Using dual classifications in the development of avian wetland indices of biological integrity for wetlands in West Virginia, USA.

Science.gov (United States)

Veselka, Walter; Anderson, James T; Kordek, Walter S

2010-05-01

Considerable resources are being used to develop and implement bioassessment methods for wetlands to ensure that "biological integrity" is maintained under the United States Clean Water Act. Previous research has demonstrated that avian composition is susceptible to human impairments at multiple spatial scales. Using a site-specific disturbance gradient, we built avian wetland indices of biological integrity (AW-IBI) specific to two wetland classification schemes, one based on vegetative structure and the other based on the wetland's position in the landscape and sources of water. The resulting class-specific AW-IBI was comprised of one to four metrics that varied in their sensitivity to the disturbance gradient. Some of these metrics were specific to only one of the classification schemes, whereas others could discriminate varying levels of disturbance regardless of classification scheme. Overall, all of the derived biological indices specific to the vegetative structure-based classes of wetlands had a significant relation with the disturbance gradient; however, the biological index derived for floodplain wetlands exhibited a more consistent response to a local disturbance gradient. We suspect that the consistency of this response is due to the inherent nature of the connectivity of available habitat in floodplain wetlands.

Comparison of Principal Component Analysis and Linear Discriminant Analysis applied to classification of excitation-emission matrices of the selected biological material

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Maciej Leśkiewicz

2016-03-01

Full Text Available Quality of two linear methods (PCA and LDA applied to reduce dimensionality of feature analysis is compared and efficiency of their algorithms in classification of the selected biological materials according to their excitation-emission fluorescence matrices is examined. It has been found that LDA method reduces the dimensions (or a number of significant variables more effectively than PCA method. A relatively good discrimination within the examined biological material has been obtained with the use of LDA algorithm.[b]Keywords[/b]: Feature Analysis, Fluorescence Spectroscopy, Biological Material Classification

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

Science.gov (United States)

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

Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology

Science.gov (United States)

Swan, Anna Louise; Mobasheri, Ali; Allaway, David; Liddell, Susan

2013-01-01

Abstract Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes. PMID:24116388

MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

Energy Technology Data Exchange (ETDEWEB)

Young, M; Craft, D [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

2016-06-15

Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve

BIOLOGIC AND ECONOMIC EFFECTS OF INCLUDING DIFFERENT ...

African Journals Online (AJOL)

The biologic and economic effects of including three agro-industrial by-products as ingredients in turkey poult diets were investigated using 48 turkey poults in a completely randomised design experiment. Diets were formulated to contain the three by-products – wheat offal, rice husk and palm kernel meal, each at 20% level ...

iTools: a framework for classification, categorization and integration of computational biology resources.

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Ivo D Dinov

2008-05-01

Full Text Available The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long

An accelerated framework for the classification of biological targets from solid-state micropore data.

Science.gov (United States)

Hanif, Madiha; Hafeez, Abdul; Suleman, Yusuf; Mustafa Rafique, M; Butt, Ali R; Iqbal, Samir M

2016-10-01

Micro- and nanoscale systems have provided means to detect biological targets, such as DNA, proteins, and human cells, at ultrahigh sensitivity. However, these devices suffer from noise in the raw data, which continues to be significant as newer and devices that are more sensitive produce an increasing amount of data that needs to be analyzed. An important dimension that is often discounted in these systems is the ability to quickly process the measured data for an instant feedback. Realizing and developing algorithms for the accurate detection and classification of biological targets in realtime is vital. Toward this end, we describe a supervised machine-learning approach that records single cell events (pulses), computes useful pulse features, and classifies the future patterns into their respective types, such as cancerous/non-cancerous cells based on the training data. The approach detects cells with an accuracy of 70% from the raw data followed by an accurate classification when larger training sets are employed. The parallel implementation of the algorithm on graphics processing unit (GPU) demonstrates a speedup of three to four folds as compared to a serial implementation on an Intel Core i7 processor. This incredibly efficient GPU system is an effort to streamline the analysis of pulse data in an academic setting. This paper presents for the first time ever, a non-commercial technique using a GPU system for realtime analysis, paired with biological cluster targeting analysis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A phylogeny and revised classification of Squamata, including 4161 species of lizards and snakes

Science.gov (United States)

2013-01-01

Background The extant squamates (>9400 known species of lizards and snakes) are one of the most diverse and conspicuous radiations of terrestrial vertebrates, but no studies have attempted to reconstruct a phylogeny for the group with large-scale taxon sampling. Such an estimate is invaluable for comparative evolutionary studies, and to address their classification. Here, we present the first large-scale phylogenetic estimate for Squamata. Results The estimated phylogeny contains 4161 species, representing all currently recognized families and subfamilies. The analysis is based on up to 12896 base pairs of sequence data per species (average = 2497 bp) from 12 genes, including seven nuclear loci (BDNF, c-mos, NT3, PDC, R35, RAG-1, and RAG-2), and five mitochondrial genes (12S, 16S, cytochrome b, ND2, and ND4). The tree provides important confirmation for recent estimates of higher-level squamate phylogeny based on molecular data (but with more limited taxon sampling), estimates that are very different from previous morphology-based hypotheses. The tree also includes many relationships that differ from previous molecular estimates and many that differ from traditional taxonomy. Conclusions We present a new large-scale phylogeny of squamate reptiles that should be a valuable resource for future comparative studies. We also present a revised classification of squamates at the family and subfamily level to bring the taxonomy more in line with the new phylogenetic hypothesis. This classification includes new, resurrected, and modified subfamilies within gymnophthalmid and scincid lizards, and boid, colubrid, and lamprophiid snakes. PMID:23627680

Biological validation of physical coastal waters classification along the NE Atlantic region based on rocky macroalgae distribution

Science.gov (United States)

Ramos, Elvira; Puente, Araceli; Juanes, José Antonio; Neto, João M.; Pedersen, Are; Bartsch, Inka; Scanlan, Clare; Wilkes, Robert; Van den Bergh, Erika; Ar Gall, Erwan; Melo, Ricardo

2014-06-01

A methodology to classify rocky shores along the North East Atlantic (NEA) region was developed. Previously, biotypes and the variability of environmental conditions within these were recognized based on abiotic data. A biological validation was required in order to support the ecological meaning of the physical typologies obtained. A database of intertidal macroalgae species occurring in the coastal area between Norway and the South Iberian Peninsula was generated. Semi-quantitative abundance data of the most representative macroalgal taxa were collected in three levels: common, rare or absent. Ordination and classification multivariate analyses revealed a clear latitudinal gradient in the distribution of macroalgae species resulting in two distinct groups: one northern and one southern group, separated at the coast of Brittany (France). In general, the results based on biological data coincided with the results based on physical characteristics. The ecological meaning of the coastal waters classification at a broad scale shown in this work demonstrates that it can be valuable as a practical tool for conservation and management purposes.

Biological indices for classification of water quality around Mae Moh power plant, Thailand

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Pongsarun Junshum and Siripen Traichaiyaporn

2007-12-01

Full Text Available The algal communities and water quality were monitored at eight sampling sites around Mae Moh power plant during January-December 2003. Three biological indices, viz. algal genus pollution index, saprobic index, and Shannon-Weaver index, were adopted to classify the water quality around the power plant in comparison with the measured physico-chemical water quality. The result shows that the Shannon-Weaver diversity index appears to be much more applicable and interpretable for the classification of water quality around the Mae Moh power plant than the algal genus pollution index and the saprobic index.

Genetic and geological classification wetlands proposed. Application to the spanish wetlands included in the Ramsar convention; Propuesta de clasificacion genetico-geologica de humedales. Aplicacion a los humedales espanoles incluidos en el Convenio de Ramsar

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Duran Valsero, J. J.; Garcia de Domingo, A.; Robledo Ardila, P.

2009-07-01

The classification represents the first step in the research of the wetlands. There are several types of classifications established according different criteria: geographic, genetic, geologic, functional, hydric, biologic and others. In this work we considered the genetic and geologic classifications criteria are the more suitable because the criteria used are very concrete, descriptive and its application should be easier to put into practice. Every group established in this type of classification determines the develop naturals conditions allowing us to establish the evolution guidelines and same main management lines. The criteria used to develop this classification have been fundamentally: geologic, geomorphologic, tectonics, stratigraphic, and hydrogeologic because these determine greatly the physical wetland characteristics (geometric parameters, hydric nourishment system, hydrochemical characteristics and others). The general characteristics, guidelines behavior of the wetland, and the early evolution of every group of wetland could be essentials to detect and identified those actuations modifying the natural evolution in each concrete wetland. In this work we are applying these classification criteria to the Spanish wetlands included in the Ramsar Convention (until February 2006), defining twelve types of basic wetlands according the geologic and genetic characteristics. (Author) 19 refs.

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

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Mei Zhan

2015-04-01

Full Text Available Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM. These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

Science.gov (United States)

Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

2015-04-01

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision

Barrett's esophagus: cancer and molecular biology

NARCIS (Netherlands)

Gibson, Michael K.; Dhaliwal, Arashinder S.; Clemons, Nicholas J.; Phillips, Wayne A.; Dvorak, Katerina; Tong, Daniel; Law, Simon; Pirchi, E. Daniel; Räsänen, Jari; Krasna, Mark J.; Parikh, Kaushal; Krishnadath, Kausilia K.; Chen, Yu; Griffiths, Leonard; Colleypriest, Benjamin J.; Farrant, J. Mark; Tosh, David; Das, Kiron M.; Bajpai, Manisha

2013-01-01

The following paper on the molecular biology of Barrett's esophagus (BE) includes commentaries on signaling pathways central to the development of BE including Hh, NF-κB, and IL-6/STAT3; surgical approaches for esophagectomy and classification of lesions by appropriate therapy; the debate over the

Lie Group Classification of a Generalized Lane-Emden Type System in Two Dimensions

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Motlatsi Molati

2012-01-01

Full Text Available The aim of this work is to perform a complete Lie symmetry classification of a generalized Lane-Emden type system in two dimensions which models many physical phenomena in biological and physical sciences. The classical approach of group classification is employed for classification. We show that several cases arise in classifying the arbitrary parameters, the forms of which include amongst others the power law nonlinearity, and exponential and quadratic forms.

Sequence-specific 1H-NMR assignments for the aromatic region of several biologically active, monomeric insulins including native human insulin.

Science.gov (United States)

Roy, M; Lee, R W; Kaarsholm, N C; Thøgersen, H; Brange, J; Dunn, M F

1990-06-12

The aromatic region of the 1H-FT-NMR spectrum of the biologically fully-potent, monomeric human insulin mutant, B9 Ser----Asp, B27 Thr----Glu has been investigated in D2O. At 1 to 5 mM concentrations, this mutant insulin is monomeric above pH 7.5. Coupling and amino acid classification of all aromatic signals is established via a combination of homonuclear one- and two-dimensional methods, including COSY, multiple quantum filters, selective spin decoupling and pH titrations. By comparisons with other insulin mutants and with chemically modified native insulins, all resonances in the aromatic region are given sequence-specific assignments without any reliance on the various crystal structures reported for insulin. These comparisons also give the sequence-specific assignments of most of the aromatic resonances of the mutant insulins B16 Tyr----Glu, B27 Thr----Glu and B25 Phe----Asp and the chemically modified species des-(B23-B30) insulin and monoiodo-Tyr A14 insulin. Chemical dispersion of the assigned resonances, ring current perturbations and comparisons at high pH have made possible the assignment of the aromatic resonances of human insulin, and these studies indicate that the major structural features of the human insulin monomer (including those critical to biological function) are also present in the monomeric mutant.

Mass spectrometry in identification of ecotoxicants including chemical and biological warfare agents

International Nuclear Information System (INIS)

Lebedev, Albert T.

2005-01-01

Mass spectrometry is a unique tool to detect and identify trace levels of organic and bioorganic compounds as well as microorganisms in the environment. The range of potential chemical warfare (CW) and biological warfare (BW) agents is very broad. An important advantage of mass spectrometry over other techniques involves potential for full spectrum detection of chemical and biological agents including mid-spectrum materials (i.e. bioactive peptides, toxins, etc.) for which biological approaches are inadequate. Being very fast (seconds and minutes), extremely sensitive (zeptomoles 10 -21 ), and informative (detailed qualitative and quantitative composition of mixtures containing hundreds of chemicals), mass spectrometry is a principal analytical tool at the sites of destruction of CW. Due to its unique features, mass spectrometry is applied not only for the detection of CW agents, but for the analysis of products of metabolism and degradation of these agents in organisms or environment as well. The present paper deals with some examples of successful application of mass spectrometry for the analyses of ecotoxicants, chemical warfare agents, explosives, and microorganisms including biology warfare agents

Radiation biology in Canada 1962-63

International Nuclear Information System (INIS)

Thacker, D.G.

1963-02-01

A survey of the research projects in radiation biology being carried out in Canada during the fiscal year 1962-63. The report includes the names of the investigators, their location, a brief description of the projects and information on the financial support being provided. A classification of the projects into areas of specific interest is also included. (author)

Classification of Recombinant Biologics in the EU

DEFF Research Database (Denmark)

Klein, Kevin; De Bruin, Marie L; Broekmans, Andre W

2015-01-01

BACKGROUND AND OBJECTIVE: Biological medicinal products (biologics) are subject to specific pharmacovigilance requirements to ensure that biologics are identifiable by brand name and batch number in adverse drug reaction (ADR) reports. Since Member States collect ADR data at the national level...... of biologics by national authorities responsible for ADR reporting. METHODS: A sample list of recombinant biologics from the European Medicines Agency database of European Public Assessment Reports was created to analyze five Member States (Belgium, the Netherlands, Spain, Sweden, and the UK) according...

Lauren classification and individualized chemotherapy in gastric cancer.

Science.gov (United States)

Ma, Junli; Shen, Hong; Kapesa, Linda; Zeng, Shan

2016-05-01

Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histological subtypes of gastric cancer proposed by the Lauren classification exhibit a number of distinct clinical and molecular characteristics, including histogenesis, cell differentiation, epidemiology, etiology, carcinogenesis, biological behaviors and prognosis. Gastric cancer exhibits varied sensitivity to chemotherapy drugs and significant heterogeneity; therefore, the disease may be a target for individualized therapy. The Lauren classification may provide the basis for individualized treatment for advanced gastric cancer, which is increasingly gaining attention in the scientific field. However, few studies have investigated individualized treatment that is guided by pathological classification. The aim of the current review is to analyze the two major histological subtypes of gastric cancer, as proposed by the Lauren classification, and to discuss the implications of this for personalized chemotherapy.

Phenotype classification of zebrafish embryos by supervised learning.

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Nathalie Jeanray

Full Text Available Zebrafish is increasingly used to assess biological properties of chemical substances and thus is becoming a specific tool for toxicological and pharmacological studies. The effects of chemical substances on embryo survival and development are generally evaluated manually through microscopic observation by an expert and documented by several typical photographs. Here, we present a methodology to automatically classify brightfield images of wildtype zebrafish embryos according to their defects by using an image analysis approach based on supervised machine learning. We show that, compared to manual classification, automatic classification results in 90 to 100% agreement with consensus voting of biological experts in nine out of eleven considered defects in 3 days old zebrafish larvae. Automation of the analysis and classification of zebrafish embryo pictures reduces the workload and time required for the biological expert and increases the reproducibility and objectivity of this classification.

Biological effects of radiation

International Nuclear Information System (INIS)

2013-01-01

This fourth chapter presents: cell structure and metabolism; radiation interaction with biological tissues; steps of the production of biological effect of radiation; radiosensitivity of tissues; classification of biological effects; reversibility, transmissivity and influence factors; pre-natal biological effects; biological effects in therapy and syndrome of acute irradiation

Classifications of track structures

International Nuclear Information System (INIS)

Paretzke, H.G.

1984-01-01

When ionizing particles interact with matter they produce random topological structures of primary activations which represent the initial boundary conditions for all subsequent physical, chemical and/or biological reactions. There are two important aspects of research on such track structures, namely their experimental or theoretical determination on one hand and the quantitative classification of these complex structures which is a basic pre-requisite for the understanding of mechanisms of radiation actions. This paper deals only with the latter topic, i.e. the problems encountered in and possible approaches to quantitative ordering and grouping of these multidimensional objects by their degrees of similarity with respect to their efficiency in producing certain final radiation effects, i.e. to their ''radiation quality.'' Various attempts of taxonometric classification with respect to radiation efficiency have been made in basic and applied radiation research including macro- and microdosimetric concepts as well as track entities and stopping power based theories. In this paper no review of those well-known approaches is given but rather an outline and discussion of alternative methods new to this field of radiation research which have some very promising features and which could possibly solve at least some major classification problems

Benthic indicators to use in Ecological Quality classification of Mediterranean soft bottom marine ecosystems, including a new Biotic Index

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N. SIMBOURA

2002-12-01

Full Text Available A general scheme for approaching the objective of Ecological Quality Status (EcoQ classification of zoobenthic marine ecosystems is presented. A system based on soft bottom benthic indicator species and related habitat types is suggested to be used for testing the typological definition of a given water body in the Mediterranean. Benthic indices including the Shannon-Wiener diversity index and the species richness are re-evaluated for use in classification. Ranges of values and of ecological quality categories are given for the diversity and species richness in different habitat types. A new biotic index (BENTIX is proposed based on the relative percentages of three ecological groups of species grouped according to their sensitivity or tolerance to disturbance factors and weighted proportionately to obtain a formula rendering a five step numerical scale of ecological quality classification. Its advantage against former biotic indices lies in the fact that it reduces the number of the ecological groups involved which makes it simpler and easier in its use. The Bentix index proposed is tested and validated with data from Greek and western Mediterranean ecosystems and examples are presented. Indicator species associated with specific habitat types and pollution indicator species, scored according to their degree of tolerance to pollution, are listed in a table. The Bentix index is compared and evaluated against the indices of diversity and species richness for use in classification. The advantages of the BENTIX index as a classification tool for ECoQ include independence from habitat type, sample size and taxonomic effort, high discriminative power and simplicity in its use which make it a robust, simple and effective tool for application in the Mediterranean Sea.

Classification

DEFF Research Database (Denmark)

Hjørland, Birger

2017-01-01

This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

Objective classification of latent behavioral states in bio-logging data using multivariate-normal hidden Markov models.

Science.gov (United States)

Phillips, Joe Scutt; Patterson, Toby A; Leroy, Bruno; Pilling, Graham M; Nicol, Simon J

2015-07-01

many different types of noisy autocorrelated data, as typically found across a range of ecological systems. Summarizing time-series data into a multivariate assemblage of dimensions relevant to the desired classification provides a means to examine these data in an appropriate behavioral space. We discuss how outputs of these models can be applied to bio-logging and other imperfect behavioral data, providing easily interpretable models for hypothesis testing.

[Classification of organisms and structuralism in biology].

Science.gov (United States)

Vasil'eva, L I

2001-01-01

Structuralism in biology is the oldest trend oriented to the search for natural "laws of forms" comparable with laws of growth of crystal, was revived at the end of 20th century on the basis of structuralist thought in socio-humanitarian sciences. The development of principal ideas of the linguistic structuralism in some aspects is similar to that of biological systematics, especially concerning the relationships between "system" and "evolution". However, apart from this general similarity, biological structuralism is strongly focused on familiar problems of the origin of diversity in nature. In their striving for the renovation of existing views, biological structuralists oppose the neo-darwinism emphasizing the existence of "law of forms", that are independent on heredity and genetic "determinism". The trend to develop so-called "rational taxonomy" is also characteristic of biological structuralism but this attempt failed being connected neither with Darwin's historicism nor with Plato's typology.

Introduction to Classification of Living Things.

Science.gov (United States)

Stettler, Donald

This monograph contains an autoinstructional packet developed for secondary school biology students. The instructions present a lesson on classification using slides and packets of pictures as the media for displaying the animals and plants to be classified. A brief historical account leads into the study of the modern classification system. No…

Chemometric and Statistical Analyses of ToF-SIMS Spectra of Increasingly Complex Biological Samples

Energy Technology Data Exchange (ETDEWEB)

Berman, E S; Wu, L; Fortson, S L; Nelson, D O; Kulp, K S; Wu, K J

2007-10-24

Characterizing and classifying molecular variation within biological samples is critical for determining fundamental mechanisms of biological processes that will lead to new insights including improved disease understanding. Towards these ends, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to examine increasingly complex samples of biological relevance, including monosaccharide isomers, pure proteins, complex protein mixtures, and mouse embryo tissues. The complex mass spectral data sets produced were analyzed using five common statistical and chemometric multivariate analysis techniques: principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), soft independent modeling of class analogy (SIMCA), and decision tree analysis by recursive partitioning. PCA was found to be a valuable first step in multivariate analysis, providing insight both into the relative groupings of samples and into the molecular basis for those groupings. For the monosaccharides, pure proteins and protein mixture samples, all of LDA, PLSDA, and SIMCA were found to produce excellent classification given a sufficient number of compound variables calculated. For the mouse embryo tissues, however, SIMCA did not produce as accurate a classification. The decision tree analysis was found to be the least successful for all the data sets, providing neither as accurate a classification nor chemical insight for any of the tested samples. Based on these results we conclude that as the complexity of the sample increases, so must the sophistication of the multivariate technique used to classify the samples. PCA is a preferred first step for understanding ToF-SIMS data that can be followed by either LDA or PLSDA for effective classification analysis. This study demonstrates the strength of ToF-SIMS combined with multivariate statistical and chemometric techniques to classify increasingly complex biological samples

Differential Classification of Dementia

Directory of Open Access Journals (Sweden)

E. Mohr

1995-01-01

Full Text Available In the absence of biological markers, dementia classification remains complex both in terms of characterization as well as early detection of the presence or absence of dementing symptoms, particularly in diseases with possible secondary dementia. An empirical, statistical approach using neuropsychological measures was therefore developed to distinguish demented from non-demented patients and to identify differential patterns of cognitive dysfunction in neurodegenerative disease. Age-scaled neurobehavioral test results (Wechsler Adult Intelligence Scale—Revised and Wechsler Memory Scale from Alzheimer's (AD and Huntington's (HD patients, matched for intellectual disability, as well as normal controls were used to derive a classification formula. Stepwise discriminant analysis accurately (99% correct distinguished controls from demented patients, and separated the two patient groups (79% correct. Variables discriminating between HD and AD patient groups consisted of complex psychomotor tasks, visuospatial function, attention and memory. The reliability of the classification formula was demonstrated with a new, independent sample of AD and HD patients which yielded virtually identical results (classification accuracy for dementia: 96%; AD versus HD: 78%. To validate the formula, the discriminant function was applied to Parkinson's (PD patients, 38% of whom were classified as demented. The validity of the classification was demonstrated by significant PD subgroup differences on measures of dementia not included in the discriminant function. Moreover, a majority of demented PD patients (65% were classified as having an HD-like pattern of cognitive deficits, in line with previous reports of the subcortical nature of PD dementia. This approach may thus be useful in classifying presence or absence of dementia and in discriminating between dementia subtypes in cases of secondary or coincidental dementia.

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

Science.gov (United States)

Ferragina, Paolo; Giancarlo, Raffaele; Greco, Valentina; Manzini, Giovanni; Valiente, Gabriel

2007-07-13

Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rather than a formula quantifying the similarity of two strings. Three approximations of USM are available, namely UCD (Universal Compression Dissimilarity), NCD (Normalized Compression Dissimilarity) and CD (Compression Dissimilarity). Their applicability and robustness is tested on various data sets yielding a first massive quantitative estimate that the USM methodology and its approximations are of value. Despite the rich theory developed around USM, its experimental assessment has limitations: only a few data compressors have been tested in conjunction with USM and mostly at a qualitative level, no comparison among UCD, NCD and CD is available and no comparison of USM with existing methods, both based on alignments and not, seems to be available. We experimentally test the USM methodology by using 25 compressors, all three of its known approximations and six data sets of relevance to Molecular Biology. This offers the first systematic and quantitative experimental assessment of this methodology, that naturally complements the many theoretical and the preliminary experimental results available. Moreover, we compare the USM methodology both with methods based on alignments and not. We may group our experiments into two sets. The first one, performed via ROC (Receiver Operating Curve) analysis, aims at

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment

Directory of Open Access Journals (Sweden)

Manzini Giovanni

2007-07-01

Full Text Available Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rather than a formula quantifying the similarity of two strings. Three approximations of USM are available, namely UCD (Universal Compression Dissimilarity, NCD (Normalized Compression Dissimilarity and CD (Compression Dissimilarity. Their applicability and robustness is tested on various data sets yielding a first massive quantitative estimate that the USM methodology and its approximations are of value. Despite the rich theory developed around USM, its experimental assessment has limitations: only a few data compressors have been tested in conjunction with USM and mostly at a qualitative level, no comparison among UCD, NCD and CD is available and no comparison of USM with existing methods, both based on alignments and not, seems to be available. Results We experimentally test the USM methodology by using 25 compressors, all three of its known approximations and six data sets of relevance to Molecular Biology. This offers the first systematic and quantitative experimental assessment of this methodology, that naturally complements the many theoretical and the preliminary experimental results available. Moreover, we compare the USM methodology both with methods based on alignments and not. We may group our experiments into two sets. The first one, performed via ROC

Rapid classification of biological components

Energy Technology Data Exchange (ETDEWEB)

Thompson, Vicki S.; Barrett, Karen B.; Key, Diane E.

2013-10-15

A method is disclosed for analyzing a biological sample by antibody profiling for identifying forensic samples or for detecting the presence of an analyte. In an illustrative embodiment of the invention, the analyte is a drug, such as marijuana, cocaine (crystalline tropane alkaloid), methamphetamine, methyltestosterone, or mesterolone. The method involves attaching antigens to a surface of a solid support in a preselected pattern to form an array wherein the locations of the antigens are known; contacting the array with the biological sample such that a portion of antibodies in the sample reacts with and binds to antigens in the array, thereby forming immune complexes; washing away antibodies that do not form immune complexes; and detecting the immune complexes, thereby forming an antibody profile. Forensic samples are identified by comparing a sample from an unknown source with a sample from a known source. Further, an assay, such as a test for illegal drug use, can be coupled to a test for identity such that the results of the assay can be positively correlated to a subject's identity.

Rapid classification of biological components

Energy Technology Data Exchange (ETDEWEB)

Thompson, Vicki S. (Idaho Falls, ID); Barrett, Karen B. (Meridian, ID); Key, Diane E. (Idaho Falls, ID)

2010-03-23

A method is disclosed for analyzing a biological sample by antibody profiling for identifying forensic samples or for detecting the presence of an analyte. In an illustrative embodiment of the invention, the analyte is a drug, such as marijuana, cocaine (crystalline tropane alkaloid), methamphetamine, methyltestosterone, or mesterolone. The method involves attaching antigens to a surface of a solid support in a preselected pattern to form an array wherein the locations of the antigens are known; contacting the array with the biological sample such that a portion of antibodies in the sample reacts with and binds to antigens in the array, thereby forming immune complexes; washing away antibodies that do not form immune complexes; and detecting the immune complexes, thereby forming an antibody profile. Forensic samples are identified by comparing a sample from an unknown source with a sample from a known source. Further, an assay, such as a test for illegal drug use, can be coupled to a test for identity such that the results of the assay can be positively correlated to a subject's identity.

Rapid classification of biological components

Energy Technology Data Exchange (ETDEWEB)

Thompson, Vicki S. (Idaho Falls, ID); Barrett, Karen B. (Meridian, ID); Key, Diane E. (Idaho Falls, ID)

2010-03-23

A method is disclosed for analyzing a biological sample by antibody profiling for identifying forensic samples or for detecting the presence of an analyte. In an illustrative embodiment of the invention, the analyte is a drug, such as marijuana, Cocaine (crystalline tropane alkaloid), methamphetamine, methyltestosterone, or mesterolone. The method involves attaching antigens of the surface of a solid support in a preselected pattern to form an array wherein the locations of the antigens are known; contacting the array with the biological sample such that a portion of antibodies in the sample reacts with and binds to antigens in the array, thereby forming immune complexes; washing away antibodies that do not form immune complexes; and detecting the immune complexes, thereby forming an antibody profile. Forensic samples are identified by comparing a sample from an unknown source with a sample from a known source. Further, an assay, such as a test for illegal drug use, can be coupled to a test for identity such that the results of the assay can be positively correlated to a subject's identity.

Rapid classification of biological components

Energy Technology Data Exchange (ETDEWEB)

Thompson, Vicki S.; Barrett, Karen B.; Key, Diane E.

2006-01-24

A method is disclosed for analyzing a biological sample by antibody profiling for identifying forensic samples or for detecting the presence of an analyte. In an illustrative embodiment of the invention, the analyte is a drug, such as marijuana, cocaine, methamphetamine, methyltestosterone, or mesterolone. The method involves attaching antigens to the surface of a solid support in a preselected pattern to form an array wherein the locations of the antigens are known; contacting the array with the biological sample such that a portion of antibodies in the sample reacts with and binds to antigens in the array, thereby forming immune complexes; washing away antibodies that do form immune complexes; and detecting the immune complexes, thereby forming an antibody profile. Forensic samples are identified by comparing a sample from an unknown source with a sample from a known source. Further, an assay, such as a test for illegal drug use, can be coupled to a test for identity such that the results of the assay can be positively correlated to the subject's identity.

Genome-Wide Comparative Gene Family Classification

Science.gov (United States)

Frech, Christian; Chen, Nansheng

2010-01-01

Correct classification of genes into gene families is important for understanding gene function and evolution. Although gene families of many species have been resolved both computationally and experimentally with high accuracy, gene family classification in most newly sequenced genomes has not been done with the same high standard. This project has been designed to develop a strategy to effectively and accurately classify gene families across genomes. We first examine and compare the performance of computer programs developed for automated gene family classification. We demonstrate that some programs, including the hierarchical average-linkage clustering algorithm MC-UPGMA and the popular Markov clustering algorithm TRIBE-MCL, can reconstruct manual curation of gene families accurately. However, their performance is highly sensitive to parameter setting, i.e. different gene families require different program parameters for correct resolution. To circumvent the problem of parameterization, we have developed a comparative strategy for gene family classification. This strategy takes advantage of existing curated gene families of reference species to find suitable parameters for classifying genes in related genomes. To demonstrate the effectiveness of this novel strategy, we use TRIBE-MCL to classify chemosensory and ABC transporter gene families in C. elegans and its four sister species. We conclude that fully automated programs can establish biologically accurate gene families if parameterized accordingly. Comparative gene family classification finds optimal parameters automatically, thus allowing rapid insights into gene families of newly sequenced species. PMID:20976221

Aspen biology, community classification, and management in the Blue Mountains

Science.gov (United States)

David K. Swanson; Craig L. Schmitt; Diane M. Shirley; Vicky Erickson; Kenneth J. Schuetz; Michael L. Tatum; David C. Powell

2010-01-01

Quaking aspen (Populus tremuloides Michx.) is a valuable species that is declining in the Blue Mountains of northeastern Oregon. This publication is a compilation of over 20 years of aspen management experience by USDA Forest Service workers in the Blue Mountains. It includes a summary of aspen biology and occurrence in the Blue Mountains, and a...

ASIST SIG/CR Classification Workshop 2000: Classification for User Support and Learning.

Science.gov (United States)

Soergel, Dagobert

2001-01-01

Reports on papers presented at the 62nd Annual Meeting of ASIST (American Society for Information Science and Technology) for the Special Interest Group in Classification Research (SIG/CR). Topics include types of knowledge; developing user-oriented classifications, including domain analysis; classification in the user interface; and automatic…

The Classification of Living Things: Nature in the Classroom.

Science.gov (United States)

Doyle, Charles

1982-01-01

Use of a classification system in teaching biology is presented as a concept aiding students' understanding of the diversity of plants and animals. The principles of classification are summarized and six learning strategies are given to show relationships among groups. (CM)

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

Science.gov (United States)

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

Information gathering for CLP classification

Directory of Open Access Journals (Sweden)

Ida Marcello

2011-01-01

Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

Genetic Bio-Ancestry and Social Construction of Racial Classification in Social Surveys in the Contemporary United States

Science.gov (United States)

Guo, Guang; Fu, Yilan; Lee, Hedwig; Cai, Tianji; Harris, Kathleen Mullan; Li, Yi

2013-01-01

Self-reported race is generally considered the basis for racial classification in social surveys, including the U.S. census. Drawing on recent advances in human molecular genetics and social science perspectives of socially constructed race, our study takes into account both genetic bio-ancestry and social context in understanding racial classification. This article accomplishes two objectives. First, our research establishes geographic genetic bio-ancestry as a component of racial classification. Second, it shows how social forces trump biology in racial classification and/or how social context interacts with bio-ancestry in shaping racial classification. The findings were replicated in two racially and ethnically diverse data sets: the College Roommate Study (N = 2,065) and the National Longitudinal Study of Adolescent Health (N = 2,281). PMID:24019100

Classifying Life, Reconstructing History and Teaching Diversity: Philosophical Issues in the Teaching of Biological Systematics and Biodiversity

Science.gov (United States)

Reydon, Thomas A. C.

2013-01-01

Classification is a central endeavor in every scientific field of work. Classification in biology, however, is distinct from classification in other fields of science in a number of ways. Thus, understanding how biological classification works is an important element in understanding the nature of biological science. In the present paper, I…

[Definition, etiology, classification and presentation forms].

Science.gov (United States)

Mas Garriga, Xavier

2014-01-01

Osteoarthritis is defined as a degenerative process affecting the joints as a result of mechanical and biological disorders that destabilize the balance between the synthesis and degradation of joint cartilage, stimulating the growth of subchondral bone; chronic synovitis is also present. Currently, the joint is considered as a functional unit that includes distinct tissues, mainly cartilage, the synovial membrane, and subchondral bone, all of which are involved in the pathogenesis of the disease. Distinct risk factors for the development of osteoarthritis have been described: general, unmodifiable risk factors (age, sex, and genetic makeup), general, modifiable risk factors (obesity and hormonal factors) and local risk factors (prior joint anomalies and joint overload). Notable among the main factors related to disease progression are joint alignment defects and generalized osteoarthritis. Several classifications of osteoarthritis have been proposed but none is particularly important for the primary care management of the disease. These classifications include etiological (primary or idiopathic forms and secondary forms) and topographical (typical and atypical localizations) classifications, the Kellgren and Lawrence classification (radiological repercussions) and that of the American College of Rheumatology for osteoarthritis of the hand, hip and knee. The prevalence of knee osteoarthritis is 10.2% in Spain and shows a marked discrepancy between clinical and radiological findings. Hand osteoarthritis, with a prevalence of symptomatic involvement of around 6.2%, has several forms of presentation (nodal osteoarthritis, generalized osteoarthritis, rhizarthrosis, and erosive osteoarthritis). Symptomatic osteoarthritis of the hip affects between 3.5% and 5.6% of persons older than 50 years and has different radiological patterns depending on femoral head migration. Copyright © 2014 Elsevier España, S.L. All rights reserved.

Molecular Classification and Correlates in Colorectal Cancer

OpenAIRE

Ogino, Shuji; Goel, Ajay

2008-01-01

Molecular classification of colorectal cancer is evolving. As our understanding of colorectal carcinogenesis improves, we are incorporating new knowledge into the classification system. In particular, global genomic status [microsatellite instability (MSI) status and chromosomal instability (CIN) status] and epigenomic status [CpG island methylator phenotype (CIMP) status] play a significant role in determining clinical, pathological and biological characteristics of colorectal cancer. In thi...

Controlled Carbon Source Addition to an Alternating Nitrification-Denitrification Wastewater Treatment Process Including Biological P Removal

DEFF Research Database (Denmark)

Isaacs, Steven Howard; Henze, Mogens

1995-01-01

The paper investigates the effect of adding an external carbon source on the rate of denitrification in an alternating activated sludge process including biological P removal. Two carbon sources were examined, acetate and hydrolysate derived from biologically hydrolyzed sludge. Preliminary batch ...

A three-way approach for protein function classification.

Directory of Open Access Journals (Sweden)

Hafeez Ur Rehman

Full Text Available The knowledge of protein functions plays an essential role in understanding biological cells and has a significant impact on human life in areas such as personalized medicine, better crops and improved therapeutic interventions. Due to expense and inherent difficulty of biological experiments, intelligent methods are generally relied upon for automatic assignment of functions to proteins. The technological advancements in the field of biology are improving our understanding of biological processes and are regularly resulting in new features and characteristics that better describe the role of proteins. It is inevitable to neglect and overlook these anticipated features in designing more effective classification techniques. A key issue in this context, that is not being sufficiently addressed, is how to build effective classification models and approaches for protein function prediction by incorporating and taking advantage from the ever evolving biological information. In this article, we propose a three-way decision making approach which provides provisions for seeking and incorporating future information. We considered probabilistic rough sets based models such as Game-Theoretic Rough Sets (GTRS and Information-Theoretic Rough Sets (ITRS for inducing three-way decisions. An architecture of protein functions classification with probabilistic rough sets based three-way decisions is proposed and explained. Experiments are carried out on Saccharomyces cerevisiae species dataset obtained from Uniprot database with the corresponding functional classes extracted from the Gene Ontology (GO database. The results indicate that as the level of biological information increases, the number of deferred cases are reduced while maintaining similar level of accuracy.

Whewell on classification and consilience.

Science.gov (United States)

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.

Refinement of diagnosis and disease classification in psychiatry.

Science.gov (United States)

Lecrubier, Yves

2008-03-01

Knowledge concerning the classification of mental disorders progressed substantially with the use of DSM III-IV and IDCD 10 because it was based on observed data, with precise definitions. These classifications a priori avoided to generate definitions related to etiology or treatment response. They are based on a categorical approach where diagnostic entities share common phenomenological features. Modifications proposed or discussed are related to the weak validity of the classification strategy described above. (a) Disorders are supposed to be independent but the current coexistence of two or more disorders is the rule; (b) They also are supposed to have stability, however anxiety disorders most of the time precede major depression. For GAD age at onset, family history, biology and symptomatology are close to those of depression. As a consequence broader entities such as depression-GAD spectrum, panic-phobias spectrum and OCD spectrum including eating disorders and pathological gambling are taken into consideration; (c) Diagnostic categories use thresholds to delimitate a border with normals. This creates "subthreshold" conditions. The relevance of such conditions is well documented. Measuring the presence and severity of different dimensions, independent from a threshold, will improve the relevance of the description of patients pathology. In addition, this dimensional approach will improve the problems posed by the mutually exclusive diagnoses (depression and GAD, schizophrenia and depression); (d) Some disorders are based on the coexistence of different dimensions. Patients may present only one set of symptoms and have different characteristics, evolution and response to treatment. An example would be negative symptoms in Schizophrenia; (e) Because no etiological model is available and most measures are subjective, objective measures (cognitive, biological) and genetics progresses created important hopes. None of these measures is pathognomonic and most appear

Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network.

Science.gov (United States)

Li, Na; Zhao, Xinbo; Yang, Yongjia; Zou, Xiaochun

2016-01-01

Humans can easily classify different kinds of objects whereas it is quite difficult for computers. As a hot and difficult problem, objects classification has been receiving extensive interests with broad prospects. Inspired by neuroscience, deep learning concept is proposed. Convolutional neural network (CNN) as one of the methods of deep learning can be used to solve classification problem. But most of deep learning methods, including CNN, all ignore the human visual information processing mechanism when a person is classifying objects. Therefore, in this paper, inspiring the completed processing that humans classify different kinds of objects, we bring forth a new classification method which combines visual attention model and CNN. Firstly, we use the visual attention model to simulate the processing of human visual selection mechanism. Secondly, we use CNN to simulate the processing of how humans select features and extract the local features of those selected areas. Finally, not only does our classification method depend on those local features, but also it adds the human semantic features to classify objects. Our classification method has apparently advantages in biology. Experimental results demonstrated that our method made the efficiency of classification improve significantly.

American College of Rheumatology classification criteria for Sjögren's syndrome

DEFF Research Database (Denmark)

Shiboski, S C; Shiboski, C H; Criswell, L A

2012-01-01

We propose new classification criteria for Sjögren's syndrome (SS), which are needed considering the emergence of biologic agents as potential treatments and their associated comorbidity. These criteria target individuals with signs/symptoms suggestive of SS.......We propose new classification criteria for Sjögren's syndrome (SS), which are needed considering the emergence of biologic agents as potential treatments and their associated comorbidity. These criteria target individuals with signs/symptoms suggestive of SS....

Biological treatment of inorganic ion contamination including radionuclides

Energy Technology Data Exchange (ETDEWEB)

Cherry, R S [Idaho National Engineering and Environmental Lab., Idaho Falls, ID (United States)

1997-12-01

Microorganisms and plants are capable of a broad range of activities useful in treating inorganic contaminants in soil, groundwater, and surface runoff water Among the advantages of biological processes for this purpose are relatively low costs (related to their mild conditions) and the practicality of letting them run unattended. This talk will review both kinds of treatment chemistry that can be done biologically as well as present data from INEEL projects on bioremediation of specific elements. Biological processes can either solubilize or immobilize metals and other ions depending on the need. Uranium ions are solubilized from soil by the local bioproduction of organic acids as chelating agents, allowing removal of this ion as part of an ex-situ treatment process. Further, the microbial production of sulfuric acid can be used to solubilize Cs contamination in concrete surfaces. More usual though is the need to control metal movement in soil or water. Various metals such as Se and Cd are taken up from soil by hyper-accumulating plants, where they can be harvested in concentrated form in the leaves and stems. Excess acidity and a broad variety of toxic metals in acid rock drainage, such as Hg, Cd, Zn and others, can be removed by the production of sulfide ion in an easily fielded biological reactor which may be useful on phosphate processing runoff water contaminated with naturally occuring radioactive materials. Soluble Co, Cu, and Cd can be treated by sorption onto immobilized algae. Inorganic ions can also be directly reduced by bacteria as part of treatment, for example the conversion of soluble selenate ion to insoluble elemental selenium and the conversion of highly toxic CR(VI) to the far less soluble and less toxic Cr(III).

Biological treatment of inorganic ion contamination including radionuclides

International Nuclear Information System (INIS)

Cherry, R.S.

1997-01-01

Microorganisms and plants are capable of a broad range of activities useful in treating inorganic contaminants in soil, groundwater, and surface runoff water Among the advantages of biological processes for this purpose are relatively low costs (related to their mild conditions) and the practicality of letting them run unattended. This talk will review both kinds of treatment chemistry that can be done biologically as well as present data from INEEL projects on bioremediation of specific elements. Biological processes can either solubilize or immobilize metals and other ions depending on the need. Uranium ions are solubilized from soil by the local bioproduction of organic acids as chelating agents, allowing removal of this ion as part of an ex-situ treatment process. Further, the microbial production of sulfuric acid can be used to solubilize Cs contamination in concrete surfaces. More usual though is the need to control metal movement in soil or water. Various metals such as Se and Cd are taken up from soil by hyper-accumulating plants, where they can be harvested in concentrated form in the leaves and stems. Excess acidity and a broad variety of toxic metals in acid rock drainage, such as Hg, Cd, Zn and others, can be removed by the production of sulfide ion in an easily fielded biological reactor which may be useful on phosphate processing runoff water contaminated with naturally occuring radioactive materials. Soluble Co, Cu, and Cd can be treated by sorption onto immobilized algae. Inorganic ions can also be directly reduced by bacteria as part of treatment, for example the conversion of soluble selenate ion to insoluble elemental selenium and the conversion of highly toxic CR(VI) to the far less soluble and less toxic Cr(III)

Towards a unified classification of the ectodermal dysplasias: opportunities outweigh challenges.

LENUS (Irish Health Repository)

Irvine, Alan D

2012-02-01

The ectodermal dysplasias include a complex and highly diverse group of heritable disorders that share in common developmental abnormalities of ectodermal derivatives. The broader definition of ectodermal dysplasias (as heritable disorders involving at least two of the ectodermal derivatives nails, teeth, hair, and eccrine sweat glands) encompasses 170-200 conditions. Some conditions included by this definition are relatively common; others are rare and, in some cases, family-specific. Classification of the ectodermal dysplasias has largely been approached by categorizing patterns of clinical findings (phenotypic grouping). In the last 2 decades great progress has been made in understanding the molecular pathogenesis and inter-relatedness of some of these conditions and a new consensus approach to classification that incorporates this new information is needed. A comprehensive and definitive classification of these disorders would be highly valuable for the many stakeholders in ED. As disease-specific molecular treatments are developed, accurate classification will assume greater importance in designing registries to enable rapid identification of those with rare disorders who may wish to participate in clinical trials. Ideally a working classification of such a disparate collection of conditions would have a design and architecture that would facilitate easy accessibility by each of the key stakeholder groups and would encourage enhanced interaction between these parties. Attaining this objective is a major challenge but is achievable. This article reviews the historical-clinical perspective and the impact of recent developments in molecular biology in the field. Reflections are offered as to the future direction of classification systems in these disorders.

Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification.

Science.gov (United States)

Doostparast Torshizi, Abolfazl; Petzold, Linda R

2018-01-01

Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects of different biological data types can boost learning capabilities and lead to a better understanding of the underlying interactions among molecular levels. In this paper we present a graph-based semi-supervised classification algorithm that incorporates latent biological knowledge in the form of biological pathways with gene expression and DNA methylation data. The process of graph construction from biological pathways is based on detecting condition-responsive genes, where 3 sets of genes are finally extracted: all condition responsive genes, high-frequency condition-responsive genes, and P-value-filtered genes. The proposed approach is applied to ovarian cancer data downloaded from the Human Genome Atlas. Extensive numerical experiments demonstrate superior performance of the proposed approach compared to other state-of-the-art algorithms, including the latest graph-based classification techniques. Simulation results demonstrate that integrating various data types enhances classification performance and leads to a better understanding of interrelations between diverse omics data types. The proposed approach outperforms many of the state-of-the-art data integration algorithms. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

SPORT FOOD ADDITIVE CLASSIFICATION

Directory of Open Access Journals (Sweden)

I. P. Prokopenko

2015-01-01

Full Text Available Correctly organized nutritive and pharmacological support is an important component of an athlete's preparation for competitions, an optimal shape maintenance, fast recovery and rehabilitation after traumas and defatigation. Special products of enhanced biological value (BAS for athletes nutrition are used with this purpose. Easy-to-use energy sources are administered into athlete's organism, yielded materials and biologically active substances which regulate and activate exchange reactions which proceed with difficulties during certain physical trainings. The article presents sport supplements classification which can be used before warm-up and trainings, after trainings and in competitions breaks.

Using biological indices to classify schizophrenia and other psychotic patients.

Science.gov (United States)

Sponheim, S R; Iacono, W G; Thuras, P D; Beiser, M

2001-07-01

Although classification of mental disorders using more than clinical description would be desirable, there is scant evidence that available laboratory tests (i.e. biological indices) would provide more valid classifications than current diagnostic systems (e.g. DSM-IV). We used cluster analysis of four biological variables to classify 163 psychotic patients and 83 nonpsychiatric comparison subjects. Analyses revealed a three-cluster solution with the first cluster reflecting electrodermal deviance, the second cluster representing nondeviant biological function, and the third cluster reflecting increased nailfold plexus visibility and ocular motor dysfunction. To assess the construct validity of proband clusters we examined ocular motor performance in 156 first-degree relatives as a function of proband cluster membership. First-degree relatives of third cluster probands exhibited worse ocular motor performance than relatives of other cluster probands. Additionally, better classification sensitivity and specificity were obtained for the relatives when they were grouped by proband cluster than by proband DSM-IV diagnosis. When a single proband characteristic (i.e. eyetracking performance) was used to group relatives, classification sensitivity and specificity failed to significantly increase over grouping by proband DSM-IV diagnosis. Multivariate biologically defined clusters may offer an advantage over DSM-IV classification when examining nosology and etiology of psychotic disorders.

Modern classification of neoplasms: reconciling differences between morphologic and molecular approaches

International Nuclear Information System (INIS)

Berman, Jules

2005-01-01

classification of neoplasms should guide the rational design and selection of a new generation of cancer medications targeted to metabolic pathways. Without a scientifically sound neoplasm classification, biological measurements on individual tumor samples cannot be generalized to class-related tumors, and constitutive properties common to a class of tumors cannot be distinguished from uninformative data in complex and chaotic biological systems. This paper discusses the importance of biological classification and examines several different approaches to the specific problem of tumor classification

Teaching Methods in Biology Education and Sustainability Education Including Outdoor Education for Promoting Sustainability--A Literature Review

Science.gov (United States)

Jeronen, Eila; Palmberg, Irmeli; Yli-Panula, Eija

2017-01-01

There are very few studies concerning the importance of teaching methods in biology education and environmental education including outdoor education for promoting sustainability at the levels of primary and secondary schools and pre-service teacher education. The material was selected using special keywords from biology and sustainable education…

Classification of EEG Signals using adaptive weighted distance nearest neighbor algorithm

Directory of Open Access Journals (Sweden)

E. Parvinnia

2014-01-01

Full Text Available Electroencephalogram (EEG signals are often used to diagnose diseases such as seizure, alzheimer, and schizophrenia. One main problem with the recorded EEG samples is that they are not equally reliable due to the artifacts at the time of recording. EEG signal classification algorithms should have a mechanism to handle this issue. It seems that using adaptive classifiers can be useful for the biological signals such as EEG. In this paper, a general adaptive method named weighted distance nearest neighbor (WDNN is applied for EEG signal classification to tackle this problem. This classification algorithm assigns a weight to each training sample to control its influence in classifying test samples. The weights of training samples are used to find the nearest neighbor of an input query pattern. To assess the performance of this scheme, EEG signals of thirteen schizophrenic patients and eighteen normal subjects are analyzed for the classification of these two groups. Several features including, fractal dimension, band power and autoregressive (AR model are extracted from EEG signals. The classification results are evaluated using Leave one (subject out cross validation for reliable estimation. The results indicate that combination of WDNN and selected features can significantly outperform the basic nearest-neighbor and the other methods proposed in the past for the classification of these two groups. Therefore, this method can be a complementary tool for specialists to distinguish schizophrenia disorder.

Computational aspects of systematic biology.

Science.gov (United States)

Lilburn, Timothy G; Harrison, Scott H; Cole, James R; Garrity, George M

2006-06-01

We review the resources available to systematic biologists who wish to use computers to build classifications. Algorithm development is in an early stage, and only a few examples of integrated applications for systematic biology are available. The availability of data is crucial if systematic biology is to enter the computer age.

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

Science.gov (United States)

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

) biology; (3) terminology; (4) mapping; and (5) future development. The workshop ended with a declaration from the attendees, with recommendations to the EEA and European Topic Centre on Biological Diversity, to take into account the outputs of the workshop, which identify weaknesses in the current classification and include proposals for its modification, and to devise a process to further develop the marine component of the EUNIS habitat classification. Copyright © 2012 Elsevier Ltd. All rights reserved.

Toward a Reasoned Classification of Diseases Using Physico-Chemical Based Phenotypes

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Laurent Schwartz

2018-02-01

Full Text Available Background: Diseases and health conditions have been classified according to anatomical site, etiological, and clinical criteria. Physico-chemical mechanisms underlying the biology of diseases, such as the flow of energy through cells and tissues, have been often overlooked in classification systems.Objective: We propose a conceptual framework toward the development of an energy-oriented classification of diseases, based on the principles of physical chemistry.Methods: A review of literature on the physical chemistry of biological interactions in a number of diseases is traced from the point of view of the fluid and solid mechanics, electricity, and chemistry.Results: We found consistent evidence in literature of decreased and/or increased physical and chemical forces intertwined with biological processes of numerous diseases, which allowed the identification of mechanical, electric and chemical phenotypes of diseases.Discussion: Biological mechanisms of diseases need to be evaluated and integrated into more comprehensive theories that should account with principles of physics and chemistry. A hypothetical model is proposed relating the natural history of diseases to mechanical stress, electric field, and chemical equilibria (ATP changes. The present perspective toward an innovative disease classification may improve drug-repurposing strategies in the future.

Toward a Reasoned Classification of Diseases Using Physico-Chemical Based Phenotypes

Science.gov (United States)

Schwartz, Laurent; Lafitte, Olivier; da Veiga Moreira, Jorgelindo

2018-01-01

Background: Diseases and health conditions have been classified according to anatomical site, etiological, and clinical criteria. Physico-chemical mechanisms underlying the biology of diseases, such as the flow of energy through cells and tissues, have been often overlooked in classification systems. Objective: We propose a conceptual framework toward the development of an energy-oriented classification of diseases, based on the principles of physical chemistry. Methods: A review of literature on the physical chemistry of biological interactions in a number of diseases is traced from the point of view of the fluid and solid mechanics, electricity, and chemistry. Results: We found consistent evidence in literature of decreased and/or increased physical and chemical forces intertwined with biological processes of numerous diseases, which allowed the identification of mechanical, electric and chemical phenotypes of diseases. Discussion: Biological mechanisms of diseases need to be evaluated and integrated into more comprehensive theories that should account with principles of physics and chemistry. A hypothetical model is proposed relating the natural history of diseases to mechanical stress, electric field, and chemical equilibria (ATP) changes. The present perspective toward an innovative disease classification may improve drug-repurposing strategies in the future. PMID:29541031

Revealing Significant Relations between Chemical/Biological Features and Activity: Associative Classification Mining for Drug Discovery

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Yu, Pulan

2012-01-01

Classification, clustering and association mining are major tasks of data mining and have been widely used for knowledge discovery. Associative classification mining, the combination of both association rule mining and classification, has emerged as an indispensable way to support decision making and scientific research. In particular, it offers a…

Automatic Classification Using Supervised Learning in a Medical Document Filtering Application.

Science.gov (United States)

Mostafa, J.; Lam, W.

2000-01-01

Presents a multilevel model of the information filtering process that permits document classification. Evaluates a document classification approach based on a supervised learning algorithm, measures the accuracy of the algorithm in a neural network that was trained to classify medical documents on cell biology, and discusses filtering…

Linking Biological Responses of Terrestrial N Eutrophication to the Final Ecosystem Goods and Services Classification System

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Bell, M. D.; Clark, C.; Blett, T.

2015-12-01

The response of a biological indicator to N deposition can indicate that an ecosystem has surpassed a critical load and is at risk of significant change. The importance of this exceedance is often difficult to digest by policy makers and public audiences if the change is not linked to a familiar ecosystem endpoint. A workshop was held to bring together scientists, resource managers, and policy makers with expertise in ecosystem functioning, critical loads, and economics in an effort to identify the ecosystem services impacted by air pollution. This was completed within the framework of the Final Ecosystem Goods and Services (FEGS) Classification System to produce a product that identified distinct interactions between society and the effects of nitrogen pollution. From each change in a biological indicator, we created multiple ecological production functions to identify the cascading effects of the change to a measureable ecosystem service that a user interacts with either by enjoying, consuming, or appreciating the good or service, or using it as an input in the human economy. This FEGS metric was then linked to a beneficiary group that interacts with the service. Chains detailing the links from the biological indicator to the beneficiary group were created for aquatic and terrestrial acidification and eutrophication at the workshop, and here we present a subset of the workshop results by highlighting for 9 different ecosystems affected by terrestrial eutrophication. A total of 213 chains that linked to 37 unique FEGS metrics and impacted 15 beneficiary groups were identified based on nitrogen deposition mediated changes to biological indicators. The chains within each ecosystem were combined in flow charts to show the complex, overlapping relationships among biological indicators, ecosystem services, and beneficiary groups. Strength of relationship values were calculated for each chain based on support for the link in the scientific literature. We produced the

Racial classification in the evolutionary sciences: a comparative analysis.

Science.gov (United States)

Billinger, Michael S

2007-01-01

Human racial classification has long been a problem for the discipline of anthropology, but much of the criticism of the race concept has focused on its social and political connotations. The central argument of this paper is that race is not a specifically human problem, but one that exists in evolutionary thought in general. This paper looks at various disciplinary approaches to racial or subspecies classification, extending its focus beyond the anthropological race concept by providing a comparative analysis of the use of racial classification in evolutionary biology, genetics, and anthropology.

On the classification of long non-coding RNAs

KAUST Repository

Ma, Lina

2013-06-01

Long non-coding RNAs (lncRNAs) have been found to perform various functions in a wide variety of important biological processes. To make easier interpretation of lncRNA functionality and conduct deep mining on these transcribed sequences, it is convenient to classify lncRNAs into different groups. Here, we summarize classification methods of lncRNAs according to their four major features, namely, genomic location and context, effect exerted on DNA sequences, mechanism of functioning and their targeting mechanism. In combination with the presently available function annotations, we explore potential relationships between different classification categories, and generalize and compare biological features of different lncRNAs within each category. Finally, we present our view on potential further studies. We believe that the classifications of lncRNAs as indicated above are of fundamental importance for lncRNA studies, helpful for further investigation of specific lncRNAs, for formulation of new hypothesis based on different features of lncRNA and for exploration of the underlying lncRNA functional mechanisms. © 2013 Landes Bioscience.

Biogeographic classification of the Caspian Sea

DEFF Research Database (Denmark)

Fendereski, F.; Vogt, M.; Payne, Mark

2014-01-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information deriv...... confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics....... from space and in-situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions...... in phytoplankton phenology, with differences in the date of bloom initiation, its duration and amplitude between ecoregions. A first qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 27 different species of plankton, fish and benthic invertebrate also...

Biogeographic classification of the Caspian Sea

Science.gov (United States)

Fendereski, F.; Vogt, M.; Payne, M. R.; Lachkar, Z.; Gruber, N.; Salmanmahiny, A.; Hosseini, S. A.

2014-11-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information derived from space and in situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions using the hierarchical agglomerative clustering (HAC) method. From an initial set of 12 potential physical variables, 6 independent variables were selected for the classification algorithm, i.e., sea surface temperature (SST), bathymetry, sea ice, seasonal variation of sea surface salinity (DSSS), total suspended matter (TSM) and its seasonal variation (DTSM). The classification results reveal a robust separation between the northern and the middle/southern basins as well as a separation of the shallow nearshore waters from those offshore. The observed patterns in ecoregions can be attributed to differences in climate and geochemical factors such as distance from river, water depth and currents. A comparison of the annual and monthly mean Chl a concentrations between the different ecoregions shows significant differences (one-way ANOVA, P qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 25 different species of plankton, fish and benthic invertebrate also confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics.

Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

Energy Technology Data Exchange (ETDEWEB)

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Giger, Maryellen L.; Li, Hui [Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States); Duewer, Fred; Malkov, Serghei; Joe, Bonnie; Kerlikowske, Karla; Shepherd, John A. [Radiology Department, University of California, San Francisco, California 94143 (United States); Flowers, Chris I. [Department of Radiology, University of South Florida, Tampa, Florida 33612 (United States); Drukteinis, Jennifer S. [Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida 33612 (United States)

2014-03-15

Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CB alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.

Fabric Weave Pattern and Yarn Color Recognition and Classification Using a Deep ELM Network

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Babar Khan

2017-10-01

Full Text Available Usually, a fabric weave pattern is recognized using methods which identify the warp floats and weft floats. Although these methods perform well for uniform or repetitive weave patterns, in the case of complex weave patterns, these methods become computationally complex and the classification error rates are comparatively higher. Furthermore, the fault-tolerance (invariance and stability (selectivity of the existing methods are still to be enhanced. We present a novel biologically-inspired method to invariantly recognize the fabric weave pattern (fabric texture and yarn color from the color image input. We proposed a model in which the fabric weave pattern descriptor is based on the HMAX model for computer vision inspired by the hierarchy in the visual cortex, the color descriptor is based on the opponent color channel inspired by the classical opponent color theory of human vision, and the classification stage is composed of a multi-layer (deep extreme learning machine. Since the weave pattern descriptor, yarn color descriptor, and the classification stage are all biologically inspired, we propose a method which is completely biologically plausible. The classification performance of the proposed algorithm indicates that the biologically-inspired computer-aided-vision models might provide accurate, fast, reliable and cost-effective solution to industrial automation.

Security classification of information

Energy Technology Data Exchange (ETDEWEB)

Quist, A.S.

1993-04-01

This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

Barrett's esophagus: cancer and molecular biology.

Science.gov (United States)

Gibson, Michael K; Dhaliwal, Arashinder S; Clemons, Nicholas J; Phillips, Wayne A; Dvorak, Katerina; Tong, Daniel; Law, Simon; Pirchi, E Daniel; Räsänen, Jari; Krasna, Mark J; Parikh, Kaushal; Krishnadath, Kausilia K; Chen, Yu; Griffiths, Leonard; Colleypriest, Benjamin J; Farrant, J Mark; Tosh, David; Das, Kiron M; Bajpai, Manisha

2013-10-01

The following paper on the molecular biology of Barrett's esophagus (BE) includes commentaries on signaling pathways central to the development of BE including Hh, NF-κB, and IL-6/STAT3; surgical approaches for esophagectomy and classification of lesions by appropriate therapy; the debate over the merits of minimally invasive esophagectomy versus open surgery; outcomes for patients with pharyngolaryngoesophagectomy; the applications of neoadjuvant chemotherapy and chemoradiotherapy; animal models examining the surgical models of BE and esophageal adenocarcinoma; the roles of various morphogens and Cdx2 in BE; and the use of in vitro BE models for chemoprevention studies. © 2013 New York Academy of Sciences.

Munitions Classification Library

Science.gov (United States)

2016-04-04

members of the community to make their own additions to any, or all, of the classification libraries . The next phase entailed data collection over less......Include area code) 04/04/2016 Final Report August 2014 - August 2015 MUNITIONS CLASSIFICATION LIBRARY Mr. Craig Murray, Parsons Dr. Thomas H. Bell, Leidos

Classification of hydrocephalus: critical analysis of classification categories and advantages of "Multi-categorical Hydrocephalus Classification" (Mc HC).

Science.gov (United States)

Oi, Shizuo

2011-10-01

Hydrocephalus is a complex pathophysiology with disturbed cerebrospinal fluid (CSF) circulation. There are numerous numbers of classification trials published focusing on various criteria, such as associated anomalies/underlying lesions, CSF circulation/intracranial pressure patterns, clinical features, and other categories. However, no definitive classification exists comprehensively to cover the variety of these aspects. The new classification of hydrocephalus, "Multi-categorical Hydrocephalus Classification" (Mc HC), was invented and developed to cover the entire aspects of hydrocephalus with all considerable classification items and categories. Ten categories include "Mc HC" category I: onset (age, phase), II: cause, III: underlying lesion, IV: symptomatology, V: pathophysiology 1-CSF circulation, VI: pathophysiology 2-ICP dynamics, VII: chronology, VII: post-shunt, VIII: post-endoscopic third ventriculostomy, and X: others. From a 100-year search of publication related to the classification of hydrocephalus, 14 representative publications were reviewed and divided into the 10 categories. The Baumkuchen classification graph made from the round o'clock classification demonstrated the historical tendency of deviation to the categories in pathophysiology, either CSF or ICP dynamics. In the preliminary clinical application, it was concluded that "Mc HC" is extremely effective in expressing the individual state with various categories in the past and present condition or among the compatible cases of hydrocephalus along with the possible chronological change in the future.

Should over-treatment of axial spondyloarthritis with biologics remain a concern after the issue of the new ASAS criteria? Data from REGISPONSERBIO (Spanish Register of Biological Therapy in Spondyloarthritides).

Science.gov (United States)

Moreno, Mireia; Gratacós, Jordi; Navarro-Compán, Victoria; de Miguel, Eugenio; Font, Pilar; Clavaguera, Teresa; Linares, Luis Francisco; Joven, Beatriz; Juanola, Xavier

2018-05-08

To study whether disease status at treatment initiation has changed after the issue of the ASAS classification criteria. REGISPONSERBIO registers patients with axial spondyloarthritis (axSpA) on biological treatment since 2013. It includes patients starting biological treatment (incident) or already on biological therapies (prevalent). Patients in both groups were compared in terms of: age at disease onset and at treatment start, disease duration, gender, HLA-B27, body mass index (BMI), BASDAI, BASFI, C-reactive protein, ESR, metrological data, ASQoL, WAPAI, extra-articular manifestations, comorbidities, radiological study, type of biological treatment and concomitant treatments. 256 patients were included, of whom 174 (65%) were already on biologic therapy. Compared to incident patients, prevalent patients started treatment with longer disease duration (15 vs. 8.6 years; p<0.001), a higher proportion of them were men (83% vs. 67%; p=0.01), a smaller proportion of them showed non-radiographic axial spondylarthritis (nr-axSpA)(17% vs. 32%; p<0.01), and a higher proportion had HLAB27 (85% vs. 73%; p=0.02). There were no statistically significant differences in terms of disease activity, degree of disability, quality of life, or prevalence of extra-articular manifestations. Data suggest that, after the issue of the new classification criteria for SpA, biological therapy is being administered earlier than previously in SpA patients and in a higher proportion of patients with nr-axSpA. However, this change in prescribing profile, apparently, has not caused an over-treatment, as patients do not seem to have a lower disease burden than prior to the issue of the criteria.

Cancer classification in the genomic era: five contemporary problems.

Science.gov (United States)

Song, Qingxuan; Merajver, Sofia D; Li, Jun Z

2015-10-19

Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., "lung cancer" designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification

Applications of intelligent optimization in biology and medicine current trends and open problems

CERN Document Server

Grosan, Crina; Tolba, Mohamed

2016-01-01

This volume provides updated, in-depth material on the application of intelligent optimization in biology and medicine. The aim of the book is to present solutions to the challenges and problems facing biology and medicine applications. This Volume comprises of 13 chapters, including an overview chapter, providing an up-to-date and state-of-the research on the application of intelligent optimization for bioinformatics applications, DNA based Steganography, a modified Particle Swarm Optimization Algorithm for Solving Capacitated Maximal Covering Location Problem in Healthcare Systems, Optimization Methods for Medical Image Super Resolution Reconstruction and breast cancer classification. Moreover, some chapters that describe several bio-inspired approaches in MEDLINE Text Mining, DNA-Binding Proteins and Classes, Optimized Tumor Breast Cancer Classification using Combining Random Subspace and Static Classifiers Selection Paradigms, and Dental Image Registration. The book will be a useful compendium for a broad...

Green mathematics: Benefits of including biological variation in your data analysis

NARCIS (Netherlands)

Tijskens, L.M.M.; Schouten, R.E.; Unuk, T.; Simcic, M.

2015-01-01

Biological variation is omnipresent in nature. It contains useful information that is neglected by the usually applied statistical procedures. To extract this information special procedures have to be applied. Biological variation is seen in properties (e.g. size, colour, firmness), but the

Integrative Biological Chemistry Program Includes the Use of Informatics Tools, GIS and SAS Software Applications

Science.gov (United States)

D'Souza, Malcolm J.; Kashmar, Richard J.; Hurst, Kent; Fiedler, Frank; Gross, Catherine E.; Deol, Jasbir K.; Wilson, Alora

2015-01-01

Wesley College is a private, primarily undergraduate minority-serving institution located in the historic district of Dover, Delaware (DE). The College recently revised its baccalaureate biological chemistry program requirements to include a one-semester Physical Chemistry for the Life Sciences course and project-based experiential learning…

Standardised classification of pre-release development in male-brooding pipefish, seahorses, and seadragons (Family Syngnathidae)

Science.gov (United States)

2012-01-01

Background Members of the family Syngnathidae share a unique reproductive mode termed male pregnancy. Males carry eggs in specialised brooding structures for several weeks and release free-swimming offspring. Here we describe a systematic investigation of pre-release development in syngnathid fishes, reviewing available data for 17 species distributed across the family. This work is complemented by in-depth examinations of the straight-nosed pipefish Nerophis ophidion, the black-striped pipefish Syngnathus abaster, and the potbellied seahorse Hippocampus abdominalis. Results We propose a standardised classification of early syngnathid development that extends from the activation of the egg to the release of newborn. The classification consists of four developmental periods – early embryogenesis, eye development, snout formation, and juvenile – which are further divided into 11 stages. Stages are characterised by morphological traits that are easily visible in live and preserved specimens using incident-light microscopy. Conclusions Our classification is derived from examinations of species representing the full range of brooding-structure complexity found in the Syngnathidae, including tail-brooding as well as trunk-brooding species, which represent independent evolutionary lineages. We chose conspicuous common traits as diagnostic features of stages to allow for rapid and consistent staging of embryos and larvae across the entire family. In view of the growing interest in the biology of the Syngnathidae, we believe that the classification proposed here will prove useful for a wide range of studies on the unique reproductive biology of these male-brooding fish. PMID:23273265

Standardised classification of pre-release development in male-brooding pipefish, seahorses, and seadragons (Family Syngnathidae

Directory of Open Access Journals (Sweden)

Sommer Stefan

2012-12-01

Full Text Available Abstract Background Members of the family Syngnathidae share a unique reproductive mode termed male pregnancy. Males carry eggs in specialised brooding structures for several weeks and release free-swimming offspring. Here we describe a systematic investigation of pre-release development in syngnathid fishes, reviewing available data for 17 species distributed across the family. This work is complemented by in-depth examinations of the straight-nosed pipefish Nerophis ophidion, the black-striped pipefish Syngnathus abaster, and the potbellied seahorse Hippocampus abdominalis. Results We propose a standardised classification of early syngnathid development that extends from the activation of the egg to the release of newborn. The classification consists of four developmental periods – early embryogenesis, eye development, snout formation, and juvenile – which are further divided into 11 stages. Stages are characterised by morphological traits that are easily visible in live and preserved specimens using incident-light microscopy. Conclusions Our classification is derived from examinations of species representing the full range of brooding-structure complexity found in the Syngnathidae, including tail-brooding as well as trunk-brooding species, which represent independent evolutionary lineages. We chose conspicuous common traits as diagnostic features of stages to allow for rapid and consistent staging of embryos and larvae across the entire family. In view of the growing interest in the biology of the Syngnathidae, we believe that the classification proposed here will prove useful for a wide range of studies on the unique reproductive biology of these male-brooding fish.

Computational intelligence techniques for biological data mining: An overview

Science.gov (United States)

Faye, Ibrahima; Iqbal, Muhammad Javed; Said, Abas Md; Samir, Brahim Belhaouari

2014-10-01

Computational techniques have been successfully utilized for a highly accurate analysis and modeling of multifaceted and raw biological data gathered from various genome sequencing projects. These techniques are proving much more effective to overcome the limitations of the traditional in-vitro experiments on the constantly increasing sequence data. However, most critical problems that caught the attention of the researchers may include, but not limited to these: accurate structure and function prediction of unknown proteins, protein subcellular localization prediction, finding protein-protein interactions, protein fold recognition, analysis of microarray gene expression data, etc. To solve these problems, various classification and clustering techniques using machine learning have been extensively used in the published literature. These techniques include neural network algorithms, genetic algorithms, fuzzy ARTMAP, K-Means, K-NN, SVM, Rough set classifiers, decision tree and HMM based algorithms. Major difficulties in applying the above algorithms include the limitations found in the previous feature encoding and selection methods while extracting the best features, increasing classification accuracy and decreasing the running time overheads of the learning algorithms. The application of this research would be potentially useful in the drug design and in the diagnosis of some diseases. This paper presents a concise overview of the well-known protein classification techniques.

Segmentation and classification of cell cycle phases in fluorescence imaging.

Science.gov (United States)

Ersoy, Ilker; Bunyak, Filiz; Chagin, Vadim; Cardoso, M Christina; Palaniappan, Kannappan

2009-01-01

Current chemical biology methods for studying spatiotemporal correlation between biochemical networks and cell cycle phase progression in live-cells typically use fluorescence-based imaging of fusion proteins. Stable cell lines expressing fluorescently tagged protein GFP-PCNA produce rich, dynamically varying sub-cellular foci patterns characterizing the cell cycle phases, including the progress during the S-phase. Variable fluorescence patterns, drastic changes in SNR, shape and position changes and abundance of touching cells require sophisticated algorithms for reliable automatic segmentation and cell cycle classification. We extend the recently proposed graph partitioning active contours (GPAC) for fluorescence-based nucleus segmentation using regional density functions and dramatically improve its efficiency, making it scalable for high content microscopy imaging. We utilize surface shape properties of GFP-PCNA intensity field to obtain descriptors of foci patterns and perform automated cell cycle phase classification, and give quantitative performance by comparing our results to manually labeled data.

Artificial intelligence in label-free microscopy biological cell classification by time stretch

CERN Document Server

Mahjoubfar, Ata; Jalali, Bahram

2017-01-01

This book introduces time-stretch quantitative phase imaging (TS-QPI), a high-throughput label-free imaging flow cytometer developed for big data acquisition and analysis in phenotypic screening. TS-QPI is able to capture quantitative optical phase and intensity images simultaneously, enabling high-content cell analysis, cancer diagnostics, personalized genomics, and drug development. The authors also demonstrate a complete machine learning pipeline that performs optical phase measurement, image processing, feature extraction, and classification, enabling high-throughput quantitative imaging that achieves record high accuracy in label -free cellular phenotypic screening and opens up a new path to data-driven diagnosis. • Demonstrates how machine learning is used in high-speed microscopy imaging to facilitate medical diagnosis; • Provides a systematic and comprehensive illustration of time stretch technology; • Enables multidisciplinary application, including industrial, biomedical, and artificial intell...

Bio-geographic classification of the Caspian Sea

Science.gov (United States)

Fendereski, F.; Vogt, M.; Payne, M. R.; Lachkar, Z.; Gruber, N.; Salmanmahiny, A.; Hosseini, S. A.

2014-03-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information derived from space and in-situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions using the Hierarchical Agglomerative Clustering (HAC) method. From an initial set of 12 potential physical variables, 6 independent variables were selected for the classification algorithm, i.e., sea surface temperature (SST), bathymetry, sea ice, seasonal variation of sea surface salinity (DSSS), total suspended matter (TSM) and its seasonal variation (DTSM). The classification results reveal a robust separation between the northern and the middle/southern basins as well as a separation of the shallow near-shore waters from those off-shore. The observed patterns in ecoregions can be attributed to differences in climate and geochemical factors such as distance from river, water depth and currents. A comparison of the annual and monthly mean Chl a concentrations between the different ecoregions shows significant differences (Kruskal-Wallis rank test, P qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 27 different species of plankton, fish and benthic invertebrate also confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics.

Collective Classification in Network Data

OpenAIRE

Sen, Prithviraj; Namata, Galileo; Bilgic, Mustafa; Getoor, Lise; University of Maryland; Galligher, Brian; Eliassi-Rad, Tina

2008-01-01

Many real-world applications produce networked data such as the world-wide web (hypertext documents connected via hyperlinks), social networks (for example, people connected by friendship links), communication networks (computers connected via communication links) and biological networks (for example, protein interaction networks). A recent focus in machine learning research has been to extend traditional machine learning classification techniques to classify nodes in such networks. In this a...

Sow-activity classification from acceleration patterns

DEFF Research Database (Denmark)

Escalante, Hugo Jair; Rodriguez, Sara V.; Cordero, Jorge

2013-01-01

sow-activity classification can be approached with standard machine learning methods for pattern classification. Individual predictions for elements of times series of arbitrary length are combined to classify it as a whole. An extensive comparison of representative learning algorithms, including......This paper describes a supervised learning approach to sow-activity classification from accelerometer measurements. In the proposed methodology, pairs of accelerometer measurements and activity types are considered as labeled instances of a usual supervised classification task. Under this scenario...... neural networks, support vector machines, and ensemble methods, is presented. Experimental results are reported using a data set for sow-activity classification collected in a real production herd. The data set, which has been widely used in related works, includes measurements from active (Feeding...

Burke-Fahn-Marsden dystonia severity, Gross Motor, Manual Ability, and Communication Function Classification scales in childhood hyperkinetic movement disorders including cerebral palsy: a 'Rosetta Stone' study.

Science.gov (United States)

Elze, Markus C; Gimeno, Hortensia; Tustin, Kylee; Baker, Lesley; Lumsden, Daniel E; Hutton, Jane L; Lin, Jean-Pierre S-M

2016-02-01

Hyperkinetic movement disorders (HMDs) can be assessed using impairment-based scales or functional classifications. The Burke-Fahn-Marsden Dystonia Rating Scale-movement (BFM-M) evaluates dystonia impairment, but may not reflect functional ability. The Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) are widely used in the literature on cerebral palsy to classify functional ability, but not in childhood movement disorders. We explore the concordance of these three functional scales in a large sample of paediatric HMDs and the impact of dystonia severity on these scales. Children with HMDs (n=161; median age 10y 3mo, range 2y 6mo-21y) were assessed using the BFM-M, GMFCS, MACS, and CFCS from 2007 to 2013. This cross-sectional study contrasts the information provided by these scales. All four scales were strongly associated (all Spearman's rank correlation coefficient rs >0.72, pdisorders including cerebral palsy can be effectively evaluated using these scales. © 2015 Mac Keith Press.

The 2017 World Health Organization classification of tumors of the pituitary gland: a summary.

Science.gov (United States)

Lopes, M Beatriz S

2017-10-01

The 4th edition of the World Health Organization (WHO) classification of endocrine tumors has been recently released. In this new edition, major changes are recommended in several areas of the classification of tumors of the anterior pituitary gland (adenophypophysis). The scope of the present manuscript is to summarize these recommended changes, emphasizing a few significant topics. These changes include the following: (1) a novel approach for classifying pituitary neuroendocrine tumors according to pituitary adenohypophyseal cell lineages; (2) changes to the histological grading of pituitary neuroendocrine tumors with the elimination of the term "atypical adenoma;" and (3) introduction of new entities like the pituitary blastoma and re-definition of old entities like the null-cell adenoma. This new classification is very practical and mostly based on immunohistochemistry for pituitary hormones, pituitary-specific transcription factors, and other immunohistochemical markers commonly used in pathology practice, not requiring routine ultrastructural analysis of the tumors. Evaluation of tumor proliferation potential, by mitotic count and Ki-67 labeling index, and tumor invasion is strongly recommended on individual case basis to identify clinically aggressive adenomas. In addition, the classification offers the treating clinical team information on tumor prognosis by identifying specific variants of adenomas associated with an elevated risk for recurrence. Changes in the classification of non-neuroendocrine tumors are also proposed, in particular those tumors arising in the posterior pituitary including pituicytoma, granular cell tumor of the posterior pituitary, and spindle cell oncocytoma. These changes endorse those previously published in the 2016 WHO classification of CNS tumors. Other tumors arising in the sellar region are also reviewed in detail including craniopharyngiomas, mesenchymal and stromal tumors, germ cell tumors, and hematopoietic tumors. It is

Using the biological literature a practical guide

CERN Document Server

Schmidt, Diane

2014-01-01

IntroductionSearching the Biological LiteratureGeneral SourcesAssociationsBibliographiesClassification, Nomenclature, and SystematicsDictionaries and EncyclopediasDirectoriesField GuidesSeriesFull-Text SourcesGeneral WorksGuides for young ScientistsGuides to the LiteratureHandbooksHistoriesMathematics and StatisticsMethods and TechniquesTextbooks and TreatisesWriting GuidesPeriodicalsReviews of the LiteratureAbstracts and IndexesBiochemistry and BiophysicsMolecular and Cellular BiologyGenetics, Biotechnology, and Developmental BiologyMicrobiology and ImmunologyEcology, Evolution, and Animal BehaviorPlant BiologyAnatomy and PhysiologyEntomologyZoologyIndex.

5th Conference of the International Federation of Classification Societies

CERN Document Server

Yajima, Keiji; Bock, Hans-Hermann; Ohsumi, Noboru; Tanaka, Yutaka; Baba, Yasumasa

1998-01-01

This volume, Data Science, Classification, and Related Methods, contains a selection of papers presented at the Fifth Conference of the International Federation of Oassification Societies (IFCS-96), which was held in Kobe, Japan, from March 27 to 30,1996. The volume covers a wide range of topics and perspectives in the growing field of data science, including theoretical and methodological advances in domains relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge discovery and seeking. It gives a broad view of the state of the art and is intended for those in the scientific community who either develop new data analysis methods or gather data and use search tools for analyzing and interpreting large and complex data sets. Presenting a wide field of applications, this book is of interest not only to data analysts, mathematicians, and statisticians but also to scientists from many areas and disciplines concerned with complex data: medicine, biology, ...

DTI measurements for Alzheimer’s classification

Science.gov (United States)

Maggipinto, Tommaso; Bellotti, Roberto; Amoroso, Nicola; Diacono, Domenico; Donvito, Giacinto; Lella, Eufemia; Monaco, Alfonso; Antonella Scelsi, Marzia; Tangaro, Sabina; Disease Neuroimaging Initiative, Alzheimer's.

2017-03-01

Diffusion tensor imaging (DTI) is a promising imaging technique that provides insight into white matter microstructure integrity and it has greatly helped identifying white matter regions affected by Alzheimer’s disease (AD) in its early stages. DTI can therefore be a valuable source of information when designing machine-learning strategies to discriminate between healthy control (HC) subjects, AD patients and subjects with mild cognitive impairment (MCI). Nonetheless, several studies have reported so far conflicting results, especially because of the adoption of biased feature selection strategies. In this paper we firstly analyzed DTI scans of 150 subjects from the Alzheimer’s disease neuroimaging initiative (ADNI) database. We measured a significant effect of the feature selection bias on the classification performance (p-value  informative content provided by DTI measurements for AD classification. Classification performances and biological insight, concerning brain regions related to the disease, provided by cross-validation analysis were both confirmed on the independent test.

Signal classification using global dynamical models, Part I: Theory

International Nuclear Information System (INIS)

Kadtke, J.; Kremliovsky, M.

1996-01-01

Detection and classification of signals is one of the principal areas of signal processing, and the utilization of nonlinear information has long been considered as a way of improving performance beyond standard linear (e.g. spectral) techniques. Here, we develop a method for using global models of chaotic dynamical systems theory to define a signal classification processing chain, which is sensitive to nonlinear correlations in the data. We use it to demonstrate classification in high noise regimes (negative SNR), and argue that classification probabilities can be directly computed from ensemble statistics in the model coefficient space. We also develop a modification for non-stationary signals (i.e. transients) using non-autonomous ODEs. In Part II of this paper, we demonstrate the analysis on actual open ocean acoustic data from marine biologics. copyright 1996 American Institute of Physics

Classification of mitocans, anti-cancer drugs acting on mitochondria

Czech Academy of Sciences Publication Activity Database

Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

2013-01-01

Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.524, year: 2013

Statistical approach for selection of biologically informative genes.

Science.gov (United States)

Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes

Classification of mitocans, anti-cancer drugs acting on mitochondria

Czech Academy of Sciences Publication Activity Database

Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

2013-01-01

Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Gene tics ; Molecular Biology Impact factor: 3.524, year: 2013

Planar optical waveguide based sandwich assay sensors and processes for the detection of biological targets including protein markers, pathogens and cellular debris

Science.gov (United States)

Martinez, Jennifer S [Santa Fe, NM; Swanson, Basil I [Los Alamos, NM; Grace, Karen M [Los Alamos, NM; Grace, Wynne K [Los Alamos, NM; Shreve, Andrew P [Santa Fe, NM

2009-06-02

An assay element is described including recognition ligands bound to a film on a single mode planar optical waveguide, the film from the group of a membrane, a polymerized bilayer membrane, and a self-assembled monolayer containing polyethylene glycol or polypropylene glycol groups therein and an assay process for detecting the presence of a biological target is described including injecting a biological target-containing sample into a sensor cell including the assay element, with the recognition ligands adapted for binding to selected biological targets, maintaining the sample within the sensor cell for time sufficient for binding to occur between selected biological targets within the sample and the recognition ligands, injecting a solution including a reporter ligand into the sensor cell; and, interrogating the sample within the sensor cell with excitation light from the waveguide, the excitation light provided by an evanescent field of the single mode penetrating into the biological target-containing sample to a distance of less than about 200 nanometers from the waveguide thereby exciting the fluorescent-label in any bound reporter ligand within a distance of less than about 200 nanometers from the waveguide and resulting in a detectable signal.

Probing spermiogenesis: a digital strategy for mouse acrosome classification.

Science.gov (United States)

Taloni, Alessandro; Font-Clos, Francesc; Guidetti, Luca; Milan, Simone; Ascagni, Miriam; Vasco, Chiara; Pasini, Maria Enrica; Gioria, Maria Rosa; Ciusani, Emilio; Zapperi, Stefano; La Porta, Caterina A M

2017-06-16

Classification of morphological features in biological samples is usually performed by a trained eye but the increasing amount of available digital images calls for semi-automatic classification techniques. Here we explore this possibility in the context of acrosome morphological analysis during spermiogenesis. Our method combines feature extraction from three dimensional reconstruction of confocal images with principal component analysis and machine learning. The method could be particularly useful in cases where the amount of data does not allow for a direct inspection by trained eye.

Classification of high resolution satellite images

OpenAIRE

Karlsson, Anders

2003-01-01

In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value.

Directory of Open Access Journals (Sweden)

Laetitia Marisa

Full Text Available Colon cancer (CC pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Fresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like, and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after

Classification for longevity potential: the use of novel biomarkers

Directory of Open Access Journals (Sweden)

Marian Beekman

2016-10-01

Full Text Available Background: In older people chronological age may not be the best predictor of residual lifespan and mortality, because with age the heterogeneity in health is increasing. Biomarkers for biological age and residual lifespan are being developed to predict disease and mortality better at an individual level than chronological age. In the current paper we aim to classify a group of older people into those with longevity potential or controls.Methods: In the Leiden Longevity Study participated 1671 offspring of nonagenarian siblings, as the group with longevity potential, and 744 similarly aged controls. Using known risk factors for cardiovascular disease, previously reported markers for human longevity and other physiological measures as predictors, classification models for longevity potential were constructed with multiple logistic regression of the offspring-control status.Results: The Framingham Risk Score is predictive for longevity potential (AUC = 64.7. Physiological parameters involved in immune responses and glucose, lipid and energy metabolism further improve the prediction performance for longevity potential (AUCmale = 71.4, AUCfemale = 68.7.Conclusion: Using the Framingham Risk Score, the classification of older people in groups with longevity potential and controls is moderate, but can be improved to a reasonably good classification in combination with markers of immune response, glucose, lipid and energy metabolism. We show that individual classification of older people for longevity potential may be feasible using biomarkers from a wide variety of different biological processes.

BClass: A Bayesian Approach Based on Mixture Models for Clustering and Classification of Heterogeneous Biological Data

Directory of Open Access Journals (Sweden)

Arturo Medrano-Soto

2004-12-01

Full Text Available Based on mixture models, we present a Bayesian method (called BClass to classify biological entities (e.g. genes when variables of quite heterogeneous nature are analyzed. Various statistical distributions are used to model the continuous/categorical data commonly produced by genetic experiments and large-scale genomic projects. We calculate the posterior probability of each entry to belong to each element (group in the mixture. In this way, an original set of heterogeneous variables is transformed into a set of purely homogeneous characteristics represented by the probabilities of each entry to belong to the groups. The number of groups in the analysis is controlled dynamically by rendering the groups as 'alive' and 'dormant' depending upon the number of entities classified within them. Using standard Metropolis-Hastings and Gibbs sampling algorithms, we constructed a sampler to approximate posterior moments and grouping probabilities. Since this method does not require the definition of similarity measures, it is especially suitable for data mining and knowledge discovery in biological databases. We applied BClass to classify genes in RegulonDB, a database specialized in information about the transcriptional regulation of gene expression in the bacterium Escherichia coli. The classification obtained is consistent with current knowledge and allowed prediction of missing values for a number of genes. BClass is object-oriented and fully programmed in Lisp-Stat. The output grouping probabilities are analyzed and interpreted using graphical (dynamically linked plots and query-based approaches. We discuss the advantages of using Lisp-Stat as a programming language as well as the problems we faced when the data volume increased exponentially due to the ever-growing number of genomic projects.

Gene-ontology enrichment analysis in two independent family-based samples highlights biologically plausible processes for autism spectrum disorders.

LENUS (Irish Health Repository)

Anney, Richard J L

2012-02-01

Recent genome-wide association studies (GWAS) have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors, association studies have yet to identify statistically robust, replicated major effect genes or SNPs. We apply the principle of the SNP ratio test methodology described by O\\'Dushlaine et al to over 2100 families from the Autism Genome Project (AGP). Using a two-stage design we examine association enrichment in 5955 unique gene-ontology classifications across four groupings based on two phenotypic and two ancestral classifications. Based on estimates from simulation we identify excess of association enrichment across all analyses. We observe enrichment in association for sets of genes involved in diverse biological processes, including pyruvate metabolism, transcription factor activation, cell-signalling and cell-cycle regulation. Both genes and processes that show enrichment have previously been examined in autistic disorders and offer biologically plausibility to these findings.

Comparison of feature selection and classification for MALDI-MS data

Directory of Open Access Journals (Sweden)

Yang Mary

2009-07-01

Full Text Available Abstract Introduction In the classification of Mass Spectrometry (MS proteomics data, peak detection, feature selection, and learning classifiers are critical to classification accuracy. To better understand which methods are more accurate when classifying data, some publicly available peak detection algorithms for Matrix assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS data were recently compared; however, the issue of different feature selection methods and different classification models as they relate to classification performance has not been addressed. With the application of intelligent computing, much progress has been made in the development of feature selection methods and learning classifiers for the analysis of high-throughput biological data. The main objective of this paper is to compare the methods of feature selection and different learning classifiers when applied to MALDI-MS data and to provide a subsequent reference for the analysis of MS proteomics data. Results We compared a well-known method of feature selection, Support Vector Machine Recursive Feature Elimination (SVMRFE, and a recently developed method, Gradient based Leave-one-out Gene Selection (GLGS that effectively performs microarray data analysis. We also compared several learning classifiers including K-Nearest Neighbor Classifier (KNNC, Naïve Bayes Classifier (NBC, Nearest Mean Scaled Classifier (NMSC, uncorrelated normal based quadratic Bayes Classifier recorded as UDC, Support Vector Machines, and a distance metric learning for Large Margin Nearest Neighbor classifier (LMNN based on Mahanalobis distance. To compare, we conducted a comprehensive experimental study using three types of MALDI-MS data. Conclusion Regarding feature selection, SVMRFE outperformed GLGS in classification. As for the learning classifiers, when classification models derived from the best training were compared, SVMs performed the best with respect to the expected testing

Sub-classification of Advanced-Stage Hepatocellular Carcinoma: A Cohort Study Including 612 Patients Treated with Sorafenib.

Science.gov (United States)

Yoo, Jeong-Ju; Chung, Goh Eun; Lee, Jeong-Hoon; Nam, Joon Yeul; Chang, Young; Lee, Jeong Min; Lee, Dong Ho; Kim, Hwi Young; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan

2018-04-01

Advanced hepatocellular carcinoma (HCC) is associated with various clinical conditions including major vessel invasion, metastasis, and poor performance status. The aim of this study was to establish a prognostic scoring system and to propose a sub-classification of the Barcelona-Clinic Liver Cancer (BCLC) stage C. This retrospective study included consecutive patientswho received sorafenib for BCLC stage C HCC at a single tertiary hospital in Korea. A Cox proportional hazard model was used to develop a scoring system, and internal validationwas performed by a 5-fold cross-validation. The performance of the model in predicting risk was assessed by the area under the curve and the Hosmer-Lemeshow test. A total of 612 BCLC stage C HCC patients were sub- classified into strata depending on their performance status. Five independent prognostic factors (Child-Pugh score, α-fetoprotein, tumor type, extrahepatic metastasis, and portal vein invasion) were identified and used in the prognostic scoring system. This scoring system showed good discrimination (area under the receiver operating characteristic curve, 0.734 to 0.818) and calibration functions (both p advanced HCC. A prognostic scoring system with five independent factors is useful in predicting the survival of patients with BCLC stage C HCC.

A supervised learning rule for classification of spatiotemporal spike patterns.

Science.gov (United States)

Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

2016-08-01

This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

Stellar Spectral Classification with Locality Preserving Projections ...

Indian Academy of Sciences (India)

With the help of computer tools and algorithms, automatic stellar spectral classification has become an area of current interest. The process of stellar spectral classification mainly includes two steps: dimension reduction and classification. As a popular dimensionality reduction technique, Principal Component Analysis (PCA) ...

Cell of origin associated classification of B-cell malignancies by gene signatures of the normal B-cell hierarchy.

Science.gov (United States)

Johnsen, Hans Erik; Bergkvist, Kim Steve; Schmitz, Alexander; Kjeldsen, Malene Krag; Hansen, Steen Møller; Gaihede, Michael; Nørgaard, Martin Agge; Bæch, John; Grønholdt, Marie-Louise; Jensen, Frank Svendsen; Johansen, Preben; Bødker, Julie Støve; Bøgsted, Martin; Dybkær, Karen

2014-06-01

Recent findings have suggested biological classification of B-cell malignancies as exemplified by the "activated B-cell-like" (ABC), the "germinal-center B-cell-like" (GCB) and primary mediastinal B-cell lymphoma (PMBL) subtypes of diffuse large B-cell lymphoma and "recurrent translocation and cyclin D" (TC) classification of multiple myeloma. Biological classification of B-cell derived cancers may be refined by a direct and systematic strategy where identification and characterization of normal B-cell differentiation subsets are used to define the cancer cell of origin phenotype. Here we propose a strategy combining multiparametric flow cytometry, global gene expression profiling and biostatistical modeling to generate B-cell subset specific gene signatures from sorted normal human immature, naive, germinal centrocytes and centroblasts, post-germinal memory B-cells, plasmablasts and plasma cells from available lymphoid tissues including lymph nodes, tonsils, thymus, peripheral blood and bone marrow. This strategy will provide an accurate image of the stage of differentiation, which prospectively can be used to classify any B-cell malignancy and eventually purify tumor cells. This report briefly describes the current models of the normal B-cell subset differentiation in multiple tissues and the pathogenesis of malignancies originating from the normal germinal B-cell hierarchy.

ON DEPARTURES FROM INDEPENDENCE IN CROSS-CLASSIFICATIONS.

Science.gov (United States)

CASE, C. MARSTON

THIS NOTE IS CONCERNED WITH IDEAS AND PROBLEMS INVOLVED IN CROSS-CLASSIFICATION OF OBSERVATIONS ON A GIVEN POPULATION, ESPECIALLY TWO-DIMENSIONAL CROSS-CLASSIFICATIONS. MAIN OBJECTIVES OF THE NOTE INCLUDE--(1) ESTABLISHMENT OF A CONCEPTUAL FRAMEWORK FOR CHARACTERIZATION AND COMPARISON OF CROSS-CLASSIFICATIONS, (2) DISCUSSION OF EXISTING METHODS…

Problems of classification in the family Paramyxoviridae.

Science.gov (United States)

Rima, Bert; Collins, Peter; Easton, Andrew; Fouchier, Ron; Kurath, Gael; Lamb, Robert A; Lee, Benhur; Maisner, Andrea; Rota, Paul; Wang, Lin-Fa

2018-05-01

A number of unassigned viruses in the family Paramyxoviridae need to be classified either as a new genus or placed into one of the seven genera currently recognized in this family. Furthermore, numerous new paramyxoviruses continue to be discovered. However, attempts at classification have highlighted the difficulties that arise by applying historic criteria or criteria based on sequence alone to the classification of the viruses in this family. While the recent taxonomic change that elevated the previous subfamily Pneumovirinae into a separate family Pneumoviridae is readily justified on the basis of RNA dependent -RNA polymerase (RdRp or L protein) sequence motifs, using RdRp sequence comparisons for assignment to lower level taxa raises problems that would require an overhaul of the current criteria for assignment into genera in the family Paramyxoviridae. Arbitrary cut off points to delineate genera and species would have to be set if classification was based on the amino acid sequence of the RdRp alone or on pairwise analysis of sequence complementarity (PASC) of all open reading frames (ORFs). While these cut-offs cannot be made consistent with the current classification in this family, resorting to genus-level demarcation criteria with additional input from the biological context may afford a way forward. Such criteria would reflect the increasingly dynamic nature of virus taxonomy even if it would require a complete revision of the current classification.

Definition and classification of epilepsy. Classification of epileptic seizures 2016

Directory of Open Access Journals (Sweden)

K. Yu. Mukhin

2017-01-01

Full Text Available Epilepsy is one of the most common neurological diseases, especially in childhood and adolescence. The incidence varies from 15 to 113 cases per 100 000 population with the maximum among children under 1 year old. The prevalence of epilepsy is high, ranging from 5 to 8 cases (in some regions – 10 cases per 1000 children under 15 years old. Classification of the disease has great importance for diagnosis, treatment and prognosis. The article presents a novel strategy for classification of epileptic seizures, developed in 2016. It contains a number of brand new concepts, including a very important one, saying that some seizures, previously considered as generalized or focal only, can be, in fact, both focal and generalized. They include tonic, atonic, myoclonic seizures and epileptic spasms. The term “secondarily generalized seizure” is replace by the term “bilateral tonic-clonic seizure” (as soon as it is not a separate type of epileptic seizures, and the term reflects the spread of discharge from any area of cerebral cortex and evolution of any types of focal seizures. International League Against Epilepsy recommends to abandon the term “pseudo-epileptic seizures” and replace it by the term “psychogenic non-epileptic seizures”. If a doctor is not sure that seizures have epileptic nature, the term “paroxysmal event” should be used without specifying the disease. The conception of childhood epileptic encephalopathies, developed within this novel classification project, is one of the most significant achievements, since in this case not only the seizures, but even epileptiform activity can induce severe disorders of higher mental functions. In addition to detailed description of the new strategy for classification of epileptic seizures, the article contains a comprehensive review of the existing principles of epilepsy and epileptic seizures classification.

Deep learning for tumor classification in imaging mass spectrometry.

Science.gov (United States)

Behrmann, Jens; Etmann, Christian; Boskamp, Tobias; Casadonte, Rita; Kriegsmann, Jörg; Maaß, Peter

2018-04-01

Tumor classification using imaging mass spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to fully process the data. Since mass spectra exhibit certain structural similarities to image data, deep learning may offer a promising strategy for classification of IMS data as it has been successfully applied to image classification. Methodologically, we propose an adapted architecture based on deep convolutional networks to handle the characteristics of mass spectrometry data, as well as a strategy to interpret the learned model in the spectral domain based on a sensitivity analysis. The proposed methods are evaluated on two algorithmically challenging tumor classification tasks and compared to a baseline approach. Competitiveness of the proposed methods is shown on both tasks by studying the performance via cross-validation. Moreover, the learned models are analyzed by the proposed sensitivity analysis revealing biologically plausible effects as well as confounding factors of the considered tasks. Thus, this study may serve as a starting point for further development of deep learning approaches in IMS classification tasks. https://gitlab.informatik.uni-bremen.de/digipath/Deep_Learning_for_Tumor_Classification_in_IMS. jbehrmann@uni-bremen.de or christianetmann@uni-bremen.de. Supplementary data are available at Bioinformatics online.

Safety classification of items in Tianwan Nuclear Power Plant

International Nuclear Information System (INIS)

Sun Yongbin

2005-01-01

The principle of integrality, moderation and equilibrium should be considered in the safety classification of items in nuclear power plant. The basic ways for safety classification of items is to classify the safety function based on the effect of the outside enclosure damage of the items (parts) on the safety. Tianwan Nuclear Power Plant adopts Russian VVER-1000/428 type reactor, it safety classification mainly refers to Russian Guidelines and standards. The safety classification of the electric equipment refers to IEEE-308(80) standard, including 1E and Non 1E classification. The safety classification of the instrumentation and control equipment refers to GB/T 15474-1995 standard, including safety 1E, safety-related SR and NC non-safety classification. The safety classification of Tianwan Nuclear Power Plant has to be approved by NNSA and satisfy Chinese Nuclear Safety Guidelines. (authors)

Gender and cultural issues in psychiatric nosological classification systems.

Science.gov (United States)

van de Water, Tanya; Suliman, Sharain; Seedat, Soraya

2016-08-01

Much has changed since the two dominant mental health nosological systems, the International Classification of Diseases (ICD) and the Diagnostic and Statistical Manual of Mental Disorders (DSM), were first published in 1900 and 1952, respectively. Despite numerous modifications to stay up to date with scientific and cultural changes (eg, exclusion of homosexuality as a disorder) and to improve the cultural sensitivity of psychiatric diagnoses, the ICD and DSM have only recently renewed attempts at harmonization. Previous nosological iterations demonstrate the oscillation in the importance placed on the biological focus, highlighting the tension between a gender- and culture-free nosology (solely biological) and a contextually relevant understanding of mental illness. In light of the release of the DSM 5, future nosological systems, such as the ICD 11, scheduled for release in 2017, and the Research Development Criteria (RDoC), can learn from history and apply critiques. This article aims to critically consider gender and culture in previous editions of the ICD and DSM to inform forthcoming classifications.

Land-cover classification with an expert classification algorithm using digital aerial photographs

Directory of Open Access Journals (Sweden)

José L. de la Cruz

2010-05-01

Full Text Available The purpose of this study was to evaluate the usefulness of the spectral information of digital aerial sensors in determining land-cover classification using new digital techniques. The land covers that have been evaluated are the following, (1 bare soil, (2 cereals, including maize (Zea mays L., oats (Avena sativa L., rye (Secale cereale L., wheat (Triticum aestivum L. and barley (Hordeun vulgare L., (3 high protein crops, such as peas (Pisum sativum L. and beans (Vicia faba L., (4 alfalfa (Medicago sativa L., (5 woodlands and scrublands, including holly oak (Quercus ilex L. and common retama (Retama sphaerocarpa L., (6 urban soil, (7 olive groves (Olea europaea L. and (8 burnt crop stubble. The best result was obtained using an expert classification algorithm, achieving a reliability rate of 95%. This result showed that the images of digital airborne sensors hold considerable promise for the future in the field of digital classifications because these images contain valuable information that takes advantage of the geometric viewpoint. Moreover, new classification techniques reduce problems encountered using high-resolution images; while reliabilities are achieved that are better than those achieved with traditional methods.

Classifying Classifications

DEFF Research Database (Denmark)

Debus, Michael S.

2017-01-01

This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

Radon classification of building ground

International Nuclear Information System (INIS)

Slunga, E.

1988-01-01

The Laboratories of Building Technology and Soil Mechanics and Foundation Engineering at the Helsinki University of Technology in cooperation with The Ministry of the Environment have proposed a radon classification for building ground. The proposed classification is based on the radon concentration in soil pores and on the permeability of the foundation soil. The classification includes four radon classes: negligible, normal, high and very high. Depending on the radon class the radon-technical solution for structures is chosen. It is proposed that the classification be done in general terms in connection with the site investigations for the planning of land use and in more detail in connection with the site investigations for an individual house. (author)

The development of a classification system for inland aquatic ...

African Journals Online (AJOL)

A classification system is described that was developed for inland aquatic ecosystems in South Africa, including wetlands. The six-tiered classification system is based on a top-down, hierarchical classification of aquatic ecosystems, following the functionally-oriented hydrogeomorphic (HGM) approach to classification but ...

Evaluation of machine learning algorithms for classification of primary biological aerosol using a new UV-LIF spectrometer

Science.gov (United States)

Ruske, Simon; Topping, David O.; Foot, Virginia E.; Kaye, Paul H.; Stanley, Warren R.; Crawford, Ian; Morse, Andrew P.; Gallagher, Martin W.

2017-03-01

Characterisation of bioaerosols has important implications within environment and public health sectors. Recent developments in ultraviolet light-induced fluorescence (UV-LIF) detectors such as the Wideband Integrated Bioaerosol Spectrometer (WIBS) and the newly introduced Multiparameter Bioaerosol Spectrometer (MBS) have allowed for the real-time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal spores and pollen.This new generation of instruments has enabled ever larger data sets to be compiled with the aim of studying more complex environments. In real world data sets, particularly those from an urban environment, the population may be dominated by non-biological fluorescent interferents, bringing into question the accuracy of measurements of quantities such as concentrations. It is therefore imperative that we validate the performance of different algorithms which can be used for the task of classification.For unsupervised learning we tested hierarchical agglomerative clustering with various different linkages. For supervised learning, 11 methods were tested, including decision trees, ensemble methods (random forests, gradient boosting and AdaBoost), two implementations for support vector machines (libsvm and liblinear) and Gaussian methods (Gaussian naïve Bayesian, quadratic and linear discriminant analysis, the k-nearest neighbours algorithm and artificial neural networks).The methods were applied to two different data sets produced using the new MBS, which provides multichannel UV-LIF fluorescence signatures for single airborne biological particles. The first data set contained mixed PSLs and the second contained a variety of laboratory-generated aerosol.Clustering in general performs slightly worse than the supervised learning methods, correctly classifying, at best, only 67. 6 and 91. 1 % for the two data sets respectively. For supervised learning the gradient boosting algorithm was

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

Science.gov (United States)

Torkzaban, Bahareh; Kayvanjoo, Amir Hossein; Ardalan, Arman; Mousavi, Soraya; Mariotti, Roberto; Baldoni, Luciana; Ebrahimie, Esmaeil; Ebrahimi, Mansour; Hosseini-Mazinani, Mehdi

2015-01-01

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two '4-targeted' and '16-targeted' experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.

6 CFR 7.20 - Classification and declassification authority.

Science.gov (United States)

2010-01-01

.... (a) Top Secret original classification authority may only be exercised by the Secretary of Homeland... up to and including Top Secret. No official who is delegated Top Secret original classification... Secret and Confidential original classification authority to other officials determined to have frequent...

Antiphospholipid syndrome (APS) revisited: Would migraine headaches be included in future classification criteria?

Science.gov (United States)

Noureldine, Mohammad Hassan A; Haydar, Ali A; Berjawi, Ahmad; Elnawar, Rody; Sweid, Ahmad; Khamashta, Munther A; Hughes, Graham R V; Uthman, Imad

2017-02-01

Headaches have been extensively reported in Antiphospholipid syndrome (APS)/Antiphospholipid antibodies (aPL)-positive patients. The aim of this study was to highlight the prevalence of headaches among APS/aPL-positive patients and discuss its association with laboratory, clinical and imaging findings. We searched the literature through Google Scholar and PubMed for publications on the epidemiology, pathogenesis, laboratory, imaging and clinical findings, and management of headaches in APS/aPL-positive patients. The following keywords were used: Antiphospholipid, Hughes syndrome, anticardiolipin, lupus anticoagulant, anti-β2 glycoprotein I, headache, migraine, tension, and cluster. All reports published between 1969 and 2015 were included. Migraine is the most commonly reported type of headache in APS/aPL-positive patients. Thrombotic and platelet dysfunction hypotheses have been studied to uncover the pathogenic role of aPL in the development of headaches. Several studies are reporting higher levels of aPL in primary and secondary APS migraineurs, but only few reached statistical significance. Migraine patients without clinical signs/symptoms of cerebral infarction rarely show positive imaging findings. Digital subtraction angiography shows promise in demonstrating small vascular lesions otherwise not detected on computed tomography, magnetic resonance imaging, or cerebral angiograms. Although it may be solitary and harmless in many cases, the deleterious effect of migraine on the quality of life of APS patients prompts rapid diagnosis and proper management. An anticoagulation trial is advisable in APS patients with migraine as many cases of severe, refractory migraine resolved with anticoagulation therapy. The profile of migraine headaches discussed in this study permits its candidacy for inclusion in future APS classification criteria.

Identifying colon cancer risk modules with better classification performance based on human signaling network.

Science.gov (United States)

Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

2014-10-01

Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

14 CFR Section 9 - Functional Classification-Operating Revenues

Science.gov (United States)

2010-01-01

... AIR CARRIERS Profit and Loss Classification Section 9 Functional Classification—Operating Revenues... shall be included in profit and loss classification 8100, Nonoperating Income and Expense-Net, and the... for all air carrier groups and shall include all revenues from the United States Government as direct...

Automatic workflow for the classification of local DNA conformations

Czech Academy of Sciences Publication Activity Database

Čech, P.; Kukal, J.; Černý, Jiří; Schneider, Bohdan; Svozil, D.

2013-01-01

Roč. 14, č. 205 (2013) ISSN 1471-2105 R&D Projects: GA ČR GAP305/12/1801 Institutional research plan: CEZ:AV0Z50520701 Keywords : DNA * Dinucleotide conformation * Classification * Machine learning * Neural network * k-NN * Cluster analysis Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.672, year: 2013

International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee

Science.gov (United States)

Ambros, P F; Ambros, I M; Brodeur, G M; Haber, M; Khan, J; Nakagawara, A; Schleiermacher, G; Speleman, F; Spitz, R; London, W B; Cohn, S L; Pearson, A D J; Maris, J M

2009-01-01

Neuroblastoma serves as a paradigm for utilising tumour genomic data for determining patient prognosis and treatment allocation. However, before the establishment of the International Neuroblastoma Risk Group (INRG) Task Force in 2004, international consensus on markers, methodology, and data interpretation did not exist, compromising the reliability of decisive genetic markers and inhibiting translational research efforts. The objectives of the INRG Biology Committee were to identify highly prognostic genetic aberrations to be included in the new INRG risk classification schema and to develop precise definitions, decisive biomarkers, and technique standardisation. The review of the INRG database (n=8800 patients) by the INRG Task Force finally enabled the identification of the most significant neuroblastoma biomarkers. In addition, the Biology Committee compared the standard operating procedures of different cooperative groups to arrive at international consensus for methodology, nomenclature, and future directions. Consensus was reached to include MYCN status, 11q23 allelic status, and ploidy in the INRG classification system on the basis of an evidence-based review of the INRG database. Standardised operating procedures for analysing these genetic factors were adopted, and criteria for proper nomenclature were developed. Neuroblastoma treatment planning is highly dependant on tumour cell genomic features, and it is likely that a comprehensive panel of DNA-based biomarkers will be used in future risk assignment algorithms applying genome-wide techniques. Consensus on methodology and interpretation is essential for uniform INRG classification and will greatly facilitate international and cooperative clinical and translational research studies. PMID:19401703

Taxonomies of Educational Objectives and Theories of Classification.

Science.gov (United States)

Travers, Robert M. W.

1980-01-01

Classification is the taxonomic science in which a system of categories is established and in which the categories have some logical structure. Scientific classifications have included those by Aristotle, Linnaeus, and Lavoisier. Educational taxonomies include those developed by Bloom, Herbart, Dewey, and Piaget. The problems of taxonomy…

Asynchronous data-driven classification of weapon systems

International Nuclear Information System (INIS)

Jin, Xin; Mukherjee, Kushal; Gupta, Shalabh; Ray, Asok; Phoha, Shashi; Damarla, Thyagaraju

2009-01-01

This communication addresses real-time weapon classification by analysis of asynchronous acoustic data, collected from microphones on a sensor network. The weapon classification algorithm consists of two parts: (i) feature extraction from time-series data using symbolic dynamic filtering (SDF), and (ii) pattern classification based on the extracted features using the language measure (LM) and support vector machine (SVM). The proposed algorithm has been tested on field data, generated by firing of two types of rifles. The results of analysis demonstrate high accuracy and fast execution of the pattern classification algorithm with low memory requirements. Potential applications include simultaneous shooter localization and weapon classification with soldier-wearable networked sensors. (rapid communication)

The normative structure of mathematization in systematic biology.

Science.gov (United States)

Sterner, Beckett; Lidgard, Scott

2014-06-01

We argue that the mathematization of science should be understood as a normative activity of advocating for a particular methodology with its own criteria for evaluating good research. As a case study, we examine the mathematization of taxonomic classification in systematic biology. We show how mathematization is a normative activity by contrasting its distinctive features in numerical taxonomy in the 1960s with an earlier reform advocated by Ernst Mayr starting in the 1940s. Both Mayr and the numerical taxonomists sought to formalize the work of classification, but Mayr introduced a qualitative formalism based on human judgment for determining the taxonomic rank of populations, while the numerical taxonomists introduced a quantitative formalism based on automated procedures for computing classifications. The key contrast between Mayr and the numerical taxonomists is how they conceptualized the temporal structure of the workflow of classification, specifically where they allowed meta-level discourse about difficulties in producing the classification. Copyright © 2014. Published by Elsevier Ltd.

Automated classification of cell morphology by coherence-controlled holographic microscopy

Science.gov (United States)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.

Towards precise classification of cancers based on robust gene functional expression profiles

Directory of Open Access Journals (Sweden)

Zhu Jing

2005-03-01

Full Text Available Abstract Background Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. Results Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. Conclusion This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge

Support Vector Machines for Pattern Classification

CERN Document Server

Abe, Shigeo

2010-01-01

A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empir

A method to incorporate uncertainty in the classification of remote sensing images

OpenAIRE

Gonçalves, Luísa M. S.; Fonte, Cidália C.; Júlio, Eduardo N. B. S.; Caetano, Mario

2009-01-01

The aim of this paper is to investigate if the incorporation of the uncertainty associated with the classification of surface elements into the classification of landscape units (LUs) increases the results accuracy. To this end, a hybrid classification method is developed, including uncertainty information in the classification of very high spatial resolution multi-spectral satellite images, to obtain a map of LUs. The developed classification methodology includes the following...

Systema naturae or the outline of living world classification

OpenAIRE

Shipunov, Alexey

2009-01-01

Here we present the short outline of the classification of living things (to the level of classes), given with two main goals: to provide a compact, synthetic overview of the biological diversity; and to supply users with up-todate information of latest taxonomic achievements. The latter is especially important in the recent epoch of molecular revolution in the taxonomy.

32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), Helmut-Schmidt-University

CERN Document Server

Lausen, Berthold; Seidel, Wilfried; Ultsch, Alfred

2010-01-01

Data Analysis, Data Handling and Business Intelligence are research areas at the intersection of computer science, artificial intelligence, mathematics, and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as in marketing, finance, economics, engineering, linguistics, archaeology, musicology, medical science, and biology. This volume contains the revised versions of selected papers presented during the 32nd Annual Conference of the German Classification Society (Gesellschaft für Klassifikation, GfKl). The conference, which was organized in cooperation with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), was hosted by Helmut-Schmidt-University, Hamburg, Germany, in July 2008.

PAI-1 and EGFR expression in adult glioma tumors: toward a molecular prognostic classification

International Nuclear Information System (INIS)

Muracciole, Xavier; Romain, Sylvie; Dufour, Henri; Palmari, Jacqueline; Chinot, Olivier; Ouafik, L'Houcine; Grisoli, Francois; Figarella-Branger, Dominique; Martin, Pierre-Marie

2002-01-01

Purpose: Molecular classification of gliomas is a major challenge in the effort to improve therapeutic decisions. The plasminogen activator system, including plasminogen activator inhibitor type 1 (PAI-1), plays a key role in tumor invasion and neoangiogenesis. Epidermal growth factor receptor (EGFR) is involved in the control of proliferation. The contribution of PAI-1 and EGFR to the survival of gliomas was retrospectively investigated. Methods and Materials: Fifty-nine adult gliomas treated by neurosurgery and conventional irradiation were analyzed, including 9 low-grade (2) and 50 high-grade (3-4) tumors (WHO classification). PAI-1 was measured on cytosols and EGFR on solubilized membranes using ELISA methods. Results: High PAI-1 levels were strongly associated with high histologic grade (p<0.001) and histologic necrosis (p<0.001). PAI-1 also correlated positively with patient age (p=0.05) and negatively with Karnofsky index (p=0.01). By univariate analysis of the high-grade population, higher PAI-1 (p<0.0001) and EGFR values (p=0.02) were associated with shorter overall survival. Only PAI-1 was an independent factor in multivariate analysis. Grade 3 tumors with low PAI-1 (100% 3-year overall survival rate) presented the same clinical outcome as the low-grade tumors. Conclusions: In this prognostic study, PAI-1 and EGFR expression revealed similarities and differences between high-grade gliomas that were not apparent by traditional clinical criteria. These data strongly support that biologic factors should be included in glioma classification and the design of clinical trials to treat more homogeneous populations

Building the United States National Vegetation Classification

Science.gov (United States)

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.

Proteomic classification of breast cancer.

LENUS (Irish Health Repository)

Kamel, Dalia

2012-11-01

Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme-linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

Science.gov (United States)

de Dumast, Priscille; Mirabel, Clément; Cevidanes, Lucia; Ruellas, Antonio; Yatabe, Marilia; Ioshida, Marcos; Ribera, Nina Tubau; Michoud, Loic; Gomes, Liliane; Huang, Chao; Zhu, Hongtu; Muniz, Luciana; Shoukri, Brandon; Paniagua, Beatriz; Styner, Martin; Pieper, Steve; Budin, Francois; Vimort, Jean-Baptiste; Pascal, Laura; Prieto, Juan Carlos

2018-07-01

The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. The findings of this

Multispectral Image classification using the theories of neural networks

International Nuclear Information System (INIS)

Ardisasmita, M.S.; Subki, M.I.R.

1997-01-01

Image classification is the one of the important part of digital image analysis. the objective of image classification is to identify and regroup the features occurring in an image into one or several classes in terms of the object. basic to the understanding of multispectral classification is the concept of the spectral response of an object as a function of the electromagnetic radiation and the wavelength of the spectrum. new approaches to classification has been developed to improve the result of analysis, these state-of-the-art classifiers are based upon the theories of neural networks. Neural network classifiers are algorithmes which mimic the computational abilities of the human brain. Artificial neurons are simple emulation's of biological neurons; they take in information from sensors or other artificial neurons, perform very simple operations on this data, and pass the result to other recognize the spectral signature of each image pixel. Neural network image classification has been divided into supervised and unsupervised training procedures. In the supervised approach, examples of each cover type can be located and the computer can compute spectral signatures to categorize all pixels in a digital image into several land cover classes. In supervised classification, spectral signatures are generated by mathematically grouping and it does not require analyst-specified training data. Thus, in the supervised approach we define useful information categories and then examine their spectral reparability; in the unsupervised approach the computer determines spectrally sapable classes and then we define thei information value

BIOLOGY OF HUMAN MALARIA PLASMODIA INCLUDING PLASMODIUM KNOWLESI

Directory of Open Access Journals (Sweden)

Spinello Antinori

2012-03-01

Full Text Available Malaria is a vector-borne infection caused by unicellular parasite of the genus Plasmodium. Plasmodia are obligate intracellular parasites that in humans after a clinically silent replication phase in the liver are able to infect and replicate within the erythrocytes. Four species (P.falciparum, P.malariae, P.ovale and P.vivax are traditionally recognized as responsible of natural infection in human beings but the recent upsurge of P.knowlesi malaria in South-East Asia has led clinicians to consider it as the fifth human malaria parasite. Recent studies in wild-living apes in Africa have revealed that P.falciparum, the most deadly form of human malaria, is not only human-host restricted as previously believed and its phylogenetic lineage is much more complex with new species identified in gorilla, bonobo and chimpanzee. Although less impressive, new data on biology of P.malariae, P.ovale and P.vivax are also emerging and will be briefly discussed in this review.

Random forests for classification in ecology

Science.gov (United States)

Cutler, D.R.; Edwards, T.C.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J.

2007-01-01

Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5) an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature. ?? 2007 by the Ecological Society of America.

Teaching Methods in Biology Education and Sustainability Education Including Outdoor Education for Promoting Sustainability—A Literature Review

Directory of Open Access Journals (Sweden)

Eila Jeronen

2016-12-01

Full Text Available There are very few studies concerning the importance of teaching methods in biology education and environmental education including outdoor education for promoting sustainability at the levels of primary and secondary schools and pre-service teacher education. The material was selected using special keywords from biology and sustainable education in several scientific databases. The article provides an overview of 24 selected articles published in peer-reviewed scientific journals from 2006–2016. The data was analyzed using qualitative content analysis. Altogether, 16 journals were selected and 24 articles were analyzed in detail. The foci of the analyses were teaching methods, learning environments, knowledge and thinking skills, psychomotor skills, emotions and attitudes, and evaluation methods. Additionally, features of good methods were investigated and their implications for teaching were emphasized. In total, 22 different teaching methods were found to improve sustainability education in different ways. The most emphasized teaching methods were those in which students worked in groups and participated actively in learning processes. Research points toward the value of teaching methods that provide a good introduction and supportive guidelines and include active participation and interactivity.

Classifications of Patterned Hair Loss: A Review.

Science.gov (United States)

Gupta, Mrinal; Mysore, Venkataram

2016-01-01

Patterned hair loss is the most common cause of hair loss seen in both the sexes after puberty. Numerous classification systems have been proposed by various researchers for grading purposes. These systems vary from the simpler systems based on recession of the hairline to the more advanced multifactorial systems based on the morphological and dynamic parameters that affect the scalp and the hair itself. Most of these preexisting systems have certain limitations. Currently, the Hamilton-Norwood classification system for males and the Ludwig system for females are most commonly used to describe patterns of hair loss. In this article, we review the various classification systems for patterned hair loss in both the sexes. Relevant articles were identified through searches of MEDLINE and EMBASE. Search terms included but were not limited to androgenic alopecia classification, patterned hair loss classification, male pattern baldness classification, and female pattern hair loss classification. Further publications were identified from the reference lists of the reviewed articles.

Classifications of patterned hair loss: a review

Directory of Open Access Journals (Sweden)

Mrinal Gupta

2016-01-01

Full Text Available Patterned hair loss is the most common cause of hair loss seen in both the sexes after puberty. Numerous classification systems have been proposed by various researchers for grading purposes. These systems vary from the simpler systems based on recession of the hairline to the more advanced multifactorial systems based on the morphological and dynamic parameters that affect the scalp and the hair itself. Most of these preexisting systems have certain limitations. Currently, the Hamilton-Norwood classification system for males and the Ludwig system for females are most commonly used to describe patterns of hair loss. In this article, we review the various classification systems for patterned hair loss in both the sexes. Relevant articles were identified through searches of MEDLINE and EMBASE. Search terms included but were not limited to androgenic alopecia classification, patterned hair loss classification, male pattern baldness classification, and female pattern hair loss classification. Further publications were identified from the reference lists of the reviewed articles.

Protist classification and the kingdoms of organisms.

Science.gov (United States)

Whittaker, R H; Margulis, L

1978-04-01

Traditional classification imposed a division into plant-like and animal-like forms on the unicellular eukaryotes, or protists; in a current view the protists are a diverse assemblage of plant-, animal- and fungus-like groups. Classification of these into phyla is difficult because of their relatively simple structure and limited geological record, but study of ultrastructure and other characteristics is providing new insight on protist classification. Possible classifications are discussed, and a summary classification of the living world into kingdoms (Monera, Protista, Fungi, Animalia, Plantae) and phyla is suggested. This classification also suggests groupings of phyla into superphyla and form-superphyla, and a broadened kingdom Protista (including green algae, oomycotes and slime molds but excluding red and brown algae). The classification thus seeks to offer a compromise between the protist and protoctist kingdoms of Whittaker and Margulis and to combine a full listing of phyla with grouping of these for synoptic treatment.

Operationalising UN security council resolution 1540: an overview of select practical activities in the chemical and biological weapon-related areas

International Nuclear Information System (INIS)

Hart, J.

2009-01-01

The UN member states are continuing to take measures to inter alia establish and effectively implement controls to prevent the proliferation of nuclear, biological and chemical weapons and their means of delivery in accordance with United Nations Security Council Resolution 1540 (2004). The resolution also encourages enhanced international cooperation on such efforts, including by working through the 1540 Committee. Most analyses on the implementation of the resolution have focused on nuclear issues. This presentation provides an overview of select practical activities in the chemical and biological weapon-related areas, including chemical product classification and identification, biosafety and biosecurity practices and criminal prosecutions for unauthorised chemical transfers.(author)

Simple Calculation Programs for Biology Other Methods

Indian Academy of Sciences (India)

First page Back Continue Last page Overview Graphics. Simple Calculation Programs for Biology Other Methods. Hemolytic potency of drugs. Raghava et al., (1994) Biotechniques 17: 1148. FPMAP: methods for classification and identification of microorganisms 16SrRNA. graphical display of restriction and fragment map of ...

Classification of Radioactive Waste. General Safety Guide

Energy Technology Data Exchange (ETDEWEB)

NONE

2009-11-15

This publication is a revision of an earlier Safety Guide of the same title issued in 1994. It recommends revised waste management strategies that reflect changes in practices and approaches since then. It sets out a classification system for the management of waste prior to disposal and for disposal, driven by long term safety considerations. It includes a number of schemes for classifying radioactive waste that can be used to assist with planning overall national approaches to radioactive waste management and to assist with operational management at facilities. Contents: 1. Introduction; 2. The radioactive waste classification scheme; Appendix: The classification of radioactive waste; Annex I: Evolution of IAEA standards on radioactive waste classification; Annex II: Methods of classification; Annex III: Origin and types of radioactive waste.

Classification of Radioactive Waste. General Safety Guide

International Nuclear Information System (INIS)

2009-01-01

This publication is a revision of an earlier Safety Guide of the same title issued in 1994. It recommends revised waste management strategies that reflect changes in practices and approaches since then. It sets out a classification system for the management of waste prior to disposal and for disposal, driven by long term safety considerations. It includes a number of schemes for classifying radioactive waste that can be used to assist with planning overall national approaches to radioactive waste management and to assist with operational management at facilities. Contents: 1. Introduction; 2. The radioactive waste classification scheme; Appendix: The classification of radioactive waste; Annex I: Evolution of IAEA standards on radioactive waste classification; Annex II: Methods of classification; Annex III: Origin and types of radioactive waste

Ototoxicity (cochleotoxicity) classifications: A review.

Science.gov (United States)

Crundwell, Gemma; Gomersall, Phil; Baguley, David M

2016-01-01

Drug-mediated ototoxicity, specifically cochleotoxicity, is a concern for patients receiving medications for the treatment of serious illness. A number of classification schemes exist, most of which are based on pure-tone audiometry, in order to assist non-audiological/non-otological specialists in the identification and monitoring of iatrogenic hearing loss. This review identifies the primary classification systems used in cochleototoxicity monitoring. By bringing together classifications published in discipline-specific literature, the paper aims to increase awareness of their relative strengths and limitations in the assessment and monitoring of ototoxic hearing loss and to indicate how future classification systems may improve upon the status-quo. Literature review. PubMed identified 4878 articles containing the search term ototox*. A systematic search identified 13 key classification systems. Cochleotoxicity classification systems can be divided into those which focus on hearing change from a baseline audiogram and those that focus on the functional impact of the hearing loss. Common weaknesses of these grading scales included a lack of sensitivity to small adverse changes in hearing thresholds, a lack of high-frequency audiometry (>8 kHz), and lack of indication of which changes are likely to be clinically significant for communication and quality of life.

A New Classification Approach Based on Multiple Classification Rules

OpenAIRE

Zhongmei Zhou

2014-01-01

A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

Parasites as biological tags of fish stocks: a meta-analysis of their discriminatory power.

Science.gov (United States)

Poulin, Robert; Kamiya, Tsukushi

2015-01-01

The use of parasites as biological tags to discriminate among marine fish stocks has become a widely accepted method in fisheries management. Here, we first link this approach to its unstated ecological foundation, the decay in the similarity of the species composition of assemblages as a function of increasing distance between them, a phenomenon almost universal in nature. We explain how distance decay of similarity can influence the use of parasites as biological tags. Then, we perform a meta-analysis of 61 uses of parasites as tags of marine fish populations in multivariate discriminant analyses, obtained from 29 articles. Our main finding is that across all studies, the observed overall probability of correct classification of fish based on parasite data was about 71%. This corresponds to a two-fold improvement over the rate of correct classification expected by chance alone, and the average effect size (Zr = 0·463) computed from the original values was also indicative of a medium-to-large effect. However, none of the moderator variables included in the meta-analysis had a significant effect on the proportion of correct classification; these moderators included the total number of fish sampled, the number of parasite species used in the discriminant analysis, the number of localities from which fish were sampled, the minimum and maximum distance between any pair of sampling localities, etc. Therefore, there are no clear-cut situations in which the use of parasites as tags is more useful than others. Finally, we provide recommendations for the future usage of parasites as tags for stock discrimination, to ensure that future applications of the method achieve statistical rigour and a high discriminatory power.

78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

Science.gov (United States)

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... response to requests from the U.S. cotton industry and ICE, AMS will offer a futures classification option...

Transportation Modes Classification Using Sensors on Smartphones

Directory of Open Access Journals (Sweden)

Shih-Hau Fang

2016-08-01

Full Text Available This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improved features and uses three machine learning algorithms including decision trees, K-nearest neighbor, and support vector machine to classify the user’s transportation and vehicular modes. In the experiments, we discussed and compared the performance from different perspectives including the accuracy for both modes, the executive time, and the model size. Results show that the proposed features enhance the accuracy, in which the support vector machine provides the best performance in classification accuracy whereas it consumes the largest prediction time. This paper also investigates the vehicle classification mode and compares the results with that of the transportation modes.

Biodiversity: molecular biological domains, symbiosis and kingdom origins

Science.gov (United States)

Margulis, L.

1992-01-01

The number of extant species of organisms is estimated to be from fewer than 3 to more than 30 x 10(6) (May, 1992). Molecular biology, comparative genetics and ultrastructural analyses provide new insights into evolutionary relationships between these species, including increasingly precise ideas of how species and higher taxa have evolved from common ancestors. Accumulation of random mutations and large macromolecular sequence change in all organisms since the Proterozoic Eon has been importantly supplemented by acquisition of inherited genomes ('symbiogenesis'). Karyotypic alterations (polyploidization and karyotypic fissioning) have been added to these other mechanisms of species origin in plants and animals during the Phanerozoic Eon. The new evolution concepts (coupled with current rapid rates of species extinction and ignorance of the extent of biodiversity) prompted this analysis of the field of systematic biology and its role in the reorganization of extant species into higher taxa. Two superkingdoms (= Domains: Prokaryotae and Eukaryotae) and five kingdoms (Monera = Procaryotae or Bacteria; Protoctista: algae, amoebae, ciliates, foraminifera, oomycetes, slime molds, etc.; Mychota: 'true' fungi; Plantae: one phylum (division) of bryophytes and nine phyla of tracheophytes; and Animalia) are recognized. Two subkingdoms comprise the monera: the great diverse lineages are Archaebacteria and Eubacteria. The criteria for classification using molecular, ultrastructural and genetic data for this scheme are mentioned. For the first time since the nineteenth century, logical, technical definitions for each group are given with their time of appearance as inferred from the fossil record in the primary scientific literature. This classification scheme, which most closely reflects the evolutionary history, molecular biology, genetics and ultrastructure of extant life, requires changes in social organization of biologists, many of whom as botanists and zoologists, still

Automated classification of cell morphology by coherence-controlled holographic microscopy.

Science.gov (United States)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Proposal of new classification of femoral trochanteric fracture by three-dimensional computed tomography and relationship to usual plain X-ray classification.

Science.gov (United States)

Shoda, Etsuo; Kitada, Shimpei; Sasaki, Yu; Hirase, Hitoshi; Niikura, Takahiro; Lee, Sang Yang; Sakurai, Atsushi; Oe, Keisuke; Sasaki, Takeharu

2017-01-01

Classification of femoral trochanteric fractures is usually based on plain X-ray findings using the Evans, Jensen, or AO/OTA classification. However, complications such as nonunion and cut out of the lag screw or blade are seen even in stable fracture. This may be due to the difficulty of exact diagnosis of fracture pattern in plain X-ray. Computed tomography (CT) may provide more information about the fracture pattern, but such data are scarce. In the present study, it was performed to propose a classification system for femoral trochanteric fractures using three-dimensional CT (3D-CT) and investigate the relationship between this classification and conventional plain X-ray classification. Using three-dimensional (3D)-CT, fractures were classified as two, three, or four parts using combinations of the head, greater trochanter, lesser trochanter, and shaft. We identified five subgroups of three-part fractures according to the fracture pattern involving the greater and lesser trochanters. In total, 239 femoral trochanteric fractures (45 men, 194 women; average age, 84.4 years) treated in four hospitals were classified using our 3D-CT classification. The relationship between this 3D-CT classification and the AO/OTA, Evans, and Jensen X-ray classifications was investigated. In the 3D-CT classification, many fractures exhibited a large oblique fragment of the greater trochanter including the lesser trochanter. This fracture type was recognized as unstable in the 3D-CT classification but was often classified as stable in each X-ray classification. It is difficult to evaluate fracture patterns involving the greater trochanter, especially large oblique fragments including the lesser trochanter, using plain X-rays. The 3D-CT shows the fracture line very clearly, making it easy to classify the fracture pattern.

Constructions and classifications of projective Poisson varieties.

Science.gov (United States)

Pym, Brent

2018-01-01

This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

Constructions and classifications of projective Poisson varieties

Science.gov (United States)

Pym, Brent

2018-03-01

This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

Insights into the classification of small GTPases

Directory of Open Access Journals (Sweden)

Dominik Heider

2010-05-01

Full Text Available Dominik Heider1, Sascha Hauke3, Martin Pyka4, Daniel Kessler21Department of Bioinformatics, Center for Medical Biotechnology, 2Institute of Cell Biology (Cancer Research, University of Duisburg-Essen, Essen, Germany; 3Institute of Computer Science, University of Münster, Münster, Germany; 4Interdisciplinary Center for Clinical Research, University Hospital of Münster, Münster, GermanyAbstract: In this study we used a Random Forest-based approach for an assignment of small guanosine triphosphate proteins (GTPases to specific subgroups. Small GTPases represent an important functional group of proteins that serve as molecular switches in a wide range of fundamental cellular processes, including intracellular transport, movement and signaling events. These proteins have further gained a special emphasis in cancer research, because within the last decades a huge variety of small GTPases from different subgroups could be related to the development of all types of tumors. Using a random forest approach, we were able to identify the most important amino acid positions for the classification process within the small GTPases superfamily and its subgroups. These positions are in line with the results of earlier studies and have been shown to be the essential elements for the different functionalities of the GTPase families. Furthermore, we provide an accurate and reliable software tool (GTPasePred to identify potential novel GTPases and demonstrate its application to genome sequences.Keywords: cancer, machine learning, classification, Random Forests, proteins

BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

Science.gov (United States)

Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

2018-04-11

The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes

RECOGNITION AND VALUATION OF BIOLOGICAL ASSETS IN TOURISM AREA. INTERNATIONAL ACCOUNTING STANDARDS

Directory of Open Access Journals (Sweden)

Corina IOANĂŞ

2009-06-01

Full Text Available Consistent with the Financial Reporting Standards Board's international convergence and harmonization policy it is proposed that a new accounting regime will prescribe the financial reporting practice and minimum disclosure requirements for agricultural activities, including the fair value of biological assets. In any financial report, the inclusion of biological assets may confuse the reality of the income profit and the wealth profit. There are many reasons it may provide misleading figures, the most obvious would be because the entity may have reported the value of heritage properties that do not actually generate any income but rather they are properties, which actually generate expenses for the entity, for example in maintenance costs. For any regime that requires entities to account and report on biological assets there should be a clear classification system that takes into account the different types of ownership structures in a society. Therefore in Romania, it is important that any financial reporting regime on biological assets should provide for the difference between business assets and cultural assets.

Marine biology

International Nuclear Information System (INIS)

Thurman, H.V.; Webber, H.H.

1984-01-01

This book discusses both taxonomic and ecological topics on marine biology. Full coverage of marine organisms of all five kingdoms is provided, along with interesting and thorough discussion of all major marine habitats. Organization into six major parts allows flexibility. It also provides insight into important topics such as disposal of nuclear waste at sea, the idea that life began on the ocean floor, and how whales, krill, and people interact. A full-color photo chapter reviews questions, and exercises. The contents are: an overview marine biology: fundamental concepts/investigating life in the ocean; the physical ocean, the ocean floor, the nature of water, the nature and motion of ocean water; general ecology, conditions for life in the sea, biological productivity and energy transfer; marine organisms; monera, protista, mycota and metaphyta; the smaller marine animals, the large animals marine habitats, the intertidal zone/benthos of the continental shelf, the photic zone, the deep ocean, the ocean under stress, marine pollution, appendix a: the metric system and conversion factors/ appendix b: prefixes and suffixes/ appendix c: taxonomic classification of common marine organisms, and glossary, and index

Systematic characterization and fluorescence threshold strategies for the wideband integrated bioaerosol sensor (WIBS) using size-resolved biological and interfering particles

Science.gov (United States)

Savage, Nicole J.; Krentz, Christine E.; Könemann, Tobias; Han, Taewon T.; Mainelis, Gediminas; Pöhlker, Christopher; Huffman, J. Alex

2017-11-01

Atmospheric particles of biological origin, also referred to as bioaerosols or primary biological aerosol particles (PBAP), are important to various human health and environmental systems. There has been a recent steep increase in the frequency of published studies utilizing commercial instrumentation based on ultraviolet laser/light-induced fluorescence (UV-LIF), such as the WIBS (wideband integrated bioaerosol sensor) or UV-APS (ultraviolet aerodynamic particle sizer), for bioaerosol detection both outdoors and in the built environment. Significant work over several decades supported the development of the general technologies, but efforts to systematically characterize the operation of new commercial sensors have remained lacking. Specifically, there have been gaps in the understanding of how different classes of biological and non-biological particles can influence the detection ability of LIF instrumentation. Here we present a systematic characterization of the WIBS-4A instrument using 69 types of aerosol materials, including a representative list of pollen, fungal spores, and bacteria as well as the most important groups of non-biological materials reported to exhibit interfering fluorescent properties. Broad separation can be seen between the biological and non-biological particles directly using the five WIBS output parameters and by taking advantage of the particle classification analysis introduced by Perring et al. (2015). We highlight the importance that particle size plays on observed fluorescence properties and thus in the Perring-style particle classification. We also discuss several particle analysis strategies, including the commonly used fluorescence threshold defined as the mean instrument background (forced trigger; FT) plus 3 standard deviations (σ) of the measurement. Changing the particle fluorescence threshold was shown to have a significant impact on fluorescence fraction and particle type classification. We conclude that raising the

The impact of classification of interest on predictive toxicogenomics

Directory of Open Access Journals (Sweden)

Pierre R. Bushel

2012-02-01

Full Text Available The era of toxicogenomics has introduced a new way of monitoring the effect of environmental stressors and toxicants on biological systems via quantification of changes in gene expression. Because the liver is one of the major organs for synthesis and secretion of substances which metabolize endogenous and exogenous materials, there has been a great deal of interest in elucidating predictive and mechanistic genomic markers of hepatotoxicity. This mini-review will bring context to a limited number of toxicogenomics studies which used genomics to evaluate the transcriptional changes in blood and liver in response to acetaminophen (APAP or other liver toxicants, but differed according to the classification of interest (COI, i.e. the partitioning of the samples a priori according to a common toxicological characteristic. The toxicogenomics studies highlighted are characterized by a classification of either no/low vs. high APAP dose exposure, none vs. observed necrosis, and severity of necrosis. The overlap or lack thereof between the gene classifiers and the modulated biological processes that are elucidated will be discussed to enhance the understanding of the effect of the particular COI model and experimental design used for prediction.

Advances in Risk Classification and Treatment Strategies for Neuroblastoma

Science.gov (United States)

Pinto, Navin R.; Applebaum, Mark A.; Volchenboum, Samuel L.; Matthay, Katherine K.; London, Wendy B.; Ambros, Peter F.; Nakagawara, Akira; Berthold, Frank; Schleiermacher, Gudrun; Park, Julie R.; Valteau-Couanet, Dominique; Pearson, Andrew D.J.

2015-01-01

Risk-based treatment approaches for neuroblastoma have been ongoing for decades. However, the criteria used to define risk in various institutional and cooperative groups were disparate, limiting the ability to compare clinical trial results. To mitigate this problem and enhance collaborative research, homogenous pretreatment patient cohorts have been defined by the International Neuroblastoma Risk Group classification system. During the past 30 years, increasingly intensive, multimodality approaches have been developed to treat patients who are classified as high risk, whereas patients with low- or intermediate-risk neuroblastoma have received reduced therapy. This treatment approach has resulted in improved outcome, although survival for high-risk patients remains poor, emphasizing the need for more effective treatments. Increased knowledge regarding the biology and genetic basis of neuroblastoma has led to the discovery of druggable targets and promising, new therapeutic approaches. Collaborative efforts of institutions and international cooperative groups have led to advances in our understanding of neuroblastoma biology, refinements in risk classification, and stratified treatment strategies, resulting in improved outcome. International collaboration will be even more critical when evaluating therapies designed to treat small cohorts of patients with rare actionable mutations. PMID:26304901

Effects of atmospheric correction and pansharpening on LULC classification accuracy using WorldView-2 imagery

Directory of Open Access Journals (Sweden)

Chinsu Lin

2015-05-01

Full Text Available Changes of Land Use and Land Cover (LULC affect atmospheric, climatic, and biological spheres of the earth. Accurate LULC map offers detail information for resources management and intergovernmental cooperation to debate global warming and biodiversity reduction. This paper examined effects of pansharpening and atmospheric correction on LULC classification. Object-Based Support Vector Machine (OB-SVM and Pixel-Based Maximum Likelihood Classifier (PB-MLC were applied for LULC classification. Results showed that atmospheric correction is not necessary for LULC classification if it is conducted in the original multispectral image. Nevertheless, pansharpening plays much more important roles on the classification accuracy than the atmospheric correction. It can help to increase classification accuracy by 12% on average compared to the ones without pansharpening. PB-MLC and OB-SVM achieved similar classification rate. This study indicated that the LULC classification accuracy using PB-MLC and OB-SVM is 82% and 89% respectively. A combination of atmospheric correction, pansharpening, and OB-SVM could offer promising LULC maps from WorldView-2 multispectral and panchromatic images.

Multi-Agent Information Classification Using Dynamic Acquaintance Lists.

Science.gov (United States)

Mukhopadhyay, Snehasis; Peng, Shengquan; Raje, Rajeev; Palakal, Mathew; Mostafa, Javed

2003-01-01

Discussion of automated information services focuses on information classification and collaborative agents, i.e. intelligent computer programs. Highlights include multi-agent systems; distributed artificial intelligence; thesauri; document representation and classification; agent modeling; acquaintances, or remote agents discovered through…

Composite Structural Motifs of Binding Sites for Delineating Biological Functions of Proteins

Science.gov (United States)

Kinjo, Akira R.; Nakamura, Haruki

2012-01-01

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures. PMID:22347478

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

Science.gov (United States)

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.

Multi trace element analysis of dry biological materials by neutron activation analysis including a chemical group separation

International Nuclear Information System (INIS)

Weers, C.A.

1980-07-01

Multi-element analysis of dry biological material by neutron activation analysis has to include radiochemical separation. The evaporation process is described in terms of the half-volume. The pretreatment of the samples and the development of the destruction-evaporation apparatus are described. The successive adsorption steps with active charcoal, Al 2 O 3 and coprecipitation with Fe(OH) 3 are described. Results obtained for standard reference materials are summarized. (G.T.H.)

Quantitative analysis of biological responses to low dose-rate γ-radiation, including dose, irradiation time, and dose-rate

International Nuclear Information System (INIS)

Magae, J.; Furukawa, C.; Kawakami, Y.; Hoshi, Y.; Ogata, H.

2003-01-01

Full text: Because biological responses to radiation are complex processes dependent on irradiation time as well as total dose, it is necessary to include dose, dose-rate and irradiation time simultaneously to predict the risk of low dose-rate irradiation. In this study, we analyzed quantitative relationship among dose, irradiation time and dose-rate, using chromosomal breakage and proliferation inhibition of human cells. For evaluation of chromosome breakage we assessed micronuclei induced by radiation. U2OS cells, a human osteosarcoma cell line, were exposed to gamma-ray in irradiation room bearing 50,000 Ci 60 Co. After the irradiation, they were cultured for 24 h in the presence of cytochalasin B to block cytokinesis, cytoplasm and nucleus were stained with DAPI and propidium iodide, and the number of binuclear cells bearing micronuclei was determined by fluorescent microscopy. For proliferation inhibition, cells were cultured for 48 h after the irradiation and [3H] thymidine was pulsed for 4 h before harvesting. Dose-rate in the irradiation room was measured with photoluminescence dosimeter. While irradiation time less than 24 h did not affect dose-response curves for both biological responses, they were remarkably attenuated as exposure time increased to more than 7 days. These biological responses were dependent on dose-rate rather than dose when cells were irradiated for 30 days. Moreover, percentage of micronucleus-forming cells cultured continuously for more than 60 days at the constant dose-rate, was gradually decreased in spite of the total dose accumulation. These results suggest that biological responses at low dose-rate, are remarkably affected by exposure time, that they are dependent on dose-rate rather than total dose in the case of long-term irradiation, and that cells are getting resistant to radiation after the continuous irradiation for 2 months. It is necessary to include effect of irradiation time and dose-rate sufficiently to evaluate risk

NMD Classifier: A reliable and systematic classification tool for nonsense-mediated decay events.

Directory of Open Access Journals (Sweden)

Min-Kung Hsu

Full Text Available Nonsense-mediated decay (NMD degrades mRNAs that include premature termination codons to avoid the translation and accumulation of truncated proteins. This mechanism has been found to participate in gene regulation and a wide spectrum of biological processes. However, the evolutionary and regulatory origins of NMD-targeted transcripts (NMDTs have been less studied, partly because of the complexity in analyzing NMD events. Here we report NMD Classifier, a tool for systematic classification of NMD events for either annotated or de novo assembled transcripts. This tool is based on the assumption of minimal evolution/regulation-an event that leads to the least change is the most likely to occur. Our simulation results indicate that NMD Classifier can correctly identify an average of 99.3% of the NMD-causing transcript structural changes, particularly exon inclusions/exclusions and exon boundary alterations. Researchers can apply NMD Classifier to evolutionary and regulatory studies by comparing NMD events of different biological conditions or in different organisms.

Modularization of biochemical networks based on classification of Petri net t-invariants.

Science.gov (United States)

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find

Modularization of biochemical networks based on classification of Petri net t-invariants

Directory of Open Access Journals (Sweden)

Grunwald Stefanie

2008-02-01

Full Text Available Abstract Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t

Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

Science.gov (United States)

Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

2014-01-01

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

Science.gov (United States)

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

Science.gov (United States)

Ten Berg, Paul W; Drijkoningen, Tessa; Strackee, Simon D; Buijze, Geert A

2016-05-01

Background In the lack of consensus, surgeon-based preference determines how acute scaphoid fractures are classified. There is a great variety of classification systems with considerable controversies. Purposes The purpose of this study was to provide an overview of the different classification systems, clarifying their subgroups and analyzing their popularity by comparing citation indexes. The intention was to improve data comparison between studies using heterogeneous fracture descriptions. Methods We performed a systematic review of the literature based on a search of medical literature from 1950 to 2015, and a manual search using the reference lists in relevant book chapters. Only original descriptions of classifications of acute scaphoid fractures in adults were included. Popularity was based on citation index as reported in the databases of Web of Science (WoS) and Google Scholar. Articles that were cited <10 times in WoS were excluded. Results Our literature search resulted in 308 potentially eligible descriptive reports of which 12 reports met the inclusion criteria. We distinguished 13 different (sub) classification systems based on (1) fracture location, (2) fracture plane orientation, and (3) fracture stability/displacement. Based on citations numbers, the Herbert classification was most popular, followed by the Russe and Mayo classifications. All classification systems were based on plain radiography. Conclusions Most classification systems were based on fracture location, displacement, or stability. Based on the controversy and limited reliability of current classification systems, suggested research areas for an updated classification include three-dimensional fracture pattern etiology and fracture fragment mobility assessed by dynamic imaging.

Peak height velocity as an alternative for maturational classification associated with motor performance

Directory of Open Access Journals (Sweden)

Leonardo Trevizan Costa

2009-01-01

Full Text Available Adolescence is a phase characterized by important physical and maturational alterations, with individuals of the same chronological age, but who are more mature, may present sportive advantages because of greater force gain and additional muscle mass. Thus, in studies evaluating motor skills of children and adolescents, maturational classification should be an efficient and easily applicable tool in order to facilitate the interpretation of the true relationship between maturation and motor performance. Therefore, the objective of this study was to compare the relationship between motor performance and different types of classification of biological maturation in 209 boys aged to 17 years (11.59 ± 2.57 practicing soccer. Anthropometric variables were obtained according to the ISAK criteria. Biological maturation was determined based on age at peak height velocity (PHV and also by self-assessment of sexual maturation (genitalia and pubic hair. Motor performance was evaluated by sit-and-reach tests, horizontal jump, modified push-ups, 50-m run, and 9/12-min run/walk. The results showed progression in the variables analyzed as the subjects reached maturity. Correlation analysis and the egression values indicated higher consistency for the PHV classification, which better explained motor performance according to maturational status, exceeding the values obtained by comparison according to age or sexual maturation. Thus, the use of PHV as a classification instrument is preferably recommended for youngsters with haracteristics similar to those of the present sample.

Minimum Error Entropy Classification

CERN Document Server

Marques de Sá, Joaquim P; Santos, Jorge M F; Alexandre, Luís A

2013-01-01

This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.

The lichens: general considerations. Role as pollution biological indicators

International Nuclear Information System (INIS)

Rivaux, E.

1998-01-01

After having recalled the morphology and the different classification of lichens, the author presents the main lichenous substances, in particular the depsides and the depsidones. A detailed study on the role of lichens as pollution biological indicators is given. (O.M.)

Single-Rooted Extraction Sockets: Classification and Treatment Protocol.

Science.gov (United States)

El Chaar, Edgar; Oshman, Sarah; Fallah Abed, Pooria

2016-09-01

Clinicians have many treatment techniques from which to choose when extracting a failing tooth and replacing it with an implant-supported restoration and when successful management of an extraction socket during the course of tooth replacement is necessary to achieve predictable and esthetic outcomes. This article presents a straightforward, yet thorough, classification for extraction sockets of single-rooted teeth and provides guidance to clinicians in the selection of appropriate and predictable treatment. The presented classification of extraction sockets for single-rooted teeth focuses on the topography of the extraction socket, while the protocol for treatment of each socket type factors in the shape of the remaining bone, the biotype, and the location of the socket whether it be in the mandible or maxilla. This system is based on the biologic foundations of wound healing and can help guide clinicians to successful treatment outcomes.

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

Science.gov (United States)

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

SoFoCles: feature filtering for microarray classification based on gene ontology.

Science.gov (United States)

Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

2010-02-01

Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

A Pruning Neural Network Model in Credit Classification Analysis

Directory of Open Access Journals (Sweden)

Yajiao Tang

2018-01-01

Full Text Available Nowadays, credit classification models are widely applied because they can help financial decision-makers to handle credit classification issues. Among them, artificial neural networks (ANNs have been widely accepted as the convincing methods in the credit industry. In this paper, we propose a pruning neural network (PNN and apply it to solve credit classification problem by adopting the well-known Australian and Japanese credit datasets. The model is inspired by synaptic nonlinearity of a dendritic tree in a biological neural model. And it is trained by an error back-propagation algorithm. The model is capable of realizing a neuronal pruning function by removing the superfluous synapses and useless dendrites and forms a tidy dendritic morphology at the end of learning. Furthermore, we utilize logic circuits (LCs to simulate the dendritic structures successfully which makes PNN be implemented on the hardware effectively. The statistical results of our experiments have verified that PNN obtains superior performance in comparison with other classical algorithms in terms of accuracy and computational efficiency.

SAW Classification Algorithm for Chinese Text Classification

OpenAIRE

Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

2015-01-01

Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

Classification in context

DEFF Research Database (Denmark)

Mai, Jens Erik

2004-01-01

This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

A NEW WASTE CLASSIFYING MODEL: HOW WASTE CLASSIFICATION CAN BECOME MORE OBJECTIVE?

Directory of Open Access Journals (Sweden)

Burcea Stefan Gabriel

2015-07-01

Full Text Available The waste management specialist must be able to identify and analyze waste generation sources and to propose proper solutions to prevent the waste generation and encurage the waste minimisation. In certain situations like implementing an integrated waste management sustem and configure the waste collection methods and capacities, practitioners can face the challenge to classify the generated waste. This will tend to be the more demanding as the literature does not provide a coherent system of criteria required for an objective waste classification process. The waste incineration will determine no doubt a different waste classification than waste composting or mechanical and biological treatment. In this case the main question is what are the proper classification criteria witch can be used to realise an objective waste classification? The article provide a short critical literature review of the existing waste classification criteria and suggests the conclusion that the literature can not provide unitary waste classification system which is unanimously accepted and assumed by ideologists and practitioners. There are various classification criteria and more interesting perspectives in the literature regarding the waste classification, but the most common criteria based on which specialists classify waste into several classes, categories and types are the generation source, physical and chemical features, aggregation state, origin or derivation, hazardous degree etc. The traditional classification criteria divided waste into various categories, subcategories and types; such an approach is a conjectural one because is inevitable that according to the context in which the waste classification is required the used criteria to differ significantly; hence the need to uniformizating the waste classification systems. For the first part of the article it has been used indirect observation research method by analyzing the literature and the various

Changing Histopathological Diagnostics by Genome-Based Tumor Classification

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Michael Kloth

2014-05-01

Full Text Available Traditionally, tumors are classified by histopathological criteria, i.e., based on their specific morphological appearances. Consequently, current therapeutic decisions in oncology are strongly influenced by histology rather than underlying molecular or genomic aberrations. The increase of information on molecular changes however, enabled by the Human Genome Project and the International Cancer Genome Consortium as well as the manifold advances in molecular biology and high-throughput sequencing techniques, inaugurated the integration of genomic information into disease classification. Furthermore, in some cases it became evident that former classifications needed major revision and adaption. Such adaptations are often required by understanding the pathogenesis of a disease from a specific molecular alteration, using this molecular driver for targeted and highly effective therapies. Altogether, reclassifications should lead to higher information content of the underlying diagnoses, reflecting their molecular pathogenesis and resulting in optimized and individual therapeutic decisions. The objective of this article is to summarize some particularly important examples of genome-based classification approaches and associated therapeutic concepts. In addition to reviewing disease specific markers, we focus on potentially therapeutic or predictive markers and the relevance of molecular diagnostics in disease monitoring.

Molecular and morphological data supporting phylogenetic reconstruction of the genus Goniothalamus (Annonaceae), including a reassessment of previous infrageneric classifications.

Science.gov (United States)

Tang, Chin Cheung; Thomas, Daniel C; Saunders, Richard M K

2015-09-01

Data is presented in support of a phylogenetic reconstruction of the species-rich early-divergent angiosperm genus Goniothalamus (Annonaceae) (Tang et al., Mol. Phylogenetic Evol., 2015) [1], inferred using chloroplast DNA (cpDNA) sequences. The data includes a list of primers for amplification and sequencing for nine cpDNA regions: atpB-rbcL, matK, ndhF, psbA-trnH, psbM-trnD, rbcL, trnL-F, trnS-G, and ycf1, the voucher information and molecular data (GenBank accession numbers) of 67 ingroup Goniothalamus accessions and 14 outgroup accessions selected from across the tribe Annoneae, and aligned data matrices for each gene region. We also present our Bayesian phylogenetic reconstructions for Goniothalamus, with information on previous infrageneric classifications superimposed to enable an evaluation of monophyly, together with a taxon-character data matrix (with 15 morphological characters scored for 66 Goniothalamus species and seven other species from the tribe Annoneae that are shown to be phylogenetically correlated).

Molecular and morphological data supporting phylogenetic reconstruction of the genus Goniothalamus (Annonaceae, including a reassessment of previous infrageneric classifications

Directory of Open Access Journals (Sweden)

Chin Cheung Tang

2015-09-01

Full Text Available Data is presented in support of a phylogenetic reconstruction of the species-rich early-divergent angiosperm genus Goniothalamus (Annonaceae (Tang et al., Mol. Phylogenetic Evol., 2015 [1], inferred using chloroplast DNA (cpDNA sequences. The data includes a list of primers for amplification and sequencing for nine cpDNA regions: atpB-rbcL, matK, ndhF, psbA-trnH, psbM-trnD, rbcL, trnL-F, trnS-G, and ycf1, the voucher information and molecular data (GenBank accession numbers of 67 ingroup Goniothalamus accessions and 14 outgroup accessions selected from across the tribe Annoneae, and aligned data matrices for each gene region. We also present our Bayesian phylogenetic reconstructions for Goniothalamus, with information on previous infrageneric classifications superimposed to enable an evaluation of monophyly, together with a taxon-character data matrix (with 15 morphological characters scored for 66 Goniothalamus species and seven other species from the tribe Annoneae that are shown to be phylogenetically correlated.

Computational Intelligence Paradigms in Advanced Pattern Classification

CERN Document Server

Jain, Lakhmi

2012-01-01

This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.

Deep learning for image classification

Science.gov (United States)

McCoppin, Ryan; Rizki, Mateen

2014-06-01

This paper provides an overview of deep learning and introduces the several subfields of deep learning including a specific tutorial of convolutional neural networks. Traditional methods for learning image features are compared to deep learning techniques. In addition, we present our preliminary classification results, our basic implementation of a convolutional restricted Boltzmann machine on the Mixed National Institute of Standards and Technology database (MNIST), and we explain how to use deep learning networks to assist in our development of a robust gender classification system.

Classification of the eye changes of Graves' disease

NARCIS (Netherlands)

Wiersinga, W. M.; Prummel, M. F.; Mourits, M. P.; Koornneef, L.; Buller, H. R.

1991-01-01

Classification of the eye changes of Graves' disease may have clinical use in the description of the present eye state, in the assessment of treatment results, and in the choice of therapy. Requirements for any classification system should include simplicity, clinical nature (i.e., easily carried

Student world view as a framework for learning genetics and evolution in high school biology

Science.gov (United States)

McCoy, Roger Wesley

Statement of the problem. Few studies in biology education have examined the underlying presuppositions which guide thinking and concept learning in adolescents. The purpose of this study was to describe and understand the biological world views of a variety of high school students before they take biology courses. Specifically, the study examined student world views in the domains of Classification, Relationship and Causation related to the concepts of heredity, evolution and biotechnology. The following served as guiding questions: (1) What are the personal world views of high school students entering biology classes, related to the domain of Classification, Relationship and Causality? (2) How do these student world views confound or enhance the learning of basic concepts in genetics and evolution? Methods. An interpretive method was chosen for this study. The six student participants were ninth graders and represented a wide range of world view backgrounds. A series of three interviews was conducted with each participant, with a focus group used for triangulation of data. The constant comparative method was used to categorize the data and facilitate the search for meaningful patterns. The analysis included a thick description of each student's personal views of classification, evolution and the appropriate use of biotechnology. Results. The study demonstrates that world view is the basis upon which students build knowledge in biology. The logic of their everyday thinking may not match that of scientists. The words they use are sometimes inconsistent with scientific terminology. This study provides evidence that students voice different opinions depending on the social situation, since they are strongly influenced by peers. Students classify animals based on behaviors. They largely believe that the natural world is unpredictable, and that humans are not really part of that world. Half are unlikely to accept the evolution of humans, but may accept it in other

78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

Science.gov (United States)

2013-09-09

... Service 7 CFR Part 27 [AMS-CN-13-0043] RIN 0581-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed rule. SUMMARY: The... optional cotton futures classification procedure--identified and known as ``registration'' by the U.S...

MicroRNAs in the Tumor Biology of Soft Tissue Sarcomas

NARCIS (Netherlands)

C.M.M. Gits (Caroline)

2013-01-01

markdownabstract__Abstract__ Soft tissue sarcomas represent a rare, heterogeneous group of mesenchymal tumors. In sarcomas, histological classification, prediction of clinical behaviour and prognosis, and targeted treatment is often a challenge. A better understanding of the biology of soft

Systems Biology of Glucocorticoids in Muscle Disease

Science.gov (United States)

2010-10-01

Introduction Duchenne muscular dystrophy (DMD) is the most common and incurable muscular dystrophy of childhood. Muscle regeneration fails with...SUBJECT TERMS Duchenne Muscular dystrophy , Glucocorticoids, Systems biology, Drug mechanism 16. SECURITY CLASSIFICATION OF: U 17. LIMITATION...better targeted and more effective therapies for Duchenne muscular dystrophy dynamically. This MDA grant proposal is led by Dr. Eric Hoffman, and it

Evaluation of normalization methods for cDNA microarray data by k-NN classification

Energy Technology Data Exchange (ETDEWEB)

Wu, Wei; Xing, Eric P; Myers, Connie; Mian, Saira; Bissell, Mina J

2004-12-17

Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Using LOOCV error of k-NNs as the evaluation criterion, three double

Reliability of a four-column classification for tibial plateau fractures.

Science.gov (United States)

Martínez-Rondanelli, Alfredo; Escobar-González, Sara Sofía; Henao-Alzate, Alejandro; Martínez-Cano, Juan Pablo

2017-09-01

A four-column classification system offers a different way of evaluating tibial plateau fractures. The aim of this study is to compare the intra-observer and inter-observer reliability between four-column and classic classifications. This is a reliability study, which included patients presenting with tibial plateau fractures between January 2013 and September 2015 in a level-1 trauma centre. Four orthopaedic surgeons blindly classified each fracture according to four different classifications: AO, Schatzker, Duparc and four-column. Kappa, intra-observer and inter-observer concordance were calculated for the reliability analysis. Forty-nine patients were included. The mean age was 39 ± 14.2 years, with no gender predominance (men: 51%; women: 49%), and 67% of the fractures included at least one of the posterior columns. The intra-observer and inter-observer concordance were calculated for each classification: four-column (84%/79%), Schatzker (60%/71%), AO (50%/59%) and Duparc (48%/58%), with a statistically significant difference among them (p = 0.001/p = 0.003). Kappa coefficient for intr-aobserver and inter-observer evaluations: Schatzker 0.48/0.39, four-column 0.61/0.34, Duparc 0.37/0.23, and AO 0.34/0.11. The proposed four-column classification showed the highest intra and inter-observer agreement. When taking into account the agreement that occurs by chance, Schatzker classification showed the highest inter-observer kappa, but again the four-column had the highest intra-observer kappa value. The proposed classification is a more inclusive classification for the posteromedial and posterolateral fractures. We suggest, therefore, that it be used in addition to one of the classic classifications in order to better understand the fracture pattern, as it allows more attention to be paid to the posterior columns, it improves the surgical planning and allows the surgical approach to be chosen more accurately.

Solubility classification of airborne products from uranium ores and tailings piles

International Nuclear Information System (INIS)

Kalkwarf, D.R.

1979-01-01

Airborne products generated at uranium mills were assigned solubility classifications for use in the ICRP Task Group Lung Model. No significant difference was seen between the dissolution behavior of airborne samples and sieved ground samples of the same product. If the product contained radionuclides that dissolved at different rates, composite classifications were assigned to show the solubility class of each component. If the dissolution data indicated that a radionuclide was present in two chemical forms that dissolved at different rates, a mixed classification was assigned to show the percentage of radionuclide in each solubility class. Uranium-ore dust was assigned the composite classification: ( 235 U, 238 U) W; ( 226 Ra) 10% D, 90% Y; ( 230 Th, 210 Pb, 210 Po) Y. Tailings-pile dust was classified: ( 226 Ra) 10% D, 90% Y; ( 230 Th, 210 Pb, 210 Po) Y. Uranium octoxide was classified Y, uranium tetrafluoride was also classified Y, ammonium diuranate was classified D, and yellow-cake dust was classified ( 235 U, 238 U) 60% D, 40% W. The term yellow cake, however, covers a variety of materials which differ significantly in dissolution rate. Solubility classifications based on the dissolution half-times of particular yellow-cake products should, thus, be used when available. The D, W, and Y classifications refer to biological half-times for clearance from the human respiratory tract of 0 to 10 days, 11 to 100 days, and > 100 days, respectively

Classification of refrigerants; Classification des fluides frigorigenes

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-07-01

This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data

Directory of Open Access Journals (Sweden)

Harris Lyndsay N

2006-04-01

Full Text Available Abstract Background Like microarray-based investigations, high-throughput proteomics techniques require machine learning algorithms to identify biomarkers that are informative for biological classification problems. Feature selection and classification algorithms need to be robust to noise and outliers in the data. Results We developed a recursive support vector machine (R-SVM algorithm to select important genes/biomarkers for the classification of noisy data. We compared its performance to a similar, state-of-the-art method (SVM recursive feature elimination or SVM-RFE, paying special attention to the ability of recovering the true informative genes/biomarkers and the robustness to outliers in the data. Simulation experiments show that a 5 %-~20 % improvement over SVM-RFE can be achieved regard to these properties. The SVM-based methods are also compared with a conventional univariate method and their respective strengths and weaknesses are discussed. R-SVM was applied to two sets of SELDI-TOF-MS proteomics data, one from a human breast cancer study and the other from a study on rat liver cirrhosis. Important biomarkers found by the algorithm were validated by follow-up biological experiments. Conclusion The proposed R-SVM method is suitable for analyzing noisy high-throughput proteomics and microarray data and it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features. The multivariate SVM-based method outperforms the univariate method in the classification performance, but univariate methods can reveal more of the differentially expressed features especially when there are correlations between the features.

An enhanced topologically significant directed random walk in cancer classification using gene expression datasets

Directory of Open Access Journals (Sweden)

Choon Sen Seah

2017-12-01

Full Text Available Microarray technology has become one of the elementary tools for researchers to study the genome of organisms. As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analysis, cancerous classification is an emerging important trend. Significant directed random walk is proposed as one of the cancerous classification approach which have higher sensitivity of risk gene prediction and higher accuracy of cancer classification. In this paper, the methodology and material used for the experiment are presented. Tuning parameter selection method and weight as parameter are applied in proposed approach. Gene expression dataset is used as the input datasets while pathway dataset is used to build a directed graph, as reference datasets, to complete the bias process in random walk approach. In addition, we demonstrate that our approach can improve sensitive predictions with higher accuracy and biological meaningful classification result. Comparison result takes place between significant directed random walk and directed random walk to show the improvement in term of sensitivity of prediction and accuracy of cancer classification.

Impact of chromosome alterations, genetic mutations and clonal hematopoiesis of indeterminate potential (CHIP) on the classification and risk stratification of MDS.

Science.gov (United States)

Ganguly, Bani Bandana; Banerjee, Debasis; Agarwal, Mohan B

2018-03-01

The advent of technological development has undoubtedly advanced biological and molecular inputs for better understanding the heterogeneous hematopoietic pre-malignant disorder of the stem cells known as myelodysplastic syndromes (MDS). Chromosomal rearrangements, including del(3q/5q/7q/11q/12p/20q), loss of 5/7/Y, trisomy 8/19, i(17q), etc. frequently detected in MDS with variable frequencies and combinations, are the integral components of the 5-tier risk-stratification and WHO-2016 classification. Observations on mutations in genes involved in RNA-splicing, DNA methylation, chromatin modification, transcription factor, signal transduction/kinases, RAS pathway, cohesin complex, DNA repair and other pathways have given insights in independent effects and biological interaction of co-occurrence on disease-phenotype and treatment outcome. However, recent concepts of clonal hematopoiesis of indeterminate potential (CHIP) and idiopathic cytopenia of undetermined significance (ICUS) have urged a re-definition of mutational events in non-clonal cytopenia and non-MDS healthy elderly but with a higher risk of overt leukemia. Considering gene mutations, chromosomal alterations, CHIP, ICUS and their significance in classification and risk-scoring certainly presents a comprehensive picture of disease-phenotype towards better understanding of MDS-pathogenesis, its evolution to AML and its response to therapeutic agents. The present review summarizes chromosomal and gene mutations, co-existence of mutational complexity, and WHO-2016 classification and risk-stratifications of MDS to facilitate a better understanding of its pathogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Cirse Quality Assurance Document and Standards for Classification of Complications: The Cirse Classification System.

Science.gov (United States)

Filippiadis, D K; Binkert, C; Pellerin, O; Hoffmann, R T; Krajina, A; Pereira, P L

2017-08-01

Interventional radiology provides a wide variety of vascular, nonvascular, musculoskeletal, and oncologic minimally invasive techniques aimed at therapy or palliation of a broad spectrum of pathologic conditions. Outcome data for these techniques are globally evaluated by hospitals, insurance companies, and government agencies targeting in a high-quality health care policy, including reimbursement strategies. To analyze effectively the outcome of a technique, accurate reporting of complications is necessary. Throughout the literature, numerous classification systems for complications grading and classification have been reported. Until now, there has been no method for uniform reporting of complications both in terms of definition and grading. The purpose of this CIRSE guideline is to provide a classification system of complications based on combining outcome and severity of sequelae. The ultimate challenge will be the adoption of this system by practitioners in different countries and health economies within the European Union and beyond.

ACCUWIND - Methods for classification of cup anemometers

DEFF Research Database (Denmark)

Dahlberg, J.-Å.; Friis Pedersen, Troels; Busche, P.

2006-01-01

the errors associated with the use of cup anemometers, and to develop a classification system for quantification of systematic errors of cup anemometers. This classification system has now been implementedin the IEC 61400-12-1 standard on power performance measurements in annex I and J. The classification...... of cup anemometers requires general external climatic operational ranges to be applied for the analysis of systematic errors. A Class A categoryclassification is connected to reasonably flat sites, and another Class B category is connected to complex terrain, General classification indices are the result...... developed in the CLASSCUP projectand earlier. A number of approaches including the use of two cup anemometer models, two methods of torque coefficient measurement, two angular response measurements, and inclusion and exclusion of influence of friction have been implemented in theclassification process...

Practical UXO Classification: Enhanced Data Processing Strategies for Technology Transition - Fort Ord: Dynamic and Cued Metalmapper Processing and Classification

Science.gov (United States)

2017-06-06

information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this...ms. 4 2.2 CLASSIFICATION Target classification is usually carried out using cued interrogation data acquired over anomalies initially...identified in the detection data. These cued interrogations eliminate relative positional errors by acquiring data with a stationary sensor. The multi-static

Prediction of bioavailability of selected bisphosphonates using in silico methods towards categorization into a biopharmaceutical classification system.

Science.gov (United States)

Biernacka, Joanna; Betlejewska-Kielak, Katarzyna; Kłosińska-Szmurło, Ewa; Pluciński, Franciszek A; Mazurek, Aleksander P

2013-01-01

The physicochemical properties relevant to biological activity of selected bisphosphonates such as clodronate disodium salt, etidronate disodium salt, pamidronate disodium salt, alendronate sodium salt, ibandronate sodium salt, risedronate sodium salt and zoledronate disodium salt were determined using in silico methods. The main aim of our research was to investigate and propose molecular determinants thataffect bioavailability of above mentioned compounds. These determinants are: stabilization energy (deltaE), free energy of solvation (deltaG(solv)), electrostatic potential, dipole moment, as well as partition and distribution coefficients estimated by the log P and log D values. Presented values indicate that selected bisphosphonates a recharacterized by high solubility and low permeability. The calculated parameters describing both solubility and permeability through biological membranes seem to be a good bioavailability indicators of bisphosphonates examined and can be a useful tool to include into Biopharmaceutical Classification System (BCS) development.

Comparison of an automated classification system with an empirical classification of circulation patterns over the Pannonian basin, Central Europe

Science.gov (United States)

Maheras, Panagiotis; Tolika, Konstantia; Tegoulias, Ioannis; Anagnostopoulou, Christina; Szpirosz, Klicász; Károssy, Csaba; Makra, László

2018-04-01

The aim of the study is to compare the performance of the two classification methods, based on the atmospheric circulation types over the Pannonian basin in Central Europe. Moreover, relationships including seasonal occurrences and correlation coefficients, as well as comparative diagrams of the seasonal occurrences of the circulation types of the two classification systems are presented. When comparing of the automated (objective) and empirical (subjective) classification methods, it was found that the frequency of the empirical anticyclonic (cyclonic) types is much higher (lower) than that of the automated anticyclonic (cyclonic) types both on an annual and seasonal basis. The highest and statistically significant correlations between the circulation types of the two classification systems, as well as those between the cumulated seasonal anticyclonic and cyclonic types occur in winter for both classifications, since the weather-influencing effect of the atmospheric circulation in this season is the most prevalent. Precipitation amounts in Budapest display a decreasing trend in accordance with the decrease in the occurrence of the automated cyclonic types. In contrast, the occurrence of the empirical cyclonic types displays an increasing trend. There occur types in a given classification that are usually accompanied by high ratios of certain types in the other classification.

Biological dosimetry: chromosomal aberration analysis for dose assessment

International Nuclear Information System (INIS)

1986-01-01

In view of the growing importance of chromosomal aberration analysis as a biological dosimeter, the present report provides a concise summary of the scientific background of the subject and a comprehensive source of information at the technical level. After a review of the basic principles of radiation dosimetry and radiation biology basic information on the biology of lymphocytes, the structure of chromosomes and the classification of chromosomal aberrations are presented. This is followed by a presentation of techniques for collecting blood, storing, transporting, culturing, making chromosomal preparations and scaring of aberrations. The physical and statistical parameters involved in dose assessment are discussed and examples of actual dose assessments taken from the scientific literature are given

On the history of biological theories of homosexuality.

Science.gov (United States)

Herrn, R

1995-01-01

Biological theories of homosexuality fit into the discourse on reproduction and sexuality that began in the nineteenth century. They arose in the context of the early homosexual rights movement, with its claim for natural rights, and the psychiatric discussions about sexual perversions. With the classification of homosexuality as a distinct category, homosexuals were excluded from the "normal". Biological theories of homosexuality were attempts not only to explain its causes, but also to maintain the exclusion of homosexuals as the "other". Biological explanations can be categorized as genetic, constitutional, endocrinological, and ethological. On the one hand, biological theories were used in the struggle for homosexual rights. On the other hand, they were used to "cure"e homosexuals. Every theory led to a specific therapy. This paper points out the roots of this thinking, traces the development of various theories, and shows the utilization of biological theories in treating homosexuality.

Phylogenetic classification of bony fishes.

Science.gov (United States)

Betancur-R, Ricardo; Wiley, Edward O; Arratia, Gloria; Acero, Arturo; Bailly, Nicolas; Miya, Masaki; Lecointre, Guillaume; Ortí, Guillermo

2017-07-06

Fish classifications, as those of most other taxonomic groups, are being transformed drastically as new molecular phylogenies provide support for natural groups that were unanticipated by previous studies. A brief review of the main criteria used by ichthyologists to define their classifications during the last 50 years, however, reveals slow progress towards using an explicit phylogenetic framework. Instead, the trend has been to rely, in varying degrees, on deep-rooted anatomical concepts and authority, often mixing taxa with explicit phylogenetic support with arbitrary groupings. Two leading sources in ichthyology frequently used for fish classifications (JS Nelson's volumes of Fishes of the World and W. Eschmeyer's Catalog of Fishes) fail to adopt a global phylogenetic framework despite much recent progress made towards the resolution of the fish Tree of Life. The first explicit phylogenetic classification of bony fishes was published in 2013, based on a comprehensive molecular phylogeny ( www.deepfin.org ). We here update the first version of that classification by incorporating the most recent phylogenetic results. The updated classification presented here is based on phylogenies inferred using molecular and genomic data for nearly 2000 fishes. A total of 72 orders (and 79 suborders) are recognized in this version, compared with 66 orders in version 1. The phylogeny resolves placement of 410 families, or ~80% of the total of 514 families of bony fishes currently recognized. The ordinal status of 30 percomorph families included in this study, however, remains uncertain (incertae sedis in the series Carangaria, Ovalentaria, or Eupercaria). Comments to support taxonomic decisions and comparisons with conflicting taxonomic groups proposed by others are presented. We also highlight cases were morphological support exist for the groups being classified. This version of the phylogenetic classification of bony fishes is substantially improved, providing resolution

International society of neuropathology-haarlem consensus guidelines for nervous system tumor classification and grading

NARCIS (Netherlands)

Louis, D.N.; Perry, A.; Burger, P.; Ellison, D.W.; Reifenberger, G.; Deimling, A. Von; Aldape, K.; Brat, D.; Collins, V.P.; Eberhart, C.; Figarella-Branger, D.; Fuller, G.N.; Giangaspero, F.; Giannini, C.; Hawkins, C.; Kleihues, P.; Korshunov, A.; Kros, J.M.; Lopes, M. Beatriz; Ng, H.K.; Ohgaki, H.; Paulus, W.; Pietsch, T.; Rosenblum, M.; Rushing, E.; Soylemezoglu, F.; Wiestler, O.; Wesseling, P.

2014-01-01

Major discoveries in the biology of nervous system tumors have raised the question of how non-histological data such as molecular information can be incorporated into the next World Health Organization (WHO) classification of central nervous system tumors. To address this question, a meeting of

Developmental biology, the stem cell of biological disciplines

OpenAIRE

Gilbert, Scott F.

2017-01-01

Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines.” Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, ...

Sequence-based classification and identification of Fungi.

Science.gov (United States)

Hibbett, David; Abarenkov, Kessy; Kõljalg, Urmas; Öpik, Maarja; Chai, Benli; Cole, James; Wang, Qiong; Crous, Pedro; Robert, Vincent; Helgason, Thorunn; Herr, Joshua R; Kirk, Paul; Lueschow, Shiloh; O'Donnell, Kerry; Nilsson, R Henrik; Oono, Ryoko; Schoch, Conrad; Smyth, Christopher; Walker, Donald M; Porras-Alfaro, Andrea; Taylor, John W; Geiser, David M

Fungal taxonomy and ecology have been revolutionized by the application of molecular methods and both have increasing connections to genomics and functional biology. However, data streams from traditional specimen- and culture-based systematics are not yet fully integrated with those from metagenomic and metatranscriptomic studies, which limits understanding of the taxonomic diversity and metabolic properties of fungal communities. This article reviews current resources, needs, and opportunities for sequence-based classification and identification (SBCI) in fungi as well as related efforts in prokaryotes. To realize the full potential of fungal SBCI it will be necessary to make advances in multiple areas. Improvements in sequencing methods, including long-read and single-cell technologies, will empower fungal molecular ecologists to look beyond ITS and current shotgun metagenomics approaches. Data quality and accessibility will be enhanced by attention to data and metadata standards and rigorous enforcement of policies for deposition of data and workflows. Taxonomic communities will need to develop best practices for molecular characterization in their focal clades, while also contributing to globally useful datasets including ITS. Changes to nomenclatural rules are needed to enable validPUBLICation of sequence-based taxon descriptions. Finally, cultural shifts are necessary to promote adoption of SBCI and to accord professional credit to individuals who contribute to community resources.

Risk factors and classifications of hilar cholangiocarcinoma.

Science.gov (United States)

Suarez-Munoz, Miguel Angel; Fernandez-Aguilar, Jose Luis; Sanchez-Perez, Belinda; Perez-Daga, Jose Antonio; Garcia-Albiach, Beatriz; Pulido-Roa, Ysabel; Marin-Camero, Naiara; Santoyo-Santoyo, Julio

2013-07-15

Cholangiocarcinoma is the second most common primary malignant tumor of the liver. Perihilar cholangiocarcinoma or Klatskin tumor represents more than 50% of all biliary tract cholangiocarcinomas. A wide range of risk factors have been identified among patients with Perihilar cholangiocarcinoma including advanced age, male gender, primary sclerosing cholangitis, choledochal cysts, cholelithiasis, cholecystitis, parasitic infection (Opisthorchis viverrini and Clonorchis sinensis), inflammatory bowel disease, alcoholic cirrhosis, nonalcoholic cirrhosis, chronic pancreatitis and metabolic syndrome. Various classifications have been used to describe the pathologic and radiologic appearance of cholangiocarcinoma. The three systems most commonly used to evaluate Perihilar cholangiocarcinoma are the Bismuth-Corlette (BC) system, the Memorial Sloan-Kettering Cancer Center and the TNM classification. The BC classification provides preoperative assessment of local spread. The Memorial Sloan-Kettering cancer center proposes a staging system according to three factors related to local tumor extent: the location and extent of bile duct involvement, the presence or absence of portal venous invasion, and the presence or absence of hepatic lobar atrophy. The TNM classification, besides the usual descriptors, tumor, node and metastases, provides additional information concerning the possibility for the residual tumor (R) and the histological grade (G). Recently, in 2011, a new consensus classification for the Perihilar cholangiocarcinoma had been published. The consensus was organised by the European Hepato-Pancreato-Biliary Association which identified the need for a new staging system for this type of tumors. The classification includes information concerning biliary or vascular (portal or arterial) involvement, lymph node status or metastases, but also other essential aspects related to the surgical risk, such as remnant hepatic volume or the possibility of underlying disease.

Geological-genetic classification for uranium deposits

International Nuclear Information System (INIS)

Terentiev, V.M.; Naumov, S.S.

1997-01-01

The paper describes a system for classification uranium deposits based on geological and genetic characteristics. The system is based on the interrelation and interdependence of uranium ore formation processes and other geological phenomena including sedimentation, magmatism and tectonics, as well as the evolution of geotectonic structures. Using these aspects, deposits are classified in three categories: endogenic - predominately hydrothermal and hydrothermal-metasomatic; exogenic - sedimentary diagenetic, biogenic sorption, and infiltrational; and polygenetic or composite types. The latter complex types includes: sedimentary/metamorphic and metamorphic and sedimentary/hydrothermal, where different ore generating processes have prevailed over a rock unit at different times. The 3 page classification is given in both the English and Russian languages. (author). 3 tabs

Urogenital tuberculosis: definition and classification.

Science.gov (United States)

Kulchavenya, Ekaterina

2014-10-01

To improve the approach to the diagnosis and management of urogenital tuberculosis (UGTB), we need clear and unique classification. UGTB remains an important problem, especially in developing countries, but it is often an overlooked disease. As with any other infection, UGTB should be cured by antibacterial therapy, but because of late diagnosis it may often require surgery. Scientific literature dedicated to this problem was critically analyzed and juxtaposed with the author's own more than 30 years' experience in tuberculosis urology. The conception, terms and definition were consolidated into one system; classification stage by stage as well as complications are presented. Classification of any disease includes dispersion on forms and stages and exact definitions for each stage. Clinical features and symptoms significantly vary between different forms and stages of UGTB. A simple diagnostic algorithm was constructed. UGTB is multivariant disease and a standard unified approach to it is impossible. Clear definition as well as unique classification are necessary for real estimation of epidemiology and the optimization of therapy. The term 'UGTB' has insufficient information in order to estimate therapy, surgery and prognosis, or to evaluate the epidemiology.

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

Energy Technology Data Exchange (ETDEWEB)

Lochner, Michelle; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K. [Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT (United Kingdom); McEwen, Jason D., E-mail: dr.michelle.lochner@gmail.com [Mullard Space Science Laboratory, University College London, Surrey RH5 6NT (United Kingdom)

2016-08-01

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

International Nuclear Information System (INIS)

Lochner, Michelle; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K.; McEwen, Jason D.

2016-01-01

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

Classification

Science.gov (United States)

Clary, Renee; Wandersee, James

2013-01-01

In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

Classification of multiple sclerosis lesions using adaptive dictionary learning.

Science.gov (United States)

Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

2015-12-01

This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Classification of heterogeneous electron microscopic projections into homogeneous subsets

International Nuclear Information System (INIS)

Herman, G.T.; Kalinowski, M.

2008-01-01

The co-existence of different states of a macromolecular complex in samples used by three-dimensional electron microscopy (3D-EM) constitutes a serious challenge. The single particle method applied directly to such heterogeneous sets is unable to provide useful information about the encountered conformational diversity and produces reconstructions with severely reduced resolution. One approach to solving this problem is to partition heterogeneous projection set into homogeneous components and apply existing reconstruction techniques to each of them. Due to the nature of the projection images and the high noise level present in them, this classification task is difficult. A method is presented to achieve the desired classification by using a novel image similarity measure and solving the corresponding optimization problem. Unlike the majority of competing approaches, the presented method employs unsupervised classification (it does not require any prior knowledge about the objects being classified) and does not involve a 3D reconstruction procedure. We demonstrate a fast implementation of this method, capable of classifying projection sets that originate from 3D-EM. The method's performance is evaluated on synthetically generated data sets produced by projecting 3D objects that resemble biological structures

Feature generation and representations for protein-protein interaction classification.

Science.gov (United States)

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

Effective Feature Selection for Classification of Promoter Sequences.

Directory of Open Access Journals (Sweden)

Kouser K

Full Text Available Exploring novel computational methods in making sense of biological data has not only been a necessity, but also productive. A part of this trend is the search for more efficient in silico methods/tools for analysis of promoters, which are parts of DNA sequences that are involved in regulation of expression of genes into other functional molecules. Promoter regions vary greatly in their function based on the sequence of nucleotides and the arrangement of protein-binding short-regions called motifs. In fact, the regulatory nature of the promoters seems to be largely driven by the selective presence and/or the arrangement of these motifs. Here, we explore computational classification of promoter sequences based on the pattern of motif distributions, as such classification can pave a new way of functional analysis of promoters and to discover the functionally crucial motifs. We make use of Position Specific Motif Matrix (PSMM features for exploring the possibility of accurately classifying promoter sequences using some of the popular classification techniques. The classification results on the complete feature set are low, perhaps due to the huge number of features. We propose two ways of reducing features. Our test results show improvement in the classification output after the reduction of features. The results also show that decision trees outperform SVM (Support Vector Machine, KNN (K Nearest Neighbor and ensemble classifier LibD3C, particularly with reduced features. The proposed feature selection methods outperform some of the popular feature transformation methods such as PCA and SVD. Also, the methods proposed are as accurate as MRMR (feature selection method but much faster than MRMR. Such methods could be useful to categorize new promoters and explore regulatory mechanisms of gene expressions in complex eukaryotic species.

Functional classifications for cerebral palsy: correlations between the gross motor function classification system (GMFCS), the manual ability classification system (MACS) and the communication function classification system (CFCS).

Science.gov (United States)

Compagnone, Eliana; Maniglio, Jlenia; Camposeo, Serena; Vespino, Teresa; Losito, Luciana; De Rinaldis, Marta; Gennaro, Leonarda; Trabacca, Antonio

2014-11-01

This study aimed to investigate a possible correlation between the gross motor function classification system-expanded and revised (GMFCS-E&R), the manual abilities classification system (MACS) and the communication function classification system (CFCS) functional levels in children with cerebral palsy (CP) by CP subtype. It was also geared to verify whether there is a correlation between these classification systems and intellectual functioning (IF) and parental socio-economic status (SES). A total of 87 children (47 males and 40 females, age range 4-18 years, mean age 8.9±4.2) were included in the study. A strong correlation was found between the three classifications: Level V of the GMFCS-E&R corresponds to Level V of the MACS (rs=0.67, p=0.001); the same relationship was found for the CFCS and the MACS (rs=0.73, p<0.001) and for the GMFCS-E&R and the CFCS (rs=0.61, p=0.001). The correlations between the IQ and the global functional disability profile were strong or moderate (GMFCS and IQ: rs=0.66, p=0.001; MACS and IQ: rs=0.58, p=0.001; CFCS and MACS: rs=0.65, p=0.001). The Kruskal-Wallis test was used to determine if there were differences between the GMFCS-E&R, the CFCS and the MACS by CP type. CP types showed different scores for the IQ level (Chi-square=8.59, df=2, p=0.014), the GMFCS-E&R (Chi-square=36.46, df=2, p<0.001), the CFCS (Chi-square=12.87, df=2, p=0.002), and the MACS Level (Chi-square=13.96, df=2, p<0.001) but no significant differences emerged for the SES (Chi-square=1.19, df=2, p=0.554). This study shows how the three functional classifications (GMFCS-E&R, CFCS and MACS) complement each other to provide a better description of the functional profile of CP. The systematic evaluation of the IQ can provide useful information about a possible future outcome for every functional level. The SES does not appear to affect functional profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Facial aging: A clinical classification

Directory of Open Access Journals (Sweden)

Shiffman Melvin

2007-01-01

Full Text Available The purpose of this classification of facial aging is to have a simple clinical method to determine the severity of the aging process in the face. This allows a quick estimate as to the types of procedures that the patient would need to have the best results. Procedures that are presently used for facial rejuvenation include laser, chemical peels, suture lifts, fillers, modified facelift and full facelift. The physician is already using his best judgment to determine which procedure would be best for any particular patient. This classification may help to refine these decisions.

International proposal for an acoustic classification scheme for dwellings

DEFF Research Database (Denmark)

Rasmussen, Birgit

2014-01-01

Acoustic classification schemes specify different quality levels for acoustic conditions. Regulations and classification schemes for dwellings typically include criteria for airborne and impact sound insulation, façade sound insulation and service equipment noise. However, although important...... classes, implying also trade barriers. Thus, a harmonized classification scheme would be useful, and the European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", running 2009-2013 with members from 32 countries, including three overseas...... for quality of life, information about acoustic conditions is rarely available, neither for new or existing housing. Regulatory acoustic requirements will, if enforced, ensure a corresponding quality for new dwellings, but satisfactory conditions for occupants are not guaranteed. Consequently, several...

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

Science.gov (United States)

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

NEW CLASSIFICATION OF ECOPOLICES

Directory of Open Access Journals (Sweden)

VOROBYOV V. V.

2016-09-01

Full Text Available Problem statement. Ecopolices are the newest stage of the urban planning. They have to be consideredsuchas material and energy informational structures, included to the dynamic-evolutionary matrix netsofex change processes in the ecosystems. However, there are not made the ecopolice classifications, developing on suchapproaches basis. And this determined the topicality of the article. Analysis of publications on theoretical and applied aspects of the ecopolices formation showed, that the work on them is managed mainly in the context of the latest scientific and technological achievements in the various knowledge fields. These settlements are technocratic. They are connected with the morphology of space, network structures of regional and local natural ecosystems, without independent stability, can not exist without continuous man support. Another words, they do not work in with an ecopolices idea. It is come to a head for objective, symbiotic searching of ecopolices concept with the development of their classifications. Purpose statement is to develop the objective evidence for ecopolices and to propose their new classification. Conclusion. On the base of the ecopolices classification have to lie an elements correlation idea of their general plans and men activity type according with natural mechanism of accepting, reworking and transmission of material, energy and information between geo-ecosystems, planet, man, ecopolices material part and Cosmos. New ecopolices classification should be based on the principles of multi-dimensional, time-spaced symbiotic clarity with exchange ecosystem networks. The ecopolice function with this approach comes not from the subjective anthropocentric economy but from the holistic objective of Genesis paradigm. Or, otherwise - not from the Consequence, but from the Cause.

Unclassified sarcomas : a study to improve classification in a cohort of Golden Retriever dogs

NARCIS (Netherlands)

Boerkamp, Kim M; Hellmén, Eva; Willén, Helena; Grinwis, Guy C M; Teske, Erik; Rutteman, Gerard R

2016-01-01

Morphologically, canine soft-tissue sarcomas (STSs) resemble human STSs. In humans, proper classification of STSs is considered essential to improve insight in the biology of these tumors, and to optimize diagnosis and therapy. To date, there is a paucity of data published on the significance of

A new classification scheme of European cold-water coral habitats: Implications for ecosystem-based management of the deep sea

Science.gov (United States)

Davies, J. S.; Guillaumont, B.; Tempera, F.; Vertino, A.; Beuck, L.; Ólafsdóttir, S. H.; Smith, C. J.; Fosså, J. H.; van den Beld, I. M. J.; Savini, A.; Rengstorf, A.; Bayle, C.; Bourillet, J.-F.; Arnaud-Haond, S.; Grehan, A.

2017-11-01

Cold-water corals (CWC) can form complex structures which provide refuge, nursery grounds and physical support for a diversity of other living organisms. However, irrespectively from such ecological significance, CWCs are still vulnerable to human pressures such as fishing, pollution, ocean acidification and global warming Providing coherent and representative conservation of vulnerable marine ecosystems including CWCs is one of the aims of the Marine Protected Areas networks being implemented across European seas and oceans under the EC Habitats Directive, the Marine Strategy Framework Directive and the OSPAR Convention. In order to adequately represent ecosystem diversity, these initiatives require a standardised habitat classification that organises the variety of biological assemblages and provides consistent and functional criteria to map them across European Seas. One such classification system, EUNIS, enables a broad level classification of the deep sea based on abiotic and geomorphological features. More detailed lower biotope-related levels are currently under-developed, particularly with regards to deep-water habitats (>200 m depth). This paper proposes a hierarchical CWC biotope classification scheme that could be incorporated by existing classification schemes such as EUNIS. The scheme was developed within the EU FP7 project CoralFISH to capture the variability of CWC habitats identified using a wealth of seafloor imagery datasets from across the Northeast Atlantic and Mediterranean. Depending on the resolution of the imagery being interpreted, this hierarchical scheme allows data to be recorded from broad CWC biotope categories down to detailed taxonomy-based levels, thereby providing a flexible yet valuable information level for management. The CWC biotope classification scheme identifies 81 biotopes and highlights the limitations of the classification framework and guidance provided by EUNIS, the EC Habitats Directive, OSPAR and FAO; which largely

The Japanese Histologic Classification and T-score in the Oxford Classification system could predict renal outcome in Japanese IgA nephropathy patients.

Science.gov (United States)

Kaihan, Ahmad Baseer; Yasuda, Yoshinari; Katsuno, Takayuki; Kato, Sawako; Imaizumi, Takahiro; Ozeki, Takaya; Hishida, Manabu; Nagata, Takanobu; Ando, Masahiko; Tsuboi, Naotake; Maruyama, Shoichi

2017-12-01

The Oxford Classification is utilized globally, but has not been fully validated. In this study, we conducted a comparative analysis between the Oxford Classification and Japanese Histologic Classification (JHC) to predict renal outcome in Japanese patients with IgA nephropathy (IgAN). A retrospective cohort study including 86 adult IgAN patients was conducted. The Oxford Classification and the JHC were evaluated by 7 independent specialists. The JHC, MEST score in the Oxford Classification, and crescents were analyzed in association with renal outcome, defined as a 50% increase in serum creatinine. In multivariate analysis without the JHC, only the T score was significantly associated with renal outcome. While, a significant association was revealed only in the JHC on multivariate analysis with JHC. The JHC and T score in the Oxford Classification were associated with renal outcome among Japanese patients with IgAN. Superiority of the JHC as a predictive index should be validated with larger study population and cohort studies in different ethnicities.

Quality-Oriented Classification of Aircraft Material Based on SVM

Directory of Open Access Journals (Sweden)

Hongxia Cai

2014-01-01

Full Text Available The existing material classification is proposed to improve the inventory management. However, different materials have the different quality-related attributes, especially in the aircraft industry. In order to reduce the cost without sacrificing the quality, we propose a quality-oriented material classification system considering the material quality character, Quality cost, and Quality influence. Analytic Hierarchy Process helps to make feature selection and classification decision. We use the improved Kraljic Portfolio Matrix to establish the three-dimensional classification model. The aircraft materials can be divided into eight types, including general type, key type, risk type, and leveraged type. Aiming to improve the classification accuracy of various materials, the algorithm of Support Vector Machine is introduced. Finally, we compare the SVM and BP neural network in the application. The results prove that the SVM algorithm is more efficient and accurate and the quality-oriented material classification is valuable.

A call for a standard classification system for future biologic research: the rationale for new PRP nomenclature.

Science.gov (United States)

Mautner, Kenneth; Malanga, Gerard A; Smith, Jay; Shiple, Brian; Ibrahim, Victor; Sampson, Steven; Bowen, Jay E

2015-04-01

Autologous cell therapies including platelet-rich plasma (PRP) and bone marrow concentrate (BMC) are increasingly popular options for soft tissue and joint-related diseases. Despite increased clinical application, conflicting research has been published regarding the efficacy of PRP, and few clinical publications pertaining to BMC are available. Preparations of PRP (and BMC) can vary in many areas, including platelet concentration, number of white blood cells, presence or absence of red blood cells, and activation status of the preparation. The potential effect of PRP characteristics on PRP efficacy is often not well understood by the treating clinician, and PRP characteristics, as well as the volume of PRP delivered, are unfortunately not included in the methods of many published research articles. It is essential to establish a standard reporting system for PRP that facilitates communication and the interpretation and synthesis of scientific investigations. Herein, the authors propose a new PRP classification system reflecting important PRP characteristics based on contemporary literature and recommend adoption of minimal standards for PRP reporting in scientific investigations. Widespread adoption of these recommendations will facilitate interpretation and comparison of clinical studies and promote scientifically based progress in the field of regenerative medicine. Copyright © 2015 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Search techniques in intelligent classification systems

CERN Document Server

Savchenko, Andrey V

2016-01-01

A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technicall...

Classification of technogenic impacts on the geological medium

International Nuclear Information System (INIS)

Trofimov, V.T.; Korolev, V.A.; Gerasimova, A.S.

1995-01-01

The available systems of classification of technology-induced impacts on the geological environment are analyzed and a classification which is elaborated by the authors and allows to break the integrated impact into individual components for their subsequent analysis, evaluation and reflection in cartographic models. This classification assumes the division of technology-induced impacts into classes and subclasses. The first class-impacts of physical nature-includes a subclass of radioactive impacts where, in its turn, two types of impacts are distinguished: radioactive contamination and radiation decontamination of the components of the geological environment. The proposed classification can serve the basis for developing standards and regulations of typification and evaluation of technology-induced impacts o the geological environment. 27 refs., 1 tab

Developmental biology, the stem cell of biological disciplines.

Science.gov (United States)

Gilbert, Scott F

2017-12-01

Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines." Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, developmental biology remains vigorous, pluripotent, and relatively undifferentiated. In many disciplines, especially in evolutionary biology and oncology, the developmental perspective is being reasserted as an important research program.

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

Science.gov (United States)

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

Oro-facial pain and temporomandibular disorders classification systems: A critical appraisal and future directions.

Science.gov (United States)

Klasser, G D; Manfredini, D; Goulet, J-P; De Laat, A

2018-03-01

It is a difficult undertaking to design a classification system for any disease entity, let alone for oro-facial pain (OFP) and more specifically for temporomandibular disorders (TMD). A further complication of this task is that both physical and psychosocial variables must be included. To augment this process, a two-step systematic review, adhering to PRISMA guidelines, of the classification systems published during the last 20 years for OFP and TMD was performed. The first search step identified 190 potential citations which ultimately resulted in only 17 articles being included for in-depth analysis and review. The second step resulted in only 5 articles being selected for inclusion in this review. Five additional articles and four classification guidelines/criteria were also included due to expansion of the search criteria. Thus, in total, 14 documents comprising articles and guidelines/criteria (8 proposals of classification systems for OFP; 6 for TMD) were selected for inclusion in the systematic review. For each, a discussion as to their advantages, strengths and limitations was provided. Suggestions regarding the future direction for improving the classification process with the use of ontological principles rather than taxonomy are discussed. Furthermore, the potential for expanding the scope of axes included in existing classification systems, to include genetic, epigenetic and neurobiological variables, is explored. It is therefore recommended that future classification system proposals be based on combined approaches aiming to provide archetypal treatment-oriented classifications. © 2017 John Wiley & Sons Ltd.

Desert plains classification based on Geomorphometrical parameters (Case study: Aghda, Yazd)

Science.gov (United States)

Tazeh, mahdi; Kalantari, Saeideh

2013-04-01

This research focuses on plains. There are several tremendous methods and classification which presented for plain classification. One of The natural resource based classification which is mostly using in Iran, classified plains into three types, Erosional Pediment, Denudation Pediment Aggradational Piedmont. The qualitative and quantitative factors to differentiate them from each other are also used appropriately. In this study effective Geomorphometrical parameters in differentiate landforms were applied for plain. Geomorphometrical parameters are calculable and can be extracted using mathematical equations and the corresponding relations on digital elevation model. Geomorphometrical parameters used in this study included Percent of Slope, Plan Curvature, Profile Curvature, Minimum Curvature, the Maximum Curvature, Cross sectional Curvature, Longitudinal Curvature and Gaussian Curvature. The results indicated that the most important affecting Geomorphometrical parameters for plain and desert classifications includes: Percent of Slope, Minimum Curvature, Profile Curvature, and Longitudinal Curvature. Key Words: Plain, Geomorphometry, Classification, Biophysical, Yazd Khezarabad.

Hand eczema classification

DEFF Research Database (Denmark)

Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M

2008-01-01

of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

A new classification of geological resources

International Nuclear Information System (INIS)

Mata Perello, Josep M; Mata Lleonart, Roger; Vintro Sanchez, Carla

2011-01-01

The traditional definition of the geological resource term excludes all those elements or processes of the physical environment that show a scientific, didactic, or cultural interest, but do not offer, in principle, an economic potential. The so called cultural geo-resources have traditionally not been included within a classification that puts them in the same hierarchical and semantic ranking than the rest of the resources, and there has been no attempt to define a classification of these resources under a more didactic and modern perspective. Hence, in order to catalogue all those geological elements that show a cultural, patrimonial, scientific, or didactic interest as a resource, this paper proposes a new classification in which geo-resources stand in the same hierarchical and semantic ranking than the rest of the resources traditionally catalogued as such.

Integrated DNA methylation and copy-number profiling identify three clinically and biologically relevant groups of anaplastic glioma.

Science.gov (United States)

Wiestler, Benedikt; Capper, David; Sill, Martin; Jones, David T W; Hovestadt, Volker; Sturm, Dominik; Koelsche, Christian; Bertoni, Anna; Schweizer, Leonille; Korshunov, Andrey; Weiß, Elisa K; Schliesser, Maximilian G; Radbruch, Alexander; Herold-Mende, Christel; Roth, Patrick; Unterberg, Andreas; Hartmann, Christian; Pietsch, Torsten; Reifenberger, Guido; Lichter, Peter; Radlwimmer, Bernhard; Platten, Michael; Pfister, Stefan M; von Deimling, Andreas; Weller, Michael; Wick, Wolfgang

2014-10-01

The outcome of patients with anaplastic gliomas varies considerably. Whether a molecular classification of anaplastic gliomas based on large-scale genomic or epigenomic analyses is superior to histopathology for reflecting distinct biological groups, predicting outcomes and guiding therapy decisions has yet to be determined. Epigenome-wide DNA methylation analysis, using a platform which also allows the detection of copy-number aberrations, was performed in a cohort of 228 patients with anaplastic gliomas (astrocytomas, oligoastrocytomas, and oligodendrogliomas), including 115 patients of the NOA-04 trial. We further compared these tumors with a group of 55 glioblastomas. Unsupervised clustering of DNA methylation patterns revealed two main groups correlated with IDH status: CpG island methylator phenotype (CIMP) positive (77.5 %) or negative (22.5 %). CIMP(pos) (IDH mutant) tumors showed a further separation based on copy-number status of chromosome arms 1p and 19q. CIMP(neg) (IDH wild type) tumors showed hallmark copy-number alterations of glioblastomas, and clustered together with CIMP(neg) glioblastomas without forming separate groups based on WHO grade. Notably, there was no molecular evidence for a distinct biological entity representing anaplastic oligoastrocytoma. Tumor classification based on CIMP and 1p/19q status was significantly associated with survival, allowing a better prediction of outcome than the current histopathological classification: patients with CIMP(pos) tumors with 1p/19q codeletion (CIMP-codel) had the best prognosis, followed by patients with CIMP(pos) tumors but intact 1p/19q status (CIMP-non-codel). Patients with CIMP(neg) anaplastic gliomas (GBM-like) had the worst prognosis. Collectively, our data suggest that anaplastic gliomas can be grouped by IDH and 1p/19q status into three molecular groups that show clear links to underlying biology and a significant association with clinical outcome in a prospective trial cohort.

Classification of the web

DEFF Research Database (Denmark)

Mai, Jens Erik

2004-01-01

This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

A New Method for Solving Supervised Data Classification Problems

Directory of Open Access Journals (Sweden)

Parvaneh Shabanzadeh

2014-01-01

Full Text Available Supervised data classification is one of the techniques used to extract nontrivial information from data. Classification is a widely used technique in various fields, including data mining, industry, medicine, science, and law. This paper considers a new algorithm for supervised data classification problems associated with the cluster analysis. The mathematical formulations for this algorithm are based on nonsmooth, nonconvex optimization. A new algorithm for solving this optimization problem is utilized. The new algorithm uses a derivative-free technique, with robustness and efficiency. To improve classification performance and efficiency in generating classification model, a new feature selection algorithm based on techniques of convex programming is suggested. Proposed methods are tested on real-world datasets. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithms.

A global biogeographic classification of the mesopelagic zone

Science.gov (United States)

Sutton, Tracey T.; Clark, Malcolm R.; Dunn, Daniel C.; Halpin, Patrick N.; Rogers, Alex D.; Guinotte, John; Bograd, Steven J.; Angel, Martin V.; Perez, Jose Angel A.; Wishner, Karen; Haedrich, Richard L.; Lindsay, Dhugal J.; Drazen, Jeffrey C.; Vereshchaka, Alexander; Piatkowski, Uwe; Morato, Telmo; Błachowiak-Samołyk, Katarzyna; Robison, Bruce H.; Gjerde, Kristina M.; Pierrot-Bults, Annelies; Bernal, Patricio; Reygondeau, Gabriel; Heino, Mikko

2017-08-01

We have developed a global biogeographic classification of the mesopelagic zone to reflect the regional scales over which the ocean interior varies in terms of biodiversity and function. An integrated approach was necessary, as global gaps in information and variable sampling methods preclude strictly statistical approaches. A panel combining expertise in oceanography, geospatial mapping, and deep-sea biology convened to collate expert opinion on the distributional patterns of pelagic fauna relative to environmental proxies (temperature, salinity, and dissolved oxygen at mesopelagic depths). An iterative Delphi Method integrating additional biological and physical data was used to classify biogeographic ecoregions and to identify the location of ecoregion boundaries or inter-regions gradients. We define 33 global mesopelagic ecoregions. Of these, 20 are oceanic while 13 are 'distant neritic.' While each is driven by a complex of controlling factors, the putative primary driver of each ecoregion was identified. While work remains to be done to produce a comprehensive and robust mesopelagic biogeography (i.e., reflecting temporal variation), we believe that the classification set forth in this study will prove to be a useful and timely input to policy planning and management for conservation of deep-pelagic marine resources. In particular, it gives an indication of the spatial scale at which faunal communities are expected to be broadly similar in composition, and hence can inform application of ecosystem-based management approaches, marine spatial planning and the distribution and spacing of networks of representative protected areas.

[Definition and classification of pulmonary arterial hypertension].

Science.gov (United States)

Nakanishi, Norifumi

2008-11-01

Pulmonary hypertension(PH) is a disorder that may occur either in the setting of a variety of underlying medical conditions or as a disease that uniquely affects the pulmonary vasculature. Because an accurate diagnosis of PH in a patient is essential to establish an effective treatment, a classification of PH has been helpful. The first classification, established at WHO Symposium in 1973, classified PH into groups based on the known cause and defined primary pulmonary hypertension (PPH) as a separate entity of unknown cause. In 1998, the second World Symposium on PPH was held in Evian. Evian classification introduced the concept of conditions that directly affected the pulmonary vasculature (i.e., PAH), which included PPH. In 2003, the third World Symposium on PAH convened in Venice. In Venice classification, the term 'PPH' was abandoned in favor of 'idiopathic' within the group of disease known as 'PAH'.

Classification of the lymphatic drainage status of a primary tumor: a proposal

International Nuclear Information System (INIS)

Munz, D.L.; Maza, S.; Ivancevic, V.; Geworski, L.

2000-01-01

Aim: Creation of a classification of the lymphatic drainage status of a primary tumour. It shall enable comparison of different approaches, standardisation and quality control. Methods: Identification and topographic localisation of the sentinel node(s) using lymphatic radionuclide gamma camera imaging and/or gamma probe detection and/or vital dye mapping. Results: A classification comprising four classes (D-Class I-IV) and distinct subclasses (A-E) proved to be simply to be learned and applicable as well as reliably reproducible. It is based on the number of sentinel lymph nodes and their locations and can be combined with the pathological and molecular biological lymph node status. D-classes/subclasses obtained in 420 patients with malignant melanoma of the skin are presented. Conclusions: The classification is applicable to different approaches. Its diagnostic, therapeutic and prognostic value should be studied prospectively in those primary tumours which preferably metastasise via their draining lymphatic vessels. (orig.) [de

DNA markers for forensic identification of non-human biological traces

NARCIS (Netherlands)

Wesselink, M.

2018-01-01

In this thesis, DNA markers are described that enable forensically relevant classification of three groups of non-human biological traces: fungi (Chapter 1), domestic cats (Chapters 2, 3 an d 4) and birch trees (Chapters 5 and 6). Because the forensic questions associated with these traces require

Hazard classification methodology

International Nuclear Information System (INIS)

Brereton, S.J.

1996-01-01

This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

Standard classification of uranium resources-an illustrative example

International Nuclear Information System (INIS)

Krishna, P.M.; Babitzke, H.R.; Curry, D.; Masters, C.D.; McCammon, R.B.; Noble, R.B.; Rodriguez, J.A.; Schanz, J.J.; Schreiber, H.W.

1983-01-01

An example illustrates the use of ASTM Standard E901-82, Classification System for Uranium Resources. The example demonstrates the dynamic nature of the process of classification and attests to the necessity of addressing both the aggregate needs of broad-scale resource planning and the specific needs of individual property evaluation. Problems that remain in fixing the classification of a given uranium resource include the uncertainty in estimating the quantity of undiscovered resources and resolving the differences that may exist in deciding when the drill-hole spacing is adequate to determine the tonnage and grade of discovered resources

Antibacterial Free Fatty Acids and Monoglycerides: Biological Activities, Experimental Testing, and Therapeutic Applications

Science.gov (United States)

Yoon, Bo Kyeong; Jackman, Joshua A.; Valle-González, Elba R.

2018-01-01

Antimicrobial lipids such as fatty acids and monoglycerides are promising antibacterial agents that destabilize bacterial cell membranes, causing a wide range of direct and indirect inhibitory effects. The goal of this review is to introduce the latest experimental approaches for characterizing how antimicrobial lipids destabilize phospholipid membranes within the broader scope of introducing current knowledge about the biological activities of antimicrobial lipids, testing strategies, and applications for treating bacterial infections. To this end, a general background on antimicrobial lipids, including structural classification, is provided along with a detailed description of their targeting spectrum and currently understood antibacterial mechanisms. Building on this knowledge, different experimental approaches to characterize antimicrobial lipids are presented, including cell-based biological and model membrane-based biophysical measurement techniques. Particular emphasis is placed on drawing out how biological and biophysical approaches complement one another and can yield mechanistic insights into how the physicochemical properties of antimicrobial lipids influence molecular self-assembly and concentration-dependent interactions with model phospholipid and bacterial cell membranes. Examples of possible therapeutic applications are briefly introduced to highlight the potential significance of antimicrobial lipids for human health and medicine, and to motivate the importance of employing orthogonal measurement strategies to characterize the activity profile of antimicrobial lipids. PMID:29642500

The Influence of Hindu Epistemology on Ranganathan's Colon Classification.

Science.gov (United States)

Maurer, Bradley Gerald

This study attempted to determine the influence of Hindu epistemology on Ranganathan's Colon Classification. Only the epistemological schools of Hindu philosophy and the Idea Plane element of Colon Classification were included. A literature search revealed that, although there is significant literature on each side of the problem, no bridges exist…

[New molecular classification of colorectal cancer, pancreatic cancer and stomach cancer: Towards "à la carte" treatment?].

Science.gov (United States)

Dreyer, Chantal; Afchain, Pauline; Trouilloud, Isabelle; André, Thierry

2016-01-01

This review reports 3 of recently published molecular classifications of the 3 main gastro-intestinal cancers: gastric, pancreatic and colorectal adenocarcinoma. In colorectal adenocarcinoma, 6 independent classifications were combined to finally hold 4 molecular sub-groups, Consensus Molecular Subtypes (CMS 1-4), linked to various clinical, molecular and survival data. CMS1 (14% MSI with immune activation); CMS2 (37%: canonical with epithelial differentiation and activation of the WNT/MYC pathway); CMS3 (13% metabolic with epithelial differentiation and RAS mutation); CMS4 (23%: mesenchymal with activation of TGFβ pathway and angiogenesis with stromal invasion). In gastric adenocarcinoma, 4 groups were established: subtype "EBV" (9%, high frequency of PIK3CA mutations, hypermetylation and amplification of JAK2, PD-L1 and PD-L2), subtype "MSI" (22%, high rate of mutation), subtype "genomically stable tumor" (20%, diffuse histology type and mutations of RAS and genes encoding integrins and adhesion proteins including CDH1) and subtype "tumors with chromosomal instability" (50%, intestinal type, aneuploidy and receptor tyrosine kinase amplification). In pancreatic adenocarcinomas, a classification in four sub-groups has been proposed, stable subtype (20%, aneuploidy), locally rearranged subtype (30%, focal event on one or two chromosoms), scattered subtype (36%,200 structural variation events, defects in DNA maintenance). Although currently away from the care of patients, these classifications open the way to "à la carte" treatment depending on molecular biology. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Protein structure: geometry, topology and classification

Energy Technology Data Exchange (ETDEWEB)

Taylor, William R.; May, Alex C.W.; Brown, Nigel P.; Aszodi, Andras [Division of Mathematical Biology, National Institute for Medical Research, London (United Kingdom)

2001-04-01

The structural principals of proteins are reviewed and analysed from a geometric perspective with a view to revealing the underlying regularities in their construction. Computer methods for the automatic comparison and classification of these structures are then reviewed with an analysis of the statistical significance of comparing different shapes. Following an analysis of the current state of the classification of proteins, more abstract geometric and topological representations are explored, including the occurrence of knotted topologies. The review concludes with a consideration of the origin of higher-level symmetries in protein structure. (author)

The correlation between biological activity and diffusion-weighted MR imaging and ADC value in cases with prostate cancer.

Science.gov (United States)

Sokmen, Bedriye Koyuncu; Sokmen, Dogukan; Ucar, Nese; Ozkurt, Huseyin; Simsek, Abdulmuttalip

2017-12-31

Firstly, we aimed to investigate the correlation among dynamic contrasted magnetic resonance (MR) images, diffusion-weighted MR images, and apparent diffusion coefficent (ADC) values in patients with prostate cancer. Secondly, we aimed to investigate the roles of these variables on clinical risk classification and the biological behavior of the prostate cancer. A total of sixty with prostatic adenocarcinoma patients diagnosed between January 2011 and May 2013 were retrospectively included in the study. Risk classification of patients were evaluated as low-risk (Group 1) (n = 20) (Stage T1c-T2a, PSA T3a, PSA > 20 ng/ml, Gleason Score > 7). Diffusion-weighted MR images, dynamic contrasted MR images, and ADC values of the prostates were correlated. ADC values of the cases in Group 3 were lower than those of the other groups (p values of the areas without malignancy did not differ significantly between groups (p > 0.05). Biological activity of the tumor tissue was determined by GS, while a negative correlation was observed between GSs and ADC values of the patients, (p values were obtained. These measured values can play a role in the noninvasive determination of the cellularity of the tumoral mass.

Classification, disease, and diagnosis.

Science.gov (United States)

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.

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

Science.gov (United States)

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

ILAE Classification of the Epilepsies Position Paper of the ILAE Commission for Classification and Terminology

Science.gov (United States)

Scheffer, Ingrid E; Berkovic, Samuel; Capovilla, Giuseppe; Connolly, Mary B; French, Jacqueline; Guilhoto, Laura; Hirsch, Edouard; Jain, Satish; Mathern, Gary W.; Moshé, Solomon L; Nordli, Douglas R; Perucca, Emilio; Tomson, Torbjörn; Wiebe, Samuel; Zhang, Yue-Hua; Zuberi, Sameer M

2017-01-01

Summary The ILAE Classification of the Epilepsies has been updated to reflect our gain in understanding of the epilepsies and their underlying mechanisms following the major scientific advances which have taken place since the last ratified classification in 1989. As a critical tool for the practising clinician, epilepsy classification must be relevant and dynamic to changes in thinking, yet robust and translatable to all areas of the globe. Its primary purpose is for diagnosis of patients, but it is also critical for epilepsy research, development of antiepileptic therapies and communication around the world. The new classification originates from a draft document submitted for public comments in 2013 which was revised to incorporate extensive feedback from the international epilepsy community over several rounds of consultation. It presents three levels, starting with seizure type where it assumes that the patient is having epileptic seizures as defined by the new 2017 ILAE Seizure Classification. After diagnosis of the seizure type, the next step is diagnosis of epilepsy type, including focal epilepsy, generalized epilepsy, combined generalized and focal epilepsy, and also an unknown epilepsy group. The third level is that of epilepsy syndrome where a specific syndromic diagnosis can be made. The new classification incorporates etiology along each stage, emphasizing the need to consider etiology at each step of diagnosis as it often carries significant treatment implications. Etiology is broken into six subgroups, selected because of their potential therapeutic consequences. New terminology is introduced such as developmental and epileptic encephalopathy. The term benign is replaced by the terms self-limited and pharmacoresponsive, to be used where appropriate. It is hoped that this new framework will assist in improving epilepsy care and research in the 21st century. PMID:28276062

CLINICAL AND MORPHOLOGICAL CLASSIFICATION OF CEREBRAL INTRAVENTRICULAR HEMORRHAGES

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V. V. Vlasyuk

2013-01-01

Full Text Available Inconsistency of the current classification of cerebral intraventricular hemorrhages is discussed in the article. The author explains divergence of including of the subependymal (1st stage and intracerebral (4th stage hemorrhages into this classification. A new classification of cerebral intraventricular hemorrhages including their origin, phases and stages is offered. The most common origin of intraventricular hemorrhages is subependymal hemorrhage (82,2%. Two phases of hemorrhage were distinguished: bleeding phase and resorption phase. Stages of intraventricular hemorrhages reflecting the blood movement after the onset of bleeding are the following: 1 — infill of the up to ½ of the lateral ventricles without their enlargement; 2 — infill of more than ½ of the lateral ventricles with their enlargement; 3 — infill of the IV ventricle, of the cerebellomedullary cistern and its dislocation into the subarachnoid space of the cerebellum, pons varolii, medulla oblongata and spinal cord.

DEPA classification: a proposal for standardising PRP use and a retrospective application of available devices.

Science.gov (United States)

Magalon, J; Chateau, A L; Bertrand, B; Louis, M L; Silvestre, A; Giraudo, L; Veran, J; Sabatier, F

2016-01-01

Significant biological differences in platelet-rich plasma (PRP) preparations have been highlighted and could explain the large variability in the clinical benefit of PRP reported in the literature. The scientific community now recommends the use of classification for PRP injection; however, these classifications are focused on platelet and leucocyte concentrations. This presents the disadvantages of (1) not taking into account the final volume of the preparation; (2) omitting the presence of red blood cells in PRP and (3) not assessing the efficiency of production. On the basis of standards classically used in the Cell Therapy field, we propose the DEPA (Dose of injected platelets, Efficiency of production, Purity of the PRP, Activation of the PRP) classification to extend the characterisation of the injected PRP preparation. We retrospectively applied this classification on 20 PRP preparations for which biological characteristics were available in the literature. Dose of injected platelets varies from 0.21 to 5.43 billion, corresponding to a 25-fold increase. Only a Magellan device was able to obtain an A score for this parameter. Assessments of the efficiency of production reveal that no device is able to recover more than 90% of platelets from the blood. Purity of the preparation reveals that a majority of the preparations are contaminated by red blood cells as only three devices reach an A score for this parameter, corresponding to a percentage of platelets compared with red blood cells and leucocytes over 90%. These findings should provide significant help to clinicians in selecting a system that meets their specific needs for a given indication.

A Two-Level Sound Classification Platform for Environmental Monitoring

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Stelios A. Mitilineos

2018-01-01

Full Text Available STORM is an ongoing European research project that aims at developing an integrated platform for monitoring, protecting, and managing cultural heritage sites through technical and organizational innovation. Part of the scheduled preventive actions for the protection of cultural heritage is the development of wireless acoustic sensor networks (WASNs that will be used for assessing the impact of human-generated activities as well as for monitoring potentially hazardous environmental phenomena. Collected sound samples will be forwarded to a central server where they will be automatically classified in a hierarchical manner; anthropogenic and environmental activity will be monitored, and stakeholders will be alarmed in the case of potential malevolent behavior or natural phenomena like excess rainfall, fire, gale, high tides, and waves. Herein, we present an integrated platform that includes sound sample denoising using wavelets, feature extraction from sound samples, Gaussian mixture modeling of these features, and a powerful two-layer neural network for automatic classification. We contribute to previous work by extending the proposed classification platform to perform low-level classification too, i.e., classify sounds to further subclasses that include airplane, car, and pistol sounds for the anthropogenic sound class; bird, dog, and snake sounds for the biophysical sound class; and fire, waterfall, and gale for the geophysical sound class. Classification results exhibit outstanding classification accuracy in both high-level and low-level classification thus demonstrating the feasibility of the proposed approach.

Featureless classification of light curves

Science.gov (United States)

Kügler, S. D.; Gianniotis, N.; Polsterer, K. L.

2015-08-01

In the era of rapidly increasing amounts of time series data, classification of variable objects has become the main objective of time-domain astronomy. Classification of irregularly sampled time series is particularly difficult because the data cannot be represented naturally as a vector which can be directly fed into a classifier. In the literature, various statistical features serve as vector representations. In this work, we represent time series by a density model. The density model captures all the information available, including measurement errors. Hence, we view this model as a generalization to the static features which directly can be derived, e.g. as moments from the density. Similarity between each pair of time series is quantified by the distance between their respective models. Classification is performed on the obtained distance matrix. In the numerical experiments, we use data from the OGLE (Optical Gravitational Lensing Experiment) and ASAS (All Sky Automated Survey) surveys and demonstrate that the proposed representation performs up to par with the best currently used feature-based approaches. The density representation preserves all static information present in the observational data, in contrast to a less-complete description by features. The density representation is an upper boundary in terms of information made available to the classifier. Consequently, the predictive power of the proposed classification depends on the choice of similarity measure and classifier, only. Due to its principled nature, we advocate that this new approach of representing time series has potential in tasks beyond classification, e.g. unsupervised learning.

Safety classification of nuclear power plant systems, structures and components

International Nuclear Information System (INIS)

1992-01-01

The Safety Classification principles used for the systems, structures and components of a nuclear power plant are detailed in the guide. For classification, the nuclear power plant is divided into structural and operational units called systems. Every structure and component under control is included into some system. The Safety Classes are 1, 2 and 3 and the Class EYT (non-nuclear). Instructions how to assign each system, structure and component to an appropriate safety class are given in the guide. The guide applies to new nuclear power plants and to the safety classification of systems, structures and components designed for the refitting of old nuclear power plants. The classification principles and procedures applying to the classification document are also given

How to Move Beyond the Diagnostic and Statistical Manual of Mental Disorders/International Classification of Diseases.

Science.gov (United States)

Schildkrout, Barbara

2016-10-01

A new nosology for mental disorders is needed as a basis for effective scientific inquiry. Diagnostic and Statistical Manual of Mental Disorders and International Classification of Diseases diagnoses are not natural, biological categories, and these diagnostic systems do not address mental phenomena that exist on a spectrum. Advances in neuroscience offer the hope of breakthroughs for diagnosing and treating major mental illness in the future. At present, a neuroscience-based understanding of brain/behavior relationships can reshape clinical thinking. Neuroscience literacy allows psychiatrists to formulate biologically informed psychological theories, to follow neuroscientific literature pertinent to psychiatry, and to embark on a path toward neurologically informed clinical thinking that can help move the field away from Diagnostic and Statistical Manual of Mental Disorders and International Classification of Diseases conceptualizations. Psychiatrists are urged to work toward attaining neuroscience literacy to prepare for and contribute to the development of a new nosology.

Ecosystem classification, Chapter 2

Science.gov (United States)

M.J. Robin-Abbott; L.H. Pardo

2011-01-01

The ecosystem classification in this report is based on the ecoregions developed through the Commission for Environmental Cooperation (CEC) for North America (CEC 1997). Only ecosystems that occur in the United States are included. CEC ecoregions are described, with slight modifications, below (CEC 1997) and shown in Figures 2.1 and 2.2. We chose this ecosystem...

Standard classification: Physics

International Nuclear Information System (INIS)

1977-01-01

This is a draft standard classification of physics. The conception is based on the physics part of the systematic catalogue of the Bayerische Staatsbibliothek and on the classification given in standard textbooks. The ICSU-AB classification now used worldwide by physics information services was not taken into account. (BJ) [de

Dense Iterative Contextual Pixel Classification using Kriging

DEFF Research Database (Denmark)

Ganz, Melanie; Loog, Marco; Brandt, Sami

2009-01-01

have been proposed to this end, e.g., iterative contextual pixel classification, iterated conditional modes, and other approaches related to Markov random fields. A problem of these methods, however, is their computational complexity, especially when dealing with high-resolution images in which......In medical applications, segmentation has become an ever more important task. One of the competitive schemes to perform such segmentation is by means of pixel classification. Simple pixel-based classification schemes can be improved by incorporating contextual label information. Various methods...... relatively long range interactions may play a role. We propose a new method based on Kriging that makes it possible to include such long range interactions, while keeping the computations manageable when dealing with large medical images....

A unified classification of alien species based on the magnitude of their environmental impacts

Czech Academy of Sciences Publication Activity Database

Blackburn, T. M.; Essl, F.; Evans, T.; Hulme, P. E.; Jeschke, J.M.; Kühn, I.; Kumschick, S.; Marková, Zuzana; Mrugala, A.; Nentwig, W.; Pergl, Jan; Pyšek, Petr; Rabitsch, W.; Ricciardi, A.; Richardson, D. M.; Sendek, A.; Vila, M.; Wilson, J. R. U.; Winter, M.; Genovesi, P.; Bacher, S.

2014-01-01

Roč. 12, č. 5 (2014), s. 1-11, e1001850 E-ISSN 1545-7885 R&D Projects: GA ČR(CZ) GAP504/11/1028; GA ČR GB14-36079G Institutional support: RVO:67985939 Keywords : biological invasions * classification * environmental impact Subject RIV: EF - Botanics Impact factor: 9.343, year: 2014

Intelligent Computer Vision System for Automated Classification

International Nuclear Information System (INIS)

Jordanov, Ivan; Georgieva, Antoniya

2010-01-01

In this paper we investigate an Intelligent Computer Vision System applied for recognition and classification of commercially available cork tiles. The system is capable of acquiring and processing gray images using several feature generation and analysis techniques. Its functionality includes image acquisition, feature extraction and preprocessing, and feature classification with neural networks (NN). We also discuss system test and validation results from the recognition and classification tasks. The system investigation also includes statistical feature processing (features number and dimensionality reduction techniques) and classifier design (NN architecture, target coding, learning complexity and performance, and training with our own metaheuristic optimization method). The NNs trained with our genetic low-discrepancy search method (GLPτS) for global optimisation demonstrated very good generalisation abilities. In our view, the reported testing success rate of up to 95% is due to several factors: combination of feature generation techniques; application of Analysis of Variance (ANOVA) and Principal Component Analysis (PCA), which appeared to be very efficient for preprocessing the data; and use of suitable NN design and learning method.

Advances in the Genetic Characterization of Cutaneous Mesenchymal Neoplasms: Implications for Tumor Classification and Novel Diagnostic Markers.

Science.gov (United States)

Compton, Leigh A; Doyle, Leona A

2017-06-01

Cutaneous mesenchymal neoplasms often pose significant diagnostic challenges; many such entities are rare or show clinical and histologic overlap with both other mesenchymal and non-mesenchymal lesions. Recent advances in the genetic classification of many cutaneous mesenchymal neoplasms have not only helped define unique pathologic entities and increase our understanding of their biology, but have also provided new diagnostic markers. This review details these recent discoveries, with a focus on their implications for tumor classification and diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

The 2015 World Health Organization Classification of Lung Tumors: Impact of Genetic, Clinical and Radiologic Advances Since the 2004 Classification.

Science.gov (United States)

Travis, William D; Brambilla, Elisabeth; Nicholson, Andrew G; Yatabe, Yasushi; Austin, John H M; Beasley, Mary Beth; Chirieac, Lucian R; Dacic, Sanja; Duhig, Edwina; Flieder, Douglas B; Geisinger, Kim; Hirsch, Fred R; Ishikawa, Yuichi; Kerr, Keith M; Noguchi, Masayuki; Pelosi, Giuseppe; Powell, Charles A; Tsao, Ming Sound; Wistuba, Ignacio

2015-09-01

The 2015 World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart has just been published with numerous important changes from the 2004 WHO classification. The most significant changes in this edition involve (1) use of immunohistochemistry throughout the classification, (2) a new emphasis on genetic studies, in particular, integration of molecular testing to help personalize treatment strategies for advanced lung cancer patients, (3) a new classification for small biopsies and cytology similar to that proposed in the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (4) a completely different approach to lung adenocarcinoma as proposed by the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (5) restricting the diagnosis of large cell carcinoma only to resected tumors that lack any clear morphologic or immunohistochemical differentiation with reclassification of the remaining former large cell carcinoma subtypes into different categories, (6) reclassifying squamous cell carcinomas into keratinizing, nonkeratinizing, and basaloid subtypes with the nonkeratinizing tumors requiring immunohistochemistry proof of squamous differentiation, (7) grouping of neuroendocrine tumors together in one category, (8) adding NUT carcinoma, (9) changing the term sclerosing hemangioma to sclerosing pneumocytoma, (10) changing the name hamartoma to "pulmonary hamartoma," (11) creating a group of PEComatous tumors that include (a) lymphangioleiomyomatosis, (b) PEComa, benign (with clear cell tumor as a variant) and (c) PEComa, malignant, (12) introducing the entity pulmonary myxoid sarcoma with an EWSR1-CREB1 translocation, (13) adding the entities myoepithelioma and myoepithelial carcinomas, which can show EWSR1 gene rearrangements, (14) recognition of usefulness of WWTR1-CAMTA1 fusions in diagnosis of epithelioid

ACCUWIND - Methods for classification of cup anemometers

Energy Technology Data Exchange (ETDEWEB)

Dahlberg, J.Aa.; Friis Pedersen, T.; Busche, P.

2006-05-15

Errors associated with the measurement of wind speed are the major sources of uncertainties in power performance testing of wind turbines. Field comparisons of well-calibrated anemometers show significant and not acceptable difference. The European CLASSCUP project posed the objectives to quantify the errors associated with the use of cup anemometers, and to develop a classification system for quantification of systematic errors of cup anemometers. This classification system has now been implemented in the IEC 61400-12-1 standard on power performance measurements in annex I and J. The classification of cup anemometers requires general external climatic operational ranges to be applied for the analysis of systematic errors. A Class A category classification is connected to reasonably flat sites, and another Class B category is connected to complex terrain, General classification indices are the result of assessment of systematic deviations. The present report focuses on methods that can be applied for assessment of such systematic deviations. A new alternative method for torque coefficient measurements at inclined flow have been developed, which have then been applied and compared to the existing methods developed in the CLASSCUP project and earlier. A number of approaches including the use of two cup anemometer models, two methods of torque coefficient measurement, two angular response measurements, and inclusion and exclusion of influence of friction have been implemented in the classification process in order to assess the robustness of methods. The results of the analysis are presented as classification indices, which are compared and discussed. (au)

A simple phenotypic classification for celiac disease

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Ajit Sood

2018-04-01

Full Text Available Background/Aims : Celiac disease is a global health problem. The presentation of celiac disease has unfolded over years and it is now known that it can manifest at different ages, has varied presentations, and is prone to develop complications, if not managed properly. Although the Oslo definitions provide consensus on the various terminologies used in literature, there is no phenotypic classification providing a composite diagnosis for the disease. Methods : Various variables identified for phenotypic classification included age at diagnosis, age at onset of symptoms, clinical presentation, family history and complications. These were applied to the existing registry of 1,664 patients at Dayanand Medical College and Hospital, Ludhiana, India. In addition, age was evaluated as below 15 and below 18 years. Cross tabulations were used for the verification of the classification using the existing data. Expert opinion was sought from both international and national experts of varying fields. Results : After empirical verification, age at diagnosis was considered appropriate in between A1 (<18 and A2 (≧18. The disease presentation has been classified into 3 types–P1 (classical, P2 (non-classical and P3 (asymptomatic. Complications were considered as absent (C0 or present (C1. A single phenotypic classification based on these 3 characteristics, namely age at the diagnosis, clinical presentation, and intestinal complications (APC classification was derived. Conclusions : APC classification (age at diagnosis, presentation, complications is a simple disease explanatory classification for patients with celiac disease aimed at providing a composite diagnosis.

Guidance on classification for reproductive toxicity under the globally harmonized system of classification and labelling of chemicals (GHS).

Science.gov (United States)

Moore, Nigel P; Boogaard, Peter J; Bremer, Susanne; Buesen, Roland; Edwards, James; Fraysse, Benoit; Hallmark, Nina; Hemming, Helena; Langrand-Lerche, Carole; McKee, Richard H; Meisters, Marie-Louise; Parsons, Paul; Politano, Valerie; Reader, Stuart; Ridgway, Peter; Hennes, Christa

2013-11-01

The Globally Harmonised System of Classification (GHS) is a framework within which the intrinsic hazards of substances may be determined and communicated. It is not a legislative instrument per se, but is enacted into national legislation with the appropriate legislative instruments. GHS covers many aspects of effects upon health and the environment, including adverse effects upon sexual function and fertility or on development. Classification for these effects is based upon observations in humans or from properly designed experiments in animals, although only the latter is covered herein. The decision to classify a substance based upon experimental data, and the category of classification ascribed, is determined by the level of evidence that is available for an adverse effect on sexual function and fertility or on development that does not arise as a secondary non-specific consequence of other toxic effect. This document offers guidance on the determination of level of concern as a measure of adversity, and the level of evidence to ascribe classification based on data from tests in laboratory animals.

Nurses' perception about risk classification in an emergency service

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Cristiane Chaves de Souza

2014-04-01

Full Text Available Objective. Get to know how nurses perceive the accomplishment of risk classification in an emergency service. Methodology. In this qualitative study, 11 nurses were included with at least two months of experience in the risk classification of patients who visited the emergency service. Semistructured interviews were used to collect the information. The data were collected between August and December 2011. For data analysis, Bardin's theoretical framework was used. Results. The nurses in the study consider the risk classification as a work organization instruments that permits closer contact between nurses and patients. The nursing skills needed for risk classification were identified: knowledge about the scale used, clinical perspective, patience and agility. The availability of risk classification scales was the main facilitator of this work. The main difficulties were the disorganization of the care network and the health team's lack of knowledge of the protocol. Conclusion. Risk classification offers an opportunity for professional autonomy to the extent that it is the main responsible for regulating care at the entry door of the emergency services.

Epidemiology and Molecular Biology of Head and Neck Cancer.

Science.gov (United States)

Jou, Adriana; Hess, Jochen

2017-01-01

Head and neck cancer is a common and aggressive malignancy with a high morbidity and mortality profile. Although the large majority of cases resemble head and neck squamous cell carcinoma (HNSCC), the current classification based on anatomic site and tumor stage fails to capture the high level of biologic heterogeneity, and appropriate clinical management remains a major challenge. Hence, a better understanding of the molecular biology of HNSCC is urgently needed to support biomarker development and personalized care for patients. This review focuses on recent findings based on integrative genomics analysis and multi-scale modeling approaches and how they are beginning to provide more sophisticated clues as to the biological and clinical diversity of HNSCC. © 2017 S. Karger GmbH, Freiburg.

The paradox of atheoretical classification

DEFF Research Database (Denmark)

Hjørland, Birger

2016-01-01

A distinction can be made between “artificial classifications” and “natural classifications,” where artificial classifications may adequately serve some limited purposes, but natural classifications are overall most fruitful by allowing inference and thus many different purposes. There is strong...... support for the view that a natural classification should be based on a theory (and, of course, that the most fruitful theory provides the most fruitful classification). Nevertheless, atheoretical (or “descriptive”) classifications are often produced. Paradoxically, atheoretical classifications may...... be very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. Based on such successes one may ask: Should the claim that classifications ideally are natural...

Spectral classification of emission-line galaxies

International Nuclear Information System (INIS)

Veilleux, S.; Osterbrock, D.E.

1987-01-01

A revised method of classification of narrow-line active galaxies and H II region-like galaxies is proposed. It involves the line ratios which take full advantage of the physical distinction between the two types of objects and minimize the effects of reddening correction and errors in the flux calibration. Large sets of internally consistent data are used, including new, previously unpublished measurements. Predictions of recent photoionization models by power-law spectra and by hot stars are compared with the observations. The classification is based on the observational data interpreted on the basis of these models. 63 references

Interagency Security Classification Appeals Panel (ISCAP) Decisions

Data.gov (United States)

National Archives and Records Administration — This online collection includes documents decided upon by the Interagency Security Classification Appeals Panel (ISCAP) starting in Fiscal Year 2012. The documents...

Interaction of Herbal Compounds with Biological Targets: A Case Study with Berberine

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Xiao-Wu Chen

2012-01-01

Full Text Available Berberine is one of the main alkaloids found in the Chinese herb Huang lian (Rhizoma Coptidis, which has been reported to have multiple pharmacological activities. This study aimed to analyze the molecular targets of berberine based on literature data followed by a pathway analysis using the PANTHER program. PANTHER analysis of berberine targets showed that the most classes of molecular functions include receptor binding, kinase activity, protein binding, transcription activity, DNA binding, and kinase regulator activity. Based on the biological process classification of in vitro berberine targets, those targets related to signal transduction, intracellular signalling cascade, cell surface receptor-linked signal transduction, cell motion, cell cycle control, immunity system process, and protein metabolic process are most frequently involved. In addition, berberine was found to interact with a mixture of biological pathways, such as Alzheimer’s disease-presenilin and -secretase pathways, angiogenesis, apoptosis signalling pathway, FAS signalling pathway, Hungtington disease, inflammation mediated by chemokine and cytokine signalling pathways, interleukin signalling pathway, and p53 pathways. We also explored the possible mechanism of action for the anti-diabetic effect of berberine. Further studies are warranted to elucidate the mechanisms of action of berberine using systems biology approach.

Transporter Classification Database (TCDB)

Data.gov (United States)

U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

Establishment of water quality classification scheme: a case study of ...

African Journals Online (AJOL)

A water quality classification scheme based on 11 routinely measured physicochemical variables has been developed for the Calabar River Estuary. The variables considered include water temperature, pH. Eh, DO, DO saturation, BOD5, COD, TSS, turbidity, NH4-N and electrical conductivity. Classification of water source ...

Characteristics and application study of AP1000 NPPs equipment reliability classification method

International Nuclear Information System (INIS)

Guan Gao

2013-01-01

AP1000 nuclear power plant applies an integrated approach to establish equipment reliability classification, which includes probabilistic risk assessment technique, maintenance rule administrative, power production reliability classification and functional equipment group bounding method, and eventually classify equipment reliability into 4 levels. This classification process and result are very different from classical RCM and streamlined RCM. It studied the characteristic of AP1000 equipment reliability classification approach, considered that equipment reliability classification should effectively support maintenance strategy development and work process control, recommended to use a combined RCM method to establish the future equipment reliability program of AP1000 nuclear power plants. (authors)

Wagner classification and culture analysis of diabetic foot infection

Directory of Open Access Journals (Sweden)

Fatma Bozkurt

2011-03-01

Full Text Available The aim of this study was to determine the concordance ratio between microorganisms isolated from deep tissue culture and those from superficial culture in patients with diabetic foot according to Wagner’s wound classification method.Materials and methods: A total of 63 patients with Diabetic foot infection, who were admitted to Dicle University Hospital between October 2006 and November 2007, were included into the study. Wagner’s classification method was used for wound classification. For microbiologic studies superficial and deep tissue specimens were obtained from each patient, and were rapidly sent to laboratory for aerob and anaerob cultures. Microbiologic data were analyzed and interpreted in line with sensitivity and specifity formula.Results: Thirty-eight (60% of the patients were in Wagner’s classification ≤2, while 25 (40% patients were Wagner’s classification ≥3. According to our culture results, 66 (69% Gr (+ and 30 (31% Gr (- microorganisms grew in Wagner classification ≤2 patients. While in Wagner classification ≥3; 25 (35% Gr (+ and 46 (65% Gr (- microorganisms grew. Microorganisms grew in 89% of superficial cultures and 64% of the deep tissue cultures in patients with Wagner classification ≤2, while microorganism grew in 64% of Wagner classification ≥3.Conclusion: In ulcers of diabetic food infections, initial treatment should be started according to result of sterile superficial culture, but deep tissue culture should be taken, if unresponsive to initial treatment.

Glioma CpG island methylator phenotype (G-CIMP): biological and clinical implications.

Science.gov (United States)

Malta, Tathiane M; de Souza, Camila F; Sabedot, Thais S; Silva, Tiago C; Mosella, Maritza S; Kalkanis, Steven N; Snyder, James; Castro, Ana Valeria B; Noushmehr, Houtan

2018-04-09

Gliomas are a heterogeneous group of brain tumors with distinct biological and clinical properties. Despite advances in surgical techniques and clinical regimens, treatment of high-grade glioma remains challenging and carries dismal rates of therapeutic success and overall survival. Challenges include the molecular complexity of gliomas, as well as inconsistencies in histopathological grading, resulting in an inaccurate prediction of disease progression and failure in the use of standard therapy. The updated 2016 World Health Organization (WHO) classification of tumors of the central nervous system reflects a refinement of tumor diagnostics by integrating the genotypic and phenotypic features, thereby narrowing the defined subgroups. The new classification recommends molecular diagnosis of isocitrate dehydrogenase (IDH) mutational status in gliomas. IDH-mutant gliomas manifest the cytosine-phosphate-guanine (CpG) island methylator phenotype (G-CIMP). Notably, the recent identification of clinically relevant subsets of G-CIMP tumors (G-CIMP-high and G-CIMP-low) provides a further refinement in glioma classification that is independent of grade and histology. This scheme may be useful for predicting patient outcome and may be translated into effective therapeutic strategies tailored to each patient. In this review, we highlight the evolution of our understanding of the G-CIMP subsets and how recent advances in characterizing the genome and epigenome of gliomas may influence future basic and translational research.

Understanding pathologic variants of renal cell carcinoma: distilling therapeutic opportunities from biologic complexity.

Science.gov (United States)

Shuch, Brian; Amin, Ali; Armstrong, Andrew J; Eble, John N; Ficarra, Vincenzo; Lopez-Beltran, Antonio; Martignoni, Guido; Rini, Brian I; Kutikov, Alexander

2015-01-01

Once believed to represent a uniform malignant phenotype, renal cell carcinoma (RCC) is now viewed as a diverse group of cancers that arise from the nephron. To review the pathologic characteristics, clinical behavior, molecular biology, and systemic therapy options of recognized RCC histologic subtypes. A systematic review of English-language articles was performed using the Medline and Web of Science databases. Manuscripts were selected with consensus of the coauthors and evaluated using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. The major findings of the evaluated manuscripts are discussed with an emphasis on the description of the pathologic features, clinical behavior, prognosis, and therapeutic strategies. Classification schemes for kidney cancer have undergone dramatic changes over the past two decades. Improvements in these classification schemes are important, as pathologic variants differ not only in disease biology, but also in clinical behavior, prognosis, and response to systemic therapy. In the era of genomic medicine, further refinements in characterization of RCC subtypes will be critical to the progress of this burgeoning clinical space. Kidney cancer can be subdivided into related but different cancers that arise from the kidney's tubules. In this article we review current classifications for kidney cancer, discuss their characteristics, and provide an overview of each subtype's clinical behavior and treatment. We stress that each subtype harbors unique biology and thus responds differently to available treatment strategies. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

Energy Technology Data Exchange (ETDEWEB)

Jürgens, Björn, E-mail: bjurgens@agenciaidea.es [Agency of Innovation and Development of Andalusia, CITPIA PATLIB Centre (Spain); Herrero-Solana, Victor, E-mail: victorhs@ugr.es [University of Granada, SCImago-UGR (SEJ036) (Spain)

2017-04-15

Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

International Nuclear Information System (INIS)

Jürgens, Björn; Herrero-Solana, Victor

2017-01-01

Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

Disease Classification and Biomarker Discovery Using ECG Data

Directory of Open Access Journals (Sweden)

Rong Huang

2015-01-01

Full Text Available In the recent decade, disease classification and biomarker discovery have become increasingly important in modern biological and medical research. ECGs are comparatively low-cost and noninvasive in screening and diagnosing heart diseases. With the development of personal ECG monitors, large amounts of ECGs are recorded and stored; therefore, fast and efficient algorithms are called for to analyze the data and make diagnosis. In this paper, an efficient and easy-to-interpret procedure of cardiac disease classification is developed through novel feature extraction methods and comparison of classifiers. Motivated by the observation that the distributions of various measures on ECGs of the diseased group are often skewed, heavy-tailed, or multimodal, we characterize the distributions by sample quantiles which outperform sample means. Three classifiers are compared in application both to all features and to dimension-reduced features by PCA: stepwise discriminant analysis (SDA, SVM, and LASSO logistic regression. It is found that SDA applied to dimension-reduced features by PCA is the most stable and effective procedure, with sensitivity, specificity, and accuracy being 89.68%, 84.62%, and 88.52%, respectively.

[Changes introduced into the recent International Classification of Headache Disorders: ICHD-III beta classification].

Science.gov (United States)

Belvis, Robert; Mas, Natàlia; Roig, Carles

2015-01-16

The International Headache Society (IHS) has published the third edition of the International Classification of Headache Disorders (ICHD-III beta), the most commonly used guide to diagnosing headaches in the world. To review the recent additions to the guide, to explain the new entities that appear in it and to compare the conditions that have had their criteria further clarified against the criteria in the previous edition. We have recorded a large number of clarifications in the criteria in practically all the headaches and neuralgias in the classification, but the conditions that have undergone the most significant clarifications are chronic migraine, primary headache associated with sexual activity, short-lasting unilateral neuralgiform headache attacks, new daily persistent headache, medication-overuse headache, syndrome of transient headache and neurological deficits with cerebrospinal fluid lymphocytosis. The most notable new entities that have been incorporated are external-compression headache, cold-stimulus headache, nummular headache, headache attributed to aeroplane travel and headache attributed to autonomic dysreflexia. Another point to be highlighted is the case of the new headaches (still not considered entities in their own right) included in the appendix, some of the most noteworthy being epicrania fugax, vestibular migraine and infantile colic. The IHS recommends no longer using the previous classification and changing over to the new classification (ICHD-III beta) in healthcare, teaching and research, in addition to making this new guide as widely known as possible.

Investigating the use of support vector machine classification on structural brain images of preterm-born teenagers as a biological marker.

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Carlton Chu

Full Text Available Preterm birth has been shown to induce an altered developmental trajectory of brain structure and function. With the aid support vector machine (SVM classification methods we aimed to investigate whether MRI data, collected in adolescence, could be used to predict whether an individual had been born preterm or at term. To this end we collected T1-weighted anatomical MRI data from 143 individuals (69 controls, mean age 14.6y. The inclusion criteria for those born preterm were birth weight ≤ 1500g and gestational age < 37w. A linear SVM was trained on the grey matter segment of MR images in two different ways. First, all the individuals were used for training and classification was performed by the leave-one-out method, yielding 93% correct classification (sensitivity = 0.905, specificity = 0.942. Separately, a random half of the available data were used for training twice and each time the other, unseen, half of the data was classified, resulting 86% and 91% accurate classifications. Both gestational age (R = -0.24, p<0.04 and birth weight (R = -0.51, p < 0.001 correlated with the distance to decision boundary within the group of individuals born preterm. Statistically significant correlations were also found between IQ (R = -0.30, p < 0.001 and the distance to decision boundary. Those born small for gestational age did not form a separate subgroup in these analyses. The high rate of correct classification by the SVM motivates further investigation. The long-term goal is to automatically and non-invasively predict the outcome of preterm-born individuals on an individual basis using as early a scan as possible.

Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

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Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

1990-01-01

Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

Small-scale classification schemes

DEFF Research Database (Denmark)

Hertzum, Morten

2004-01-01

Small-scale classification schemes are used extensively in the coordination of cooperative work. This study investigates the creation and use of a classification scheme for handling the system requirements during the redevelopment of a nation-wide information system. This requirements...... classification inherited a lot of its structure from the existing system and rendered requirements that transcended the framework laid out by the existing system almost invisible. As a result, the requirements classification became a defining element of the requirements-engineering process, though its main...... effects remained largely implicit. The requirements classification contributed to constraining the requirements-engineering process by supporting the software engineers in maintaining some level of control over the process. This way, the requirements classification provided the software engineers...

A new classification of post-sternotomy dehiscence

Science.gov (United States)

Anger, Jaime; Dantas, Daniel Chagas; Arnoni, Renato Tambellini; Farsky, Pedro Sílvio

2015-01-01

The dehiscence after median transesternal sternotomy used as surgical access for cardiac surgery is one of its complications and it increases the patient's morbidity and mortality. A variety of surgical techniques were recently described resulting to the need of a classification bringing a measure of objectivity to the management of these complex and dangerous wounds. The different related classifications are based in the primary causal infection, but recently the anatomical description of the wound including the deepness and the vertical extension showed to be more useful. We propose a new classification based only on the anatomical changes following sternotomy dehiscence and chronic wound formation separating it in four types according to the deepness and in two sub-groups according to the vertical extension based on the inferior insertion of the pectoralis major muscle. PMID:25859875

Erythroleukemia shares biological features and outcome with myelodysplastic syndromes with excess blasts: a rationale for its inclusion into future classifications of myelodysplastic syndromes.

Science.gov (United States)

Calvo, Xavier; Arenillas, Leonor; Luño, Elisa; Senent, Leonor; Arnan, Montserrat; Ramos, Fernando; Ardanaz, María Teresa; Pedro, Carme; Tormo, Mar; Montoro, Julia; Díez-Campelo, María; Arrizabalaga, Beatriz; Xicoy, Blanca; Bonanad, Santiago; Jerez, Andrés; Nomdedeu, Benet; Ferrer, Ana; Sanz, Guillermo F; Florensa, Lourdes

2016-12-01

Erythroleukemia was considered an acute myeloid leukemia in the 2008 World Health Organization (WHO) classification and is defined by the presence of ≥50% bone marrow erythroblasts, having <20% bone marrow blasts from total nucleated cells but ≥20% bone marrow myeloblasts from nonerythroid cells. Erythroleukemia shares clinicopathologic features with myelodysplastic syndromes, especially with erythroid-predominant myelodysplastic syndromes (≥50% bone marrow erythroblasts). The upcoming WHO revision proposes to eliminate the nonerythroid blast cell count rule and to move erythroleukemia patients into the appropriate myelodysplastic syndrome category on the basis of the absolute blast cell count. We conducted a retrospective study of patients with de novo erythroleukemia and compared their clinico-biological features and outcome with those of de novo myelodysplastic syndromes, focusing on erythroid-predominant myelodysplastic syndromes. Median overall survival of 405 erythroid-predominant myelodysplastic syndromes without excess blasts was significantly longer than that observed in 57 erythroid-predominant refractory anemias with excess blasts-1 and in 59 erythroleukemias, but no significant difference was observed between erythroid-predominant refractory anemias with excess blasts-1 and erythroleukemias. In this subset of patients with ≥50% bone marrow erythroblasts and excess blasts, the presence of a high-risk karyotype defined by the International Prognostic Scoring System or by the Revised International Prognostic Scoring System was the main prognostic factor. In the same way, the survival of 459 refractory anemias with excess blasts-2, independently of having ≥20% bone marrow blasts from nonerythroid cells or not, was almost identical to the observed in 59 erythroleukemias. Interestingly, 11 low-blast count erythroleukemias with 5 to <10% bone marrow blasts from total nucleated cells showed similar survival than the rest of erythroleukemias. Our data

Trends and concepts in fern classification

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Christenhusz, Maarten J. M.; Chase, Mark W.

2014-01-01

sister to all other vascular plants, whereas the whisk ferns (Psilotaceae), often included in the lycopods or believed to be associated with the first vascular plants, are sister to Ophioglossaceae and thus belong to the fern clade. The horsetails (Equisetaceae) are also members of the fern clade (sometimes inappropriately called ‘monilophytes’), but, within that clade, their placement is still uncertain. Leptosporangiate ferns are better understood, although deep relationships within this group are still unresolved. Earlier, almost all leptosporangiate ferns were placed in a single family (Polypodiaceae or Dennstaedtiaceae), but these families have been redefined to narrower more natural entities. Conclusions Concluding this paper, a classification is presented based on our current understanding of relationships of fern and lycopod clades. Major changes in our understanding of these families are highlighted, illustrating issues of classification in relation to convergent evolution and false homologies. Problems with the current classification and groups that still need study are pointed out. A summary phylogenetic tree is also presented. A new classification in which Aspleniaceae, Cyatheaceae, Polypodiaceae and Schizaeaceae are expanded in comparison with the most recent classifications is presented, which is a modification of those proposed by Smith et al. (2006, 2008) and Christenhusz et al. (2011). These classifications are now finding a wider acceptance and use, and even though a few amendments are made based on recently published results from molecular analyses, we have aimed for a stable family and generic classification of ferns. PMID:24532607

Trends and concepts in fern classification.

Science.gov (United States)

Christenhusz, Maarten J M; Chase, Mark W

2014-03-01

the whisk ferns (Psilotaceae), often included in the lycopods or believed to be associated with the first vascular plants, are sister to Ophioglossaceae and thus belong to the fern clade. The horsetails (Equisetaceae) are also members of the fern clade (sometimes inappropriately called 'monilophytes'), but, within that clade, their placement is still uncertain. Leptosporangiate ferns are better understood, although deep relationships within this group are still unresolved. Earlier, almost all leptosporangiate ferns were placed in a single family (Polypodiaceae or Dennstaedtiaceae), but these families have been redefined to narrower more natural entities. Concluding this paper, a classification is presented based on our current understanding of relationships of fern and lycopod clades. Major changes in our understanding of these families are highlighted, illustrating issues of classification in relation to convergent evolution and false homologies. Problems with the current classification and groups that still need study are pointed out. A summary phylogenetic tree is also presented. A new classification in which Aspleniaceae, Cyatheaceae, Polypodiaceae and Schizaeaceae are expanded in comparison with the most recent classifications is presented, which is a modification of those proposed by Smith et al. (2006, 2008) and Christenhusz et al. (2011). These classifications are now finding a wider acceptance and use, and even though a few amendments are made based on recently published results from molecular analyses, we have aimed for a stable family and generic classification of ferns.

Reproductive Biology Including Evidence for Superfetation in the European Badger Meles meles (Carnivora: Mustelidae.

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Leigh A L Corner

Full Text Available The reproductive biology of the European badger (Meles meles is of wide interest because it is one of the few mammal species that show delayed implantation and one of only five which are suggested to show superfetation as a reproductive strategy. This study aimed to describe the reproductive biology of female Irish badgers with a view to increasing our understanding of the process of delayed implantation and superfetation. We carried out a detailed histological examination of the reproductive tract of 264 female badgers taken from sites across 20 of the 26 counties in the Republic of Ireland. The key results show evidence of multiple blastocysts at different stages of development present simultaneously in the same female, supporting the view that superfetation is relatively common in this population of badgers. In addition we present strong evidence that the breeding rate in Irish badgers is limited by failure to conceive, rather than failure at any other stages of the breeding cycle. We show few effects of age on breeding success, suggesting no breeding suppression by adult females in this population. The study sheds new light on this unusual breeding strategy of delayed implantation and superfetation, and highlights a number of significant differences between the reproductive biology of female Irish badgers and those of Great Britain and Swedish populations.

Automatic liver volume segmentation and fibrosis classification

Science.gov (United States)

Bal, Evgeny; Klang, Eyal; Amitai, Michal; Greenspan, Hayit

2018-02-01

In this work, we present an automatic method for liver segmentation and fibrosis classification in liver computed-tomography (CT) portal phase scans. The input is a full abdomen CT scan with an unknown number of slices, and the output is a liver volume segmentation mask and a fibrosis grade. A multi-stage analysis scheme is applied to each scan, including: volume segmentation, texture features extraction and SVM based classification. Data contains portal phase CT examinations from 80 patients, taken with different scanners. Each examination has a matching Fibroscan grade. The dataset was subdivided into two groups: first group contains healthy cases and mild fibrosis, second group contains moderate fibrosis, severe fibrosis and cirrhosis. Using our automated algorithm, we achieved an average dice index of 0.93 ± 0.05 for segmentation and a sensitivity of 0.92 and specificity of 0.81for classification. To the best of our knowledge, this is a first end to end automatic framework for liver fibrosis classification; an approach that, once validated, can have a great potential value in the clinic.

Knowledge-based approach to video content classification

Science.gov (United States)

Chen, Yu; Wong, Edward K.

2001-01-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

Host Rock Classification (HRC) system for nuclear waste disposal in crystalline bedrock

International Nuclear Information System (INIS)

Hagros, A.

2006-01-01

A new rock mass classification scheme, the Host Rock Classification system (HRC-system) has been developed for evaluating the suitability of volumes of rock mass for the disposal of high-level nuclear waste in Precambrian crystalline bedrock. To support the development of the system, the requirements of host rock to be used for disposal have been studied in detail and the significance of the various rock mass properties have been examined. The HRC-system considers both the long-term safety of the repository and the constructability in the rock mass. The system is specific to the KBS-3V disposal concept and can be used only at sites that have been evaluated to be suitable at the site scale. By using the HRC-system, it is possible to identify potentially suitable volumes within the site at several different scales (repository, tunnel and canister scales). The selection of the classification parameters to be included in the HRC-system is based on an extensive study on the rock mass properties and their various influences on the long-term safety, the constructability and the layout and location of the repository. The parameters proposed for the classification at the repository scale include fracture zones, strength/stress ratio, hydraulic conductivity and the Groundwater Chemistry Index. The parameters proposed for the classification at the tunnel scale include hydraulic conductivity, Q' and fracture zones and the parameters proposed for the classification at the canister scale include hydraulic conductivity, Q', fracture zones, fracture width (aperture + filling) and fracture trace length. The parameter values will be used to determine the suitability classes for the volumes of rock to be classified. The HRC-system includes four suitability classes at the repository and tunnel scales and three suitability classes at the canister scale and the classification process is linked to several important decisions regarding the location and acceptability of many components of

Independent Comparison of Popular DPI Tools for Traffic Classification

DEFF Research Database (Denmark)

Bujlow, Tomasz; Carela-Español, Valentín; Barlet-Ros, Pere

2015-01-01

Deep Packet Inspection (DPI) is the state-of-the-art technology for traffic classification. According to the conventional wisdom, DPI is the most accurate classification technique. Consequently, most popular products, either commercial or open-source, rely on some sort of DPI for traffic classifi......Deep Packet Inspection (DPI) is the state-of-the-art technology for traffic classification. According to the conventional wisdom, DPI is the most accurate classification technique. Consequently, most popular products, either commercial or open-source, rely on some sort of DPI for traffic......, application and web service). We carefully built a labeled dataset with more than 750K flows, which contains traffic from popular applications. We used the Volunteer-Based System (VBS), developed at Aalborg University, to guarantee the correct labeling of the dataset. We released this dataset, including full...

15th Conference of the International Federation of Classification Societies

CERN Document Server

Montanari, Angela; Vichi, Maurizio

2017-01-01

This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.

Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System.

Science.gov (United States)

de Moura, Karina de O A; Balbinot, Alexandre

2018-05-01

recovered the classification accuracy after the degradations, reaching an average of 5.7% below the classification of the clean signal, that is the signal without the contaminants or the original signal. Moreover, the proposed intelligent technique minimizes the impact of the motion classification caused by signal contamination related to degrading events over time. There are improvements in the virtual sensor model and in the algorithm optimization that need further development to provide an increase the clinical application of myoelectric prostheses but already presents robust results to enable research with virtual sensors on biological signs with stochastic behavior.

Physiotherapy movement based classification approaches to low back pain: comparison of subgroups through review and developer/expert survey

Directory of Open Access Journals (Sweden)

Karayannis Nicholas V

2012-02-01

Full Text Available Abstract Background Several classification schemes, each with its own philosophy and categorizing method, subgroup low back pain (LBP patients with the intent to guide treatment. Physiotherapy derived schemes usually have a movement impairment focus, but the extent to which other biological, psychological, and social factors of pain are encompassed requires exploration. Furthermore, within the prevailing 'biological' domain, the overlap of subgrouping strategies within the orthopaedic examination remains unexplored. The aim of this study was "to review and clarify through developer/expert survey, the theoretical basis and content of physical movement classification schemes, determine their relative reliability and similarities/differences, and to consider the extent of incorporation of the bio-psycho-social framework within the schemes". Methods A database search for relevant articles related to LBP and subgrouping or classification was conducted. Five dominant movement-based schemes were identified: Mechanical Diagnosis and Treatment (MDT, Treatment Based Classification (TBC, Pathoanatomic Based Classification (PBC, Movement System Impairment Classification (MSI, and O'Sullivan Classification System (OCS schemes. Data were extracted and a survey sent to the classification scheme developers/experts to clarify operational criteria, reliability, decision-making, and converging/diverging elements between schemes. Survey results were integrated into the review and approval obtained for accuracy. Results Considerable diversity exists between schemes in how movement informs subgrouping and in the consideration of broader neurosensory, cognitive, emotional, and behavioural dimensions of LBP. Despite differences in assessment philosophy, a common element lies in their objective to identify a movement pattern related to a pain reduction strategy. Two dominant movement paradigms emerge: (i loading strategies (MDT, TBC, PBC aimed at eliciting a phenomenon

Automatic classification of blank substrate defects

Science.gov (United States)

Boettiger, Tom; Buck, Peter; Paninjath, Sankaranarayanan; Pereira, Mark; Ronald, Rob; Rost, Dan; Samir, Bhamidipati

2014-10-01

Mask preparation stages are crucial in mask manufacturing, since this mask is to later act as a template for considerable number of dies on wafer. Defects on the initial blank substrate, and subsequent cleaned and coated substrates, can have a profound impact on the usability of the finished mask. This emphasizes the need for early and accurate identification of blank substrate defects and the risk they pose to the patterned reticle. While Automatic Defect Classification (ADC) is a well-developed technology for inspection and analysis of defects on patterned wafers and masks in the semiconductors industry, ADC for mask blanks is still in the early stages of adoption and development. Calibre ADC is a powerful analysis tool for fast, accurate, consistent and automatic classification of defects on mask blanks. Accurate, automated classification of mask blanks leads to better usability of blanks by enabling defect avoidance technologies during mask writing. Detailed information on blank defects can help to select appropriate job-decks to be written on the mask by defect avoidance tools [1][4][5]. Smart algorithms separate critical defects from the potentially large number of non-critical defects or false defects detected at various stages during mask blank preparation. Mechanisms used by Calibre ADC to identify and characterize defects include defect location and size, signal polarity (dark, bright) in both transmitted and reflected review images, distinguishing defect signals from background noise in defect images. The Calibre ADC engine then uses a decision tree to translate this information into a defect classification code. Using this automated process improves classification accuracy, repeatability and speed, while avoiding the subjectivity of human judgment compared to the alternative of manual defect classification by trained personnel [2]. This paper focuses on the results from the evaluation of Automatic Defect Classification (ADC) product at MP Mask

Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

CERN Document Server

Pisharady, Pramod Kumar; Poh, Loh Ai

2014-01-01

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

Biological agents with potential for misuse: a historical perspective and defensive measures

International Nuclear Information System (INIS)

Bhalla, Deepak K.; Warheit, David B.

2004-01-01

Biological and chemical agents capable of producing serious illness or mortality have been used in biowarfare from ancient times. Use of these agents has progressed from crude forms in early and middle ages, when snakes and infected cadavers were used as weapons in battles, to sophisticated preparations for use during and after the second World War. Cults and terrorist organizations have attempted the use of biological agents with an aim to immobilize populations or cause serious harm. The reasons for interest in these agents by individuals and organizations include relative ease of acquisition, potential for causing mass casualty or panic, modest financing requirement, availability of technology, and relative ease of delivery. The Centers for Disease Control and Prevention has classified Critical Biological Agents into three major categories. This classification was based on several criteria, which include severity of impact on human health, potential for delivery in a weapon, capacity to cause panic and special needs for development, and stockpiling of medication. Agents that could cause the greatest harm following deliberate use were placed in category A. Category B included agents capable of producing serious harm and significant mortality but of lower magnitude than category A agents. Category C included emerging pathogens that could be developed for mass dispersion in future and their potential as a major health threat. A brief description of the category A bioagents is included and the pathophysiology of two particularly prominent agents, namely anthrax and smallpox, is discussed in detail. The potential danger from biological agents and their ever increasing threat to human populations have created a need for developing technologies for their early detection, for developing treatment strategies, and for refinement of procedures to ensure survival of affected individuals so as to attain the ultimate goal of eliminating the threat from intentional use of

Biological agents with potential for misuse: a historical perspective and defensive measures.

Science.gov (United States)

Bhalla, Deepak K; Warheit, David B

2004-08-15

Biological and chemical agents capable of producing serious illness or mortality have been used in biowarfare from ancient times. Use of these agents has progressed from crude forms in early and middle ages, when snakes and infected cadavers were used as weapons in battles, to sophisticated preparations for use during and after the second World War. Cults and terrorist organizations have attempted the use of biological agents with an aim to immobilize populations or cause serious harm. The reasons for interest in these agents by individuals and organizations include relative ease of acquisition, potential for causing mass casualty or panic, modest financing requirement, availability of technology, and relative ease of delivery. The Centers for Disease Control and Prevention has classified Critical Biological Agents into three major categories. This classification was based on several criteria, which include severity of impact on human health, potential for delivery in a weapon, capacity to cause panic and special needs for development, and stockpiling of medication. Agents that could cause the greatest harm following deliberate use were placed in category A. Category B included agents capable of producing serious harm and significant mortality but of lower magnitude than category A agents. Category C included emerging pathogens that could be developed for mass dispersion in future and their potential as a major health threat. A brief description of the category A bioagents is included and the pathophysiology of two particularly prominent agents, namely anthrax and smallpox, is discussed in detail. The potential danger from biological agents and their ever increasing threat to human populations have created a need for developing technologies for their early detection, for developing treatment strategies, and for refinement of procedures to ensure survival of affected individuals so as to attain the ultimate goal of eliminating the threat from intentional use of

Ordinary and Activated Bone Grafts: Applied Classification and the Main Features

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R. V. Deev

2015-01-01

Full Text Available Bone grafts are medical devices that are in high demand in clinical practice for substitution of bone defects and recovery of atrophic bone regions. Based on the analysis of the modern groups of bone grafts, the particularities of their composition, the mechanisms of their biological effects, and their therapeutic indications, applicable classification was proposed that separates the bone substitutes into “ordinary” and “activated.” The main differential criterion is the presence of biologically active components in the material that are standardized by qualitative and quantitative parameters: growth factors, cells, or gene constructions encoding growth factors. The pronounced osteoinductive and (or osteogenic properties of activated osteoplastic materials allow drawing upon their efficacy in the substitution of large bone defects.

A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification [version 2; referees: 2 approved

Directory of Open Access Journals (Sweden)

Jessica Roelands

2018-02-01

Full Text Available The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB. In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.

Bend-scale geomorphic classification and assessment of the Lower Missouri River from Sioux City, Iowa, to the Mississippi River for application to pallid sturgeon management

Science.gov (United States)

Jacobson, Robert B.; Colvin, Michael E.; Bulliner, Edward A.; Pickard, Darcy; Elliott, Caroline M.

2018-06-07

Management actions intended to increase growth and survival of pallid sturgeon (Scaphirhynchus albus) age-0 larvae on the Lower Missouri River require a comprehensive understanding of the geomorphic habitat template of the river. The study described here had two objectives relating to where channel-reconfiguration projects should be located to optimize effectiveness. The first objective was to develop a bend-scale (that is, at the scale of individual bends, defined as “cross-over to cross-over”) geomorphic classification of the Lower Missouri River to help in the design of monitoring and evaluation of such projects. The second objective was to explore whether geomorphic variables could provide insight into varying capacities of bends to intercept drifting larvae. The bend-scale classification was based on geomorphic and engineering variables for 257 bends from Sioux City, Iowa, to the confluence with the Mississippi River near St. Louis, Missouri. We used k-means clustering to identify groupings of bends that shared the same characteristics. Separate 3-, 4-, and 6-cluster classifications were developed and mapped. The three classifications are nested in a hierarchical structure. We also explored capacities of bends to intercept larvae through evaluation of linear models that predicted persistent sand area or catch per unit effort (CPUE) of age-0 sturgeon as a function of the same geomorphic variables used in the classification. All highly ranked models that predict persistent sand area contained mean channel width and standard deviation of channel width as significant variables. Some top-ranked models also included contributions of channel sinuosity and density of navigation structures. The sand-area prediction models have r-squared values of 0.648–0.674. In contrast, the highest-ranking CPUE models have r-squared values of 0.011–0.170, indicating much more uncertainty for the biological response variable. Whereas the persistent sand model documents that

Couinaud's classification v.s. Cho's classification. Their feasibility in the right hepatic lobe

International Nuclear Information System (INIS)

Shioyama, Yasukazu; Ikeda, Hiroaki; Sato, Motohito; Yoshimi, Fuyo; Kishi, Kazushi; Sato, Morio; Kimura, Masashi

2008-01-01

The objective of this study was to investigate if the new classification system proposed by Cho is feasible to clinical usage comparing with the classical Couinaud's one. One hundred consecutive cases of abdominal CT were studied using a 64 or an 8 slice multislice CT and created three dimensional portal vein images for analysis by the Workstation. We applied both Cho's classification and the classical Couinaud's one for each cases according to their definitions. Three diagnostic radiologists assessed their feasibility as category one (unable to classify) to five (clear to classify with total suit with the original classification criteria). And in each cases, we tried to judge whether Cho's or the classical Couinaud' classification could more easily transmit anatomical information. Analyzers could classified portal veins clearly (category 5) in 77 to 80% of cases and clearly (category 5) or almost clearly (category 4) in 86-93% along with both classifications. In the feasibility of classification, there was no statistically significant difference between two classifications. In 15 cases we felt that using Couinaud's classification is more convenient for us to transmit anatomical information to physicians than using Cho's one, because in these cases we noticed two large portal veins ramify from right main portal vein cranialy and caudaly and then we could not classify P5 as a branch of antero-ventral segment (AVS). Conversely in 17 cases we felt Cho's classification is more convenient because we could not divide right posterior branch as P6 and P7 and in these cases the right posterior portal vein ramified to several small branches. The anterior fissure vein was clearly noticed in only 60 cases. Comparing the classical Couinaud's classification and Cho's one in feasility of classification, there was no statistically significant difference. We propose we routinely report hepatic anatomy with the classical Couinauds classification and in the preoperative cases we

PROGRESSIVE DENSIFICATION AND REGION GROWING METHODS FOR LIDAR DATA CLASSIFICATION

Directory of Open Access Journals (Sweden)

J. L. Pérez-García

2012-07-01

Full Text Available At present, airborne laser scanner systems are one of the most frequent methods used to obtain digital terrain elevation models. While having the advantage of direct measurement on the object, the point cloud obtained has the need for classification of their points according to its belonging to the ground. This need for classification of raw data has led to appearance of multiple filters focused LiDAR classification information. According this approach, this paper presents a classification method that combines LiDAR data segmentation techniques and progressive densification to carry out the location of the points belonging to the ground. The proposed methodology is tested on several datasets with different terrain characteristics and data availability. In all case, we analyze the advantages and disadvantages that have been obtained compared with the individual techniques application and, in a special way, the benefits derived from the integration of both classification techniques. In order to provide a more comprehensive quality control of the classification process, the obtained results have been compared with the derived from a manual procedure, which is used as reference classification. The results are also compared with other automatic classification methodologies included in some commercial software packages, highly contrasted by users for LiDAR data treatment.

MeMoVolc report on classification and dynamics of volcanic explosive eruptions

Science.gov (United States)

Bonadonna, C.; Cioni, R.; Costa, A.; Druitt, T.; Phillips, J.; Pioli, L.; Andronico, D.; Harris, A.; Scollo, S.; Bachmann, O.; Bagheri, G.; Biass, S.; Brogi, F.; Cashman, K.; Dominguez, L.; Dürig, T.; Galland, O.; Giordano, G.; Gudmundsson, M.; Hort, M.; Höskuldsson, A.; Houghton, B.; Komorowski, J. C.; Küppers, U.; Lacanna, G.; Le Pennec, J. L.; Macedonio, G.; Manga, M.; Manzella, I.; Vitturi, M. de'Michieli; Neri, A.; Pistolesi, M.; Polacci, M.; Ripepe, M.; Rossi, E.; Scheu, B.; Sulpizio, R.; Tripoli, B.; Valade, S.; Valentine, G.; Vidal, C.; Wallenstein, N.

2016-11-01

Classifications of volcanic eruptions were first introduced in the early twentieth century mostly based on qualitative observations of eruptive activity, and over time, they have gradually been developed to incorporate more quantitative descriptions of the eruptive products from both deposits and observations of active volcanoes. Progress in physical volcanology, and increased capability in monitoring, measuring and modelling of explosive eruptions, has highlighted shortcomings in the way we classify eruptions and triggered a debate around the need for eruption classification and the advantages and disadvantages of existing classification schemes. Here, we (i) review and assess existing classification schemes, focussing on subaerial eruptions; (ii) summarize the fundamental processes that drive and parameters that characterize explosive volcanism; (iii) identify and prioritize the main research that will improve the understanding, characterization and classification of volcanic eruptions and (iv) provide a roadmap for producing a rational and comprehensive classification scheme. In particular, classification schemes need to be objective-driven and simple enough to permit scientific exchange and promote transfer of knowledge beyond the scientific community. Schemes should be comprehensive and encompass a variety of products, eruptive styles and processes, including for example, lava flows, pyroclastic density currents, gas emissions and cinder cone or caldera formation. Open questions, processes and parameters that need to be addressed and better characterized in order to develop more comprehensive classification schemes and to advance our understanding of volcanic eruptions include conduit processes and dynamics, abrupt transitions in eruption regime, unsteadiness, eruption energy and energy balance.

Adaptive SVM for Data Stream Classification

Directory of Open Access Journals (Sweden)

Isah A. Lawal

2017-07-01

Full Text Available In this paper, we address the problem of learning an adaptive classifier for the classification of continuous streams of data. We present a solution based on incremental extensions of the Support Vector Machine (SVM learning paradigm that updates an existing SVM whenever new training data are acquired. To ensure that the SVM effectiveness is guaranteed while exploiting the newly gathered data, we introduce an on-line model selection approach in the incremental learning process. We evaluated the proposed method on real world applications including on-line spam email filtering and human action classification from videos. Experimental results show the effectiveness and the potential of the proposed approach.

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

Science.gov (United States)

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Cheese Classification, Characterization, and Categorization: A Global Perspective.

Science.gov (United States)

Almena-Aliste, Montserrat; Mietton, Bernard

2014-02-01

Cheese is one of the most fascinating, complex, and diverse foods enjoyed today. Three elements constitute the cheese ecosystem: ripening agents, consisting of enzymes and microorganisms; the composition of the fresh cheese; and the environmental conditions during aging. These factors determine and define not only the sensory quality of the final cheese product but also the vast diversity of cheeses produced worldwide. How we define and categorize cheese is a complicated matter. There are various approaches to cheese classification, and a global approach for classification and characterization is needed. We review current cheese classification schemes and the limitations inherent in each of the schemes described. While some classification schemes are based on microbiological criteria, others rely on descriptions of the technologies used for cheese production. The goal of this review is to present an overview of comprehensive and practical integrative classification models in order to better describe cheese diversity and the fundamental differences within cheeses, as well as to connect fundamental technological, microbiological, chemical, and sensory characteristics to contribute to an overall characterization of the main families of cheese, including the expanding world of American artisanal cheeses.

An interobserver reliability comparison between the Orthopaedic Trauma Association's open fracture classification and the Gustilo and Anderson classification.

Science.gov (United States)

Ghoshal, A; Enninghorst, N; Sisak, K; Balogh, Z J

2018-02-01

To evaluate interobserver reliability of the Orthopaedic Trauma Association's open fracture classification system (OTA-OFC). Patients of any age with a first presentation of an open long bone fracture were included. Standard radiographs, wound photographs, and a short clinical description were given to eight orthopaedic surgeons, who independently evaluated the injury using both the Gustilo and Anderson (GA) and OTA-OFC classifications. The responses were compared for variability using Cohen's kappa. The overall interobserver agreement was ĸ = 0.44 for the GA classification and ĸ = 0.49 for OTA-OFC, which reflects moderate agreement (0.41 to 0.60) for both classifications. The agreement in the five categories of OTA-OFC was: for skin, ĸ = 0.55 (moderate); for muscle, ĸ = 0.44 (moderate); for arterial injury, ĸ = 0.74 (substantial); for contamination, ĸ = 0.35 (fair); and for bone loss, ĸ = 0.41 (moderate). Although the OTA-OFC, with similar interobserver agreement to GA, offers a more detailed description of open fractures, further development may be needed to make it a reliable and robust tool. Cite this article: Bone Joint J 2018;100-B:242-6. ©2018 The British Editorial Society of Bone & Joint Surgery.

Embedding filtering criteria into a wrapper marker selection method for brain tumor classification: an application on metabolic peak area ratios

International Nuclear Information System (INIS)

Kounelakis, M G; Zervakis, M E; Giakos, G C; Postma, G J; Buydens, L M C; Kotsiakis, X

2011-01-01

The purpose of this study is to identify reliable sets of metabolic markers that provide accurate classification of complex brain tumors and facilitate the process of clinical diagnosis. Several ratios of metabolites are tested alone or in combination with imaging markers. A wrapper feature selection and classification methodology is studied, employing Fisher's criterion for ranking the markers. The set of extracted markers that express statistical significance is further studied in terms of biological behavior with respect to the brain tumor type and grade. The outcome of this study indicates that the proposed method by exploiting the intrinsic properties of data can actually reveal reliable and biologically relevant sets of metabolic markers, which form an important adjunct toward a more accurate type and grade discrimination of complex brain tumors

ANALYSIS OF THE GUIDELINES FOR CLASSIFICATION OFADVERTISING COSTS IN TAXATION

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A. Diederichs

2016-07-01

Full Text Available Advertising plays a distinct role in economies around the world. Previous studieshave not resolved the question related to the classification of advertising as anexpense or capital asset. Understanding the principles set out in TheIncome TaxAct 58 of 1962, with regard to the classification of advertising cost as capital orrevenue of nature is important, since the incorrect interpretation of principles willhave a direct impact on tax liability. The focus of this study is the classification ofadvertising costs for tax purposes. Research questions posed in this paper areanswered through the development of a classification process that may assist withthe classification of advertising costs for the purpose of taxation. Guidelines forthe classification of advertising costs as capital or revenue of nature are needed tocorrectly classify advertising costs for tax purposes. Furthermore, thedetermination of when advertising costs will be regarded as capital of nature isalso determined. A qualitative research approach is applied, including a literaturereview of case law and income tax acts. The contribution of this study is found inthe guidelines set for the classification of advertising costs for tax purposes byusing principles from national and international case law.

Classification of human cancers based on DNA copy number amplification modeling

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Knuutila Sakari

2008-05-01

Full Text Available Abstract Background DNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associate with amplification mechanisms. Methods We applied a machine learning approach to model DNA copy number amplifications using a data set of binary amplification records at chromosome sub-band resolution from 4400 cases that represent 82 cancer types. Amplification data was fused with background data: clinical, histological and biological classifications, and cytogenetic annotations. Statistical hypothesis testing was used to mine associations between the data sets. Results Probabilistic clustering of each chromosome identified 111 amplification models and divided the cancer cases into clusters. The distribution of classification terms in the amplification-model based clustering of cancer cases revealed cancer classes that were associated with specific DNA copy number amplification models. Amplification patterns – finite or bounded descriptions of the ranges of the amplifications in the chromosome – were extracted from the clustered data and expressed according to the original cytogenetic nomenclature. This was achieved by maximal frequent itemset mining using the cluster-specific data sets. The boundaries of amplification patterns were shown to be enriched with fragile sites, telomeres, centromeres, and light chromosome bands. Conclusions Our results demonstrate that amplifications are non-random chromosomal changes and specifically selected in tumor tissue microenvironment. Furthermore, statistical evidence showed that specific chromosomal features

The history of female genital tract malformation classifications and proposal of an updated system.

Science.gov (United States)

Acién, Pedro; Acién, Maribel I

2011-01-01

A correct classification of malformations of the female genital tract is essential to prevent unnecessary and inadequate surgical operations and to compare reproductive results. An ideal classification system should be based on aetiopathogenesis and should suggest the appropriate therapeutic strategy. We conducted a systematic review of relevant articles found in PubMed, Scopus, Scirus and ISI webknowledge, and analysis of historical collections of 'female genital malformations' and 'classifications'. Of 124 full-text articles assessed for eligibility, 64 were included because they contained original general, partial or modified classifications. All the existing classifications were analysed and grouped. The unification of terms and concepts was also analysed. Traditionally, malformations of the female genital tract have been catalogued and classified as Müllerian malformations due to agenesis, lack of fusion, the absence of resorption and lack of posterior development of the Müllerian ducts. The American Fertility Society classification of the late 1980s included seven basic groups of malformations also considering the Müllerian development and the relationship of the malformations to fertility. Other classifications are based on different aspects: functional, defects in vertical fusion, embryological or anatomical (Vagina, Cervix, Uterus, Adnex and Associated Malformation: VCUAM classification). However, an embryological-clinical classification system seems to be the most appropriate. Accepting the need for a new classification system of genitourinary malformations that considers the experience gained from the application of the current classification systems, the aetiopathogenesis and that also suggests the appropriate treatment, we proposed an update of our embryological-clinical classification as a new system with six groups of female genitourinary anomalies.

Behavioral state classification in epileptic brain using intracranial electrophysiology

Science.gov (United States)

Kremen, Vaclav; Duque, Juliano J.; Brinkmann, Benjamin H.; Berry, Brent M.; Kucewicz, Michal T.; Khadjevand, Fatemeh; Van Gompel, Jamie; Stead, Matt; St. Louis, Erik K.; Worrell, Gregory A.

2017-04-01

Objective. Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. Approach. Data from seven patients (age 34+/- 12 , 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1-600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. Main results. Classification accuracy of 97.8  ±  0.3% (normal tissue) and 89.4  ±  0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8  ±  0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1  ±  1.6%). Spectral power in high frequency band features (Ripple (80-250 Hz), Fast Ripple (250-600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy  ⩾90% using a single electrode contact and single spectral feature. Significance. Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.

Alphanumerical classification for the subject files of the department of documentation of the Atomic Energy Commission; Classification alpha-numerique pour le fichier matieres du service de documentation du Commissariat a l'Energie Atomique

Energy Technology Data Exchange (ETDEWEB)

Braffort, P; Iung, J [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1956-07-01

The research activities of the Atomic Energy Commission cover a large variety of different subjects from theoretical physics and nuclear physics to biology, medicine or geology. Thus, about 350 scientific reviews are received and presented in the library. All those documents need to be classified to make the research of information easier for researchers. It describes the classification and codification of such a large quantity of documents. The classification uses a bidimensional system with 5 columns with inter-scale phenomena, corpuscular scale, nuclear scale, atomic and molecular scale and macroscopic scale as subject and 5 lines with theoretical problems, production, measurement, description and utilisation as topic. Some of the rules are given and examples are presented. (M.P.)

Classification with support hyperplanes

NARCIS (Netherlands)

G.I. Nalbantov (Georgi); J.C. Bioch (Cor); P.J.F. Groenen (Patrick)

2006-01-01

textabstractA new classification method is proposed, called Support Hy- perplanes (SHs). To solve the binary classification task, SHs consider the set of all hyperplanes that do not make classification mistakes, referred to as semi-consistent hyperplanes. A test object is classified using

Classification of Flotation Frothers

Directory of Open Access Journals (Sweden)

Jan Drzymala

2018-02-01

Full Text Available In this paper, a scheme of flotation frothers classification is presented. The scheme first indicates the physical system in which a frother is present and four of them i.e., pure state, aqueous solution, aqueous solution/gas system and aqueous solution/gas/solid system are distinguished. As a result, there are numerous classifications of flotation frothers. The classifications can be organized into a scheme described in detail in this paper. The frother can be present in one of four physical systems, that is pure state, aqueous solution, aqueous solution/gas and aqueous solution/gas/solid system. It results from the paper that a meaningful classification of frothers relies on choosing the physical system and next feature, trend, parameter or parameters according to which the classification is performed. The proposed classification can play a useful role in characterizing and evaluation of flotation frothers.

Impact of job classification on employment of seasonal workers

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Zoran Pandža

2011-07-01

Full Text Available The paper aims to improve the existing work organization, thus improving success of business process and ultimately reducing company costs. A change in organizational structure is proposed with the objective of achieving better and more efficient use of resources available within the company. Since the existing organization and classification of jobs does not meet the requirements of the age we live in, there is a need for new classification which would address many changes that have taken place over the years, including changes that are yet to be made for the purpose of further development of the company. Organization and management of the company as well as reorganization and implementation of a new classification is necessary to make it possible for the company to perform regular adjustment of business activities, because the conditions in which the company operates are changing fast. New classification would not actually change the number of sectors. Rather, existing personnel would be allocated in a better way, which would result in reduced needs for seasonal work force. In the process of defining the new organizational structure, one should consider the type, way of doing business, structural variables (division of labour, unity of command, authority and responsibility, span of control, division in business units, etc.. Expected results include improved organization and classification of jobs, improved quality of work, speed and efficiency. It should result in a company organized according to standards that are adjusted to modern times.

The correlation between biological activity and diffusion-weighted MR imaging and ADC value in cases with prostate cancer

Directory of Open Access Journals (Sweden)

Bedriye Koyuncu Sokmen

2017-12-01

Full Text Available Purpose: Firstly, we aimed to investigate the correlation among dynamic contrasted magnetic resonance (MR images, diffusion-weighted MR images, and apparent diffusion coefficent (ADC values in patients with prostate cancer. Secondly, we aimed to investigate the roles of these variables on clinical risk classification and the biological behavior of the prostate cancer. Methods: A total of sixty with prostatic adenocarcinoma patients diagnosed between January 2011 and May 2013 were retrospectively included in the study. Risk classification of patients were evaluated as low-risk (Group 1 (n = 20 (Stage T1c-T2a, PSA T3a, PSA > 20 ng/ml, Gleason Score > 7. Diffusion-weighted MR images, dynamic contrasted MR images, and ADC values of the prostates were correlated. Results: ADC values of the cases in Group 3 were lower than those of the other groups (p 0.05. Biological activity of the tumor tissue was determined by GS, while a negative correlation was observed between GSs and ADC values of the patients, (p < 0.001. Conclusion: In tumors with higher Gleason scores, lower ADC values were obtained. These measured values can play a role in the noninvasive determination of the cellularity of the tumoral mass.

Neural network models: from biology to many - body phenomenology

International Nuclear Information System (INIS)

Clark, J.W.

1993-01-01

Theoretical work in neural networks has a strange feel for most physicists. In some cases the aspect of design becomes paramount. More comfortable ground at least for many body theorists may be found in realistic biological simulation, although the complexity of most problems is so awesome that incisive results will be hard won. It has also shown the impressive capabilities of artificial networks in pattern recognition and classification may be exploited to solve management problems in experimental physics and for discovery of radically new theoretical description of physical systems. This advance represents an important step towards the ultimate goal of neuro biological paradigm. (A.B.)

DOE LLW classification rationale

International Nuclear Information System (INIS)

Flores, A.Y.

1991-01-01

This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission's classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems

Asteroid taxonomic classifications

International Nuclear Information System (INIS)

Tholen, D.J.

1989-01-01

This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

Recursive Cluster Elimination (RCE for classification and feature selection from gene expression data

Directory of Open Access Journals (Sweden)

Showe Louise C

2007-05-01

provide greater insight into the structure of the microarray data. Clustering genes for classification appears to result in some concomitant clustering of samples into subgroups. Our present implementation of SVM-RCE groups genes using the correlation metric. The success of the SVM-RCE method in classification suggests that gene interaction networks or other biologically relevant metrics that group genes based on functional parameters might also be useful.

Chromosomal Instability in Gastric Cancer Biology

Directory of Open Access Journals (Sweden)

Saffiyeh Saboor Maleki

2017-05-01

Full Text Available Gastric cancer (GC is the fifth most common cancer in the world and accounts for 7% of the total cancer incidence. The prognosis of GC is dismal in Western countries due to late diagnosis: approximately 70% of the patients die within 5 years following initial diagnosis. Recently, integrative genomic analyses led to the proposal of a molecular classification of GC into four subtypes, i.e.,microsatellite-instable, Epstein-Barr virus–positive, chromosomal-instable (CIN, and genomically stable GCs. Molecular classification of GC advances our knowledge of the biology of GC and may have implications for diagnostics and patient treatment. Diagnosis of microsatellite-instable GC and Epstein-Barr virus–positive GC is more or less straightforward. Microsatellite instability can be tested by immunohistochemistry (MLH1, PMS2, MSH2, and MSH6 and/or molecular-biological analysis. Epstein-Barr virus–positive GC can be tested by in situ hybridization (Epstein-Barr virus encoded small RNA. However, with regard to CIN, testing may be more complicated and may require a more in-depth knowledge of the underlying mechanism leading to CIN. In addition, CIN GC may not constitute a distinct subgroup but may rather be a compilation of a more heterogeneous group of tumors. In this review, we aim to clarify the definition of CIN and to point out the molecular mechanisms leading to this molecular phenotype and the challenges faced in characterizing this type of cancer.

Checking the Course of Colorectal Carcinoma Follow up Using Mathematical Classification of Tumor Marker Profiles

Czech Academy of Sciences Publication Activity Database

Holubec jr., L.; Botterlich, N.; Topolčan, O.; Finek, J.; Pikner, R.; Pecen, Ladislav; Holubec, L.

2002-01-01

Roč. 23, Suppl.1 (2002), s. 57 ISSN 1010-4283. [Meeting of the International Society for Oncodevelopmental Biology and Medicine /30./. 08.09.2002-12.09.2002, Boston] R&D Projects: GA MŠk ME 438 Institutional research plan: AV0Z1030915 Keywords : tumor markers * colorectal CA * mathematical classification Subject RIV: BA - General Mathematics

Understanding the use of standardized nursing terminology and classification systems in published research: A case study using the International Classification for Nursing Practice(®).

Science.gov (United States)

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice(®), Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions' impact on quality, safety and patient outcomes in published research is relatively unknown. This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice(®) as a case study. A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice(®) were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature. Since 2006, 38 studies have been published on the International Classification for Nursing Practice(®). The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice. Based on the published literature that features the International Classification for Nursing

The 'antisocial' person: an insight in to biology, classification and current evidence on treatment

Directory of Open Access Journals (Sweden)

Rajapakse Senaka

2010-07-01

Full Text Available Abstract Background This review analyses and summarises the recent advances in understanding the neurobiology of violence and empathy, taxonomical issues on defining personality disorders characterised by disregard for social norms, evidence for efficacy of different treatment modalities and ethical implications in defining 'at-risk' individuals for preventive interventions. Methods PubMed was searched with the keywords 'antisocial personality disorder', 'dissocial personality disorder' and 'psychopathy'. The search was limited to articles published in English over the last 10 years (1999 to 2009 Results Both diagnostic manuals used in modern psychiatry, the Diagnostic and Statistical Manual published by the American Psychiatric Association and the International Classification of Diseases published by the World Health Organization, identify a personality disorder sharing similar traits. It is termed antisocial personality disorder in the diagnostic and statistical manual and dissocial personality disorder in the International Classification of Diseases. However, some authors query the ability of the existing manuals to identify a special category termed 'psychopathy', which in their opinion deserves special attention. On treatment-related issues, many psychological and behavioural therapies have shown success rates ranging from 25% to 62% in different cohorts. Multisystemic therapy and cognitive behaviour therapy have been proven efficacious in many trials. There is no substantial evidence for the efficacy of pharmacological therapy. Currently, the emphasis is on early identification and prevention of antisocial behaviour despite the ethical implications of defining at-risk children. Conclusions Further research is needed in the areas of neuroendocrinological associations of violent behaviour, taxonomic existence of psychopathy and efficacy of treatment modalities.

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

Science.gov (United States)

Akbari, D.

2017-11-01

In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF) algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1) unsupervised feature extraction methods including principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF); (2) supervised feature extraction including decision boundary feature extraction (DBFE), discriminate analysis feature extraction (DAFE), and nonparametric weighted feature extraction (NWFE); (3) genetic algorithm (GA). The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

Improvement of Bioactive Compound Classification through Integration of Orthogonal Cell-Based Biosensing Methods

Directory of Open Access Journals (Sweden)

Goran N. Jovanovic

2007-01-01

Full Text Available Lack of specificity for different classes of chemical and biological agents, and false positives and negatives, can limit the range of applications for cell-based biosensors. This study suggests that the integration of results from algal cells (Mesotaenium caldariorum and fish chromatophores (Betta splendens improves classification efficiency and detection reliability. Cells were challenged with paraquat, mercuric chloride, sodium arsenite and clonidine. The two detection systems were independently investigated for classification of the toxin set by performing discriminant analysis. The algal system correctly classified 72% of the bioactive compounds, whereas the fish chromatophore system correctly classified 68%. The combined classification efficiency was 95%. The algal sensor readout is based on fluorescence measurements of changes in the energy producing pathways of photosynthetic cells, whereas the response from fish chromatophores was quantified using optical density. Change in optical density reflects interference with the functioning of cellular signal transduction networks. Thus, algal cells and fish chromatophores respond to the challenge agents through sufficiently different mechanisms of action to be considered orthogonal.

Alphanumerical classification for the subject files of the department of documentation of the Atomic Energy Commission; Classification alpha-numerique pour le fichier matieres du service de documentation du Commissariat a l'Energie Atomique

Energy Technology Data Exchange (ETDEWEB)

Braffort, P.; Iung, J. [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1956-07-01

The research activities of the Atomic Energy Commission cover a large variety of different subjects from theoretical physics and nuclear physics to biology, medicine or geology. Thus, about 350 scientific reviews are received and presented in the library. All those documents need to be classified to make the research of information easier for researchers. It describes the classification and codification of such a large quantity of documents. The classification uses a bidimensional system with 5 columns with inter-scale phenomena, corpuscular scale, nuclear scale, atomic and molecular scale and macroscopic scale as subject and 5 lines with theoretical problems, production, measurement, description and utilisation as topic. Some of the rules are given and examples are presented. (M.P.)

Branching processes in biology

CERN Document Server

Kimmel, Marek

2015-01-01

This book provides a theoretical background of branching processes and discusses their biological applications. Branching processes are a well-developed and powerful set of tools in the field of applied probability. The range of applications considered includes molecular biology, cellular biology, human evolution and medicine. The branching processes discussed include Galton-Watson, Markov, Bellman-Harris, Multitype, and General Processes. As an aid to understanding specific examples, two introductory chapters, and two glossaries are included that provide background material in mathematics and in biology. The book will be of interest to scientists who work in quantitative modeling of biological systems, particularly probabilists, mathematical biologists, biostatisticians, cell biologists, molecular biologists, and bioinformaticians. The authors are a mathematician and cell biologist who have collaborated for more than a decade in the field of branching processes in biology for this new edition. This second ex...

Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes.

Science.gov (United States)

Yates, Katherine L; Mellin, Camille; Caley, M Julian; Radford, Ben T; Meeuwig, Jessica J

2016-01-01

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are

Validation of a new classification for periprosthetic shoulder fractures.

Science.gov (United States)

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.

Biological role of lectins: A review

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K Kiran Kumar

2012-01-01

Full Text Available Lectins comprise a stracturally vary diverse class of proteins charecterized by their ability to selectively bind carbohydrate moieties of the glycoproteins of the cell surface. Lectins may be derived from plants, microbial or animal sources and may be soluble or membrane bound. Lectins is a tetramer made up of four nearly identical subunits. In human, lectins have been reported to cause food poisoning, hemolytic anemia, jaundice, digestive distress, protein and carbohydrate malabsorption and type I allergies. The present review focuses on the classification, structures, biological significance and application of lectins.

Marine molecular biology: An emerging field of biological sciences

Digital Repository Service at National Institute of Oceanography (India)

Thakur, N.L.; Jain, R.; Natalio, F.; Hamer, B.; Thakur, A.N.; Muller, W.E.G.

An appreciation of the potential applications of molecular biology is of growing importance in many areas of life sciences, including marine biology. During the past two decades, the development of sophisticated molecular technologies...

Revue bibliographique: les méthodes chimiques d'identification et de classification des champignons

Directory of Open Access Journals (Sweden)

Verscheure M.

2002-01-01

Full Text Available Chemotaxonomy of fungi : a review. For few years, advancements of molecular methods and analytical techniques enabled scientists to realise a classification of microorganisms based on biochemical characteristics. This classification, called chemotaxonomy, includes molecular methods and chemical methods which provide additional data and lead to a better identification and/or classification.

Characterization of carbon nanotubes and analytical methods for their determination in environmental and biological samples: A review

Energy Technology Data Exchange (ETDEWEB)

Herrero-Latorre, C., E-mail: carlos.herrero@usc.es; Álvarez-Méndez, J.; Barciela-García, J.; García-Martín, S.; Peña-Crecente, R.M.

2015-01-01

Highlights: • Analytical techniques for characterization of CNTs: classification, description and examples. • Determination methods for CNTs in biological and environmental samples. • Future trends and perspectives for characterization and determination of CNTs. - Abstract: In the present paper, a critical overview of the most commonly used techniques for the characterization and the determination of carbon nanotubes (CNTs) is given on the basis of 170 references (2000–2014). The analytical techniques used for CNT characterization (including microscopic and diffraction, spectroscopic, thermal and separation techniques) are classified, described, and illustrated with applied examples. Furthermore, the performance of sampling procedures as well as the available methods for the determination of CNTs in real biological and environmental samples are reviewed and discussed according to their analytical characteristics. In addition, future trends and perspectives in this field of work are critically presented.

32 CFR 2001.15 - Classification guides.

Science.gov (United States)

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

FACET CLASSIFICATIONS OF E-LEARNING TOOLS

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Olena Yu. Balalaieva

2013-12-01

Full Text Available The article deals with the classification of e-learning tools based on the facet method, which suggests the separation of the parallel set of objects into independent classification groups; at the same time it is not assumed rigid classification structure and pre-built finite groups classification groups are formed by a combination of values taken from the relevant facets. An attempt to systematize the existing classification of e-learning tools from the standpoint of classification theory is made for the first time. Modern Ukrainian and foreign facet classifications of e-learning tools are described; their positive and negative features compared to classifications based on a hierarchical method are analyzed. The original author's facet classification of e-learning tools is proposed.

Procurement of a Large Area Mapping FTIR Microscope for Organic-Inorganic Interfacial Analysis in Biological Materials

Science.gov (United States)

2015-12-31

SECURITY CLASSIFICATION OF: After acquiring the Infrared Imaging Microscope with large area mapping capabilities for structure -function research and...Inorganic Interfacial Analysis in Biological Materials The views, opinions and/or findings contained in this report are those of the author(s) and should...of a Large Area Mapping FTIR Microscope for Organic-Inorganic Interfacial Analysis in Biological Materials Report Title After acquiring the Infrared

Full-motion video analysis for improved gender classification

Science.gov (United States)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

Systematic analysis of ocular trauma by a new proposed ocular trauma classification

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Bhartendu Shukla

2017-01-01

Full Text Available Purpose: The current classification of ocular trauma does not incorporate adnexal trauma, injuries that are attributable to a nonmechanical cause and destructive globe injuries. This study proposes a new classification system of ocular trauma which is broader-based to allow for the classification of a wider range of ocular injuries not covered by the current classification. Methods: A clinic-based cross-sectional study to validate the proposed classification. We analyzed 535 cases of ocular injury from January 1, 2012 to February 28, 2012 over a 4-year period in an eye hospital in central India using our proposed classification system and compared it with conventional classification. Results: The new classification system allowed for classification of all 535 cases of ocular injury. The conventional classification was only able to classify 364 of the 535 trauma cases. Injuries involving the adnexa, nonmechanical injuries and destructive globe injuries could not be classified by the conventional classification, thus missing about 33% of cases. Conclusions: Our classification system shows an improvement over existing ocular trauma classification as it allows for the classification of all type of ocular injuries and will allow for better and specific prognostication. This system has the potential to aid communication between physicians and result in better patient care. It can also provide a more authentic, wide spectrum of ocular injuries in correlation with etiology. By including adnexal injuries and nonmechanical injuries, we have been able to classify all 535 cases of trauma. Otherwise, about 30% of cases would have been excluded from the study.

Maxillectomy defects: a suggested classification scheme.

Science.gov (United States)

Akinmoladun, V I; Dosumu, O O; Olusanya, A A; Ikusika, O F

2013-06-01

The term "maxillectomy" has been used to describe a variety of surgical procedures for a spectrum of diseases involving a diverse anatomical site. Hence, classifications of maxillectomy defects have often made communication difficult. This article highlights this problem, emphasises the need for a uniform system of classification and suggests a classification system which is simple and comprehensive. Articles related to this subject, especially those with specified classifications of maxillary surgical defects were sourced from the internet through Google, Scopus and PubMed using the search terms maxillectomy defects classification. A manual search through available literature was also done. The review of the materials revealed many classifications and modifications of classifications from the descriptive, reconstructive and prosthodontic perspectives. No globally acceptable classification exists among practitioners involved in the management of diseases in the mid-facial region. There were over 14 classifications of maxillary defects found in the English literature. Attempts made to address the inadequacies of previous classifications have tended to result in cumbersome and relatively complex classifications. A single classification that is based on both surgical and prosthetic considerations is most desirable and is hereby proposed.

TFOS DEWS II Definition and Classification Report.

Science.gov (United States)

Craig, Jennifer P; Nichols, Kelly K; Akpek, Esen K; Caffery, Barbara; Dua, Harminder S; Joo, Choun-Ki; Liu, Zuguo; Nelson, J Daniel; Nichols, Jason J; Tsubota, Kazuo; Stapleton, Fiona

2017-07-01

The goals of the TFOS DEWS II Definition and Classification Subcommittee were to create an evidence-based definition and a contemporary classification system for dry eye disease (DED). The new definition recognizes the multifactorial nature of dry eye as a disease where loss of homeostasis of the tear film is the central pathophysiological concept. Ocular symptoms, as a broader term that encompasses reports of discomfort or visual disturbance, feature in the definition and the key etiologies of tear film instability, hyperosmolarity, and ocular surface inflammation and damage were determined to be important for inclusion in the definition. In the light of new data, neurosensory abnormalities were also included in the definition for the first time. In the classification of DED, recent evidence supports a scheme based on the pathophysiology where aqueous deficient and evaporative dry eye exist as a continuum, such that elements of each are considered in diagnosis and management. Central to the scheme is a positive diagnosis of DED with signs and symptoms, and this is directed towards management to restore homeostasis. The scheme also allows consideration of various related manifestations, such as non-obvious disease involving ocular surface signs without related symptoms, including neurotrophic conditions where dysfunctional sensation exists, and cases where symptoms exist without demonstrable ocular surface signs, including neuropathic pain. This approach is not intended to override clinical assessment and judgment but should prove helpful in guiding clinical management and research. Copyright © 2017 Elsevier Inc. All rights reserved.

Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

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Tsatsoulis Costas

2010-05-01

Full Text Available Abstract Background There is increasing evidence that gene location and surrounding genes influence the functionality of genes in the eukaryotic genome. Knowing the Gene Ontology Slim terms associated with a gene gives us insight into a gene's functionality by informing us how its gene product behaves in a cellular context using three different ontologies: molecular function, biological process, and cellular component. In this study, we analyzed if we could classify a gene in Saccharomyces cerevisiae to its correct Gene Ontology Slim term using information about its location in the genome and information from its nearest-neighbouring genes using classification learning. Results We performed experiments to establish that the MultiBoostAB algorithm using the J48 classifier could correctly classify Gene Ontology Slim terms of a gene given information regarding the gene's location and information from its nearest-neighbouring genes for training. Different neighbourhood sizes were examined to determine how many nearest neighbours should be included around each gene to provide better classification rules. Our results show that by just incorporating neighbour information from each gene's two-nearest neighbours, the percentage of correctly classified genes to their correct Gene Ontology Slim term for each ontology reaches over 80% with high accuracy (reflected in F-measures over 0.80 of the classification rules produced. Conclusions We confirmed that in classifying genes to their correct Gene Ontology Slim term, the inclusion of neighbour information from those genes is beneficial. Knowing the location of a gene and the Gene Ontology Slim information from neighbouring genes gives us insight into that gene's functionality. This benefit is seen by just including information from a gene's two-nearest neighbouring genes.

Transporter taxonomy - a comparison of different transport protein classification schemes.

Science.gov (United States)

Viereck, Michael; Gaulton, Anna; Digles, Daniela; Ecker, Gerhard F

2014-06-01

Currently, there are more than 800 well characterized human membrane transport proteins (including channels and transporters) and there are estimates that about 10% (approx. 2000) of all human genes are related to transport. Membrane transport proteins are of interest as potential drug targets, for drug delivery, and as a cause of side effects and drug–drug interactions. In light of the development of Open PHACTS, which provides an open pharmacological space, we analyzed selected membrane transport protein classification schemes (Transporter Classification Database, ChEMBL, IUPHAR/BPS Guide to Pharmacology, and Gene Ontology) for their ability to serve as a basis for pharmacology driven protein classification. A comparison of these membrane transport protein classification schemes by using a set of clinically relevant transporters as use-case reveals the strengths and weaknesses of the different taxonomy approaches.

Constructing criticality by classification

DEFF Research Database (Denmark)

Machacek, Erika

2017-01-01

" in the bureaucratic practice of classification: Experts construct material criticality in assessments as they allot information on the materials to the parameters of the assessment framework. In so doing, they ascribe a new set of connotations to the materials, namely supply risk, and their importance to clean energy......, legitimizing a criticality discourse.Specifically, the paper introduces a typology delineating the inferences made by the experts from their produced recommendations in the classification of rare earth element criticality. The paper argues that the classification is a specific process of constructing risk....... It proposes that the expert bureaucratic practice of classification legitimizes (i) the valorisation that was made in the drafting of the assessment framework for the classification, and (ii) political operationalization when enacted that might have (non-)distributive implications for the allocation of public...

12 CFR 403.4 - Derivative classification.

Science.gov (United States)

2010-01-01

... SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative classification. (1) Unlike original classification which is an initial determination, derivative classification... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Derivative classification. 403.4 Section 403.4...

Supernova Photometric Lightcurve Classification

Science.gov (United States)

Zaidi, Tayeb; Narayan, Gautham

2016-01-01

This is a preliminary report on photometric supernova classification. We first explore the properties of supernova light curves, and attempt to restructure the unevenly sampled and sparse data from assorted datasets to allow for processing and classification. The data was primarily drawn from the Dark Energy Survey (DES) simulated data, created for the Supernova Photometric Classification Challenge. This poster shows a method for producing a non-parametric representation of the light curve data, and applying a Random Forest classifier algorithm to distinguish between supernovae types. We examine the impact of Principal Component Analysis to reduce the dimensionality of the dataset, for future classification work. The classification code will be used in a stage of the ANTARES pipeline, created for use on the Large Synoptic Survey Telescope alert data and other wide-field surveys. The final figure-of-merit for the DES data in the r band was 60% for binary classification (Type I vs II).Zaidi was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program (AST-1262829).

Project implementation : classification of organic soils and classification of marls - training of INDOT personnel.

Science.gov (United States)

2012-09-01

This is an implementation project for the research completed as part of the following projects: SPR3005 Classification of Organic Soils : and SPR3227 Classification of Marl Soils. The methods developed for the classification of both soi...

45 CFR 601.5 - Derivative classification.

Science.gov (United States)

2010-10-01

... CLASSIFICATION AND DECLASSIFICATION OF NATIONAL SECURITY INFORMATION § 601.5 Derivative classification. Distinct... 45 Public Welfare 3 2010-10-01 2010-10-01 false Derivative classification. 601.5 Section 601.5... classification guide, need not possess original classification authority. (a) If a person who applies derivative...

Learning features for tissue classification with the classification restricted Boltzmann machine

DEFF Research Database (Denmark)

van Tulder, Gijs; de Bruijne, Marleen

2014-01-01

Performance of automated tissue classification in medical imaging depends on the choice of descriptive features. In this paper, we show how restricted Boltzmann machines (RBMs) can be used to learn features that are especially suited for texture-based tissue classification. We introduce the convo...... outperform conventional RBM-based feature learning, which is unsupervised and uses only a generative learning objective, as well as often-used filter banks. We show that a mixture of generative and discriminative learning can produce filters that give a higher classification accuracy....

Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics.

Science.gov (United States)

Chepelev, Leonid L; Riazanov, Alexandre; Kouznetsov, Alexandre; Low, Hong Sang; Dumontier, Michel; Baker, Christopher J O

2011-07-26

The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI) framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of our integrative methodology in the context of

Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics

Directory of Open Access Journals (Sweden)

Dumontier Michel

2011-07-01

Full Text Available Abstract Background The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. Results As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of

Darwin’s legacy in South African evolutionary biology

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S. D. Johnson

2010-02-01

Full Text Available In the two decades after publication of the Origin of Species, Charles Darwin facilitated the publication of numerous scientific papers by settler naturalists in South Africa. This helped to establish the strong tradition of natural history which has characterised evolutionary research in South African museums, herbaria and universities. Significant developments in the early 20th century included the hominid fossil discoveries of Raymond Dart, Robert Broom, and others, but there was otherwise very little South African involvement in the evolutionary synthesis of the 1930s and 1940s. Evolutionary biology developed into a distinct discipline in South Africa during the 1970s and 1980s when it was dominated by mammalian palaeontology and a vigorous debate around species concepts. In the post-apartheid era, the main focus of evolutionary biology has been the construction of phylogenies for African plants and animals using molecular data, and the use of these phylogenies to answer questions about taxonomic classification and trait evolution. South African biologists have also recently contributed important evidence for some of Darwin’s ideas about plant–animal coevolution, sexual selection, and the role of natural selection in speciation. A bibliographic analysis shows that South African authors produce 2–3% of the world’s publications in the field of evolutionary biology, which is much higher than the value of about 0.5% for publications in all sciences. With its extraordinary biodiversity and well-developed research infrastructure, South Africa is an ideal laboratory from which to advance evolutionary research.

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach.

Science.gov (United States)

Irshad, Humayun; Jalali, Sepehr; Roux, Ludovic; Racoceanu, Daniel; Hwee, Lim Joo; Naour, Gilles Le; Capron, Frédérique

2013-01-01

According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. The aim is to investigate the various texture features and Hierarchical Model and X (HMAX) biologically inspired approach for mitosis detection using machine-learning techniques. We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT) features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM), and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for an International Conference on Pattern Recognition (ICPR) 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and classification rate.

Classification of smooth Fano polytopes

DEFF Research Database (Denmark)

Øbro, Mikkel

A simplicial lattice polytope containing the origin in the interior is called a smooth Fano polytope, if the vertices of every facet is a basis of the lattice. The study of smooth Fano polytopes is motivated by their connection to toric varieties. The thesis concerns the classification of smooth...... Fano polytopes up to isomorphism. A smooth Fano -polytope can have at most vertices. In case of vertices an explicit classification is known. The thesis contains the classification in case of vertices. Classifications of smooth Fano -polytopes for fixed exist only for . In the thesis an algorithm...... for the classification of smooth Fano -polytopes for any given is presented. The algorithm has been implemented and used to obtain the complete classification for ....

Models for synthetic biology.

Science.gov (United States)

Kaznessis, Yiannis N

2007-11-06

Synthetic biological engineering is emerging from biology as a distinct discipline based on quantification. The technologies propelling synthetic biology are not new, nor is the concept of designing novel biological molecules. What is new is the emphasis on system behavior. The objective is the design and construction of new biological devices and systems to deliver useful applications. Numerous synthetic gene circuits have been created in the past decade, including bistable switches, oscillators, and logic gates, and possible applications abound, including biofuels, detectors for biochemical and chemical weapons, disease diagnosis, and gene therapies. More than fifty years after the discovery of the molecular structure of DNA, molecular biology is mature enough for real quantification that is useful for biological engineering applications, similar to the revolution in modeling in chemistry in the 1950s. With the excitement that synthetic biology is generating, the engineering and biological science communities appear remarkably willing to cross disciplinary boundaries toward a common goal.

Use of Ecohydraulic-Based Mesohabitat Classification and Fish Species Traits for Stream Restoration Design

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John S. Schwartz

2016-11-01

Full Text Available Stream restoration practice typically relies on a geomorphological design approach in which the integration of ecological criteria is limited and generally qualitative, although the most commonly stated project objective is to restore biological integrity by enhancing habitat and water quality. Restoration has achieved mixed results in terms of ecological successes and it is evident that improved methodologies for assessment and design are needed. A design approach is suggested for mesohabitat restoration based on a review and integration of fundamental processes associated with: (1 lotic ecological concepts; (2 applied geomorphic processes for mesohabitat self-maintenance; (3 multidimensional hydraulics and habitat suitability modeling; (4 species functional traits correlated with fish mesohabitat use; and (5 multi-stage ecohydraulics-based mesohabitat classification. Classification of mesohabitat units demonstrated in this article were based on fish preferences specifically linked to functional trait strategies (i.e., feeding resting, evasion, spawning, and flow refugia, recognizing that habitat preferences shift by season and flow stage. A multi-stage classification scheme developed under this premise provides the basic “building blocks” for ecological design criteria for stream restoration. The scheme was developed for Midwest US prairie streams, but the conceptual framework for mesohabitat classification and functional traits analysis can be applied to other ecoregions.

Odor Classification using Agent Technology

Directory of Open Access Journals (Sweden)

Sigeru OMATU

2014-03-01

Full Text Available In order to measure and classify odors, Quartz Crystal Microbalance (QCM can be used. In the present study, seven QCM sensors and three different odors are used. The system has been developed as a virtual organization of agents using an agent platform called PANGEA (Platform for Automatic coNstruction of orGanizations of intElligent Agents. This is a platform for developing open multi-agent systems, specifically those including organizational aspects. The main reason for the use of agents is the scalability of the platform, i.e. the way in which it models the services. The system models functionalities as services inside the agents, or as Service Oriented Approach (SOA architecture compliant services using Web Services. This way the adaptation of the odor classification systems with new algorithms, tools and classification techniques is allowed.

Juvenile idiopathic arthritis in adulthood: fulfilment of classification criteria for adult rheumatic diseases, long-term outcomes and predictors of inactive disease, functional status and damage.

Science.gov (United States)

Oliveira-Ramos, Filipa; Eusébio, Mónica; M Martins, Fernando; Mourão, Ana Filipa; Furtado, Carolina; Campanilho-Marques, Raquel; Cordeiro, Inês; Ferreira, Joana; Cerqueira, Marcos; Figueira, Ricardo; Brito, Iva; Canhão, Helena; Santos, Maria José; Melo-Gomes, José A; Fonseca, João Eurico

2016-01-01

To determine how adult juvenile idiopathic arthritis (JIA) patients fulfil classification criteria for adult rheumatic diseases, evaluate their outcomes and determine clinical predictors of inactive disease, functional status and damage. Patients with JIA registered on the Rheumatic Diseases Portuguese Register (Reuma.pt) older than 18 years and with more than 5 years of disease duration were included. Data regarding sociodemographic features, fulfilment of adult classification criteria, Health Assessment Questionnaire, Juvenile Arthritis Damage Index-articular (JADI-A) and Juvenile Arthritis Damage Index-extra-articular (JADI-E) damage index and disease activity were analysed. 426 patients were included. Most of patients with systemic JIA fulfilled criteria for Adult Still's disease. 95.6% of the patients with rheumatoid factor (RF)-positive polyarthritis and 57.1% of the patients with RF-negative polyarthritis matched criteria for rheumatoid arthritis (RA). 38.9% of the patients with extended oligoarthritis were classified as RA while 34.8% of the patients with persistent oligoarthritis were classified as spondyloarthritis. Patients with enthesitis-related arthritis fulfilled criteria for spondyloarthritis in 94.7%. Patients with psoriatic arthritis maintained this classification. Patients with inactive disease had lower disease duration, lower diagnosis delay and corticosteroids exposure. Longer disease duration was associated with higher HAQ, JADI-A and JADI-E. Higher JADI-A was also associated with biological treatment and retirement due to JIA disability and higher JADI-E with corticosteroids exposure. Younger age at disease onset was predictive of higher HAQ, JADI-A and JADI-E and decreased the chance of inactive disease. Most of the included patients fulfilled classification criteria for adult rheumatic diseases, maintain active disease and have functional impairment. Younger age at disease onset was predictive of higher disability and decreased the

Merkel Cell Carcinomas Arising in Autoimmune Disease Affected Patients Treated with Biologic Drugs, Including Anti-TNF.

Science.gov (United States)

Rotondo, John Charles; Bononi, Ilaria; Puozzo, Andrea; Govoni, Marcello; Foschi, Valentina; Lanza, Giovanni; Gafà, Roberta; Gaboriaud, Pauline; Touzé, Françoise Antoine; Selvatici, Rita; Martini, Fernanda; Tognon, Mauro

2017-07-15

Purpose: The purpose of this investigation was to characterize Merkel cell carcinomas (MCC) arisen in patients affected by autoimmune diseases and treated with biologic drugs. Experimental Design: Serum samples from patients with MCC were analyzed for the presence and titer of antibodies against antigens of the oncogenic Merkel cell polyomavirus (MCPyV). IgG antibodies against the viral oncoproteins large T (LT) and small T (ST) antigens and the viral capsid protein-1 were analyzed by indirect ELISA. Viral antigens were recombinant LT/ST and virus-like particles (VLP), respectively. MCPyV DNA sequences were studied using PCR methods in MCC tissues and in peripheral blood mononuclear cells (PBMC). Immunohistochemical (IHC) analyses were carried out in MCC tissues to reveal MCPyV LT oncoprotein. Results: MCPyV DNA sequences identified in MCC tissues showed 100% homology with the European MKL-1 strain. PBMCs from patients tested MCPyV-negative. Viral DNA loads in the three MCC tissues were in the 0.1 to 30 copy/cell range. IgG antibodies against LT/ST were detected in patients 1 and 3, whereas patient 2 did not react to the MCPyV LT/ST antigen. Sera from the three patients with MCC contained IgG antibodies against MCPyV VP1. MCC tissues tested MCPyV LT-antigen-positive in IHC assays, with strong LT expression with diffuse nuclear localization. Normal tissues tested MCPyV LT-negative when employed as control. Conclusions: We investigated three new MCCs in patients affected by rheumatologic diseases treated with biologic drugs, including TNF. A possible cause-effect relationship between pharmacologic immunosuppressive treatment and MCC onset is suggested. Indeed, MCC is associated with MCPyV LT oncoprotein activity. Clin Cancer Res; 23(14); 3929-34. ©2017 AACR . ©2017 American Association for Cancer Research.

Comparison between Possibilistic c-Means (PCM and Artificial Neural Network (ANN Classification Algorithms in Land use/ Land cover Classification

Directory of Open Access Journals (Sweden)

Ganchimeg Ganbold

2017-03-01

Full Text Available There are several statistical classification algorithms available for landuse/land cover classification. However, each has a certain bias orcompromise. Some methods like the parallel piped approach in supervisedclassification, cannot classify continuous regions within a feature. Onthe other hand, while unsupervised classification method takes maximumadvantage of spectral variability in an image, the maximally separableclusters in spectral space may not do much for our perception of importantclasses in a given study area. In this research, the output of an ANNalgorithm was compared with the Possibilistic c-Means an improvementof the fuzzy c-Means on both moderate resolutions Landsat8 and a highresolution Formosat 2 images. The Formosat 2 image comes with an8m spectral resolution on the multispectral data. This multispectral imagedata was resampled to 10m in order to maintain a uniform ratio of1:3 against Landsat 8 image. Six classes were chosen for analysis including:Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC, the six features reflecteddifferently in the infrared region with wheat producing the brightestpixel values. Signature collection per class was therefore easily obtainedfor all classifications. The output of both ANN and FCM, were analyzedseparately for accuracy and an error matrix generated to assess the qualityand accuracy of the classification algorithms. When you compare theresults of the two methods on a per-class-basis, ANN had a crisperoutput compared to PCM which yielded clusters with pixels especiallyon the moderate resolution Landsat 8 imagery.

Ontology-supported research on vaccine efficacy, safety and integrative biological networks.

Science.gov (United States)

He, Yongqun

2014-07-01

While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including Vaccine Ontology, Ontology of Adverse Events and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network ('OneNet') Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms.

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan

2014-09-07

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan; Wang, Yi; Zhao, Shiguang; Gao, Xin

2014-01-01

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

NOAA Point Shapefile- Benthic Habitat Classifications from Minibat ROV Underwater Video, US Virgin Islands, Project NF-04-06, 2004, UTM 20N WGS84

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a point shapefile with benthic habitat classifications of vertical relief, geomorphological structure, substrate, and biological cover for...

Phenomenology and classification of dystonia: a consensus update.

Science.gov (United States)

Albanese, Alberto; Bhatia, Kailash; Bressman, Susan B; Delong, Mahlon R; Fahn, Stanley; Fung, Victor S C; Hallett, Mark; Jankovic, Joseph; Jinnah, Hyder A; Klein, Christine; Lang, Anthony E; Mink, Jonathan W; Teller, Jan K

2013-06-15

This report describes the consensus outcome of an international panel consisting of investigators with years of experience in this field that reviewed the definition and classification of dystonia. Agreement was obtained based on a consensus development methodology during 3 in-person meetings and manuscript review by mail. Dystonia is defined as a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both. Dystonic movements are typically patterned and twisting, and may be tremulous. Dystonia is often initiated or worsened by voluntary action and associated with overflow muscle activation. Dystonia is classified along 2 axes: clinical characteristics, including age at onset, body distribution, temporal pattern and associated features (additional movement disorders or neurological features); and etiology, which includes nervous system pathology and inheritance. The clinical characteristics fall into several specific dystonia syndromes that help to guide diagnosis and treatment. We provide here a new general definition of dystonia and propose a new classification. We encourage clinicians and researchers to use these innovative definition and classification and test them in the clinical setting on a variety of patients with dystonia. © 2013 Movement Disorder Society. © 2013 Movement Disorder Society.

Has Modern Biology Entered the Mouth? The Clinical Impact of Biological Research.

Science.gov (United States)

Baum, Bruce J.

1991-01-01

Three areas of biological research that are beginning to have an impact on clinical medicine are examined, including molecular biology, cell biology, and biotechnology. It is concluded that oral biologists and educators must work cooperatively to bring rapid biological and biomedical advances into dental training in a meaningful way. (MSE)

Archigregarines of the English Channel revisited: New molecular data on Selenidium species including early described and new species and the uncertainties of phylogenetic relationships

Czech Academy of Sciences Publication Activity Database

Rueckert, S.; Horák, Aleš

2017-01-01

Roč. 12, č. 11 (2017), č. článku e0187430. E-ISSN 1932-6203 R&D Projects: GA ČR GA15-17643S EU Projects: European Commission(XE) 316304 - MODBIOLIN Institutional support: RVO:60077344 Keywords : gregarine parasites apicomplexa * sabellaria alveolata l * revised classification * sequence alignment * genome-sequence * ultrastructure * checklist * lecudina * sporozoa Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Biochemistry and molecular biology Impact factor: 2.806, year: 2016

Scalable Packet Classification with Hash Tables

Science.gov (United States)

Wang, Pi-Chung

In the last decade, the technique of packet classification has been widely deployed in various network devices, including routers, firewalls and network intrusion detection systems. In this work, we improve the performance of packet classification by using multiple hash tables. The existing hash-based algorithms have superior scalability with respect to the required space; however, their search performance may not be comparable to other algorithms. To improve the search performance, we propose a tuple reordering algorithm to minimize the number of accessed hash tables with the aid of bitmaps. We also use pre-computation to ensure the accuracy of our search procedure. Performance evaluation based on both real and synthetic filter databases shows that our scheme is effective and scalable and the pre-computation cost is moderate.

[The importance of classifications in psychiatry].

Science.gov (United States)

Lempérière, T

1995-12-01

The classifications currently used in psychiatry have different aims: to facilitate communication between researchers and clinicians at national and international levels through the use of a common language, or at least a clearly and precisely defined nomenclature; to provide a nosographical reference system which can be used in practice (diagnosis, prognosis, treatment); to optimize research by ensuring that sample cases are as homogeneous as possible; to facilitate statistical records for public health institutions. A classification is of practical interest only if it is reliable, valid and acceptable to all potential users. In recent decades, there has been a considerable systematic and coordinated effort to improve the methodological approach to classification and categorization in the field of psychiatry, including attempts to create operational definitions, field trials of inter-assessor reliability, attempts to validate the selected nosological categories by analysis of correlation between progression, treatment response, family history and additional examinations. The introduction of glossaries, and particularly of diagnostic criteria, marked a decisive step in this new approach. The key problem remains that of the validity of diagnostic criteria. Ideally, these should be based on demonstrable etiologic or pathogenic data, but such information is rarely available in psychiatry. Current classifications rely on the use of extremely diverse elements in differing degrees: descriptive criteria, evolutive criteria, etiopathogenic criteria, psychopathogenic criteria, etc. Certain syndrome-based classifications such as DSM III and its successors aim to be atheoretical and pragmatic. Others, such as ICD-10, while more eclectic than the different versions of DSM, follow suit by abandoning the terms "disease" and "illness" in favor of the more consensual "disorder". The legitimacy of classifications in the field of psychiatry has been fiercely contested, being

Classification of high resolution imagery based on fusion of multiscale texture features

International Nuclear Information System (INIS)

Liu, Jinxiu; Liu, Huiping; Lv, Ying; Xue, Xiaojuan

2014-01-01

In high resolution data classification process, combining texture features with spectral bands can effectively improve the classification accuracy. However, the window size which is difficult to choose is regarded as an important factor influencing overall classification accuracy in textural classification and current approaches to image texture analysis only depend on a single moving window which ignores different scale features of various land cover types. In this paper, we propose a new method based on the fusion of multiscale texture features to overcome these problems. The main steps in new method include the classification of fixed window size spectral/textural images from 3×3 to 15×15 and comparison of all the posterior possibility values for every pixel, as a result the biggest probability value is given to the pixel and the pixel belongs to a certain land cover type automatically. The proposed approach is tested on University of Pavia ROSIS data. The results indicate that the new method improve the classification accuracy compared to results of methods based on fixed window size textural classification

Cluster Based Text Classification Model

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

2011-01-01

We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

Ontologies vs. Classification Systems

DEFF Research Database (Denmark)

Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

2009-01-01

What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

Multi-label literature classification based on the Gene Ontology graph

Directory of Open Access Journals (Sweden)

Lu Xinghua

2008-12-01

Full Text Available Abstract Background The Gene Ontology is a controlled vocabulary for representing knowledge related to genes and proteins in a computable form. The current effort of manually annotating proteins with the Gene Ontology is outpaced by the rate of accumulation of biomedical knowledge in literature, which urges the development of text mining approaches to facilitate the process by automatically extracting the Gene Ontology annotation from literature. The task is usually cast as a text classification problem, and contemporary methods are confronted with unbalanced training data and the difficulties associated with multi-label classification. Results In this research, we investigated the methods of enhancing automatic multi-label classification of biomedical literature by utilizing the structure of the Gene Ontology graph. We have studied three graph-based multi-label classification algorithms, including a novel stochastic algorithm and two top-down hierarchical classification methods for multi-label literature classification. We systematically evaluated and compared these graph-based classification algorithms to a conventional flat multi-label algorithm. The results indicate that, through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods can significantly improve predictions of the Gene Ontology terms implied by the analyzed text. Furthermore, the graph-based multi-label classifiers are capable of suggesting Gene Ontology annotations (to curators that are closely related to the true annotations even if they fail to predict the true ones directly. A software package implementing the studied algorithms is available for the research community. Conclusion Through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods have better potential than the conventional flat multi-label classification approach to facilitate

CLASSIFICATION OF CRIMINAL GROUPS

OpenAIRE

Natalia Romanova

2013-01-01

New types of criminal groups are emerging in modern society.  These types have their special criminal subculture. The research objective is to develop new parameters of classification of modern criminal groups, create a new typology of criminal groups and identify some features of their subculture. Research methodology is based on the system approach that includes using the method of analysis of documentary sources (materials of a criminal case), method of conversations with themembers of the...

An Ultrasonic Pattern Recognition Approach to Welding Defect Classification

International Nuclear Information System (INIS)

Song, Sung Jin

1995-01-01

Classification of flaws in weldments from their ultrasonic scattering signals is very important in quantitative nondestructive evaluation. This problem is ideally suited to a modern ultrasonic pattern recognition technique. Here brief discussion on systematic approach to this methodology is presented including ultrasonic feature extraction, feature selection and classification. A stronger emphasis is placed on probabilistic neural networks as efficient classifiers for many practical classification problems. In an example probabilistic neural networks are applied to classify flaws in weldments into 3 classes such as cracks, porosity and slag inclusions. Probabilistic nets are shown to be able to exhibit high performance of other classifiers without any training time overhead. In addition, forward selection scheme for sensitive features is addressed to enhance network performance

Effects of uncertainty and variability on population declines and IUCN Red List classifications.

Science.gov (United States)

Rueda-Cediel, Pamela; Anderson, Kurt E; Regan, Tracey J; Regan, Helen M

2018-01-22

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age-structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates

AN EXTENDED SPECTRAL–SPATIAL CLASSIFICATION APPROACH FOR HYPERSPECTRAL DATA

Directory of Open Access Journals (Sweden)

D. Akbari

2017-11-01

Full Text Available In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1 unsupervised feature extraction methods including principal component analysis (PCA, independent component analysis (ICA, and minimum noise fraction (MNF; (2 supervised feature extraction including decision boundary feature extraction (DBFE, discriminate analysis feature extraction (DAFE, and nonparametric weighted feature extraction (NWFE; (3 genetic algorithm (GA. The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

Objective classification of ecological status in marine water bodies using ecotoxicological information and multivariate analysis.

Science.gov (United States)

Beiras, Ricardo; Durán, Iria

2014-12-01

Some relevant shortcomings have been identified in the current approach for the classification of ecological status in marine water bodies, leading to delays in the fulfillment of the Water Framework Directive objectives. Natural variability makes difficult to settle fixed reference values and boundary values for the Ecological Quality Ratios (EQR) for the biological quality elements. Biological responses to environmental degradation are frequently of nonmonotonic nature, hampering the EQR approach. Community structure traits respond only once ecological damage has already been done and do not provide early warning signals. An alternative methodology for the classification of ecological status integrating chemical measurements, ecotoxicological bioassays and community structure traits (species richness and diversity), and using multivariate analyses (multidimensional scaling and cluster analysis), is proposed. This approach does not depend on the arbitrary definition of fixed reference values and EQR boundary values, and it is suitable to integrate nonlinear, sensitive signals of ecological degradation. As a disadvantage, this approach demands the inclusion of sampling sites representing the full range of ecological status in each monitoring campaign. National or international agencies in charge of coastal pollution monitoring have comprehensive data sets available to overcome this limitation.

The book classification of William Torrey Harris: influences of Bacon and Hegel in library classification

Directory of Open Access Journals (Sweden)

Rodrigo de Sales

2017-09-01

Full Text Available The studies of library classification generally interact with the historical contextualization approach and with the classification ideas typical of Philosophy. In the 19th century, the North-American philosopher and educator William Torrey Harris developed a book classification at the St. Louis Public School, based on Francis Bacon and Georg Wilhelm Friedrich Hegel. The objective of this essay is to analyze Harris’s classification, reflecting upon his theoretical and philosophical backgrounds. To achieve such objective, this essay adopts a critical-descriptive approach for analysis. Results show some influences of Bacon and Hegel in Harris’s classification.

Classification of Strawberry Fruit Shape by Machine Learning

Science.gov (United States)

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

2018-05-01

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

Adverse events following cervical manipulative therapy: consensus on classification among Dutch medical specialists, manual therapists, and patients.

Science.gov (United States)

Kranenburg, Hendrikus A; Lakke, Sandra E; Schmitt, Maarten A; Van der Schans, Cees P

2017-12-01

To obtain consensus-based agreement on a classification system of adverse events (AE) following cervical spinal manipulation. The classification system should be comprised of clear definitions, include patients' and clinicians' perspectives, and have an acceptable number of categories. Design : A three-round Delphi study. Participants : Thirty Dutch participants (medical specialists, manual therapists, and patients) participated in an online survey. Procedure : Participants inventoried AE and were asked about their preferences for either a three- or a four-category classification system. The identified AE were classified by two analysts following the International Classification of Functioning, Disability and Health (ICF), and the International Classification of Diseases and Related Health Problems (ICD-10). Participants were asked to classify the severity for all AE in relation to the time duration. Consensus occurred in a three-category classification system. There was strong consensus for 16 AE in all severities (no, minor, and major AE) and all three time durations [hours, days, weeks]. The 16 AE included anxiety, flushing, skin rash, fainting, dizziness, coma, altered sensation, muscle tenderness, pain, increased pain during movement, radiating pain, dislocation, fracture, transient ischemic attack, stroke, and death. Mild to strong consensus was reached for 13 AE. A consensus-based classification system of AE is established which includes patients' and clinicians' perspectives and has three categories. The classification comprises a precise description of potential AE in accordance with internationally accepted classifications. After international validation, clinicians and researchers may use this AE classification system to report AE in clinical practice and research.

Reliability of Oronasal Fistula Classification.

Science.gov (United States)

Sitzman, Thomas J; Allori, Alexander C; Matic, Damir B; Beals, Stephen P; Fisher, David M; Samson, Thomas D; Marcus, Jeffrey R; Tse, Raymond W

2018-01-01

Objective Oronasal fistula is an important complication of cleft palate repair that is frequently used to evaluate surgical quality, yet reliability of fistula classification has never been examined. The objective of this study was to determine the reliability of oronasal fistula classification both within individual surgeons and between multiple surgeons. Design Using intraoral photographs of children with repaired cleft palate, surgeons rated the location of palatal fistulae using the Pittsburgh Fistula Classification System. Intrarater and interrater reliability scores were calculated for each region of the palate. Participants Eight cleft surgeons rated photographs obtained from 29 children. Results Within individual surgeons reliability for each region of the Pittsburgh classification ranged from moderate to almost perfect (κ = .60-.96). By contrast, reliability between surgeons was lower, ranging from fair to substantial (κ = .23-.70). Between-surgeon reliability was lowest for the junction of the soft and hard palates (κ = .23). Within-surgeon and between-surgeon reliability were almost perfect for the more general classification of fistula in the secondary palate (κ = .95 and κ = .83, respectively). Conclusions This is the first reliability study of fistula classification. We show that the Pittsburgh Fistula Classification System is reliable when used by an individual surgeon, but less reliable when used among multiple surgeons. Comparisons of fistula occurrence among surgeons may be subject to less bias if they use the more general classification of "presence or absence of fistula of the secondary palate" rather than the Pittsburgh Fistula Classification System.

Value of multi-slice CT in the classification diagnosis of hilar cholangiocarcinoma

International Nuclear Information System (INIS)

Qian Yi; Zeng Mengsu; Ling Zhiqing; Rao Shengxiang; Liu Yalan

2008-01-01

Objective: To evaluate the value of multi-slice CT (MSCT) classification in the assessment of the hilar cholangiocarcinoma resectability. Methods: Thirty patients with surgically and histopathologically proved hilar cholangiocarcinomas who underwent preoperative MSCT and were diagnosed correctly were included in present study. Transverse images and reconstructed MPR images were reviewed for Bismuth-Corlette classification and morphological classification of hilar cholangiocarcinoma. Then MSCT classification was compared with findings of surgery and histopathology. Curative resectabilty of different types according to Bismuth-Corlette classification and morphological classification were analyzed with chi-square test. Results: In 30 cases, the numbers of Type I, II, IIIa, IIIb and IV according to Bismuth-Corlette classification were 1, 3, 4, 5 and 17. Seventeen patients underwent curative resections, among which 1, 2, 1, 4 and 9 belonged to Type I, II, IIIa, IIIb and IV respectively. However, there was no significant difference in curative resectability among different types of Bismuth-Corlette classification (χ 2 = 0.9875, P>0.05). In present study, the accuracy of MSCT in Bismuth-Corlette classification reached 86.7% (26/30). The numbers of periductal infiltrating, mass forming and intraductal growing type were 13, 13 and 4, while 6, 8 and 3 cases of each type underwent curative resections. There was no significant difference in curative resectability among different types of morphological classification (χ 2 =1.2583, P>0.05). The accuracy of MSCT in morphological classification was 100% (30/30) in this study group. Conclusion: MSCT can make accurate diagnosis of Bismuth-Corlette classification and morphological classification, which is helpful in preoperative respectability assessment of hilar cholangiocarcinoma. (authors)

Alphanumerical classification for the subject files of the department of documentation of the Atomic Energy Commission

International Nuclear Information System (INIS)

Braffort, P.; Iung, J.

1956-01-01

The research activities of the Atomic Energy Commission cover a large variety of different subjects from theoretical physics and nuclear physics to biology, medicine or geology. Thus, about 350 scientific reviews are received and presented in the library. All those documents need to be classified to make the research of information easier for researchers. It describes the classification and codification of such a large quantity of documents. The classification uses a bidimensional system with 5 columns with inter-scale phenomena, corpuscular scale, nuclear scale, atomic and molecular scale and macroscopic scale as subject and 5 lines with theoretical problems, production, measurement, description and utilisation as topic. Some of the rules are given and examples are presented. (M.P.)

5 CFR 1312.7 - Derivative classification.

Science.gov (United States)

2010-01-01

..., DOWNGRADING, DECLASSIFICATION AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION Classification and Declassification of National Security Information § 1312.7 Derivative classification. A derivative classification... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Derivative classification. 1312.7 Section...

Deep Recurrent Neural Networks for Supernovae Classification

Science.gov (United States)

Charnock, Tom; Moss, Adam

2017-03-01

We apply deep recurrent neural networks, which are capable of learning complex sequential information, to classify supernovae (code available at https://github.com/adammoss/supernovae). The observational time and filter fluxes are used as inputs to the network, but since the inputs are agnostic, additional data such as host galaxy information can also be included. Using the Supernovae Photometric Classification Challenge (SPCC) data, we find that deep networks are capable of learning about light curves, however the performance of the network is highly sensitive to the amount of training data. For a training size of 50% of the representational SPCC data set (around 104 supernovae) we obtain a type-Ia versus non-type-Ia classification accuracy of 94.7%, an area under the Receiver Operating Characteristic curve AUC of 0.986 and an SPCC figure-of-merit F 1 = 0.64. When using only the data for the early-epoch challenge defined by the SPCC, we achieve a classification accuracy of 93.1%, AUC of 0.977, and F 1 = 0.58, results almost as good as with the whole light curve. By employing bidirectional neural networks, we can acquire impressive classification results between supernovae types I, II and III at an accuracy of 90.4% and AUC of 0.974. We also apply a pre-trained model to obtain classification probabilities as a function of time and show that it can give early indications of supernovae type. Our method is competitive with existing algorithms and has applications for future large-scale photometric surveys.

Deep learning for EEG-Based preference classification

Science.gov (United States)

Teo, Jason; Hou, Chew Lin; Mountstephens, James

2017-10-01

Electroencephalogram (EEG)-based emotion classification is rapidly becoming one of the most intensely studied areas of brain-computer interfacing (BCI). The ability to passively identify yet accurately correlate brainwaves with our immediate emotions opens up truly meaningful and previously unattainable human-computer interactions such as in forensic neuroscience, rehabilitative medicine, affective entertainment and neuro-marketing. One particularly useful yet rarely explored areas of EEG-based emotion classification is preference recognition [1], which is simply the detection of like versus dislike. Within the limited investigations into preference classification, all reported studies were based on musically-induced stimuli except for a single study which used 2D images. The main objective of this study is to apply deep learning, which has been shown to produce state-of-the-art results in diverse hard problems such as in computer vision, natural language processing and audio recognition, to 3D object preference classification over a larger group of test subjects. A cohort of 16 users was shown 60 bracelet-like objects as rotating visual stimuli on a computer display while their preferences and EEGs were recorded. After training a variety of machine learning approaches which included deep neural networks, we then attempted to classify the users' preferences for the 3D visual stimuli based on their EEGs. Here, we show that that deep learning outperforms a variety of other machine learning classifiers for this EEG-based preference classification task particularly in a highly challenging dataset with large inter- and intra-subject variability.

IAEA Classification of Uranium Deposits

International Nuclear Information System (INIS)

Bruneton, Patrice

2014-01-01

Classifications of uranium deposits follow two general approaches, focusing on: • descriptive features such as the geotectonic position, the host rock type, the orebody morphology, …… : « geologic classification »; • or on genetic aspects: « genetic classification »

The classification of ambiguity in polarimetric reconstruction of coronal mass ejection

International Nuclear Information System (INIS)

Dai, Xinghua; Wang, Huaning; Huang, Xin; Du, Zhanle; He, Han

2014-01-01

The Thomson scattering theory indicates that there exist explicit and implicit ambiguities in polarimetric analyses of coronal mass ejection (CME) observations. We suggest a classification for these ambiguities in CME reconstruction. Three samples, including double explicit, mixed, and double implicit ambiguity, are shown with the polarimetric analyses of STEREO CME observations. These samples demonstrate that this classification is helpful for improving polarimetric reconstruction.

A territorial classification for the ecological strategy

International Nuclear Information System (INIS)

Arias de Greiff, Jorge

2002-01-01

The author proposes a territorial classification including at the sun, the water, the atmosphere, the vegetable earth and the vegetation of green leaf, describes each one of the elements, he refers to the micro-climates and he gives a territorial organization for the ecological emergency

Vulnerable land ecosystems classification using spatial context and spectral indices

Science.gov (United States)

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martín, Consuelo; Marcello, Javier

2017-10-01

Natural habitats are exposed to growing pressure due to intensification of land use and tourism development. Thus, obtaining information on the vegetation is necessary for conservation and management projects. In this context, remote sensing is an important tool for monitoring and managing habitats, being classification a crucial stage. The majority of image classifications techniques are based upon the pixel-based approach. An alternative is the object-based (OBIA) approach, in which a previous segmentation step merges image pixels to create objects that are then classified. Besides, improved results may be gained by incorporating additional spatial information and specific spectral indices into the classification process. The main goal of this work was to implement and assess object-based classification techniques on very-high resolution imagery incorporating spectral indices and contextual spatial information in the classification models. The study area was Teide National Park in Canary Islands (Spain) using Worldview-2 orthoready imagery. In the classification model, two common indices were selected Normalized Difference Vegetation Index (NDVI) and Optimized Soil Adjusted Vegetation Index (OSAVI), as well as two specific Worldview-2 sensor indices, Worldview Vegetation Index and Worldview Soil Index. To include the contextual information, Grey Level Co-occurrence Matrices (GLCM) were used. The classification was performed training a Support Vector Machine with sufficient and representative number of vegetation samples (Spartocytisus supranubius, Pterocephalus lasiospermus, Descurainia bourgaeana and Pinus canariensis) as well as urban, road and bare soil classes. Confusion Matrices were computed to evaluate the results from each classification model obtaining the highest overall accuracy (90.07%) combining both Worldview indices with the GLCM-dissimilarity.

Descriptor Based Classification of Shapes in Terms of Style and Function

DEFF Research Database (Denmark)

Welnicka, Katarzyna; Bærentzen, Jakob Andreas; Aanæs, Henrik

of a specific human being have some commonality that separate them from those of another person. Thus, one could argue that an individual represents a style. Style in the context of biological variation is something that we explore in the work presented here. Specifically, we investigate whether we can define...... of functions, since, as we discuss below, the function of the object (what it is) clearly also has a profound impact on shape. Thus, our work can be summed up as example based classification of digital 3D shapes in both style and function categories....

32 CFR 2400.15 - Classification guides.

Science.gov (United States)

2010-07-01

... REGULATIONS TO IMPLEMENT E.O. 12356; OFFICE OF SCIENCE AND TECHNOLOGY POLICY INFORMATION SECURITY PROGRAM Derivative Classification § 2400.15 Classification guides. (a) OSTP shall issue and maintain classification guides to facilitate the proper and uniform derivative classification of information. These guides shall...

Integrated Biological Control

International Nuclear Information System (INIS)

JOHNSON, A.R.

2002-01-01

Biological control is any activity taken to prevent, limit, clean up, or remediate potential environmental, health and safety, or workplace quality impacts from plants, animals, or microorganisms. At Hanford the principal emphasis of biological control is to prevent the transport of radioactive contamination by biological vectors (plants, animals, or microorganisms), and where necessary, control and clean up resulting contamination. Other aspects of biological control at Hanford include industrial weed control (e.g.; tumbleweeds), noxious weed control (invasive, non-native plant species), and pest control (undesirable animals such as rodents and stinging insects; and microorganisms such as molds that adversely affect the quality of the workplace environment). Biological control activities may be either preventive (apriori) or in response to existing contamination spread (aposteriori). Surveillance activities, including ground, vegetation, flying insect, and other surveys, and apriori control actions, such as herbicide spraying and placing biological barriers, are important in preventing radioactive contamination spread. If surveillance discovers that biological vectors have spread radioactive contamination, aposteriori control measures, such as fixing contamination, followed by cleanup and removal of the contamination to an approved disposal location are typical response functions. In some cases remediation following the contamination cleanup and removal is necessary. Biological control activities for industrial weeds, noxious weeds and pests have similar modes of prevention and response

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

Science.gov (United States)

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.

5 CFR 9901.223 - Appeal to DoD for review of classification decisions.

Science.gov (United States)

2010-01-01

... state specific points of disagreement with the current classification. The employee may also include a....223 Appeal to DoD for review of classification decisions. (a) Employee representation. An employee may... an appeal. A management official may disallow an employee's representative when— (1) An individual's...

New guidelines for dam safety classification

International Nuclear Information System (INIS)

Dascal, O.

1999-01-01

Elements are outlined of recommended new guidelines for safety classification of dams. Arguments are provided for the view that dam classification systems should require more than one system as follows: (a) classification for selection of design criteria, operation procedures and emergency measures plans, based on potential consequences of a dam failure - the hazard classification of water retaining structures; (b) classification for establishment of surveillance activities and for safety evaluation of dams, based on the probability and consequences of failure - the risk classification of water retaining structures; and (c) classification for establishment of water management plans, for safety evaluation of the entire project, for preparation of emergency measures plans, for definition of the frequency and extent of maintenance operations, and for evaluation of changes and modifications required - the hazard classification of the project. The hazard classification of the dam considers, as consequence, mainly the loss of lives or persons in jeopardy and the property damages to third parties. Difficulties in determining the risk classification of the dam lie in the fact that no tool exists to evaluate the probability of the dam's failure. To overcome this, the probability of failure can be substituted for by a set of dam characteristics that express the failure potential of the dam and its foundation. The hazard classification of the entire project is based on the probable consequences of dam failure influencing: loss of life, persons in jeopardy, property and environmental damage. The classification scheme is illustrated for dam threatening events such as earthquakes and floods. 17 refs., 5 tabs

A comparative study of PCA, SIMCA and Cole model for classification of bioimpedance spectroscopy measurements.

Science.gov (United States)

Nejadgholi, Isar; Bolic, Miodrag

2015-08-01

Due to safety and low cost of bioimpedance spectroscopy (BIS), classification of BIS can be potentially a preferred way of detecting changes in living tissues. However, for longitudinal datasets linear classifiers fail to classify conventional Cole parameters extracted from BIS measurements because of their high variability. In some applications, linear classification based on Principal Component Analysis (PCA) has shown more accurate results. Yet, these methods have not been established for BIS classification, since PCA features have neither been investigated in combination with other classifiers nor have been compared to conventional Cole features in benchmark classification tasks. In this work, PCA and Cole features are compared in three synthesized benchmark classification tasks which are expected to be detected by BIS. These three tasks are classification of before and after geometry change, relative composition change and blood perfusion in a cylindrical organ. Our results show that in all tasks the features extracted by PCA are more discriminant than Cole parameters. Moreover, a pilot study was done on a longitudinal arm BIS dataset including eight subjects and three arm positions. The goal of the study was to compare different methods in arm position classification which includes all three synthesized changes mentioned above. Our comparative study on various classification methods shows that the best classification accuracy is obtained when PCA features are classified by a K-Nearest Neighbors (KNN) classifier. The results of this work suggest that PCA+KNN is a promising method to be considered for classification of BIS datasets that deal with subject and time variability. Copyright © 2015 Elsevier Ltd. All rights reserved.

7 CFR 28.911 - Review classification.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Review classification. 28.911 Section 28.911... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification § 28.911 Review classification. (a) A producer may request one review...

Using methods from the data mining and machine learning literature for disease classification and prediction: A case study examining classification of heart failure sub-types

Science.gov (United States)

Austin, Peter C.; Tu, Jack V.; Ho, Jennifer E.; Levy, Daniel; Lee, Douglas S.

2014-01-01

Objective Physicians classify patients into those with or without a specific disease. Furthermore, there is often interest in classifying patients according to disease etiology or subtype. Classification trees are frequently used to classify patients according to the presence or absence of a disease. However, classification trees can suffer from limited accuracy. In the data-mining and machine learning literature, alternate classification schemes have been developed. These include bootstrap aggregation (bagging), boosting, random forests, and support vector machines. Study design and Setting We compared the performance of these classification methods with those of conventional classification trees to classify patients with heart failure according to the following sub-types: heart failure with preserved ejection fraction (HFPEF) vs. heart failure with reduced ejection fraction (HFREF). We also compared the ability of these methods to predict the probability of the presence of HFPEF with that of conventional logistic regression. Results We found that modern, flexible tree-based methods from the data mining literature offer substantial improvement in prediction and classification of heart failure sub-type compared to conventional classification and regression trees. However, conventional logistic regression had superior performance for predicting the probability of the presence of HFPEF compared to the methods proposed in the data mining literature. Conclusion The use of tree-based methods offers superior performance over conventional classification and regression trees for predicting and classifying heart failure subtypes in a population-based sample of patients from Ontario. However, these methods do not offer substantial improvements over logistic regression for predicting the presence of HFPEF. PMID:23384592

Cancer classification using the Immunoscore: a worldwide task force.

Science.gov (United States)

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

Cancer classification using the Immunoscore: a worldwide task force

Directory of Open Access Journals (Sweden)

Galon Jérôme

2012-10-01

Full Text Available Abstract 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

Packet Classification by Multilevel Cutting of the Classification Space: An Algorithmic-Architectural Solution for IP Packet Classification in Next Generation Networks

Directory of Open Access Journals (Sweden)

Motasem Aldiab

2008-01-01

Full Text Available Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Proposition of a Classification of Adult Patients with Hemiparesis in Chronic Phase.

Science.gov (United States)

Chantraine, Frédéric; Filipetti, Paul; Schreiber, Céline; Remacle, Angélique; Kolanowski, Elisabeth; Moissenet, Florent

2016-01-01

Patients who have developed hemiparesis as a result of a central nervous system lesion, often experience reduced walking capacity and worse gait quality. Although clinically, similar gait patterns have been observed, presently, no clinically driven classification has been validated to group these patients' gait abnormalities at the level of the hip, knee and ankle joints. This study has thus intended to put forward a new gait classification for adult patients with hemiparesis in chronic phase, and to validate its discriminatory capacity. Twenty-six patients with hemiparesis were included in this observational study. Following a clinical examination, a clinical gait analysis, complemented by a video analysis, was performed whereby participants were requested to walk spontaneously on a 10m walkway. A patient's classification was established from clinical examination data and video analysis. This classification was made up of three groups, including two sub-groups, defined with key abnormalities observed whilst walking. Statistical analysis was achieved on the basis of 25 parameters resulting from the clinical gait analysis in order to assess the discriminatory characteristic of the classification as displayed by the walking speed and kinematic parameters. Results revealed that the parameters related to the discriminant criteria of the proposed classification were all significantly different between groups and subgroups. More generally, nearly two thirds of the 25 parameters showed significant differences (p<0.05) between the groups and sub-groups. However, prior to being fully validated, this classification must still be tested on a larger number of patients, and the repeatability of inter-operator measures must be assessed. This classification enables patients to be grouped on the basis of key abnormalities observed whilst walking and has the advantage of being able to be used in clinical routines without necessitating complex apparatus. In the midterm, this

The new UN international framework classification for reserves/resources and its relation to uranium resource classification

International Nuclear Information System (INIS)

Barthel, F.H.; Kelter, D.

2001-01-01

to facilitate investments. The UN Framework Classification provides information about: the stage of geological assessment, subdivided into: Reconnaissance, Prospecting, General Exploration and Detailed Exploration; the stage of feasibility assessment, subdivided into: Geological Study, Prefeasibility Study and Feasibility Study/Mining Report; the degree of economic viability, subdivided into: Economic, Potentially Economic and Intrinsically Economic. The Mineral Reserve is defined as the economically extractable part of the Total Mineral Resource, demonstrated by feasibility assessment. A numerical codification of the eight resource classes available was introduced to facilitate the application. Due to many similarities to the classification of uranium resources used by the NEA and IAEA the new UN Framework Classification can be used to classify uranium resources. In general Reasonably Assured Resources of the lowest cost category (presently economically extractable amounts) are consistent with the UN term Proved Reserve. It is therefore hoped that the UN Framework, which now will be tested internationally for three years, will be accepted by all countries and for all mineral commodities including uranium. (author)