The value of protein structure classification information—Surveying the scientific literature

PubMed Central

Fox, Naomi K.; Brenner, Steven E.

2015-01-01

ABSTRACT The Structural Classification of Proteins (SCOP) and Class, Architecture, Topology, Homology (CATH) databases have been valuable resources for protein structure classification for over 20 years. Development of SCOP (version 1) concluded in June 2009 with SCOP 1.75. The SCOPe (SCOP–extended) database offers continued development of the classic SCOP hierarchy, adding over 33,000 structures. We have attempted to assess the impact of these two decade old resources and guide future development. To this end, we surveyed recent articles to learn how structure classification data are used. Of 571 articles published in 2012–2013 that cite SCOP, 439 actually use data from the resource. We found that the type of use was fairly evenly distributed among four top categories: A) study protein structure or evolution (27% of articles), B) train and/or benchmark algorithms (28% of articles), C) augment non‐SCOP datasets with SCOP classification (21% of articles), and D) examine the classification of one protein/a small set of proteins (22% of articles). Most articles described computational research, although 11% described purely experimental research, and a further 9% included both. We examined how CATH and SCOP were used in 158 articles that cited both databases: while some studies used only one dataset, the majority used data from both resources. Protein structure classification remains highly relevant for a diverse range of problems and settings. Proteins 2015; 83:2025–2038. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:26313554

Learning about the internal structure of categories through classification and feature inference.

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

Nucleic and Amino Acid Sequences Support Structure-Based Viral Classification.

PubMed

Sinclair, Robert M; Ravantti, Janne J; Bamford, Dennis H

2017-04-15

Viral capsids ensure viral genome integrity by protecting the enclosed nucleic acids. Interactions between the genome and capsid and between individual capsid proteins (i.e., capsid architecture) are intimate and are expected to be characterized by strong evolutionary conservation. For this reason, a capsid structure-based viral classification has been proposed as a way to bring order to the viral universe. The seeming lack of sufficient sequence similarity to reproduce this classification has made it difficult to reject structural convergence as the basis for the classification. We reinvestigate whether the structure-based classification for viral coat proteins making icosahedral virus capsids is in fact supported by previously undetected sequence similarity. Since codon choices can influence nascent protein folding cotranslationally, we searched for both amino acid and nucleotide sequence similarity. To demonstrate the sensitivity of the approach, we identify a candidate gene for the pandoravirus capsid protein. We show that the structure-based classification is strongly supported by amino acid and also nucleotide sequence similarities, suggesting that the similarities are due to common descent. The correspondence between structure-based and sequence-based analyses of the same proteins shown here allow them to be used in future analyses of the relationship between linear sequence information and macromolecular function, as well as between linear sequence and protein folds. IMPORTANCE Viral capsids protect nucleic acid genomes, which in turn encode capsid proteins. This tight coupling of protein shell and nucleic acids, together with strong functional constraints on capsid protein folding and architecture, leads to the hypothesis that capsid protein-coding nucleotide sequences may retain signatures of ancient viral evolution. We have been able to show that this is indeed the case, using the major capsid proteins of viruses forming icosahedral capsids. Importantly

Nucleic and Amino Acid Sequences Support Structure-Based Viral Classification

PubMed Central

Sinclair, Robert M.; Ravantti, Janne J.

2017-01-01

ABSTRACT Viral capsids ensure viral genome integrity by protecting the enclosed nucleic acids. Interactions between the genome and capsid and between individual capsid proteins (i.e., capsid architecture) are intimate and are expected to be characterized by strong evolutionary conservation. For this reason, a capsid structure-based viral classification has been proposed as a way to bring order to the viral universe. The seeming lack of sufficient sequence similarity to reproduce this classification has made it difficult to reject structural convergence as the basis for the classification. We reinvestigate whether the structure-based classification for viral coat proteins making icosahedral virus capsids is in fact supported by previously undetected sequence similarity. Since codon choices can influence nascent protein folding cotranslationally, we searched for both amino acid and nucleotide sequence similarity. To demonstrate the sensitivity of the approach, we identify a candidate gene for the pandoravirus capsid protein. We show that the structure-based classification is strongly supported by amino acid and also nucleotide sequence similarities, suggesting that the similarities are due to common descent. The correspondence between structure-based and sequence-based analyses of the same proteins shown here allow them to be used in future analyses of the relationship between linear sequence information and macromolecular function, as well as between linear sequence and protein folds. IMPORTANCE Viral capsids protect nucleic acid genomes, which in turn encode capsid proteins. This tight coupling of protein shell and nucleic acids, together with strong functional constraints on capsid protein folding and architecture, leads to the hypothesis that capsid protein-coding nucleotide sequences may retain signatures of ancient viral evolution. We have been able to show that this is indeed the case, using the major capsid proteins of viruses forming icosahedral capsids

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

NASA Astrophysics Data System (ADS)

Jain, Sankalp; Grandits, Melanie; Richter, Lars; Ecker, Gerhard F.

2017-06-01

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

Classification of the Pospiviroidae based on their structural hallmarks.

PubMed

Giguère, Tamara; Perreault, Jean-Pierre

2017-01-01

The simplest known plant pathogens are the viroids. Because of their non-coding single-stranded circular RNA genome, they depend on both their sequence and their structure for both a successful infection and their replication. In the recent years, important progress in the elucidation of their structures was achieved using an adaptation of the selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) protocol in order to probe viroid structures in solution. Previously, SHAPE has been adapted to elucidate the structures of all of the members of the family Avsunviroidae, as well as those of a few members of the family Pospiviroidae. In this study, with the goal of providing an entire compendium of the secondary structures of the various viroid species, a total of thirteen new Pospiviroidae members were probed in solution using the SHAPE protocol. More specifically, the secondary structures of eleven species for which the genus was previously known were initially elucidated. At this point, considering all of the SHAPE elucidated secondary structures, a classification system for viroids in their respective genera was proposed. On the basis of the structural classification reported here, the probings of both the Grapevine latent viroid and the Dahlia latent viroid provide sound arguments for the determination of their respective genera, which appear to be Apscaviroid and Hostuviroid, respectively. More importantly, this study provides the complete repertoire of the secondary structures, mapped in solution, of all of the accepted viroid species reported thus far. In addition, a classification scheme based on structural hallmarks, an important tool for many biological studies, is proposed.

Classification of the Pospiviroidae based on their structural hallmarks

PubMed Central

Giguère, Tamara

2017-01-01

The simplest known plant pathogens are the viroids. Because of their non-coding single-stranded circular RNA genome, they depend on both their sequence and their structure for both a successful infection and their replication. In the recent years, important progress in the elucidation of their structures was achieved using an adaptation of the selective 2’-hydroxyl acylation analyzed by primer extension (SHAPE) protocol in order to probe viroid structures in solution. Previously, SHAPE has been adapted to elucidate the structures of all of the members of the family Avsunviroidae, as well as those of a few members of the family Pospiviroidae. In this study, with the goal of providing an entire compendium of the secondary structures of the various viroid species, a total of thirteen new Pospiviroidae members were probed in solution using the SHAPE protocol. More specifically, the secondary structures of eleven species for which the genus was previously known were initially elucidated. At this point, considering all of the SHAPE elucidated secondary structures, a classification system for viroids in their respective genera was proposed. On the basis of the structural classification reported here, the probings of both the Grapevine latent viroid and the Dahlia latent viroid provide sound arguments for the determination of their respective genera, which appear to be Apscaviroid and Hostuviroid, respectively. More importantly, this study provides the complete repertoire of the secondary structures, mapped in solution, of all of the accepted viroid species reported thus far. In addition, a classification scheme based on structural hallmarks, an important tool for many biological studies, is proposed. PMID:28783761

Hierarchical structure for audio-video based semantic classification of sports video sequences

NASA Astrophysics Data System (ADS)

Kolekar, M. H.; Sengupta, S.

2005-07-01

A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

33 CFR 67.01-15 - Classification of structures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Classification of structures. 67.01-15 Section 67.01-15 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY AIDS TO NAVIGATION AIDS TO NAVIGATION ON ARTIFICIAL ISLANDS AND FIXED STRUCTURES General Requirements...

3D Complex: A Structural Classification of Protein Complexes

PubMed Central

Levy, Emmanuel D; Pereira-Leal, Jose B; Chothia, Cyrus; Teichmann, Sarah A

2006-01-01

Most of the proteins in a cell assemble into complexes to carry out their function. It is therefore crucial to understand the physicochemical properties as well as the evolution of interactions between proteins. The Protein Data Bank represents an important source of information for such studies, because more than half of the structures are homo- or heteromeric protein complexes. Here we propose the first hierarchical classification of whole protein complexes of known 3-D structure, based on representing their fundamental structural features as a graph. This classification provides the first overview of all the complexes in the Protein Data Bank and allows nonredundant sets to be derived at different levels of detail. This reveals that between one-half and two-thirds of known structures are multimeric, depending on the level of redundancy accepted. We also analyse the structures in terms of the topological arrangement of their subunits and find that they form a small number of arrangements compared with all theoretically possible ones. This is because most complexes contain four subunits or less, and the large majority are homomeric. In addition, there is a strong tendency for symmetry in complexes, even for heteromeric complexes. Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. Our classification, available as a database and Web server at http://www.3Dcomplex.org, will be a starting point for future work aimed at understanding the structure and evolution of protein complexes. PMID:17112313

TIM Barrel Protein Structure Classification Using Alignment Approach and Best Hit Strategy

NASA Astrophysics Data System (ADS)

Chu, Jia-Han; Lin, Chun Yuan; Chang, Cheng-Wen; Lee, Chihan; Yang, Yuh-Shyong; Tang, Chuan Yi

2007-11-01

The classification of protein structures is essential for their function determination in bioinformatics. It has been estimated that around 10% of all known enzymes have TIM barrel domains from the Structural Classification of Proteins (SCOP) database. With its high sequence variation and diverse functionalities, TIM barrel protein becomes to be an attractive target for protein engineering and for the evolution study. Hence, in this paper, an alignment approach with the best hit strategy is proposed to classify the TIM barrel protein structure in terms of superfamily and family levels in the SCOP. This work is also used to do the classification for class level in the Enzyme nomenclature (ENZYME) database. Two testing data sets, TIM40D and TIM95D, both are used to evaluate this approach. The resulting classification has an overall prediction accuracy rate of 90.3% for the superfamily level in the SCOP, 89.5% for the family level in the SCOP and 70.1% for the class level in the ENZYME. These results demonstrate that the alignment approach with the best hit strategy is a simple and viable method for the TIM barrel protein structure classification, even only has the amino acid sequences information.

Classification of ligand molecules in PDB with graph match-based structural superposition.

PubMed

Shionyu-Mitsuyama, Clara; Hijikata, Atsushi; Tsuji, Toshiyuki; Shirai, Tsuyoshi

2016-12-01

The fast heuristic graph match algorithm for small molecules, COMPLIG, was improved by adding a structural superposition process to verify the atom-atom matching. The modified method was used to classify the small molecule ligands in the Protein Data Bank (PDB) by their three-dimensional structures, and 16,660 types of ligands in the PDB were classified into 7561 clusters. In contrast, a classification by a previous method (without structure superposition) generated 3371 clusters from the same ligand set. The characteristic feature in the current classification system is the increased number of singleton clusters, which contained only one ligand molecule in a cluster. Inspections of the singletons in the current classification system but not in the previous one implied that the major factors for the isolation were differences in chirality, cyclic conformations, separation of substructures, and bond length. Comparisons between current and previous classification systems revealed that the superposition-based classification was effective in clustering functionally related ligands, such as drugs targeted to specific biological processes, owing to the strictness of the atom-atom matching.

An unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data - A case study in complex temperate forest stands

NASA Astrophysics Data System (ADS)

Abdullahi, Sahra; Schardt, Mathias; Pretzsch, Hans

2017-05-01

Forest structure at stand level plays a key role for sustainable forest management, since the biodiversity, productivity, growth and stability of the forest can be positively influenced by managing its structural diversity. In contrast to field-based measurements, remote sensing techniques offer a cost-efficient opportunity to collect area-wide information about forest stand structure with high spatial and temporal resolution. Especially Interferometric Synthetic Aperture Radar (InSAR), which facilitates worldwide acquisition of 3d information independent from weather conditions and illumination, is convenient to capture forest stand structure. This study purposes an unsupervised two-stage clustering approach for forest structure classification based on height information derived from interferometric X-band SAR data which was performed in complex temperate forest stands of Traunstein forest (South Germany). In particular, a four dimensional input data set composed of first-order height statistics was non-linearly projected on a two-dimensional Self-Organizing Map, spatially ordered according to similarity (based on the Euclidean distance) in the first stage and classified using the k-means algorithm in the second stage. The study demonstrated that X-band InSAR data exhibits considerable capabilities for forest structure classification. Moreover, the unsupervised classification approach achieved meaningful and reasonable results by means of comparison to aerial imagery and LiDAR data.

Topological Classification of Crystalline Insulators through Band Structure Combinatorics

NASA Astrophysics Data System (ADS)

Kruthoff, Jorrit; de Boer, Jan; van Wezel, Jasper; Kane, Charles L.; Slager, Robert-Jan

2017-10-01

We present a method for efficiently enumerating all allowed, topologically distinct, electronic band structures within a given crystal structure in all physically relevant dimensions. The algorithm applies to crystals without time-reversal, particle-hole, chiral, or any other anticommuting or anti-unitary symmetries. The results presented match the mathematical structure underlying the topological classification of these crystals in terms of K -theory and therefore elucidate this abstract mathematical framework from a simple combinatorial perspective. Using a straightforward counting procedure, we classify all allowed topological phases of spinless particles in crystals in class A . Employing this classification, we study transitions between topological phases within class A that are driven by band inversions at high-symmetry points in the first Brillouin zone. This enables us to list all possible types of phase transitions within a given crystal structure and to identify whether or not they give rise to intermediate Weyl semimetallic phases.

Facilitating Facilitators: Enhancing PBL through a Structured Facilitator Development Program

ERIC Educational Resources Information Center

Salinitri, Francine D.; Wilhelm, Sheila M.; Crabtree, Brian L.

2015-01-01

With increasing adoption of the problem-based learning (PBL) model, creative approaches to enhancing facilitator training and optimizing resources to maintain effective learning in small groups is essential. We describe a theoretical framework for the development of a PBL facilitator training program that uses the constructivist approach as the…

Fourier-based classification of protein secondary structures.

PubMed

Shu, Jian-Jun; Yong, Kian Yan

2017-04-15

The correct prediction of protein secondary structures is one of the key issues in predicting the correct protein folded shape, which is used for determining gene function. Existing methods make use of amino acids properties as indices to classify protein secondary structures, but are faced with a significant number of misclassifications. The paper presents a technique for the classification of protein secondary structures based on protein "signal-plotting" and the use of the Fourier technique for digital signal processing. New indices are proposed to classify protein secondary structures by analyzing hydrophobicity profiles. The approach is simple and straightforward. Results show that the more types of protein secondary structures can be classified by means of these newly-proposed indices. Copyright © 2017 Elsevier Inc. All rights reserved.

Whose statistical reasoning is facilitated by a causal structure intervention?

PubMed

McNair, Simon; Feeney, Aidan

2015-02-01

People often struggle when making Bayesian probabilistic estimates on the basis of competing sources of statistical evidence. Recently, Krynski and Tenenbaum (Journal of Experimental Psychology: General, 136, 430-450, 2007) proposed that a causal Bayesian framework accounts for peoples' errors in Bayesian reasoning and showed that, by clarifying the causal relations among the pieces of evidence, judgments on a classic statistical reasoning problem could be significantly improved. We aimed to understand whose statistical reasoning is facilitated by the causal structure intervention. In Experiment 1, although we observed causal facilitation effects overall, the effect was confined to participants high in numeracy. We did not find an overall facilitation effect in Experiment 2 but did replicate the earlier interaction between numerical ability and the presence or absence of causal content. This effect held when we controlled for general cognitive ability and thinking disposition. Our results suggest that clarifying causal structure facilitates Bayesian judgments, but only for participants with sufficient understanding of basic concepts in probability and statistics.

49 CFR 25.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-10-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 25.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

22 CFR 229.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-04-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 229.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

22 CFR 229.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-04-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 229.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

22 CFR 146.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-04-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 146.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

22 CFR 146.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-04-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 146.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

22 CFR 229.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-04-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 229.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

49 CFR 25.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-10-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 25.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

22 CFR 146.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-04-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 146.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

28 CFR 54.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-07-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 54.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

22 CFR 229.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-04-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 229.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

10 CFR 1042.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-01-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1042.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

22 CFR 229.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-04-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 229.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

10 CFR 1042.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-01-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1042.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

28 CFR 54.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-07-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 54.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

28 CFR 54.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-07-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 54.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

22 CFR 146.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-04-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 146.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

28 CFR 54.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-07-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 54.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

49 CFR 25.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-10-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 25.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

49 CFR 25.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-10-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 25.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

10 CFR 1042.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-01-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1042.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

10 CFR 1042.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-01-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1042.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

22 CFR 146.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-04-01

... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 146.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

43 CFR 41.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-10-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 41.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

43 CFR 41.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-10-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 41.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

10 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Energy NUCLEAR REGULATORY COMMISSION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

44 CFR 19.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., DEPARTMENT OF HOMELAND SECURITY GENERAL NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 19.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

43 CFR 41.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-10-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 41.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

10 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Energy NUCLEAR REGULATORY COMMISSION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

44 CFR 19.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., DEPARTMENT OF HOMELAND SECURITY GENERAL NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 19.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

34 CFR 106.55 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 34 Education 1 2012-07-01 2012-07-01 false Job classification and structure. 106.55 Section 106.55 Education Regulations of the Offices of the Department of Education OFFICE FOR CIVIL RIGHTS, DEPARTMENT OF EDUCATION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL...

10 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Energy NUCLEAR REGULATORY COMMISSION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

40 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-07-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

34 CFR 106.55 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 1 2010-07-01 2010-07-01 false Job classification and structure. 106.55 Section 106.55 Education Regulations of the Offices of the Department of Education OFFICE FOR CIVIL RIGHTS, DEPARTMENT OF EDUCATION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL...

43 CFR 41.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-10-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 41.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

40 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-07-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

43 CFR 41.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-10-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 41.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

10 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Energy NUCLEAR REGULATORY COMMISSION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

34 CFR 106.55 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 34 Education 1 2014-07-01 2014-07-01 false Job classification and structure. 106.55 Section 106.55 Education Regulations of the Offices of the Department of Education OFFICE FOR CIVIL RIGHTS, DEPARTMENT OF EDUCATION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL...

44 CFR 19.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., DEPARTMENT OF HOMELAND SECURITY GENERAL NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 19.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

44 CFR 19.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., DEPARTMENT OF HOMELAND SECURITY GENERAL NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 19.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

40 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-07-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

44 CFR 19.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., DEPARTMENT OF HOMELAND SECURITY GENERAL NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 19.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

40 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-07-01

... BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

34 CFR 106.55 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 1 2011-07-01 2011-07-01 false Job classification and structure. 106.55 Section 106.55 Education Regulations of the Offices of the Department of Education OFFICE FOR CIVIL RIGHTS, DEPARTMENT OF EDUCATION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL...

10 CFR 5.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Energy NUCLEAR REGULATORY COMMISSION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 5.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

34 CFR 106.55 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 34 Education 1 2013-07-01 2013-07-01 false Job classification and structure. 106.55 Section 106.55 Education Regulations of the Offices of the Department of Education OFFICE FOR CIVIL RIGHTS, DEPARTMENT OF EDUCATION NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL...

Generic Language Facilitates Children's Cross-Classification

ERIC Educational Resources Information Center

Nguyen, Simone P.; Gelman, A.

2012-01-01

Four studies examined the role of generic language in facilitating 4- and 5-year-old children's ability to cross-classify. Participants were asked to classify an item into a familiar (taxonomic or script) category, then cross-classify it into a novel (script or taxonomic) category with the help of a clue expressed in either generic or specific…

Local pulmonary structure classification for computer-aided nodule detection

NASA Astrophysics Data System (ADS)

Bahlmann, Claus; Li, Xianlin; Okada, Kazunori

2006-03-01

We propose a new method of classifying the local structure types, such as nodules, vessels, and junctions, in thoracic CT scans. This classification is important in the context of computer aided detection (CAD) of lung nodules. The proposed method can be used as a post-process component of any lung CAD system. In such a scenario, the classification results provide an effective means of removing false positives caused by vessels and junctions thus improving overall performance. As main advantage, the proposed solution transforms the complex problem of classifying various 3D topological structures into much simpler 2D data clustering problem, to which more generic and flexible solutions are available in literature, and which is better suited for visualization. Given a nodule candidate, first, our solution robustly fits an anisotropic Gaussian to the data. The resulting Gaussian center and spread parameters are used to affine-normalize the data domain so as to warp the fitted anisotropic ellipsoid into a fixed-size isotropic sphere. We propose an automatic method to extract a 3D spherical manifold, containing the appropriate bounding surface of the target structure. Scale selection is performed by a data driven entropy minimization approach. The manifold is analyzed for high intensity clusters, corresponding to protruding structures. Techniques involve EMclustering with automatic mode number estimation, directional statistics, and hierarchical clustering with a modified Bhattacharyya distance. The estimated number of high intensity clusters explicitly determines the type of pulmonary structures: nodule (0), attached nodule (1), vessel (2), junction (>3). We show accurate classification results for selected examples in thoracic CT scans. This local procedure is more flexible and efficient than current state of the art and will help to improve the accuracy of general lung CAD systems.

Volta phase plate data collection facilitates image processing and cryo-EM structure determination.

PubMed

von Loeffelholz, Ottilie; Papai, Gabor; Danev, Radostin; Myasnikov, Alexander G; Natchiar, S Kundhavai; Hazemann, Isabelle; Ménétret, Jean-François; Klaholz, Bruno P

2018-06-01

A current bottleneck in structure determination of macromolecular complexes by cryo electron microscopy (cryo-EM) is the large amount of data needed to obtain high-resolution 3D reconstructions, including through sorting into different conformations and compositions with advanced image processing. Additionally, it may be difficult to visualize small ligands that bind in sub-stoichiometric levels. Volta phase plates (VPP) introduce a phase shift in the contrast transfer and drastically increase the contrast of the recorded low-dose cryo-EM images while preserving high frequency information. Here we present a comparative study to address the behavior of different data sets during image processing and quantify important parameters during structure refinement. The automated data collection was done from the same human ribosome sample either as a conventional defocus range dataset or with a Volta phase plate close to focus (cfVPP) or with a small defocus (dfVPP). The analysis of image processing parameters shows that dfVPP data behave more robustly during cryo-EM structure refinement because particle alignments, Euler angle assignments and 2D & 3D classifications behave more stably and converge faster. In particular, less particle images are required to reach the same resolution in the 3D reconstructions. Finally, we find that defocus range data collection is also applicable to VPP. This study shows that data processing and cryo-EM map interpretation, including atomic model refinement, are facilitated significantly by performing VPP cryo-EM, which will have an important impact on structural biology. Copyright © 2018 Elsevier Inc. All rights reserved.

6 CFR 17.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-01-01

... ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 17.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

29 CFR 36.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Labor Office of the Secretary of Labor NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 36.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

6 CFR 17.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-01-01

... ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 17.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

14 CFR 1253.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1253.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

14 CFR 1253.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1253.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

29 CFR 36.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Labor Office of the Secretary of Labor NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 36.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

6 CFR 17.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-01-01

... ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 17.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

29 CFR 36.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Labor Office of the Secretary of Labor NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR... Education Programs or Activities Prohibited § 36.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or establish separate lines of...

6 CFR 17.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-01-01

... ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 17.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 86.55 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-10-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 86.55 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 86.55 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-10-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 86.55 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 86.55 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-10-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 86.55 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 86.55 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-10-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 86.55 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

14 CFR 1253.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1253.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 86.55 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-10-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 86.55 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

14 CFR 1253.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1253.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

6 CFR 17.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-01-01

... ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 17.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

Structural brain changes versus self-report: machine-learning classification of chronic fatigue syndrome patients.

PubMed

Sevel, Landrew S; Boissoneault, Jeff; Letzen, Janelle E; Robinson, Michael E; Staud, Roland

2018-05-30

Chronic fatigue syndrome (CFS) is a disorder associated with fatigue, pain, and structural/functional abnormalities seen during magnetic resonance brain imaging (MRI). Therefore, we evaluated the performance of structural MRI (sMRI) abnormalities in the classification of CFS patients versus healthy controls and compared it to machine learning (ML) classification based upon self-report (SR). Participants included 18 CFS patients and 15 healthy controls (HC). All subjects underwent T1-weighted sMRI and provided visual analogue-scale ratings of fatigue, pain intensity, anxiety, depression, anger, and sleep quality. sMRI data were segmented using FreeSurfer and 61 regions based on functional and structural abnormalities previously reported in patients with CFS. Classification was performed in RapidMiner using a linear support vector machine and bootstrap optimism correction. We compared ML classifiers based on (1) 61 a priori sMRI regional estimates and (2) SR ratings. The sMRI model achieved 79.58% classification accuracy. The SR (accuracy = 95.95%) outperformed both sMRI models. Estimates from multiple brain areas related to cognition, emotion, and memory contributed strongly to group classification. This is the first ML-based group classification of CFS. Our findings suggest that sMRI abnormalities are useful for discriminating CFS patients from HC, but SR ratings remain most effective in classification tasks.

Chinese wine classification system based on micrograph using combination of shape and structure features

NASA Astrophysics Data System (ADS)

Wan, Yi

2011-06-01

Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

18 CFR 1317.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-04-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1317.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 618.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-10-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 618.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

18 CFR 1317.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-04-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1317.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

31 CFR 28.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-07-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 28.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

31 CFR 28.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-07-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 28.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 618.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-10-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 618.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

31 CFR 28.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-07-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 28.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

31 CFR 28.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-07-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 28.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

18 CFR 1317.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-04-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1317.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 618.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-10-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 618.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

18 CFR 1317.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-04-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1317.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 618.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-10-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 618.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

31 CFR 28.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-07-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 28.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

45 CFR 618.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-10-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 618.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

18 CFR 1317.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-04-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1317.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

Principles for ecological classification

Treesearch

Dennis H. Grossman; Patrick Bourgeron; Wolf-Dieter N. Busch; David T. Cleland; William Platts; G. Ray; C. Robins; Gary Roloff

1999-01-01

The principal purpose of any classification is to relate common properties among different entities to facilitate understanding of evolutionary and adaptive processes. In the context of this volume, it is to facilitate ecosystem stewardship, i.e., to help support ecosystem conservation and management objectives.

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

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

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

DOE PAGES

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.; ...

2015-10-09

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

Structural knowledge learning from maps for supervised land cover/use classification: Application to the monitoring of land cover/use maps in French Guiana

NASA Astrophysics Data System (ADS)

Bayoudh, Meriam; Roux, Emmanuel; Richard, Gilles; Nock, Richard

2015-03-01

The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.

Protein structure database search and evolutionary classification.

PubMed

Yang, Jinn-Moon; Tung, Chi-Hua

2006-01-01

As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using this method, we first identified 23 states of the structural alphabet that represent pattern profiles of the backbone fragments and then used them to represent protein structure databases as structural alphabet sequence databases (SADB). Our method enhanced BLAST as a search method, using a new structural alphabet substitution matrix (SASM) to find the longest common substructures with high-scoring structured segment pairs from an SADB database. Using personal computers with Intel Pentium4 (2.8 GHz) processors, our method searched more than 10 000 protein structures in 1.3 s and achieved a good agreement with search results from detailed structure alignment methods. [3D-BLAST is available at http://3d-blast.life.nctu.edu.tw].

The helical structure of DNA facilitates binding

NASA Astrophysics Data System (ADS)

Berg, Otto G.; Mahmutovic, Anel; Marklund, Emil; Elf, Johan

2016-09-01

The helical structure of DNA imposes constraints on the rate of diffusion-limited protein binding. Here we solve the reaction-diffusion equations for DNA-like geometries and extend with simulations when necessary. We find that the helical structure can make binding to the DNA more than twice as fast compared to a case where DNA would be reactive only along one side. We also find that this rate advantage remains when the contributions from steric constraints and rotational diffusion of the DNA-binding protein are included. Furthermore, we find that the association rate is insensitive to changes in the steric constraints on the DNA in the helix geometry, while it is much more dependent on the steric constraints on the DNA-binding protein. We conclude that the helical structure of DNA facilitates the nonspecific binding of transcription factors and structural DNA-binding proteins in general.

Structural classification of small, disulfide-rich protein domains.

PubMed

Cheek, Sara; Krishna, S Sri; Grishin, Nick V

2006-05-26

Disulfide-rich domains are small protein domains whose global folds are stabilized primarily by the formation of disulfide bonds and, to a much lesser extent, by secondary structure and hydrophobic interactions. Disulfide-rich domains perform a wide variety of roles functioning as growth factors, toxins, enzyme inhibitors, hormones, pheromones, allergens, etc. These domains are commonly found both as independent (single-domain) proteins and as domains within larger polypeptides. Here, we present a comprehensive structural classification of approximately 3000 small, disulfide-rich protein domains. We find that these domains can be arranged into 41 fold groups on the basis of structural similarity. Our fold groups, which describe broader structural relationships than existing groupings of these domains, bring together representatives with previously unacknowledged similarities; 18 of the 41 fold groups include domains from several SCOP folds. Within the fold groups, the domains are assembled into families of homologs. We define 98 families of disulfide-rich domains, some of which include newly detected homologs, particularly among knottin-like domains. On the basis of this classification, we have examined cases of convergent and divergent evolution of functions performed by disulfide-rich proteins. Disulfide bonding patterns in these domains are also evaluated. Reducible disulfide bonding patterns are much less frequent, while symmetric disulfide bonding patterns are more common than expected from random considerations. Examples of variations in disulfide bonding patterns found within families and fold groups are discussed.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions.

PubMed

Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z; Gao, Xin

2017-01-01

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

An interactive graphics system to facilitate finite element structural analysis

NASA Technical Reports Server (NTRS)

Burk, R. C.; Held, F. H.

1973-01-01

The characteristics of an interactive graphics systems to facilitate the finite element method of structural analysis are described. The finite element model analysis consists of three phases: (1) preprocessing (model generation), (2) problem solution, and (3) postprocessing (interpretation of results). The advantages of interactive graphics to finite element structural analysis are defined.

SCOPe: Manual Curation and Artifact Removal in the Structural Classification of Proteins - extended Database.

PubMed

Chandonia, John-Marc; Fox, Naomi K; Brenner, Steven E

2017-02-03

SCOPe (Structural Classification of Proteins-extended, http://scop.berkeley.edu) is a database of relationships between protein structures that extends the Structural Classification of Proteins (SCOP) database. SCOP is an expert-curated ordering of domains from the majority of proteins of known structure in a hierarchy according to structural and evolutionary relationships. SCOPe classifies the majority of protein structures released since SCOP development concluded in 2009, using a combination of manual curation and highly precise automated tools, aiming to have the same accuracy as fully hand-curated SCOP releases. SCOPe also incorporates and updates the ASTRAL compendium, which provides several databases and tools to aid in the analysis of the sequences and structures of proteins classified in SCOPe. SCOPe continues high-quality manual classification of new superfamilies, a key feature of SCOP. Artifacts such as expression tags are now separated into their own class, in order to distinguish them from the homology-based annotations in the remainder of the SCOPe hierarchy. SCOPe 2.06 contains 77,439 Protein Data Bank entries, double the 38,221 structures classified in SCOP. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

41 CFR 101-4.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-07-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 101-4.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

41 CFR 101-4.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-07-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 101-4.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

41 CFR 101-4.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-07-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 101-4.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

41 CFR 101-4.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-07-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 101-4.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

41 CFR 101-4.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-07-01

... EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 101-4.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

Classification of Structural Coal-Controlling Styles and Analysis on Structural Coal-Controlling Actions

NASA Astrophysics Data System (ADS)

Zhan, Wen-feng

2017-11-01

Tectonism was the primary geologic factors for controlling the formation, deformation, and occurrence of coal measures. As the core of a new round of prediction and evaluation on the coalfield resource potential, the effect of coal-controlling structure was further strengthened and deepened in related researches. By systematically combing the tectonic coal-controlling effect and structure, this study determined the geodynamical classification basis for coal-controlling structures. According to the systematic analysis and summary on the related research results, the coal-controlling structure was categorized into extensional structure, compressive structure, shearing and rotational structure, inverted structure, as well as the sliding structure, syndepositional structure with coalfield structure characteristics. In accordance with the structure combination and distribution characteristics, the six major classes were further classified into 32 subclasses. Moreover, corresponding mode maps were drawn to discuss the basic characteristics and effect of the coal-controlling structures.

15 CFR 8a.520 - Job classification and structure.

Code of Federal Regulations, 2011 CFR

2011-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 8a.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

15 CFR 8a.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 8a.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

15 CFR 8a.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 8a.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

15 CFR 8a.520 - Job classification and structure.

Code of Federal Regulations, 2010 CFR

2010-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 8a.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

15 CFR 8a.520 - Job classification and structure.

Code of Federal Regulations, 2012 CFR

2012-01-01

... THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 8a.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

Cross-over between discrete and continuous protein structure space: insights into automatic classification and networks of protein structures.

PubMed

Pascual-García, Alberto; Abia, David; Ortiz, Angel R; Bastolla, Ugo

2009-03-01

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we

Welcoming with risk classification in teaching hospitals: assessment of structure, process and result.

PubMed

Vituri, Dagmar Willamowius; Inoue, Kelly Cristina; Bellucci Júnior, José Aparecido; de Oliveira, Carlos Aparecido; Rossi, Robson Marcelo; Matsuda, Laura Misue

2013-01-01

To assess, from the worker's viewpoint, the structure, the process and the results of the Emergency Hospital Services that have taken up the guideline of "Welcoming with Risk Classification" in two teaching hospitals of the state of Paraná. Quantitative and descriptive research, exploratory and prospective, using random sampling stratified by professional category, comprising a universe of 216 professional people. They found some points of agreement regarding the promotion of a welcoming and humane environment; privacy and security; welcome and shelter of the companion and also the sheltering and classification of all patients; however, there was disagreement about the comfort of the environment, reference system and counter-reference, prioritisation of seriously ill patients in post-classification service, communication between the members of the multi-professional team and reassessment of the guideline. The workers assess the development of the guideline as being precarious, due mainly to the lack of physical structure, due to the lack of physical structure and shortcomings in the service process.

Acyl carrier protein structural classification and normal mode analysis

PubMed Central

Cantu, David C; Forrester, Michael J; Charov, Katherine; Reilly, Peter J

2012-01-01

All acyl carrier protein primary and tertiary structures were gathered into the ThYme database. They are classified into 16 families by amino acid sequence similarity, with members of the different families having sequences with statistically highly significant differences. These classifications are supported by tertiary structure superposition analysis. Tertiary structures from a number of families are very similar, suggesting that these families may come from a single distant ancestor. Normal vibrational mode analysis was conducted on experimentally determined freestanding structures, showing greater fluctuations at chain termini and loops than in most helices. Their modes overlap more so within families than between different families. The tertiary structures of three acyl carrier protein families that lacked any known structures were predicted as well. PMID:22374859

14 CFR § 1253.520 - Job classification and structure.

Code of Federal Regulations, 2014 CFR

2014-01-01

... NONDISCRIMINATION ON THE BASIS OF SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 1253.520 Job classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

Performance-scalable volumetric data classification for online industrial inspection

NASA Astrophysics Data System (ADS)

Abraham, Aby J.; Sadki, Mustapha; Lea, R. M.

2002-03-01

Non-intrusive inspection and non-destructive testing of manufactured objects with complex internal structures typically requires the enhancement, analysis and visualization of high-resolution volumetric data. Given the increasing availability of fast 3D scanning technology (e.g. cone-beam CT), enabling on-line detection and accurate discrimination of components or sub-structures, the inherent complexity of classification algorithms inevitably leads to throughput bottlenecks. Indeed, whereas typical inspection throughput requirements range from 1 to 1000 volumes per hour, depending on density and resolution, current computational capability is one to two orders-of-magnitude less. Accordingly, speeding up classification algorithms requires both reduction of algorithm complexity and acceleration of computer performance. A shape-based classification algorithm, offering algorithm complexity reduction, by using ellipses as generic descriptors of solids-of-revolution, and supporting performance-scalability, by exploiting the inherent parallelism of volumetric data, is presented. A two-stage variant of the classical Hough transform is used for ellipse detection and correlation of the detected ellipses facilitates position-, scale- and orientation-invariant component classification. Performance-scalability is achieved cost-effectively by accelerating a PC host with one or more COTS (Commercial-Off-The-Shelf) PCI multiprocessor cards. Experimental results are reported to demonstrate the feasibility and cost-effectiveness of the data-parallel classification algorithm for on-line industrial inspection applications.

Classification of Chemicals Based On Structured Toxicity ...

EPA Pesticide Factsheets

Thirty years and millions of dollars worth of pesticide registration toxicity studies, historically stored as hardcopy and scanned documents, have been digitized into highly standardized and structured toxicity data within the Toxicity Reference Database (ToxRefDB). Toxicity-based classifications of chemicals were performed as a model application of ToxRefDB. These endpoints will ultimately provide the anchoring toxicity information for the development of predictive models and biological signatures utilizing in vitro assay data. Utilizing query and structured data mining approaches, toxicity profiles were uniformly generated for greater than 300 chemicals. Based on observation rate, species concordance and regulatory relevance, individual and aggregated effects have been selected to classify the chemicals providing a set of predictable endpoints. ToxRefDB exhibits the utility of transforming unstructured toxicity data into structured data and, furthermore, into computable outputs, and serves as a model for applying such data to address modern toxicological problems.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Protein classification using probabilistic chain graphs and the Gene Ontology structure.

PubMed

Carroll, Steven; Pavlovic, Vladimir

2006-08-01

Probabilistic graphical models have been developed in the past for the task of protein classification. In many cases, classifications obtained from the Gene Ontology have been used to validate these models. In this work we directly incorporate the structure of the Gene Ontology into the graphical representation for protein classification. We present a method in which each protein is represented by a replicate of the Gene Ontology structure, effectively modeling each protein in its own 'annotation space'. Proteins are also connected to one another according to different measures of functional similarity, after which belief propagation is run to make predictions at all ontology terms. The proposed method was evaluated on a set of 4879 proteins from the Saccharomyces Genome Database whose interactions were also recorded in the GRID project. Results indicate that direct utilization of the Gene Ontology improves predictive ability, outperforming traditional models that do not take advantage of dependencies among functional terms. Average increase in accuracy (precision) of positive and negative term predictions of 27.8% (2.0%) over three different similarity measures and three subontologies was observed. C/C++/Perl implementation is available from authors upon request.

Aesthetics-based classification of geological structures in outcrops for geotourism purposes: a tentative proposal

NASA Astrophysics Data System (ADS)

Mikhailenko, Anna V.; Nazarenko, Olesya V.; Ruban, Dmitry A.; Zayats, Pavel P.

2017-03-01

The current growth in geotourism requires an urgent development of classifications of geological features on the basis of criteria that are relevant to tourist perceptions. It appears that structure-related patterns are especially attractive for geotourists. Consideration of the main criteria by which tourists judge beauty and observations made in the geodiversity hotspot of the Western Caucasus allow us to propose a tentative aesthetics-based classification of geological structures in outcrops, with two classes and four subclasses. It is possible to distinguish between regular and quasi-regular patterns (i.e., striped and lined and contorted patterns) and irregular and complex patterns (paysage and sculptured patterns). Typical examples of each case are found both in the study area and on a global scale. The application of the proposed classification permits to emphasise features of interest to a broad range of tourists. Aesthetics-based (i.e., non-geological) classifications are necessary to take into account visions and attitudes of visitors.

From Classification to Epilepsy Ontology and Informatics

PubMed Central

Zhang, Guo-Qiang; Sahoo, Satya S; Lhatoo, Samden D

2012-01-01

Summary The 2010 International League Against Epilepsy (ILAE) classification and terminology commission report proposed a much needed departure from previous classifications to incorporate advances in molecular biology, neuroimaging, and genetics. It proposed an interim classification and defined two key requirements that need to be satisfied. The first is the ability to classify epilepsy in dimensions according to a variety of purposes including clinical research, patient care, and drug discovery. The second is the ability of the classification system to evolve with new discoveries. Multi-dimensionality and flexibility are crucial to the success of any future classification. In addition, a successful classification system must play a central role in the rapidly growing field of epilepsy informatics. An epilepsy ontology, based on classification, will allow information systems to facilitate data-intensive studies and provide a proven route to meeting the two foregoing key requirements. Epilepsy ontology will be a structured terminology system that accommodates proposed and evolving ILAE classifications, the NIH/NINDS Common Data Elements, the ICD systems and explicitly specifies all known relationships between epilepsy concepts in a proper framework. This will aid evidence based epilepsy diagnosis, investigation, treatment and research for a diverse community of clinicians and researchers. Benefits range from systematization of electronic patient records to multi-modal data repositories for research and training manuals for those involved in epilepsy care. Given the complexity, heterogeneity and pace of research advances in the epilepsy domain, such an ontology must be collaboratively developed by key stakeholders in the epilepsy community and experts in knowledge engineering and computer science. PMID:22765502

Classification Structures for Career Information. Occupational Statements, Volume I. Part 1. SOC Numbers 1099 to 4490. Interim Edition.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. National Center for Research in Vocational Education.

"Classification Structures for Career Information" was created to provide Career Information Delivery Systems (CIDS) staff with pertinent and useful occupational information arranged according to the Standard Occupational Classification (SOC) structure. Through this publication, the National Occupational Information Coordinating…

Classification Structures for Career Information. Occupational Statements, Volume I. Part 2. SOC Numbers 4499 to 6560. Interim Edition.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. National Center for Research in Vocational Education.

"Classification Structures for Career Information" was created to provide Career Information Delivery Systems (CIDS) staff with pertinent and useful occupational information arranged according to the Standard Occupational Classification (SOC) structure. Through this publication, the National Occupational Information Coordinating…

Classification Structures for Career Information. Occupational Statements, Volume I. Part 3. SOC Numbers 6699 to 9900. Interim Edition.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. National Center for Research in Vocational Education.

"Classification Structures for Career Information" was created to provide Career Information Delivery Systems (CIDS) staff with pertinent and useful occupational information arranged according to the Standard Occupational Classification (SOC) structure. Through this publication, the National Occupational Information Coordinating…

Barriers and facilitators to mobile phone use for people with aphasia.

PubMed

Greig, Carole-Ann; Harper, Renée; Hirst, Tanya; Howe, Tami; Davidson, Bronwyn

2008-01-01

Mobile phone use increases social participation. People with the communication disorder of aphasia are disadvantaged in the use of information and communication technology such as mobile phones and are reported to be more socially isolated than their peers. The World Health Organization's International Classification of Functioning, Disability and Health provides a framework to address the impact of environmental factors on individual participation. The aim of this preliminary study was to identify the barriers and facilitators to mobile phone use for people with aphasia. A qualitative descriptive study involving two phases was conducted: (1) semi-structured interviews with 6 individuals with aphasia who owned or expressed a desire to own a mobile phone; (2) structured observations of key scenarios identified in the interviews of 3 participants who were sampled from the interview study. Results identified 18 barriers and 9 facilitators to mobile phone use. Key barriers and facilitators were identified in the areas of design and features, written support and training, and communicative partners. Mobile phone use can be problematic for people with aphasia. Intervention needs to address the barriers and utilise the facilitators to mobile phone use for this population. Further research is required to inform policy and intervention programs to ensure that people with aphasia have access to this technology.

Classification of mathematics deficiency using shape and scale analysis of 3D brain structures

NASA Astrophysics Data System (ADS)

Kurtek, Sebastian; Klassen, Eric; Gore, John C.; Ding, Zhaohua; Srivastava, Anuj

2011-03-01

We investigate the use of a recent technique for shape analysis of brain substructures in identifying learning disabilities in third-grade children. This Riemannian technique provides a quantification of differences in shapes of parameterized surfaces, using a distance that is invariant to rigid motions and re-parameterizations. Additionally, it provides an optimal registration across surfaces for improved matching and comparisons. We utilize an efficient gradient based method to obtain the optimal re-parameterizations of surfaces. In this study we consider 20 different substructures in the human brain and correlate the differences in their shapes with abnormalities manifested in deficiency of mathematical skills in 106 subjects. The selection of these structures is motivated in part by the past links between their shapes and cognitive skills, albeit in broader contexts. We have studied the use of both individual substructures and multiple structures jointly for disease classification. Using a leave-one-out nearest neighbor classifier, we obtained a 62.3% classification rate based on the shape of the left hippocampus. The use of multiple structures resulted in an improved classification rate of 71.4%.

Semantic Shot Classification in Sports Video

NASA Astrophysics Data System (ADS)

Duan, Ling-Yu; Xu, Min; Tian, Qi

2003-01-01

In this paper, we present a unified framework for semantic shot classification in sports videos. Unlike previous approaches, which focus on clustering by aggregating shots with similar low-level features, the proposed scheme makes use of domain knowledge of a specific sport to perform a top-down video shot classification, including identification of video shot classes for each sport, and supervised learning and classification of the given sports video with low-level and middle-level features extracted from the sports video. It is observed that for each sport we can predefine a small number of semantic shot classes, about 5~10, which covers 90~95% of sports broadcasting video. With the supervised learning method, we can map the low-level features to middle-level semantic video shot attributes such as dominant object motion (a player), camera motion patterns, and court shape, etc. On the basis of the appropriate fusion of those middle-level shot classes, we classify video shots into the predefined video shot classes, each of which has a clear semantic meaning. The proposed method has been tested over 4 types of sports videos: tennis, basketball, volleyball and soccer. Good classification accuracy of 85~95% has been achieved. With correctly classified sports video shots, further structural and temporal analysis, such as event detection, video skimming, table of content, etc, will be greatly facilitated.

A simple working classification proposed for the latrogenic lesions of teeth and associated structures in the oral cavity.

PubMed

Shamim, Thorakkal

2013-09-01

Iatrogenic lesions can affect both hard and soft tissues in the oral cavity, induced by the dentist's activity, manner or therapy. There is no approved simple working classification for the iatrogenic lesions of teeth and associated structures in the oral cavity in the literature. A simple working classification is proposed here for iatrogenic lesions of teeth and associated structures in the oral cavity based on its relation with dental specialities. The dental specialities considered in this classification are conservative dentistry and endodontics, orthodontics, oral and maxillofacial surgery and prosthodontics. This classification will be useful for the dental clinician who is dealing with diseases of oral cavity.

Automated artery-venous classification of retinal blood vessels based on structural mapping method

NASA Astrophysics Data System (ADS)

Joshi, Vinayak S.; Garvin, Mona K.; Reinhardt, Joseph M.; Abramoff, Michael D.

2012-03-01

Retinal blood vessels show morphologic modifications in response to various retinopathies. However, the specific responses exhibited by arteries and veins may provide a precise diagnostic information, i.e., a diabetic retinopathy may be detected more accurately with the venous dilatation instead of average vessel dilatation. In order to analyze the vessel type specific morphologic modifications, the classification of a vessel network into arteries and veins is required. We previously described a method for identification and separation of retinal vessel trees; i.e. structural mapping. Therefore, we propose the artery-venous classification based on structural mapping and identification of color properties prominent to the vessel types. The mean and standard deviation of each of green channel intensity and hue channel intensity are analyzed in a region of interest around each centerline pixel of a vessel. Using the vector of color properties extracted from each centerline pixel, it is classified into one of the two clusters (artery and vein), obtained by the fuzzy-C-means clustering. According to the proportion of clustered centerline pixels in a particular vessel, and utilizing the artery-venous crossing property of retinal vessels, each vessel is assigned a label of an artery or a vein. The classification results are compared with the manually annotated ground truth (gold standard). We applied the proposed method to a dataset of 15 retinal color fundus images resulting in an accuracy of 88.28% correctly classified vessel pixels. The automated classification results match well with the gold standard suggesting its potential in artery-venous classification and the respective morphology analysis.

Classification of damage in structural systems using time series analysis and supervised and unsupervised pattern recognition techniques

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; de Lautour, Oliver R.

2010-04-01

Developed for studying long, periodic records of various measured quantities, time series analysis methods are inherently suited and offer interesting possibilities for Structural Health Monitoring (SHM) applications. However, their use in SHM can still be regarded as an emerging application and deserves more studies. In this research, Autoregressive (AR) models were used to fit experimental acceleration time histories from two experimental structural systems, a 3- storey bookshelf-type laboratory structure and the ASCE Phase II SHM Benchmark Structure, in healthy and several damaged states. The coefficients of the AR models were chosen as damage sensitive features. Preliminary visual inspection of the large, multidimensional sets of AR coefficients to check the presence of clusters corresponding to different damage severities was achieved using Sammon mapping - an efficient nonlinear data compression technique. Systematic classification of damage into states based on the analysis of the AR coefficients was achieved using two supervised classification techniques: Nearest Neighbor Classification (NNC) and Learning Vector Quantization (LVQ), and one unsupervised technique: Self-organizing Maps (SOM). This paper discusses the performance of AR coefficients as damage sensitive features and compares the efficiency of the three classification techniques using experimental data.

Multilabel user classification using the community structure of online networks

PubMed Central

Papadopoulos, Symeon; Kompatsiaris, Yiannis

2017-01-01

We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user’s graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score. PMID:28278242

Multilabel user classification using the community structure of online networks.

PubMed

Rizos, Georgios; Papadopoulos, Symeon; Kompatsiaris, Yiannis

2017-01-01

We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.

An integrative dimensional classification of personality disorder.

PubMed

Widiger, Thomas A; Livesley, W John; Clark, Lee Anna

2009-09-01

Psychological assessment research concerns how to describe psychological dysfunction in ways that are both valid and useful. Recent advances in assessment research hold the promise of facilitating significant improvements in description and diagnosis. One such contribution is in the classification of personality disorder symptomatology. The American Psychiatric Association's diagnostic manual considers personality disorders to be categorically distinct entities. However, research assessing personality disorders has consistently supported a dimensional perspective. Recognition of the many limitations of categorical models of personality disorder classification has led to the development of a variety of alternative proposals, which further research has indicated can be integrated within a common hierarchical structure. This article offers an alternative integrated dimensional model of normal and abnormal personality structure, and it illustrates how such a model could be used clinically to describe patients' normal adaptive personality traits as well as their maladaptive personality traits that could provide the basis for future assessments of personality disorder. The empirical support, feasibility, and clinical utility of the proposal are discussed. Points of ambiguity and dispute are highlighted, and suggestions for future research are provided. Copyright 2009 APA, all rights reserved.

Automatic classification of protein structures relying on similarities between alignments

PubMed Central

2012-01-01

Background Identification of protein structural cores requires isolation of sets of proteins all sharing a same subset of structural motifs. In the context of an ever growing number of available 3D protein structures, standard and automatic clustering algorithms require adaptations so as to allow for efficient identification of such sets of proteins. Results When considering a pair of 3D structures, they are stated as similar or not according to the local similarities of their matching substructures in a structural alignment. This binary relation can be represented in a graph of similarities where a node represents a 3D protein structure and an edge states that two 3D protein structures are similar. Therefore, classifying proteins into structural families can be viewed as a graph clustering task. Unfortunately, because such a graph encodes only pairwise similarity information, clustering algorithms may include in the same cluster a subset of 3D structures that do not share a common substructure. In order to overcome this drawback we first define a ternary similarity on a triple of 3D structures as a constraint to be satisfied by the graph of similarities. Such a ternary constraint takes into account similarities between pairwise alignments, so as to ensure that the three involved protein structures do have some common substructure. We propose hereunder a modification algorithm that eliminates edges from the original graph of similarities and gives a reduced graph in which no ternary constraints are violated. Our approach is then first to build a graph of similarities, then to reduce the graph according to the modification algorithm, and finally to apply to the reduced graph a standard graph clustering algorithm. Such method was used for classifying ASTRAL-40 non-redundant protein domains, identifying significant pairwise similarities with Yakusa, a program devised for rapid 3D structure alignments. Conclusions We show that filtering similarities prior to standard

Classification of document page images based on visual similarity of layout structures

NASA Astrophysics Data System (ADS)

Shin, Christian K.; Doermann, David S.

1999-12-01

Searching for documents by their type or genre is a natural way to enhance the effectiveness of document retrieval. The layout of a document contains a significant amount of information that can be used to classify a document's type in the absence of domain specific models. A document type or genre can be defined by the user based primarily on layout structure. Our classification approach is based on 'visual similarity' of the layout structure by building a supervised classifier, given examples of the class. We use image features, such as the percentages of tex and non-text (graphics, image, table, and ruling) content regions, column structures, variations in the point size of fonts, the density of content area, and various statistics on features of connected components which can be derived from class samples without class knowledge. In order to obtain class labels for training samples, we conducted a user relevance test where subjects ranked UW-I document images with respect to the 12 representative images. We implemented our classification scheme using the OC1, a decision tree classifier, and report our findings.

The history of the CATH structural classification of protein domains.

PubMed

Sillitoe, Ian; Dawson, Natalie; Thornton, Janet; Orengo, Christine

2015-12-01

This article presents a historical review of the protein structure classification database CATH. Together with the SCOP database, CATH remains comprehensive and reasonably up-to-date with the now more than 100,000 protein structures in the PDB. We review the expansion of the CATH and SCOP resources to capture predicted domain structures in the genome sequence data and to provide information on the likely functions of proteins mediated by their constituent domains. The establishment of comprehensive function annotation resources has also meant that domain families can be functionally annotated allowing insights into functional divergence and evolution within protein families. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

Harnessing user generated multimedia content in the creation of collaborative classification structures and retrieval learning games

NASA Astrophysics Data System (ADS)

Borchert, Otto Jerome

This paper describes a software tool to assist groups of people in the classification and identification of real world objects called the Classification, Identification, and Retrieval-based Collaborative Learning Environment (CIRCLE). A thorough literature review identified current pedagogical theories that were synthesized into a series of five tasks: gathering, elaboration, classification, identification, and reinforcement through game play. This approach is detailed as part of an included peer reviewed paper. Motivation is increased through the use of formative and summative gamification; getting points completing important portions of the tasks and playing retrieval learning based games, respectively, which is also included as a peer-reviewed conference proceedings paper. Collaboration is integrated into the experience through specific tasks and communication mediums. Implementation focused on a REST-based client-server architecture. The client is a series of web-based interfaces to complete each of the tasks, support formal classroom interaction through faculty accounts and student tracking, and a module for peers to help each other. The server, developed using an in-house JavaMOO platform, stores relevant project data and serves data through a series of messages implemented as a JavaScript Object Notation Application Programming Interface (JSON API). Through a series of two beta tests and two experiments, it was discovered the second, elaboration, task requires considerable support. While students were able to properly suggest experiments and make observations, the subtask involving cleaning the data for use in CIRCLE required extra support. When supplied with more structured data, students were enthusiastic about the classification and identification tasks, showing marked improvement in usability scores and in open ended survey responses. CIRCLE tracks a variety of educationally relevant variables, facilitating support for instructors and researchers. Future

Structural vibration-based damage classification of delaminated smart composite laminates

NASA Astrophysics Data System (ADS)

Khan, Asif; Kim, Heung Soo; Sohn, Jung Woo

2018-03-01

Separation along the interfaces of layers (delamination) is a principal mode of failure in laminated composites and its detection is of prime importance for structural integrity of composite materials. In this work, structural vibration response is employed to detect and classify delaminations in piezo-bonded laminated composites. Improved layerwise theory and finite element method are adopted to develop the electromechanically coupled governing equation of a smart composite laminate with and without delaminations. Transient responses of the healthy and damaged structures are obtained through a surface bonded piezoelectric sensor by solving the governing equation in the time domain. Wavelet packet transform (WPT) and linear discriminant analysis (LDA) are employed to extract discriminative features from the structural vibration response of the healthy and delaminated structures. Dendrogram-based support vector machine (DSVM) is used to classify the discriminative features. The confusion matrix of the classification algorithm provided physically consistent results.

Structure D'Ensemble, Multiple Classification, Multiple Seriation and Amount of Irrelevant Information

ERIC Educational Resources Information Center

Hamel, B. Remmo; Van Der Veer, M. A. A.

1972-01-01

A significant positive correlation between multiple classification was found, in testing 65 children aged 6 to 8 years, at the stage of concrete operations. This is interpreted as support for the existence of a structure d'ensemble of operational schemes in the period of concrete operations. (Authors)

Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification.

PubMed

Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V; Robles, Montserrat; Aparici, F; Martí-Bonmatí, L; García-Gómez, Juan M

2015-01-01

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation.

Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

PubMed Central

Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V.; Robles, Montserrat; Aparici, F.; Martí-Bonmatí, L.; García-Gómez, Juan M.

2015-01-01

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation. PMID:25978453

The Role of Facial Attractiveness and Facial Masculinity/Femininity in Sex Classification of Faces

PubMed Central

Hoss, Rebecca A.; Ramsey, Jennifer L.; Griffin, Angela M.; Langlois, Judith H.

2005-01-01

We tested whether adults (Experiment 1) and 4–5-year-old children (Experiment 2) identify the sex of high attractive faces faster and more accurately than low attractive faces in a reaction time task. We also assessed whether facial masculinity/femininity facilitated identification of sex. Results showed that attractiveness facilitated adults’ sex classification of both female and male faces and children’s sex classification of female, but not male, faces. Moreover, attractiveness affected the speed and accuracy of sex classification independent of masculinity/femininity. High masculinity in male faces, but not high femininity in female faces, also facilitated sex classification for both adults and children. These findings provide important new data on how the facial cues of attractiveness and masculinity/femininity contribute to the task of sex classification and provide evidence for developmental differences in how adults and children use these cues. Additionally, these findings provide support for Langlois and Roggman’s (1990) averageness theory of attractiveness. PMID:16457167

Di-codon Usage for Gene Classification

NASA Astrophysics Data System (ADS)

Nguyen, Minh N.; Ma, Jianmin; Fogel, Gary B.; Rajapakse, Jagath C.

Classification of genes into biologically related groups facilitates inference of their functions. Codon usage bias has been described previously as a potential feature for gene classification. In this paper, we demonstrate that di-codon usage can further improve classification of genes. By using both codon and di-codon features, we achieve near perfect accuracies for the classification of HLA molecules into major classes and sub-classes. The method is illustrated on 1,841 HLA sequences which are classified into two major classes, HLA-I and HLA-II. Major classes are further classified into sub-groups. A binary SVM using di-codon usage patterns achieved 99.95% accuracy in the classification of HLA genes into major HLA classes; and multi-class SVM achieved accuracy rates of 99.82% and 99.03% for sub-class classification of HLA-I and HLA-II genes, respectively. Furthermore, by combining codon and di-codon usages, the prediction accuracies reached 100%, 99.82%, and 99.84% for HLA major class classification, and for sub-class classification of HLA-I and HLA-II genes, respectively.

Probability of major depression diagnostic classification using semi-structured versus fully structured diagnostic interviews.

PubMed

Levis, Brooke; Benedetti, Andrea; Riehm, Kira E; Saadat, Nazanin; Levis, Alexander W; Azar, Marleine; Rice, Danielle B; Chiovitti, Matthew J; Sanchez, Tatiana A; Cuijpers, Pim; Gilbody, Simon; Ioannidis, John P A; Kloda, Lorie A; McMillan, Dean; Patten, Scott B; Shrier, Ian; Steele, Russell J; Ziegelstein, Roy C; Akena, Dickens H; Arroll, Bruce; Ayalon, Liat; Baradaran, Hamid R; Baron, Murray; Beraldi, Anna; Bombardier, Charles H; Butterworth, Peter; Carter, Gregory; Chagas, Marcos H; Chan, Juliana C N; Cholera, Rushina; Chowdhary, Neerja; Clover, Kerrie; Conwell, Yeates; de Man-van Ginkel, Janneke M; Delgadillo, Jaime; Fann, Jesse R; Fischer, Felix H; Fischler, Benjamin; Fung, Daniel; Gelaye, Bizu; Goodyear-Smith, Felicity; Greeno, Catherine G; Hall, Brian J; Hambridge, John; Harrison, Patricia A; Hegerl, Ulrich; Hides, Leanne; Hobfoll, Stevan E; Hudson, Marie; Hyphantis, Thomas; Inagaki, Masatoshi; Ismail, Khalida; Jetté, Nathalie; Khamseh, Mohammad E; Kiely, Kim M; Lamers, Femke; Liu, Shen-Ing; Lotrakul, Manote; Loureiro, Sonia R; Löwe, Bernd; Marsh, Laura; McGuire, Anthony; Mohd Sidik, Sherina; Munhoz, Tiago N; Muramatsu, Kumiko; Osório, Flávia L; Patel, Vikram; Pence, Brian W; Persoons, Philippe; Picardi, Angelo; Rooney, Alasdair G; Santos, Iná S; Shaaban, Juwita; Sidebottom, Abbey; Simning, Adam; Stafford, Lesley; Sung, Sharon; Tan, Pei Lin Lynnette; Turner, Alyna; van der Feltz-Cornelis, Christina M; van Weert, Henk C; Vöhringer, Paul A; White, Jennifer; Whooley, Mary A; Winkley, Kirsty; Yamada, Mitsuhiko; Zhang, Yuying; Thombs, Brett D

2018-06-01

Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.AimsTo evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics. Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit. A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15-3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98-10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7-15) (OR = 0.96; 95% CI = 0.56-1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26-0.97). The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.Declaration of interestDrs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the

Object Classification in Semi Structured Enviroment Using Forward-Looking Sonar

PubMed Central

dos Santos, Matheus; Ribeiro, Pedro Otávio; Núñez, Pedro; Botelho, Silvia

2017-01-01

The submarine exploration using robots has been increasing in recent years. The automation of tasks such as monitoring, inspection, and underwater maintenance requires the understanding of the robot’s environment. The object recognition in the scene is becoming a critical issue for these systems. On this work, an underwater object classification pipeline applied in acoustic images acquired by Forward-Looking Sonar (FLS) are studied. The object segmentation combines thresholding, connected pixels searching and peak of intensity analyzing techniques. The object descriptor extract intensity and geometric features of the detected objects. A comparison between the Support Vector Machine, K-Nearest Neighbors, and Random Trees classifiers are presented. An open-source tool was developed to annotate and classify the objects and evaluate their classification performance. The proposed method efficiently segments and classifies the structures in the scene using a real dataset acquired by an underwater vehicle in a harbor area. Experimental results demonstrate the robustness and accuracy of the method described in this paper. PMID:28961163

Bayesian Network Structure Learning for Urban Land Use Classification from Landsat ETM+ and Ancillary Data

NASA Astrophysics Data System (ADS)

Park, M.; Stenstrom, M. K.

2004-12-01

Recognizing urban information from the satellite imagery is problematic due to the diverse features and dynamic changes of urban landuse. The use of Landsat imagery for urban land use classification involves inherent uncertainty due to its spatial resolution and the low separability among land uses. To resolve the uncertainty problem, we investigated the performance of Bayesian networks to classify urban land use since Bayesian networks provide a quantitative way of handling uncertainty and have been successfully used in many areas. In this study, we developed the optimized networks for urban land use classification from Landsat ETM+ images of Marina del Rey area based on USGS land cover/use classification level III. The networks started from a tree structure based on mutual information between variables and added the links to improve accuracy. This methodology offers several advantages: (1) The network structure shows the dependency relationships between variables. The class node value can be predicted even with particular band information missing due to sensor system error. The missing information can be inferred from other dependent bands. (2) The network structure provides information of variables that are important for the classification, which is not available from conventional classification methods such as neural networks and maximum likelihood classification. In our case, for example, bands 1, 5 and 6 are the most important inputs in determining the land use of each pixel. (3) The networks can be reduced with those input variables important for classification. This minimizes the problem without considering all possible variables. We also examined the effect of incorporating ancillary data: geospatial information such as X and Y coordinate values of each pixel and DEM data, and vegetation indices such as NDVI and Tasseled Cap transformation. The results showed that the locational information improved overall accuracy (81%) and kappa coefficient (76%), and

Using discordance to improve classification in narrative clinical databases: an application to community-acquired pneumonia.

PubMed

Hripcsak, George; Knirsch, Charles; Zhou, Li; Wilcox, Adam; Melton, Genevieve B

2007-03-01

Data mining in electronic medical records may facilitate clinical research, but much of the structured data may be miscoded, incomplete, or non-specific. The exploitation of narrative data using natural language processing may help, although nesting, varying granularity, and repetition remain challenges. In a study of community-acquired pneumonia using electronic records, these issues led to poor classification. Limiting queries to accurate, complete records led to vastly reduced, possibly biased samples. We exploited knowledge latent in the electronic records to improve classification. A similarity metric was used to cluster cases. We defined discordance as the degree to which cases within a cluster give different answers for some query that addresses a classification task of interest. Cases with higher discordance are more likely to be incorrectly classified, and can be reviewed manually to adjust the classification, improve the query, or estimate the likely accuracy of the query. In a study of pneumonia--in which the ICD9-CM coding was found to be very poor--the discordance measure was statistically significantly correlated with classification correctness (.45; 95% CI .15-.62).

Single-particle cryo-EM using alignment by classification (ABC): the structure of Lumbricus terrestris haemoglobin.

PubMed

Afanasyev, Pavel; Seer-Linnemayr, Charlotte; Ravelli, Raimond B G; Matadeen, Rishi; De Carlo, Sacha; Alewijnse, Bart; Portugal, Rodrigo V; Pannu, Navraj S; Schatz, Michael; van Heel, Marin

2017-09-01

Single-particle cryogenic electron microscopy (cryo-EM) can now yield near-atomic resolution structures of biological complexes. However, the reference-based alignment algorithms commonly used in cryo-EM suffer from reference bias, limiting their applicability (also known as the 'Einstein from random noise' problem). Low-dose cryo-EM therefore requires robust and objective approaches to reveal the structural information contained in the extremely noisy data, especially when dealing with small structures. A reference-free pipeline is presented for obtaining near-atomic resolution three-dimensional reconstructions from heterogeneous ('four-dimensional') cryo-EM data sets. The methodologies integrated in this pipeline include a posteriori camera correction, movie-based full-data-set contrast transfer function determination, movie-alignment algorithms, (Fourier-space) multivariate statistical data compression and unsupervised classification, 'random-startup' three-dimensional reconstructions, four-dimensional structural refinements and Fourier shell correlation criteria for evaluating anisotropic resolution. The procedures exclusively use information emerging from the data set itself, without external 'starting models'. Euler-angle assignments are performed by angular reconstitution rather than by the inherently slower projection-matching approaches. The comprehensive 'ABC-4D' pipeline is based on the two-dimensional reference-free 'alignment by classification' (ABC) approach, where similar images in similar orientations are grouped by unsupervised classification. Some fundamental differences between X-ray crystallography versus single-particle cryo-EM data collection and data processing are discussed. The structure of the giant haemoglobin from Lumbricus terrestris at a global resolution of ∼3.8 Å is presented as an example of the use of the ABC-4D procedure.

Classification and Framing in the Case Method: Discussion Leaders' Questions

ERIC Educational Resources Information Center

Badger, James

2010-01-01

Basil Bernstein's classification and framing was adopted as a theoretical model to analyse the instruction of two university professors who incorporated case studies into their graduate business and education courses. Classification and framing allows for a meaningful analysis of the discussion leader's questions that facilitate students'…

Applying an Ensemble Classification Tree Approach to the Prediction of Completion of a 12-Step Facilitation Intervention with Stimulant Abusers

PubMed Central

Doyle, Suzanne R.; Donovan, Dennis M.

2014-01-01

Aims The purpose of this study was to explore the selection of predictor variables in the evaluation of drug treatment completion using an ensemble approach with classification trees. The basic methodology is reviewed and the subagging procedure of random subsampling is applied. Methods Among 234 individuals with stimulant use disorders randomized to a 12-Step facilitative intervention shown to increase stimulant use abstinence, 67.52% were classified as treatment completers. A total of 122 baseline variables were used to identify factors associated with completion. Findings The number of types of self-help activity involvement prior to treatment was the predominant predictor. Other effective predictors included better coping self-efficacy for substance use in high-risk situations, more days of prior meeting attendance, greater acceptance of the Disease model, higher confidence for not resuming use following discharge, lower ASI Drug and Alcohol composite scores, negative urine screens for cocaine or marijuana, and fewer employment problems. Conclusions The application of an ensemble subsampling regression tree method utilizes the fact that classification trees are unstable but, on average, produce an improved prediction of the completion of drug abuse treatment. The results support the notion there are early indicators of treatment completion that may allow for modification of approaches more tailored to fitting the needs of individuals and potentially provide more successful treatment engagement and improved outcomes. PMID:25134038

Text Classification for Organizational Researchers

PubMed Central

Kobayashi, Vladimer B.; Mol, Stefan T.; Berkers, Hannah A.; Kismihók, Gábor; Den Hartog, Deanne N.

2017-01-01

Organizations are increasingly interested in classifying texts or parts thereof into categories, as this enables more effective use of their information. Manual procedures for text classification work well for up to a few hundred documents. However, when the number of documents is larger, manual procedures become laborious, time-consuming, and potentially unreliable. Techniques from text mining facilitate the automatic assignment of text strings to categories, making classification expedient, fast, and reliable, which creates potential for its application in organizational research. The purpose of this article is to familiarize organizational researchers with text mining techniques from machine learning and statistics. We describe the text classification process in several roughly sequential steps, namely training data preparation, preprocessing, transformation, application of classification techniques, and validation, and provide concrete recommendations at each step. To help researchers develop their own text classifiers, the R code associated with each step is presented in a tutorial. The tutorial draws from our own work on job vacancy mining. We end the article by discussing how researchers can validate a text classification model and the associated output. PMID:29881249

Integrative Chemical-Biological Read-Across Approach for Chemical Hazard Classification

PubMed Central

Low, Yen; Sedykh, Alexander; Fourches, Denis; Golbraikh, Alexander; Whelan, Maurice; Rusyn, Ivan; Tropsha, Alexander

2013-01-01

Traditional read-across approaches typically rely on the chemical similarity principle to predict chemical toxicity; however, the accuracy of such predictions is often inadequate due to the underlying complex mechanisms of toxicity. Here we report on the development of a hazard classification and visualization method that draws upon both chemical structural similarity and comparisons of biological responses to chemicals measured in multiple short-term assays (”biological” similarity). The Chemical-Biological Read-Across (CBRA) approach infers each compound's toxicity from those of both chemical and biological analogs whose similarities are determined by the Tanimoto coefficient. Classification accuracy of CBRA was compared to that of classical RA and other methods using chemical descriptors alone, or in combination with biological data. Different types of adverse effects (hepatotoxicity, hepatocarcinogenicity, mutagenicity, and acute lethality) were classified using several biological data types (gene expression profiling and cytotoxicity screening). CBRA-based hazard classification exhibited consistently high external classification accuracy and applicability to diverse chemicals. Transparency of the CBRA approach is aided by the use of radial plots that show the relative contribution of analogous chemical and biological neighbors. Identification of both chemical and biological features that give rise to the high accuracy of CBRA-based toxicity prediction facilitates mechanistic interpretation of the models. PMID:23848138

Structural MRI-based detection of Alzheimer's disease using feature ranking and classification error.

PubMed

Beheshti, Iman; Demirel, Hasan; Farokhian, Farnaz; Yang, Chunlan; Matsuda, Hiroshi

2016-12-01

This paper presents an automatic computer-aided diagnosis (CAD) system based on feature ranking for detection of Alzheimer's disease (AD) using structural magnetic resonance imaging (sMRI) data. The proposed CAD system is composed of four systematic stages. First, global and local differences in the gray matter (GM) of AD patients compared to the GM of healthy controls (HCs) are analyzed using a voxel-based morphometry technique. The aim is to identify significant local differences in the volume of GM as volumes of interests (VOIs). Second, the voxel intensity values of the VOIs are extracted as raw features. Third, the raw features are ranked using a seven-feature ranking method, namely, statistical dependency (SD), mutual information (MI), information gain (IG), Pearson's correlation coefficient (PCC), t-test score (TS), Fisher's criterion (FC), and the Gini index (GI). The features with higher scores are more discriminative. To determine the number of top features, the estimated classification error based on training set made up of the AD and HC groups is calculated, with the vector size that minimized this error selected as the top discriminative feature. Fourth, the classification is performed using a support vector machine (SVM). In addition, a data fusion approach among feature ranking methods is introduced to improve the classification performance. The proposed method is evaluated using a data-set from ADNI (130 AD and 130 HC) with 10-fold cross-validation. The classification accuracy of the proposed automatic system for the diagnosis of AD is up to 92.48% using the sMRI data. An automatic CAD system for the classification of AD based on feature-ranking method and classification errors is proposed. In this regard, seven-feature ranking methods (i.e., SD, MI, IG, PCC, TS, FC, and GI) are evaluated. The optimal size of top discriminative features is determined by the classification error estimation in the training phase. The experimental results indicate that

A Functional-Phylogenetic Classification System for Transmembrane Solute Transporters

PubMed Central

Saier, Milton H.

2000-01-01

A comprehensive classification system for transmembrane molecular transporters has been developed and recently approved by the transport panel of the nomenclature committee of the International Union of Biochemistry and Molecular Biology. This system is based on (i) transporter class and subclass (mode of transport and energy coupling mechanism), (ii) protein phylogenetic family and subfamily, and (iii) substrate specificity. Almost all of the more than 250 identified families of transporters include members that function exclusively in transport. Channels (115 families), secondary active transporters (uniporters, symporters, and antiporters) (78 families), primary active transporters (23 families), group translocators (6 families), and transport proteins of ill-defined function or of unknown mechanism (51 families) constitute distinct categories. Transport mode and energy coupling prove to be relatively immutable characteristics and therefore provide primary bases for classification. Phylogenetic grouping reflects structure, function, mechanism, and often substrate specificity and therefore provides a reliable secondary basis for classification. Substrate specificity and polarity of transport prove to be more readily altered during evolutionary history and therefore provide a tertiary basis for classification. With very few exceptions, a phylogenetic family of transporters includes members that function by a single transport mode and energy coupling mechanism, although a variety of substrates may be transported, sometimes with either inwardly or outwardly directed polarity. In this review, I provide cross-referencing of well-characterized constituent transporters according to (i) transport mode, (ii) energy coupling mechanism, (iii) phylogenetic grouping, and (iv) substrates transported. The structural features and distribution of recognized family members throughout the living world are also evaluated. The tabulations should facilitate familial and functional

Multivariate Classification of Structural MRI Data Detects Chronic Low Back Pain

PubMed Central

Ung, Hoameng; Brown, Justin E.; Johnson, Kevin A.; Younger, Jarred; Hush, Julia; Mackey, Sean

2014-01-01

Chronic low back pain (cLBP) has a tremendous personal and socioeconomic impact, yet the underlying pathology remains a mystery in the majority of cases. An objective measure of this condition, that augments self-report of pain, could have profound implications for diagnostic characterization and therapeutic development. Contemporary research indicates that cLBP is associated with abnormal brain structure and function. Multivariate analyses have shown potential to detect a number of neurological diseases based on structural neuroimaging. Therefore, we aimed to empirically evaluate such an approach in the detection of cLBP, with a goal to also explore the relevant neuroanatomy. We extracted brain gray matter (GM) density from magnetic resonance imaging scans of 47 patients with cLBP and 47 healthy controls. cLBP was classified with an accuracy of 76% by support vector machine analysis. Primary drivers of the classification included areas of the somatosensory, motor, and prefrontal cortices—all areas implicated in the pain experience. Differences in areas of the temporal lobe, including bordering the amygdala, medial orbital gyrus, cerebellum, and visual cortex, were also useful for the classification. Our findings suggest that cLBP is characterized by a pattern of GM changes that can have discriminative power and reflect relevant pathological brain morphology. PMID:23246778

A crystal-chemical classification of borate structures with emphasis on hydrated borates

USGS Publications Warehouse

Christ, C.L.; Clark, J.R.

1977-01-01

The rules governing formation of hydrated borate polyanions that were proposed by C.L. Christ in 1960 are critically reviewed and new rules added on the basis of recent crystal structure determinations. Principles and classifications previously published by others are also critically reviewed briefly. The fundamental building blocks from which borate polyanions can be constructed are defined on the basis of the number n of boron atoms, and the fully hydrated polyanions are illustrated. Known structures are grouped accordingly, and a shorthand notation using n and symbols ?? = triangle, T = tetrahedron is introduced so that the polyanions can be easily characterized. For example, 3:??+2T describes [B3O3(OH)5]2-. Correct structural formulas are assigned borates with known structures whereas borates of unknown structure are grouped separately. ?? 1977 Springer-Verlag.

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

Rapid Classification of Ordinary Chondrites Using Raman Spectroscopy

NASA Technical Reports Server (NTRS)

Fries, M.; Welzenbach, L.

2014-01-01

Classification of ordinary chondrites is typically done through measurements of the composition of olivine and pyroxenes. Historically, this measurement has usually been performed via electron microprobe, oil immersion or other methods which can be costly through lost sample material during thin section preparation. Raman microscopy can perform the same measurements but considerably faster and with much less sample preparation allowing for faster classification. Raman spectroscopy can facilitate more rapid classification of large amounts of chondrites such as those retrieved from North Africa and potentially Antarctica, are present in large collections, or are submitted to a curation facility by the public. With development, this approach may provide a completely automated classification method of all chondrite types.

Object-based forest classification to facilitate landscape-scale conservation in the Mississippi Alluvial Valley

USGS Publications Warehouse

Mitchell, Michael; Wilson, R. Randy; Twedt, Daniel J.; Mini, Anne E.; James, J. Dale

2016-01-01

The Mississippi Alluvial Valley is a floodplain along the southern extent of the Mississippi River extending from southern Missouri to the Gulf of Mexico. This area once encompassed nearly 10 million ha of floodplain forests, most of which has been converted to agriculture over the past two centuries. Conservation programs in this region revolve around protection of existing forest and reforestation of converted lands. Therefore, an accurate and up to date classification of forest cover is essential for conservation planning, including efforts that prioritize areas for conservation activities. We used object-based image analysis with Random Forest classification to quickly and accurately classify forest cover. We used Landsat band, band ratio, and band index statistics to identify and define similar objects as our training sets instead of selecting individual training points. This provided a single rule-set that was used to classify each of the 11 Landsat 5 Thematic Mapper scenes that encompassed the Mississippi Alluvial Valley. We classified 3,307,910±85,344 ha (32% of this region) as forest. Our overall classification accuracy was 96.9% with Kappa statistic of 0.96. Because this method of forest classification is rapid and accurate, assessment of forest cover can be regularly updated and progress toward forest habitat goals identified in conservation plans can be periodically evaluated.

Functional classification of protein structures by local structure matching in graph representation.

PubMed

Mills, Caitlyn L; Garg, Rohan; Lee, Joslynn S; Tian, Liang; Suciu, Alexandru; Cooperman, Gene; Beuning, Penny J; Ondrechen, Mary Jo

2018-03-31

As a result of high-throughput protein structure initiatives, over 14,400 protein structures have been solved by structural genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP-Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP-Func method to our previously reported method, structurally aligned local sites of activity (SALSA), using the ribulose phosphate binding barrel (RPBB), 6-hairpin glycosidase (6-HG), and Concanavalin A-like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP-Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP-Func methods to predict function. Forty-one SG proteins in the RPBB superfamily, nine SG proteins in the 6-HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community. © 2018 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Classification, disease, and diagnosis.

PubMed

Jutel, Annemarie

2011-01-01

Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

Enhancing communication by using the Coordinated Care Classification System.

PubMed

O'Neal, P V; Kozeny, D K; Garland, P P; Gaunt, S M; Gordon, S C

1998-07-01

Because of the changes in our healthcare system, some clinical nurse specialists (CNSs) are having to expand their traditional roles of clinician, educator, consultant, leader, and researcher to include case management activities. The CNSs at Promina Gwinnett Health System in Lawrenceville, Georgia, have combined CNS and case manager activities and have adopted the title "CNS/Outcomes Coordinator." The CNS/Outcomes Coordinator is responsible for coordinating patient care, promoting team collaboration, and facilitating communication. To inform the healthcare team of the CNS/Outcomes Coordinator's patient responsibilities, the CNS/Outcomes Coordinators developed a Coordinated Care Classification System. This article describes how coordinating patient care, promoting team collaboration, and facilitating communication can be enhanced by the use of a classification system.

Classification of mental disorders*

PubMed Central

Stengel, E.

1959-01-01

One of the fundamental difficulties in devising a classification of mental disorders is the lack of agreement among psychiatrists regarding the concepts upon which it should be based: diagnoses can rarely be verified objectively and the same or similar conditions are described under a confusing variety of names. This situation militates against the ready exchange of ideas and experiences and hampers progress. As a first step towards remedying this state of affairs, the author of the article below has undertaken a critical survey of existing classifications. He shows how some of the difficulties created by lack of knowledge regarding pathology and etiology may be overcome by the use of “operational definitions” and outlines the basic principles on which he believes a generally acceptable international classification might be constructed. If this can be done it should lead to a greater measure of agreement regarding the value of specific treatments for mental disorders and greatly facilitate a broad epidemiological approach to psychiatric research. PMID:13834299

Magnesium-binding architectures in RNA crystal structures: validation, binding preferences, classification and motif detection

PubMed Central

Zheng, Heping; Shabalin, Ivan G.; Handing, Katarzyna B.; Bujnicki, Janusz M.; Minor, Wladek

2015-01-01

The ubiquitous presence of magnesium ions in RNA has long been recognized as a key factor governing RNA folding, and is crucial for many diverse functions of RNA molecules. In this work, Mg2+-binding architectures in RNA were systematically studied using a database of RNA crystal structures from the Protein Data Bank (PDB). Due to the abundance of poorly modeled or incorrectly identified Mg2+ ions, the set of all sites was comprehensively validated and filtered to identify a benchmark dataset of 15 334 ‘reliable’ RNA-bound Mg2+ sites. The normalized frequencies by which specific RNA atoms coordinate Mg2+ were derived for both the inner and outer coordination spheres. A hierarchical classification system of Mg2+ sites in RNA structures was designed and applied to the benchmark dataset, yielding a set of 41 types of inner-sphere and 95 types of outer-sphere coordinating patterns. This classification system has also been applied to describe six previously reported Mg2+-binding motifs and detect them in new RNA structures. Investigation of the most populous site types resulted in the identification of seven novel Mg2+-binding motifs, and all RNA structures in the PDB were screened for the presence of these motifs. PMID:25800744

[Landscape classification: research progress and development trend].

PubMed

Liang, Fa-Chao; Liu, Li-Ming

2011-06-01

Landscape classification is the basis of the researches on landscape structure, process, and function, and also, the prerequisite for landscape evaluation, planning, protection, and management, directly affecting the precision and practicability of landscape research. This paper reviewed the research progress on the landscape classification system, theory, and methodology, and summarized the key problems and deficiencies of current researches. Some major landscape classification systems, e. g. , LANMAP and MUFIC, were introduced and discussed. It was suggested that a qualitative and quantitative comprehensive classification based on the ideology of functional structure shape and on the integral consideration of landscape classification utility, landscape function, landscape structure, physiogeographical factors, and human disturbance intensity should be the major research directions in the future. The integration of mapping, 3S technology, quantitative mathematics modeling, computer artificial intelligence, and professional knowledge to enhance the precision of landscape classification would be the key issues and the development trend in the researches of landscape classification.

Facilitation as Attenuating of Environmental Stress among Structured Microbial Populations.

PubMed

Martins, Suzana Cláudia Silveira; Santaella, Sandra Tédde; Martins, Claudia Miranda; Martins, Rogério Parentoni

2016-01-01

There is currently an intense debate in microbial societies on whether evolution in complex communities is driven by competition or cooperation. Since Darwin, competition for scarce food resources has been considered the main ecological interaction shaping population dynamics and community structure both in vivo and in vitro. However, facilitation may be widespread across several animal and plant species. This could also be true in microbial strains growing under environmental stress. Pure and mixed strains of Serratia marcescens and Candida rugosa were grown in mineral culture media containing phenol. Growth rates were estimated as the angular coefficients computed from linearized growth curves. Fitness index was estimated as the quotient between growth rates computed for lineages grown in isolation and in mixed cultures. The growth rates were significantly higher in associated cultures than in pure cultures and fitness index was greater than 1 for both microbial species showing that the interaction between Serratia marcescens and Candida rugosa yielded more efficient phenol utilization by both lineages. This result corroborates the hypothesis that facilitation between microbial strains can increase their fitness and performance in environmental bioremediation.

Classification Model for Damage Localization in a Plate Structure

NASA Astrophysics Data System (ADS)

Janeliukstis, R.; Ruchevskis, S.; Chate, A.

2018-01-01

The present study is devoted to the problem of damage localization by means of data classification. The commercial ANSYS finite-elements program was used to make a model of a cantilevered composite plate equipped with numerous strain sensors. The plate was divided into zones, and, for data classification purposes, each of them housed several points to which a point mass of magnitude 5 and 10% of plate mass was applied. At each of these points, a numerical modal analysis was performed, from which the first few natural frequencies and strain readings were extracted. The strain data for every point were the input for a classification procedure involving k nearest neighbors and decision trees. The classification model was trained and optimized by finetuning the key parameters of both algorithms. Finally, two new query points were simulated and subjected to a classification in terms of assigning a label to one of the zones of the plate, thus localizing these points. Damage localization results were compared for both algorithms and were found to be in good agreement with the actual application positions of point load.

Do we need a new classification of parotid gland surgery?

PubMed

Wierzbicka, Małgorzata; Piwowarczyk, Krzysztof; Nogala, Hanna; Błaszczyńska, Marzena; Kosiedrowski, Michał; Mazurek, Cezary

2016-06-30

In February 2016 the European Salivary Gland Society (ESGS) presented and recommended classification of parotidectomies based on the anatomical I-V level division of parotid gland. The main goal of this paper is to present the new classification, and to answer the question if it is more precise compared to classic one. 607 patients (315 man, 292 women) operated on for parotid tumours in a tertiary referral centre, Department of Otolaryngology, Head and Neck Surgery, Medical University of Poznań (502 benign and 105 malignant tumours). Parotid surgery descriptions provided by retrospective analysis of all operating protocols covering the years 2006-2015 were "translated" into the new classification proposed by the ESGS. Analysis of operating protocols and fitting them into the new classification proposed by the ESGS show some discrepancies, in both benign and malignant tumours. Based on the re-evaluation of 607 cases, in 94 procedures for benign tumors the only information available was that "surgery was performed within the superficial lobe". Thus, the new classification forces the surgeon to be much more precise than previously. In 3 cases the whole superficial lobe was removed, together with the upper part of the deep lobe. Because the classification lacked parotidectomy I-II-IV, it indicated that the new classification was insufficient in the aforementioned three cases. In 6 cases of ECD more than one parotid gland tumour was removed. Among malignant tumours, total parotidectomy was the predominant procedure. In 3/13 cases of expanded parotidectomy the temporomandibular joint (TMJ) was additionally removed and it seems that the acronym TMJ should be included among the additional resected structures. It is also necessary to supplement the description of the treatment with casuistically resected anatomical structures for oncological purposes (RT planning) and follow-up imaging. Currently, since 2015 in Poland there has been the National Cancer Registry of benign

Facilitating the openEHR approach - organizational structures for defining high-quality archetypes.

PubMed

Kohl, Christian Dominik; Garde, Sebastian; Knaup, Petra

2008-01-01

Using openEHR archetypes to establish an electronic patient record promises rapid development and system interoperability by using or adopting existing archetypes. However, internationally accepted, high quality archetypes which enable a comprehensive semantic interoperability require adequate development and maintenance processes. Therefore, structures have to be created involving different health professions. In the following we present a model which facilitates and governs distributed but cooperative development and adoption of archetypes by different professionals including peer reviews. Our model consists of a hierarchical structure of professional committees and descriptions of the archetype development process considering these different committees.

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Quality assurance of chemical ingredient classification for the National Drug File - Reference Terminology.

PubMed

Zheng, Ling; Yumak, Hasan; Chen, Ling; Ochs, Christopher; Geller, James; Kapusnik-Uner, Joan; Perl, Yehoshua

2017-09-01

The National Drug File - Reference Terminology (NDF-RT) is a large and complex drug terminology consisting of several classification hierarchies on top of an extensive collection of drug concepts. These hierarchies provide important information about clinical drugs, e.g., their chemical ingredients, mechanisms of action, dosage form and physiological effects. Within NDF-RT such information is represented using tens of thousands of roles connecting drugs to classifications. In previous studies, we have introduced various kinds of Abstraction Networks to summarize the content and structure of terminologies in order to facilitate their visual comprehension, and support quality assurance of terminologies. However, these previous kinds of Abstraction Networks are not appropriate for summarizing the NDF-RT classification hierarchies, due to its unique structure. In this paper, we present the novel Ingredient Abstraction Network (IAbN) to summarize, visualize and support the audit of NDF-RT's Chemical Ingredients hierarchy and its associated drugs. A common theme in our quality assurance framework is to use characterizations of sets of concepts, revealed by the Abstraction Network structure, to capture concepts, the modeling of which is more complex than for other concepts. For the IAbN, we characterize drug ingredient concepts as more complex if they belong to IAbN groups with multiple parent groups. We show that such concepts have a statistically significantly higher rate of errors than a control sample and identify two especially common patterns of errors. Copyright © 2017 Elsevier Inc. All rights reserved.

T-RMSD: a web server for automated fine-grained protein structural classification.

PubMed

Magis, Cedrik; Di Tommaso, Paolo; Notredame, Cedric

2013-07-01

This article introduces the T-RMSD web server (tree-based on root-mean-square deviation), a service allowing the online computation of structure-based protein classification. It has been developed to address the relation between structural and functional similarity in proteins, and it allows a fine-grained structural clustering of a given protein family or group of structurally related proteins using distance RMSD (dRMSD) variations. These distances are computed between all pairs of equivalent residues, as defined by the ungapped columns within a given multiple sequence alignment. Using these generated distance matrices (one per equivalent position), T-RMSD produces a structural tree with support values for each cluster node, reminiscent of bootstrap values. These values, associated with the tree topology, allow a quantitative estimate of structural distances between proteins or group of proteins defined by the tree topology. The clusters thus defined have been shown to be structurally and functionally informative. The T-RMSD web server is a free website open to all users and available at http://tcoffee.crg.cat/apps/tcoffee/do:trmsd.

T-RMSD: a web server for automated fine-grained protein structural classification

PubMed Central

Magis, Cedrik; Di Tommaso, Paolo; Notredame, Cedric

2013-01-01

This article introduces the T-RMSD web server (tree-based on root-mean-square deviation), a service allowing the online computation of structure-based protein classification. It has been developed to address the relation between structural and functional similarity in proteins, and it allows a fine-grained structural clustering of a given protein family or group of structurally related proteins using distance RMSD (dRMSD) variations. These distances are computed between all pairs of equivalent residues, as defined by the ungapped columns within a given multiple sequence alignment. Using these generated distance matrices (one per equivalent position), T-RMSD produces a structural tree with support values for each cluster node, reminiscent of bootstrap values. These values, associated with the tree topology, allow a quantitative estimate of structural distances between proteins or group of proteins defined by the tree topology. The clusters thus defined have been shown to be structurally and functionally informative. The T-RMSD web server is a free website open to all users and available at http://tcoffee.crg.cat/apps/tcoffee/do:trmsd. PMID:23716642

Automatic grade classification of Barretts Esophagus through feature enhancement

NASA Astrophysics Data System (ADS)

Ghatwary, Noha; Ahmed, Amr; Ye, Xujiong; Jalab, Hamid

2017-03-01

Barretts Esophagus (BE) is a precancerous condition that affects the esophagus tube and has the risk of developing esophageal adenocarcinoma. BE is the process of developing metaplastic intestinal epithelium and replacing the normal cells in the esophageal area. The detection of BE is considered difficult due to its appearance and properties. The diagnosis is usually done through both endoscopy and biopsy. Recently, Computer Aided Diagnosis systems have been developed to support physicians opinion when facing difficulty in detection/classification in different types of diseases. In this paper, an automatic classification of Barretts Esophagus condition is introduced. The presented method enhances the internal features of a Confocal Laser Endomicroscopy (CLE) image by utilizing a proposed enhancement filter. This filter depends on fractional differentiation and integration that improve the features in the discrete wavelet transform of an image. Later on, various features are extracted from each enhanced image on different levels for the multi-classification process. Our approach is validated on a dataset that consists of a group of 32 patients with 262 images with different histology grades. The experimental results demonstrated the efficiency of the proposed technique. Our method helps clinicians for more accurate classification. This potentially helps to reduce the need for biopsies needed for diagnosis, facilitate the regular monitoring of treatment/development of the patients case and can help train doctors with the new endoscopy technology. The accurate automatic classification is particularly important for the Intestinal Metaplasia (IM) type, which could turn into deadly cancerous. Hence, this work contributes to automatic classification that facilitates early intervention/treatment and decreasing biopsy samples needed.

Robust evaluation of time series classification algorithms for structural health monitoring

NASA Astrophysics Data System (ADS)

Harvey, Dustin Y.; Worden, Keith; Todd, Michael D.

2014-03-01

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and mechanical infrastructure through analysis of structural response measurements. The supervised learning methodology for data-driven SHM involves computation of low-dimensional, damage-sensitive features from raw measurement data that are then used in conjunction with machine learning algorithms to detect, classify, and quantify damage states. However, these systems often suffer from performance degradation in real-world applications due to varying operational and environmental conditions. Probabilistic approaches to robust SHM system design suffer from incomplete knowledge of all conditions a system will experience over its lifetime. Info-gap decision theory enables nonprobabilistic evaluation of the robustness of competing models and systems in a variety of decision making applications. Previous work employed info-gap models to handle feature uncertainty when selecting various components of a supervised learning system, namely features from a pre-selected family and classifiers. In this work, the info-gap framework is extended to robust feature design and classifier selection for general time series classification through an efficient, interval arithmetic implementation of an info-gap data model. Experimental results are presented for a damage type classification problem on a ball bearing in a rotating machine. The info-gap framework in conjunction with an evolutionary feature design system allows for fully automated design of a time series classifier to meet performance requirements under maximum allowable uncertainty.

An Integrative Dimensional Classification of Personality Disorder

ERIC Educational Resources Information Center

Widiger, Thomas A.; Livesley, W. John; Clark, Lee Anna

2009-01-01

Psychological assessment research concerns how to describe psychological dysfunction in ways that are both valid and useful. Recent advances in assessment research hold the promise of facilitating significant improvements in description and diagnosis. One such contribution is in the classification of personality disorder symptomatology. The…

Facilitation as Attenuating of Environmental Stress among Structured Microbial Populations

PubMed Central

Santaella, Sandra Tédde; Martins, Claudia Miranda; Martins, Rogério Parentoni

2016-01-01

There is currently an intense debate in microbial societies on whether evolution in complex communities is driven by competition or cooperation. Since Darwin, competition for scarce food resources has been considered the main ecological interaction shaping population dynamics and community structure both in vivo and in vitro. However, facilitation may be widespread across several animal and plant species. This could also be true in microbial strains growing under environmental stress. Pure and mixed strains of Serratia marcescens and Candida rugosa were grown in mineral culture media containing phenol. Growth rates were estimated as the angular coefficients computed from linearized growth curves. Fitness index was estimated as the quotient between growth rates computed for lineages grown in isolation and in mixed cultures. The growth rates were significantly higher in associated cultures than in pure cultures and fitness index was greater than 1 for both microbial species showing that the interaction between Serratia marcescens and Candida rugosa yielded more efficient phenol utilization by both lineages. This result corroborates the hypothesis that facilitation between microbial strains can increase their fitness and performance in environmental bioremediation. PMID:26904719

Comparative study of classification algorithms for damage classification in smart composite laminates

NASA Astrophysics Data System (ADS)

Khan, Asif; Ryoo, Chang-Kyung; Kim, Heung Soo

2017-04-01

This paper presents a comparative study of different classification algorithms for the classification of various types of inter-ply delaminations in smart composite laminates. Improved layerwise theory is used to model delamination at different interfaces along the thickness and longitudinal directions of the smart composite laminate. The input-output data obtained through surface bonded piezoelectric sensor and actuator is analyzed by the system identification algorithm to get the system parameters. The identified parameters for the healthy and delaminated structure are supplied as input data to the classification algorithms. The classification algorithms considered in this study are ZeroR, Classification via regression, Naïve Bayes, Multilayer Perceptron, Sequential Minimal Optimization, Multiclass-Classifier, and Decision tree (J48). The open source software of Waikato Environment for Knowledge Analysis (WEKA) is used to evaluate the classification performance of the classifiers mentioned above via 75-25 holdout and leave-one-sample-out cross-validation regarding classification accuracy, precision, recall, kappa statistic and ROC Area.

Terminology and classification of muscle injuries in sport: The Munich consensus statement

PubMed Central

Mueller-Wohlfahrt, Hans-Wilhelm; Haensel, Lutz; Mithoefer, Kai; Ekstrand, Jan; English, Bryan; McNally, Steven; Orchard, John; van Dijk, C Niek; Kerkhoffs, Gino M; Schamasch, Patrick; Blottner, Dieter; Swaerd, Leif; Goedhart, Edwin; Ueblacker, Peter

2013-01-01

Objective To provide a clear terminology and classification of muscle injuries in order to facilitate effective communication among medical practitioners and development of systematic treatment strategies. Methods Thirty native English-speaking scientists and team doctors of national and first division professional sports teams were asked to complete a questionnaire on muscle injuries to evaluate the currently used terminology of athletic muscle injury. In addition, a consensus meeting of international sports medicine experts was established to develop practical and scientific definitions of muscle injuries as well as a new and comprehensive classification system. Results The response rate of the survey was 63%. The responses confirmed the marked variability in the use of the terminology relating to muscle injury, with the most obvious inconsistencies for the term strain. In the consensus meeting, practical and systematic terms were defined and established. In addition, a new comprehensive classification system was developed, which differentiates between four types: functional muscle disorders (type 1: overexertion-related and type 2: neuromuscular muscle disorders) describing disorders without macroscopic evidence of fibre tear and structural muscle injuries (type 3: partial tears and type 4: (sub)total tears/tendinous avulsions) with macroscopic evidence of fibre tear, that is, structural damage. Subclassifications are presented for each type. Conclusions A consistent English terminology as well as a comprehensive classification system for athletic muscle injuries which is proven in the daily practice are presented. This will help to improve clarity of communication for diagnostic and therapeutic purposes and can serve as the basis for future comparative studies to address the continued lack of systematic information on muscle injuries in the literature. What are the new things Consensus definitions of the terminology which is used in the field of muscle injuries

Multiclass Classification by Adaptive Network of Dendritic Neurons with Binary Synapses Using Structural Plasticity

PubMed Central

Hussain, Shaista; Basu, Arindam

2016-01-01

The development of power-efficient neuromorphic devices presents the challenge of designing spike pattern classification algorithms which can be implemented on low-precision hardware and can also achieve state-of-the-art performance. In our pursuit of meeting this challenge, we present a pattern classification model which uses a sparse connection matrix and exploits the mechanism of nonlinear dendritic processing to achieve high classification accuracy. A rate-based structural learning rule for multiclass classification is proposed which modifies a connectivity matrix of binary synaptic connections by choosing the best “k” out of “d” inputs to make connections on every dendritic branch (k < < d). Because learning only modifies connectivity, the model is well suited for implementation in neuromorphic systems using address-event representation (AER). We develop an ensemble method which combines several dendritic classifiers to achieve enhanced generalization over individual classifiers. We have two major findings: (1) Our results demonstrate that an ensemble created with classifiers comprising moderate number of dendrites performs better than both ensembles of perceptrons and of complex dendritic trees. (2) In order to determine the moderate number of dendrites required for a specific classification problem, a two-step solution is proposed. First, an adaptive approach is proposed which scales the relative size of the dendritic trees of neurons for each class. It works by progressively adding dendrites with fixed number of synapses to the network, thereby allocating synaptic resources as per the complexity of the given problem. As a second step, theoretical capacity calculations are used to convert each neuronal dendritic tree to its optimal topology where dendrites of each class are assigned different number of synapses. The performance of the model is evaluated on classification of handwritten digits from the benchmark MNIST dataset and compared with other

Spatial-spectral blood cell classification with microscopic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ran, Qiong; Chang, Lan; Li, Wei; Xu, Xiaofeng

2017-10-01

Microscopic hyperspectral images provide a new way for blood cell examination. The hyperspectral imagery can greatly facilitate the classification of different blood cells. In this paper, the microscopic hyperspectral images are acquired by connecting the microscope and the hyperspectral imager, and then tested for blood cell classification. For combined use of the spectral and spatial information provided by hyperspectral images, a spatial-spectral classification method is improved from the classical extreme learning machine (ELM) by integrating spatial context into the image classification task with Markov random field (MRF) model. Comparisons are done among ELM, ELM-MRF, support vector machines(SVM) and SVMMRF methods. Results show the spatial-spectral classification methods(ELM-MRF, SVM-MRF) perform better than pixel-based methods(ELM, SVM), and the proposed ELM-MRF has higher precision and show more accurate location of cells.

Classification of hyperlipidaemias and hyperlipoproteinaemias*

PubMed Central

1970-01-01

Many studies of atherosclerosis have indicated hyperlipidaemia as a predisposing factor to vascular disease. The relationship holds even for mild degrees of hyperlipidaemia, a fact that underlines the importance of this category of disorders. Both primary and secondary hyperlipidaemias represent such a variety of abnormalities that an internationally acceptable provisional classification is highly desirable in order to facilitate communication between scientists with different backgrounds. The present memorandum presents such a classification; it briefly describes the criteria for diagnosis of the main types of hyperlipidaemia as well as the methods of their determination. Because lipoproteins offer more information than analysis of plasma lipids (most of the plasma lipids being bound to various proteins), the classification is based on lipoprotein analyses by electrophoresis and ultracentrifugation. Simpler methods, however, such as the observation of plasma and measurements of cholesterol and triglycerides, are used to the fullest possible extent in determining the lipoprotein patterns. PMID:4930042

A new classification of glaucomas

PubMed Central

Bordeianu, Constantin-Dan

2014-01-01

Purpose To suggest a new glaucoma classification that is pathogenic, etiologic, and clinical. Methods After discussing the logical pathway used in criteria selection, the paper presents the new classification and compares it with the classification currently in use, that is, the one issued by the European Glaucoma Society in 2008. Results The paper proves that the new classification is clear (being based on a coherent and consistently followed set of criteria), is comprehensive (framing all forms of glaucoma), and helps in understanding the sickness understanding (in that it uses a logical framing system). The great advantage is that it facilitates therapeutic decision making in that it offers direct therapeutic suggestions and avoids errors leading to disasters. Moreover, the scheme remains open to any new development. Conclusion The suggested classification is a pathogenic, etiologic, and clinical classification that fulfills the conditions of an ideal classification. The suggested classification is the first classification in which the main criterion is consistently used for the first 5 to 7 crossings until its differentiation capabilities are exhausted. Then, secondary criteria (etiologic and clinical) pick up the relay until each form finds its logical place in the scheme. In order to avoid unclear aspects, the genetic criterion is no longer used, being replaced by age, one of the clinical criteria. The suggested classification brings only benefits to all categories of ophthalmologists: the beginners will have a tool to better understand the sickness and to ease their decision making, whereas the experienced doctors will have their practice simplified. For all doctors, errors leading to therapeutic disasters will be less likely to happen. Finally, researchers will have the object of their work gathered in the group of glaucoma with unknown or uncertain pathogenesis, whereas the results of their work will easily find a logical place in the scheme, as the

Structural classification of CDR-H3 revisited: a lesson in antibody modeling.

PubMed

Kuroda, Daisuke; Shirai, Hiroki; Kobori, Masato; Nakamura, Haruki

2008-11-15

Among the six complementarity-determining regions (CDRs) in the variable domains of an antibody, the third CDR of the heavy chain (CDR-H3), which lies in the center of the antigen-binding site, plays a particularly important role in antigen recognition. CDR-H3 shows significant variability in its length, sequence, and structure. Although difficult, model building of this segment is the most critical step in antibody modeling. Since our first proposal of the "H3-rules," which classify CDR-H3 structure based on amino acid sequence, the number of experimentally determined antibody structures has increased. Here, we revise these H3-rules and propose an improved classification scheme for CDR-H3 structure modeling. In addition, we determine the common features of CDR-H3 in antibody drugs as well as discuss the concept of "antibody druggability," which can be applied as an indicator of antibody evaluation during drug discovery.

Groenewold-Moyal product, α*-cohomology, and classification of translation-invariant non-commutative structures

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

Varshovi, Amir Abbass

2013-07-15

The theory of α*-cohomology is studied thoroughly and it is shown that in each cohomology class there exists a unique 2-cocycle, the harmonic form, which generates a particular Groenewold-Moyal star product. This leads to an algebraic classification of translation-invariant non-commutative structures and shows that any general translation-invariant non-commutative quantum field theory is physically equivalent to a Groenewold-Moyal non-commutative quantum field theory.

Classifications for Cesarean Section: A Systematic Review

PubMed Central

Torloni, Maria Regina; Betran, Ana Pilar; Souza, Joao Paulo; Widmer, Mariana; Allen, Tomas; Gulmezoglu, Metin; Merialdi, Mario

2011-01-01

classification. The use of a single CS classification will facilitate auditing, analyzing and comparing CS rates across different settings and help to create and implement effective strategies specifically targeted to optimize CS rates where necessary. PMID:21283801

Damage classification and estimation in experimental structures using time series analysis and pattern recognition

NASA Astrophysics Data System (ADS)

de Lautour, Oliver R.; Omenzetter, Piotr

2010-07-01

Developed for studying long sequences of regularly sampled data, time series analysis methods are being increasingly investigated for the use of Structural Health Monitoring (SHM). In this research, Autoregressive (AR) models were used to fit the acceleration time histories obtained from two experimental structures: a 3-storey bookshelf structure and the ASCE Phase II Experimental SHM Benchmark Structure, in undamaged and limited number of damaged states. The coefficients of the AR models were considered to be damage-sensitive features and used as input into an Artificial Neural Network (ANN). The ANN was trained to classify damage cases or estimate remaining structural stiffness. The results showed that the combination of AR models and ANNs are efficient tools for damage classification and estimation, and perform well using small number of damage-sensitive features and limited sensors.

The search for structure - Object classification in large data sets. [for astronomers

NASA Technical Reports Server (NTRS)

Kurtz, Michael J.

1988-01-01

Research concerning object classifications schemes are reviewed, focusing on large data sets. Classification techniques are discussed, including syntactic, decision theoretic methods, fuzzy techniques, and stochastic and fuzzy grammars. Consideration is given to the automation of MK classification (Morgan and Keenan, 1973) and other problems associated with the classification of spectra. In addition, the classification of galaxies is examined, including the problems of systematic errors, blended objects, galaxy types, and galaxy clusters.

The Classification of Protein Domains.

PubMed

Dawson, Natalie; Sillitoe, Ian; Marsden, Russell L; Orengo, Christine A

2017-01-01

The significant expansion in protein sequence and structure data that we are now witnessing brings with it a pressing need to bring order to the protein world. Such order enables us to gain insights into the evolution of proteins, their function and the extent to which the functional repertoire can vary across the three kingdoms of life. This has lead to the creation of a wide range of protein family classifications that aim to group proteins based upon their evolutionary relationships.In this chapter we discuss the approaches and methods that are frequently used in the classification of proteins, with a specific emphasis on the classification of protein domains. The construction of both domain sequence and domain structure databases is considered and we show how the use of domain family annotations to assign structural and functional information is enhancing our understanding of genomes.

Classification and Compression of Multi-Resolution Vectors: A Tree Structured Vector Quantizer Approach

DTIC Science & Technology

2002-01-01

their expression profile and for classification of cells into tumerous and non- tumerous classes. Then we will present a parallel tree method for... cancerous cells. We will use the same dataset and use tree structured classifiers with multi-resolution analysis for classifying cancerous from non- cancerous ...cells. We have the expressions of 4096 genes from 98 different cell types. Of these 98, 72 are cancerous while 26 are non- cancerous . We are interested

Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity

PubMed Central

Jeni, László A.; Lőrincz, András; Szabó, Zoltán; Cohn, Jeffrey F.; Kanade, Takeo

2016-01-01

In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time. As a consequence, high-dimensional representations such as SIFT and Gabor features have been favored despite their much greater computational cost and potential loss of information. We propose a Kernel Structured Sparsity (KSS) method that can handle both the temporal alignment problem and the structured sparse reconstruction within a common framework, and it can rely on simple features. We characterize spatio-temporal events as time-series of motion patterns and by utilizing time-series kernels we apply standard structured-sparse coding techniques to tackle this important problem. We evaluated the KSS method using both gesture and facial expression datasets that include spontaneous behavior and differ in degree of difficulty and type of ground truth coding. KSS outperformed both sparse and non-sparse methods that utilize complex image features and their temporal extensions. In the case of early facial event classification KSS had 10% higher accuracy as measured by F1 score over kernel SVM methods1. PMID:27830214

Bioinformatics analyses of Shigella CRISPR structure and spacer classification.

PubMed

Wang, Pengfei; Zhang, Bing; Duan, Guangcai; Wang, Yingfang; Hong, Lijuan; Wang, Linlin; Guo, Xiangjiao; Xi, Yuanlin; Yang, Haiyan

2016-03-01

Clustered regularly interspaced short palindromic repeats (CRISPR) are inheritable genetic elements of a variety of archaea and bacteria and indicative of the bacterial ecological adaptation, conferring acquired immunity against invading foreign nucleic acids. Shigella is an important pathogen for anthroponosis. This study aimed to analyze the features of Shigella CRISPR structure and classify the spacers through bioinformatics approach. Among 107 Shigella, 434 CRISPR structure loci were identified with two to seven loci in different strains. CRISPR-Q1, CRISPR-Q4 and CRISPR-Q5 were widely distributed in Shigella strains. Comparison of the first and last repeats of CRISPR1, CRISPR2 and CRISPR3 revealed several base variants and different stem-loop structures. A total of 259 cas genes were found among these 107 Shigella strains. The cas gene deletions were discovered in 88 strains. However, there is one strain that does not contain cas gene. Intact clusters of cas genes were found in 19 strains. From comprehensive analysis of sequence signature and BLAST and CRISPRTarget score, the 708 spacers were classified into three subtypes: Type I, Type II and Type III. Of them, Type I spacer referred to those linked with one gene segment, Type II spacer linked with two or more different gene segments, and Type III spacer undefined. This study examined the diversity of CRISPR/cas system in Shigella strains, demonstrated the main features of CRISPR structure and spacer classification, which provided critical information for elucidation of the mechanisms of spacer formation and exploration of the role the spacers play in the function of the CRISPR/cas system.

Structure constrained semi-nonnegative matrix factorization for EEG-based motor imagery classification.

PubMed

Lu, Na; Li, Tengfei; Pan, Jinjin; Ren, Xiaodong; Feng, Zuren; Miao, Hongyu

2015-05-01

Electroencephalogram (EEG) provides a non-invasive approach to measure the electrical activities of brain neurons and has long been employed for the development of brain-computer interface (BCI). For this purpose, various patterns/features of EEG data need to be extracted and associated with specific events like cue-paced motor imagery. However, this is a challenging task since EEG data are usually non-stationary time series with a low signal-to-noise ratio. In this study, we propose a novel method, called structure constrained semi-nonnegative matrix factorization (SCS-NMF), to extract the key patterns of EEG data in time domain by imposing the mean envelopes of event-related potentials (ERPs) as constraints on the semi-NMF procedure. The proposed method is applicable to general EEG time series, and the extracted temporal features by SCS-NMF can also be combined with other features in frequency domain to improve the performance of motor imagery classification. Real data experiments have been performed using the SCS-NMF approach for motor imagery classification, and the results clearly suggest the superiority of the proposed method. Comparison experiments have also been conducted. The compared methods include ICA, PCA, Semi-NMF, Wavelets, EMD and CSP, which further verified the effectivity of SCS-NMF. The SCS-NMF method could obtain better or competitive performance over the state of the art methods, which provides a novel solution for brain pattern analysis from the perspective of structure constraint. Copyright © 2015 Elsevier Ltd. All rights reserved.

A data-stream classification system for investigating terrorist threats

NASA Astrophysics Data System (ADS)

Schulz, Alexia; Dettman, Joshua; Gottschalk, Jeffrey; Kotson, Michael; Vuksani, Era; Yu, Tamara

2016-05-01

The role of cyber forensics in criminal investigations has greatly increased in recent years due to the wealth of data that is collected and available to investigators. Physical forensics has also experienced a data volume and fidelity revolution due to advances in methods for DNA and trace evidence analysis. Key to extracting insight is the ability to correlate across multi-modal data, which depends critically on identifying a touch-point connecting the separate data streams. Separate data sources may be connected because they refer to the same individual, entity or event. In this paper we present a data source classification system tailored to facilitate the investigation of potential terrorist activity. This taxonomy is structured to illuminate the defining characteristics of a particular terrorist effort and designed to guide reporting to decision makers that is complete, concise, and evidence-based. The classification system has been validated and empirically utilized in the forensic analysis of a simulated terrorist activity. Next-generation analysts can use this schema to label and correlate across existing data streams, assess which critical information may be missing from the data, and identify options for collecting additional data streams to fill information gaps.

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study

PubMed Central

Qureshi, Muhammad Naveed Iqbal; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

2016-01-01

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex. PMID:27500640

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study.

PubMed

Qureshi, Muhammad Naveed Iqbal; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

2016-01-01

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex.

Proposed structure of putative glucose channel in GLUT1 facilitative glucose transporter.

PubMed Central

Zeng, H; Parthasarathy, R; Rampal, A L; Jung, C Y

1996-01-01

A family of structurally related intrinsic membrane proteins (facilitative glucose transporters) catalyzes the movement of glucose across the plasma membrane of animal cells. Evidence indicates that these proteins show a common structural motif where approximately 50% of the mass is embedded in lipid bilayer (transmembrane domain) in 12 alpha-helices (transmembrane helices; TMHs) and accommodates a water-filled channel for substrate passage (glucose channel) whose tertiary structure is currently unknown. Using recent advances in protein structure prediction algorithms we proposed here two three-dimensional structural models for the transmembrane glucose channel of GLUT1 glucose transporter. Our models emphasize the physical dimension and water accessibility of the channel, loop lengths between TMHs, the macrodipole orientation in four-helix bundle motif, and helix packing energy. Our models predict that five TMHs, either TMHs 3, 4, 7, 8, 11 (Model 1) or TMHs 2, 5, 11, 8, 7 (Model 2), line the channel, and the remaining TMHs surround these channel-lining TMHs. We discuss how our models are compatible with the experimental data obtained with this protein, and how they can be used in designing new biochemical and molecular biological experiments in elucidation of the structural basis of this important protein function. Images FIGURE 1 FIGURE 2 FIGURE 4 FIGURE 5 PMID:8770183

Competition and facilitation structure plant communities under nurse tree canopies in extremely stressful environments.

PubMed

Al-Namazi, Ali A; El-Bana, Magdy I; Bonser, Stephen P

2017-04-01

Nurse plant facilitation in stressful environments can produce an environment with relatively low stress under its canopy. These nurse plants may produce the conditions promoting intense competition between coexisting species under the canopy, and canopies may establish stress gradients, where stress increases toward the edge of the canopy. Competition and facilitation on these stress gradients may control species distributions in the communities under canopies. We tested the following predictions: (1) interactions between understory species shift from competition to facilitation in habitats experiencing increasing stress from the center to the edge of canopy of a nurse plant, and (2) species distributions in understory communities are controlled by competitive interactions at the center of canopy, and facilitation at the edge of the canopy. We tested these predictions using a neighbor removal experiment under nurse trees growing in arid environments. Established individuals of each of four of the most common herbaceous species in the understory were used in the experiment. Two species were more frequent in the center of the canopy, and two species were more frequent at the edge of the canopy. Established individuals of each species were subjected to neighbor removal or control treatments in both canopy center and edge habitats. We found a shift from competitive to facilitative interactions from the center to the edge of the canopy. The shift in the effect of neighbors on the target species can help to explain species distributions in these canopies. Canopy-dominant species only perform well in the presence of neighbors in the edge microhabitat. Competition from canopy-dominant species can also limit the performance of edge-dominant species in the canopy microhabitat. The shift from competition to facilitation under nurse plant canopies can structure the understory communities in extremely stressful environments.

a Point Cloud Classification Approach Based on Vertical Structures of Ground Objects

NASA Astrophysics Data System (ADS)

Zhao, Y.; Hu, Q.; Hu, W.

2018-04-01

This paper proposes a novel method for point cloud classification using vertical structural characteristics of ground objects. Since urbanization develops rapidly nowadays, urban ground objects also change frequently. Conventional photogrammetric methods cannot satisfy the requirements of updating the ground objects' information efficiently, so LiDAR (Light Detection and Ranging) technology is employed to accomplish this task. LiDAR data, namely point cloud data, can obtain detailed three-dimensional coordinates of ground objects, but this kind of data is discrete and unorganized. To accomplish ground objects classification with point cloud, we first construct horizontal grids and vertical layers to organize point cloud data, and then calculate vertical characteristics, including density and measures of dispersion, and form characteristic curves for each grids. With the help of PCA processing and K-means algorithm, we analyze the similarities and differences of characteristic curves. Curves that have similar features will be classified into the same class and point cloud correspond to these curves will be classified as well. The whole process is simple but effective, and this approach does not need assistance of other data sources. In this study, point cloud data are classified into three classes, which are vegetation, buildings, and roads. When horizontal grid spacing and vertical layer spacing are 3 m and 1 m respectively, vertical characteristic is set as density, and the number of dimensions after PCA processing is 11, the overall precision of classification result is about 86.31 %. The result can help us quickly understand the distribution of various ground objects.

Argument structure hierarchy system and method for facilitating analysis and decision-making processes

DOEpatents

Janssen, Terry

2000-01-01

A system and method for facilitating decision-making comprising a computer program causing linkage of data representing a plurality of argument structure units into a hierarchical argument structure. Each argument structure unit comprises data corresponding to a hypothesis and its corresponding counter-hypothesis, data corresponding to grounds that provide a basis for inference of the hypothesis or its corresponding counter-hypothesis, data corresponding to a warrant linking the grounds to the hypothesis or its corresponding counter-hypothesis, and data corresponding to backing that certifies the warrant. The hierarchical argument structure comprises a top level argument structure unit and a plurality of subordinate level argument structure units. Each of the plurality of subordinate argument structure units comprises at least a portion of the grounds of the argument structure unit to which it is subordinate. Program code located on each of a plurality of remote computers accepts input from one of a plurality of contributors. Each input comprises data corresponding to an argument structure unit in the hierarchical argument structure and supports the hypothesis or its corresponding counter-hypothesis. A second programming code is adapted to combine the inputs into a single hierarchical argument structure. A third computer program code is responsive to the second computer program code and is adapted to represent a degree of support for the hypothesis and its corresponding counter-hypothesis in the single hierarchical argument structure.

Facilitators and Barriers to Performing Activities and Participation in Children With Cerebral Palsy: Caregivers' Perspective.

PubMed

Earde, Pinailug Tantilipikorn; Praipruk, Aina; Rodpradit, Phanlerd; Seanjumla, Parichad

2018-01-01

To investigate contextual factors that were facilitators and barriers to performing activity and participation for children with cerebral palsy from the caregivers' perspective. Qualitative in-depth interview with primary caregivers of children with cerebral palsy aged 4 to 12 years was conducted in the metropolitan area of Thailand. Semistructured questions related to environmental and personal factors were recorded. Interviews were transcribed verbatim and analyzed for main themes on the basis of the International Classification of Functioning, Disability, and Health-Children and Youth Version (ICF-CY) classification. Twenty-seven caregivers participated. Facilitators were appropriateness of assistive devices, support and acceptance from family, friends, and society, health services, willingness, and self-acceptance. Barriers were inappropriate design and facilities, overprotection of family, nonacceptance from family, friends, and society, inconvenient transportation, financial problems, limited health services, limited access to education, frustration, and being an introvert. Contextual factors that can be facilitators and barriers to perform activities and participation should be considered for improving lives of children with cerebral palsy.

The Advantages and Limitations of International Classification of Diseases, Injuries and Causes of Death from Aspect of Existing Health Care System of Bosnia and Herzegovina

PubMed Central

Kurbasic, Izeta; Pandza, Haris; Masic, Izet; Huseinagic, Senad; Tandir, Salih; Alicajic, Fredi; Toromanovic, Selim

2008-01-01

CONFLICT OF INTEREST: NONE DECLARED Introduction The International classification of diseases (ICD) is the most important classification in medicine. It is used by all medical professionals. Concept The basic concept of ICD is founded on the standardization of the nomenclature for the names of diseases and their basic systematization in the hierarchically structured category. Advantages and disadvantages The health care provider institutions such as hospitals are subjects that should facilitate implementation of medical applications that follows the patient medical condition and facts connected with him. The definitive diagnosis that can be coded using ICD can be achieved after several visits of patient and rarely during the first visit. Conclusion The ICD classification is one of the oldest and most important classifications in medicine. In the scope of ICD are all fields of medicine. It is used in statistical purpose and as a coding system in medical databases. PMID:24109155

Eukaryotic major facilitator superfamily transporter modeling based on the prokaryotic GlpT crystal structure.

PubMed

Lemieux, M Joanne

2007-01-01

The major facilitator superfamily (MFS) of transporters represents the largest family of secondary active transporters and has a diverse range of substrates. With structural information for four MFS transporters, we can see a strong structural commonality suggesting, as predicted, a common architecture for MFS transporters. The rate for crystal structure determination of MFS transporters is slow, making modeling of both prokaryotic and eukaryotic transporters more enticing. In this review, models of eukaryotic transporters Glut1, G6PT, OCT1, OCT2 and Pho84, based on the crystal structures of the prokaryotic GlpT, based on the crystal structure of LacY are discussed. The techniques used to generate the different models are compared. In addition, the validity of these models and the strategy of using prokaryotic crystal structures to model eukaryotic proteins are discussed. For comparison, E. coli GlpT was modeled based on the E. coli LacY structure and compared to the crystal structure of GlpT demonstrating that experimental evidence is essential for accurate modeling of membrane proteins.

Automated compound classification using a chemical ontology.

PubMed

Bobach, Claudia; Böhme, Timo; Laube, Ulf; Püschel, Anett; Weber, Lutz

2012-12-29

Classification of chemical compounds into compound classes by using structure derived descriptors is a well-established method to aid the evaluation and abstraction of compound properties in chemical compound databases. MeSH and recently ChEBI are examples of chemical ontologies that provide a hierarchical classification of compounds into general compound classes of biological interest based on their structural as well as property or use features. In these ontologies, compounds have been assigned manually to their respective classes. However, with the ever increasing possibilities to extract new compounds from text documents using name-to-structure tools and considering the large number of compounds deposited in databases, automated and comprehensive chemical classification methods are needed to avoid the error prone and time consuming manual classification of compounds. In the present work we implement principles and methods to construct a chemical ontology of classes that shall support the automated, high-quality compound classification in chemical databases or text documents. While SMARTS expressions have already been used to define chemical structure class concepts, in the present work we have extended the expressive power of such class definitions by expanding their structure-based reasoning logic. Thus, to achieve the required precision and granularity of chemical class definitions, sets of SMARTS class definitions are connected by OR and NOT logical operators. In addition, AND logic has been implemented to allow the concomitant use of flexible atom lists and stereochemistry definitions. The resulting chemical ontology is a multi-hierarchical taxonomy of concept nodes connected by directed, transitive relationships. A proposal for a rule based definition of chemical classes has been made that allows to define chemical compound classes more precisely than before. The proposed structure-based reasoning logic allows to translate chemistry expert knowledge into a

Automated compound classification using a chemical ontology

PubMed Central

2012-01-01

Background Classification of chemical compounds into compound classes by using structure derived descriptors is a well-established method to aid the evaluation and abstraction of compound properties in chemical compound databases. MeSH and recently ChEBI are examples of chemical ontologies that provide a hierarchical classification of compounds into general compound classes of biological interest based on their structural as well as property or use features. In these ontologies, compounds have been assigned manually to their respective classes. However, with the ever increasing possibilities to extract new compounds from text documents using name-to-structure tools and considering the large number of compounds deposited in databases, automated and comprehensive chemical classification methods are needed to avoid the error prone and time consuming manual classification of compounds. Results In the present work we implement principles and methods to construct a chemical ontology of classes that shall support the automated, high-quality compound classification in chemical databases or text documents. While SMARTS expressions have already been used to define chemical structure class concepts, in the present work we have extended the expressive power of such class definitions by expanding their structure-based reasoning logic. Thus, to achieve the required precision and granularity of chemical class definitions, sets of SMARTS class definitions are connected by OR and NOT logical operators. In addition, AND logic has been implemented to allow the concomitant use of flexible atom lists and stereochemistry definitions. The resulting chemical ontology is a multi-hierarchical taxonomy of concept nodes connected by directed, transitive relationships. Conclusions A proposal for a rule based definition of chemical classes has been made that allows to define chemical compound classes more precisely than before. The proposed structure-based reasoning logic allows to translate

Single-particle cryo-EM using alignment by classification (ABC): the structure of Lumbricus terrestris haemoglobin

PubMed Central

Seer-Linnemayr, Charlotte; Ravelli, Raimond B. G.; Matadeen, Rishi; De Carlo, Sacha; Alewijnse, Bart; Portugal, Rodrigo V.; Pannu, Navraj S.; Schatz, Michael; van Heel, Marin

2017-01-01

Single-particle cryogenic electron microscopy (cryo-EM) can now yield near-atomic resolution structures of biological complexes. However, the reference-based alignment algorithms commonly used in cryo-EM suffer from reference bias, limiting their applicability (also known as the ‘Einstein from random noise’ problem). Low-dose cryo-EM therefore requires robust and objective approaches to reveal the structural information contained in the extremely noisy data, especially when dealing with small structures. A reference-free pipeline is presented for obtaining near-atomic resolution three-dimensional reconstructions from heterogeneous (‘four-dimensional’) cryo-EM data sets. The methodologies integrated in this pipeline include a posteriori camera correction, movie-based full-data-set contrast transfer function determination, movie-alignment algorithms, (Fourier-space) multivariate statistical data compression and unsupervised classification, ‘random-startup’ three-dimensional reconstructions, four-dimensional structural refinements and Fourier shell correlation criteria for evaluating anisotropic resolution. The procedures exclusively use information emerging from the data set itself, without external ‘starting models’. Euler-angle assignments are performed by angular reconstitution rather than by the inherently slower projection-matching approaches. The comprehensive ‘ABC-4D’ pipeline is based on the two-dimensional reference-free ‘alignment by classification’ (ABC) approach, where similar images in similar orientations are grouped by unsupervised classification. Some fundamental differences between X-ray crystallography versus single-particle cryo-EM data collection and data processing are discussed. The structure of the giant haemoglobin from Lumbricus terrestris at a global resolution of ∼3.8 Å is presented as an example of the use of the ABC-4D procedure. PMID:28989723

Towards a Collaborative Intelligent Tutoring System Classification Scheme

ERIC Educational Resources Information Center

Harsley, Rachel

2014-01-01

This paper presents a novel classification scheme for Collaborative Intelligent Tutoring Systems (CITS), an emergent research field. The three emergent classifications of CITS are unstructured, semi-structured, and fully structured. While all three types of CITS offer opportunities to improve student learning gains, the full extent to which these…

The characteristics of effective secondary math and science instructional facilitators and the necessary support structures as perceived by practitioners and principals

NASA Astrophysics Data System (ADS)

Mahagan, Vikki Lynn

Instructional facilitators are known by a variety of titles depending on the school district in which they are employed. They are sometimes called instructional coaches, teacher leaders, lead teachers, and instructional specialist (Denton & Hasbrouck, 2009). Throughout this study, the title instructional facilitator was used and will refer to secondary math or science instructional facilitators who are housed at least one day per week on a campus. This study is a mixed-methods descriptive study which has identified character traits, specials skill, and talents possessed by effective secondary math and science instructional facilitators as perceived by practicing facilitators and principals and assistant principals who work along side instructional facilitators. Specific job training to help ensure the success of a facilitator was identified as viewed by both facilitators and principals. Additionally, this study compared the perceptions of practicing facilitators and principals to determine if significant differences exist with respect to perceptions of staff development opportunities, support structures, and resources available for instructional facilitators.

Comparing drug classification systems.

PubMed

Mahoney, Anne; Evans, Jonathan

2008-11-06

An essential quality of drug classification systems is the ability to assign medications to a structured hierarchy for categories such as mechanism of action, physiological effects, and therapeutic indications. No single classification system can meet all of these needs; however, there should be consistency among those that group by the same underlying principals. We discovered discrepancies in how drugs with multiple therapeutic indications are classified among four widely used schemas.

Functional Basis of Microorganism Classification.

PubMed

Zhu, Chengsheng; Delmont, Tom O; Vogel, Timothy M; Bromberg, Yana

2015-08-01

Correctly identifying nearest "neighbors" of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned with

Reduction of herbivorous fish pressure can facilitate focal algal species forestation on artificial structures.

PubMed

Gianni, Fabrizio; Bartolini, Fabrizio; Airoldi, Laura; Mangialajo, Luisa

2018-07-01

Coastal areas have been transformed worldwide by urbanization, so that artificial structures are now widespread. Current coastal development locally depletes many native marine species, while offering limited possibilities for their expansion. Eco-engineering interventions intend to identify ways to facilitate the presence of focal species and their associated functions on artificial habitats. An important but overlooked factor controlling restoration operations is overgrazing by herbivores. The aim of this study was to quantify the effects of different potential feeders on Cystoseira amentacea, a native canopy-forming alga of the Mediterranean infralittoral fringe, and test whether manipulation of grazing pressure can facilitate the human-guided installation of this focal species on coastal structures. Results of laboratory tests and field experiments revealed that Sarpa salpa, the only strictly native herbivorous fish in the Western Mediterranean Sea, can be a very effective grazer of C. amentacea in artificial habitats, up to as far as the infralittoral fringe, which is generally considered less accessible to fishes. S. salpa can limit the success of forestation operations in artificial novel habitats, causing up to 90% of Cystoseira loss after a few days. Other grazers, such as limpets and crabs, had only a moderate impact. Future engineering operations,intended to perform forestation of canopy-forming algae on artificial structures, should consider relevant biotic factors, such as fish overgrazing, identifying cost-effective techniques to limit their impact, as is the usual practice in restoration programmes on land. Copyright © 2018 Elsevier Ltd. All rights reserved.

Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE Commission on Classification and Terminology, 2005-2009.

PubMed

Berg, Anne T; Berkovic, Samuel F; Brodie, Martin J; Buchhalter, Jeffrey; Cross, J Helen; van Emde Boas, Walter; Engel, Jerome; French, Jacqueline; Glauser, Tracy A; Mathern, Gary W; Moshé, Solomon L; Nordli, Douglas; Plouin, Perrine; Scheffer, Ingrid E

2010-04-01

The International League Against Epilepsy (ILAE) Commission on Classification and Terminology has revised concepts, terminology, and approaches for classifying seizures and forms of epilepsy. Generalized and focal are redefined for seizures as occurring in and rapidly engaging bilaterally distributed networks (generalized) and within networks limited to one hemisphere and either discretely localized or more widely distributed (focal). Classification of generalized seizures is simplified. No natural classification for focal seizures exists; focal seizures should be described according to their manifestations (e.g., dyscognitive, focal motor). The concepts of generalized and focal do not apply to electroclinical syndromes. Genetic, structural-metabolic, and unknown represent modified concepts to replace idiopathic, symptomatic, and cryptogenic. Not all epilepsies are recognized as electroclinical syndromes. Organization of forms of epilepsy is first by specificity: electroclinical syndromes, nonsyndromic epilepsies with structural-metabolic causes, and epilepsies of unknown cause. Further organization within these divisions can be accomplished in a flexible manner depending on purpose. Natural classes (e.g., specific underlying cause, age at onset, associated seizure type), or pragmatic groupings (e.g., epileptic encephalopathies, self-limited electroclinical syndromes) may serve as the basis for organizing knowledge about recognized forms of epilepsy and facilitate identification of new forms.

Structural and functional perspectives on classification and seriation in psychotic and normal children.

PubMed

Breslow, L; Cowan, P A

1984-02-01

This study describes a strategy for examining cognitive functioning in psychotic and normal children without the usual confounding effects of marked differences in cognitive structure that occur when children of the same age are compared. Participants were 14 psychotic children, 12 males and 2 females, mean age 9-2, matched with normal children at preoperational and concrete operational stage levels on a set of Piagetian classification tasks. The mean age of the normal children was 6-4, replicating the usually found developmental delay in psychotic samples. Participants were then compared on both structural level and functional abilities on a set of tasks involving seriation of sticks; the higher-level children were also administered a seriation drawing task. Analysis of children's processes of seriating and seriation drawings indicated that over and above the structural retardation, psychotic children at all levels showed functional deficits, especially in the use of anticipatory imagery. The implications for general developmental theory are that progress in structural development is not sufficient for imaginal development, and that structural development of logical concepts is relatively independent of the development of imagery. It was suggested that "thought disorder" may not be a disordered structure of thinking or a retardation in psychotic populations but rather a mismatch between higher-level logical structures and lower-level functions.

Structural barriers and facilitators in HIV prevention: a review of international research.

PubMed

Parker, R G; Easton, D; Klein, C H

2000-06-01

This article provides an overview of a growing body of international research focusing on the structural and environmental factors that shape the spread of the HIV/AIDS epidemic, and create barriers and facilitators in relation to HIV-prevention programs. OVERVIEW OF STRUCTURAL-FACTORS LITERATURE: Most of the research on structural and environmental factors can be grouped into a small number of analytically distinct but interconnected categories: economic (under)development and poverty; mobility, including migration, seasonal work, and social disruption due to war and political instability; and gender inequalities. An additional focus in research on structural and environmental factors has been on the effects of particular governmental and intergovernmental policies in increasing or diminishing HIV vulnerability and transmission. A smaller subset of the research on structural factors describes and/or evaluates specific interventions in detail. Approaches that have received significant attention include targeted interventions developed for heterosexual women, female commercial sex workers, male truck drivers, and men who have sex with men. The structural and environmental factors literature offers important insights and reveals a number of productive intervention strategies that might be explored in both resource-rich and -poor settings. However, new methodologies are required to document and evaluate the effects of the structural interventions, which by their very nature involve large-scale elements that cannot be easily controlled by experimental or quasi-experimental research designs. Innovative, interdisciplinary approaches are needed that can move beyond the limited successes of traditional behavioral interventions and explicitly attempt to achieve broader social and structural change.

Support Vector Machine-based classification of protein folds using the structural properties of amino acid residues and amino acid residue pairs.

PubMed

Shamim, Mohammad Tabrez Anwar; Anwaruddin, Mohammad; Nagarajaram, H A

2007-12-15

Fold recognition is a key step in the protein structure discovery process, especially when traditional sequence comparison methods fail to yield convincing structural homologies. Although many methods have been developed for protein fold recognition, their accuracies remain low. This can be attributed to insufficient exploitation of fold discriminatory features. We have developed a new method for protein fold recognition using structural information of amino acid residues and amino acid residue pairs. Since protein fold recognition can be treated as a protein fold classification problem, we have developed a Support Vector Machine (SVM) based classifier approach that uses secondary structural state and solvent accessibility state frequencies of amino acids and amino acid pairs as feature vectors. Among the individual properties examined secondary structural state frequencies of amino acids gave an overall accuracy of 65.2% for fold discrimination, which is better than the accuracy by any method reported so far in the literature. Combination of secondary structural state frequencies with solvent accessibility state frequencies of amino acids and amino acid pairs further improved the fold discrimination accuracy to more than 70%, which is approximately 8% higher than the best available method. In this study we have also tested, for the first time, an all-together multi-class method known as Crammer and Singer method for protein fold classification. Our studies reveal that the three multi-class classification methods, namely one versus all, one versus one and Crammer and Singer method, yield similar predictions. Dataset and stand-alone program are available upon request.

Similarity-Dissimilarity Competition in Disjunctive Classification Tasks

PubMed Central

Mathy, Fabien; Haladjian, Harry H.; Laurent, Eric; Goldstone, Robert L.

2013-01-01

Typical disjunctive artificial classification tasks require participants to sort stimuli according to rules such as “x likes cars only when black and coupe OR white and SUV.” For categories like this, increasing the salience of the diagnostic dimensions has two simultaneous effects: increasing the distance between members of the same category and increasing the distance between members of opposite categories. Potentially, these two effects respectively hinder and facilitate classification learning, leading to competing predictions for learning. Increasing saliency may lead to members of the same category to be considered less similar, while the members of separate categories might be considered more dissimilar. This implies a similarity-dissimilarity competition between two basic classification processes. When focusing on sub-category similarity, one would expect more difficult classification when members of the same category become less similar (disregarding the increase of between-category dissimilarity); however, the between-category dissimilarity increase predicts a less difficult classification. Our categorization study suggests that participants rely more on using dissimilarities between opposite categories than finding similarities between sub-categories. We connect our results to rule- and exemplar-based classification models. The pattern of influences of within- and between-category similarities are challenging for simple single-process categorization systems based on rules or exemplars. Instead, our results suggest that either these processes should be integrated in a hybrid model, or that category learning operates by forming clusters within each category. PMID:23403979

Structured reporting platform improves CAD-RADS assessment.

PubMed

Szilveszter, Bálint; Kolossváry, Márton; Karády, Júlia; Jermendy, Ádám L; Károlyi, Mihály; Panajotu, Alexisz; Bagyura, Zsolt; Vecsey-Nagy, Milán; Cury, Ricardo C; Leipsic, Jonathon A; Merkely, Béla; Maurovich-Horvat, Pál

2017-11-01

Structured reporting in cardiac imaging is strongly encouraged to improve quality through consistency. The Coronary Artery Disease - Reporting and Data System (CAD-RADS) was recently introduced to facilitate interdisciplinary communication of coronary CT angiography (CTA) results. We aimed to assess the agreement between manual and automated CAD-RADS classification using a structured reporting platform. Five readers prospectively interpreted 500 coronary CT angiographies using a structured reporting platform that automatically calculates the CAD-RADS score based on stenosis and plaque parameters manually entered by the reader. In addition, all readers manually assessed CAD-RADS blinded to the automatically derived results, which was used as the reference standard. We evaluated factors influencing reader performance including CAD-RADS training, clinical load, time of the day and level of expertise. Total agreement between manual and automated classification was 80.2%. Agreement in stenosis categories was 86.7%, whereas the agreement in modifiers was 95.8% for "N", 96.8% for "S", 95.6% for "V" and 99.4% for "G". Agreement for V improved after CAD-RADS training (p = 0.047). Time of the day and clinical load did not influence reader performance (p > 0.05 both). Less experienced readers had a higher total agreement as compared to more experienced readers (87.0% vs 78.0%, respectively; p = 0.011). Even though automated CAD-RADS classification uses data filled in by the readers, it outperforms manual classification by preventing human errors. Structured reporting platforms with automated calculation of the CAD-RADS score might improve data quality and support standardization of clinical decision making. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Classification of cirrhotic liver in Gadolinium-enhanced MR images

NASA Astrophysics Data System (ADS)

Lee, Gobert; Uchiyama, Yoshikazu; Zhang, Xuejun; Kanematsu, Masayuki; Zhou, Xiangrong; Hara, Takeshi; Kato, Hiroki; Kondo, Hiroshi; Fujita, Hiroshi; Hoshi, Hiroaki

2007-03-01

Cirrhosis of the liver is characterized by the presence of widespread nodules and fibrosis in the liver. The fibrosis and nodules formation causes distortion of the normal liver architecture, resulting in characteristic texture patterns. Texture patterns are commonly analyzed with the use of co-occurrence matrix based features measured on regions-of-interest (ROIs). A classifier is subsequently used for the classification of cirrhotic or non-cirrhotic livers. Problem arises if the classifier employed falls into the category of supervised classifier which is a popular choice. This is because the 'true disease states' of the ROIs are required for the training of the classifier but is, generally, not available. A common approach is to adopt the 'true disease state' of the liver as the 'true disease state' of all ROIs in that liver. This paper investigates the use of a nonsupervised classifier, the k-means clustering method in classifying livers as cirrhotic or non-cirrhotic using unlabelled ROI data. A preliminary result with a sensitivity and specificity of 72% and 60%, respectively, demonstrates the feasibility of using the k-means non-supervised clustering method in generating a characteristic cluster structure that could facilitate the classification of cirrhotic and non-cirrhotic livers.

Resolving anthropogenic aerosol pollution types - deconvolution and exploratory classification of pollution events

NASA Astrophysics Data System (ADS)

Äijälä, Mikko; Heikkinen, Liine; Fröhlich, Roman; Canonaco, Francesco; Prévôt, André S. H.; Junninen, Heikki; Petäjä, Tuukka; Kulmala, Markku; Worsnop, Douglas; Ehn, Mikael

2017-03-01

Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesizing this raw data into chemical information necessitates the use of advanced, statistics-based data analytical techniques. In the field of analytical aerosol chemistry, statistical, dimensionality reductive methods have become widespread in the last decade, yet comparable advanced chemometric techniques for data classification and identification remain marginal. Here we present an example of combining data dimensionality reduction (factorization) with exploratory classification (clustering), and show that the results cannot only reproduce and corroborate earlier findings, but also complement and broaden our current perspectives on aerosol chemical classification. We find that applying positive matrix factorization to extract spectral characteristics of the organic component of air pollution plumes, together with an unsupervised clustering algorithm, k-means+ + , for classification, reproduces classical organic aerosol speciation schemes. Applying appropriately chosen metrics for spectral dissimilarity along with optimized data weighting, the source-specific pollution characteristics can be statistically resolved even for spectrally very similar aerosol types, such as different combustion-related anthropogenic aerosol species and atmospheric aerosols with similar degree of oxidation. In addition to the typical oxidation level and source-driven aerosol classification, we were also able to classify and characterize outlier groups that would likely be disregarded in a more conventional analysis. Evaluating solution quality for the classification also provides means to assess the performance of mass spectral similarity metrics and optimize weighting for mass spectral variables. This facilitates algorithm-based evaluation of aerosol spectra, which may prove invaluable for future development of automatic methods for spectra identification

A classification of ecological boundaries

USGS Publications Warehouse

Strayer, D.L.; Power, M.E.; Fagan, W.F.; Pickett, S.T.A.; Belnap, J.

2003-01-01

Ecologists use the term boundary to refer to a wide range of real and conceptual structures. Because imprecise terminology may impede the search for general patterns and theories about ecological boundaries, we present a classification of the attributes of ecological boundaries to aid in communication and theory development. Ecological boundaries may differ in their origin and maintenance, their spatial structure, their function, and their temporal dynamics. A classification system based on these attributes should help ecologists determine whether boundaries are truly comparable. This system can be applied when comparing empirical studies, comparing theories, and testing theoretical predictions against empirical results.

Fast Gaussian kernel learning for classification tasks based on specially structured global optimization.

PubMed

Zhong, Shangping; Chen, Tianshun; He, Fengying; Niu, Yuzhen

2014-09-01

For a practical pattern classification task solved by kernel methods, the computing time is mainly spent on kernel learning (or training). However, the current kernel learning approaches are based on local optimization techniques, and hard to have good time performances, especially for large datasets. Thus the existing algorithms cannot be easily extended to large-scale tasks. In this paper, we present a fast Gaussian kernel learning method by solving a specially structured global optimization (SSGO) problem. We optimize the Gaussian kernel function by using the formulated kernel target alignment criterion, which is a difference of increasing (d.i.) functions. Through using a power-transformation based convexification method, the objective criterion can be represented as a difference of convex (d.c.) functions with a fixed power-transformation parameter. And the objective programming problem can then be converted to a SSGO problem: globally minimizing a concave function over a convex set. The SSGO problem is classical and has good solvability. Thus, to find the global optimal solution efficiently, we can adopt the improved Hoffman's outer approximation method, which need not repeat the searching procedure with different starting points to locate the best local minimum. Also, the proposed method can be proven to converge to the global solution for any classification task. We evaluate the proposed method on twenty benchmark datasets, and compare it with four other Gaussian kernel learning methods. Experimental results show that the proposed method stably achieves both good time-efficiency performance and good classification performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

DATA-MEAns: an open source tool for the classification and management of neural ensemble recordings.

PubMed

Bonomini, María P; Ferrandez, José M; Bolea, Jose Angel; Fernandez, Eduardo

2005-10-30

The number of laboratories using techniques that allow to acquire simultaneous recordings of as many units as possible is considerably increasing. However, the development of tools used to analyse this multi-neuronal activity is generally lagging behind the development of the tools used to acquire these data. Moreover, the data exchange between research groups using different multielectrode acquisition systems is hindered by commercial constraints such as exclusive file structures, high priced licenses and hard policies on intellectual rights. This paper presents a free open-source software for the classification and management of neural ensemble data. The main goal is to provide a graphical user interface that links the experimental data to a basic set of routines for analysis, visualization and classification in a consistent framework. To facilitate the adaptation and extension as well as the addition of new routines, tools and algorithms for data analysis, the source code and documentation are freely available.

Multisensor multiresolution data fusion for improvement in classification

NASA Astrophysics Data System (ADS)

Rubeena, V.; Tiwari, K. C.

2016-04-01

The rapid advancements in technology have facilitated easy availability of multisensor and multiresolution remote sensing data. Multisensor, multiresolution data contain complementary information and fusion of such data may result in application dependent significant information which may otherwise remain trapped within. The present work aims at improving classification by fusing features of coarse resolution hyperspectral (1 m) LWIR and fine resolution (20 cm) RGB data. The classification map comprises of eight classes. The class names are Road, Trees, Red Roof, Grey Roof, Concrete Roof, Vegetation, bare Soil and Unclassified. The processing methodology for hyperspectral LWIR data comprises of dimensionality reduction, resampling of data by interpolation technique for registering the two images at same spatial resolution, extraction of the spatial features to improve classification accuracy. In the case of fine resolution RGB data, the vegetation index is computed for classifying the vegetation class and the morphological building index is calculated for buildings. In order to extract the textural features, occurrence and co-occurence statistics is considered and the features will be extracted from all the three bands of RGB data. After extracting the features, Support Vector Machine (SVMs) has been used for training and classification. To increase the classification accuracy, post processing steps like removal of any spurious noise such as salt and pepper noise is done which is followed by filtering process by majority voting within the objects for better object classification.

Gene function prediction based on the Gene Ontology hierarchical structure.

PubMed

Cheng, Liangxi; Lin, Hongfei; Hu, Yuncui; Wang, Jian; Yang, Zhihao

2014-01-01

The information of the Gene Ontology annotation is helpful in the explanation of life science phenomena, and can provide great support for the research of the biomedical field. The use of the Gene Ontology is gradually affecting the way people store and understand bioinformatic data. To facilitate the prediction of gene functions with the aid of text mining methods and existing resources, we transform it into a multi-label top-down classification problem and develop a method that uses the hierarchical relationships in the Gene Ontology structure to relieve the quantitative imbalance of positive and negative training samples. Meanwhile the method enhances the discriminating ability of classifiers by retaining and highlighting the key training samples. Additionally, the top-down classifier based on a tree structure takes the relationship of target classes into consideration and thus solves the incompatibility between the classification results and the Gene Ontology structure. Our experiment on the Gene Ontology annotation corpus achieves an F-value performance of 50.7% (precision: 52.7% recall: 48.9%). The experimental results demonstrate that when the size of training set is small, it can be expanded via topological propagation of associated documents between the parent and child nodes in the tree structure. The top-down classification model applies to the set of texts in an ontology structure or with a hierarchical relationship.

Alternative temporal classification of long Gamma Ray Bursts

NASA Astrophysics Data System (ADS)

Alejandro Vasquez, Nicolas; Baquero, Andres; Andrade, David

2015-08-01

In order to increase the understanding on Gamma Ray Bursts, many attempts of classification have been proposed. Starting with the canonical classification into long and short GRBs, alternative classifications taking into account the cosmological origin of GRBs have been analyzed. In the present work we propose an alternative classification based on two temporal estimators, the Auto Correlation Function (ACF) of the light curves and the emission time which considered the time where the bursts engine is active. The time estimators chosen reflects the internal evolution of the GRB and the internal structure. Using a sample of 61 bright GRBs detected by SWIFT satellite with known redshift, we proposed a bimodal distribution of long bursts. The two types of bursts have different internal structure suggesting different progenitors.

Protein classification using sequential pattern mining.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2006-01-01

Protein classification in terms of fold recognition can be employed to determine the structural and functional properties of a newly discovered protein. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. One of the most efficient SPM algorithms, cSPADE, is employed for protein primary structure analysis. Then a classifier uses the extracted sequential patterns for classifying proteins of unknown structure in the appropriate fold category. The proposed methodology exhibited an overall accuracy of 36% in a multi-class problem of 17 candidate categories. The classification performance reaches up to 65% when the three most probable protein folds are considered.

Functional Basis of Microorganism Classification

PubMed Central

Zhu, Chengsheng; Delmont, Tom O.; Vogel, Timothy M.; Bromberg, Yana

2015-01-01

Correctly identifying nearest “neighbors” of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned

Feature selection and classification of multiparametric medical images using bagging and SVM

NASA Astrophysics Data System (ADS)

Fan, Yong; Resnick, Susan M.; Davatzikos, Christos

2008-03-01

This paper presents a framework for brain classification based on multi-parametric medical images. This method takes advantage of multi-parametric imaging to provide a set of discriminative features for classifier construction by using a regional feature extraction method which takes into account joint correlations among different image parameters; in the experiments herein, MRI and PET images of the brain are used. Support vector machine classifiers are then trained based on the most discriminative features selected from the feature set. To facilitate robust classification and optimal selection of parameters involved in classification, in view of the well-known "curse of dimensionality", base classifiers are constructed in a bagging (bootstrap aggregating) framework for building an ensemble classifier and the classification parameters of these base classifiers are optimized by means of maximizing the area under the ROC (receiver operating characteristic) curve estimated from their prediction performance on left-out samples of bootstrap sampling. This classification system is tested on a sex classification problem, where it yields over 90% classification rates for unseen subjects. The proposed classification method is also compared with other commonly used classification algorithms, with favorable results. These results illustrate that the methods built upon information jointly extracted from multi-parametric images have the potential to perform individual classification with high sensitivity and specificity.

Structured Play Therapy Groups for Preschoolers: facilitating the emergence of social competence.

PubMed

Stone, Susan; Stark, Martha

2013-01-01

Over the years, we have developed a working model of Structured Play Therapy Groups for Preschoolers, an innovative treatment approach designed to address the needs of young children ages 3 to 5 struggling to adjust to the social demands of their preschool classrooms. These short-term therapy groups facilitate development of the young child's social competence and capacity to participate effectively in a classroom environment. Although the literature on therapy groups for children suggests that preschoolers are not yet evolved enough developmentally to engage actively in a group process, our experience indicates otherwise. The model of treatment presented here will therefore challenge that contention with the claim that not only can preschoolers participate in a structured therapy group of peers but they can, by virtue of that very participation, benefit in ways that will prepare them (as they transition from preschool to kindergarten) for the ever-increasing demands of their ever-expanding social milieus.

The United Nations Framework Classification for World Petroleum Resources

USGS Publications Warehouse

Ahlbrandt, T.S.; Blystad, P.; Young, E.D.; Slavov, S.; Heiberg, S.

2003-01-01

The United Nations has developed an international framework classification for solid fuels and minerals (UNFC). This is now being extended to petroleum by building on the joint classification of the Society of Petroleum Engineers (SPE), the World Petroleum Congresses (WPC) and the American Association of Petroleum Geologists (AAPG). The UNFC is a 3-dimansional classification. This: Is necessary in order to migrate accounts of resource quantities that are developed on one or two of the axes to the common basis; Provides for more precise reporting and analysis. This is particularly useful in analyses of contingent resources. The characteristics of the SPE/WPC/AAPG classification has been preserved and enhanced to facilitate improved international and national petroleum resource management, corporate business process management and financial reporting. A UN intergovernmental committee responsible for extending the UNFC to extractive energy resources (coal, petroleum and uranium) will meet in Geneva on October 30th and 31st to review experiences gained and comments received during 2003. A recommended classification will then be delivered for consideration to the United Nations through the Committee on Sustainable Energy of the Economic Commission for Europe (UN ECE).

Facial clefts and facial dysplasia: revisiting the classification.

PubMed

Mazzola, Riccardo F; Mazzola, Isabella C

2014-01-01

Most craniofacial malformations are identified by their appearance. The majority of the classification systems are mainly clinical or anatomical, not related to the different levels of development of the malformation, and underlying pathology is usually not taken into consideration. In 1976, Tessier first emphasized the relationship between soft tissues and the underlying bone stating that "a fissure of the soft tissue corresponds, as a general rule, with a cleft of the bony structure". He introduced a cleft numbering system around the orbit from 0 to 14 depending on its relationship to the zero line (ie, the vertical midline cleft of the face). The classification, easy to understand, became widely accepted because the recording of the malformations was simple and communication between observers facilitated. It represented a great breakthrough in identifying craniofacial malformations, named clefts by him. In the present paper, the embryological-based classification of craniofacial malformations, proposed in 1983 and in 1990 by us, has been revisited. Its aim was to clarify some unanswered questions regarding apparently atypical or bizarre anomalies and to establish as much as possible the moment when this event occurred. In our opinion, this classification system may well integrate the one proposed by Tessier and tries at the same time to find a correlation between clinical observation and morphogenesis.Terminology is important. The overused term cleft should be reserved to true clefts only, developed from disturbances in the union of the embryonic facial processes, between the lateronasal and maxillary process (or oro-naso-ocular cleft); between the medionasal and maxillary process (or cleft of the lip); between the maxillary processes (or cleft of the palate); and between the maxillary and mandibular process (or macrostomia).For the other types of defects, derived from alteration of bone production centers, the word dysplasia should be used instead. Facial

Nursing Classification Systems

PubMed Central

Henry, Suzanne Bakken; Mead, Charles N.

1997-01-01

Abstract Our premise is that from the perspective of maximum flexibility of data usage by computer-based record (CPR) systems, existing nursing classification systems are necessary, but not sufficient, for representing important aspects of “what nurses do.” In particular, we have focused our attention on those classification systems that represent nurses' clinical activities through the abstraction of activities into categories of nursing interventions. In this theoretical paper, we argue that taxonomic, combinatorial vocabularies capable of coding atomic-level nursing activities are required to effectively capture in a reproducible and reversible manner the clinical decisions and actions of nurses, and that, without such vocabularies and associated grammars, potentially important clinical process data is lost during the encoding process. Existing nursing intervention classification systems do not fulfill these criteria. As background to our argument, we first present an overview of the content, methods, and evaluation criteria used in previous studies whose focus has been to evaluate the effectiveness of existing coding and classification systems. Next, using the Ingenerf typology of taxonomic vocabularies, we categorize the formal type and structure of three existing nursing intervention classification systems—Nursing Interventions Classification, Omaha System, and Home Health Care Classification. Third, we use records from home care patients to show examples of lossy data transformation, the loss of potentially significant atomic data, resulting from encoding using each of the three systems. Last, we provide an example of the application of a formal representation methodology (conceptual graphs) which we believe could be used as a model to build the required combinatorial, taxonomic vocabulary for representing nursing interventions. PMID:9147341

Constructing a classification of hypersensitivity/allergic diseases for ICD-11 by crowdsourcing the allergist community.

PubMed

Tanno, L K; Calderon, M A; Goldberg, B J; Gayraud, J; Bircher, A J; Casale, T; Li, J; Sanchez-Borges, M; Rosenwasser, L J; Pawankar, R; Papadopoulos, N G; Demoly, P

2015-06-01

The global allergy community strongly believes that the 11th revision of the International Classification of Diseases (ICD-11) offers a unique opportunity to improve the classification and coding of hypersensitivity/allergic diseases via inclusion of a specific chapter dedicated to this disease area to facilitate epidemiological studies, as well as to evaluate the true size of the allergy epidemic. In this context, an international collaboration has decided to revise the classification of hypersensitivity/allergic diseases and to validate it for ICD-11 by crowdsourcing the allergist community. After careful comparison between ICD-10 and 11 beta phase linearization codes, we identified gaps and trade-offs allowing us to construct a classification proposal, which was sent to the European Academy of Allergy and Clinical Immunology (EAACI) sections, interest groups, executive committee as well as the World Allergy Organization (WAO), and American Academy of Allergy Asthma and Immunology (AAAAI) leaderships. The crowdsourcing process produced comments from 50 of 171 members contacted by e-mail. The classification proposal has also been discussed at face-to-face meetings with experts of EAACI sections and interest groups and presented in a number of business meetings during the 2014 EAACI annual congress in Copenhagen. As a result, a high-level complex structure of classification for hypersensitivity/allergic diseases has been constructed. The model proposed has been presented to the WHO groups in charge of the ICD revision. The international collaboration of allergy experts appreciates bilateral discussion and aims to get endorsement of their proposals for the final ICD-11. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

U.S. Fish and Wildlife Service 1979 wetland classification: a review

USGS Publications Warehouse

Cowardin, L.M.; Golet, F.C.

1995-01-01

In 1979 the US Fish and Wildlife Service published and adopted a classification of wetlands and deepwater habitats of the United States. The system was designed for use in a national inventory of wetlands. It was intended to be ecologically based, to furnish the mapping units needed for the inventory, and to provide national consistency in terminology and definition. We review the performance of the classification after 13 years of use. The definition of wetland is based on national lists of hydric soils and plants that occur in wetlands. Our experience suggests that wetland classifications must facilitate mapping and inventory because these data gathering functions are essential to management and preservation of the wetland resource, but the definitions and taxa must have ecological basis. The most serious problem faced in construction of the classification was lack of data for many of the diverse wetland types. Review of the performance of the classification suggests that, for the most part, it was successful in accomplishing its objectives, but that problem areas should be corrected and modification could strengthen its utility. The classification, at least in concept, could be applied outside the United States. Experience gained in use of the classification can furnish guidance as to pitfalls to be avoided in the wetland classification process.

Impact of Growth in the Universe of Subjects on Classification.

ERIC Educational Resources Information Center

Ranganathan, Shiyali Ramamritam

The development of the removal of rigidity in library classification is traced from the Enumerative Classification of DC (1876) through the Nearly-Faceted Classification of UDC (1896), the rigidly, though fully faceted version of CC (1933), the generalized faceted structure of version 2 of CC (1949), down to the Freely Faceted Classification of…

On the classification of weakly integral modular categories

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

Bruillard, Paul; Galindo, César; Ng, Siu-Hung

In this paper we classify all modular categories of dimension 4m, where m is an odd square-free integer, and all rank 6 and rank 7 weakly integral modular categories. This completes the classification of weakly integral modular categories through rank 7. In particular, our results imply that all integral modular categories of rank at most 7 are pointed (that is, every simple object has dimension 1). All the non-integral (but weakly integral) modular categories of ranks 6 and 7 have dimension 4m, with m an odd square free integer, so their classification is an application of our main result. Themore » classification of rank 7 integral modular categories is facilitated by an analysis of the two group actions on modular categories: the Galois group of the field generated by the entries of the S-matrix and the group of invertible isomorphism classes of objects. We derive some valuable arithmetic consequences from these actions.« less

28 CFR 54.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-07-01

... SEX IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the Basis of Sex in Employment in Education Programs or Activities Prohibited § 54.520 Job classification... based on sex; or (c) Maintain or establish separate lines of progression, seniority systems, career...

Classification systems for natural resource management

USGS Publications Warehouse

Kleckner, Richard L.

1981-01-01

Resource managers employ various types of resource classification systems in their management activities such as inventory, mapping, and data analysis. Classification is the ordering or arranging of objects into groups or sets on the basis of their relationships, and as such, provide the resource managers with a structure for organizing their needed information. In addition of conforming to certain logical principles, resource classifications should be flexible, widely applicable to a variety of environmental conditions, and useable with minimal training. The process of classification may be approached from the bottom up (aggregation) or the top down (subdivision) or a combination of both, depending on the purpose of the classification. Most resource classification systems in use today focus on a single resource and are used for a single, limited purpose. However, resource managers now must employ the concept of multiple use in their management activities. What they need is an integrated, ecologically based approach to resource classification which would fulfill multiple-use mandates. In an effort to achieve resource-data compatibility and data sharing among Federal agencies, and interagency agreement has been signed by five Federal agencies to coordinate and cooperate in the area of resource classification and inventory.

Development of a template for the classification of traditional medical knowledge in Korea.

PubMed

Kim, Sungha; Kim, Boyoung; Mun, Sujeong; Park, Jeong Hwan; Kim, Min-Kyeoung; Choi, Sunmi; Lee, Sanghun

2016-02-03

Traditional Medical Knowledge (TMK) is a form of Traditional Knowledge associated with medicine that is handed down orally or by written material. There are efforts to document TMK, and make database to conserve Traditional Medicine and facilitate future research to validate traditional use. Despite of these efforts, there is no widely accepted template in data file format that is specific for TMK and, at the same time, helpful for understanding and organizing TMK. We aimed to develop a template to classify TMK. First, we reviewed books, articles, and health-related classification systems, and used focus group discussion to establish the definition, scope, and constituents of TMK. Second, we developed an initial version of the template to classify TMK, and applied it to TMK data. Third, we revised the template, based on the results of the initial template and input from experts, and applied it to the data. We developed the template for classification of TMK. The constituents of the template were summary, properties, tools/ingredients, indication/preparation/application, and international standard classification. We applied International Patent Classification, International Classification of Diseases (Korea version), and Classification of Korean Traditional Knowledge Resources to provide legal protection of TMK and facilitate academic research. The template provides standard terms for ingredients, preparation, administration route, and procedure method to assess safety and efficacy. This is the first template that is specialized for TMK for arranging and classifying TMK. The template would have important roles in preserving TMK, and protecting intellectual property. TMK data classified with the template could be used as the preliminary data to screen potential candidates for new pharmaceuticals. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

49 CFR 25.520 - Job classification and structure.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 25.520 Transportation Office of the Secretary of Transportation NONDISCRIMINATION ON THE BASIS OF SEX... Basis of Sex in Employment in Education Programs or Activities Prohibited § 25.520 Job classification... based on sex; or (c) Maintain or establish separate lines of progression, seniority systems, career...

Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data.

PubMed

Cho, Youngsang; Seong, Joon-Kyung; Jeong, Yong; Shin, Sung Yong

2012-02-01

Patterns of brain atrophy measured by magnetic resonance structural imaging have been utilized as significant biomarkers for diagnosis of Alzheimer's disease (AD). However, brain atrophy is variable across patients and is non-specific for AD in general. Thus, automatic methods for AD classification require a large number of structural data due to complex and variable patterns of brain atrophy. In this paper, we propose an incremental method for AD classification using cortical thickness data. We represent the cortical thickness data of a subject in terms of their spatial frequency components, employing the manifold harmonic transform. The basis functions for this transform are obtained from the eigenfunctions of the Laplace-Beltrami operator, which are dependent only on the geometry of a cortical surface but not on the cortical thickness defined on it. This facilitates individual subject classification based on incremental learning. In general, methods based on region-wise features poorly reflect the detailed spatial variation of cortical thickness, and those based on vertex-wise features are sensitive to noise. Adopting a vertex-wise cortical thickness representation, our method can still achieve robustness to noise by filtering out high frequency components of the cortical thickness data while reflecting their spatial variation. This compromise leads to high accuracy in AD classification. We utilized MR volumes provided by Alzheimer's Disease Neuroimaging Initiative (ADNI) to validate the performance of the method. Our method discriminated AD patients from Healthy Control (HC) subjects with 82% sensitivity and 93% specificity. It also discriminated Mild Cognitive Impairment (MCI) patients, who converted to AD within 18 months, from non-converted MCI subjects with 63% sensitivity and 76% specificity. Moreover, it showed that the entorhinal cortex was the most discriminative region for classification, which is consistent with previous pathological findings. In

Classification and description of world formation types

Treesearch

D. Faber-Langendoen; T. Keeler-Wolf; D. Meidinger; C. Josse; A. Weakley; D. Tart; G. Navarro; B. Hoagland; S. Ponomarenko; G. Fults; Eileen Helmer

2016-01-01

An ecological vegetation classification approach has been developed in which a combination of vegetation attributes (physiognomy, structure, and floristics) and their response to ecological and biogeographic factors are used as the basis for classifying vegetation types. This approach can help support international, national, and subnational classification efforts. The...

Discovering interesting molecular substructures for molecular classification.

PubMed

Lam, Winnie W M; Chan, Keith C C

2010-06-01

Given a set of molecular structure data preclassified into a number of classes, the molecular classification problem is concerned with the discovering of interesting structural patterns in the data so that "unseen" molecules not originally in the dataset can be accurately classified. To tackle the problem, interesting molecular substructures have to be discovered and this is done typically by first representing molecular structures in molecular graphs, and then, using graph-mining algorithms to discover frequently occurring subgraphs in them. These subgraphs are then used to characterize different classes for molecular classification. While such an approach can be very effective, it should be noted that a substructure that occurs frequently in one class may also does occur in another. The discovering of frequent subgraphs for molecular classification may, therefore, not always be the most effective. In this paper, we propose a novel technique called mining interesting substructures in molecular data for classification (MISMOC) that can discover interesting frequent subgraphs not just for the characterization of a molecular class but also for the distinguishing of it from the others. Using a test statistic, MISMOC screens each frequent subgraph to determine if they are interesting. For those that are interesting, their degrees of interestingness are determined using an information-theoretic measure. When classifying an unseen molecule, its structure is then matched against the interesting subgraphs in each class and a total interestingness measure for the unseen molecule to be classified into a particular class is determined, which is based on the interestingness of each matched subgraphs. The performance of MISMOC is evaluated using both artificial and real datasets, and the results show that it can be an effective approach for molecular classification.

Disturbance and density-dependent processes (competition and facilitation) influence the fine-scale genetic structure of a tree species' population.

PubMed

Fajardo, Alex; Torres-Díaz, Cristian; Till-Bottraud, Irène

2016-01-01

Disturbances, dispersal and biotic interactions are three major drivers of the spatial distribution of genotypes within populations, the last of which has been less studied than the other two. This study aimed to determine the role of competition and facilitation in the degree of conspecific genetic relatedness of nearby individuals of tree populations. It was expected that competition among conspecifics will lead to low relatedness, while facilitation will lead to high relatedness (selection for high relatedness within clusters). The stand structure and spatial genetic structure (SGS) of trees were examined within old-growth and second-growth forests (including multi-stemmed trees at the edge of forests) of Nothofagus pumilio following large-scale fires in Patagonia, Chile. Genetic spatial autocorrelations were computed on a spatially explicit sampling of the forests using five microsatellite loci. As biotic plant interactions occur among immediate neighbours, mean nearest neighbour distance (MNND) among trees was computed as a threshold for distinguishing the effects of disturbances and biotic interactions. All forests exhibited a significant SGS for distances greater than the MNND. The old-growth forest genetic and stand structure indicated gap recolonization from nearby trees (significantly related trees at distances between 4 and 10 m). At distances smaller than the MNND, trees of the second-growth interior forest showed significantly lower relatedness, suggesting a fading of the recolonization structure by competition, whereas the second-growth edge forest showed a positive and highly significant relatedness among trees (higher among stems of a cluster than among stems of different clusters), resulting from facilitation. Biotic interactions are shown to influence the genetic composition of a tree population. However, facilitation can only persist if individuals are related. Thus, the genetic composition in turn influences what type of biotic interactions

Online adaptive decision trees: pattern classification and function approximation.

PubMed

Basak, Jayanta

2006-09-01

Recently we have shown that decision trees can be trained in the online adaptive (OADT) mode (Basak, 2004), leading to better generalization score. OADTs were bottlenecked by the fact that they are able to handle only two-class classification tasks with a given structure. In this article, we provide an architecture based on OADT, ExOADT, which can handle multiclass classification tasks and is able to perform function approximation. ExOADT is structurally similar to OADT extended with a regression layer. We also show that ExOADT is capable not only of adapting the local decision hyperplanes in the nonterminal nodes but also has the potential of smoothly changing the structure of the tree depending on the data samples. We provide the learning rules based on steepest gradient descent for the new model ExOADT. Experimentally we demonstrate the effectiveness of ExOADT in the pattern classification and function approximation tasks. Finally, we briefly discuss the relationship of ExOADT with other classification models.

Formalization of the classification pattern: survey of classification modeling in information systems engineering.

PubMed

Partridge, Chris; de Cesare, Sergio; Mitchell, Andrew; Odell, James

2018-01-01

Formalization is becoming more common in all stages of the development of information systems, as a better understanding of its benefits emerges. Classification systems are ubiquitous, no more so than in domain modeling. The classification pattern that underlies these systems provides a good case study of the move toward formalization in part because it illustrates some of the barriers to formalization, including the formal complexity of the pattern and the ontological issues surrounding the "one and the many." Powersets are a way of characterizing the (complex) formal structure of the classification pattern, and their formalization has been extensively studied in mathematics since Cantor's work in the late nineteenth century. One can use this formalization to develop a useful benchmark. There are various communities within information systems engineering (ISE) that are gradually working toward a formalization of the classification pattern. However, for most of these communities, this work is incomplete, in that they have not yet arrived at a solution with the expressiveness of the powerset benchmark. This contrasts with the early smooth adoption of powerset by other information systems communities to, for example, formalize relations. One way of understanding the varying rates of adoption is recognizing that the different communities have different historical baggage. Many conceptual modeling communities emerged from work done on database design, and this creates hurdles to the adoption of the high level of expressiveness of powersets. Another relevant factor is that these communities also often feel, particularly in the case of domain modeling, a responsibility to explain the semantics of whatever formal structures they adopt. This paper aims to make sense of the formalization of the classification pattern in ISE and surveys its history through the literature, starting from the relevant theoretical works of the mathematical literature and gradually shifting focus

[Evaluation of new and emerging health technologies. Proposal for classification].

PubMed

Prados-Torres, J D; Vidal-España, F; Barnestein-Fonseca, P; Gallo-García, C; Irastorza-Aldasoro, A; Leiva-Fernández, F

2011-01-01

Review and develop a proposal for the classification of health technologies (HT) evaluated by the Health Technology Assessment Agencies (HTAA). Peer review of AETS of the previous proposed classification of HT. Analysis of their input and suggestions for amendments. Construction of a new classification. Pilot study with physicians. Andalusian Public Health System. Spanish HTAA. Experts from HTAA. Tutors of family medicine residents. HT Update classification previously made by the research team. Peer review by Spanish HTAA. Qualitative and quantitative analysis of responses. Construction of a new and pilot study based on 12 evaluation reports of the HTAA. We obtained 11 thematic categories that are classified into 6 major head groups: 1, prevention technology; 2, diagnostic technology; 3, therapeutic technologies; 4, diagnostic and therapeutic technologies; 5, organizational technology, and 6, knowledge management and quality of care. In the pilot there was a good concordance in the classification of 8 of the 12 reports reviewed by physicians. Experts agree on 11 thematic categories of HT. A new classification of HT with double entry (Nature and purpose of HT) is proposed. APPLICABILITY: According to experts, the classification of the work of the HTAA may represent a useful tool to transfer and manage knowledge. Moreover, an adequate classification of the HTAA reports would help clinicians and other potential users to locate them and this can facilitate their dissemination. Copyright © 2010 SECA. Published by Elsevier Espana. All rights reserved.

Machine Learning Based Dimensionality Reduction Facilitates Ligand Diffusion Paths Assessment: A Case of Cytochrome P450cam.

PubMed

Rydzewski, J; Nowak, W

2016-04-12

In this work we propose an application of a nonlinear dimensionality reduction method to represent the high-dimensional configuration space of the ligand-protein dissociation process in a manner facilitating interpretation. Rugged ligand expulsion paths are mapped into 2-dimensional space. The mapping retains the main structural changes occurring during the dissociation. The topological similarity of the reduced paths may be easily studied using the Fréchet distances, and we show that this measure facilitates machine learning classification of the diffusion pathways. Further, low-dimensional configuration space allows for identification of residues active in transport during the ligand diffusion from a protein. The utility of this approach is illustrated by examination of the configuration space of cytochrome P450cam involved in expulsing camphor by means of enhanced all-atom molecular dynamics simulations. The expulsion trajectories are sampled and constructed on-the-fly during molecular dynamics simulations using the recently developed memetic algorithms [ Rydzewski, J.; Nowak, W. J. Chem. Phys. 2015 , 143 ( 12 ), 124101 ]. We show that the memetic algorithms are effective for enforcing the ligand diffusion and cavity exploration in the P450cam-camphor complex. Furthermore, we demonstrate that machine learning techniques are helpful in inspecting ligand diffusion landscapes and provide useful tools to examine structural changes accompanying rare events.

Automatic Classification of Time-variable X-Ray Sources

NASA Astrophysics Data System (ADS)

Lo, Kitty K.; Farrell, Sean; Murphy, Tara; Gaensler, B. M.

2014-05-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ~97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7-500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.

Automatic classification of time-variable X-ray sources

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

Lo, Kitty K.; Farrell, Sean; Murphy, Tara

2014-05-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, andmore » other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ∼97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7–500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.« less

CHANGING OUR DIAGNOSTIC PARADIGM: MOVEMENT SYSTEM DIAGNOSTIC CLASSIFICATION

PubMed Central

Kamonseki, Danilo H.; Staker, Justin L.; Lawrence, Rebekah L.; Braman, Jonathan P.

2017-01-01

Proper diagnosis is a first step in applying best available treatments, and prognosticating outcomes for clients. Currently, the majority of musculoskeletal diagnoses are classified according to pathoanatomy. However, the majority of physical therapy treatments are applied toward movement system impairments or pain. While advocated within the physical therapy profession for over thirty years, diagnostic classification within a movement system framework has not been uniformly developed or adopted. We propose a basic framework and rationale for application of a movement system diagnostic classification for atraumatic shoulder pain conditions, as a case for the broader development of movement system diagnostic labels. Shifting our diagnostic paradigm has potential to enhance communication, improve educational efficiency, facilitate research, directly link to function, improve clinical care, and accelerate preventive interventions. PMID:29158950

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

Entanglement classification with algebraic geometry

NASA Astrophysics Data System (ADS)

Sanz, M.; Braak, D.; Solano, E.; Egusquiza, I. L.

2017-05-01

We approach multipartite entanglement classification in the symmetric subspace in terms of algebraic geometry, its natural language. We show that the class of symmetric separable states has the structure of a Veronese variety and that its k-secant varieties are SLOCC invariants. Thus SLOCC classes gather naturally into families. This classification presents useful properties such as a linear growth of the number of families with the number of particles, and nesting, i.e. upward consistency of the classification. We attach physical meaning to this classification through the required interaction length of parent Hamiltonians. We show that the states W N and GHZ N are in the same secant family and that, effectively, the former can be obtained in a limit from the latter. This limit is understood in terms of tangents, leading to a refinement of the previous families. We compute explicitly the classification of symmetric states with N≤slant4 qubits in terms of both secant families and its refinement using tangents. This paves the way to further use of projective varieties in algebraic geometry to solve open problems in entanglement theory.

Structurally Altered Hard Coal in the Areas of Tectonic Disturbances - An Initial Attempt at Classification

NASA Astrophysics Data System (ADS)

Godyń, Katarzyna

2016-09-01

As regards the exploitation of hard coal seams, the near-fault zones and faults themselves are considered to be particularly dangerous areas, which is due to a high probability of the occurrence of gasogeodynamic phenomena. Tectonic dislocations running across a seam have a destructive impact on coal. Degradation of the coal structure, particularly visible in the microscale, is reflected in the coal's strength or gas properties. Such "structurally altered" coal is characterized by the presence of numerous fracturings, crushed areas, or dislocations of some of its fragments, and sometimes even the total destruction of the original structure. The present paper provides a detailed analysis and description of near-fault coal obtained from selected seams of the Upper Silesian Coal Basin, completed due to the application of optical methods. Both the type and the degree of changes in the structure of such coal were identified. On this basis, the author attempted to systematize the nomenclature used in relation to selected Upper Silesian hard coal seams, which, in turn, resulted in a proposed classification of the "altered structures" of the near-fault coal.

Unveiling a spinor field classification with non-Abelian gauge symmetries

NASA Astrophysics Data System (ADS)

Fabbri, Luca; da Rocha, Roldão

2018-05-01

A spinor fields classification with non-Abelian gauge symmetries is introduced, generalizing the U(1) gauge symmetries-based Lounesto's classification. Here, a more general classification, contrary to the Lounesto's one, encompasses spinor multiplets, corresponding to non-Abelian gauge fields. The particular case of SU(2) gauge symmetry, encompassing electroweak and electromagnetic conserved charges, is then implemented by a non-Abelian spinor classification, now involving 14 mixed classes of spinor doublets. A richer flagpole, dipole, and flag-dipole structure naturally descends from this general classification. The Lounesto's classification of spinors is shown to arise as a Pauli's singlet, into this more general classification.

Facilitating adverse drug event detection in pharmacovigilance databases using molecular structure similarity: application to rhabdomyolysis

PubMed Central

Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul

2011-01-01

Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238

Hierarchic Agglomerative Clustering Methods for Automatic Document Classification.

ERIC Educational Resources Information Center

Griffiths, Alan; And Others

1984-01-01

Considers classifications produced by application of single linkage, complete linkage, group average, and word clustering methods to Keen and Cranfield document test collections, and studies structure of hierarchies produced, extent to which methods distort input similarity matrices during classification generation, and retrieval effectiveness…

Facilitating the Design of a Campus Leadership Team

ERIC Educational Resources Information Center

Meyers, Renee A.; Johnson, John R.

2008-01-01

This essay describes how we facilitated the design of a campus leadership team. What is particularly interesting about this consultative project is that both authors participated--one as facilitator and the other as participant. The facilitation included a needs assessment prior to the event, the use of structured controversy techniques,…

Facilitators in Ambivalence

ERIC Educational Resources Information Center

Karlsson, Mikael R.; Erlandson, Peter

2018-01-01

This is part of a larger ethnographical study concerning how school development in a local educational context sets cultural and social life in motion. The main data "in this article" consists of semi-structural interviews with teachers (facilitators) who have the responsibility of carrying out a project about formative assessment in…

A Descriptive Genetic Classification for Glaciovolcanoes

NASA Astrophysics Data System (ADS)

Edwards, B. R.; Russell, K.; Porritt, L. A.

2014-12-01

We review the recently published descriptive genetic classification for glaciovolcanoes (Russell et al., Quat Sci Rv, 2014). The new classification uses 'tuya' as a root word for all glaciovolcanic edifices, and with modifiers that make the classification descriptive (e.g., andesitic, lava-dominated, flat topped tuya). Although tuyas can range in composition from basaltic to rhyolitic, many of the characteristics diagnostic of glaciovolcanic environments are largely independent of lava composition (e.g., edifice morphology, columnar jointing patterns, glass distributions, pyroclast shapes). Tuya subtypes are first classified on the basis of variations in edifice-scale morphologies (e.g., conical tuya) then, on the proportions of the essential lithofacies (e.g., tephra-dominated conical tuya), and lastly on magma composition (e.g., basaltic, tephra-dominated, conical tuya). The lithofacies associations within tuyas broadly record the interplay between magmatic and glaciohydraulic conditions extent during the active phases of the eruption, including the dominant style of eruption (e.g., explosive vs. effusive). We present nine distinct, endmember models for glaciovolcanic edifices that simultaneously record changes in eruption conditions (explosive, transitional, effusive) for different general glaciohydraulic conditions (closed/sealed, leaky/partly sealed, open/well-drained). To date we have identified potential examples for 7 of the 9 models. Use of a simplified, descriptive classification scheme for glaciovolcanoes will facilitate communications amongst volcanologists and planetary scientists and the use of tuyas for recovering critical paleo-environmental information, particularly the local glaciohydraulics extent during eruptions.

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan

2018-03-01

In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.

River reach classification for the Greater Mekong Region at high spatial resolution

NASA Astrophysics Data System (ADS)

Ouellet Dallaire, C.; Lehner, B.

2014-12-01

River classifications have been used in river health and ecological assessments as coarse proxies to represent aquatic biodiversity when comprehensive biological and/or species data is unavailable. Currently there are no river classifications or biological data available in a consistent format for the extent of the Greater Mekong Region (GMR; including the Irrawaddy, the Salween, the Chao Praya, the Mekong and the Red River basins). The current project proposes a new river habitat classification for the region, facilitated by the HydroSHEDS (HYDROlogical SHuttle Elevation Derivatives at multiple Scales) database at 500m pixel resolution. The classification project is based on the Global River Classification framework relying on the creation of multiple sub-classifications based on different disciplines. The resulting classes from the sub-classification are later combined into final classes to create a holistic river reach classification. For the GMR, a final habitat classification was created based on three sub-classifications: a hydrological sub-classification based only on discharge indices (river size and flow variability); a physio-climatic sub-classification based on large scale indices of climate and elevation (biomes, ecoregions and elevation); and a geomorphological sub-classification based on local morphology (presence of floodplains, reach gradient and sand transport). Key variables and thresholds were identified in collaboration with local experts to ensure that regional knowledge was included. The final classification is composed 54 unique final classes based on 3 sub-classifications with less than 15 classes each. The resulting classifications are driven by abiotic variables and do not include biological data, but they represent a state-of-the art product based on best available data (mostly global data). The most common river habitat type is the "dry broadleaf, low gradient, very small river". These classifications could be applied in a wide range of

Cross-Linking and Mass Spectrometry Methodologies to Facilitate Structural Biology: Finding a Path through the Maze

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

Merkley, Eric D.; Cort, John R.; Adkins, Joshua N.

2013-09-01

Multiprotein complexes, rather than individual proteins, make up a large part of the biological macromolecular machinery of a cell. Understanding the structure and organization of these complexes is critical to understanding cellular function. Chemical cross-linking coupled with mass spectrometry is emerging as a complementary technique to traditional structural biology methods and can provide low-resolution structural information for a multitude of purposes, such as distance constraints in computational modeling of protein complexes. In this review, we discuss the experimental considerations for successful application of chemical cross-linking-mass spectrometry in biological studies and highlight three examples of such studies from the recent literature.more » These examples (as well as many others) illustrate the utility of a chemical cross-linking-mass spectrometry approach in facilitating structural analysis of large and challenging complexes.« less

Computer-Aided Screening of Conjugated Polymers for Organic Solar Cell: Classification by Random Forest.

PubMed

Nagasawa, Shinji; Al-Naamani, Eman; Saeki, Akinori

2018-05-17

Owing to the diverse chemical structures, organic photovoltaic (OPV) applications with a bulk heterojunction framework have greatly evolved over the last two decades, which has produced numerous organic semiconductors exhibiting improved power conversion efficiencies (PCEs). Despite the recent fast progress in materials informatics and data science, data-driven molecular design of OPV materials remains challenging. We report a screening of conjugated molecules for polymer-fullerene OPV applications by supervised learning methods (artificial neural network (ANN) and random forest (RF)). Approximately 1000 experimental parameters including PCE, molecular weight, and electronic properties are manually collected from the literature and subjected to machine learning with digitized chemical structures. Contrary to the low correlation coefficient in ANN, RF yields an acceptable accuracy, which is twice that of random classification. We demonstrate the application of RF screening for the design, synthesis, and characterization of a conjugated polymer, which facilitates a rapid development of optoelectronic materials.

Toward genetics-based virus taxonomy: comparative analysis of a genetics-based classification and the taxonomy of picornaviruses.

PubMed

Lauber, Chris; Gorbalenya, Alexander E

2012-04-01

Virus taxonomy has received little attention from the research community despite its broad relevance. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3890-3904, 2012), we have introduced a quantitative approach to hierarchically classify viruses of a family using pairwise evolutionary distances (PEDs) as a measure of genetic divergence. When applied to the six most conserved proteins of the Picornaviridae, it clustered 1,234 genome sequences in groups at three hierarchical levels (to which we refer as the "GENETIC classification"). In this study, we compare the GENETIC classification with the expert-based picornavirus taxonomy and outline differences in the underlying frameworks regarding the relation of virus groups and genetic diversity that represent, respectively, the structure and content of a classification. To facilitate the analysis, we introduce two novel diagrams. The first connects the genetic diversity of taxa to both the PED distribution and the phylogeny of picornaviruses. The second depicts a classification and the accommodated genetic diversity in a standardized manner. Generally, we found striking agreement between the two classifications on species and genus taxa. A few disagreements concern the species Human rhinovirus A and Human rhinovirus C and the genus Aphthovirus, which were split in the GENETIC classification. Furthermore, we propose a new supergenus level and universal, level-specific PED thresholds, not reached yet by many taxa. Since the species threshold is approached mostly by taxa with large sampling sizes and those infecting multiple hosts, it may represent an upper limit on divergence, beyond which homologous recombination in the six most conserved genes between two picornaviruses might not give viable progeny.

A fuzzy decision tree for fault classification.

PubMed

Zio, Enrico; Baraldi, Piero; Popescu, Irina C

2008-02-01

In plant accident management, the control room operators are required to identify the causes of the accident, based on the different patterns of evolution of the monitored process variables thereby developing. This task is often quite challenging, given the large number of process parameters monitored and the intense emotional states under which it is performed. To aid the operators, various techniques of fault classification have been engineered. An important requirement for their practical application is the physical interpretability of the relationships among the process variables underpinning the fault classification. In this view, the present work propounds a fuzzy approach to fault classification, which relies on fuzzy if-then rules inferred from the clustering of available preclassified signal data, which are then organized in a logical and transparent decision tree structure. The advantages offered by the proposed approach are precisely that a transparent fault classification model is mined out of the signal data and that the underlying physical relationships among the process variables are easily interpretable as linguistic if-then rules that can be explicitly visualized in the decision tree structure. The approach is applied to a case study regarding the classification of simulated faults in the feedwater system of a boiling water reactor.

Reliability of a novel, semi-quantitative scale for classification of structural brain magnetic resonance imaging in children with cerebral palsy.

PubMed

Fiori, Simona; Cioni, Giovanni; Klingels, Katrjin; Ortibus, Els; Van Gestel, Leen; Rose, Stephen; Boyd, Roslyn N; Feys, Hilde; Guzzetta, Andrea

2014-09-01

To describe the development of a novel rating scale for classification of brain structural magnetic resonance imaging (MRI) in children with cerebral palsy (CP) and to assess its interrater and intrarater reliability. The scale consists of three sections. Section 1 contains descriptive information about the patient and MRI. Section 2 contains the graphical template of brain hemispheres onto which the lesion is transposed. Section 3 contains the scoring system for the quantitative analysis of the lesion characteristics, grouped into different global scores and subscores that assess separately side, regions, and depth. A larger interrater and intrarater reliability study was performed in 34 children with CP (22 males, 12 females; mean age at scan of 9 y 5 mo [SD 3 y 3 mo], range 4 y-16 y 11 mo; Gross Motor Function Classification System level I, [n=22], II [n=10], and level III [n=2]). Very high interrater and intrarater reliability of the total score was found with indices above 0.87. Reliability coefficients of the lobar and hemispheric subscores ranged between 0.53 and 0.95. Global scores for hemispheres, basal ganglia, brain stem, and corpus callosum showed reliability coefficients above 0.65. This study presents the first visual, semi-quantitative scale for classification of brain structural MRI in children with CP. The high degree of reliability of the scale supports its potential application for investigating the relationship between brain structure and function and examining treatment response according to brain lesion severity in children with CP. © 2014 Mac Keith Press.

Lithology-derived structure classification from the joint interpretation of magnetotelluric and seismic models

USGS Publications Warehouse

Bedrosian, P.A.; Maercklin, N.; Weckmann, U.; Bartov, Y.; Ryberg, T.; Ritter, O.

2007-01-01

Magnetotelluric and seismic methods provide complementary information about the resistivity and velocity structure of the subsurface on similar scales and resolutions. No global relation, however, exists between these parameters, and correlations are often valid for only a limited target area. Independently derived inverse models from these methods can be combined using a classification approach to map geologic structure. The method employed is based solely on the statistical correlation of physical properties in a joint parameter space and is independent of theoretical or empirical relations linking electrical and seismic parameters. Regions of high correlation (classes) between resistivity and velocity can in turn be mapped back and re-examined in depth section. The spatial distribution of these classes, and the boundaries between them, provide structural information not evident in the individual models. This method is applied to a 10 km long profile crossing the Dead Sea Transform in Jordan. Several prominent classes are identified with specific lithologies in accordance with local geology. An abrupt change in lithology across the fault, together with vertical uplift of the basement suggest the fault is sub-vertical within the upper crust. ?? 2007 The Authors Journal compilation ?? 2007 RAS.

Protein classification using modified n-grams and skip-grams.

PubMed

Islam, S M Ashiqul; Heil, Benjamin J; Kearney, Christopher Michel; Baker, Erich J

2018-05-01

Classification by supervised machine learning greatly facilitates the annotation of protein characteristics from their primary sequence. However, the feature generation step in this process requires detailed knowledge of attributes used to classify the proteins. Lack of this knowledge risks the selection of irrelevant features, resulting in a faulty model. In this study, we introduce a supervised protein classification method with a novel means of automating the work-intensive feature generation step via a Natural Language Processing (NLP)-dependent model, using a modified combination of n-grams and skip-grams (m-NGSG). A meta-comparison of cross-validation accuracy with twelve training datasets from nine different published studies demonstrates a consistent increase in accuracy of m-NGSG when compared to contemporary classification and feature generation models. We expect this model to accelerate the classification of proteins from primary sequence data and increase the accessibility of protein characteristic prediction to a broader range of scientists. m-NGSG is freely available at Bitbucket: https://bitbucket.org/sm_islam/mngsg/src. A web server is available at watson.ecs.baylor.edu/ngsg. erich_baker@baylor.edu. Supplementary data are available at Bioinformatics online.

Molecular classification of pesticides including persistent organic pollutants, phenylurea and sulphonylurea herbicides.

PubMed

Torrens, Francisco; Castellano, Gloria

2014-06-05

Pesticide residues in wine were analyzed by liquid chromatography-tandem mass spectrometry. Retentions are modelled by structure-property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy-morphological determination-natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.

Facilitation and practice in verb acquisition.

PubMed

Keren-Portnoy, Tamar

2006-08-01

This paper presents a model of syntax acquisition, whose main points are as follows: Syntax is acquired in an item-based manner; early learning facilitates subsequent learning--as evidenced by the accelerating rate of new verbs entering a given structure; and mastery of syntactic knowledge is typically achieved through practice--as evidenced by intensive use and common word order errors--and this slows down learning during the early stages of acquiring a structure. The facilitation and practice hypotheses were tested on naturalistic production samples of six Hebrew-acquiring children ranging from ages 1;1 to 2;7 (average ages 1;6 to 2;4 months). Results show that most structures did in fact accelerate; the notion of 'practice' is supported by the inverse correlation found between number of verbs and number of errors in the earliest productions in a given structure; and the absence of acceleration in a minority of the structures is due to the fact that they involve relatively less practice.

ClaRNA: a classifier of contacts in RNA 3D structures based on a comparative analysis of various classification schemes

PubMed Central

Waleń, Tomasz; Chojnowski, Grzegorz; Gierski, Przemysław; Bujnicki, Janusz M.

2014-01-01

The understanding of folding and function of RNA molecules depends on the identification and classification of interactions between ribonucleotide residues. We developed a new method named ClaRNA for computational classification of contacts in RNA 3D structures. Unique features of the program are the ability to identify imperfect contacts and to process coarse-grained models. Each doublet of spatially close ribonucleotide residues in a query structure is compared to clusters of reference doublets obtained by analysis of a large number of experimentally determined RNA structures, and assigned a score that describes its similarity to one or more known types of contacts, including pairing, stacking, base–phosphate and base–ribose interactions. The accuracy of ClaRNA is 0.997 for canonical base pairs, 0.983 for non-canonical pairs and 0.961 for stacking interactions. The generalized squared correlation coefficient (GC2) for ClaRNA is 0.969 for canonical base pairs, 0.638 for non-canonical pairs and 0.824 for stacking interactions. The classifier can be easily extended to include new types of spatial relationships between pairs or larger assemblies of nucleotide residues. ClaRNA is freely available via a web server that includes an extensive set of tools for processing and visualizing structural information about RNA molecules. PMID:25159614

Parent Involvement Facilitators: Unlocking Social Capital Wealth

ERIC Educational Resources Information Center

Ferrara, Margaret M.

2015-01-01

This case study provides an overview of a family outreach intervention that supports student retention in school through a school-home communication link. This intervention structure, which employs staff appropriately called parent involvement facilitators (PIFs), is one that school districts have employed to facilitate family engagement in…

Structural plasticity in hippocampal cells related to the facilitative effect of intracranial self-stimulation on a spatial memory task.

PubMed

Chamorro-López, Jacobo; Miguéns, Miguel; Morgado-Bernal, Ignacio; Kastanauskaite, Asta; Selvas, Abraham; Cabané-Cucurella, Alberto; Aldavert-Vera, Laura; DeFelipe, Javier; Segura-Torres, Pilar

2015-12-01

Posttraining intracranial self-stimulation (SS) in the lateral hypothalamus facilitates the acquisition and retention of several implicit and explicit memory tasks. Here, intracellular injections of Lucifer yellow were used to assess morphological changes in hippocampal neurons that might be specifically related to the facilitative posttraining SS effect upon the acquisition and retention of a distributed spatial task in the Morris water maze. We examined the structure, size and branching complexity of cornus ammonis 1 (CA1) cells, and the spine density of CA1 pyramidal neurons and granular cells of the dentate gyrus (DG). Animals that received SS after each acquisition session performed faster and better than Sham ones--an improvement that was also evident in a probe trial 3 days after the last training session. The neuromorphological analysis revealed an increment in the size and branching complexity in apical CA1 dendritic arborization in SS-treated subjects as compared with Sham animals. Furthermore, increased spine density was observed in the CA1 field in SS animals, whereas no effects were observed in DG cells. Our results support the hypothesis that the facilitating effect of SS on the acquisition and retention of a spatial memory task could be related to structural plasticity in CA1 hippocampal cells. (c) 2015 APA, all rights reserved).

Consensus classification of posterior cortical atrophy.

PubMed

Crutch, Sebastian J; Schott, Jonathan M; Rabinovici, Gil D; Murray, Melissa; Snowden, Julie S; van der Flier, Wiesje M; Dickerson, Bradford C; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H; Boeve, Bradley F; Butler, Christopher; Cappa, Stefano F; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R; Hof, Patrick R; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F; Nestor, Peter J; Onyike, Chiadi U; Pelak, Victoria S; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N; Ryan, Natalie S; Scheltens, Philip; Shakespeare, Timothy J; Suárez González, Aida; Tang-Wai, David F; Yong, Keir X X; Carrillo, Maria; Fox, Nick C

2017-08-01

A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. Copyright © 2017 The Authors

Consensus classification of posterior cortical atrophy

PubMed Central

Crutch, Sebastian J.; Schott, Jonathan M.; Rabinovici, Gil D.; Murray, Melissa; Snowden, Julie S.; van der Flier, Wiesje M.; Dickerson, Bradford C.; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H.; Boeve, Bradley F.; Butler, Christopher; Cappa, Stefano F.; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R.; Hof, Patrick R.; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F.; Nestor, Peter J.; Onyike, Chiadi U.; Pelak, Victoria S.; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N.; Ryan, Natalie S.; Scheltens, Philip; Shakespeare, Timothy J.; González, Aida Suárez; Tang-Wai, David F.; Yong, Keir X. X.; Carrillo, Maria; Fox, Nick C.

2017-01-01

Introduction A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Methods Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. Results A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. Discussion There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future

A Mixtures-of-Trees Framework for Multi-Label Classification

PubMed Central

Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

2015-01-01

We propose a new probabilistic approach for multi-label classification that aims to represent the class posterior distribution P(Y|X). Our approach uses a mixture of tree-structured Bayesian networks, which can leverage the computational advantages of conditional tree-structured models and the abilities of mixtures to compensate for tree-structured restrictions. We develop algorithms for learning the model from data and for performing multi-label predictions using the learned model. Experiments on multiple datasets demonstrate that our approach outperforms several state-of-the-art multi-label classification methods. PMID:25927011

A Ternary Brain-Computer Interface Based on Single-Trial Readiness Potentials of Self-initiated Fine Movements: A Diversified Classification Scheme

PubMed Central

Abou Zeid, Elias; Rezazadeh Sereshkeh, Alborz; Schultz, Benjamin; Chau, Tom

2017-01-01

In recent years, the readiness potential (RP), a type of pre-movement neural activity, has been investigated for asynchronous electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Since the RP is attenuated for involuntary movements, a BCI driven by RP alone could facilitate intentional control amid a plethora of unintentional movements. Previous studies have mainly attempted binary single-trial classification of RP. An RP-based BCI with three or more states would expand the options for functional control. Here, we propose a ternary BCI based on single-trial RPs. This BCI classifies amongst an idle state, a left hand and a right hand self-initiated fine movement. A pipeline of spatio-temporal filtering with per participant parameter optimization was used for feature extraction. The ternary classification was decomposed into binary classifications using a decision-directed acyclic graph (DDAG). For each class pair in the DDAG structure, an ordered diversified classifier system (ODCS-DDAG) was used to select the best among various classification algorithms or to combine the results of different classification algorithms. Using EEG data from 14 participants performing self-initiated left or right key presses, punctuated with rest periods, we compared the performance of ODCS-DDAG to a ternary classifier and four popular multiclass decomposition methods using only a single classification algorithm. ODCS-DDAG had the highest performance (0.769 Cohen's Kappa score) and was significantly better than the ternary classifier and two of the four multiclass decomposition methods. Our work supports further study of RP-based BCI for intuitive asynchronous environmental control or augmentative communication. PMID:28596725

An information-based network approach for protein classification

PubMed Central

Wan, Xiaogeng; Zhao, Xin; Yau, Stephen S. T.

2017-01-01

Protein classification is one of the critical problems in bioinformatics. Early studies used geometric distances and polygenetic-tree to classify proteins. These methods use binary trees to present protein classification. In this paper, we propose a new protein classification method, whereby theories of information and networks are used to classify the multivariate relationships of proteins. In this study, protein universe is modeled as an undirected network, where proteins are classified according to their connections. Our method is unsupervised, multivariate, and alignment-free. It can be applied to the classification of both protein sequences and structures. Nine examples are used to demonstrate the efficiency of our new method. PMID:28350835

The facilitators and impediment factors of structural empowerment in pregnancy and delivery care: achievement of power

PubMed Central

Janighorban, M; Yousefi, H; Yamani, N

2015-01-01

Background: The organizations essentially affect empowerment of personnel through the preparation of the needed grounds for them. Also, the students may acquire the required potentials and capabilities in the educational organizations when the possibility is provided to them to access power and opportunity in educational environments. Objective: The present study aimed to explain the facilitators and impediment factors of structural empowerment in pregnancy and delivery care. Methods: According to Kanter’s theory, this qualitative study was conducted with the participation of 15 superior midwifery students, ten academic teachers of midwifery, and two midwives employed in the educational hospitals. Data were collected by semi-structured interviews individually and in the group and analyzed by using a directed content analysis method. Results: To explain the facilitators and impediment factors of empowerment in pregnancy and delivery care in the power structure, the access was provided to a support formed by three broad categories of support from the instructors, support from personnel, and support from a classmate. The access to resources was created with three broad categories of access to the appropriate clinical environment, to the laboratory of clinical skills and to information sources, and to information, forming with two broad categories of awareness of the educational objectives as well as legal and legitimate issues. Conclusion: One could prepare the ground for the midwifery students to access this empowerment in pregnancy and delivery cares more than ever by providing equipped clinical environments and the presence of all-inclusive supportive climate in such environments. Along with the efficient training of students in the laboratory PMID:28316710

Heuristic Classification. Technical Report Number 12.

ERIC Educational Resources Information Center

Clancey, William J.

A broad range of well-structured problems--embracing forms of diagnosis, catalog selection, and skeletal planning--are solved in expert computer systems by the method of heuristic classification. These programs have a characteristic inference structure that systematically relates data to a pre-enumerated set of solutions by abstraction, heuristic…

Classification and reduction of pilot error

NASA Technical Reports Server (NTRS)

Rogers, W. H.; Logan, A. L.; Boley, G. D.

1989-01-01

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses.

Novel chromatin texture features for the classification of pap smears

NASA Astrophysics Data System (ADS)

Bejnordi, Babak E.; Moshavegh, Ramin; Sujathan, K.; Malm, Patrik; Bengtsson, Ewert; Mehnert, Andrew

2013-03-01

This paper presents a set of novel structural texture features for quantifying nuclear chromatin patterns in cells on a conventional Pap smear. The features are derived from an initial segmentation of the chromatin into bloblike texture primitives. The results of a comprehensive feature selection experiment, including the set of proposed structural texture features and a range of different cytology features drawn from the literature, show that two of the four top ranking features are structural texture features. They also show that a combination of structural and conventional features yields a classification performance of 0.954±0.019 (AUC±SE) for the discrimination of normal (NILM) and abnormal (LSIL and HSIL) slides. The results of a second classification experiment, using only normal-appearing cells from both normal and abnormal slides, demonstrates that a single structural texture feature measuring chromatin margination yields a classification performance of 0.815±0.019. Overall the results demonstrate the efficacy of the proposed structural approach and that it is possible to detect malignancy associated changes (MACs) in Papanicoloau stain.

Structure of the periplasmic adaptor protein from a major facilitator superfamily (MFS) multidrug efflux pump.

PubMed

Hinchliffe, Philip; Greene, Nicholas P; Paterson, Neil G; Crow, Allister; Hughes, Colin; Koronakis, Vassilis

2014-08-25

Periplasmic adaptor proteins are key components of bacterial tripartite efflux pumps. The 2.85 Å resolution structure of an MFS (major facilitator superfamily) pump adaptor, Aquifex aeolicus EmrA, shows linearly arranged α-helical coiled-coil, lipoyl, and β-barrel domains, but lacks the fourth membrane-proximal domain shown in other pumps to interact with the inner membrane transporter. The adaptor α-hairpin, which binds outer membrane TolC, is exceptionally long at 127 Å, and the β-barrel contains a conserved disordered loop. The structure extends the view of adaptors as flexible, modular components that mediate diverse pump assembly, and suggests that in MFS tripartite pumps a hexamer of adaptors could provide a periplasmic seal. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Probabilistic Gait Classification in Children with Cerebral Palsy: A Bayesian Approach

ERIC Educational Resources Information Center

Van Gestel, Leen; De Laet, Tinne; Di Lello, Enrico; Bruyninckx, Herman; Molenaers, Guy; Van Campenhout, Anja; Aertbelien, Erwin; Schwartz, Mike; Wambacq, Hans; De Cock, Paul; Desloovere, Kaat

2011-01-01

Three-dimensional gait analysis (3DGA) generates a wealth of highly variable data. Gait classifications help to reduce, simplify and interpret this vast amount of 3DGA data and thereby assist and facilitate clinical decision making in the treatment of CP. CP gait is often a mix of several clinically accepted distinct gait patterns. Therefore,…

Identification and classification of structural soil conservation measures based on very high resolution stereo satellite data.

PubMed

Eckert, Sandra; Tesfay Ghebremicael, Selamawit; Hurni, Hans; Kohler, Thomas

2017-05-15

Land degradation affects large areas of land around the globe, with grave consequences for those living off the land. Major efforts are being made to implement soil and water conservation measures that counteract soil erosion and help secure vital ecosystem services. However, where and to what extent such measures have been implemented is often not well documented. Knowledge about this could help to identify areas where soil and water conservation measures are successfully supporting sustainable land management, as well as areas requiring urgent rehabilitation of conservation structures such as terraces and bunds. This study explores the potential of the latest satellite-based remote sensing technology for use in assessing and monitoring the extent of existing soil and water conservation structures. We used a set of very high resolution stereo Geoeye-1 satellite data, from which we derived a detailed digital surface model as well as a set of other spectral, terrain, texture, and filtered information layers. We developed and applied an object-based classification approach, working on two segmentation levels. On the coarser level, the aim was to delimit certain landscape zones. Information about these landscape zones is useful in distinguishing different types of soil and water conservation structures, as each zone contains certain specific types of structures. On the finer level, the goal was to extract and identify different types of linear soil and water conservation structures. The classification rules were based mainly on spectral, textural, shape, and topographic properties, and included object relationships. This approach enabled us to identify and separate from other classes the majority (78.5%) of terraces and bunds, as well as most hillside terraces (81.25%). Omission and commission errors are similar to those obtained by the few existing studies focusing on the same research objective but using different types of remotely sensed data. Based on our results

Assessing Facilitator Performance as an Influence on Student Satisfaction

ERIC Educational Resources Information Center

Dunlap, Scotty; May, David

2011-01-01

Growth in class size within the online environment has resulted in a facilitator model in which an instructor teaches the class with the assistance of facilitators who interact with students in smaller groups. This research sought to determine the effectiveness of a structured performance evaluation for facilitators and the correlation to student…

Using EUNIS habitat classification for benthic mapping in European seas: present concerns and future needs.

PubMed

Galparsoro, Ibon; Connor, David W; Borja, Angel; Aish, Annabelle; Amorim, Patricia; Bajjouk, Touria; Chambers, Caroline; Coggan, Roger; Dirberg, Guillaume; Ellwood, Helen; Evans, Douglas; Goodin, Kathleen L; Grehan, Anthony; Haldin, Jannica; Howell, Kerry; Jenkins, Chris; Michez, Noëmie; Mo, Giulia; Buhl-Mortensen, Pål; Pearce, Bryony; Populus, Jacques; Salomidi, Maria; Sánchez, Francisco; Serrano, Alberto; Shumchenia, Emily; Tempera, Fernando; Vasquez, Mickaël

2012-12-01

The EUNIS (European Union Nature Information System) habitat classification system aims to provide a common European reference set of habitat types within a hierarchical classification, and to cover all terrestrial, freshwater and marine habitats of Europe. The classification facilitates reporting of habitat data in a comparable manner, for use in nature conservation (e.g. inventories, monitoring and assessments), habitat mapping and environmental management. For the marine environment the importance of a univocal habitat classification system is confirmed by the fact that many European initiatives, aimed at marine mapping, assessment and reporting, are increasingly using EUNIS habitat categories and respective codes. For this reason substantial efforts have been made to include information on marine benthic habitats from different regions, aiming to provide a comprehensive geographical coverage of European seas. However, there still remain many concerns on its applicability as only a small fraction of Europe's seas are fully mapped and increasing knowledge and application raise further issues to be resolved. This paper presents an overview of the main discussion and conclusions of a workshop, organised by the MeshAtlantic project, focusing upon the experience in using the EUNIS habitats classification across different countries and seas, together with case studies. The aims of the meeting were to: (i) bring together scientists with experience in the use of the EUNIS marine classification and representatives from the European Environment Agency (EEA); (ii) agree on enhancements to EUNIS that ensure an improved representation of the European marine habitats; and (iii) establish practices that make marine habitat maps produced by scientists more consistent with the needs of managers and decision-makers. During the workshop challenges for the future development of EUNIS were identified, which have been classified into five categories: (1) structure and hierarchy; (2

Comprehensive structural and substrate specificity classification of the Saccharomyces cerevisiae methyltransferome.

PubMed

Wlodarski, Tomasz; Kutner, Jan; Towpik, Joanna; Knizewski, Lukasz; Rychlewski, Leszek; Kudlicki, Andrzej; Rowicka, Maga; Dziembowski, Andrzej; Ginalski, Krzysztof

2011-01-01

Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity). Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity.

Towards an International Classification for Patient Safety: the conceptual framework.

PubMed

Sherman, Heather; Castro, Gerard; Fletcher, Martin; Hatlie, Martin; Hibbert, Peter; Jakob, Robert; Koss, Richard; Lewalle, Pierre; Loeb, Jerod; Perneger, Thomas; Runciman, William; Thomson, Richard; Van Der Schaaf, Tjerk; Virtanen, Martti

2009-02-01

Global advances in patient safety have been hampered by the lack of a uniform classification of patient safety concepts. This is a significant barrier to developing strategies to reduce risk, performing evidence-based research and evaluating existing healthcare policies relevant to patient safety. Since 2005, the World Health Organization's World Alliance for Patient Safety has undertaken the Project to Develop an International Classification for Patient Safety (ICPS) to devise a classification which transforms patient safety information collected from disparate systems into a common format to facilitate aggregation, analysis and learning across disciplines, borders and time. A drafting group, comprised of experts from the fields of patient safety, classification theory, health informatics, consumer/patient advocacy, law and medicine, identified and defined key patient safety concepts and developed an internationally agreed conceptual framework for the ICPS based upon existing patient safety classifications. The conceptual framework was iteratively improved through technical expert meetings and a two-stage web-based modified Delphi survey of over 250 international experts. This work culminated in a conceptual framework consisting of ten high level classes: incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors/hazards, organizational outcomes, detection, mitigating factors, ameliorating actions and actions taken to reduce risk. While the framework for the ICPS is in place, several challenges remain. Concepts need to be defined, guidance for using the classification needs to be provided, and further real-world testing needs to occur to progressively refine the ICPS to ensure it is fit for purpose.

Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective

PubMed Central

Zhao, Changbo; Li, Guo-Zheng; Wang, Chengjun; Niu, Jinling

2015-01-01

As a complementary and alternative medicine in medical field, traditional Chinese medicine (TCM) has drawn great attention in the domestic field and overseas. In practice, TCM provides a quite distinct methodology to patient diagnosis and treatment compared to western medicine (WM). Syndrome (ZHENG or pattern) is differentiated by a set of symptoms and signs examined from an individual by four main diagnostic methods: inspection, auscultation and olfaction, interrogation, and palpation which reflects the pathological and physiological changes of disease occurrence and development. Patient classification is to divide patients into several classes based on different criteria. In this paper, from the machine learning perspective, a survey on patient classification issue will be summarized on three major aspects of TCM: sign classification, syndrome differentiation, and disease classification. With the consideration of different diagnostic data analyzed by different computational methods, we present the overview for four subfields of TCM diagnosis, respectively. For each subfield, we design a rectangular reference list with applications in the horizontal direction and machine learning algorithms in the longitudinal direction. According to the current development of objective TCM diagnosis for patient classification, a discussion of the research issues around machine learning techniques with applications to TCM diagnosis is given to facilitate the further research for TCM patient classification. PMID:26246834

Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.

Validation of a new classification for periprosthetic shoulder fractures.

PubMed

Kirchhoff, Chlodwig; Beirer, Marc; Brunner, Ulrich; Buchholz, Arne; Biberthaler, Peter; Crönlein, Moritz

2018-06-01

Successful treatment of periprosthetic shoulder fractures depends on the right strategy, starting with a well-structured classification of the fracture. Unfortunately, clinically relevant factors for treatment planning are missing in the pre-existing classifications. Therefore, the aim of the present study was to describe a new specific classification system for periprosthetic shoulder fractures including a structured treatment algorithm for this important fragility fracture issue. The classification was established, focussing on five relevant items, naming the prosthesis type, the fracture localisation, the rotator cuff status, the anatomical fracture region and the stability of the implant. After considering each single item, the individual treatment concept can be assessed in one last step. To evaluate the introduced classification, a retrospective analysis of pre- and post-operative data of patients, treated with periprosthetic shoulder fractures, was conducted by two board certified trauma surgery consultants. The data of 19 patients (8 male, 11 female) with a mean age of 74 ± five years have been analysed in our study. The suggested treatment algorithm was proven to be reliable, detected by good clinical outcome in 15 of 16 (94%) cases, where the suggested treatment was maintained. Only one case resulted in poor outcome due to post-operative wound infection and had to be revised. The newly developed six-step classification is easy to utilise and extends the pre-existing classification systems in terms of clinically-relevant information. This classification should serve as a simple tool for the surgeon to consider the optimal treatment for his patients.

Classification of proteins with shared motifs and internal repeats in the ECOD database

PubMed Central

Kinch, Lisa N.; Liao, Yuxing

2016-01-01

Abstract Proteins and their domains evolve by a set of events commonly including the duplication and divergence of small motifs. The presence of short repetitive regions in domains has generally constituted a difficult case for structural domain classifications and their hierarchies. We developed the Evolutionary Classification Of protein Domains (ECOD) in part to implement a new schema for the classification of these types of proteins. Here we document the ways in which ECOD classifies proteins with small internal repeats, widespread functional motifs, and assemblies of small domain‐like fragments in its evolutionary schema. We illustrate the ways in which the structural genomics project impacted the classification and characterization of new structural domains and sequence families over the decade. PMID:26833690

Toward Genetics-Based Virus Taxonomy: Comparative Analysis of a Genetics-Based Classification and the Taxonomy of Picornaviruses

PubMed Central

Lauber, Chris

2012-01-01

Virus taxonomy has received little attention from the research community despite its broad relevance. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3890–3904, 2012), we have introduced a quantitative approach to hierarchically classify viruses of a family using pairwise evolutionary distances (PEDs) as a measure of genetic divergence. When applied to the six most conserved proteins of the Picornaviridae, it clustered 1,234 genome sequences in groups at three hierarchical levels (to which we refer as the “GENETIC classification”). In this study, we compare the GENETIC classification with the expert-based picornavirus taxonomy and outline differences in the underlying frameworks regarding the relation of virus groups and genetic diversity that represent, respectively, the structure and content of a classification. To facilitate the analysis, we introduce two novel diagrams. The first connects the genetic diversity of taxa to both the PED distribution and the phylogeny of picornaviruses. The second depicts a classification and the accommodated genetic diversity in a standardized manner. Generally, we found striking agreement between the two classifications on species and genus taxa. A few disagreements concern the species Human rhinovirus A and Human rhinovirus C and the genus Aphthovirus, which were split in the GENETIC classification. Furthermore, we propose a new supergenus level and universal, level-specific PED thresholds, not reached yet by many taxa. Since the species threshold is approached mostly by taxa with large sampling sizes and those infecting multiple hosts, it may represent an upper limit on divergence, beyond which homologous recombination in the six most conserved genes between two picornaviruses might not give viable progeny. PMID:22278238

The Universal Decimal Classification: Some Factors Concerning Its Origins, Development, and Influence.

ERIC Educational Resources Information Center

McIlwaine, I. C.

1997-01-01

Discusses the history and development of the Universal Decimal Classification (UDC). Topics include the relationship with Dewey Decimal Classification; revision process; structure; facet analysis; lack of standard rules for application; application in automated systems; influence of UDC on classification development; links with thesauri; and use…

Supply chain planning classification

NASA Astrophysics Data System (ADS)

Hvolby, Hans-Henrik; Trienekens, Jacques; Bonde, Hans

2001-10-01

Industry experience a need to shift in focus from internal production planning towards planning in the supply network. In this respect customer oriented thinking becomes almost a common good amongst companies in the supply network. An increase in the use of information technology is needed to enable companies to better tune their production planning with customers and suppliers. Information technology opportunities and supply chain planning systems facilitate companies to monitor and control their supplier network. In spite if these developments, most links in today's supply chains make individual plans, because the real demand information is not available throughout the chain. The current systems and processes of the supply chains are not designed to meet the requirements now placed upon them. For long term relationships with suppliers and customers, an integrated decision-making process is needed in order to obtain a satisfactory result for all parties. Especially when customized production and short lead-time is in focus. An effective value chain makes inventory available and visible among the value chain members, minimizes response time and optimizes total inventory value held throughout the chain. In this paper a supply chain planning classification grid is presented based current manufacturing classifications and supply chain planning initiatives.

Classification framework for partially observed dynamical systems

NASA Astrophysics Data System (ADS)

Shen, Yuan; Tino, Peter; Tsaneva-Atanasova, Krasimira

2017-04-01

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using point estimates of model parameters to represent individual data items, we employ posterior distributions over model parameters, thus taking into account in a principled manner the uncertainty due to both the generative (observational and/or dynamic noise) and observation (sampling in time) processes. We evaluate the framework on two test beds: a biological pathway model and a stochastic double-well system. Crucially, we show that the classification performance is not impaired when the model structure used for inferring posterior distributions is much more simple than the observation-generating model structure, provided the reduced-complexity inferential model structure captures the essential characteristics needed for the given classification task.

T-RMSD: a fine-grained, structure-based classification method and its application to the functional characterization of TNF receptors.

PubMed

Magis, Cedrik; Stricher, François; van der Sloot, Almer M; Serrano, Luis; Notredame, Cedric

2010-07-16

This study addresses the relation between structural and functional similarity in proteins. We introduce a novel method named tree based on root mean square deviation (T-RMSD), which uses distance RMSD (dRMSD) variations to build fine-grained structure-based classifications of proteins. The main improvement of the T-RMSD over similar methods, such as Dali, is its capacity to produce the equivalent of a bootstrap value for each cluster node. We validated our approach on two domain families studied extensively for their role in many biological and pathological pathways: the small GTPase RAS superfamily and the cysteine-rich domains (CRDs) associated with the tumor necrosis factor receptors (TNFRs) family. Our analysis showed that T-RMSD is able to automatically recover and refine existing classifications. In the case of the small GTPase ARF subfamily, T-RMSD can distinguish GTP- from GDP-bound states, while in the case of CRDs it can identify two new subgroups associated with well defined functional features (ligand binding and formation of ligand pre-assembly complex). We show how hidden Markov models (HMMs) can be built on these new groups and propose a methodology to use these models simultaneously in order to do fine-grained functional genomic annotation without known 3D structures. T-RMSD, an open source freeware incorporated in the T-Coffee package, is available online. 2010 Elsevier Ltd. All rights reserved.

Novel Strength Test Battery to Permit Evidence-Based Paralympic Classification

PubMed Central

Beckman, Emma M.; Newcombe, Peter; Vanlandewijck, Yves; Connick, Mark J.; Tweedy, Sean M.

2014-01-01

Abstract Ordinal-scale strength assessment methods currently used in Paralympic athletics classification prevent the development of evidence-based classification systems. This study evaluated a battery of 7, ratio-scale, isometric tests with the aim of facilitating the development of evidence-based methods of classification. This study aimed to report sex-specific normal performance ranges, evaluate test–retest reliability, and evaluate the relationship between the measures and body mass. Body mass and strength measures were obtained from 118 participants—63 males and 55 females—ages 23.2 years ± 3.7 (mean ± SD). Seventeen participants completed the battery twice to evaluate test–retest reliability. The body mass–strength relationship was evaluated using Pearson correlations and allometric exponents. Conventional patterns of force production were observed. Reliability was acceptable (mean intraclass correlation = 0.85). Eight measures had moderate significant correlations with body size (r = 0.30–61). Allometric exponents were higher in males than in females (mean 0.99 vs 0.30). Results indicate that this comprehensive and parsimonious battery is an important methodological advance because it has psychometric properties critical for the development of evidence-based classification. Measures were interrelated with body size, indicating further research is required to determine whether raw measures require normalization in order to be validly applied in classification. PMID:25068950

Surgical management of morbidity due to lymphatic filariasis: the usefulness of a standardized international clinical classification of hydroceles.

PubMed

Capuano, G P; Capuano, C

2012-03-01

The objective of this work is to evaluate the usefulness of a standardized clinical classification of hydroceles in lymphatic filariasis endemic countries to guide their surgical management. 64 patients with hydroceles were operated in 2009-2010, in Level II hospitals (WHO classification), during two visits to Fiji, by the same mobile surgical team. The number of hydroceles treated was 83. We developed and evaluated a much needed clinical classification of hydroceles based on four criteria: Type (uni/bilateral); Side (left/right); Stage of enlargement of the scrotum rated from I to VI; Grade of burial of the penis rated from 0 to 4. It lead to the conclusion that 1) A Stage I or II hydrocele, associated with Grade 0 or 1 penis burial could be considered a "Simple Hydrocele". The surgical treatment is simple with no anticipated early complication. WHO Level II of health care structure seems adapted. 2) A Stage III or IV hydrocele associated with Grade 2, 3 or 4 penis burial could be considered a "Complicated Hydrocele". The operation is longer, more complicated and the possibility of occurrence of complications seems greater. A level III health care facility would be more adapted under the normal functioning of the health system. We conclude that a standardized clinical classification of hydroceles based on the Stage of enlargement of the scrotum and the Grade of burial of the penis appears to be a useful tool to guide the decision about the level of care and the surgical technique required. We use the same classification for penoscrotal lymphoedema. A decision tree is presented for the management of hydroceles in lymphatic filariasis endemic countries which could usefully complement the "Algorithm for management of scrotal swelling" proposed by WHO in 2002. An international classification system of hydroceles would also allow standardization and facilitate study design and comparisons of their results.

The Value of Ensari's Proposal in Evaluating the Mucosal Pathology of Childhood Celiac Disease: Old Classification versus New Version.

PubMed

Güreşci, Servet; Hızlı, Samil; Simşek, Gülçin Güler

2012-09-01

Small intestinal biopsy remains the gold standard in diagnosing celiac disease (CD); however, the wide spectrum of histopathological states and differential diagnosis of CD is still a diagnostic problem for pathologists. Recently, Ensari reviewed the literature and proposed an update of the histopathological diagnosis and classification for CD. In this study, the histopathological materials of 54 children in whom CD was diagnosed at our hospital were reviewed to compare the previous Marsh and Modified Marsh-Oberhuber classifications with this new proposal. In this study, we show that the Ensari classification is as accurate as the Marsh and Modified Marsh classifications in describing the consecutive states of mucosal damage seen in CD. Ensari's classification is simple, practical and facilitative in diagnosing and subtyping of mucosal pathology of CD.

Rapid automated classification of anesthetic depth levels using GPU based parallelization of neural networks.

PubMed

Peker, Musa; Şen, Baha; Gürüler, Hüseyin

2015-02-01

The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is important for the rapid solution of problems in the field of biomedical signal processing. However numerous, time-consuming mathematical operations are required when training and testing stages of the classification algorithms, especially in neural networks. In this study, to accelerate the process, parallel programming and computing platform (Nvidia CUDA) facilitates dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU) was utilized. The system was employed to detect anesthetic depth level on related electroencephalogram (EEG) data set. This dataset is rather complex and large. Moreover, the achieving more anesthetic levels with rapid response is critical in anesthesia. The proposed parallelization method yielded high accurate classification results in a faster time.

Facilitated diffusion in chromatin lattices: mechanistic diversity and regulatory potential.

PubMed

Kampmann, Martin

2005-08-01

The interaction between a protein and a specific DNA site is the molecular basis for vital processes in all organisms. Location of the DNA target site by the protein commonly involves facilitated diffusion. Mechanisms of facilitated diffusion vary among proteins; they include one- and two-dimensional sliding along DNA, direct transfer between uncorrelated sites, as well as combinations of these mechanisms. Facilitated diffusion has almost exclusively been studied in vitro. This review discusses facilitated diffusion in the context of the living cell and proposes a theoretical model for facilitated diffusion in chromatin lattices. Chromatin structure differentially affects proteins in different modes of diffusion. The interplay of facilitated diffusion and chromatin structure can determine the rate of protein association with the target site, the frequency of association-dissociation events at the target site, and, under particular conditions, the occupancy of the target site. Facilitated diffusion is required in vivo for efficient DNA repair and bacteriophage restriction and has potential roles in fine-tuning gene regulatory networks and kinetically compartmentalizing the eukaryotic nucleus.

Classification of crystal structure using a convolutional neural network

PubMed Central

Park, Woon Bae; Chung, Jiyong; Sohn, Keemin; Pyo, Myoungho

2017-01-01

A deep machine-learning technique based on a convolutional neural network (CNN) is introduced. It has been used for the classification of powder X-ray diffraction (XRD) patterns in terms of crystal system, extinction group and space group. About 150 000 powder XRD patterns were collected and used as input for the CNN with no handcrafted engineering involved, and thereby an appropriate CNN architecture was obtained that allowed determination of the crystal system, extinction group and space group. In sharp contrast with the traditional use of powder XRD pattern analysis, the CNN never treats powder XRD patterns as a deconvoluted and discrete peak position or as intensity data, but instead the XRD patterns are regarded as nothing but a pattern similar to a picture. The CNN interprets features that humans cannot recognize in a powder XRD pattern. As a result, accuracy levels of 81.14, 83.83 and 94.99% were achieved for the space-group, extinction-group and crystal-system classifications, respectively. The well trained CNN was then used for symmetry identification of unknown novel inorganic compounds. PMID:28875035

Classification of crystal structure using a convolutional neural network.

PubMed

Park, Woon Bae; Chung, Jiyong; Jung, Jaeyoung; Sohn, Keemin; Singh, Satendra Pal; Pyo, Myoungho; Shin, Namsoo; Sohn, Kee-Sun

2017-07-01

A deep machine-learning technique based on a convolutional neural network (CNN) is introduced. It has been used for the classification of powder X-ray diffraction (XRD) patterns in terms of crystal system, extinction group and space group. About 150 000 powder XRD patterns were collected and used as input for the CNN with no handcrafted engineering involved, and thereby an appropriate CNN architecture was obtained that allowed determination of the crystal system, extinction group and space group. In sharp contrast with the traditional use of powder XRD pattern analysis, the CNN never treats powder XRD patterns as a deconvoluted and discrete peak position or as intensity data, but instead the XRD patterns are regarded as nothing but a pattern similar to a picture. The CNN interprets features that humans cannot recognize in a powder XRD pattern. As a result, accuracy levels of 81.14, 83.83 and 94.99% were achieved for the space-group, extinction-group and crystal-system classifications, respectively. The well trained CNN was then used for symmetry identification of unknown novel inorganic compounds.

Barriers and facilitators of sports in Dutch Paralympic athletes: An explorative study.

PubMed

Jaarsma, E A; Geertzen, J H B; de Jong, R; Dijkstra, P U; Dekker, R

2014-10-01

The purpose of this study was to gain insight in barriers and facilitators of sports in paralympic athletes. An online questionnaire was distributed through the Netherlands Olympic Committee and National Sports Confederation to determine personal and environmental barriers and facilitators of sports participation. The International Classification of Functioning, Disability and Health model and theory of planned behavior were used to respectively categorize the results in environmental and personal factors, and attitude, subjective norm and perceived behavioral control. Seventy-six Dutch Paralympic athletes completed the questionnaire (51% response rate). Barriers and facilitators experienced by ambulant and wheelchair athletes were compared. Most frequently mentioned personal barrier was dependency of others (22%), while most frequently mentioned environmental barrier was lack of sports facilities (30%). Wheelchair athletes mentioned more barriers (median = 3, interquartile range: 0.5-6), than ambulant athletes (median = 1.0,interquartile range:0.0-3.0, P = 0.023). One-third of the athletes did not experience any barriers. Most frequently mentioned personal facilitators to initiate sports participation were fun (78%), health (61%), and competition (53%). Most frequently mentioned environmental facilitator was social support (40%). This study indicated that barriers of sport were mostly environmental, while facilitators were usually personal factors. Attitude and subjective norm were considered the most important components for intention to participation in sports. The facilitators outweighed the barriers and kept the athletes being active in sports. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Classification and Lineage Tracing of SH2 Domains Throughout Eukaryotes.

PubMed

Liu, Bernard A

2017-01-01

Today there exists a rapidly expanding number of sequenced genomes. Cataloging protein interaction domains such as the Src Homology 2 (SH2) domain across these various genomes can be accomplished with ease due to existing algorithms and predictions models. An evolutionary analysis of SH2 domains provides a step towards understanding how SH2 proteins integrated with existing signaling networks to position phosphotyrosine signaling as a crucial driver of robust cellular communication networks in metazoans. However organizing and tracing SH2 domain across organisms and understanding their evolutionary trajectory remains a challenge. This chapter describes several methodologies towards analyzing the evolutionary trajectory of SH2 domains including a global SH2 domain classification system, which facilitates annotation of new SH2 sequences essential for tracing the lineage of SH2 domains throughout eukaryote evolution. This classification utilizes a combination of sequence homology, protein domain architecture and the boundary positions between introns and exons within the SH2 domain or genes encoding these domains. Discrete SH2 families can then be traced across various genomes to provide insight into its origins. Furthermore, additional methods for examining potential mechanisms for divergence of SH2 domains from structural changes to alterations in the protein domain content and genome duplication will be discussed. Therefore a better understanding of SH2 domain evolution may enhance our insight into the emergence of phosphotyrosine signaling and the expansion of protein interaction domains.

Columba: an integrated database of proteins, structures, and annotations.

PubMed

Trissl, Silke; Rother, Kristian; Müller, Heiko; Steinke, Thomas; Koch, Ina; Preissner, Robert; Frömmel, Cornelius; Leser, Ulf

2005-03-31

Structural and functional research often requires the computation of sets of protein structures based on certain properties of the proteins, such as sequence features, fold classification, or functional annotation. Compiling such sets using current web resources is tedious because the necessary data are spread over many different databases. To facilitate this task, we have created COLUMBA, an integrated database of annotations of protein structures. COLUMBA currently integrates twelve different databases, including PDB, KEGG, Swiss-Prot, CATH, SCOP, the Gene Ontology, and ENZYME. The database can be searched using either keyword search or data source-specific web forms. Users can thus quickly select and download PDB entries that, for instance, participate in a particular pathway, are classified as containing a certain CATH architecture, are annotated as having a certain molecular function in the Gene Ontology, and whose structures have a resolution under a defined threshold. The results of queries are provided in both machine-readable extensible markup language and human-readable format. The structures themselves can be viewed interactively on the web. The COLUMBA database facilitates the creation of protein structure data sets for many structure-based studies. It allows to combine queries on a number of structure-related databases not covered by other projects at present. Thus, information on both many and few protein structures can be used efficiently. The web interface for COLUMBA is available at http://www.columba-db.de.

A novel method to guide classification of para swimmers with limb deficiency.

PubMed

Hogarth, Luke; Payton, Carl; Van de Vliet, Peter; Connick, Mark; Burkett, Brendan

2018-05-30

The International Paralympic Committee has directed International Federations that govern Para sports to develop evidence-based classification systems. This study defined the impact of limb deficiency impairment on 100 m freestyle performance to guide an evidence-based classification system in Para Swimming, which will be implemented following the 2020 Tokyo Paralympic games. Impairment data and competitive race performances of 90 international swimmers with limb deficiency were collected. Ensemble partial least squares regression established the relationship between relative limb length measures and competitive 100 m freestyle performance. The model explained 80% of the variance in 100 m freestyle performance, and found hand length and forearm length to be the most important predictors of performance. Based on the results of this model, Para swimmers were clustered into four-, five-, six- and seven-class structures using nonparametric kernel density estimations. The validity of these classification structures, and effectiveness against the current classification system, were examined by establishing within-class variations in 100 m freestyle performance and differences between adjacent classes. The derived classification structures were found to be more effective than current classification based on these criteria. This study provides a novel method that can be used to improve the objectivity and transparency of decision-making in Para sport classification. Expert consensus from experienced coaches, Para swimmers, classifiers and sport science and medicine personnel will benefit the translation of these findings into a revised classification system that is accepted by the Para swimming community. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Random forest classification of large volume structures for visuo-haptic rendering in CT images

NASA Astrophysics Data System (ADS)

Mastmeyer, Andre; Fortmeier, Dirk; Handels, Heinz

2016-03-01

For patient-specific voxel-based visuo-haptic rendering of CT scans of the liver area, the fully automatic segmentation of large volume structures such as skin, soft tissue, lungs and intestine (risk structures) is important. Using a machine learning based approach, several existing segmentations from 10 segmented gold-standard patients are learned by random decision forests individually and collectively. The core of this paper is feature selection and the application of the learned classifiers to a new patient data set. In a leave-some-out cross-validation, the obtained full volume segmentations are compared to the gold-standard segmentations of the untrained patients. The proposed classifiers use a multi-dimensional feature space to estimate the hidden truth, instead of relying on clinical standard threshold and connectivity based methods. The result of our efficient whole-body section classification are multi-label maps with the considered tissues. For visuo-haptic simulation, other small volume structures would have to be segmented additionally. We also take a look into these structures (liver vessels). For an experimental leave-some-out study consisting of 10 patients, the proposed method performs much more efficiently compared to state of the art methods. In two variants of leave-some-out experiments we obtain best mean DICE ratios of 0.79, 0.97, 0.63 and 0.83 for skin, soft tissue, hard bone and risk structures. Liver structures are segmented with DICE 0.93 for the liver, 0.43 for blood vessels and 0.39 for bile vessels.

Detailed Quantitative Classifications of Galaxy Morphology

NASA Astrophysics Data System (ADS)

Nair, Preethi

2018-01-01

Understanding the physical processes responsible for the growth of galaxies is one of the key challenges in extragalactic astronomy. The assembly history of a galaxy is imprinted in a galaxy’s detailed morphology. The bulge-to-total ratio of galaxies, the presence or absence of bars, rings, spiral arms, tidal tails etc, all have implications for the past merger, star formation, and feedback history of a galaxy. However, current quantitative galaxy classification schemes are only useful for broad binning. They cannot classify or exploit the wide variety of galaxy structures seen in nature. Therefore, comparisons of observations with theoretical predictions of secular structure formation have only been conducted on small samples of visually classified galaxies. However large samples are needed to disentangle the complex physical processes of galaxy formation. With the advent of large surveys, like the Sloan Digital Sky Survey (SDSS) and the upcoming Large Synoptic Survey Telescope (LSST) and WFIRST, the problem of statistics will be resolved. However, the need for a robust quantitative classification scheme will still remain. Here I will present early results on promising machine learning algorithms that are providing detailed classifications, identifying bars, rings, multi-armed spiral galaxies, and Hubble type.

New Features for Neuron Classification.

PubMed

Hernández-Pérez, Leonardo A; Delgado-Castillo, Duniel; Martín-Pérez, Rainer; Orozco-Morales, Rubén; Lorenzo-Ginori, Juan V

2018-04-28

This paper addresses the problem of obtaining new neuron features capable of improving results of neuron classification. Most studies on neuron classification using morphological features have been based on Euclidean geometry. Here three one-dimensional (1D) time series are derived from the three-dimensional (3D) structure of neuron instead, and afterwards a spatial time series is finally constructed from which the features are calculated. Digitally reconstructed neurons were separated into control and pathological sets, which are related to three categories of alterations caused by epilepsy, Alzheimer's disease (long and local projections), and ischemia. These neuron sets were then subjected to supervised classification and the results were compared considering three sets of features: morphological, features obtained from the time series and a combination of both. The best results were obtained using features from the time series, which outperformed the classification using only morphological features, showing higher correct classification rates with differences of 5.15, 3.75, 5.33% for epilepsy and Alzheimer's disease (long and local projections) respectively. The morphological features were better for the ischemia set with a difference of 3.05%. Features like variance, Spearman auto-correlation, partial auto-correlation, mutual information, local minima and maxima, all related to the time series, exhibited the best performance. Also we compared different evaluators, among which ReliefF was the best ranked.

Constructal Law of Vascular Trees for Facilitation of Flow

PubMed Central

Razavi, Mohammad S.; Shirani, Ebrahim; Salimpour, Mohammad Reza; Kassab, Ghassan S.

2014-01-01

Diverse tree structures such as blood vessels, branches of a tree and river basins exist in nature. The constructal law states that the evolution of flow structures in nature has a tendency to facilitate flow. This study suggests a theoretical basis for evaluation of flow facilitation within vascular structure from the perspective of evolution. A novel evolution parameter (Ev) is proposed to quantify the flow capacity of vascular structures. Ev is defined as the ratio of the flow conductance of an evolving structure (configuration with imperfection) to the flow conductance of structure with least imperfection. Attaining higher Ev enables the structure to expedite flow circulation with less energy dissipation. For both Newtonian and non-Newtonian fluids, the evolution parameter was developed as a function of geometrical shape factors in laminar and turbulent fully developed flows. It was found that the non-Newtonian or Newtonian behavior of fluid as well as flow behavior such as laminar or turbulent behavior affects the evolution parameter. Using measured vascular morphometric data of various organs and species, the evolution parameter was calculated. The evolution parameter of the tree structures in biological systems was found to be in the range of 0.95 to 1. The conclusion is that various organs in various species have high capacity to facilitate flow within their respective vascular structures. PMID:25551617

Three-Way Analysis of Spectrospatial Electromyography Data: Classification and Interpretation

PubMed Central

Kauppi, Jukka-Pekka; Hahne, Janne; Müller, Klaus-Robert; Hyvärinen, Aapo

2015-01-01

Classifying multivariate electromyography (EMG) data is an important problem in prosthesis control as well as in neurophysiological studies and diagnosis. With modern high-density EMG sensor technology, it is possible to capture the rich spectrospatial structure of the myoelectric activity. We hypothesize that multi-way machine learning methods can efficiently utilize this structure in classification as well as reveal interesting patterns in it. To this end, we investigate the suitability of existing three-way classification methods to EMG-based hand movement classification in spectrospatial domain, as well as extend these methods by sparsification and regularization. We propose to use Fourier-domain independent component analysis as preprocessing to improve classification and interpretability of the results. In high-density EMG experiments on hand movements across 10 subjects, three-way classification yielded higher average performance compared with state-of-the art classification based on temporal features, suggesting that the three-way analysis approach can efficiently utilize detailed spectrospatial information of high-density EMG. Phase and amplitude patterns of features selected by the classifier in finger-movement data were found to be consistent with known physiology. Thus, our approach can accurately resolve hand and finger movements on the basis of detailed spectrospatial information, and at the same time allows for physiological interpretation of the results. PMID:26039100

Towards an International Classification for Patient Safety: the conceptual framework

PubMed Central

Sherman, Heather; Castro, Gerard; Fletcher, Martin; Hatlie, Martin; Hibbert, Peter; Jakob, Robert; Koss, Richard; Lewalle, Pierre; Loeb, Jerod; Perneger, Thomas; Runciman, William; Thomson, Richard; Van Der Schaaf, Tjerk; Virtanen, Martti

2009-01-01

Global advances in patient safety have been hampered by the lack of a uniform classification of patient safety concepts. This is a significant barrier to developing strategies to reduce risk, performing evidence-based research and evaluating existing healthcare policies relevant to patient safety. Since 2005, the World Health Organization's World Alliance for Patient Safety has undertaken the Project to Develop an International Classification for Patient Safety (ICPS) to devise a classification which transforms patient safety information collected from disparate systems into a common format to facilitate aggregation, analysis and learning across disciplines, borders and time. A drafting group, comprised of experts from the fields of patient safety, classification theory, health informatics, consumer/patient advocacy, law and medicine, identified and defined key patient safety concepts and developed an internationally agreed conceptual framework for the ICPS based upon existing patient safety classifications. The conceptual framework was iteratively improved through technical expert meetings and a two-stage web-based modified Delphi survey of over 250 international experts. This work culminated in a conceptual framework consisting of ten high level classes: incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors/hazards, organizational outcomes, detection, mitigating factors, ameliorating actions and actions taken to reduce risk. While the framework for the ICPS is in place, several challenges remain. Concepts need to be defined, guidance for using the classification needs to be provided, and further real-world testing needs to occur to progressively refine the ICPS to ensure it is fit for purpose. PMID:19147595

Large-scale classification of traffic signs under real-world conditions

NASA Astrophysics Data System (ADS)

Hazelhoff, Lykele; Creusen, Ivo; van de Wouw, Dennis; de With, Peter H. N.

2012-02-01

Traffic sign inventories are important to governmental agencies as they facilitate evaluation of traffic sign locations and are beneficial for road and sign maintenance. These inventories can be created (semi-)automatically based on street-level panoramic images. In these images, object detection is employed to detect the signs in each image, followed by a classification stage to retrieve the specific sign type. Classification of traffic signs is a complicated matter, since sign types are very similar with only minor differences within the sign, a high number of different signs is involved and multiple distortions occur, including variations in capturing conditions, occlusions, viewpoints and sign deformations. Therefore, we propose a method for robust classification of traffic signs, based on the Bag of Words approach for generic object classification. We extend the approach with a flexible, modular codebook to model the specific features of each sign type independently, in order to emphasize at the inter-sign differences instead of the parts common for all sign types. Additionally, this allows us to model and label the present false detections. Furthermore, analysis of the classification output provides the unreliable results. This classification system has been extensively tested for three different sign classes, covering 60 different sign types in total. These three data sets contain the sign detection results on street-level panoramic images, extracted from a country-wide database. The introduction of the modular codebook shows a significant improvement for all three sets, where the system is able to classify about 98% of the reliable results correctly.

A Novel Modulation Classification Approach Using Gabor Filter Network

PubMed Central

Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

2014-01-01

A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel. PMID:25126603

Iridescence of a Marine Bacterium and Classification of Prokaryotic Structural Colors

PubMed Central

Vukusic, Peter; Luke, Stephen

2012-01-01

Iridescence is a property of structural color that is occasionally encountered in higher eukaryotes but that has been poorly documented in the prokaryotic kingdom. In the present work, we describe a marine bacterium, identified as Cellulophaga lytica, isolated from the surface of an anemone, that exhibits bright green iridescent colonies under direct epi-illumination. This phenomenon has not previously been investigated in detail. In this study, color changes of C. lytica colonies were observed at various angles of direct illumination or observation. Its iridescent green appearance was dominant on various growth media. Red and violet colors were also discerned on colony edges. Remarkable C. lytica bacterial iridescence was revealed and characterized using high-resolution optical spectrometry. In addition to this, by culturing other bacterial strains to which various forms of faintly iridescent traits have previously been attributed, we identify four principal appearance characteristics of structural color in prokaryotes. A new general classification of bacterial iridescence is therefore proposed in this study. Furthermore, a specific separate class is described for iridescent C. lytica strains because they exhibit what is so far a unique intense glitter-like iridescence in reflection. C. lytica is the first prokaryote discovered to produce the same sort of intense iridescence under direct illumination as that associated with higher eukaryotes, like some insects and birds. Due to the nature of bacterial biology, cultivation, and ubiquity, this discovery may be of significant interest for both ecological and nanoscience endeavors. PMID:22267664

Searching bioremediation patents through Cooperative Patent Classification (CPC).

PubMed

Prasad, Rajendra

2016-03-01

Patent classification systems have traditionally evolved independently at each patent jurisdiction to classify patents handled by their examiners to be able to search previous patents while dealing with new patent applications. As patent databases maintained by them went online for free access to public as also for global search of prior art by examiners, the need arose for a common platform and uniform structure of patent databases. The diversity of different classification, however, posed problems of integrating and searching relevant patents across patent jurisdictions. To address this problem of comparability of data from different sources and searching patents, WIPO in the recent past developed what is known as International Patent Classification (IPC) system which most countries readily adopted to code their patents with IPC codes along with their own codes. The Cooperative Patent Classification (CPC) is the latest patent classification system based on IPC/European Classification (ECLA) system, developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) which is likely to become a global standard. This paper discusses this new classification system with reference to patents on bioremediation.

Automated noninvasive classification of renal cancer on multiphase CT

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

Linguraru, Marius George; Wang, Shijun; Shah, Furhawn

2011-10-15

Purpose: To explore the added value of the shape of renal lesions for classifying renal neoplasms. To investigate the potential of computer-aided analysis of contrast-enhanced computed-tomography (CT) to quantify and classify renal lesions. Methods: A computer-aided clinical tool based on adaptive level sets was employed to analyze 125 renal lesions from contrast-enhanced abdominal CT studies of 43 patients. There were 47 cysts and 78 neoplasms: 22 Von Hippel-Lindau (VHL), 16 Birt-Hogg-Dube (BHD), 19 hereditary papillary renal carcinomas (HPRC), and 21 hereditary leiomyomatosis and renal cell cancers (HLRCC). The technique quantified the three-dimensional size and enhancement of lesions. Intrapatient and interphasemore » registration facilitated the study of lesion serial enhancement. The histograms of curvature-related features were used to classify the lesion types. The areas under the curve (AUC) were calculated for receiver operating characteristic curves. Results: Tumors were robustly segmented with 0.80 overlap (0.98 correlation) between manual and semi-automated quantifications. The method further identified morphological discrepancies between the types of lesions. The classification based on lesion appearance, enhancement and morphology between cysts and cancers showed AUC = 0.98; for BHD + VHL (solid cancers) vs. HPRC + HLRCC AUC = 0.99; for VHL vs. BHD AUC = 0.82; and for HPRC vs. HLRCC AUC = 0.84. All semi-automated classifications were statistically significant (p < 0.05) and superior to the analyses based solely on serial enhancement. Conclusions: The computer-aided clinical tool allowed the accurate quantification of cystic, solid, and mixed renal tumors. Cancer types were classified into four categories using their shape and enhancement. Comprehensive imaging biomarkers of renal neoplasms on abdominal CT may facilitate their noninvasive classification, guide clinical management, and monitor responses to drugs or interventions.« less

Classification of trabeculae into three-dimensional rodlike and platelike structures via local inertial anisotropy.

PubMed

Vasilić, Branimir; Rajapakse, Chamith S; Wehrli, Felix W

2009-07-01

Trabecular bone microarchitecture is a significant determinant of the bone's mechanical properties and is thus of major clinical relevance in predicting fracture risk. The three-dimensional nature of trabecular bone is characterized by parameters describing scale, topology, and orientation of structural elements. However, none of the current methods calculates all three types of parameters simultaneously and in three dimensions. Here the authors present a method that produces a continuous classification of voxels as belonging to platelike or rodlike structures that determines their orientation and estimates their thickness. The method, dubbed local inertial anisotropy (LIA), treats the image as a distribution of mass density and the orientation of trabeculae is determined from a locally calculated tensor of inertia at each voxel. The orientation entropies of rods and plates are introduced, which can provide new information about microarchitecture not captured by existing parameters. The robustness of the method to noise corruption, resolution reduction, and image rotation is demonstrated. Further, the method is compared with established three-dimensional parameters including the structure-model index and topological surface-to-curve ratio. Finally, the method is applied to data acquired in a previous translational pilot study showing that the trabecular bone of untreated hypogonadal men is less platelike than that of their eugonadal peers.

Classification of Instructional Programs: 2000 Edition.

ERIC Educational Resources Information Center

Education Statistics Quarterly, 2002

2002-01-01

Describes the methods, processes, and procedures used to develop the Classification of Instructional Programs 2000 (CIP:2000), the National Center for Education Statistics taxonomy of instructional programs, and provides information on the CIP's structure, contents, and organization. (SLD)

Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination.

PubMed

Sørensen, Lauge; Nielsen, Mads

2018-05-15

The International Challenge for Automated Prediction of MCI from MRI data offered independent, standardized comparison of machine learning algorithms for multi-class classification of normal control (NC), mild cognitive impairment (MCI), converting MCI (cMCI), and Alzheimer's disease (AD) using brain imaging and general cognition. We proposed to use an ensemble of support vector machines (SVMs) that combined bagging without replacement and feature selection. SVM is the most commonly used algorithm in multivariate classification of dementia, and it was therefore valuable to evaluate the potential benefit of ensembling this type of classifier. The ensemble SVM, using either a linear or a radial basis function (RBF) kernel, achieved multi-class classification accuracies of 55.6% and 55.0% in the challenge test set (60 NC, 60 MCI, 60 cMCI, 60 AD), resulting in a third place in the challenge. Similar feature subset sizes were obtained for both kernels, and the most frequently selected MRI features were the volumes of the two hippocampal subregions left presubiculum and right subiculum. Post-challenge analysis revealed that enforcing a minimum number of selected features and increasing the number of ensemble classifiers improved classification accuracy up to 59.1%. The ensemble SVM outperformed single SVM classifications consistently in the challenge test set. Ensemble methods using bagging and feature selection can improve the performance of the commonly applied SVM classifier in dementia classification. This resulted in competitive classification accuracies in the International Challenge for Automated Prediction of MCI from MRI data. Copyright © 2018 Elsevier B.V. All rights reserved.

Texture operator for snow particle classification into snowflake and graupel

NASA Astrophysics Data System (ADS)

Nurzyńska, Karolina; Kubo, Mamoru; Muramoto, Ken-ichiro

2012-11-01

In order to improve the estimation of precipitation, the coefficients of Z-R relation should be determined for each snow type. Therefore, it is necessary to identify the type of falling snow. Consequently, this research addresses a problem of snow particle classification into snowflake and graupel in an automatic manner (as these types are the most common in the study region). Having correctly classified precipitation events, it is believed that it will be possible to estimate the related parameters accurately. The automatic classification system presented here describes the images with texture operators. Some of them are well-known from the literature: first order features, co-occurrence matrix, grey-tone difference matrix, run length matrix, and local binary pattern, but also a novel approach to design simple local statistic operators is introduced. In this work the following texture operators are defined: mean histogram, min-max histogram, and mean-variance histogram. Moreover, building a feature vector, which is based on the structure created in many from mentioned algorithms is also suggested. For classification, the k-nearest neighbourhood classifier was applied. The results showed that it is possible to achieve correct classification accuracy above 80% by most of the techniques. The best result of 86.06%, was achieved for operator built from a structure achieved in the middle stage of the co-occurrence matrix calculation. Next, it was noticed that describing an image with two texture operators does not improve the classification results considerably. In the best case the correct classification efficiency was 87.89% for a pair of texture operators created from local binary pattern and structure build in a middle stage of grey-tone difference matrix calculation. This also suggests that the information gathered by each texture operator is redundant. Therefore, the principal component analysis was applied in order to remove the unnecessary information and

A Visual mining based framework for classification accuracy estimation

NASA Astrophysics Data System (ADS)

Arun, Pattathal Vijayakumar

2013-12-01

Classification techniques have been widely used in different remote sensing applications and correct classification of mixed pixels is a tedious task. Traditional approaches adopt various statistical parameters, however does not facilitate effective visualisation. Data mining tools are proving very helpful in the classification process. We propose a visual mining based frame work for accuracy assessment of classification techniques using open source tools such as WEKA and PREFUSE. These tools in integration can provide an efficient approach for getting information about improvements in the classification accuracy and helps in refining training data set. We have illustrated framework for investigating the effects of various resampling methods on classification accuracy and found that bilinear (BL) is best suited for preserving radiometric characteristics. We have also investigated the optimal number of folds required for effective analysis of LISS-IV images. Techniki klasyfikacji są szeroko wykorzystywane w różnych aplikacjach teledetekcyjnych, w których poprawna klasyfikacja pikseli stanowi poważne wyzwanie. Podejście tradycyjne wykorzystujące różnego rodzaju parametry statystyczne nie zapewnia efektywnej wizualizacji. Wielce obiecujące wydaje się zastosowanie do klasyfikacji narzędzi do eksploracji danych. W artykule zaproponowano podejście bazujące na wizualnej analizie eksploracyjnej, wykorzystujące takie narzędzia typu open source jak WEKA i PREFUSE. Wymienione narzędzia ułatwiają korektę pół treningowych i efektywnie wspomagają poprawę dokładności klasyfikacji. Działanie metody sprawdzono wykorzystując wpływ różnych metod resampling na zachowanie dokładności radiometrycznej i uzyskując najlepsze wyniki dla metody bilinearnej (BL).

Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection.

PubMed

Jahandideh, Samad; Srinivasasainagendra, Vinodh; Zhi, Degui

2012-11-07

RNA-protein interaction plays an important role in various cellular processes, such as protein synthesis, gene regulation, post-transcriptional gene regulation, alternative splicing, and infections by RNA viruses. In this study, using Gene Ontology Annotated (GOA) and Structural Classification of Proteins (SCOP) databases an automatic procedure was designed to capture structurally solved RNA-binding protein domains in different subclasses. Subsequently, we applied tuned multi-class SVM (TMCSVM), Random Forest (RF), and multi-class ℓ1/ℓq-regularized logistic regression (MCRLR) for analysis and classifying RNA-binding protein domains based on a comprehensive set of sequence and structural features. In this study, we compared prediction accuracy of three different state-of-the-art predictor methods. From our results, TMCSVM outperforms the other methods and suggests the potential of TMCSVM as a useful tool for facilitating the multi-class prediction of RNA-binding protein domains. On the other hand, MCRLR by elucidating importance of features for their contribution in predictive accuracy of RNA-binding protein domains subclasses, helps us to provide some biological insights into the roles of sequences and structures in protein-RNA interactions.

Ensemble Sparse Classification of Alzheimer’s Disease

PubMed Central

Liu, Manhua; Zhang, Daoqiang; Shen, Dinggang

2012-01-01

The high-dimensional pattern classification methods, e.g., support vector machines (SVM), have been widely investigated for analysis of structural and functional brain images (such as magnetic resonance imaging (MRI)) to assist the diagnosis of Alzheimer’s disease (AD) including its prodromal stage, i.e., mild cognitive impairment (MCI). Most existing classification methods extract features from neuroimaging data and then construct a single classifier to perform classification. However, due to noise and small sample size of neuroimaging data, it is challenging to train only a global classifier that can be robust enough to achieve good classification performance. In this paper, instead of building a single global classifier, we propose a local patch-based subspace ensemble method which builds multiple individual classifiers based on different subsets of local patches and then combines them for more accurate and robust classification. Specifically, to capture the local spatial consistency, each brain image is partitioned into a number of local patches and a subset of patches is randomly selected from the patch pool to build a weak classifier. Here, the sparse representation-based classification (SRC) method, which has shown effective for classification of image data (e.g., face), is used to construct each weak classifier. Then, multiple weak classifiers are combined to make the final decision. We evaluate our method on 652 subjects (including 198 AD patients, 225 MCI and 229 normal controls) from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using MR images. The experimental results show that our method achieves an accuracy of 90.8% and an area under the ROC curve (AUC) of 94.86% for AD classification and an accuracy of 87.85% and an AUC of 92.90% for MCI classification, respectively, demonstrating a very promising performance of our method compared with the state-of-the-art methods for AD/MCI classification using MR images. PMID:22270352

Doppler Feature Based Classification of Wind Profiler Data

NASA Astrophysics Data System (ADS)

Sinha, Swati; Chandrasekhar Sarma, T. V.; Lourde. R, Mary

2017-01-01

Wind Profilers (WP) are coherent pulsed Doppler radars in UHF and VHF bands. They are used for vertical profiling of wind velocity and direction. This information is very useful for weather modeling, study of climatic patterns and weather prediction. Observations at different height and different wind velocities are possible by changing the operating parameters of WP. A set of Doppler power spectra is the standard form of WP data. Wind velocity, direction and wind velocity turbulence at different heights can be derived from it. Modern wind profilers operate for long duration and generate approximately 4 megabytes of data per hour. The radar data stream contains Doppler power spectra from different radar configurations with echoes from different atmospheric targets. In order to facilitate systematic study, this data needs to be segregated according the type of target. A reliable automated target classification technique is required to do this job. Classical techniques of radar target identification use pattern matching and minimization of mean squared error, Euclidean distance etc. These techniques are not effective for the classification of WP echoes, as these targets do not have well-defined signature in Doppler power spectra. This paper presents an effective target classification technique based on range-Doppler features.

An exploration of tutors' experiences of facilitating problem-based learning. Part 2--implications for the facilitation of problem based learning.

PubMed

Haith-Cooper, Melanie

2003-01-01

This paper is the second of two parts exploring a study that was undertaken to investigate the role of the tutor in facilitating problem-based learning (PBL). The first part focussed on the methodological underpinnings of the study. This paper aims to focus on the findings of the study and their implications for the facilitation of PBL. Six essential themes emerged from the findings that described the facilitation role. The tutors believed that their facilitation role was essentially structured around the decision of when to intervene and how to intervene in the PBL process. Modelling and non-verbal communication were seen as essential strategies for the facilitator. Underpinning these decisions was the need to trust in the philosophy of PBL. However, within many of the themes, there was a divergence of opinion as to how the role should actually be undertaken. Despite this, these findings have implications for the future role of PBL facilitators in Health Professional Education.

Towards Automatic Classification of Wikipedia Content

NASA Astrophysics Data System (ADS)

Szymański, Julian

Wikipedia - the Free Encyclopedia encounters the problem of proper classification of new articles everyday. The process of assignment of articles to categories is performed manually and it is a time consuming task. It requires knowledge about Wikipedia structure, which is beyond typical editor competence, which leads to human-caused mistakes - omitting or wrong assignments of articles to categories. The article presents application of SVM classifier for automatic classification of documents from The Free Encyclopedia. The classifier application has been tested while using two text representations: inter-documents connections (hyperlinks) and word content. The results of the performed experiments evaluated on hand crafted data show that the Wikipedia classification process can be partially automated. The proposed approach can be used for building a decision support system which suggests editors the best categories that fit new content entered to Wikipedia.

European validation of The Comprehensive International Classification of Functioning, Disability and Health Core Set for Osteoarthritis from the perspective of patients with osteoarthritis of the knee or hip.

PubMed

Weigl, Martin; Wild, Heike

2017-09-15

To validate the International Classification of Functioning, Disability and Health Comprehensive Core Set for Osteoarthritis from the patient perspective in Europe. This multicenter cross-sectional study involved 375 patients with knee or hip osteoarthritis. Trained health professionals completed the Comprehensive Core Set, and patients completed the Short-Form 36 questionnaire. Content validity was evaluated by calculating prevalences of impairments in body function and structures, limitations in activities and participation and environmental factors, which were either barriers or facilitators. Convergent construct validity was evaluated by correlating the International Classification of Functioning, Disability and Health categories with the Short-Form 36 Physical Component Score and the SF-36 Mental Component Score in a subgroup of 259 patients. The prevalences of all body function, body structure and activities and participation categories were >40%, >32% and >20%, respectively, and all environmental factors were relevant for >16% of patients. Few categories showed relevant differences between knee and hip osteoarthritis. All body function categories and all but two activities and participation categories showed significant correlations with the Physical Component Score. Body functions from the ICF chapter Mental Functions showed higher correlations with the Mental Component Score than with the Physical Component Score. This study supports the validity of the International Classification of Functioning, Disability and Health Comprehensive Core Set for Osteoarthritis. Implications for Rehabilitation Comprehensive International Classification of Functioning, Disability and Health Core Sets were developed as practical tools for application in multidisciplinary assessments. The validity of the Comprehensive International Classification of Functioning, Disability and Health Core Set for Osteoarthritis in this study supports its application in European patients with

Cluster analysis of novel isometric strength measures produces a valid and evidence-based classification structure for wheelchair track racing.

PubMed

Connick, Mark J; Beckman, Emma; Vanlandewijck, Yves; Malone, Laurie A; Blomqvist, Sven; Tweedy, Sean M

2017-11-25

The Para athletics wheelchair-racing classification system employs best practice to ensure that classes comprise athletes whose impairments cause a comparable degree of activity limitation. However, decision-making is largely subjective and scientific evidence which reduces this subjectivity is required. To evaluate whether isometric strength tests were valid for the purposes of classifying wheelchair racers and whether cluster analysis of the strength measures produced a valid classification structure. Thirty-two international level, male wheelchair racers from classes T51-54 completed six isometric strength tests evaluating elbow extensors, shoulder flexors, trunk flexors and forearm pronators and two wheelchair performance tests-Top-Speed (0-15 m) and Top-Speed (absolute). Strength tests significantly correlated with wheelchair performance were included in a cluster analysis and the validity of the resulting clusters was assessed. All six strength tests correlated with performance (r=0.54-0.88). Cluster analysis yielded four clusters with reasonable overall structure (mean silhouette coefficient=0.58) and large intercluster strength differences. Six athletes (19%) were allocated to clusters that did not align with their current class. While the mean wheelchair racing performance of the resulting clusters was unequivocally hierarchical, the mean performance of current classes was not, with no difference between current classes T53 and T54. Cluster analysis of isometric strength tests produced classes comprising athletes who experienced a similar degree of activity limitation. The strength tests reported can provide the basis for a new, more transparent, less subjective wheelchair racing classification system, pending replication of these findings in a larger, representative sample. This paper also provides guidance for development of evidence-based systems in other Para sports. © Article author(s) (or their employer(s) unless otherwise stated in the text of

A topological approach for protein classification

DOE PAGES

Cang, Zixuan; Mu, Lin; Wu, Kedi; ...

2015-11-04

Here, protein function and dynamics are closely related to its sequence and structure. However, prediction of protein function and dynamics from its sequence and structure is still a fundamental challenge in molecular biology. Protein classification, which is typically done through measuring the similarity between proteins based on protein sequence or physical information, serves as a crucial step toward the understanding of protein function and dynamics.

Automated spectral classification and the GAIA project

NASA Technical Reports Server (NTRS)

Lasala, Jerry; Kurtz, Michael J.

1995-01-01

Two dimensional spectral types for each of the stars observed in the global astrometric interferometer for astrophysics (GAIA) mission would provide additional information for the galactic structure and stellar evolution studies, as well as helping in the identification of unusual objects and populations. The classification of the large quantity generated spectra requires that automated techniques are implemented. Approaches for the automatic classification are reviewed, and a metric-distance method is discussed. In tests, the metric-distance method produced spectral types with mean errors comparable to those of human classifiers working at similar resolution. Data and equipment requirements for an automated classification survey, are discussed. A program of auxiliary observations is proposed to yield spectral types and radial velocities for the GAIA-observed stars.

Is overall similarity classification less effortful than single-dimension classification?

PubMed

Wills, Andy J; Milton, Fraser; Longmore, Christopher A; Hester, Sarah; Robinson, Jo

2013-01-01

It is sometimes argued that the implementation of an overall similarity classification is less effortful than the implementation of a single-dimension classification. In the current article, we argue that the evidence securely in support of this view is limited, and report additional evidence in support of the opposite proposition--overall similarity classification is more effortful than single-dimension classification. Using a match-to-standards procedure, Experiments 1A, 1B and 2 demonstrate that concurrent load reduces the prevalence of overall similarity classification, and that this effect is robust to changes in the concurrent load task employed, the level of time pressure experienced, and the short-term memory requirements of the classification task. Experiment 3 demonstrates that participants who produced overall similarity classifications from the outset have larger working memory capacities than those who produced single-dimension classifications initially, and Experiment 4 demonstrates that instructions to respond meticulously increase the prevalence of overall similarity classification.

Free classification of regional dialects of American English

PubMed Central

Clopper, Cynthia G.; Pisoni, David B.

2011-01-01

Recent studies have found that naïve listeners perform poorly in forced-choice dialect categorization tasks. However, the listeners' error patterns in these tasks reveal systematic confusions between phonologically similar dialects. In the present study, a free classification procedure was used to measure the perceptual similarity structure of regional dialect variation in the United States. In two experiments, participants listened to a set of short English sentences produced by male talkers only (Experiment 1) and by male and female talkers (Experiment 2). The listeners were instructed to group the talkers by regional dialect into as many groups as they wanted with as many talkers in each group as they wished. Multidimensional scaling analyses of the data revealed three primary dimensions of perceptual similarity (linguistic markedness, geography, and gender). In addition, a comparison of the results obtained from the free classification task to previous results using the same stimulus materials in six-alternative forced-choice categorization tasks revealed that response biases in the six-alternative task were reduced or eliminated in the free classification task. Thus, the results obtained with the free classification task in the current study provided further evidence that the underlying structure of perceptual dialect category representations reflects important linguistic and sociolinguistic factors. PMID:21423862

Free classification of regional dialects of American English.

PubMed

Clopper, Cynthia G; Pisoni, David B

2007-07-01

Recent studies have found that naïve listeners perform poorly in forced-choice dialect categorization tasks. However, the listeners' error patterns in these tasks reveal systematic confusions between phonologically similar dialects. In the present study, a free classification procedure was used to measure the perceptual similarity structure of regional dialect variation in the United States. In two experiments, participants listened to a set of short English sentences produced by male talkers only (Experiment 1) and by male and female talkers (Experiment 2). The listeners were instructed to group the talkers by regional dialect into as many groups as they wanted with as many talkers in each group as they wished. Multidimensional scaling analyses of the data revealed three primary dimensions of perceptual similarity (linguistic markedness, geography, and gender). In addition, a comparison of the results obtained from the free classification task to previous results using the same stimulus materials in six-alternative forced-choice categorization tasks revealed that response biases in the six-alternative task were reduced or eliminated in the free classification task. Thus, the results obtained with the free classification task in the current study provided further evidence that the underlying structure of perceptual dialect category representations reflects important linguistic and sociolinguistic factors.

Updated United Nations Framework Classification for reserves and resources of extractive industries

USGS Publications Warehouse

Ahlbrandt, T.S.; Blaise, J.R.; Blystad, P.; Kelter, D.; Gabrielyants, G.; Heiberg, S.; Martinez, A.; Ross, J.G.; Slavov, S.; Subelj, A.; Young, E.D.

2004-01-01

The United Nations have studied how the oil and gas resource classification developed jointly by the SPE, the World Petroleum Congress (WPC) and the American Association of Petroleum Geologists (AAPG) could be harmonized with the United Nations Framework Classification (UNFC) for Solid Fuel and Mineral Resources (1). The United Nations has continued to build on this and other works, with support from many relevant international organizations, with the objective of updating the UNFC to apply to the extractive industries. The result is the United Nations Framework Classification for Energy and Mineral Resources (2) that this paper will present. Reserves and resources are categorized with respect to three sets of criteria: ??? Economic and commercial viability ??? Field project status and feasibility ??? The level of geologic knowledge The field project status criteria are readily recognized as the ones highlighted in the SPE/WPC/AAPG classification system of 2000. The geologic criteria absorb the rich traditions that form the primary basis for the Russian classification system, and the ones used to delimit, in part, proved reserves. Economic and commercial criteria facilitate the use of the classification in general, and reflect the commercial considerations used to delimit proved reserves in particular. The classification system will help to develop a common understanding of reserves and resources for all the extractive industries and will assist: ??? International and national resources management to secure supplies; ??? Industries' management of business processes to achieve efficiency in exploration and production; and ??? An appropriate basis for documenting the value of reserves and resources in financial statements.

The DSM-5: Classification and criteria changes.

PubMed

Regier, Darrel A; Kuhl, Emily A; Kupfer, David J

2013-06-01

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) marks the first significant revision of the publication since the DSM-IV in 1994. Changes to the DSM were largely informed by advancements in neuroscience, clinical and public health need, and identified problems with the classification system and criteria put forth in the DSM-IV. Much of the decision-making was also driven by a desire to ensure better alignment with the International Classification of Diseases and its upcoming 11th edition (ICD-11). In this paper, we describe select revisions in the DSM-5, with an emphasis on changes projected to have the greatest clinical impact and those that demonstrate efforts to enhance international compatibility, including integration of cultural context with diagnostic criteria and changes that facilitate DSM-ICD harmonization. It is anticipated that this collaborative spirit between the American Psychiatric Association (APA) and the World Health Organization (WHO) will continue as the DSM-5 is updated further, bringing the field of psychiatry even closer to a singular, cohesive nosology. Copyright © 2013 World Psychiatric Association.

Disturbance-mediated facilitation by an intertidal ecosystem engineer.

PubMed

Wright, Jeffrey T; Gribben, Paul E

2017-09-01

Ecosystem engineers facilitate communities by providing a structural habitat that reduces abiotic stress or predation pressure for associated species. However, disturbance may damage or move the engineer to a more stressful environment, possibly increasing the importance of facilitation for associated communities. In this study, we determined how disturbance to intertidal boulders (i.e., flipping) and the subsequent movement of a structural ecosystem engineer, the tube-forming serpulid worm Galeolaria caespitosa, from the bottom (natural state, low abiotic stress) to the top (disturbed state, high abiotic stress) surface of boulders influenced the importance of facilitation for intertidal communities across two intertidal zones. Theory predicts stronger relative facilitation should occur in the harsher environments of the top of boulders and the high intertidal zone. To test this prediction, we experimentally positioned boulders with the serpulids either face up or face down for 12 months in low and high zones in an intertidal boulder field. There were very different communities associated with the different boulders and serpulids had the strongest facilitative effects on the more stressful top surface of boulders with approximately double the species richness compared to boulders lacking serpulids. Moreover, within the serpulid matrix itself there was also approximately double the species richness (both zones) and abundance (high zone only) of small invertebrates on the top of boulders compared to the bottom. The high relative facilitation on the top of boulders reflected a large reduction in temperature by the serpulid matrix on that surface (up to 10°C) highlighting a key role for modification of the abiotic environment in determining the community-wide facilitation. This study has demonstrated that disturbance and subsequent movement of an ecosystem engineer to a more stressful environment increased the importance of facilitation and allowed species to

Classification of lymphoid neoplasms: the microscope as a tool for disease discovery

PubMed Central

Harris, Nancy Lee; Stein, Harald; Isaacson, Peter G.

2008-01-01

In the past 50 years, we have witnessed explosive growth in the understanding of normal and neoplastic lymphoid cells. B-cell, T-cell, and natural killer (NK)–cell neoplasms in many respects recapitulate normal stages of lymphoid cell differentiation and function, so that they can be to some extent classified according to the corresponding normal stage. Likewise, the molecular mechanisms involved the pathogenesis of lymphomas and lymphoid leukemias are often based on the physiology of the lymphoid cells, capitalizing on deregulated normal physiology by harnessing the promoters of genes essential for lymphocyte function. The clinical manifestations of lymphomas likewise reflect the normal function of lymphoid cells in vivo. The multiparameter approach to classification adopted by the World Health Organization (WHO) classification has been validated in international studies as being highly reproducible, and enhancing the interpretation of clinical and translational studies. In addition, accurate and precise classification of disease entities facilitates the discovery of the molecular basis of lymphoid neoplasms in the basic science laboratory. PMID:19029456

Geometry-based ensembles: toward a structural characterization of the classification boundary.

PubMed

Pujol, Oriol; Masip, David

2009-06-01

This paper introduces a novel binary discriminative learning technique based on the approximation of the nonlinear decision boundary by a piecewise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points-points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and nonlinear behavior is obtained. The simplicity of the method allows its extension to cope with some of today's machine learning challenges, such as online learning, large-scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database, comparing with several state-of-the-art classification techniques. Finally, we apply our technique in online and large-scale scenarios and in six real-life computer vision and pattern recognition problems: gender recognition based on face images, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease myocardial damage severity detection, old musical scores clef classification, and action recognition using 3D accelerometer data from a wearable device. The results are promising and this paper opens a line of research that deserves further attention.

Use of Neuroanatomical Pattern Classification to Identify Subjects in At-Risk Mental States of Psychosis and Predict Disease Transition

PubMed Central

Koutsouleris, Nikolaos; Meisenzahl, Eva M.; Davatzikos, Christos; Bottlender, Ronald; Frodl, Thomas; Scheuerecker, Johanna; Schmitt, Gisela; Zetzsche, Thomas; Decker, Petra; Reiser, Maximilian; Möller, Hans-Jürgen; Gaser, Christian

2014-01-01

Context Identification of individuals at high risk of developing psychosis has relied on prodromal symptomatology. Recently, machine learning algorithms have been successfully used for magnetic resonance imaging–based diagnostic classification of neuropsychiatric patient populations. Objective To determine whether multivariate neuroanatomical pattern classification facilitates identification of individuals in different at-risk mental states (ARMS) of psychosis and enables the prediction of disease transition at the individual level. Design Multivariate neuroanatomical pattern classification was performed on the structural magnetic resonance imaging data of individuals in early or late ARMS vs healthy controls (HCs). The predictive power of the method was then evaluated by categorizing the baseline imaging data of individuals with transition to psychosis vs those without transition vs HCs after 4 years of clinical follow-up. Classification generalizability was estimated by cross-validation and by categorizing an independent cohort of 45 new HCs. Setting Departments of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany. Participants The first classification analysis included 20 early and 25 late at-risk individuals and 25 matched HCs. The second analysis consisted of 15 individuals with transition, 18 without transition, and 17 matched HCs. Main Outcome Measures Specificity, sensitivity, and accuracy of classification. Results The 3-group, cross-validated classification accuracies of the first analysis were 86% (HCs vs the rest), 91% (early at-risk individuals vs the rest), and 86% (late at-risk individuals vs the rest). The accuracies in the second analysis were 90% (HCs vs the rest), 88% (individuals with transition vs the rest), and 86% (individuals without transition vs the rest). Independent HCs were correctly classified in 96% (first analysis) and 93% (second analysis) of cases. Conclusions Different ARMSs and their clinical outcomes

Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries

PubMed Central

Md Noor, Siti Salwa; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-01-01

In our preliminary study, the reflectance signatures obtained from hyperspectral imaging (HSI) of normal and abnormal corneal epithelium tissues of porcine show similar morphology with subtle differences. Here we present image enhancement algorithms that can be used to improve the interpretability of data into clinically relevant information to facilitate diagnostics. A total of 25 corneal epithelium images without the application of eye staining were used. Three image feature extraction approaches were applied for image classification: (i) image feature classification from histogram using a support vector machine with a Gaussian radial basis function (SVM-GRBF); (ii) physical image feature classification using deep-learning Convolutional Neural Networks (CNNs) only; and (iii) the combined classification of CNNs and SVM-Linear. The performance results indicate that our chosen image features from the histogram and length-scale parameter were able to classify with up to 100% accuracy; particularly, at CNNs and CNNs-SVM, by employing 80% of the data sample for training and 20% for testing. Thus, in the assessment of corneal epithelium injuries, HSI has high potential as a method that could surpass current technologies regarding speed, objectivity, and reliability. PMID:29144388

Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries.

PubMed

Noor, Siti Salwa Md; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-11-16

In our preliminary study, the reflectance signatures obtained from hyperspectral imaging (HSI) of normal and abnormal corneal epithelium tissues of porcine show similar morphology with subtle differences. Here we present image enhancement algorithms that can be used to improve the interpretability of data into clinically relevant information to facilitate diagnostics. A total of 25 corneal epithelium images without the application of eye staining were used. Three image feature extraction approaches were applied for image classification: (i) image feature classification from histogram using a support vector machine with a Gaussian radial basis function (SVM-GRBF); (ii) physical image feature classification using deep-learning Convolutional Neural Networks (CNNs) only; and (iii) the combined classification of CNNs and SVM-Linear. The performance results indicate that our chosen image features from the histogram and length-scale parameter were able to classify with up to 100% accuracy; particularly, at CNNs and CNNs-SVM, by employing 80% of the data sample for training and 20% for testing. Thus, in the assessment of corneal epithelium injuries, HSI has high potential as a method that could surpass current technologies regarding speed, objectivity, and reliability.

LiDAR point classification based on sparse representation

NASA Astrophysics Data System (ADS)

Li, Nan; Pfeifer, Norbert; Liu, Chun

2017-04-01

In order to combine the initial spatial structure and features of LiDAR data for accurate classification. The LiDAR data is represented as a 4-order tensor. Sparse representation for classification(SRC) method is used for LiDAR tensor classification. It turns out SRC need only a few of training samples from each class, meanwhile can achieve good classification result. Multiple features are extracted from raw LiDAR points to generate a high-dimensional vector at each point. Then the LiDAR tensor is built by the spatial distribution and feature vectors of the point neighborhood. The entries of LiDAR tensor are accessed via four indexes. Each index is called mode: three spatial modes in direction X ,Y ,Z and one feature mode. Sparse representation for classification(SRC) method is proposed in this paper. The sparsity algorithm is to find the best represent the test sample by sparse linear combination of training samples from a dictionary. To explore the sparsity of LiDAR tensor, the tucker decomposition is used. It decomposes a tensor into a core tensor multiplied by a matrix along each mode. Those matrices could be considered as the principal components in each mode. The entries of core tensor show the level of interaction between the different components. Therefore, the LiDAR tensor can be approximately represented by a sparse tensor multiplied by a matrix selected from a dictionary along each mode. The matrices decomposed from training samples are arranged as initial elements in the dictionary. By dictionary learning, a reconstructive and discriminative structure dictionary along each mode is built. The overall structure dictionary composes of class-specified sub-dictionaries. Then the sparse core tensor is calculated by tensor OMP(Orthogonal Matching Pursuit) method based on dictionaries along each mode. It is expected that original tensor should be well recovered by sub-dictionary associated with relevant class, while entries in the sparse tensor associated with

Classification in Australia.

ERIC Educational Resources Information Center

McKinlay, John

Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms.

PubMed

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

2018-05-01

In this paper, two novel feature extraction methods, using neighborhood structural similarity (NSS), are proposed for the characterization of mammographic masses as benign or malignant. Since gray-level distribution of pixels is different in benign and malignant masses, more regular and homogeneous patterns are visible in benign masses compared to malignant masses; the proposed method exploits the similarity between neighboring regions of masses by designing two new features, namely, NSS-I and NSS-II, which capture global similarity at different scales. Complementary to these global features, uniform local binary patterns are computed to enhance the classification efficiency by combining with the proposed features. The performance of the features are evaluated using the images from the mini-mammographic image analysis society (mini-MIAS) and digital database for screening mammography (DDSM) databases, where a tenfold cross-validation technique is incorporated with Fisher linear discriminant analysis, after selecting the optimal set of features using stepwise logistic regression method. The best area under the receiver operating characteristic curve of 0.98 with an accuracy of is achieved with the mini-MIAS database, while the same for the DDSM database is 0.93 with accuracy .

Recursive heuristic classification

NASA Technical Reports Server (NTRS)

Wilkins, David C.

1994-01-01

The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

Analysis and application of classification methods of complex carbonate reservoirs

NASA Astrophysics Data System (ADS)

Li, Xiongyan; Qin, Ruibao; Ping, Haitao; Wei, Dan; Liu, Xiaomei

2018-06-01

There are abundant carbonate reservoirs from the Cenozoic to Mesozoic era in the Middle East. Due to variation in sedimentary environment and diagenetic process of carbonate reservoirs, several porosity types coexist in carbonate reservoirs. As a result, because of the complex lithologies and pore types as well as the impact of microfractures, the pore structure is very complicated. Therefore, it is difficult to accurately calculate the reservoir parameters. In order to accurately evaluate carbonate reservoirs, based on the pore structure evaluation of carbonate reservoirs, the classification methods of carbonate reservoirs are analyzed based on capillary pressure curves and flow units. Based on the capillary pressure curves, although the carbonate reservoirs can be classified, the relationship between porosity and permeability after classification is not ideal. On the basis of the flow units, the high-precision functional relationship between porosity and permeability after classification can be established. Therefore, the carbonate reservoirs can be quantitatively evaluated based on the classification of flow units. In the dolomite reservoirs, the average absolute error of calculated permeability decreases from 15.13 to 7.44 mD. Similarly, the average absolute error of calculated permeability of limestone reservoirs is reduced from 20.33 to 7.37 mD. Only by accurately characterizing pore structures and classifying reservoir types, reservoir parameters could be calculated accurately. Therefore, characterizing pore structures and classifying reservoir types are very important to accurate evaluation of complex carbonate reservoirs in the Middle East.

Structural health monitoring feature design by genetic programming

NASA Astrophysics Data System (ADS)

Harvey, Dustin Y.; Todd, Michael D.

2014-09-01

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems.

Classification versus inference learning contrasted with real-world categories.

PubMed

Jones, Erin L; Ross, Brian H

2011-07-01

Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.

ESPEN endorsed recommendations. Definition and classification of intestinal failure in adults.

PubMed

Pironi, Loris; Arends, Jann; Baxter, Janet; Bozzetti, Federico; Peláez, Rosa Burgos; Cuerda, Cristina; Forbes, Alastair; Gabe, Simon; Gillanders, Lyn; Holst, Mette; Jeppesen, Palle Bekker; Joly, Francisca; Kelly, Darlene; Klek, Stanislaw; Irtun, Øivind; Olde Damink, S W; Panisic, Marina; Rasmussen, Henrik Højgaard; Staun, Michael; Szczepanek, Kinga; Van Gossum, André; Wanten, Geert; Schneider, Stéphane Michel; Shaffer, Jon

2015-04-01

Intestinal failure (IF) is not included in the list of PubMed Mesh terms, as failure is the term describing a state of non functioning of other organs, and as such is not well recognized. No scientific society has yet devised a formal definition and classification of IF. The European Society for Clinical Nutrition and Metabolism guideline committee endorsed its "home artificial nutrition and chronic IF" and "acute IF" special interest groups to write recommendations on these issues. After a Medline Search, in December 2013, for "intestinal failure" and "review"[Publication Type], the project was developed using the Delphi round methodology. The final consensus was reached on March 2014, after 5 Delphi rounds and two live meetings. The recommendations comprise the definition of IF, a functional and a pathophysiological classification for both acute and chronic IF and a clinical classification of chronic IF. IF was defined as "the reduction of gut function below the minimum necessary for the absorption of macronutrients and/or water and electrolytes, such that intravenous supplementation is required to maintain health and/or growth". This formal definition and classification of IF, will facilitate communication and cooperation among professionals in clinical practice, organization and management, and research. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Classification with asymmetric label noise: Consistency and maximal denoising

DOE PAGES

Blanchard, Gilles; Flaska, Marek; Handy, Gregory; ...

2016-09-20

In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that the two classes are separable, that the label noise is independent of the true class label, or that the noise proportions for each class are known. In this work, we give conditions that are necessary and sufficient for the true class-conditional distributions to be identifiable. These conditions are weaker than those analyzed previously, and allow for the classes to be nonseparable and the noise levels to be asymmetric and unknown. The conditions essentially state that amore » majority of the observed labels are correct and that the true class-conditional distributions are “mutually irreducible,” a concept we introduce that limits the similarity of the two distributions. For any label noise problem, there is a unique pair of true class-conditional distributions satisfying the proposed conditions, and we argue that this pair corresponds in a certain sense to maximal denoising of the observed distributions. Our results are facilitated by a connection to “mixture proportion estimation,” which is the problem of estimating the maximal proportion of one distribution that is present in another. We establish a novel rate of convergence result for mixture proportion estimation, and apply this to obtain consistency of a discrimination rule based on surrogate loss minimization. Experimental results on benchmark data and a nuclear particle classification problem demonstrate the efficacy of our approach. MSC 2010 subject classifications: Primary 62H30; secondary 68T10. Keywords and phrases: Classification, label noise, mixture proportion estimation, surrogate loss, consistency.« less

Classification with asymmetric label noise: Consistency and maximal denoising

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

Blanchard, Gilles; Flaska, Marek; Handy, Gregory

In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that the two classes are separable, that the label noise is independent of the true class label, or that the noise proportions for each class are known. In this work, we give conditions that are necessary and sufficient for the true class-conditional distributions to be identifiable. These conditions are weaker than those analyzed previously, and allow for the classes to be nonseparable and the noise levels to be asymmetric and unknown. The conditions essentially state that amore » majority of the observed labels are correct and that the true class-conditional distributions are “mutually irreducible,” a concept we introduce that limits the similarity of the two distributions. For any label noise problem, there is a unique pair of true class-conditional distributions satisfying the proposed conditions, and we argue that this pair corresponds in a certain sense to maximal denoising of the observed distributions. Our results are facilitated by a connection to “mixture proportion estimation,” which is the problem of estimating the maximal proportion of one distribution that is present in another. We establish a novel rate of convergence result for mixture proportion estimation, and apply this to obtain consistency of a discrimination rule based on surrogate loss minimization. Experimental results on benchmark data and a nuclear particle classification problem demonstrate the efficacy of our approach. MSC 2010 subject classifications: Primary 62H30; secondary 68T10. Keywords and phrases: Classification, label noise, mixture proportion estimation, surrogate loss, consistency.« less

Manifold regularized multitask learning for semi-supervised multilabel image classification.

PubMed

Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

2013-02-01

It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

Factors influencing speech and language outcomes of children with early identified severe/profound hearing loss: Clinician-identified facilitators and barriers.

PubMed

Fulcher, Anne Nivelles; Purcell, Alison; Baker, Elise; Munro, Natalie

2015-06-01

Early identification of severe/profound childhood hearing loss (HL) gives these children access to hearing devices and early intervention to facilitate improved speech and language outcomes. Predicting which infants will go on to achieve such outcomes remains difficult. This study describes clinician identified malleable and non-malleable factors that may influence speech and language outcomes for children with severe/profound HL. Semi-structured interviews were conducted with six experienced auditory verbal clinicians. A collective case study design was implemented. The interviews were transcribed and coded into themes using constant comparative analysis. Clinicians identified that, for children with severe/profound HL, early identification, early amplification and commencing auditory-verbal intervention under 6 months of age may facilitate child progress. Possible barriers were living in rural/remote areas, the clinicians' lack of experience and confidence in providing intervention for infants under age 6-months and belonging to a family with a culturally and linguistically diverse (CALD) background. The results indicate that multiple factors need to be considered by clinicians working with children with HL and their families to determine how each child functions within their own environment and personal contexts, consistent with the International Classification of Functioning, Disability and Health (ICF) framework. Such an approach is likely to empower clinicians to carefully balance potential barriers to, and facilitators of, optimal speech and language outcomes for all children with HL.

Classification of Dynamical Diffusion States in Single Molecule Tracking Microscopy

PubMed Central

Bosch, Peter J.; Kanger, Johannes S.; Subramaniam, Vinod

2014-01-01

Single molecule tracking of membrane proteins by fluorescence microscopy is a promising method to investigate dynamic processes in live cells. Translating the trajectories of proteins to biological implications, such as protein interactions, requires the classification of protein motion within the trajectories. Spatial information of protein motion may reveal where the protein interacts with cellular structures, because binding of proteins to such structures often alters their diffusion speed. For dynamic diffusion systems, we provide an analytical framework to determine in which diffusion state a molecule is residing during the course of its trajectory. We compare different methods for the quantification of motion to utilize this framework for the classification of two diffusion states (two populations with different diffusion speed). We found that a gyration quantification method and a Bayesian statistics-based method are the most accurate in diffusion-state classification for realistic experimentally obtained datasets, of which the gyration method is much less computationally demanding. After classification of the diffusion, the lifetime of the states can be determined, and images of the diffusion states can be reconstructed at high resolution. Simulations validate these applications. We apply the classification and its applications to experimental data to demonstrate the potential of this approach to obtain further insights into the dynamics of cell membrane proteins. PMID:25099798

The Transporter Classification Database: recent advances.

PubMed

Saier, Milton H; Yen, Ming Ren; Noto, Keith; Tamang, Dorjee G; Elkan, Charles

2009-01-01

The Transporter Classification Database (TCDB), freely accessible at http://www.tcdb.org, is a relational database containing sequence, structural, functional and evolutionary information about transport systems from a variety of living organisms, based on the International Union of Biochemistry and Molecular Biology-approved transporter classification (TC) system. It is a curated repository for factual information compiled largely from published references. It uses a functional/phylogenetic system of classification, and currently encompasses about 5000 representative transporters and putative transporters in more than 500 families. We here describe novel software designed to support and extend the usefulness of TCDB. Our recent efforts render it more user friendly, incorporate machine learning to input novel data in a semiautomatic fashion, and allow analyses that are more accurate and less time consuming. The availability of these tools has resulted in recognition of distant phylogenetic relationships and tremendous expansion of the information available to TCDB users.

The development of a classification schema for arts-based approaches to knowledge translation.

PubMed

Archibald, Mandy M; Caine, Vera; Scott, Shannon D

2014-10-01

Arts-based approaches to knowledge translation are emerging as powerful interprofessional strategies with potential to facilitate evidence uptake, communication, knowledge, attitude, and behavior change across healthcare provider and consumer groups. These strategies are in the early stages of development. To date, no classification system for arts-based knowledge translation exists, which limits development and understandings of effectiveness in evidence syntheses. We developed a classification schema of arts-based knowledge translation strategies based on two mechanisms by which these approaches function: (a) the degree of precision in key message delivery, and (b) the degree of end-user participation. We demonstrate how this classification is necessary to explore how context, time, and location shape arts-based knowledge translation strategies. Classifying arts-based knowledge translation strategies according to their core attributes extends understandings of the appropriateness of these approaches for various healthcare settings and provider groups. The classification schema developed may enhance understanding of how, where, and for whom arts-based knowledge translation approaches are effective, and enable theorizing of essential knowledge translation constructs, such as the influence of context, time, and location on utilization strategies. The classification schema developed may encourage systematic inquiry into the effectiveness of these approaches in diverse interprofessional contexts. © 2014 Sigma Theta Tau International.

Classification-based reasoning

NASA Technical Reports Server (NTRS)

Gomez, Fernando; Segami, Carlos

1991-01-01

A representation formalism for N-ary relations, quantification, and definition of concepts is described. Three types of conditions are associated with the concepts: (1) necessary and sufficient properties, (2) contingent properties, and (3) necessary properties. Also explained is how complex chains of inferences can be accomplished by representing existentially quantified sentences, and concepts denoted by restrictive relative clauses as classification hierarchies. The representation structures that make possible the inferences are explained first, followed by the reasoning algorithms that draw the inferences from the knowledge structures. All the ideas explained have been implemented and are part of the information retrieval component of a program called Snowy. An appendix contains a brief session with the program.

Automated hierarchical classification of protein domain subfamilies based on functionally-divergent residue signatures

PubMed Central

2012-01-01

Background The NCBI Conserved Domain Database (CDD) consists of a collection of multiple sequence alignments of protein domains that are at various stages of being manually curated into evolutionary hierarchies based on conserved and divergent sequence and structural features. These domain models are annotated to provide insights into the relationships between sequence, structure and function via web-based BLAST searches. Results Here we automate the generation of conserved domain (CD) hierarchies using a combination of heuristic and Markov chain Monte Carlo (MCMC) sampling procedures and starting from a (typically very large) multiple sequence alignment. This procedure relies on statistical criteria to define each hierarchy based on the conserved and divergent sequence patterns associated with protein functional-specialization. At the same time this facilitates the sequence and structural annotation of residues that are functionally important. These statistical criteria also provide a means to objectively assess the quality of CD hierarchies, a non-trivial task considering that the protein subgroups are often very distantly related—a situation in which standard phylogenetic methods can be unreliable. Our aim here is to automatically generate (typically sub-optimal) hierarchies that, based on statistical criteria and visual comparisons, are comparable to manually curated hierarchies; this serves as the first step toward the ultimate goal of obtaining optimal hierarchical classifications. A plot of runtimes for the most time-intensive (non-parallelizable) part of the algorithm indicates a nearly linear time complexity so that, even for the extremely large Rossmann fold protein class, results were obtained in about a day. Conclusions This approach automates the rapid creation of protein domain hierarchies and thus will eliminate one of the most time consuming aspects of conserved domain database curation. At the same time, it also facilitates protein domain

A Robust Geometric Model for Argument Classification

NASA Astrophysics Data System (ADS)

Giannone, Cristina; Croce, Danilo; Basili, Roberto; de Cao, Diego

Argument classification is the task of assigning semantic roles to syntactic structures in natural language sentences. Supervised learning techniques for frame semantics have been recently shown to benefit from rich sets of syntactic features. However argument classification is also highly dependent on the semantics of the involved lexicals. Empirical studies have shown that domain dependence of lexical information causes large performance drops in outside domain tests. In this paper a distributional approach is proposed to improve the robustness of the learning model against out-of-domain lexical phenomena.

Quantitative Survey and Structural Classification of Hydraulic Fracturing Chemicals Reported in Unconventional Gas Production.

PubMed

Elsner, Martin; Hoelzer, Kathrin

2016-04-05

Much interest is directed at the chemical structure of hydraulic fracturing (HF) additives in unconventional gas exploitation. To bridge the gap between existing alphabetical disclosures by function/CAS number and emerging scientific contributions on fate and toxicity, we review the structural properties which motivate HF applications, and which determine environmental fate and toxicity. Our quantitative overview relied on voluntary U.S. disclosures evaluated from the FracFocus registry by different sources and on a House of Representatives ("Waxman") list. Out of over 1000 reported substances, classification by chemistry yielded succinct subsets able to illustrate the rationale of their use, and physicochemical properties relevant for environmental fate, toxicity and chemical analysis. While many substances were nontoxic, frequent disclosures also included notorious groundwater contaminants like petroleum hydrocarbons (solvents), precursors of endocrine disruptors like nonylphenols (nonemulsifiers), toxic propargyl alcohol (corrosion inhibitor), tetramethylammonium (clay stabilizer), biocides or strong oxidants. Application of highly oxidizing chemicals, together with occasional disclosures of putative delayed acids and complexing agents (i.e., compounds designed to react in the subsurface) suggests that relevant transformation products may be formed. To adequately investigate such reactions, available information is not sufficient, but instead a full disclosure of HF additives is necessary.

Structure-Guided Combinatorial Engineering Facilitates Affinity and Specificity Optimization of Anti-CD81 Antibodies.

PubMed

Nelson, Bryce; Adams, Jarrett; Kuglstatter, Andreas; Li, Zhijian; Harris, Seth F; Liu, Yang; Bohini, Sandya; Ma, Han; Klumpp, Klaus; Gao, Junjun; Sidhu, Sachdev S

2018-07-06

Hepatitis C viral infection is the major cause of chronic hepatitis that affects as many as 71 million people worldwide. Rather than target the rapidly shifting viruses and their numerous serotypes, four independent antibodies were made to target the host antigen CD81 and were shown to block hepatitis C viral entry. The single-chain variable fragment of each antibody was crystallized in complex with the CD81 large extracellular loop in order to guide affinity maturation of two distinct antibodies by phage display. Affinity maturation of antibodies using phage display has proven to be critical to therapeutic antibody development and typically involves modification of the paratope for increased affinity, improved specificity, enhanced stability or a combination of these traits. One antibody was engineered for increased affinity for human CD81 large extracellular loop that equated to increased efficacy, while the second antibody was engineered for cross-reactivity with cynomolgus CD81 to facilitate animal model testing. The use of structures to guide affinity maturation library design demonstrates the utility of combining structural analysis with phage display technologies. Copyright © 2018 Elsevier Ltd. All rights reserved.

A standard lexicon for biodiversity conservation: unified classifications of threats and actions.

PubMed

Salafsky, Nick; Salzer, Daniel; Stattersfield, Alison J; Hilton-Taylor, Craig; Neugarten, Rachel; Butchart, Stuart H M; Collen, Ben; Cox, Neil; Master, Lawrence L; O'Connor, Sheila; Wilkie, David

2008-08-01

An essential foundation of any science is a standard lexicon. Any given conservation project can be described in terms of the biodiversity targets, direct threats, contributing factors at the project site, and the conservation actions that the project team is employing to change the situation. These common elements can be linked in a causal chain, which represents a theory of change about how the conservation actions are intended to bring about desired project outcomes. If project teams want to describe and share their work and learn from one another, they need a standard and precise lexicon to specifically describe each node along this chain. To date, there have been several independent efforts to develop standard classifications for the direct threats that affect biodiversity and the conservation actions required to counteract these threats. Recognizing that it is far more effective to have only one accepted global scheme, we merged these separate efforts into unified classifications of threats and actions, which we present here. Each classification is a hierarchical listing of terms and associated definitions. The classifications are comprehensive and exclusive at the upper levels of the hierarchy, expandable at the lower levels, and simple, consistent, and scalable at all levels. We tested these classifications by applying them post hoc to 1191 threatened bird species and 737 conservation projects. Almost all threats and actions could be assigned to the new classification systems, save for some cases lacking detailed information. Furthermore, the new classification systems provided an improved way of analyzing and comparing information across projects when compared with earlier systems. We believe that widespread adoption of these classifications will help practitioners more systematically identify threats and appropriate actions, managers to more efficiently set priorities and allocate resources, and most important, facilitate cross-project learning and the

A proposal for classification of entities combining vascular malformations and deregulated growth.

PubMed

Oduber, Charlène E U; van der Horst, Chantal M A M; Sillevis Smitt, J Henk; Smeulders, Mark J C; Mendiratta, Vibhu; Harper, John I; van Steensel, Maurice A M; Hennekam, Raoul C M

2011-01-01

Agreement on terminology and nomenclature is fundamental and essential for effective exchange of information between clinicians and researchers. An adequate terminology to describe all patients showing vascular malformations combined with deregulated growth is at present not available. To propose a classification of patients with vascular malformations, not restricted to the face, and growth disturbances based on simple, clinically visible characteristics, on which clinicians and researchers can comment and which should eventually lead to an internationally accepted classification. Rooted in our joint experience we established a classification of vascular malformation not limited to the face, with growth disturbances. It is based on the nature and localization of the vascular malformations; the nature, localization and timing of growth disturbances; the nature of co-localization of the vascular malformations and growth disturbances; the presence or absence of other features. Subsequently a mixed (experienced and non-experienced) group of observers evaluated 146 patients (106 from the Netherlands; 40 from the UK) with vascular malformations and disturbed growth, using the classification. Inter-observer variability was assessed by estimating the Intra-Class Correlation (ICC) coefficient and its 95% confidence interval. We defined 6 subgroups within the group of entities with vascular malformation-deregulated growth. Scoring the patients using the proposed classification yielded a high inter-observer reproducibility (ICC varying between 0.747 and 0.895 for all levels of flow). The presently proposed classification was found to be reliable and easy to use for patients with vascular malformations with growth disturbances. We invite both clinicians and researchers to comment on the classification, in order to improve it further. This way we may obtain our final aim of an internationally accepted classification of patients, which should facilitate both clinical treatment

The Value of Ensari’s Proposal in Evaluating the Mucosal Pathology of Childhood Celiac Disease: Old Classification versus New Version

PubMed Central

Güreşci, Servet; Hızlı, Şamil; Şimşek, Gülçin Güler

2012-01-01

Objective: Small intestinal biopsy remains the gold standard in diagnosing celiac disease (CD); however, the wide spectrum of histopathological states and differential diagnosis of CD is still a diagnostic problem for pathologists. Recently, Ensari reviewed the literature and proposed an update of the histopathological diagnosis and classification for CD. Materials and Methods: In this study, the histopathological materials of 54 children in whom CD was diagnosed at our hospital were reviewed to compare the previous Marsh and Modified Marsh-Oberhuber classifications with this new proposal. Results: In this study, we show that the Ensari classification is as accurate as the Marsh and Modified Marsh classifications in describing the consecutive states of mucosal damage seen in CD. Conclusions: Ensari’s classification is simple, practical and facilitative in diagnosing and subtyping of mucosal pathology of CD. PMID:25207015

Facilitating Developmental Guidance through Behavioral Management.

ERIC Educational Resources Information Center

Davis, Donna H.

1980-01-01

The counselor, facilitating classroom development guidance lessons, may experience conflict and difficulty. The management system presented here allows for flexibility and provides sufficient behavioral structure, while encouraging individual expression from students. This behavioral management approach is supportive of, but secondary to,…

78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-18

...-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing... regulations to allow for the addition of an optional cotton futures classification procedure--identified and known as ``registration'' by the U.S. cotton industry and the Intercontinental Exchange (ICE). In...

Various forms of indexing HDMR for modelling multivariate classification problems

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

Aksu, Çağrı; Tunga, M. Alper

2014-12-10

The Indexing HDMR method was recently developed for modelling multivariate interpolation problems. The method uses the Plain HDMR philosophy in partitioning the given multivariate data set into less variate data sets and then constructing an analytical structure through these partitioned data sets to represent the given multidimensional problem. Indexing HDMR makes HDMR be applicable to classification problems having real world data. Mostly, we do not know all possible class values in the domain of the given problem, that is, we have a non-orthogonal data structure. However, Plain HDMR needs an orthogonal data structure in the given problem to be modelled.more » In this sense, the main idea of this work is to offer various forms of Indexing HDMR to successfully model these real life classification problems. To test these different forms, several well-known multivariate classification problems given in UCI Machine Learning Repository were used and it was observed that the accuracy results lie between 80% and 95% which are very satisfactory.« less

[Accuracy improvement of spectral classification of crop using microwave backscatter data].

PubMed

Jia, Kun; Li, Qiang-Zi; Tian, Yi-Chen; Wu, Bing-Fang; Zhang, Fei-Fei; Meng, Ji-Hua

2011-02-01

In the present study, VV polarization microwave backscatter data used for improving accuracies of spectral classification of crop is investigated. Classification accuracy using different classifiers based on the fusion data of HJ satellite multi-spectral and Envisat ASAR VV backscatter data are compared. The results indicate that fusion data can take full advantage of spectral information of HJ multi-spectral data and the structure sensitivity feature of ASAR VV polarization data. The fusion data enlarges the spectral difference among different classifications and improves crop classification accuracy. The classification accuracy using fusion data can be increased by 5 percent compared to the single HJ data. Furthermore, ASAR VV polarization data is sensitive to non-agrarian area of planted field, and VV polarization data joined classification can effectively distinguish the field border. VV polarization data associating with multi-spectral data used in crop classification enlarges the application of satellite data and has the potential of spread in the domain of agriculture.

A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

PubMed

Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

2014-10-01

Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

Nasal Septal Deviations: A Systematic Review of Classification Systems.

PubMed

Teixeira, Jeffrey; Certal, Victor; Chang, Edward T; Camacho, Macario

2016-01-01

Objective. To systematically review the international literature for internal nasal septal deviation classification systems and summarize them for clinical and research purposes. Data Sources. Four databases (including PubMed/MEDLINE) were systematically searched through December 16, 2015. Methods. Systematic review, adhering to PRISMA. Results. After removal of duplicates, this study screened 952 articles for relevance. A final comprehensive review of 50 articles identified that 15 of these articles met the eligibility criteria. The classification systems defined in these articles included C-shaped, S-shaped, reverse C-shaped, and reverse S-shaped descriptions of the septal deviation in both the cephalocaudal and anteroposterior dimensions. Additional studies reported use of computed tomography and categorized deviation based on predefined locations. Three studies graded the severity of septal deviations based on the amount of deflection. The systems defined in the literature also included an evaluation of nasal septal spurs and perforations. Conclusion. This systematic review ascertained that the majority of the currently published classification systems for internal nasal septal deviations can be summarized by C-shaped or reverse C-shaped, as well as S-shaped or reverse S-shaped deviations in the anteroposterior and cephalocaudal dimensions. For imaging studies, predefined points have been defined along the septum. Common terminology can facilitate future research.

Hydrological Climate Classification: Can We Improve on Köppen-Geiger?

NASA Astrophysics Data System (ADS)

Knoben, W.; Woods, R. A.; Freer, J. E.

2017-12-01

Classification is essential in the study of complex natural systems, yet hydrology so far has no formal way to structure the climate forcing which underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might use. From gridded global data we calculate a gridded aridity index, an aridity seasonality index and a rain-vs-snow index, which we use to cluster global locations into climate groups. We then define the membership degree of nearly 1100 catchments to each of our climate groups based on each catchment's climate and investigate the extent to which streamflow responses within each climate group are similar. We compare this climate classification approach with the often-used Köppen-Geiger classification, using statistical tests based on streamflow signature values. We find that three climate indices are sufficient to distinguish 18 different climate types world-wide. Climates tend to change gradually in space and catchments can thus belong to multiple climate groups, albeit with different degrees of membership. Streamflow responses within a climate group tend to be similar, regardless of the catchments' geographical proximity. A Wilcoxon two-sample test based on streamflow signature values for each climate group shows that the new classification can distinguish different flow regimes using this classification scheme. The Köppen-Geiger approach uses 29 climate classes but is less able to differentiate streamflow regimes. Climate forcing exerts a strong control on typical hydrologic response and both change gradually in space. This makes arbitrary hard boundaries in any classification scheme difficult to defend. Any hydrological classification should thus acknowledge these gradual changes in forcing. Catchment characteristics (soil or vegetation type, land use, etc) can vary more quickly in space than climate does, which

Building the United States National Vegetation Classification

USGS Publications Warehouse

Franklin, S.B.; Faber-Langendoen, D.; Jennings, M.; Keeler-Wolf, T.; Loucks, O.; Peet, R.; Roberts, D.; McKerrow, A.

2012-01-01

The Federal Geographic Data Committee (FGDC) Vegetation Subcommittee, the Ecological Society of America Panel on Vegetation Classification, and NatureServe have worked together to develop the United States National Vegetation Classification (USNVC). The current standard was accepted in 2008 and fosters consistency across Federal agencies and non-federal partners for the description of each vegetation concept and its hierarchical classification. The USNVC is structured as a dynamic standard, where changes to types at any level may be proposed at any time as new information comes in. But, because much information already exists from previous work, the NVC partners first established methods for screening existing types to determine their acceptability with respect to the 2008 standard. Current efforts include a screening process to assign confidence to Association and Group level descriptions, and a review of the upper three levels of the classification. For the upper levels especially, the expectation is that the review process includes international scientists. Immediate future efforts include the review of remaining levels and the development of a proposal review process.

Automatic topic identification of health-related messages in online health community using text classification.

PubMed

Lu, Yingjie

2013-01-01

To facilitate patient involvement in online health community and obtain informative support and emotional support they need, a topic identification approach was proposed in this paper for identifying automatically topics of the health-related messages in online health community, thus assisting patients in reaching the most relevant messages for their queries efficiently. Feature-based classification framework was presented for automatic topic identification in our study. We first collected the messages related to some predefined topics in a online health community. Then we combined three different types of features, n-gram-based features, domain-specific features and sentiment features to build four feature sets for health-related text representation. Finally, three different text classification techniques, C4.5, Naïve Bayes and SVM were adopted to evaluate our topic classification model. By comparing different feature sets and different classification techniques, we found that n-gram-based features, domain-specific features and sentiment features were all considered to be effective in distinguishing different types of health-related topics. In addition, feature reduction technique based on information gain was also effective to improve the topic classification performance. In terms of classification techniques, SVM outperformed C4.5 and Naïve Bayes significantly. The experimental results demonstrated that the proposed approach could identify the topics of online health-related messages efficiently.

Lagrangian methods of cosmic web classification

NASA Astrophysics Data System (ADS)

Fisher, J. D.; Faltenbacher, A.; Johnson, M. S. T.

2016-05-01

The cosmic web defines the large-scale distribution of matter we see in the Universe today. Classifying the cosmic web into voids, sheets, filaments and nodes allows one to explore structure formation and the role environmental factors have on halo and galaxy properties. While existing studies of cosmic web classification concentrate on grid-based methods, this work explores a Lagrangian approach where the V-web algorithm proposed by Hoffman et al. is implemented with techniques borrowed from smoothed particle hydrodynamics. The Lagrangian approach allows one to classify individual objects (e.g. particles or haloes) based on properties of their nearest neighbours in an adaptive manner. It can be applied directly to a halo sample which dramatically reduces computational cost and potentially allows an application of this classification scheme to observed galaxy samples. Finally, the Lagrangian nature admits a straightforward inclusion of the Hubble flow negating the necessity of a visually defined threshold value which is commonly employed by grid-based classification methods.

Tissue classification for laparoscopic image understanding based on multispectral texture analysis

NASA Astrophysics Data System (ADS)

Zhang, Yan; Wirkert, Sebastian J.; Iszatt, Justin; Kenngott, Hannes; Wagner, Martin; Mayer, Benjamin; Stock, Christian; Clancy, Neil T.; Elson, Daniel S.; Maier-Hein, Lena

2016-03-01

Intra-operative tissue classification is one of the prerequisites for providing context-aware visualization in computer-assisted minimally invasive surgeries. As many anatomical structures are difficult to differentiate in conventional RGB medical images, we propose a classification method based on multispectral image patches. In a comprehensive ex vivo study we show (1) that multispectral imaging data is superior to RGB data for organ tissue classification when used in conjunction with widely applied feature descriptors and (2) that combining the tissue texture with the reflectance spectrum improves the classification performance. Multispectral tissue analysis could thus evolve as a key enabling technique in computer-assisted laparoscopy.

Neuromuscular disease classification system

NASA Astrophysics Data System (ADS)

Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

2013-06-01

Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

Vascular Anomalies (Part I): Classification and Diagnostics of Vascular Anomalies.

PubMed

Sadick, Maliha; Müller-Wille, René; Wildgruber, Moritz; Wohlgemuth, Walter A

2018-06-06

 Vascular anomalies are a diagnostic and therapeutic challenge. They require dedicated interdisciplinary management. Optimal patient care relies on integral medical evaluation and a classification system established by experts in the field, to provide a better understanding of these complex vascular entities.  A dedicated classification system according to the International Society for the Study of Vascular Anomalies (ISSVA) and the German Interdisciplinary Society of Vascular Anomalies (DiGGefA) is presented. The vast spectrum of diagnostic modalities, ranging from ultrasound with color Doppler, conventional X-ray, CT with 4 D imaging and MRI as well as catheter angiography for appropriate assessment is discussed.  Congenital vascular anomalies are comprised of vascular tumors, based on endothelial cell proliferation and vascular malformations with underlying mesenchymal and angiogenetic disorder. Vascular tumors tend to regress with patient's age, vascular malformations increase in size and are subdivided into capillary, venous, lymphatic, arterio-venous and combined malformations, depending on their dominant vasculature. According to their appearance, venous malformations are the most common representative of vascular anomalies (70 %), followed by lymphatic malformations (12 %), arterio-venous malformations (8 %), combined malformation syndromes (6 %) and capillary malformations (4 %).  The aim is to provide an overview of the current classification system and diagnostic characterization of vascular anomalies in order to facilitate interdisciplinary management of vascular anomalies.   · Vascular anomalies are comprised of vascular tumors and vascular malformations, both considered to be rare diseases.. · Appropriate treatment depends on correct classification and diagnosis of vascular anomalies, which is based on established national and international classification systems, recommendations and guidelines.. · In the classification

ClassyFire: automated chemical classification with a comprehensive, computable taxonomy.

PubMed

Djoumbou Feunang, Yannick; Eisner, Roman; Knox, Craig; Chepelev, Leonid; Hastings, Janna; Owen, Gareth; Fahy, Eoin; Steinbeck, Christoph; Subramanian, Shankar; Bolton, Evan; Greiner, Russell; Wishart, David S

2016-01-01

Scientists have long been driven by the desire to describe, organize, classify, and compare objects using taxonomies and/or ontologies. In contrast to biology, geology, and many other scientific disciplines, the world of chemistry still lacks a standardized chemical ontology or taxonomy. Several attempts at chemical classification have been made; but they have mostly been limited to either manual, or semi-automated proof-of-principle applications. This is regrettable as comprehensive chemical classification and description tools could not only improve our understanding of chemistry but also improve the linkage between chemistry and many other fields. For instance, the chemical classification of a compound could help predict its metabolic fate in humans, its druggability or potential hazards associated with it, among others. However, the sheer number (tens of millions of compounds) and complexity of chemical structures is such that any manual classification effort would prove to be near impossible. We have developed a comprehensive, flexible, and computable, purely structure-based chemical taxonomy (ChemOnt), along with a computer program (ClassyFire) that uses only chemical structures and structural features to automatically assign all known chemical compounds to a taxonomy consisting of >4800 different categories. This new chemical taxonomy consists of up to 11 different levels (Kingdom, SuperClass, Class, SubClass, etc.) with each of the categories defined by unambiguous, computable structural rules. Furthermore each category is named using a consensus-based nomenclature and described (in English) based on the characteristic common structural properties of the compounds it contains. The ClassyFire webserver is freely accessible at http://classyfire.wishartlab.com/. Moreover, a Ruby API version is available at https://bitbucket.org/wishartlab/classyfire_api, which provides programmatic access to the ClassyFire server and database. ClassyFire has been used to

Woody structure facilitates invasion of woody plants by providing perches for birds.

PubMed

Prather, Chelse M; Huynh, Andrew; Pennings, Steven C

2017-10-01

Woody encroachment threatens prairie ecosystems globally, and thus understanding the mechanisms that facilitate woody encroachment is of critical importance. Coastal tallgrass prairies along the Gulf Coast of the US are currently threatened by the spread of several species of woody plants. We studied a coastal tallgrass prairie in Texas, USA, to determine if existing woody structure increased the supply of seeds from woody plants via dispersal by birds. Specifically, we determined if (i) more seedlings of an invasive tree ( Tridacia sebifera ) are present surrounding a native woody plant ( Myrica cerifera ); (ii) wooden perches increase the quantity of seeds dispersed to a grassland; and (iii) perches alter the composition of the seed rain seasonally in prairie habitats with differing amounts of native and invasive woody vegetation, both underneath and away from artificial wooden perches. More T. sebifera seedlings were found within M. cerifera patches than in graminoid-dominated areas. Although perches did not affect the total number of seeds, perches changed the composition of seed rain to be less dominated by grasses and forbs. Specifically, 20-30 times as many seeds of two invasive species of woody plants were found underneath perches independent of background vegetation, especially during months when seed rain was highest. These results suggest that existing woody structure in a grassland can promote further woody encroachment by enhancing seed dispersal by birds. This finding argues for management to reduce woody plant abundance before exotic plants set seeds and argues against the use of artificial perches as a restoration technique in grasslands threatened by woody species.

Chemical-Help Application for Classification and Identification of Stormwater Constituents

USGS Publications Warehouse

Granato, Gregory E.; Driskell, Timothy R.; Nunes, Catherine

2000-01-01

A computer application called Chemical Help was developed to facilitate review of reports for the National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS). The application provides a tool to quickly find a proper classification for any constituent in the NDAMS review sheets. Chemical Help contents include the name of each water-quality property, constituent, or parameter, the section number within the NDAMS review sheet, the organizational levels within a classification hierarchy, the database number, and where appropriate, the chemical formula, the Chemical Abstract Service number, and a list of synonyms (for the organic chemicals). Therefore, Chemical Help provides information necessary to research available reference data for the water-quality properties and constituents of potential interest in stormwater studies. Chemical Help is implemented in the Microsoft help-system interface. (Computer files for the use and documentation of Chemical Help are included on an accompanying diskette.)

Toward validation of a structural approach to conceptualizing psychopathology: A special section of the Journal of Abnormal Psychology.

PubMed

Krueger, Robert F; Tackett, Jennifer L; MacDonald, Angus

2016-11-01

Traditionally, psychopathology has been conceptualized in terms of polythetic categories derived from committee deliberations and enshrined in authoritative psychiatric nosologies-most notably the Diagnostic and Statistical Manual of Mental Disorders (DSM; American Psychiatric Association [APA], 2013). As the limitations of this form of classification have become evident, empirical data have been increasingly relied upon to investigate the structure of psychopathology. These efforts have borne fruit in terms of an increasingly consistent set of psychopathological constructs closely connected with similar personality constructs. However, the work of validating these constructs using convergent sources of data is an ongoing enterprise. This special section collects several new efforts to use structural approaches to study the validity of this empirically based organizational scheme for psychopathology. Inasmuch as a structural approach reflects the natural organization of psychopathology, it has great potential to facilitate comprehensive organization of information on the correlates of psychopathology, providing evidence for the convergent and discriminant validity of an empirical approach to classification. Here, we highlight several themes that emerge from this burgeoning literature. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Two Influential Primate Classifications Logically Aligned

PubMed Central

Franz, Nico M.; Pier, Naomi M.; Reeder, Deeann M.; Chen, Mingmin; Yu, Shizhuo; Kianmajd, Parisa; Bowers, Shawn; Ludäscher, Bertram

2016-01-01

Classifications and phylogenies of perceived natural entities change in the light of new evidence. Taxonomic changes, translated into Code-compliant names, frequently lead to name:meaning dissociations across succeeding treatments. Classification standards such as the Mammal Species of the World (MSW) may experience significant levels of taxonomic change from one edition to the next, with potential costs to long-term, large-scale information integration. This circumstance challenges the biodiversity and phylogenetic data communities to express taxonomic congruence and incongruence in ways that both humans and machines can process, that is, to logically represent taxonomic alignments across multiple classifications. We demonstrate that such alignments are feasible for two classifications of primates corresponding to the second and third MSW editions. Our approach has three main components: (i) use of taxonomic concept labels, that is name sec. author (where sec. means according to), to assemble each concept hierarchy separately via parent/child relationships; (ii) articulation of select concepts across the two hierarchies with user-provided Region Connection Calculus (RCC-5) relationships; and (iii) the use of an Answer Set Programming toolkit to infer and visualize logically consistent alignments of these input constraints. Our use case entails the Primates sec. Groves (1993; MSW2–317 taxonomic concepts; 233 at the species level) and Primates sec. Groves (2005; MSW3–483 taxonomic concepts; 376 at the species level). Using 402 RCC-5 input articulations, the reasoning process yields a single, consistent alignment and 153,111 Maximally Informative Relations that constitute a comprehensive meaning resolution map for every concept pair in the Primates sec. MSW2/MSW3. The complete alignment, and various partitions thereof, facilitate quantitative analyses of name:meaning dissociation, revealing that nearly one in three taxonomic names are not reliable across

Whewell on classification and consilience.

PubMed

Quinn, Aleta

2017-08-01

In this paper I sketch William Whewell's attempts to impose order on classificatory mineralogy, which was in Whewell's day (1794-1866) a confused science of uncertain prospects. Whewell argued that progress was impeded by the crude reductionist assumption that all macroproperties of crystals could be straightforwardly explained by reference to the crystals' chemical constituents. By comparison with biological classification, Whewell proposed methodological reforms that he claimed would lead to a natural classification of minerals, which in turn would support advances in causal understanding of the properties of minerals. Whewell's comparison to successful biological classification is particularly striking given that classificatory biologists did not share an understanding of the causal structure underlying the natural classification of life (the common descent with modification of all organisms). Whewell's key proposed methodological reform is consideration of multiple, distinct principles of classification. The most powerful evidence in support of a natural classificatory claim is the consilience of claims arrived at through distinct lines of reasoning, rooted in distinct conceptual approaches to the target objects. Mineralogists must consider not only elemental composition and chemical affinities, but also symmetry and polarity. Geometrical properties are central to what makes an individual mineral the type of mineral that it is. In Whewell's view, function and organization jointly define life, and so are the keys to understanding what makes an organism the type of organism that it is. I explain the relationship between Whewell's teleological account of life and his natural theology. I conclude with brief comments about the importance of Whewell's classificatory theory for the further development of his philosophy of science and in particular his account of consilience. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cancer classification using the Immunoscore: a worldwide task force.

PubMed

Galon, Jérôme; Pagès, Franck; Marincola, Francesco M; Angell, Helen K; Thurin, Magdalena; Lugli, Alessandro; Zlobec, Inti; Berger, Anne; Bifulco, Carlo; Botti, Gerardo; Tatangelo, Fabiana; Britten, Cedrik M; Kreiter, Sebastian; Chouchane, Lotfi; Delrio, Paolo; Arndt, Hartmann; Asslaber, Martin; Maio, Michele; Masucci, Giuseppe V; Mihm, Martin; Vidal-Vanaclocha, Fernando; Allison, James P; Gnjatic, Sacha; Hakansson, Leif; Huber, Christoph; Singh-Jasuja, Harpreet; Ottensmeier, Christian; Zwierzina, Heinz; Laghi, Luigi; Grizzi, Fabio; Ohashi, Pamela S; Shaw, Patricia A; Clarke, Blaise A; Wouters, Bradly G; Kawakami, Yutaka; Hazama, Shoichi; Okuno, Kiyotaka; Wang, Ena; O'Donnell-Tormey, Jill; Lagorce, Christine; Pawelec, Graham; Nishimura, Michael I; Hawkins, Robert; Lapointe, Réjean; Lundqvist, Andreas; Khleif, Samir N; Ogino, Shuji; Gibbs, Peter; Waring, Paul; Sato, Noriyuki; Torigoe, Toshihiko; Itoh, Kyogo; Patel, Prabhu S; Shukla, Shilin N; Palmqvist, Richard; Nagtegaal, Iris D; Wang, Yili; D'Arrigo, Corrado; Kopetz, Scott; Sinicrope, Frank A; Trinchieri, Giorgio; Gajewski, Thomas F; Ascierto, Paolo A; Fox, Bernard A

2012-10-03

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J

Nature and the natural environment as health facilitators: the need to reconceptualize the ICF environmental factors.

PubMed

Day, Adam M B; Theurer, Julie A; Dykstra, Allyson D; Doyle, Philip C

2012-01-01

This work examines the environmental factors component of the International Classification of Functioning, Disability, and Health (ICF) relative to current health-facilitating evidence about natural environmental factors. We argue that the environmental factors component warrants reconceptualization in order to offer an extended and more systematic framework for identifying and measuring health-facilitating natural environmental factors. Current evidence highlighting the potential health-facilitating benefits of natural environmental factors is synthesized and considered in the context of the ICF framework and its coding system. In its current form, the ICF's conceptual framework and coding system are inadequate for identifying and measuring natural environmental factors in individuals and groups with and/or without health conditions. The ICF provides an advanced framework for health and disability that reflects contemporary conceptualizations about health. However, given the scope of emerging evidence highlighting positive health and well-being outcomes associated with natural environmental factors, we believe the environmental factors component requires further advancement to reflect this current knowledge. Reconceptualizing the environmental factors component supports a more holistic interpretation of the continuum of environmental factors as both facilitators and barriers. In doing so, it strengthens the ICF's utility in identifying and measuring health-facilitating natural environmental factors.

Classification of octet AB-type binary compounds using dynamical charges: A materials informatics perspective

DOE PAGES

Pilania, G.; Gubernatis, J. E.; Lookman, T.

2015-12-03

The role of dynamical (or Born effective) charges in classification of octet AB-type binary compounds between four-fold (zincblende/wurtzite crystal structures) and six-fold (rocksalt crystal structure) coordinated systems is discussed. We show that the difference in the dynamical charges of the fourfold and sixfold coordinated structures, in combination with Harrison’s polarity, serves as an excellent feature to classify the coordination of 82 sp–bonded binary octet compounds. We use a support vector machine classifier to estimate the average classification accuracy and the associated variance in our model where a decision boundary is learned in a supervised manner. Lastly, we compare the out-of-samplemore » classification accuracy achieved by our feature pair with those reported previously.« less

Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

NASA Astrophysics Data System (ADS)

Li, Xiaoxiao; Myint, Soe W.; Zhang, Yujia; Galletti, Chritopher; Zhang, Xiaoxiang; Turner, Billie L.

2014-12-01

Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

An initial analysis of LANDSAT 4 Thematic Mapper data for the classification of agricultural, forested wetland, and urban land covers

NASA Technical Reports Server (NTRS)

Quattrochi, D. A.; Anderson, J. E.; Brannon, D. P.; Hill, C. L.

1982-01-01

An initial analysis of LANDSAT 4 thematic mapper (TM) data for the delineation and classification of agricultural, forested wetland, and urban land covers was conducted. A study area in Poinsett County, Arkansas was used to evaluate a classification of agricultural lands derived from multitemporal LANDSAT multispectral scanner (MSS) data in comparison with a classification of TM data for the same area. Data over Reelfoot Lake in northwestern Tennessee were utilized to evaluate the TM for delineating forested wetland species. A classification of the study area was assessed for accuracy in discriminating five forested wetland categories. Finally, the TM data were used to identify urban features within a small city. A computer generated classification of Union City, Tennessee was analyzed for accuracy in delineating urban land covers. An evaluation of digitally enhanced TM data using principal components analysis to facilitate photointerpretation of urban features was also performed.

Learning semantic histopathological representation for basal cell carcinoma classification

NASA Astrophysics Data System (ADS)

Gutiérrez, Ricardo; Rueda, Andrea; Romero, Eduardo

2013-03-01

Diagnosis of a histopathology glass slide is a complex process that involves accurate recognition of several structures, their function in the tissue and their relation with other structures. The way in which the pathologist represents the image content and the relations between those objects yields a better and accurate diagnoses. Therefore, an appropriate semantic representation of the image content will be useful in several analysis tasks such as cancer classification, tissue retrieval and histopahological image analysis, among others. Nevertheless, to automatically recognize those structures and extract their inner semantic meaning are still very challenging tasks. In this paper we introduce a new semantic representation that allows to describe histopathological concepts suitable for classification. The approach herein identify local concepts using a dictionary learning approach, i.e., the algorithm learns the most representative atoms from a set of random sampled patches, and then models the spatial relations among them by counting the co-occurrence between atoms, while penalizing the spatial distance. The proposed approach was compared with a bag-of-features representation in a tissue classification task. For this purpose, 240 histological microscopical fields of view, 24 per tissue class, were collected. Those images fed a Support Vector Machine classifier per class, using 120 images as train set and the remaining ones for testing, maintaining the same proportion of each concept in the train and test sets. The obtained classification results, averaged from 100 random partitions of training and test sets, shows that our approach is more sensitive in average than the bag-of-features representation in almost 6%.

An updated version of NPIDB includes new classifications of DNA–protein complexes and their families

PubMed Central

Zanegina, Olga; Kirsanov, Dmitriy; Baulin, Eugene; Karyagina, Anna; Alexeevski, Andrei; Spirin, Sergey

2016-01-01

The recent upgrade of nucleic acid–protein interaction database (NPIDB, http://npidb.belozersky.msu.ru/) includes a newly elaborated classification of complexes of protein domains with double-stranded DNA and a classification of families of related complexes. Our classifications are based on contacting structural elements of both DNA: the major groove, the minor groove and the backbone; and protein: helices, beta-strands and unstructured segments. We took into account both hydrogen bonds and hydrophobic interaction. The analyzed material contains 1942 structures of protein domains from 748 PDB entries. We have identified 97 interaction modes of individual protein domain–DNA complexes and 17 DNA–protein interaction classes of protein domain families. We analyzed the sources of diversity of DNA–protein interaction modes in different complexes of one protein domain family. The observed interaction mode is sometimes influenced by artifacts of crystallization or diversity in secondary structure assignment. The interaction classes of domain families are more stable and thus possess more biological sense than a classification of single complexes. Integration of the classification into NPIDB allows the user to browse the database according to the interacting structural elements of DNA and protein molecules. For each family, we present average DNA shape parameters in contact zones with domains of the family. PMID:26656949

The dawn of a new era in onco-cardiology: The Kumamoto Classification.

PubMed

Sueta, Daisuke; Tabata, Noriaki; Akasaka, Tomonori; Yamashita, Takayoshi; Ikemoto, Tomokazu; Hokimoto, Seiji

2016-10-01

The term "onco-cardiology" has been used in reference to cardiotoxicity in the treatment of malignant disease. In actual clinical situations, however, cardiovascular disease (CVD) associated with malignant disease and the concurrence of atherosclerotic disease with malignant disease are commonly observed, complicating the course of treatment. Patients with malignant disease associated with coronary artery disease often die from the cardiovascular disease, so it is essential to classify these disease states. Additionally, the prevalence of these classifications makes it easy to manage patients with malignant disease and coronary artery disease. We divided the broad field of onco-cardiology into 4 classifications based on clinical scenarios (CSs): CS1 represents the so-called paraneoplastic syndrome. CS2 represents cardiotoxicity during treatment of malignant diseases. CS3 represents the concurrence of atherosclerotic disease with malignant disease, and CS4 represents cardiovascular disease with benign tumors. This classification facilitates the management of patients with malignant disease and coronary artery disease by promoting not only the primary but also the secondary prevention of CVD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Abnormal uterine bleeding: advantages of formal classification to patients, clinicians and researchers.

PubMed

Madhra, Mayank; Fraser, Ian S; Munro, Malcolm G; Critchley, Hilary O D

2014-07-01

To highlight the advantages of formal classification of causes of abnormal uterine bleeding from a clinical and scientific perspective. Review and recommendations for local implementation. In the past, research in the field of menstrual disorders has not been funded adequately with respect to the impact of symptoms on individuals, healthcare systems and society. This was confounded by a diverse terminology, which lead to confusion between clinical and scientific groups, ultimately harming the underlying evidence base. To address this, a formal classification system (PALM-COEIN) for the causes of abnormal uterine bleeding has been published for worldwide use by FIGO (International Federation of Gynecology and Obstetrics). This commentary explains problems created by the prior absence of such a system, the potential advantages stemming from its use, and practical suggestions for local implementation. The PALM-COEIN classification is applicable globally and, as momentum gathers, will ameliorate recurrence of historic problems, and harmonise reporting of clinical and scientific research to facilitate future progress in women's health. © 2014 Nordic Federation of Societies of Obstetrics and Gynecology.

Acoustic transient classification with a template correlation processor.

PubMed

Edwards, R T

1999-10-01

I present an architecture for acoustic pattern classification using trinary-trinary template correlation. In spite of its computational simplicity, the algorithm and architecture represent a method which greatly reduces bandwidth of the input, storage requirements of the classifier memory, and power consumption of the system without compromising classification accuracy. The linear system should be amenable to training using recently-developed methods such as Independent Component Analysis (ICA), and we predict that behavior will be qualitatively similar to that of structures in the auditory cortex.

Concerning a new classification of tricyanides

NASA Technical Reports Server (NTRS)

Krafft, F.; Vonhansen, A.

1979-01-01

A new classification series of tricyanides is presented. Several tricyanides are synthesized by a simple method from aluminum chloride, benzonitrile, and a respective alkyl or phenyl chloride, purified by recrystallization and distillation, and then analyzed. Structural formulae are suggested, and molecular weights, melting points, and boiling points are determined for each.

Structural and functional insight into the N-terminal domain of the clathrin adaptor Ent5 from Saccharomyces cerevisiae.

PubMed

Zhang, Fan; Song, Yang; Ebrahimi, Mohammad; Niu, Liwen; Teng, Maikun; Li, Xu

2016-09-02

Clathrin-coated vesicles (CCVs) play critical roles in multiple cellular processes, including nutrient uptake, endosome/lysosome biogenesis, pathogen invasion, regulation of signalling receptors, etc. Saccharomyces cerevisiae Ent5 (ScEnt5) is one of the two major adaptors supporting the CCV-mediated TGN/endosome traffic in yeast cells. However, the classification and phosphoinositide binding characteristic of ScEnt5 remain elusive. Here we report the crystal structures of the ScEnt5 N-terminal domain, and find that ScEnt5 contains an insertion α' helix that does not exist in other ENTH or ANTH domains. Furthermore, we investigate the classification of ScEnt5-N(31-191) by evolutionary history analyses and structure comparisons, and find that the ScEnt5 N-terminal domain shows different phosphoinositide binding property from rEpsin1 and rCALM. Above results facilitate the understanding of the ScEnt5-mediated vesicle coat formation process. Copyright © 2016 Elsevier Inc. All rights reserved.

Facilitating classroom based interprofessional learning: a grounded theory study of university educators' perceptions of their role adequacy as facilitators.

PubMed

Derbyshire, Julie A; Machin, Alison I; Crozier, Suzanne

2015-01-01

The provision of inter professional learning (IPL) within undergraduate programmes is now well established within many Higher Education Institutions (HEIs). IPL aims to better equip nurses and other health professionals with effective collaborative working skills and knowledge to improve the quality of patient care. Although there is still ambiguity in relation to the optimum timing and method for delivering IPL, effective facilitation is seen as essential. This paper reports on a grounded theory study of university educators' perceptions of the knowledge and skills needed for their role adequacy as IPL facilitators. Data was collected using semi structured interviews with nine participants who were theoretically sampled from a range of professional backgrounds, with varied experiences of education and involvement in facilitating IPL. Constant comparative analysis was used to generate four data categories: creating and sustaining an IPL group culture through transformational IPL leadership (core category), readiness for IPL facilitation, drawing on past interprofessional learning and working experiences and role modelling an interprofessional approach. The grounded theory generated from this study, although propositional, suggests that role adequacy for IPL facilitation is dependent on facilitator engagement in a process of 'transformational interprofessional learning leadership' to create and sustain a group culture. Copyright © 2014 Elsevier Ltd. All rights reserved.

Functional classification of pulmonary hypertension in children: Report from the PVRI pediatric taskforce, Panama 2011.

PubMed

Lammers, Astrid E; Adatia, Ian; Cerro, Maria Jesus Del; Diaz, Gabriel; Freudenthal, Alexandra Heath; Freudenthal, Franz; Harikrishnan, S; Ivy, Dunbar; Lopes, Antonio A; Raj, J Usha; Sandoval, Julio; Stenmark, Kurt; Haworth, Sheila G

2011-08-02

The members of the Pediatric Task Force of the Pulmonary Vascular Research Institute (PVRI) were aware of the need to develop a functional classification of pulmonary hypertension in children. The proposed classification follows the same pattern and uses the same criteria as the Dana Point pulmonary hypertension specific classification for adults. Modifications were necessary for children, since age, physical growth and maturation influences the way in which the functional effects of a disease are expressed. It is essential to encapsulate a child's clinical status, to make it possible to review progress with time as he/she grows up, as consistently and as objectively as possible. Particularly in younger children we sought to include objective indicators such as thriving, need for supplemental feeds and the record of school or nursery attendance. This helps monitor the clinical course of events and response to treatment over the years. It also facilitates the development of treatment algorithms for children. We present a consensus paper on a functional classification system for children with pulmonary hypertension, discussed at the Annual Meeting of the PVRI in Panama City, February 2011.

Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.

PubMed

Zare, Marzieh; Rezvani, Zahra; Benasich, April A

2016-07-01

This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier detection of developmental disorders that disrupt language acquisition. Network connectivity measures derived from 62-channel electroencephalogram (EEG) recording were used to identify selected features within two infant groups who differed on LLD risk: infants with a family history of LLD (FH+) and typically-developing infants without such a history (FH-). A support vector machine was deployed; global efficiency and global and local clustering coefficients were computed. A novel minimum spanning tree (MST) approach was also applied. Cross-validation was employed to assess the resultant classification. Infants were classified with about 80% accuracy into FH+ and FH- groups with 89% specificity and precision of 92%. Clustering patterns differed by risk group and MST network analysis suggests that FH+ infants' EEG complexity patterns were significantly different from FH- infants. The automatic classification techniques used here were shown to be both robust and reliable and should provide valuable information when applied to early identification of risk or clinical groups. The ability to identify infants at highest risk for LLD using "automatic classification" strategies is a novel convergent approach that may facilitate earlier diagnosis and remediation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Adenosine monophosphate-activated protein kinase-based classification of diabetes pharmacotherapy

PubMed Central

Dutta, D; Kalra, S; Sharma, M

2017-01-01

The current classification of both diabetes and antidiabetes medication is complex, preventing a treating physician from choosing the most appropriate treatment for an individual patient, sometimes resulting in patient-drug mismatch. We propose a novel, simple systematic classification of drugs, based on their effect on adenosine monophosphate-activated protein kinase (AMPK). AMPK is the master regular of energy metabolism, an energy sensor, activated when cellular energy levels are low, resulting in activation of catabolic process, and inactivation of anabolic process, having a beneficial effect on glycemia in diabetes. This listing of drugs makes it easier for students and practitioners to analyze drug profiles and match them with patient requirements. It also facilitates choice of rational combinations, with complementary modes of action. Drugs are classified as stimulators, inhibitors, mixed action, possible action, and no action on AMPK activity. Metformin and glitazones are pure stimulators of AMPK. Incretin-based therapies have a mixed action on AMPK. Sulfonylureas either inhibit AMPK or have no effect on AMPK. Glycemic efficacy of alpha-glucosidase inhibitors, sodium glucose co-transporter-2 inhibitor, colesevelam, and bromocriptine may also involve AMPK activation, which warrants further evaluation. Berberine, salicylates, and resveratrol are newer promising agents in the management of diabetes, having well-documented evidence of AMPK stimulation medicated glycemic efficacy. Hence, AMPK-based classification of antidiabetes medications provides a holistic unifying understanding of pharmacotherapy in diabetes. This classification is flexible with a scope for inclusion of promising agents of future. PMID:27652986

Categorization of intraoperative ureteroscopy complications using modified Satava classification system.

PubMed

Tepeler, Abdulkadir; Resorlu, Berkan; Sahin, Tolga; Sarikaya, Selcuk; Bayindir, Mirze; Oguz, Ural; Armagan, Abdullah; Unsal, Ali

2014-02-01

To review our experience with ureteroscopy (URS) in the treatment of ureteral calculi and stratify intraoperative complications of URS according to the modified Satava classification system. We performed a retrospective analysis of 1,208 patients (672 males and 536 females), with a mean age of 43.1 years (range 1-78), who underwent ureteroscopic procedures for removal of ureteral stones. Intraoperative complications were recorded according to modified Satava classification system. Grade 1 complications included incidents without consequences for the patient; grade 2 complications, which are treated intraoperatively with endoscopic surgery (grade 2a) or required endoscopic re-treatment (grade 2b); and grade 3 complications included incidents requiring open or laparoscopic surgery. The stones were completely removed in 1,067 (88.3%) patients after primary procedure by either simple extraction or after fragmentation. The overall incidence of intraoperative complications was 12.6%. The most common complications were proximal stone migration (3.9%), mucosal injury (2.8%), bleeding (1.9%), inability to reach stone (1.8%), malfunctioning or breakage of instruments (0.8%), ureteral perforation (0.8%) and ureteral avulsion (0.16%). According to modified Satava classification system, there were 4.5% grade 1; 4.4% grade 2a; 3.2% grade 2b; and 0.57% grade 3 complications. We think that modified Satava classification is a quick and simple system for describing the severity of intraoperative URS complications and this grading system will facilitate a better comparison for the surgical outcomes obtained from different centers.

A classification scheme for risk assessment methods.

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

Stamp, Jason Edwin; Campbell, Philip LaRoche

2004-08-01

This report presents a classification scheme for risk assessment methods. This scheme, like all classification schemes, provides meaning by imposing a structure that identifies relationships. Our scheme is based on two orthogonal aspects--level of detail, and approach. The resulting structure is shown in Table 1 and is explained in the body of the report. Each cell in the Table represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that amore » method chosen is optimal for a situation given. This report imposes structure on the set of risk assessment methods in order to reveal their relationships and thus optimize their usage.We present a two-dimensional structure in the form of a matrix, using three abstraction levels for the rows and three approaches for the columns. For each of the nine cells in the matrix we identify the method type by name and example. The matrix helps the user understand: (1) what to expect from a given method, (2) how it relates to other methods, and (3) how best to use it. Each cell in the matrix represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. The matrix, with type names in the cells, is introduced in Table 2 on page 13 below. Unless otherwise stated we use the word 'method' in this report to refer to a 'risk assessment method', though often times we use the full phrase. The use of the terms 'risk assessment' and 'risk management' are close enough that we do not attempt to distinguish them in this report. The remainder of this report is organized as follows. In Section 2 we provide context for

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks.

PubMed

Chai, Rifai; Ling, Sai Ho; San, Phyo Phyo; Naik, Ganesh R; Nguyen, Tuan N; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T

2017-01-01

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively.

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks

PubMed Central

Chai, Rifai; Ling, Sai Ho; San, Phyo Phyo; Naik, Ganesh R.; Nguyen, Tuan N.; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T.

2017-01-01

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively. PMID:28326009

Structural insights into RISC assembly facilitated by dsRNA-binding domains of human RNA helicase A (DHX9)

PubMed Central

Fu, Qinqin; Yuan, Y. Adam

2013-01-01

Intensive research interest has focused on small RNA-processing machinery and the RNA-induced silencing complex (RISC), key cellular machines in RNAi pathways. However, the structural mechanism regarding RISC assembly, the primary step linking small RNA processing and RNA-mediated gene silencing, is largely unknown. Human RNA helicase A (DHX9) was reported to function as an RISC-loading factor, and such function is mediated mainly by its dsRNA-binding domains (dsRBDs). Here, we report the crystal structures of human RNA helicase A (RHA) dsRBD1 and dsRBD2 domains in complex with dsRNAs, respectively. Structural analysis not only reveals higher siRNA duplex-binding affinity displayed by dsRBD1, but also identifies a crystallographic dsRBD1 pair of physiological significance in cooperatively recognizing dsRNAs. Structural observations are further validated by isothermal titration calorimetric (ITC) assay. Moreover, co-immunoprecipitation (co-IP) assay coupled with mutagenesis demonstrated that both dsRBDs are required for RISC association, and such association is mediated by dsRNA. Hence, our structural and functional efforts have revealed a potential working model for siRNA recognition by RHA tandem dsRBDs, and together they provide direct structural insights into RISC assembly facilitated by RHA. PMID:23361462

Structural insights into RISC assembly facilitated by dsRNA-binding domains of human RNA helicase A (DHX9).

PubMed

Fu, Qinqin; Yuan, Y Adam

2013-03-01

Intensive research interest has focused on small RNA-processing machinery and the RNA-induced silencing complex (RISC), key cellular machines in RNAi pathways. However, the structural mechanism regarding RISC assembly, the primary step linking small RNA processing and RNA-mediated gene silencing, is largely unknown. Human RNA helicase A (DHX9) was reported to function as an RISC-loading factor, and such function is mediated mainly by its dsRNA-binding domains (dsRBDs). Here, we report the crystal structures of human RNA helicase A (RHA) dsRBD1 and dsRBD2 domains in complex with dsRNAs, respectively. Structural analysis not only reveals higher siRNA duplex-binding affinity displayed by dsRBD1, but also identifies a crystallographic dsRBD1 pair of physiological significance in cooperatively recognizing dsRNAs. Structural observations are further validated by isothermal titration calorimetric (ITC) assay. Moreover, co-immunoprecipitation (co-IP) assay coupled with mutagenesis demonstrated that both dsRBDs are required for RISC association, and such association is mediated by dsRNA. Hence, our structural and functional efforts have revealed a potential working model for siRNA recognition by RHA tandem dsRBDs, and together they provide direct structural insights into RISC assembly facilitated by RHA.