2008-2012 compared to 2003-2007 and 1997-2002 (P < 0.001). The predominant language was Spanish, displaced by English in the last 5 years. A total of 88.76% of the key words referred to the Health Sciences Descriptors (DeCS) and had a public health and community orientation related to the Americas. The Burton and Kebler half-life of bibliographic references was 8 years, although it decreased to 5 years in 2012. The Price index was 20.47% and the nucleus of Bradford was made up of 20 mainstream journals. The percentage of self-citation was low (2.07%). The RPSP is an international publication with bibliometric indicators similar to those of the most representative Latin American health science journals, with improvements in the recent years studied that lead it to fully meet international publishing criteria.

Finger Vein Recognition Using Optimal Partitioning Uniform Rotation Invariant LBP Descriptor

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Bang Chao Liu

2016-01-01

Full Text Available As a promising biometric system, finger vein identification has been studied widely and many relevant researches have been proposed. However, it is hard to extract a satisfied finger vein pattern due to the various vein thickness, illumination, low contrast region, and noise existing. And most of the feature extraction algorithms rely on high-quality finger vein database and take a long time for a large dimensional feature vector. In this paper, we proposed two block selection methods which are based on the estimate of the amount of information in each block and the contribution of block location by looking at recognition rate of each block position to reduce feature extraction time and matching time. The specific approach is to find out some local finger vein areas with low-quality and noise, which will be useless for feature description. Local binary pattern (LBP descriptors are proposed to extract the finger vein pattern feature. Two finger vein databases are taken to test our algorithm performance. Experimental results show that proposed block selection algorithms can reduce the feature vector dimensionality in a large extent.

Structural details (kinks and non-α conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors

Science.gov (United States)

Rigoutsos, Isidore; Riek, Peter; Graham, Robert M.; Novotny, Jiri

2003-01-01

One of the promising methods of protein structure prediction involves the use of amino acid sequence-derived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular α-helical character (i.e. π-helices, 310-helices and kinks). A ‘search engine’ derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above ‘non-canonical’ helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from α-helicity are encoded locally in sequence patterns only about 7–9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure–function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html. PMID:12888523

Structural details (kinks and non-alpha conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors.

Science.gov (United States)

Rigoutsos, Isidore; Riek, Peter; Graham, Robert M; Novotny, Jiri

2003-08-01

One of the promising methods of protein structure prediction involves the use of amino acid sequence-derived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular alpha-helical character (i.e. pi-helices, 3(10)-helices and kinks). A 'search engine' derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above 'non-canonical' helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from alpha-helicity are encoded locally in sequence patterns only about 7-9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure-function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html.

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

Science.gov (United States)

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

2014-12-01

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

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

Science.gov (United States)

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

2006-11-01

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

Potential for protein surface shape analysis using spherical harmonics and 3D Zernike descriptors.

Science.gov (United States)

Venkatraman, Vishwesh; Sael, Lee; Kihara, Daisuke

2009-01-01

With structure databases expanding at a rapid rate, the task at hand is to provide reliable clues to their molecular function and to be able to do so on a large scale. This, however, requires suitable encodings of the molecular structure which are amenable to fast screening. To this end, moment-based representations provide a compact and nonredundant description of molecular shape and other associated properties. In this article, we present an overview of some commonly used representations with specific focus on two schemes namely spherical harmonics and their extension, the 3D Zernike descriptors. Key features and differences of the two are reviewed and selected applications are highlighted. We further discuss recent advances covering aspects of shape and property-based comparison at both global and local levels and demonstrate their applicability through some of our studies.

Simple thermal to thermal face verification method based on local texture descriptors

Science.gov (United States)

Grudzien, A.; Palka, Norbert; Kowalski, M.

2017-08-01

Biometrics is a science that studies and analyzes physical structure of a human body and behaviour of people. Biometrics found many applications ranging from border control systems, forensics systems for criminal investigations to systems for access control. Unique identifiers, also referred to as modalities are used to distinguish individuals. One of the most common and natural human identifiers is a face. As a result of decades of investigations, face recognition achieved high level of maturity, however recognition in visible spectrum is still challenging due to illumination aspects or new ways of spoofing. One of the alternatives is recognition of face in different parts of light spectrum, e.g. in infrared spectrum. Thermal infrared offer new possibilities for human recognition due to its specific properties as well as mature equipment. In this paper we present the scheme of subject's verification methodology by using facial images in thermal range. The study is focused on the local feature extraction methods and on the similarity metrics. We present comparison of two local texture-based descriptors for thermal 1-to-1 face recognition.

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

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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.

Pain intensity among institutionalized elderly: a comparison between numerical scales and verbal descriptors

Directory of Open Access Journals (Sweden)

Lílian Varanda Pereira

2015-10-01

Full Text Available AbstractOBJECTIVECorrelating two unidimensional scales for measurement of self-reported pain intensity for elderly and identifying a preference for one of the scales.METHODA study conducted with 101 elderly people living in Nursing Home who reported any pain and reached ( 13 the scores on the Mini-Mental State Examination. A Numeric Rating Scale - (NRS of 11 points and a Verbal Descriptor Scale (VDS of five points were compared in three evaluations: overall, at rest and during movement.RESULTSWomen were more representative (61.4% and the average age was 77.0±9.1 years. NRS was completed by 94.8% of the elderly while VDS by 100%. The association between the mean scores of NRS with the categories of VDS was significant, indicating convergent validity and a similar metric between the scales.CONCLUSIONPain measurements among institutionalized elderly can be made by NRS and VDS; however, the preferred scale for the elderly was the VDS, regardless of gender.

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

Science.gov (United States)

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2012-06-14

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

An Early Detection Method of Type-2 Diabetes Mellitus in Public Hospital

Directory of Open Access Journals (Sweden)

Hermansyah Hermansyah

2011-08-01

Full Text Available Diabetes is a chronic disease and major problem of morbidity and mortality in developing countries. The International Diabetes Federation estimates that 285 million people around the world have diabetes. This total is expected to rise to 438 million within 20 years. Type-2 diabetes mellitus (T2DM is the most common type of diabetes and accounts for 90-95% of all diabetes. Detection of T2DM from various factors or symptoms became an issue which was not free from false presumptions accompanied by unpredictable effects. According to this context, data mining and machine learning could be used as an alternative way help us in knowledge discovery from data. We applied several learning methods, such as instance based learners, naive bayes, decision tree, support vector machines, and boosted algorithm acquire information from historical data of patients medical records of Mohammad Hoesin public hospital in Southern Sumatera. Rules are extracted from Decision tree to offer decision-making support through early detection of T2DM for clinicians.

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...

Low Dimensional Representation of Fisher Vectors for Microscopy Image Classification.

Science.gov (United States)

Song, Yang; Li, Qing; Huang, Heng; Feng, Dagan; Chen, Mei; Cai, Weidong

2017-08-01

Microscopy image classification is important in various biomedical applications, such as cancer subtype identification, and protein localization for high content screening. To achieve automated and effective microscopy image classification, the representative and discriminative capability of image feature descriptors is essential. To this end, in this paper, we propose a new feature representation algorithm to facilitate automated microscopy image classification. In particular, we incorporate Fisher vector (FV) encoding with multiple types of local features that are handcrafted or learned, and we design a separation-guided dimension reduction method to reduce the descriptor dimension while increasing its discriminative capability. Our method is evaluated on four publicly available microscopy image data sets of different imaging types and applications, including the UCSB breast cancer data set, MICCAI 2015 CBTC challenge data set, and IICBU malignant lymphoma, and RNAi data sets. Our experimental results demonstrate the advantage of the proposed low-dimensional FV representation, showing consistent performance improvement over the existing state of the art and the commonly used dimension reduction techniques.

Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes.

Science.gov (United States)

Bonàs-Guarch, Sílvia; Guindo-Martínez, Marta; Miguel-Escalada, Irene; Grarup, Niels; Sebastian, David; Rodriguez-Fos, Elias; Sánchez, Friman; Planas-Fèlix, Mercè; Cortes-Sánchez, Paula; González, Santi; Timshel, Pascal; Pers, Tune H; Morgan, Claire C; Moran, Ignasi; Atla, Goutham; González, Juan R; Puiggros, Montserrat; Martí, Jonathan; Andersson, Ehm A; Díaz, Carlos; Badia, Rosa M; Udler, Miriam; Leong, Aaron; Kaur, Varindepal; Flannick, Jason; Jørgensen, Torben; Linneberg, Allan; Jørgensen, Marit E; Witte, Daniel R; Christensen, Cramer; Brandslund, Ivan; Appel, Emil V; Scott, Robert A; Luan, Jian'an; Langenberg, Claudia; Wareham, Nicholas J; Pedersen, Oluf; Zorzano, Antonio; Florez, Jose C; Hansen, Torben; Ferrer, Jorge; Mercader, Josep Maria; Torrents, David

2018-01-22

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662057, associated with a twofold increased risk for T2D in males. rs146662057 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches.

Report on research outline in 1999 fiscal year on public collection type research of nuclear fuel cycle.

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-07-01

The Japan Nuclear Cycle Development Institute (JNC) initiated a system to promote the public collection type researches of nuclear fuel cycle since 1999, in order to intend to promote collaboration with universities and research institutes. The system aims to intend to activate researching environment in JNC by intercourse, information exchange, publication of results and so on between researchers in and out of JNC, effectively to proceed basic and fundamental R and D. Here were outlined on eleven researching theme, such as upgrading of velocity and temperature measurement of non-contact type fluid by using electromagnetic ultrasonic wave, development of temperature history memory elements for radiation environment test of a fast breeder reactor, direct glassification of salt wastes by using oxygen plasma, a method on dissolving extraction of metal oxides by using a super-critical fluid, creation of highly separable materials by assistance of computational chemistry (aiming at high order processing of high level radioactive wastes), and so on. (G.K.)

Report on research outline in 1999 fiscal year on public collection type research of nuclear fuel cycle

International Nuclear Information System (INIS)

2000-07-01

The Japan Nuclear Cycle Development Institute (JNC) initiated a system to promote the public collection type researches of nuclear fuel cycle since 1999, in order to intend to promote collaboration with universities and research institutes. The system aims to intend to activate researching environment in JNC by intercourse, information exchange, publication of results and so on between researchers in and out of JNC, effectively to proceed basic and fundamental R and D. Here were outlined on eleven researching theme, such as upgrading of velocity and temperature measurement of non-contact type fluid by using electromagnetic ultrasonic wave, development of temperature history memory elements for radiation environment test of a fast breeder reactor, direct glassification of salt wastes by using oxygen plasma, a method on dissolving extraction of metal oxides by using a super-critical fluid, creation of highly separable materials by assistance of computational chemistry (aiming at high order processing of high level radioactive wastes), and so on. (G.K.)

Development of public health program for type 1 diabetes in a university community: preliminary evaluation of behavioural change wheel.

Science.gov (United States)

Nwose, Ezekiel Uba; Digban, K A; Anyasodor, A E; Bwititi, P T; Richards, R S; Igumbor, E O

2017-10-23

Diabetes mellitus, including type 1 is a global public health problem among the young persons. While public health campaign and screening program is a potential strategy, but communication skills, knowledge and opinion of the healthcare personnel are indicated as variables that can impact patient's education, which will lead to better outcome of care. Thus, in designing or planning a program for public health, workforce development considers opinion and behavioural change wheel of prospective personnel. The purpose of this preliminary study was to evaluate if a university academic department has the behavioural change wheel to function as workforce infrastructure for an envisioned program. Survey of knowledge, attitude and practice (KAP) of a university community regarding diabetes type 1 was performed. The KAP were translated into behavioural change wheel comprising capacity, motivation and opportunity (CMO). There are baseline indications of the behavioural change wheel potential of the public health department to run a T1D screening program. The number of participants who knew someone with T1D was significantly higher than the subgroup with no such knowledge (pwheel or CMO to develop a workforce infrastructure for T1D screening program, the experience that comes with age of lecturers will be an important factor to enable such program to succeed.

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

Science.gov (United States)

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

2011-09-01

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

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.

Protected area types, strategies and impacts in Brazil's Amazon: public protected area strategies do not yield a consistent ranking of protected area types by impact.

Science.gov (United States)

Pfaff, Alexander; Robalino, Juan; Sandoval, Catalina; Herrera, Diego

2015-11-05

The leading policy to conserve forest is protected areas (PAs). Yet, PAs are not a single tool: land users and uses vary by PA type; and public PA strategies vary in the extent of each type and in the determinants of impact for each type, i.e. siting and internal deforestation. Further, across regions and time, strategies respond to pressures (deforestation and political). We estimate deforestation impacts of PA types for a critical frontier, the Brazilian Amazon. We separate regions and time periods that differ in their deforestation and political pressures and document considerable variation in PA strategies across regions, time periods and types. The siting of PAs varies across regions. For example, all else being equal, PAs in the arc of deforestation are relatively far from non-forest, while in other states they are relatively near. Internal deforestation varies across time periods, e.g. it is more similar across the PA types for PAs after 2000. By contrast, after 2000, PA extent is less similar across PA types with little non-indigenous area created inside the arc. PA strategies generate a range of impacts for PA types--always far higher within the arc--but not a consistent ranking of PA types by impact. © 2015 The Author(s).

Public Service Motivation

Directory of Open Access Journals (Sweden)

Raluca-Marilena Mihalcioiu

2011-05-01

Full Text Available Public Service Motivation concept was developed in North America and focuses on specific motivations of public servants, such as employee satisfaction, organizational commitment, reward preferences, organizational and individual performance. Other types of motivation, as financial consideration, are relevant but have less important influences with regard to this kind of work outcomes. This strengthen the assertion for a diversified motivational strategy, which affect various types of motivation, while not losing sight of the public value that one organization shows and therefore valuing public service motivation as a specific contribution to work outcomes. The concept has been increasingly applied in European public administration. This paper presents Status Quo of international Public Service Motivation research and locates in them empirical evidences from contries that are already working with this concept, like Austria. It also analyses implications for central questions of public management. The main focus of this article is general appropriateness and possible applications for Romanian public management research.

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.

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

Transferring Instantly the State of Higher-Order Linear Descriptor (Regular Differential Systems Using Impulsive Inputs

Directory of Open Access Journals (Sweden)

Athanasios D. Karageorgos

2009-01-01

Full Text Available In many applications, and generally speaking in many dynamical differential systems, the problem of transferring the initial state of the system to a desired state in (almost zero-time time is desirable but difficult to achieve. Theoretically, this can be achieved by using a linear combination of Dirac -function and its derivatives. Obviously, such an input is physically unrealizable. However, we can think of it approximately as a combination of small pulses of very high magnitude and infinitely small duration. In this paper, the approximation process of the distributional behaviour of higher-order linear descriptor (regular differential systems is presented. Thus, new analytical formulae based on linear algebra methods and generalized inverses theory are provided. Our approach is quite general and some significant conditions are derived. Finally, a numerical example is presented and discussed.

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

Science.gov (United States)

Tian, Feifei; Zhou, Peng; Li, Zhiliang

2007-03-01

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

Protected area types, strategies and impacts in Brazil's Amazon: public protected area strategies do not yield a consistent ranking of protected area types by impact

Science.gov (United States)

Pfaff, Alexander; Robalino, Juan; Sandoval, Catalina; Herrera, Diego

2015-01-01

The leading policy to conserve forest is protected areas (PAs). Yet, PAs are not a single tool: land users and uses vary by PA type; and public PA strategies vary in the extent of each type and in the determinants of impact for each type, i.e. siting and internal deforestation. Further, across regions and time, strategies respond to pressures (deforestation and political). We estimate deforestation impacts of PA types for a critical frontier, the Brazilian Amazon. We separate regions and time periods that differ in their deforestation and political pressures and document considerable variation in PA strategies across regions, time periods and types. The siting of PAs varies across regions. For example, all else being equal, PAs in the arc of deforestation are relatively far from non-forest, while in other states they are relatively near. Internal deforestation varies across time periods, e.g. it is more similar across the PA types for PAs after 2000. By contrast, after 2000, PA extent is less similar across PA types with little non-indigenous area created inside the arc. PA strategies generate a range of impacts for PA types—always far higher within the arc—but not a consistent ranking of PA types by impact. PMID:26460126

Application of MPEG-7 descriptors for content-based indexing of sports videos

Science.gov (United States)

Hoeynck, Michael; Auweiler, Thorsten; Ohm, Jens-Rainer

2003-06-01

The amount of multimedia data available worldwide is increasing every day. There is a vital need to annotate multimedia data in order to allow universal content access and to provide content-based search-and-retrieval functionalities. Since supervised video annotation can be time consuming, an automatic solution is appreciated. We review recent approaches to content-based indexing and annotation of videos for different kind of sports, and present our application for the automatic annotation of equestrian sports videos. Thereby, we especially concentrate on MPEG-7 based feature extraction and content description. We apply different visual descriptors for cut detection. Further, we extract the temporal positions of single obstacles on the course by analyzing MPEG-7 edge information and taking specific domain knowledge into account. Having determined single shot positions as well as the visual highlights, the information is jointly stored together with additional textual information in an MPEG-7 description scheme. Using this information, we generate content summaries which can be utilized in a user front-end in order to provide content-based access to the video stream, but further content-based queries and navigation on a video-on-demand streaming server.

Multichannel linear descriptors analysis for event-related EEG of vascular dementia patients during visual detection task.

Science.gov (United States)

Lou, Wutao; Xu, Jin; Sheng, Hengsong; Zhao, Songzhen

2011-11-01

Multichannel EEG recorded in a task condition could contain more information about cognition. However, that has not been widely investigated in the vascular-dementia (VaD)- related studies. The purpose of this study was to explore the differences of brain functional states between VaD patients and normal controls while performing a detection task. Three multichannel linear descriptors, i.e. spatial complexity (Ω), field strength (Σ) and frequency of field changes (Φ), were applied to analyse four frequency bands (delta, theta, alpha and beta) of multichannel event-related EEG signals for 12 VaD patients (mean age ± SD: 69.25 ± 10.56 years ; MMSE score ± SD: 22.58 ± 4.42) and 12 age-matched healthy subjects (mean age ± SD: 67.17 ± 5.97 years ; MMSE score ± SD: 29.08 ± 0.9). The correlations between the three measures and MMSE scores were also analysed. VaD patients showed a significant higher Ω value in the delta (p = 0.013) and theta (p = 0.021) frequency bands, a lower Σ value (p = 0.011) and a higher Φ (p = 0.008) value in the delta frequency band compared with normal controls. The MMSE scores were negatively correlated with the Ω (r = -0.52, p = 0.01) and Φ (r = -0.47, p = 0.02) values in the delta frequency band. The results indicated the VaD patients presented a reduction of synchronization in the slow frequency band during target detection, and suggested more neurons might be activated in VaD patients compared with normal controls. The Ω and Φ measures in the delta frequency band might be used to evaluate the degree of cognitive dysfunction. The multichannel linear descriptors are promising measures to reveal the differences in brain functions between VaD patients and normal subjects, and could potentially be used to evaluate the degree of cognitive dysfunction in VaD patients. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

Science.gov (United States)

Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

2017-01-01

Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99

Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach

Directory of Open Access Journals (Sweden)

Miraemiliana Murat

2017-09-01

Full Text Available Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM, Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD, Histogram of Oriented Gradients (HOG, Hu invariant moments (Hu and Zernike moments (ZM. Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN, random forest (RF, support vector machine (SVM, k-nearest neighbour (k-NN, linear discriminant analysis (LDA and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM. In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS and Pearson’s coefficient correlation (PCC. The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia

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

Science.gov (United States)

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

2016-12-01

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

{sup 13}C NMR spectral data and molecular descriptors to predict the antioxidant activity of flavonoids

Energy Technology Data Exchange (ETDEWEB)

Fernandes, Mariane Balerine; Muramatsu, Eric [Universidade de Sao Paulo (USP). Ribeirao Preto, SP (Brazil). Fac. de Ciencias Farmauceuticas; Emereciano, Vicente de Paula [Universidade de Sao Paulo (USP), SP (Brazil). Inst. de Quimica; Scotti, Marcus Tullius [Universidade Federal da Paraiba (UFPA), Joao Pessoa, PA (Brazil). Centro de Ciencias Aplicadas e Educacao; Scotti, Luciana; Tavares, Josean Fechine; Silva, Marcelo Sobral da [Universidade Federal da Paraiba (UFPA), Joao Pessoa, PA (Brazil). Lab. de Tecnologia Farmaceutica

2011-04-15

Tissue damage due to oxidative stress is directly linked to development of many, if not all, human morbidity factors and chronic diseases. In this context, the search for dietary natural occurring molecules with antioxidant activity, such as flavonoids, has become essential. In this study, we investigated a set of 41 flavonoids (23 flavones and 18 flavonols) analyzing their structures and biological antioxidant activity. The experimental data were submitted to a QSAR (quantitative structure-activity relationships) study. NMR {sup 13}C data were used to perform a Kohonen self-organizing map study, analyzing the weight that each carbon has in the activity. Additionally, we performed MLR (multilinear regression) using GA (genetic algorithms) and molecular descriptors to analyze the role that specific carbons and substitutions play in the activity. (author)

Uso de descritores de dispneia traduzidos da língua inglesa em pacientes com doenças cardiorrespiratórias ou obesidade Dyspnea descriptors translated from English to Portuguese: application in obese patients and in patients with cardiorespiratory diseases

Directory of Open Access Journals (Sweden)

Christiane Aires Teixeira

2011-08-01

Full Text Available OBJETIVO: Investigar a utilidade de descritores de dispneia, desenvolvidos em língua inglesa e traduzidos para o português falado no Brasil, em pacientes com quatro condições distintas que cursam com dispneia. MÉTODOS: Uma lista de 15 descritores de dispneia construída em um estudo nos EUA foi traduzida para o português. Esse conjunto de descritores foi aplicado a 50 pacientes com asma, 50 com DPOC, 30 com insuficiência cardíaca e 50 com obesidade graus II ou III. Os termos selecionados como os três melhores para descrever a sensação de dispneia pelos pacientes foram estudados por análise de agrupamentos. Também foram investigadas as possíveis associações entre os agrupamentos encontrados e as quatro condições clínicas incluídas. RESULTADOS: O emprego dessa lista levou a uma solução com nove agrupamentos, denominados expiração, fome de ar, sufoco, superficial, rápido, aperto, falta de ar, trabalho e inspiração. Houve acentuada superposição no uso de descritores pelos pacientes com as quatro condições clínicas. Asma, DPOC e insuficiência cardíaca mostraram associações relevantes com inspiração. Insuficiência cardíaca mostrou associação adicional com trabalho, enquanto nenhum agrupamento se associou de maneira expressiva com obesidade. CONCLUSÕES: O uso de descritores de dispneia traduzidos da língua inglesa por pacientes no Brasil levou a identificação de agrupamentos distintos, os quais guardaram semelhança com aqueles obtidos em um estudo nos EUA. Esses descritores traduzidos foram menos úteis do que um grupo de descritores desenvolvido no Brasil no que se refere à capacidade de gerar associações significativas com as condições clínicas investigadas.OBJECTIVE: To investigate the usefulness of descriptive terms applied to the sensation of dyspnea (dyspnea descriptors that were developed in English and translated to Brazilian Portuguese in patients with four distinct clinical conditions that

SOCIO - CULTURAL ASPECTS OF TUBERCULOSIS AND DIALOGUE WITH PUBLIC HEALTH POLICIES IN BRAZIL

Directory of Open Access Journals (Sweden)

Débora Regina Marques Barbosa

2013-03-01

Full Text Available Tuberculosis away from individuals affected by their social and affective and reconstructionof collective values, relegating them to the condition of inferiority and subservience Sartrean,liabilities oppressive conditions imposed by society, which dismisses the other as legitimatein the intersubjective social construction. This work aims to address the social, psychologicaland symbolic carrier of tuberculosis and PPS in Brazil through integrative review in databasesScientific Electronic Library Online (Scielo and Google Scholar using the descriptorsTuberculosis Society, Culture, Psychosocial Aspects, Sociocultural Aspects; Public Policy inHealth, Social Movements and Social Control, individually or grouped according to theirproximity or remoteness to the guiding question: "How Public Policies on Health dialoguewith social movements and sociocultural aspects of Tuberculosis?". Whereas the way ofseeing a situation and its meaning in a certain reality is guiding factor, even though subjective,of actions, it is stressed that interventions should take in the full measure of human socio-economic-political-cultural. In this sense, knowledge of cultural and socioeconomic situationof a region is essential to confronting the chain of events that disease primarily social in agiven community.

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.

Ozone pollution and ozone biomonitoring in European cities Part II. Ozone-induced plant injury and its relationship with descriptors of ozone pollution

DEFF Research Database (Denmark)

Klumpp, A.; Ansel, W.; Klumpp, G.

2006-01-01

within local networks were relatively small, but seasonal and inter-annual differences were strong due to the variability of meteorological conditions and related ozone concentrations. The 2001 data revealed a significant relationship between foliar injury degree and various descriptors of ozone...... pollution such as mean value, AOT20 and AOT40. Examining individual sites of the local monitoring networks separately, however, yielded noticeable differences. Some sites showed no association between ozone pollution and ozone-induced effects, whereas others featured almost linear relationships...

Public licenses and public domain as alternatives to copyright

OpenAIRE

Köppel, Petr

2012-01-01

The work first introduces the area of public licenses as a space between the copyright law and public domain. After that, consecutively for proprietary software, free and open source software, open hardware and open content, it maps particular types of public licenses and the accompanying social and cultural movements, puts them in mutual as well as historical context, examines their characteristics and compares them to each other, shows how the public licenses are defined by various accompan...

Types, Purposes And Simulation Of Contributions In Vocational Training In Health: Narrative Review

Directory of Open Access Journals (Sweden)

Fillipi André dos Santos Silva

2017-01-01

Full Text Available Objective: To identify the types, purposes and the contributions of simulation in training in health. Method: This is a narrative review of the literature in its construction were used studies surveyed in databases Latin American and Caribbean Health Sciences (LILACS and Scopus, and other data sources. Results: The types of simulations and simulators are characterized by the degree of organization of landscape and simulator technology: low, medium and high fidelity. These degrees of fidelity enable the development of skills and abilities in students in the context of health education.  Conclusion: Considering the scope and possibilities of its use, the simulation can be a positive tool in health education process.  Descriptors: Education. Simulation. Health. Education. Formative feedback.

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.

The vulnerabilities in childhood and adolescence and the Brazilian public policy intervention.

Science.gov (United States)

Fonseca, Franciele Fagundes; Sena, Ramony Kris R; dos Santos, Rocky Lane A; Dias, Orlene Veloso; Costa, Simone de Melo

2013-06-01

To review and discuss childhood and adolescence vulnerabilities, as well as Brazilian public policies of intervention. A narrative review was performed, considering studies published between 1990 and 2012, found in the Virtual Health Library databases (Biblioteca Virtual em Saúde - BVS). A combination of the following descriptors was used in the search strategy: "Adolescent Health", "Child Health", "Health Public Politics" and "Vulnerability". In addition, Brazilian official documents, the Statute of the Child and the Adolescent, Guardianship Council, Bolsa Família and Saúde na Escola Programs were evaluated. The results were divided into five categories of analysis: Vulnerability of Children and Adolescents in Brazil, Public Politics of Intervention to Risk Factors in Childhood and Adolescence, the Statute of the Child and the Adolescent and Guardianship Council, Bolsa Família Program and Saúde na Escola Program. The studies show that children and adolescents are vulnerable to environmental and social situations. Vulnerabilities are exhibited in daily violence within families and schools, which results in the premature entrance of children and adolescents in the work environment and/or in the drug traffic. To deal with these problems, the Brazilian Government established the Statute of the Child and the Adolescent as well as social programs. Literature exposes the risks experienced by children and adolescents in Brazil. In the other hand, a Government endeavor was identified to eliminate or minimize the suffering of those in vulnerable situations through public policies targeted to this population group.

MULTIMODAL CLASSIFICATION OF DEMENTIA USING FUNCTIONAL DATA, ANATOMICAL FEATURES AND 3D INVARIANT SHAPE DESCRIPTORS.

Science.gov (United States)

Mikhno, Arthur; Nuevo, Pablo Martinez; Devanand, Davangere P; Parsey, Ramin V; Laine, Andrew F

2012-01-01

Multimodality classification of Alzheimer's disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), is of interest to the medical community. We improve on prior classification frameworks by incorporating multiple features from MRI and PET data obtained with multiple radioligands, fluorodeoxyglucose (FDG) and Pittsburg compound B (PIB). We also introduce a new MRI feature, invariant shape descriptors based on 3D Zernike moments applied to the hippocampus region. Classification performance is evaluated on data from 17 healthy controls (CTR), 22 MCI, and 17 AD subjects. Zernike significantly outperforms volume, accuracy (Zernike to volume): CTR/AD (90.7% to 71.6%), CTR/MCI (76.2% to 60.0%), MCI/AD (84.3% to 65.5%). Zernike also provides comparable and complementary performance to PET. Optimal accuracy is achieved when Zernike and PET features are combined (accuracy, specificity, sensitivity), CTR/AD (98.8%, 99.5%, 98.1%), CTR/MCI (84.3%, 82.9%, 85.9%) and MCI/AD (93.3%, 93.6%, 93.3%).

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Quantitative Radiomics System Decoding the Tumor Phenotype | Informatics Technology for Cancer Research (ITCR)

Science.gov (United States)

Our goal is to construct a publicly available computational radiomics system for the objective and automated extraction of quantitative imaging features that we believe will yield biomarkers of greater prognostic value compared with routinely extracted descriptors of tumor size. We will create a generalized, open, portable, and extensible radiomics platform that is widely applicable across cancer types and imaging modalities and describe how we will use lung and head and neck cancers as models to validate our developments.

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

Science.gov (United States)

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

2018-06-15

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

Elliptical Fourier descriptors of outline and morphological analysis in caudal view of foramen magnum of the tropical raccoon (Procyon cancrivorus) (Linnaeus, 1758).

Science.gov (United States)

Samuel, O M; Casanova, P M; Olopade, J O

2018-03-01

To evaluate sexual-size dimorphism and attempt at categorization of inter-individual shapes of foramen magnum outlines using Fourier descriptors which allow for shape outline evaluations with a resultant specimen character definition. Individual characterization and quantification of foramen magnum shapes in direct caudal view based on elliptical Fourier technique was applied to 46 tropical raccoon skulls (26 females, 20 males). Incremental number of harmonics demonstrates morphological contributions of such descriptors with their relations to specific anatomical constructions established. The initial harmonics (1st to 3rd) described the general foramen shapes while the second (4th to 12th) demonstrated fine morphological details. Sexual-size dimorphism was observed in females (87.1%) and 91.7% in males, normalization of size produces 75% in females and 83% in males. With respect to foramen magnum dimorphism analysis, the result obtained through elliptic Fourier analysis was comparatively better in detail information of outline contours than earlier classical methods. The first four effective principal components defined 70.63% of its shape properties while the rest (22.51%) constituted fine details of morphology. Both size and shape seems important in sexual dimorphisms in this species, this investigation suggest clinical implications, taxonomic and anthropologic perspectives in foramen characterization magnum characterization and further postulates an increased possibility of volume reduction cerebellar protrusion, ontogenic magnum shape irregularities in the sample population with neurologic consequences especially among females. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Public Sector and Europeanization Challenges

Directory of Open Access Journals (Sweden)

Lucica Matei

2006-02-01

Accepting the market-type mechanisms instead of bureaucratic mechanisms, meaning not the simple provision of public services but the creation of some governmental “actors”, functioning completely on commercial bases, supporting the development of the partnerships between the public and private sector, introducing privatisation is achieved in view of creating “the facilitating state”. We discuss about “facilities” such as citizens and society involvement in public businesses, making public administration more citizen-friendly and the state closer to the public need. The citizens’ involvement, as customers in the flow of the public service contributes to creating an organic ensemble characterised by two fundamental dimensions: level and type of influence of the customers and the private-public dichotomy. Synthesising, the relationships and market mechanisms enable to the public sector to get closer to the public needs and to create a modern administration based on efficiency, effectiveness and openness towards change.

Public Transparency

OpenAIRE

UNCTAD; World Bank

2018-01-01

This note provides guidance on the type of information about agricultural investments that investors and governments can make publicly available. Transparency about certain aspects of investments can improve relations between investors and communities, enable external stakeholders to hold investors to commitments, and improve investors’ public image. Although some information should be kep...

Publication point indicators

DEFF Research Database (Denmark)

Elleby, Anita; Ingwersen, Peter

2010-01-01

The paper presents comparative analyses of two publication point systems, The Norwegian and the in-house system from the interdiscplinary Danish Institute for International Studies (DIIS), used as case in the study for publications published 2006, and compares central citation-based indicators...... with novel publication point indicators (PPIs) that are formalized and exemplified. Two diachronic citation windows are applied: 2006-07 and 2006-08. Web of Science (WoS) as well as Google Scholar (GS) are applied to observe the cite delay and citedness for the different document types published by DIIS...... for all document types. Statistical significant correlations were only found between WoS and GS and the two publication point systems in between, respectively. The study demonstrates how the nCPPI can be applied to institutions as evaluation tools supplementary to JCI in various combinations...

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

DEFF Research Database (Denmark)

Marcatili, Paolo; Mochament, Konstantinos; Agathangelidis, Andreas

2016-01-01

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

Public Sector and Europeanization Challenges

Directory of Open Access Journals (Sweden)

Lucica Matei

2006-04-01

Full Text Available The paper emphasises the role of the market-type mechanisms within the activity of the organisations from the public sector. The end of the 20th century was defined by the effects of the public sector reform. The public sector is placed within the cultural and political environment of each country and the reforms have aimed to redefine the structures of the state organisations in the economy and the relationships such as market-government, government-bureaucracy, government- citizens, bureaucracy-citizens, civil servants-politicians-citizens. The public sector reform, achieved at the managerial systems, organisational structures and regulations levels is accompanied by specific and structural reforms. Accepting the market-type mechanisms instead of bureaucratic mechanisms, meaning not the simple provision of public services but the creation of some governmental “actors”, functioning completely on commercial bases, supporting the development of the partnerships between the public and private sector, introducing privatisation is achieved in view of creating “the facilitating state”. We discuss about “facilities” such as citizens and society involvement in public businesses, making public administration more citizen-friendly and the state closer to the public need. The citizens’ involvement, as customers in the flow of the public service contributes to creating an organic ensemble characterised by two fundamental dimensions: level and type of influence of the customers and the private-public dichotomy. Synthesising, the relationships and market mechanisms enable to the public sector to get closer to the public needs and to create a modern administration based on efficiency, effectiveness and openness towards change.

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

Science.gov (United States)

Herega, Alexander; Sukhanov, Volodymyr; Vyrovoy, Valery

2017-12-01

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

Public-Private Partnerships as Hybrid Organizational Drivers of Innovation in the Public Sector

DEFF Research Database (Denmark)

Dam, Sofie

Decision-makers increasingly mention public-private partnerships (PPPs) as potential tools for innovation in the public sector. In contrast, literature on PPPs has mostly evaluated their economic efficiency, whereas their ability to enhance innovation has been subordinated and sometimes assumed....... Empirical investigations of innovations in PPPs have been rather scarce and scattered between different PPP types and sectors. This article strives for a more comprehensive and reflexive approach and contribute to an increasing body of literature on public sector innovation by constructing a conceptual...... framework, which can be used to investigate the potential for innovation in different PPP types across sectors. The last decades have seen sequential waves of public sector reforms, which have resulted in an increased hybridity in the public sector, where ideas, goals and tools from hierarchy, market...

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.

A Taxonomy of Injuries for Public Health Monitoring and Reporting. Addendum 1, Body Regions and Injury Types. Addendum 2, Fiscal Year 2018 Update

Science.gov (United States)

2017-12-01

This document establishes a taxonomy for categorizing and consistently defining physical injuries that are included in public health surveillance...public health epidemiologic efforts. As its focus is on physical injuries, behavioral and mental conditions are excluded. 3 INTRODUCTION...military health care, as well as the physical readiness of individual Soldiers and units. In 2006, the most common type of non-fatal military injury

Atom-type-based AI topological descriptors: application in structure-boiling point correlations of oxo organic compounds.

Science.gov (United States)

Ren, Biye

2003-01-01

Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.

Publicly available models to predict normal boiling point of organic compounds

International Nuclear Information System (INIS)

Oprisiu, Ioana; Marcou, Gilles; Horvath, Dragos; Brunel, Damien Bernard; Rivollet, Fabien; Varnek, Alexandre

2013-01-01

Quantitative structure–property models to predict the normal boiling point (T b ) of organic compounds were developed using non-linear ASNNs (associative neural networks) as well as multiple linear regression – ISIDA-MLR and SQS (stochastic QSAR sampler). Models were built on a diverse set of 2098 organic compounds with T b varying in the range of 185–491 K. In ISIDA-MLR and ASNN calculations, fragment descriptors were used, whereas fragment, FPTs (fuzzy pharmacophore triplets), and ChemAxon descriptors were employed in SQS models. Prediction quality of the models has been assessed in 5-fold cross validation. Obtained models were implemented in the on-line ISIDA predictor at (http://infochim.u-strasbg.fr/webserv/VSEngine.html)

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.

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

Science.gov (United States)

Venkatraman, Vishwesh; Chakravarthy, Padmasini Ramji; Kihara, Daisuke

2009-12-17

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. 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. 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.

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

Science.gov (United States)

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

2010-02-01

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

Selected DOE headquarters publications, October 1979

International Nuclear Information System (INIS)

1981-01-01

The publication provides cumulative listings of and an index to DOE headquarters publications issued since October 1979. Publications issued during October 1977 to September 1979 are covered in DOE/AD-0010/6. Publications from 26 headquarters offices are presented and consist of three types: publications dealing mainly with program and policy that are attributed to and issued by headquarters organizations; reports prepared by contractors (and published by DOE) to describe research and development work they have performed for the Department under 01-type contracts; and environmental development plans, impact statements, and readiness documents. Availability of the documents is described

Selected DOE headquarters publications, October 1979

Energy Technology Data Exchange (ETDEWEB)

None

1981-01-01

The publication provides cumulative listings of and an index to DOE headquarters publications issued since October 1979. Publications issued during October 1977 to September 1979 are covered in DOE/AD-0010/6. Publications from 26 headquarters offices are presented and consist of three types: publications dealing mainly with program and policy that are attributed to and issued by headquarters organizations; reports prepared by contractors (and published by DOE) to describe research and development work they have performed for the Department under 01-type contracts; and environmental development plans, impact statements, and readiness documents. Availability of the documents is described.

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

Directory of Open Access Journals (Sweden)

A. Calantropio

2018-05-01

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

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.

Classification of Strawberry Fruit Shape by Machine Learning

Science.gov (United States)

Ishikawa, T.; Hayashi, A.; Nagamatsu, S.; Kyutoku, Y.; Dan, I.; Wada, T.; Oku, K.; Saeki, Y.; Uto, T.; Tanabata, T.; Isobe, S.; Kochi, N.

2018-05-01

Shape is one of the most important traits of agricultural products due to its relationships with the quality, quantity, and value of the products. For strawberries, the nine types of fruit shape were defined and classified by humans based on the sampler patterns of the nine types. In this study, we tested the classification of strawberry shapes by machine learning in order to increase the accuracy of the classification, and we introduce the concept of computerization into this field. Four types of descriptors were extracted from the digital images of strawberries: (1) the Measured Values (MVs) including the length of the contour line, the area, the fruit length and width, and the fruit width/length ratio; (2) the Ellipse Similarity Index (ESI); (3) Elliptic Fourier Descriptors (EFDs), and (4) Chain Code Subtraction (CCS). We used these descriptors for the classification test along with the random forest approach, and eight of the nine shape types were classified with combinations of MVs + CCS + EFDs. CCS is a descriptor that adds human knowledge to the chain codes, and it showed higher robustness in classification than the other descriptors. Our results suggest machine learning's high ability to classify fruit shapes accurately. We will attempt to increase the classification accuracy and apply the machine learning methods to other plant species.

Breast ultrasound image segmentation: an optimization approach based on super-pixels and high-level descriptors

Science.gov (United States)

Massich, Joan; Lemaître, Guillaume; Martí, Joan; Mériaudeau, Fabrice

2015-04-01

Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the breast are essential for CAD systems in order to extract information needed to perform diagnosis. This article proposes a highly modular and flexible framework for segmenting lesions and tissues present in BUS images. The proposal takes advantage of optimization strategies using super-pixels and high-level descriptors, which are analogous to the visual cues used by radiologists. Qualitative and quantitative results are provided stating a performance within the range of the state-of-the-art.

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

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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.

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-10-15

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

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

Science.gov (United States)

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259