WorldWideScience

Sample records for accurate molecular classification

  1. Accurate molecular classification of cancer using simple rules

    Gotoh Osamu; Wang Xiaosheng

    2009-01-01

    Abstract Background One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often ...

  2. Accurate molecular classification of cancer using simple rules

    Gotoh Osamu

    2009-10-01

    Full Text Available Abstract Background One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible. Methods We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV of training sets and classification of independent test sets. Results We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML], lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML. Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods. Conclusion In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.

  3. ACCURATE TIME SERIES CLASSIFICATION USING SHAPELETS

    M. Arathi; A. GOVARDHAN

    2014-01-01

    Time series data are sequences of values measured o ver time. One of the most recent approaches to classification of time series data is to find shape lets within a data set. Time series shapelets are time series subsequences which represent a class. In order to compare two time series sequences, existing work use s Euclidean distance measure. The problem with Euclid ean distance is that it requires data to be standardized if scales ...

  4. Molecular classification of gastric cancer.

    Chia, N-Y; Tan, P

    2016-05-01

    Gastric cancer (GC), a heterogeneous disease characterized by epidemiologic and histopathologic differences across countries, is a leading cause of cancer-related death. Treatment of GC patients is currently suboptimal due to patients being commonly treated in a uniform fashion irrespective of disease subtype. With the advent of next-generation sequencing and other genomic technologies, GCs are now being investigated in great detail at the molecular level. High-throughput technologies now allow a comprehensive study of genomic and epigenomic alterations associated with GC. Gene mutations, chromosomal aberrations, differential gene expression and epigenetic alterations are some of the genetic/epigenetic influences on GC pathogenesis. In addition, integrative analyses of molecular profiling data have led to the identification of key dysregulated pathways and importantly, the establishment of GC molecular classifiers. Recently, The Cancer Genome Atlas (TCGA) network proposed a four subtype classification scheme for GC based on the underlying tumor molecular biology of each subtype. This landmark study, together with other studies, has expanded our understanding on the characteristics of GC at the molecular level. Such knowledge may improve the medical management of GC in the future. PMID:26861606

  5. Tumor classification: molecular analysis meets Aristotle

    Traditionally, tumors have been classified by their morphologic appearances. Unfortunately, tumors with similar histologic features often follow different clinical courses or respond differently to chemotherapy. Limitations in the clinical utility of morphology-based tumor classifications have prompted a search for a new tumor classification based on molecular analysis. Gene expression array data and proteomic data from tumor samples will provide complex data that is unobtainable from morphologic examination alone. The growing question facing cancer researchers is, 'How can we successfully integrate the molecular, morphologic and clinical characteristics of human cancer to produce a helpful tumor classification?' Current efforts to classify cancers based on molecular features ignore lessons learned from millennia of experience in biological classification. A tumor classification must include every type of tumor and must provide a unique place for each tumor within the classification. Groups within a classification inherit the properties of their ancestors and impart properties to their descendants. A classification was prepared grouping tumors according to their histogenetic development. The classification is simple (reducing the complexity of information received from the molecular analysis of tumors), comprehensive (providing a place for every tumor of man), and consistent with recent attempts to characterize tumors by cytogenetic and molecular features. The clinical and research value of this historical approach to tumor classification is discussed. This manuscript reviews tumor classification and provides a new and comprehensive classification for neoplasia that preserves traditional nomenclature while incorporating information derived from the molecular analysis of tumors. The classification is provided as an open access XML document that can be used by cancer researchers to relate tumor classes with heterogeneous experimental and clinical tumor

  6. Molecular Classification and Correlates in Colorectal Cancer

    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...

  7. Automatic classification and accurate size measurement of blank mask defects

    Bhamidipati, Samir; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter

    2015-07-01

    complexity of defects encountered. The variety arises due to factors such as defect nature, size, shape and composition; and the optical phenomena occurring around the defect. This paper focuses on preliminary characterization results, in terms of classification and size estimation, obtained by Calibre MDPAutoClassify tool on a variety of mask blank defects. It primarily highlights the challenges faced in achieving the results with reference to the variety of defects observed on blank mask substrates and the underlying complexities which make accurate defect size measurement an important and challenging task.

  8. Accurate mobile malware detection and classification in the cloud.

    Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

    2015-01-01

    As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service. PMID:26543718

  9. Tumor classification: molecular analysis meets Aristotle

    Berman Jules J

    2004-01-01

    Abstract Background Traditionally, tumors have been classified by their morphologic appearances. Unfortunately, tumors with similar histologic features often follow different clinical courses or respond differently to chemotherapy. Limitations in the clinical utility of morphology-based tumor classifications have prompted a search for a new tumor classification based on molecular analysis. Gene expression array data and proteomic data from tumor samples will provide complex data that is unobt...

  10. Accurate phylogenetic classification of DNA fragments based onsequence composition

    McHardy, Alice C.; Garcia Martin, Hector; Tsirigos, Aristotelis; Hugenholtz, Philip; Rigoutsos, Isidore

    2006-05-01

    Metagenome studies have retrieved vast amounts of sequenceout of a variety of environments, leading to novel discoveries and greatinsights into the uncultured microbial world. Except for very simplecommunities, diversity makes sequence assembly and analysis a verychallenging problem. To understand the structure a 5 nd function ofmicrobial communities, a taxonomic characterization of the obtainedsequence fragments is highly desirable, yet currently limited mostly tothose sequences that contain phylogenetic marker genes. We show that forclades at the rank of domain down to genus, sequence composition allowsthe very accurate phylogenetic 10 characterization of genomic sequence.We developed a composition-based classifier, PhyloPythia, for de novophylogenetic sequence characterization and have trained it on adata setof 340 genomes. By extensive evaluation experiments we show that themethodis accurate across all taxonomic ranks considered, even forsequences that originate fromnovel organisms and are as short as 1kb.Application to two metagenome datasets 15 obtained from samples ofphosphorus-removing sludge showed that the method allows the accurateclassification at genus level of most sequence fragments from thedominant populations, while at the same time correctly characterizingeven larger parts of the samples at higher taxonomic levels.

  11. Medulloblastoma: molecular pathways and histopathological classification.

    Borowska, Anna; Jóźwiak, Jarosław

    2016-06-01

    Malignant brain tumors are the leading cause of cancer death among pediatric patients, and medulloblastoma constitutes 20% of them. Currently, the treatment is risk-adapted. Maximum surgical resection is recommended, always followed by chemotherapy and neuroaxis radiotherapy. In spite of the improving survival rate, survivors succumb to treatment-induced side effects. To reduce toxic effects, molecular-targeted treatment is proposed. Medulloblastoma research is very robust, and new articles on the subject are published daily. In the current review we have tried to bring together molecular pathophysiology of the neoplasm and current pathological classification, thus making an effort to relate tumor biology and the histological picture. PMID:27279861

  12. INDUS - a composition-based approach for rapid and accurate taxonomic classification of metagenomic sequences

    Mohammed, Monzoorul Haque; Ghosh, Tarini Shankar; Reddy, Rachamalla Maheedhar; Reddy, Chennareddy Venkata Siva Kumar; Singh, Nitin Kumar; Sharmila S Mande

    2011-01-01

    Background Taxonomic classification of metagenomic sequences is the first step in metagenomic analysis. Existing taxonomic classification approaches are of two types, similarity-based and composition-based. Similarity-based approaches, though accurate and specific, are extremely slow. Since, metagenomic projects generate millions of sequences, adopting similarity-based approaches becomes virtually infeasible for research groups having modest computational resources. In this study, we present ...

  13. Transcriptome classification reveals molecular subtypes in psoriasis

    Ainali Chrysanthi

    2012-09-01

    Full Text Available Abstract Background Psoriasis is an immune-mediated disease characterised by chronically elevated pro-inflammatory cytokine levels, leading to aberrant keratinocyte proliferation and differentiation. Although certain clinical phenotypes, such as plaque psoriasis, are well defined, it is currently unclear whether there are molecular subtypes that might impact on prognosis or treatment outcomes. Results We present a pipeline for patient stratification through a comprehensive analysis of gene expression in paired lesional and non-lesional psoriatic tissue samples, compared with controls, to establish differences in RNA expression patterns across all tissue types. Ensembles of decision tree predictors were employed to cluster psoriatic samples on the basis of gene expression patterns and reveal gene expression signatures that best discriminate molecular disease subtypes. This multi-stage procedure was applied to several published psoriasis studies and a comparison of gene expression patterns across datasets was performed. Conclusion Overall, classification of psoriasis gene expression patterns revealed distinct molecular sub-groups within the clinical phenotype of plaque psoriasis. Enrichment for TGFb and ErbB signaling pathways, noted in one of the two psoriasis subgroups, suggested that this group may be more amenable to therapies targeting these pathways. Our study highlights the potential biological relevance of using ensemble decision tree predictors to determine molecular disease subtypes, in what may initially appear to be a homogenous clinical group. The R code used in this paper is available upon request.

  14. A robust and accurate formulation of molecular and colloidal electrostatics

    Sun, Qiang; Klaseboer, Evert; Chan, Derek Y. C.

    2016-08-01

    This paper presents a re-formulation of the boundary integral method for the Debye-Hückel model of molecular and colloidal electrostatics that removes the mathematical singularities that have to date been accepted as an intrinsic part of the conventional boundary integral equation method. The essence of the present boundary regularized integral equation formulation consists of subtracting a known solution from the conventional boundary integral method in such a way as to cancel out the singularities associated with the Green's function. This approach better reflects the non-singular physical behavior of the systems on boundaries with the benefits of the following: (i) the surface integrals can be evaluated accurately using quadrature without any need to devise special numerical integration procedures, (ii) being able to use quadratic or spline function surface elements to represent the surface more accurately and the variation of the functions within each element is represented to a consistent level of precision by appropriate interpolation functions, (iii) being able to calculate electric fields, even at boundaries, accurately and directly from the potential without having to solve hypersingular integral equations and this imparts high precision in calculating the Maxwell stress tensor and consequently, intermolecular or colloidal forces, (iv) a reliable way to handle geometric configurations in which different parts of the boundary can be very close together without being affected by numerical instabilities, therefore potentials, fields, and forces between surfaces can be found accurately at surface separations down to near contact, and (v) having the simplicity of a formulation that does not require complex algorithms to handle singularities will result in significant savings in coding effort and in the reduction of opportunities for coding errors. These advantages are illustrated using examples drawn from molecular and colloidal electrostatics.

  15. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  16. HMM-FRAME: accurate protein domain classification for metagenomic sequences containing frameshift errors

    Sun Yanni

    2011-05-01

    Full Text Available Abstract Background Protein domain classification is an important step in metagenomic annotation. The state-of-the-art method for protein domain classification is profile HMM-based alignment. However, the relatively high rates of insertions and deletions in homopolymer regions of pyrosequencing reads create frameshifts, causing conventional profile HMM alignment tools to generate alignments with marginal scores. This makes error-containing gene fragments unclassifiable with conventional tools. Thus, there is a need for an accurate domain classification tool that can detect and correct sequencing errors. Results We introduce HMM-FRAME, a protein domain classification tool based on an augmented Viterbi algorithm that can incorporate error models from different sequencing platforms. HMM-FRAME corrects sequencing errors and classifies putative gene fragments into domain families. It achieved high error detection sensitivity and specificity in a data set with annotated errors. We applied HMM-FRAME in Targeted Metagenomics and a published metagenomic data set. The results showed that our tool can correct frameshifts in error-containing sequences, generate much longer alignments with significantly smaller E-values, and classify more sequences into their native families. Conclusions HMM-FRAME provides a complementary protein domain classification tool to conventional profile HMM-based methods for data sets containing frameshifts. Its current implementation is best used for small-scale metagenomic data sets. The source code of HMM-FRAME can be downloaded at http://www.cse.msu.edu/~zhangy72/hmmframe/ and at https://sourceforge.net/projects/hmm-frame/.

  17. Molecular classification of Maize cytoplasms in a breeding program

    Colombo. N * , Presello, D.A. , Kandus M. , G.E. Eyherabide and J.C. Salerno

    2012-06-01

    Full Text Available Cytoplasmic male sterility (CMS is maternally inherited in most of higher plants species. Together with nuclear restorer genes (Rf, CMS cytoplasms contribute significantly to the efficient production of hybrid seed. Three main types of male sterile cytoplasms are known in maize: T, S and C, which can be distinguished by crossing with specific restorer lines. Recently, PCR markers have been developed allowing the identification of different cytoplasms quickly and accurately. Our objective was to classify the cytoplasm type of maize inbred lines used in our breeding program and F1s obtained from crosses between CMS lines and elite maize lines using PCR multiplex. A multiplex PCR protocol was optimized for our conditions. We obtained the molecular classification of the analyzed cytoplasms. The optimized protocol is a valuable tool to trace male sterile cytoplasms and determine hybrid seed purity in our maize breeding program.

  18. The challenge of producing an accurate statewide land cover classification of digital satellite data

    A general land use/land cover data set for South Carolina produced from 1989/1990 SPOT multispectral data is presented. This data set incorporates eight categories: urban/built-up, agricultural/grass, scrub/shrub, forest, water, forested wetland, nonforested wetland, and barren. A statewide inventory of these land use/land cover 'associations' is prepared using integrated pcERDAS and prARC/INFO software by the South Carolina Land Resources Commission with unsupervised classification and reclassification routines, and subsequent air photo verification. Land cover data are produced by county and evaluated for reliability (88-percent average classification accuracy). Multiple applications are served by accurate and timely county land cover inventories for resource management and economic development at state and local government levels, specifically for purposes of land use planning and site location analysis. 6 refs

  19. Quantitatively accurate calculations of conductance and thermopower of molecular junctions

    Markussen, Troels; Jin, Chengjun; Thygesen, Kristian Sommer

    2013-01-01

    Thermopower measurements of molecular junctions have recently gained interest as a characterization technique that supplements the more traditional conductance measurements. Here we investigate the electronic conductance and thermopower of benzenediamine (BDA) and benzenedicarbonitrile (BDCN) con...

  20. GPD: a graph pattern diffusion kernel for accurate graph classification with applications in cheminformatics.

    Smalter, Aaron; Huan, Jun Luke; Jia, Yi; Lushington, Gerald

    2010-01-01

    Graph data mining is an active research area. Graphs are general modeling tools to organize information from heterogeneous sources and have been applied in many scientific, engineering, and business fields. With the fast accumulation of graph data, building highly accurate predictive models for graph data emerges as a new challenge that has not been fully explored in the data mining community. In this paper, we demonstrate a novel technique called graph pattern diffusion (GPD) kernel. Our idea is to leverage existing frequent pattern discovery methods and to explore the application of kernel classifier (e.g., support vector machine) in building highly accurate graph classification. In our method, we first identify all frequent patterns from a graph database. We then map subgraphs to graphs in the graph database and use a process we call "pattern diffusion" to label nodes in the graphs. Finally, we designed a graph alignment algorithm to compute the inner product of two graphs. We have tested our algorithm using a number of chemical structure data. The experimental results demonstrate that our method is significantly better than competing methods such as those kernel functions based on paths, cycles, and subgraphs. PMID:20431140

  1. Integrating tumor microenvironment with cancer molecular classifications

    Becht, Etienne; De Reyniès, Aurélien; Fridman, Wolf H.

    2015-01-01

    Editorial summary The composition of the tumor microenvironment is associated with a patient's prognosis and can be therapeutically targeted. A link between the cellular composition and genomic features of the tumor and its response to immunotherapy is beginning to emerge. Analyzing the microenvironment of tumor molecular subgroups can be a useful approach to tailor immunotherapies.

  2. Clinical and molecular classification of cardiomyopathies

    Franco Cecchi

    2012-07-01

    Full Text Available The term “cardiomyopathies” was used for the first time 55 years ago, in 1957. Since then awareness and knowledge of this important and complex group of heart muscle diseases have improved substantially. Over these past five decades a large number of definitions, nomenclature and schemes, have been advanced by experts and consensus panel, which reflect the fast and continued advance of the scientific understanding in the field. Cardiomyopathies are a heterogeneous group of inherited myocardial diseases, which represent an important cause of disability and adverse outcome. Although considered rare diseases, the overall estimated prevalence of all cardiomyopathies is at least 3% in the general population worldwide. Furthermore, their recognition is increasing due to advances in imaging techniques and greater awareness in both the public and medical community. Cardiomyopathies represent an ideal translational model of integration between basic and clinical sciences. A multidisciplinary approach is therefore essential in order to ensure their correct diagnosis and management. In the present work, we aim to provide a concise overview of the historical background, genetic and phenotypic spectrum and evolving concepts leading to the various attempts of cardiomyopathy classifications produced over the decades.

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

    For over 150 years, pathologists have relied on histomorphology to classify and diagnose neoplasms. Their success has been stunning, permitting the accurate diagnosis of thousands of different types of neoplasms using only a microscope and a trained eye. In the past two decades, cancer genomics has challenged the supremacy of histomorphology by identifying genetic alterations shared by morphologically diverse tumors and by finding genetic features that distinguish subgroups of morphologically homogeneous tumors. The Developmental Lineage Classification and Taxonomy of Neoplasms groups neoplasms by their embryologic origin. The putative value of this classification is based on the expectation that tumors of a common developmental lineage will share common metabolic pathways and common responses to drugs that target these pathways. The purpose of this manuscript is to show that grouping tumors according to their developmental lineage can reconcile certain fundamental discrepancies resulting from morphologic and molecular approaches to neoplasm classification. In this study, six issues in tumor classification are described that exemplify the growing rift between morphologic and molecular approaches to tumor classification: 1) the morphologic separation between epithelial and non-epithelial tumors; 2) the grouping of tumors based on shared cellular functions; 3) the distinction between germ cell tumors and pluripotent tumors of non-germ cell origin; 4) the distinction between tumors that have lost their differentiation and tumors that arise from uncommitted stem cells; 5) the molecular properties shared by morphologically disparate tumors that have a common developmental lineage, and 6) the problem of re-classifying morphologically identical but clinically distinct subsets of tumors. The discussion of these issues in the context of describing different methods of tumor classification is intended to underscore the clinical value of a robust tumor classification. A

  4. Efficient molecular subtype classification of high-grade serous ovarian cancer.

    Leong, Huei San; Galletta, Laura; Etemadmoghadam, Dariush; George, Joshy; Köbel, Martin; Ramus, Susan J; Bowtell, David

    2015-07-01

    High-grade serous carcinomas (HGSCs) account for approximately 70% of all epithelial ovarian cancers diagnosed. Using microarray gene expression profiling, we previously identified four molecular subtypes of HGSC: C1 (mesenchymal), C2 (immunoreactive), C4 (differentiated), and C5 (proliferative), which correlate with patient survival and have distinct biological features. Here, we describe molecular classification of HGSC based on a limited number of genes to allow cost-effective and high-throughput subtype analysis. We determined a minimal signature for accurate classification, including 39 differentially expressed and nine control genes from microarray experiments. Taqman-based (low-density arrays and Fluidigm), fluorescent oligonucleotides (Nanostring), and targeted RNA sequencing (Illumina) assays were then compared for their ability to correctly classify fresh and formalin-fixed, paraffin-embedded samples. All platforms achieved > 90% classification accuracy with RNA from fresh frozen samples. The Illumina and Nanostring assays were superior with fixed material. We found that the C1, C2, and C4 molecular subtypes were largely consistent across multiple surgical deposits from individual chemo-naive patients. In contrast, we observed substantial subtype heterogeneity in patients whose primary ovarian sample was classified as C5. The development of an efficient molecular classifier of HGSC should enable further biological characterization of molecular subtypes and the development of targeted clinical trials. PMID:25810134

  5. Pathological Bases for a Robust Application of Cancer Molecular Classification

    Salvador J. Diaz-Cano

    2015-04-01

    Full Text Available Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes, and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors.

  6. Feature Selection and Molecular Classification of Cancer Using Genetic Programming

    Jianjun Yu

    2007-04-01

    Full Text Available Despite important advances in microarray-based molecular classification of tumors, its application in clinical settings remains formidable. This is in part due to the limitation of current analysis programs in discovering robust biomarkers and developing classifiers with a practical set of genes. Genetic programming (GP is a type of machine learning technique that uses evolutionary algorithm to simulate natural selection as well as population dynamics, hence leading to simple and comprehensible classifiers. Here we applied GP to cancer expression profiling data to select feature genes and build molecular classifiers by mathematical integration of these genes. Analysis of thousands of GP classifiers generated for a prostate cancer data set revealed repetitive use of a set of highly discriminative feature genes, many of which are known to be disease associated. GP classifiers often comprise five or less genes and successfully predict cancer types and subtypes. More importantly, GP classifiers generated in one study are able to predict samples from an independent study, which may have used different microarray platforms. In addition, GP yielded classification accuracy better than or similar to conventional classification methods. Furthermore, the mathematical expression of GP classifiers provides insights into relationships between classifier genes. Taken together, our results demonstrate that GP may be valuable for generating effective classifiers containing a practical set of genes for diagnostic/ prognostic cancer classification.

  7. A Highly Accurate Classification of TM Data through Correction of Atmospheric Effects

    Bill Smith; Frank Scarpace; Widad Elmahboub

    2009-01-01

    Atmospheric correction impacts on the accuracy of satellite image-based land cover classification are a growing concern among scientists. In this study, the principle objective was to enhance classification accuracy by minimizing contamination effects from aerosol scattering in Landsat TM images due to the variation in solar zenith angle corresponding to cloud-free earth targets. We have derived a mathematical model for aerosols to compute and subtract the aerosol scattering noise per pixel o...

  8. Molecular Pathological Classification of Neurodegenerative Diseases: Turning towards Precision Medicine.

    Kovacs, Gabor G

    2016-01-01

    Neurodegenerative diseases (NDDs) are characterized by selective dysfunction and loss of neurons associated with pathologically altered proteins that deposit in the human brain but also in peripheral organs. These proteins and their biochemical modifications can be potentially targeted for therapy or used as biomarkers. Despite a plethora of modifications demonstrated for different neurodegeneration-related proteins, such as amyloid-β, prion protein, tau, α-synuclein, TAR DNA-binding protein 43 (TDP-43), or fused in sarcoma protein (FUS), molecular classification of NDDs relies on detailed morphological evaluation of protein deposits, their distribution in the brain, and their correlation to clinical symptoms together with specific genetic alterations. A further facet of the neuropathology-based classification is the fact that many protein deposits show a hierarchical involvement of brain regions. This has been shown for Alzheimer and Parkinson disease and some forms of tauopathies and TDP-43 proteinopathies. The present paper aims to summarize current molecular classification of NDDs, focusing on the most relevant biochemical and morphological aspects. Since the combination of proteinopathies is frequent, definition of novel clusters of patients with NDDs needs to be considered in the era of precision medicine. Optimally, neuropathological categorizing of NDDs should be translated into in vivo detectable biomarkers to support better prediction of prognosis and stratification of patients for therapy trials. PMID:26848654

  9. Molecular Pathological Classification of Neurodegenerative Diseases: Turning towards Precision Medicine

    Gabor G. Kovacs

    2016-02-01

    Full Text Available Neurodegenerative diseases (NDDs are characterized by selective dysfunction and loss of neurons associated with pathologically altered proteins that deposit in the human brain but also in peripheral organs. These proteins and their biochemical modifications can be potentially targeted for therapy or used as biomarkers. Despite a plethora of modifications demonstrated for different neurodegeneration-related proteins, such as amyloid-β, prion protein, tau, α-synuclein, TAR DNA-binding protein 43 (TDP-43, or fused in sarcoma protein (FUS, molecular classification of NDDs relies on detailed morphological evaluation of protein deposits, their distribution in the brain, and their correlation to clinical symptoms together with specific genetic alterations. A further facet of the neuropathology-based classification is the fact that many protein deposits show a hierarchical involvement of brain regions. This has been shown for Alzheimer and Parkinson disease and some forms of tauopathies and TDP-43 proteinopathies. The present paper aims to summarize current molecular classification of NDDs, focusing on the most relevant biochemical and morphological aspects. Since the combination of proteinopathies is frequent, definition of novel clusters of patients with NDDs needs to be considered in the era of precision medicine. Optimally, neuropathological categorizing of NDDs should be translated into in vivo detectable biomarkers to support better prediction of prognosis and stratification of patients for therapy trials.

  10. A Highly Accurate Classification of TM Data through Correction of Atmospheric Effects

    Bill Smith

    2009-07-01

    Full Text Available Atmospheric correction impacts on the accuracy of satellite image-based land cover classification are a growing concern among scientists. In this study, the principle objective was to enhance classification accuracy by minimizing contamination effects from aerosol scattering in Landsat TM images due to the variation in solar zenith angle corresponding to cloud-free earth targets. We have derived a mathematical model for aerosols to compute and subtract the aerosol scattering noise per pixel of different vegetation classes from TM images of Nicolet in north-eastern Wisconsin. An algorithm in C++ has been developed with iterations to simulate, model, and correct for the solar zenith angle influences on scattering. Results from a supervised classification with corrected TM images showed increased class accuracy for land cover types over uncorrected images. The overall accuracy of the supervised classification was improved substantially (between 13% and 18%. The z-score shows significant difference between the corrected data and the raw data (between 4.0 and 12.0. Therefore, the atmospheric correction was essential for enhancing the image classification.

  11. Genetic classification and molecular mechanisms of primary dystonia

    Xueping Chen; Huifang Shang; Zuming Luo

    2008-01-01

    BACKGROUND: Primary dystonia is a heterogeneous disease, with a complex genetic basis. In previous studies, primary dystonia was classified according to age of onset, involved regions, and other clinical characteristics. With the development of molecular genetics, new virulence genes and sites have been discovered. Therefore, there is a gradual understanding of the various forms of dystonia, based on new viewpoints. There are 15 subtypes of dystonia, based on the molecular level, i.e., DYT1 to DYT15. OBJECTIVE: To analyze the genetic development of dystonia in detail, and to further investigate molecular mechanisms of dystonia. RETRIEVAL STRATEGY: A computer-based online search was conducted in PubMed for English language publications containing the keywords "dystonia and genetic" from January 1980 to March 2007. There were 105 articles in total. Inclusion criteria: ① the contents of the articles should closely address genetic classification and molecular mechanisms of primary dystonia; ② the articles published in recent years or in high-impact journals took preference. Exclusion criteria: duplicated articles. LITERATURE EVALUATION: The selected articles were on genetic classification and molecular genetics mechanism of primary dystonia. Of those, 27 were basic or clinical studies. DATA SYNTHESIS: ① Dystonia is a heterogeneous disease, with a complex genetic basis. According to the classification of the Human Genome Organization, there are 15 dystonia subtypes, based on genetics, i.e., DYT1-DYT15,including primary dystonia, dystonia plus syndrome, degeneration plus dystonia, and paroxysmal dyskinesia plus dystonia. ② To date, the chromosomes of 13 subtypes have been localized; however, DYT2 and DYT4 remain unclear. Six subtypes have been located within virulence genes. Specifically, torsinA gene expression results in the DYT1 genotype; autosomal dominant GTP cyclohydrolase I gene expression and recessive tyrosine hydroxylase expression result in the DYT5

  12. GPD: A Graph Pattern Diffusion Kernel for Accurate Graph Classification with Applications in Cheminformatics

    Smalter, Aaron; Huan, Jun; Jia, Yi; Lushington, Gerald

    2010-01-01

    Graph data mining is an active research area. Graphs are general modeling tools to organize information from heterogeneous sources and have been applied in many scientific, engineering, and business fields. With the fast accumulation of graph data, building highly accurate predictive models for graph data emerges as a new challenge that has not been fully explored in the data mining community. In this paper, we demonstrate a novel technique called graph pattern diffusion (GPD) kernel. Our ide...

  13. Novel approaches for the molecular classification of prostate cancer

    Robert H. Getzenberg

    2010-01-01

    @@ Among the urologic cancers, prostate cancer is by far the most common, and it appears to have the potential to affect almost all men throughout the world as they age. A number of studies have shown that many men with prostate cancer will not die from their disease, but rather with the disease but from other causes. These men have a form of prostate cancer that is de-scribed as "very low risk" and has often been called indolent. There are however a group of men that have a form of prostate cancer that is much more aggressive and life threatening. Unlike other cancer types, we have few tools to provide for the molecular classification of prostate cancer.

  14. Two fast and accurate heuristic RBF learning rules for data classification.

    Rouhani, Modjtaba; Javan, Dawood S

    2016-03-01

    This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher efficiency is achieved by fewer numbers of neurons, while the learning algorithm remains fast and simple. To retain network size limited, neurons are added to network recursively until termination condition is met. Each neuron covers some of train data. The termination condition is to cover all training data or to reach the maximum number of neurons. In each step, the center and spread of the new neuron are selected based on maximization of its coverage. Maximization of coverage of the neurons leads to a network with fewer neurons and indeed lower VC dimension and better generalization property. Using power exponential distribution function as the activation function of hidden neurons, and in the light of new learning approaches, it is proved that all data became linearly separable in the space of hidden layer outputs which implies that there exist linear output layer weights with zero training error. The proposed methods are applied to some well-known datasets and the simulation results, compared with SVM and some other leading RBF learning methods, show their satisfactory and comparable performance. PMID:26797472

  15. Fast and accurate quantum molecular dynamics of dense plasmas across temperature regimes

    Sjostrom, Travis; Daligault, Jerome

    2014-01-01

    We have developed and implemented a new quantum molecular dynamics approximation that allows fast and accurate simulations of dense plasmas from cold to hot conditions. The method is based on a carefully designed orbital-free implementation of density functional theory (DFT). The results for hydrogen and aluminum are in very good agreement with Kohn-Sham (orbital-based) DFT and path integral Monte Carlo (PIMC) for microscopic features such as the electron density as well as equation of state....

  16. Accurate modeling of molecular optical properties by a combination of molecular dynamics and quantum chemistry

    Andrushchenko, Valery; Bouř, Petr

    Katowice : University of Silesia, 2014. O6. [Chemistry towards Biology. Central Europe Conference /7./. 09.09.2014-12.09.2014, Katowice] R&D Projects: GA ČR(CZ) GA14-03564S Grant ostatní: AV ČR(CZ) M200550902 Institutional support: RVO:61388963 Keywords : molecular dynamics * quantum chemistry * multi-scale spectra Subject RIV: CF - Physical ; Theoretical Chemistry

  17. Classification of signaling proteins based on molecular star graph descriptors using Machine Learning models.

    Fernandez-Lozano, Carlos; Cuiñas, Rubén F; Seoane, José A; Fernández-Blanco, Enrique; Dorado, Julian; Munteanu, Cristian R

    2015-11-01

    Signaling proteins are an important topic in drug development due to the increased importance of finding fast, accurate and cheap methods to evaluate new molecular targets involved in specific diseases. The complexity of the protein structure hinders the direct association of the signaling activity with the molecular structure. Therefore, the proposed solution involves the use of protein star graphs for the peptide sequence information encoding into specific topological indices calculated with S2SNet tool. The Quantitative Structure-Activity Relationship classification model obtained with Machine Learning techniques is able to predict new signaling peptides. The best classification model is the first signaling prediction model, which is based on eleven descriptors and it was obtained using the Support Vector Machines-Recursive Feature Elimination (SVM-RFE) technique with the Laplacian kernel (RFE-LAP) and an AUROC of 0.961. Testing a set of 3114 proteins of unknown function from the PDB database assessed the prediction performance of the model. Important signaling pathways are presented for three UniprotIDs (34 PDBs) with a signaling prediction greater than 98.0%. PMID:26297890

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

    Laetitia Marisa

    Full Text Available BACKGROUND: 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. METHODS AND FINDINGS: 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

  19. Head and neck paragangliomas: clinical and molecular genetic classification.

    Offergeld, Christian; Brase, Christoph; Yaremchuk, Svetlana; Mader, Irina; Rischke, Hans Christian; Gläsker, Sven; Schmid, Kurt W; Wiech, Thorsten; Preuss, Simon F; Suárez, Carlos; Kopeć, Tomasz; Patocs, Attila; Wohllk, Nelson; Malekpour, Mahdi; Boedeker, Carsten C; Neumann, Hartmut P H

    2012-01-01

    Head and neck paragangliomas are tumors arising from specialized neural crest cells. Prominent locations are the carotid body along with the vagal, jugular, and tympanic glomus. Head and neck paragangliomas are slowly growing tumors, with some carotid body tumors being reported to exist for many years as a painless lateral mass on the neck. Symptoms depend on the specific locations. In contrast to paraganglial tumors of the adrenals, abdomen and thorax, head and neck paragangliomas seldom release catecholamines and are hence rarely vasoactive. Petrous bone, jugular, and tympanic head and neck paragangliomas may cause hearing loss. The internationally accepted clinical classifications for carotid body tumors are based on the Shamblin Class I-III stages, which correspond to postoperative permanent side effects. For petrous-bone paragangliomas in the head and neck, the Fisch classification is used. Regarding the molecular genetics, head and neck paragangliomas have been associated with nine susceptibility genes: NF1, RET, VHL, SDHA, SDHB, SDHC, SDHD, SDHAF2 (SDH5), and TMEM127. Hereditary HNPs are mostly caused by mutations of the SDHD gene, but SDHB and SDHC mutations are not uncommon in such patients. Head and neck paragangliomas are rarely associated with mutations of VHL, RET, or NF1. The research on SDHA, SDHAF2 and TMEM127 is ongoing. Multiple head and neck paragangliomas are common in patients with SDHD mutations, while malignant head and neck paraganglioma is mostly seen in patients with SDHB mutations. The treatment of choice is surgical resection. Good postoperative results can be expected in carotid body tumors of Shamblin Class I and II, whereas operations on other carotid body tumors and other head and neck paragangliomas frequently result in deficits of the cranial nerves adjacent to the tumors. Slow growth and the tendency of hereditary head and neck paragangliomas to be multifocal may justify less aggressive treatment strategies. PMID:22584701

  20. Head and neck paragangliomas: clinical and molecular genetic classification

    Christian Offergeld

    2012-01-01

    Full Text Available Head and neck paragangliomas are tumors arising from specialized neural crest cells. Prominent locations are the carotid body along with the vagal, jugular, and tympanic glomus. Head and neck paragangliomas are slowly growing tumors, with some carotid body tumors being reported to exist for many years as a painless lateral mass on the neck. Symptoms depend on the specific locations. In contrast to paraganglial tumors of the adrenals, abdomen and thorax, head and neck paragangliomas seldom release catecholamines and are hence rarely vasoactive. Petrous bone, jugular, and tympanic head and neck paragangliomas may cause hearing loss. The internationally accepted clinical classifications for carotid body tumors are based on the Shamblin Class I-III stages, which correspond to postoperative permanent side effects. For petrous-bone paragangliomas in the head and neck, the Fisch classification is used. Regarding the molecular genetics, head and neck paragangliomas have been associated with nine susceptibility genes: NF1, RET, VHL, SDHA, SDHB, SDHC, SDHD, SDHAF2 (SDH5, and TMEM127. Hereditary HNPs are mostly caused by mutations of the SDHD gene, but SDHB and SDHC mutations are not uncommon in such patients. Head and neck paragangliomas are rarely associated with mutations of VHL, RET, or NF1. The research on SDHA, SDHAF2 and TMEM127 is ongoing. Multiple head and neck paragangliomas are common in patients with SDHD mutations, while malignant head and neck paraganglioma is mostly seen in patients with SDHB mutations. The treatment of choice is surgical resection. Good postoperative results can be expected in carotid body tumors of Shamblin Class I and II, whereas operations on other carotid body tumors and other head and neck paragangliomas frequently result in deficits of the cranial nerves adjacent to the tumors. Slow growth and the tendency of hereditary head and neck paragangliomas to be multifocal may justify less aggressive treatment strategies.

  1. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the 'holy grail' of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies

  2. CAST: a new program package for the accurate characterization of large and flexible molecular systems.

    Grebner, Christoph; Becker, Johannes; Weber, Daniel; Bellinger, Daniel; Tafipolski, Maxim; Brückner, Charlotte; Engels, Bernd

    2014-09-15

    The presented program package, Conformational Analysis and Search Tool (CAST) allows the accurate treatment of large and flexible (macro) molecular systems. For the determination of thermally accessible minima CAST offers the newly developed TabuSearch algorithm, but algorithms such as Monte Carlo (MC), MC with minimization, and molecular dynamics are implemented as well. For the determination of reaction paths, CAST provides the PathOpt, the Nudge Elastic band, and the umbrella sampling approach. Access to free energies is possible through the free energy perturbation approach. Along with a number of standard force fields, a newly developed symmetry-adapted perturbation theory-based force field is included. Semiempirical computations are possible through DFTB+ and MOPAC interfaces. For calculations based on density functional theory, a Message Passing Interface (MPI) interface to the Graphics Processing Unit (GPU)-accelerated TeraChem program is available. The program is available on request. PMID:25056524

  3. Molecular Simulation of the Free Energy for the Accurate Determination of Phase Transition Properties of Molecular Solids

    Sellers, Michael; Lisal, Martin; Brennan, John

    2015-06-01

    Investigating the ability of a molecular model to accurately represent a real material is crucial to model development and use. When the model simulates materials in extreme conditions, one such property worth evaluating is the phase transition point. However, phase transitions are often overlooked or approximated because of difficulty or inaccuracy when simulating them. Techniques such as super-heating or super-squeezing a material to induce a phase change suffer from inherent timescale limitations leading to ``over-driving,'' and dual-phase simulations require many long-time runs to seek out what frequently results in an inexact location of phase-coexistence. We present a compilation of methods for the determination of solid-solid and solid-liquid phase transition points through the accurate calculation of the chemical potential. The methods are applied to the Smith-Bharadwaj atomistic potential's representation of cyclotrimethylene trinitramine (RDX) to accurately determine its melting point (Tm) and the alpha to gamma solid phase transition pressure. We also determine Tm for a coarse-grain model of RDX, and compare its value to experiment and atomistic counterpart. All methods are employed via the LAMMPS simulator, resulting in 60-70 simulations that total 30-50 ns. Approved for public release. Distribution is unlimited.

  4. Fast and accurate quantum molecular dynamics of dense plasmas across temperature regimes

    Sjostrom, Travis

    2014-01-01

    We have developed and implemented a new quantum molecular dynamics approximation that allows fast and accurate simulations of dense plasmas from cold to hot conditions. The method is based on a carefully designed orbital-free implementation of density functional theory (DFT). The results for hydrogen and aluminum are in very good agreement with Kohn-Sham (orbital-based) DFT and path integral Monte Carlo (PIMC) for microscopic features such as the electron density as well as equation of state. The present approach does not scale with temperature and hence extends to higher temperatures than is accessible in Kohn-Sham method and lower temperatures than is accessible by PIMC, while being significantly less computationally expensive than either of those two methods

  5. PyVCI: A flexible open-source code for calculating accurate molecular infrared spectra

    Sibaev, Marat; Crittenden, Deborah L.

    2016-06-01

    The PyVCI program package is a general purpose open-source code for simulating accurate molecular spectra, based upon force field expansions of the potential energy surface in normal mode coordinates. It includes harmonic normal coordinate analysis and vibrational configuration interaction (VCI) algorithms, implemented primarily in Python for accessibility but with time-consuming routines written in C. Coriolis coupling terms may be optionally included in the vibrational Hamiltonian. Non-negligible VCI matrix elements are stored in sparse matrix format to alleviate the diagonalization problem. CPU and memory requirements may be further controlled by algorithmic choices and/or numerical screening procedures, and recommended values are established by benchmarking using a test set of 44 molecules for which accurate analytical potential energy surfaces are available. Force fields in normal mode coordinates are obtained from the PyPES library of high quality analytical potential energy surfaces (to 6th order) or by numerical differentiation of analytic second derivatives generated using the GAMESS quantum chemical program package (to 4th order).

  6. Surface electron density models for accurate ab initio molecular dynamics with electronic friction

    Novko, D.; Blanco-Rey, M.; Alducin, M.; Juaristi, J. I.

    2016-06-01

    Ab initio molecular dynamics with electronic friction (AIMDEF) is a valuable methodology to study the interaction of atomic particles with metal surfaces. This method, in which the effect of low-energy electron-hole (e-h) pair excitations is treated within the local density friction approximation (LDFA) [Juaristi et al., Phys. Rev. Lett. 100, 116102 (2008), 10.1103/PhysRevLett.100.116102], can provide an accurate description of both e-h pair and phonon excitations. In practice, its applicability becomes a complicated task in those situations of substantial surface atoms displacements because the LDFA requires the knowledge at each integration step of the bare surface electron density. In this work, we propose three different methods of calculating on-the-fly the electron density of the distorted surface and we discuss their suitability under typical surface distortions. The investigated methods are used in AIMDEF simulations for three illustrative adsorption cases, namely, dissociated H2 on Pd(100), N on Ag(111), and N2 on Fe(110). Our AIMDEF calculations performed with the three approaches highlight the importance of going beyond the frozen surface density to accurately describe the energy released into e-h pair excitations in case of large surface atom displacements.

  7. Pediatric Medulloblastoma – Update on Molecular Classification Driving Targeted Therapies

    Ruth eDeSouza; Jones, Benjamin R. T.; Lowis, Stephen P.; Kurian, Kathreena M.

    2014-01-01

    As advances in the molecular and genetic profiling of paediatric medulloblastoma evolve, associations with prognosis and treatment are found (prognostic and predictive biomarkers) and research is directed at molecular therapies. Medulloblastoma typically affects young patients, where the implications of any treatment on the developing brain must be carefully considered. The aim of this article is to provide a clear comprehensible update on the role molecular profiling and subgroups in paediat...

  8. Hydration free energies of cyanide and hydroxide ions from molecular dynamics simulations with accurate force fields

    Lee, M.W.; Meuwly, M.

    2013-01-01

    The evaluation of hydration free energies is a sensitive test to assess force fields used in atomistic simulations. We showed recently that the vibrational relaxation times, 1D- and 2D-infrared spectroscopies for CN(-) in water can be quantitatively described from molecular dynamics (MD) simulations with multipolar force fields and slightly enlarged van der Waals radii for the C- and N-atoms. To validate such an approach, the present work investigates the solvation free energy of cyanide in water using MD simulations with accurate multipolar electrostatics. It is found that larger van der Waals radii are indeed necessary to obtain results close to the experimental values when a multipolar force field is used. For CN(-), the van der Waals ranges refined in our previous work yield hydration free energy between -72.0 and -77.2 kcal mol(-1), which is in excellent agreement with the experimental data. In addition to the cyanide ion, we also study the hydroxide ion to show that the method used here is readily applicable to similar systems. Hydration free energies are found to sensitively depend on the intermolecular interactions, while bonded interactions are less important, as expected. We also investigate in the present work the possibility of applying the multipolar force field in scoring trajectories generated using computationally inexpensive methods, which should be useful in broader parametrization studies with reduced computational resources, as scoring is much faster than the generation of the trajectories.

  9. Accurate calculation of binding energies for molecular clusters - Assessment of different models

    Friedrich, Joachim; Fiedler, Benjamin

    2016-06-01

    In this work we test different strategies to compute high-level benchmark energies for medium-sized molecular clusters. We use the incremental scheme to obtain CCSD(T)/CBS energies for our test set and carefully validate the accuracy for binding energies by statistical measures. The local errors of the incremental scheme are benchmark values are ΔE = - 278.01 kJ/mol for (H2O)10, ΔE = - 221.64 kJ/mol for (HF)10, ΔE = - 45.63 kJ/mol for (CH4)10, ΔE = - 19.52 kJ/mol for (H2)20 and ΔE = - 7.38 kJ/mol for (H2)10 . Furthermore we test state-of-the-art wave-function-based and DFT methods. Our benchmark data will be very useful for critical validations of new methods. We find focal-point-methods for estimating CCSD(T)/CBS energies to be highly accurate and efficient. For foQ-i3CCSD(T)-MP2/TZ we get a mean error of 0.34 kJ/mol and a standard deviation of 0.39 kJ/mol.

  10. A simple method to combine multiple molecular biomarkers for dichotomous diagnostic classification

    Amin Manik A

    2006-10-01

    Full Text Available Abstract Background In spite of the recognized diagnostic potential of biomarkers, the quest for squelching noise and wringing in information from a given set of biomarkers continues. Here, we suggest a statistical algorithm that – assuming each molecular biomarker to be a diagnostic test – enriches the diagnostic performance of an optimized set of independent biomarkers employing established statistical techniques. We validated the proposed algorithm using several simulation datasets in addition to four publicly available real datasets that compared i subjects having cancer with those without; ii subjects with two different cancers; iii subjects with two different types of one cancer; and iv subjects with same cancer resulting in differential time to metastasis. Results Our algorithm comprises of three steps: estimating the area under the receiver operating characteristic curve for each biomarker, identifying a subset of biomarkers using linear regression and combining the chosen biomarkers using linear discriminant function analysis. Combining these established statistical methods that are available in most statistical packages, we observed that the diagnostic accuracy of our approach was 100%, 99.94%, 96.67% and 93.92% for the real datasets used in the study. These estimates were comparable to or better than the ones previously reported using alternative methods. In a synthetic dataset, we also observed that all the biomarkers chosen by our algorithm were indeed truly differentially expressed. Conclusion The proposed algorithm can be used for accurate diagnosis in the setting of dichotomous classification of disease states.

  11. Review of current classification, molecular alterations, and tyrosine kinase inhibitor therapies in myeloproliferative disorders with hypereosinophilia

    Havelange V

    2013-08-01

    Full Text Available Violaine Havelange,1,2 Jean-Baptiste Demoulin1 1de Duve Institute, Université catholique de Louvain, Brussels, Belgium; 2Department of Hematology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium Abstract: Recent advances in our understanding of the molecular mechanisms underlying hypereosinophilia have led to the development of a 'molecular' classification of myeloproliferative disorders with eosinophilia. The revised 2008 World Health Organization classification of myeloid neoplasms included a new category called “myeloid and lymphoid neoplasms with eosinophilia and abnormalities of PDGFRA, PDGFRB or FGFR1.” Despite the molecular heterogeneity of PDGFR (platelet-derived growth factor receptor rearrangements, tyrosine kinase inhibitors at low dose induce rapid and complete hematological remission in the majority of these patients. Other kinase inhibitors are promising. Further discoveries of new molecular alterations will direct the development of new specific inhibitors. In this review, an update of the classifications of myeloproliferative disorders associated with hypereosinophilia is discussed together with open and controversial questions. Molecular mechanisms and promising results of tyrosine kinase inhibitor treatments are reviewed. Keywords: hypereosinophilia, classification, myeloproliferative disorders, molecular alterations, tyrosine kinase inhibitor

  12. Classification

    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…

  13. Balancing an accurate representation of the molecular surface in generalized Born formalisms with integrator stability in molecular dynamics simulations

    Chocholoušová, Jana; Feig, M.

    2006-01-01

    Roč. 27, č. 6 (2006), s. 719-729. ISSN 0192-8651 Keywords : molecular surface * generalized Born formalisms * molecular dynamic simulations Subject RIV: CC - Organic Chemistry Impact factor: 4.893, year: 2006

  14. Appraisal of progenitor markers in the context of molecular classification of breast cancers

    Haviv, Izhak

    2011-01-01

    Clinical management of breast cancer relies on case stratification, which increasingly employs molecular markers. The motivation behind delineating breast epithelial differentiation is to better target cancer cases through innate sensitivities bequeathed to the cancer from its normal progenitor state. A combination of histopathological and molecular classification of breast cancer cases suggests a role for progenitors in particular breast cancer cases. Although a remarkable fraction of the re...

  15. Molecular phylogeny of the Bothriocephalidea (Cestoda): molecular data challenge morphological classification.

    Brabec, Jan; Waeschenbach, Andrea; Scholz, Tomáš; Littlewood, D Timothy J; Kuchta, Roman

    2015-10-01

    In this study, the relationships of the cestode order Bothriocephalidea, parasites of marine and freshwater bony fish, were assessed using multi-gene molecular phylogenetic analyses. The dataset included 59 species, covering approximately 70% of currently recognised genera, a sample of bothriocephalidean biodiversity gathered through an intense 15year effort. The order as currently circumscribed, while monophyletic, includes three non-monophyletic and one monophyletic families. Bothriocephalidae is monophyletic and forms the most derived lineage of the order, comprised of a single freshwater and several marine clades. Biogeographic patterns within the freshwater clade are indicative of past radiations having occurred in Africa and North America. The earliest diverging lineages of the order comprise a paraphyletic Triaenophoridae. The Echinophallidae, consisting nearly exclusively of parasites of pelagic fish, was also resolved as paraphyletic with respect to the Bothriocephalidae. Philobythoides sp., the only representative included from the Philobythiidae, a unique family of parasites of bathypelagic fish, was sister to the genus Eubothrium, the latter constituting one of the lineages of the paraphyletic Triaenophoridae. Due to the weak statistical support for most of the basal nodes of the Triaenophoridae and Echinophallidae, as well as the lack of obvious morphological synapomorphies shared by taxa belonging to the statistically well-supported lineages, the current family-level classification, although mostly non-monophyletic, is provisionally retained, with the exception of the family Philobythiidae, which is recognised as a synonym of the Triaenophoridae. In addition, Schyzocotyle is resurrected to accommodate the invasive Asian fish tapeworm, Schyzocotyle acheilognathi (Yamaguti, 1934) n. comb. (syn. Bothriocephalus acheilognathi Yamaguti, 1934), which is of veterinary importance, and Schyzocotyle nayarensis (Malhotra, 1983) n. comb. (syn. Ptychobothrium

  16. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

    Bechet, P.; Mitran, R.; Munteanu, M.

    2013-08-01

    Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

  17. Laryngeal Squamous Intraepithelial Lesions: An Updated Review on Etiology, Classification, Molecular Changes, and Treatment.

    Gale, Nina; Gnepp, Douglas R; Poljak, Mario; Strojan, Primož; Cardesa, Antonio; Helliwell, Tim; Šifrer, Robert; Volavšek, Metka; Sandison, Ann; Zidar, Nina

    2016-03-01

    Laryngeal carcinogenesis is a multistep process, characterized by an accumulation of genetic changes associated with architectural and cytologic alterations, ranging from squamous hyperplasia to carcinoma in situ and encompassed by the terminology of squamous intraepithelial lesions (SILs). The etiology, classification, genetic changes, and malignant progression of these lesions are reviewed. Tobacco remains the principal etiological factor with gastroesophageal reflux disease recently considered as a possible factor. In contrast, there is little evidence that microbiological agents, especially human papillomavirus infection, are frequently involved in laryngeal carcinogenesis and probably subjectivity, remains the mainstay of accurate diagnosis, prognosis, and guidance for a patient's treatment. The currently used classifications, the dysplasia system, squamous intraepithelial neoplasia, and the Ljubljana classification, reflect different standpoints on this important topic. The modified Ljubljana classification, with good interobserver agreement, could be considered as a proposal for a unified classification of laryngeal SILs. This review also briefly discusses recently discovered genetic changes, such as CDKN2A and CTNNB1 genes, and chromosome instability of chromosomes 1 and 7; however, none of these can at present improve histologic diagnosis. Malignant progression of precursor lesions varies from 2% to 74%, according to different studies. Cold-steel microinstruments, CO2 laser, and radiotherapy are used to treat the different grades of precursor lesions. There is as yet no worldwide agreement on the treatment of high-grade lesions and carcinoma in situ. PMID:26849814

  18. Accurate prediction of interference minima in linear molecular harmonic spectra by a modified two-center model

    Xin, Cui; Di-Yu, Zhang; Gao, Chen; Ji-Gen, Chen; Si-Liang, Zeng; Fu-Ming, Guo; Yu-Jun, Yang

    2016-03-01

    We demonstrate that the interference minima in the linear molecular harmonic spectra can be accurately predicted by a modified two-center model. Based on systematically investigating the interference minima in the linear molecular harmonic spectra by the strong-field approximation (SFA), it is found that the locations of the harmonic minima are related not only to the nuclear distance between the two main atoms contributing to the harmonic generation, but also to the symmetry of the molecular orbital. Therefore, we modify the initial phase difference between the double wave sources in the two-center model, and predict the harmonic minimum positions consistent with those simulated by SFA. Project supported by the National Basic Research Program of China (Grant No. 2013CB922200) and the National Natural Science Foundation of China (Grant Nos. 11274001, 11274141, 11304116, 11247024, and 11034003), and the Jilin Provincial Research Foundation for Basic Research, China (Grant Nos. 20130101012JC and 20140101168JC).

  19. Accurate CO2 JouleůThomson Inversion Curve by Molecular Simulations

    Colina, C. M.; Lísal, Martin; Siperstein, F. R.; Gubbins, K. E.

    2002-01-01

    Roč. 202, č. 2 (2002), s. 253-262. ISSN 0378-3812 R&D Projects: GA ČR GA203/02/0805 Grant ostatní: NSF(US) CHE 9876674 Keywords : carbon dioxide * Joule- Thomson inversion curve * molecular simulation Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.011, year: 2002

  20. Utilizing fast multipole expansions for efficient and accurate quantum-classical molecular dynamics simulations.

    Schwörer, Magnus; Lorenzen, Konstantin; Mathias, Gerald; Tavan, Paul

    2015-03-14

    Recently, a novel approach to hybrid quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations has been suggested [Schwörer et al., J. Chem. Phys. 138, 244103 (2013)]. Here, the forces acting on the atoms are calculated by grid-based density functional theory (DFT) for a solute molecule and by a polarizable molecular mechanics (PMM) force field for a large solvent environment composed of several 10(3)-10(5) molecules as negative gradients of a DFT/PMM hybrid Hamiltonian. The electrostatic interactions are efficiently described by a hierarchical fast multipole method (FMM). Adopting recent progress of this FMM technique [Lorenzen et al., J. Chem. Theory Comput. 10, 3244 (2014)], which particularly entails a strictly linear scaling of the computational effort with the system size, and adapting this revised FMM approach to the computation of the interactions between the DFT and PMM fragments of a simulation system, here, we show how one can further enhance the efficiency and accuracy of such DFT/PMM-MD simulations. The resulting gain of total performance, as measured for alanine dipeptide (DFT) embedded in water (PMM) by the product of the gains in efficiency and accuracy, amounts to about one order of magnitude. We also demonstrate that the jointly parallelized implementation of the DFT and PMM-MD parts of the computation enables the efficient use of high-performance computing systems. The associated software is available online. PMID:25770527

  1. Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm.

    Mark D McDonnell

    Full Text Available Recent advances in training deep (multi-layer architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the 'Extreme Learning Machine' (ELM approach, which also enables a very rapid training time (∼ 10 minutes. Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random 'receptive field' sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems.

  2. Molecular phylogenetic perspectives for character classification and convergence: Framing some issues with nematode vulval appendages and telotylenchid tail termini

    Characters flagged as convergent based on newer molecular phylogenetic trees inform both practical identification and more esoteric classification. Nematode morphological characters such as lateral lines, bullae and laciniae are quite independent structures from those similarly named in other organi...

  3. 善用《中图法》(第五版)改善图书文献归类准确性%Books and Documents'Accurate Classification by Using Chinese Library Classification ( Sth Edition)

    汤彩霞

    2011-01-01

    从三个方面讨论如何善用《中图法》(第五版)(以下简称CLC5)改善图书文献归类准确性,分别是:做好和CLC5相关的前期准备工作,如新旧分类法的比对等;了解和掌握《中图法》(第五版)的部分通用分类规则;制定启用CLC5的本馆分类规定。%From three aspects, this paper discusses how to classify books and documents accurately by using the Chinese Library Classification (Sth Edition) (hereafter referred to as CLC5 ), such as: making a good preliminary preparation for CLCS, including the comparison of the new with the old classification, etc. ; Understanding and grasping some universal classification rules of CLCS; Making the regulations of launching CLC5 in our library.

  4. Molecular Detection of Foodborne Pathogens: A Rapid and Accurate Answer to Food Safety.

    Mangal, Manisha; Bansal, Sangita; Sharma, Satish K; Gupta, Ram K

    2016-07-01

    Food safety is a global health concern. For the prevention and recognition of problems related to health and safety, detection of foodborne pathogen is of utmost importance at all levels of food production chain. For several decades, a lot of research has been targeted at the development of rapid methodology as reducing the time needed to complete pathogen detection tests has been the primary goal of food microbiologists. With the result, food microbiology laboratories now have a wide array of detection methods and automated technologies such as enzyme immunoassay, polymerase chain reaction, and microarrays, which can cut test times considerably. Nucleic acid amplification strategies and advances in amplicon detection methodologies have been the key factors in the progress of molecular microbiology. A comprehensive literature survey has been carried out to give an overview in the field of foodborne pathogen detection. In this paper, we describe the conventional methods, as well as recent developments in food pathogen detection, identification, and quantification, with a major emphasis on molecular detection methods. PMID:25830555

  5. Accurate reaction-diffusion operator splitting on tetrahedral meshes for parallel stochastic molecular simulations.

    Hepburn, I; Chen, W; De Schutter, E

    2016-08-01

    Spatial stochastic molecular simulations in biology are limited by the intense computation required to track molecules in space either in a discrete time or discrete space framework, which has led to the development of parallel methods that can take advantage of the power of modern supercomputers in recent years. We systematically test suggested components of stochastic reaction-diffusion operator splitting in the literature and discuss their effects on accuracy. We introduce an operator splitting implementation for irregular meshes that enhances accuracy with minimal performance cost. We test a range of models in small-scale MPI simulations from simple diffusion models to realistic biological models and find that multi-dimensional geometry partitioning is an important consideration for optimum performance. We demonstrate performance gains of 1-3 orders of magnitude in the parallel implementation, with peak performance strongly dependent on model specification. PMID:27497550

  6. A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat

    Liu, Jian; Li, Dezhang; Liu, Xinzijian

    2016-07-01

    We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.

  7. Accurate reaction-diffusion operator splitting on tetrahedral meshes for parallel stochastic molecular simulations

    Hepburn, I.; Chen, W.; De Schutter, E.

    2016-08-01

    Spatial stochastic molecular simulations in biology are limited by the intense computation required to track molecules in space either in a discrete time or discrete space framework, which has led to the development of parallel methods that can take advantage of the power of modern supercomputers in recent years. We systematically test suggested components of stochastic reaction-diffusion operator splitting in the literature and discuss their effects on accuracy. We introduce an operator splitting implementation for irregular meshes that enhances accuracy with minimal performance cost. We test a range of models in small-scale MPI simulations from simple diffusion models to realistic biological models and find that multi-dimensional geometry partitioning is an important consideration for optimum performance. We demonstrate performance gains of 1-3 orders of magnitude in the parallel implementation, with peak performance strongly dependent on model specification.

  8. Automated Analysis and Classification of Histological Tissue Features by Multi-Dimensional Microscopic Molecular Profiling.

    Daniel P Riordan

    Full Text Available Characterization of the molecular attributes and spatial arrangements of cells and features within complex human tissues provides a critical basis for understanding processes involved in development and disease. Moreover, the ability to automate steps in the analysis and interpretation of histological images that currently require manual inspection by pathologists could revolutionize medical diagnostics. Toward this end, we developed a new imaging approach called multidimensional microscopic molecular profiling (MMMP that can measure several independent molecular properties in situ at subcellular resolution for the same tissue specimen. MMMP involves repeated cycles of antibody or histochemical staining, imaging, and signal removal, which ultimately can generate information analogous to a multidimensional flow cytometry analysis on intact tissue sections. We performed a MMMP analysis on a tissue microarray containing a diverse set of 102 human tissues using a panel of 15 informative antibody and 5 histochemical stains plus DAPI. Large-scale unsupervised analysis of MMMP data, and visualization of the resulting classifications, identified molecular profiles that were associated with functional tissue features. We then directly annotated H&E images from this MMMP series such that canonical histological features of interest (e.g. blood vessels, epithelium, red blood cells were individually labeled. By integrating image annotation data, we identified molecular signatures that were associated with specific histological annotations and we developed statistical models for automatically classifying these features. The classification accuracy for automated histology labeling was objectively evaluated using a cross-validation strategy, and significant accuracy (with a median per-pixel rate of 77% per feature from 15 annotated samples for de novo feature prediction was obtained. These results suggest that high-dimensional profiling may advance the

  9. The molecular subtype classification is a determinant of sentinel node positivity in early breast carcinoma.

    Fabien Reyal

    Full Text Available INTRODUCTION: Several authors have underscored a strong relation between the molecular subtypes and the axillary status of breast cancer patients. The aim of our work was to decipher the interaction between this classification and the probability of a positive sentinel node biopsy. MATERIALS AND METHODS: Our dataset consisted of a total number of 2654 early-stage breast cancer patients. Patients treated at first by conservative breast surgery plus sentinel node biopsies were selected. A multivariate logistic regression model was trained and validated. Interaction covariate between ER and HER2 markers was a forced input of this model. The performance of the multivariate model in the training and the two validation sets was analyzed in terms of discrimination and calibration. Probability of axillary metastasis was detailed for each molecular subtype. RESULTS: The interaction covariate between ER and HER2 status was a stronger predictor (p = 0.0031 of positive sentinel node biopsy than the ER status by itself (p = 0.016. A multivariate model to determine the probability of sentinel node positivity was defined with the following variables; tumour size, lympho-vascular invasion, molecular subtypes and age at diagnosis. This model showed similar results in terms of discrimination (AUC = 0.72/0.73/0.72 and calibration (HL p = 0.28/0.05/0.11 in the training and validation sets. The interaction between molecular subtypes, tumour size and sentinel nodes status was approximated. DISCUSSION: We showed that biologically-driven analyses are able to build new models with higher performance in terms of breast cancer axillary status prediction. The molecular subtype classification strongly interacts with the axillary and distant metastasis process.

  10. Modern classification of breast cancer: should we stick with morphology or convert to molecular profile characteristics.

    Rakha, Emad A; Ellis, Ian O

    2011-07-01

    Breast cancer represents a heterogeneous group of tumors with varied morphologic and biological features, behavior, and response to therapy. The present routine clinical management of breast cancer relies on the availability of robust prognostic and predictive factors to support decision making. Breast cancer patients are stratified into risk groups based on a combination of classical time-dependent prognostic variables (staging) and biological prognostic and predictive variables. Staging variables include tumor size, lymph node stage, and extent of tumor spread. Classical biological variables include morphologic variables such as tumor grade and molecular markers such as hormone receptor and human epidermal growth factor receptor 2 status. Although individual molecular markers were introduced in the field of breast cancer management many years ago, the concept of molecular classification was raised after the introduction of global gene expression profiling and the identification of multigene classifiers. Although there is no doubt that gene expression profiling technology has revolutionized the field of breast cancer research and have been widely expected to improve breast cancer prognostication, the unprecedented speed of progress and publicity associated with the introduction of these commercially-based multigene classifiers should not lead us to expect this technology to replace the classical classification systems. These multigene classifiers have the potential to complement traditional methods through provision of additional biological prognostic and predictive information in presently indeterminate risk groups. Here we present updated information on the present clinical value of classical clinicopathologic factors, molecular taxonomy, and multigene classifiers in routine patients management and provide some critical views and practical expectations. PMID:21654357

  11. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    Inti eZlobec

    2012-02-01

    Full Text Available Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP, microsatellite instability (MSI, KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1, MGMT, MSI, KRAS and BRAF. Tumors were CIMP-high or CIMP-low if ≥4 and 1-3 promoters were methylated, respectively. Results: CIMP-high, CIMP-low and CIMP–negative were found in 7.1%, 43% and 49.9% cases, respectively. 123 tumors (41% could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-low, 14 CIMP-high and 2 CIMP-negative cases. The 10-year survival rate for CIMP-high patients (22.6% (95%CI: 7-43 was significantly lower than for CIMP-low or CIMP-negative (p=0.0295. Only the combined analysis of BRAF and CIMP (negative versus low/high led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  12. Bottom-up coarse-grained models that accurately describe the structure, pressure, and compressibility of molecular liquids

    The present work investigates the capability of bottom-up coarse-graining (CG) methods for accurately modeling both structural and thermodynamic properties of all-atom (AA) models for molecular liquids. In particular, we consider 1, 2, and 3-site CG models for heptane, as well as 1 and 3-site CG models for toluene. For each model, we employ the multiscale coarse-graining method to determine interaction potentials that optimally approximate the configuration dependence of the many-body potential of mean force (PMF). We employ a previously developed “pressure-matching” variational principle to determine a volume-dependent contribution to the potential, UV(V), that approximates the volume-dependence of the PMF. We demonstrate that the resulting CG models describe AA density fluctuations with qualitative, but not quantitative, accuracy. Accordingly, we develop a self-consistent approach for further optimizing UV, such that the CG models accurately reproduce the equilibrium density, compressibility, and average pressure of the AA models, although the CG models still significantly underestimate the atomic pressure fluctuations. Additionally, by comparing this array of models that accurately describe the structure and thermodynamic pressure of heptane and toluene at a range of different resolutions, we investigate the impact of bottom-up coarse-graining upon thermodynamic properties. In particular, we demonstrate that UV accounts for the reduced cohesion in the CG models. Finally, we observe that bottom-up coarse-graining introduces subtle correlations between the resolution, the cohesive energy density, and the “simplicity” of the model

  13. SpineAnalyzer™ is an accurate and precise method of vertebral fracture detection and classification on dual-energy lateral vertebral assessment scans

    Osteoporotic fractures of the spine are associated with significant morbidity, are highly predictive of hip fractures, but frequently do not present clinically. When there is a low to moderate clinical suspicion of vertebral fracture, which would not justify acquisition of a radiograph, vertebral fracture assessment (VFA) using Dual-energy X-ray Absorptiometry (DXA) offers a low-dose opportunity for diagnosis. Different approaches to the classification of vertebral fractures have been documented. The aim of this study was to measure the precision and accuracy of SpineAnalyzer™, a quantitative morphometry software program. Lateral vertebral assessment images of 64 men were analysed using SpineAnalyzer™ and standard GE Lunar software. The images were also analysed by two expert readers using a semi-quantitative approach. Agreement between groups ranged from 95.99% to 98.60%. The intra-rater precision for the application of SpineAnalyzer™ to vertebrae was poor in the upper thoracic regions, but good elsewhere. SpineAnalyzer™ is a reproducible and accurate method for measuring vertebral height and quantifying vertebral fractures from VFA scans. - Highlights: • Vertebral fracture assessment (VFA) using Dual-energy X-ray Absorptiometry (DXA) offers a low-dose opportunity for diagnosis. • Agreement between VFA software (SpineAnalyzer™) and expert readers is high. • Intra-rater precision of SpineAnalyzer™ applied to upper thoracic vertebrae is poor, but good elsewhere. • SpineAnalyzer™ is reproducible and accurate for vertebral height measurement and fracture quantification from VFA scans

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

    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

  15. Molecular phylogenetic evaluation of classification and scenarios of character evolution in calcareous sponges (Porifera, Class Calcarea.

    Oliver Voigt

    Full Text Available Calcareous sponges (Phylum Porifera, Class Calcarea are known to be taxonomically difficult. Previous molecular studies have revealed many discrepancies between classically recognized taxa and the observed relationships at the order, family and genus levels; these inconsistencies question underlying hypotheses regarding the evolution of certain morphological characters. Therefore, we extended the available taxa and character set by sequencing the complete small subunit (SSU rDNA and the almost complete large subunit (LSU rDNA of additional key species and complemented this dataset by substantially increasing the length of available LSU sequences. Phylogenetic analyses provided new hypotheses about the relationships of Calcarea and about the evolution of certain morphological characters. We tested our phylogeny against competing phylogenetic hypotheses presented by previous classification systems. Our data reject the current order-level classification by again finding non-monophyletic Leucosolenida, Clathrinida and Murrayonida. In the subclass Calcinea, we recovered a clade that includes all species with a cortex, which is largely consistent with the previously proposed order Leucettida. Other orders that had been rejected in the current system were not found, but could not be rejected in our tests either. We found several additional families and genera polyphyletic: the families Leucascidae and Leucaltidae and the genus Leucetta in Calcinea, and in Calcaronea the family Amphoriscidae and the genus Ute. Our phylogeny also provided support for the vaguely suspected close relationship of several members of Grantiidae with giantortical diactines to members of Heteropiidae. Similarly, our analyses revealed several unexpected affinities, such as a sister group relationship between Leucettusa (Leucaltidae and Leucettidae and between Leucascandra (Jenkinidae and Sycon carteri (Sycettidae. According to our results, the taxonomy of Calcarea is in

  16. Molecular phylogenetic evaluation of classification and scenarios of character evolution in calcareous sponges (Porifera, Class Calcarea).

    Voigt, Oliver; Wülfing, Eilika; Wörheide, Gert

    2012-01-01

    Calcareous sponges (Phylum Porifera, Class Calcarea) are known to be taxonomically difficult. Previous molecular studies have revealed many discrepancies between classically recognized taxa and the observed relationships at the order, family and genus levels; these inconsistencies question underlying hypotheses regarding the evolution of certain morphological characters. Therefore, we extended the available taxa and character set by sequencing the complete small subunit (SSU) rDNA and the almost complete large subunit (LSU) rDNA of additional key species and complemented this dataset by substantially increasing the length of available LSU sequences. Phylogenetic analyses provided new hypotheses about the relationships of Calcarea and about the evolution of certain morphological characters. We tested our phylogeny against competing phylogenetic hypotheses presented by previous classification systems. Our data reject the current order-level classification by again finding non-monophyletic Leucosolenida, Clathrinida and Murrayonida. In the subclass Calcinea, we recovered a clade that includes all species with a cortex, which is largely consistent with the previously proposed order Leucettida. Other orders that had been rejected in the current system were not found, but could not be rejected in our tests either. We found several additional families and genera polyphyletic: the families Leucascidae and Leucaltidae and the genus Leucetta in Calcinea, and in Calcaronea the family Amphoriscidae and the genus Ute. Our phylogeny also provided support for the vaguely suspected close relationship of several members of Grantiidae with giantortical diactines to members of Heteropiidae. Similarly, our analyses revealed several unexpected affinities, such as a sister group relationship between Leucettusa (Leucaltidae) and Leucettidae and between Leucascandra (Jenkinidae) and Sycon carteri (Sycettidae). According to our results, the taxonomy of Calcarea is in desperate need of a

  17. Molecular classification and prognostication of 300 node-negative breast cancer cases: A tertiary care experience

    Shemin, K. M. Zuhara; Smitha, N. V.; Jojo, Annie; Vijaykumar, D. K.

    2015-01-01

    Background: The proportion of node-negative breast cancer patients has been increasing with improvement of diagnostic modalities and early detection. However, there is a 20–30% recurrence in node-negative breast cancers. Determining who should receive adjuvant therapy is challenging, as the majority are cured by surgery alone. Hence, it requires further stratification using additional prognostic and predictive factors. Subjects and Methods: Ours is a single institution retrospective study, on 300 node-negative breast cancer cases, who underwent primary surgery over a period of 7 years (2005–2011). We excluded all cases who took NACT. Prognostic factors of age, size, lymphovascular emboli, estrogen receptor (ER), progesterone receptor (PR), HER2neu Ki-67, grade and molecular classification were analyzed with respect to those with and without early events (recurrence, metastases or second malignancy, death) using-Pearson Chi-square method and logistic regression method for statistical analysis. Results: Majority belonged to the age group of 50–70 years. On univariate analysis, size >5 cm (P = 0.03) and ER negativity had significant association (P = 0.05) for early failures; PR negativity and lymphovascular emboli (LVE) had borderline significance (P = 0.07). Multivariate analysis showed size >5 cm to be significant (P = 0.04) and LVE positivity showed borderline significant association (P = 0.07) with early failures. About 62% belonged to luminal category followed by basal-like (25%) in molecular classification. Conclusions: ER negativity, PR negativity, LVE/lymphovascular invasion positivity and size >5 cm (T3 and T4) are associated with poor prognosis in node-negative breast cancers. PMID:26981506

  18. Molecular classification and prognostication of 300 node-negative breast cancer cases: A tertiary care experience

    K M Zuhara Shemin

    2015-01-01

    Full Text Available Background: The proportion of node-negative breast cancer patients has been increasing with improvement of diagnostic modalities and early detection. However, there is a 20-30% recurrence in node-negative breast cancers. Determining who should receive adjuvant therapy is challenging, as the majority are cured by surgery alone. Hence, it requires further stratification using additional prognostic and predictive factors. Subjects and Methods: Ours is a single institution retrospective study, on 300 node-negative breast cancer cases, who underwent primary surgery over a period of 7 years (2005-2011. We excluded all cases who took NACT. Prognostic factors of age, size, lymphovascular emboli, estrogen receptor (ER, progesterone receptor (PR, HER2neu Ki-67, grade and molecular classification were analyzed with respect to those with and without early events (recurrence, metastases or second malignancy, death using-Pearson Chi-square method and logistic regression method for statistical analysis. Results: Majority belonged to the age group of 50-70 years. On univariate analysis, size >5 cm (P = 0.03 and ER negativity had significant association (P = 0.05 for early failures; PR negativity and lymphovascular emboli (LVE had borderline significance (P = 0.07. Multivariate analysis showed size >5 cm to be significant (P = 0.04 and LVE positivity showed borderline significant association (P = 0.07 with early failures. About 62% belonged to luminal category followed by basal-like (25% in molecular classification. Conclusions: ER negativity, PR negativity, LVE/lymphovascular invasion positivity and size >5 cm (T3 and T4 are associated with poor prognosis in node-negative breast cancers.

  19. Nonlinear Optical Properties of Fluorescent Dyes Allow for Accurate Determination of Their Molecular Orientations in Phospholipid Membranes.

    Timr, Štěpán; Brabec, Jiří; Bondar, Alexey; Ryba, Tomáš; Železný, Miloš; Lazar, Josef; Jungwirth, Pavel

    2015-07-30

    Several methods based on single- and two-photon fluorescence detected linear dichroism have recently been used to determine the orientational distributions of fluorescent dyes in lipid membranes. However, these determinations relied on simplified descriptions of nonlinear anisotropic properties of the dye molecules, using a transition dipole-moment-like vector instead of an absorptivity tensor. To investigate the validity of the vector approximation, we have now carried out a combination of computer simulations and polarization microscopy experiments on two representative fluorescent dyes (DiI and F2N12S) embedded in aqueous phosphatidylcholine bilayers. Our results indicate that a simplified vector-like treatment of the two-photon transition tensor is applicable for molecular geometries sampled in the membrane at ambient conditions. Furthermore, our results allow evaluation of several distinct polarization microscopy techniques. In combination, our results point to a robust and accurate experimental and computational treatment of orientational distributions of DiI, F2N12S, and related dyes (including Cy3, Cy5, and others), with implications to monitoring physiologically relevant processes in cellular membranes in a novel way. PMID:26146848

  20. Accurate molecular van der Waals interactions from ground-state electron density and free-atom reference data

    Tkatchenko, A.; Scheffler, M.

    2009-01-01

    We present a parameter-free method for an accurate determination of long-range van der Waals interactions from mean-field electronic structure calculations. Our method relies on the summation of interatomic C6 coefficients, derived from the electron density of a molecule or solid and accurate reference data for the free atoms. The mean absolute error in the C6 coefficients is 5.5% when compared to accurate experimental values for 1225 intermolecular pairs, irrespective of the employed exchang...

  1. Immunohistochemical Expression of Survivin in Breast Carcinoma: Relationship with Clinico pathological Parameters, Proliferation and Molecular Classification

    Background and Objective: Survivin is a novel member of the inhibitor of apoptosis (IAP) gene family. It is associated with more aggressive behavior and parameters of poor prognosis in most human cancers including gastric, colorectal and bladder carcinomas. However, conflicting data exist on its prognostic effect in breast cancer. This current study is designed to assess survivin expression in breast carcinoma relating results with clinico pathological parameters, proliferation (MIB-1) and molecular classification. Material and Methods: Our retrospective study com- prised of 65 archived cases of breast carcinoma. Samples from the tumor and the adjacent normal breast tissue were immuno stained for survivin and MIB-1. Nuclear and cytoplasmic survivin expression was evaluated in normal breast tissue and carcinoma regarding both the intensity and the percentage of positive cells. ER, PR, HER2 were used as surrogate markers to classify the cases into four molecular subtypes. Results: Survivin expression was detected in 78.5% of breast carcinomas. The adjacent normal breast tissue was immuno negative. Survivin expression showed significant association with increased tumor size ( p <0.0001), high histologic grade ( p =0.04), lymph node metastases ( p <0.001), advanced tumor stage ( p <0.0001), MIB-1 expression ( p =0.02), negative estrogen receptor status ( p =0.01) and negative progesterone receptor status ( p <0.0001). The subcellular localization of survivin significantly related to histologic grade, stage and lymph node involvement. The percentage of TNP (triple negative phenotype) and HER2+/ER-PR- tumors expressing survivin were significantly higher compared to the Luminal subtypes ( p =0.01). Conclusion: Survivin expression was associated with parameters of poor prognosis in breast cancer. Moreover, the cancer-specific expression of survivin, coupled with its importance in inhibiting cell death and in regulating cell division, makes it a potential target for novel

  2. Reconciling molecular phylogeny, morphological divergence and classification of Madagascan narrow-mouthed frogs (Amphibia: Microhylidae).

    Scherz, Mark D; Vences, Miguel; Rakotoarison, Andolalao; Andreone, Franco; Köhler, Jörn; Glaw, Frank; Crottini, Angelica

    2016-07-01

    A recent study clarified several aspects of microhylid phylogeny by combining DNA sequences from Sanger sequencing and anchored phylogenomics, although numerous aspects of tree topology proved highly susceptible to data partition and chosen model. Although the phylogenetic results of the study were in conflict with previous publications, the authors made several changes to the taxonomy of Madagascar's cophyline microhylids. We re-analyzed part of their data together with our own molecular and morphological data. Based on a supermatrix of 11 loci, we propose a new phylogeny of the Cophylinae, and discuss it in the context of a newly generated osteological dataset. We found several sample misidentifications, partially explaining their deviant results, and propose to resurrect the genera Platypelis and Stumpffia from the synonymy of Cophyla and Rhombophryne, respectively. We provide support for the previous genus-level taxonomy of this subfamily, and erect a new genus, Anilany gen. nov., in order to eliminate paraphyly of Stumpffia and to account for the osteological differences observed among these groups. Deep nodes in our phylogeny remain poorly supported, and future works will certainly refine our classification, but we are confident that these will not produce large-scale rearrangements. PMID:27085671

  3. Molecular phylogeny of the families Pleuronectidae and Poecilopsettidae (PISCES, Pleuronectiformes) from Korea, with a Proposal for a new classification

    Ji, Hwan-Sung; Kim, Jin-Koo; Kim, Byung-Jik

    2016-03-01

    A new classification of the Korean pleuronectids was proposed based on a molecular phylogeny using specimens collected from Korea (including some Japanese specimens) between 2008 and 2013. A molecular phylogeny based on partial sequences of the two mitochondrial DNA regions (COI and 16S rRNA) supported the reciprocal monophyly of the three genera, Cleisthenes, Pleuronectes and Pseudopleuronectes. We also found that the genus Poecilopsetta is clearly distinct from Pleuronectidae at the family level. Therefore, the previous classification of the Korean pleuronectids should be changed as follows; two families (Pleuronectidae and Poecilopsettidae), 18 genera, and 26 species. Further research is required to resolve the taxonomic uncertainty of the five species in the genus Limanda, which clustered into two clades in our analysis.

  4. A Molecular Phylogeny for the Leaf-Roller Moths (Lepidoptera: Tortricidae) and Its Implications for Classification and Life History Evolution

    Regier, Jerome C; John W. Brown; Mitter, Charles; Baixeras, Joaquín; Cho, Soowon; Cummings, Michael P.; Zwick, Andreas

    2012-01-01

    Background Tortricidae, one of the largest families of microlepidopterans, comprise about 10,000 described species worldwide, including important pests, biological control agents and experimental models. Understanding of tortricid phylogeny, the basis for a predictive classification, is currently provisional. We present the first detailed molecular estimate of relationships across the tribes and subfamilies of Tortricidae, assess its concordance with previous morphological evidence, and re-ex...

  5. Pharmacological Classification and Activity Evaluation of Furan and Thiophene Amide Derivatives Applying Semi-Empirical ab initio Molecular Modeling Methods

    Leszek Bober; Tomasz Baczek; Piotr Kawczak

    2012-01-01

    Pharmacological and physicochemical classification of the furan and thiophene amide derivatives by multiple regression analysis and partial least square (PLS) based on semi-empirical ab initio molecular modeling studies and high-performance liquid chromatography (HPLC) retention data is proposed. Structural parameters obtained from the PCM (Polarizable Continuum Model) method and the literature values of biological activity (antiproliferative for the A431 cells) expressed...

  6. The classification of gene products in the molecular biology domain: Realism, objectivity, and the limitations of the Gene Ontology

    Mayor, Charlie

    2012-01-01

    Background: Controlled vocabularies in the molecular biology domain exist to facilitate data integration across database resources. One such tool is the Gene Ontology (GO), a classification designed to act as a universal index for gene products from any species. The Gene Ontology is used extensively in annotating gene products and analysing gene expression data, yet very little research exists from a library and information science perspective exploring the design principles, philosophy and s...

  7. Molecular Classification of Pesticides Including Persistent Organic Pollutants, Phenylurea and Sulphonylurea Herbicides

    Francisco Torrens

    2014-06-01

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

  8. Rapid and accurate taxonomic classification of insect (class Insecta) cytochrome c oxidase subunit 1 (COI) DNA barcode sequences using a naïve Bayesian classifier

    Porter, Teresita M.; Gibson, Joel F; Shokralla, Shadi; Baird, Donald J.; Golding, G. Brian; Hajibabaei, Mehrdad

    2014-01-01

    Current methods to identify unknown insect (class Insecta) cytochrome c oxidase (COI barcode) sequences often rely on thresholds of distances that can be difficult to define, sequence similarity cut-offs, or monophyly. Some of the most commonly used metagenomic classification methods do not provide a measure of confidence for the taxonomic assignments they provide. The aim of this study was to use a naïve Bayesian classifier (Wang et al. Applied and Environmental Microbiology, 2007; 73: 5261)...

  9. A preliminary phylogeny of the 'didymocarpoid Gesneriaceae' based on three molecular data sets: Incongruence with available tribal classifications.

    Möller, Michael; Pfosser, Martin; Jang, Chang-Gee; Mayer, Veronika; Clark, Alexandra; Hollingsworth, Michelle L; Barfuss, Michael H J; Wang, Yin-Zheng; Kiehn, Michael; Weber, Anton

    2009-05-01

    The 'didymocarpoid Gesneriaceae' (traditional subfam. Cyrtandroideae excluding Epithemateae) are the largest group of Old World Gesneriaceae, comprising 85 genera and 1800 species. We attempt to resolve their hitherto poorly understood generic relationships using three molecular markers on 145 species, of which 128 belong to didymocarpoid Gesneriaceae. Our analyses demonstrate that consistent topological relationships can be retrieved from data sets with missing data using subsamples and different combinations of gene sequences. We show that all available classifications in Old World Gesneriaceae are artificial and do not reflect natural relationships. At the base of the didymocarpoids are grades of clades comprising isolated genera and small groups from Asia and Europe. These are followed by a clade comprising the African and Madagascan genera. The remaining clades represent the advanced Asiatic and Malesian genera. They include a major group with mostly twisted capsules. The much larger group of remaining genera comprises exclusively genera with straight capsules and the huge genus Cyrtandra with indehiscent fruits. Several genera such as Briggsia, Henckelia, and Chirita are not monophyletic; Chirita is even distributed throughout five clades. This degree of incongruence between molecular phylogenies, traditional classifications, and generic delimitations indicates the problems with classifications based on, sometimes a single, morphological characters. PMID:21628251

  10. Nonlinear Optical Properties of Fluorescent Dyes Allow for Accurate Determination of Their Molecular Orientations in Phospholipid Membranes

    Timr, Štěpán; Brabec, J.; Bondar, Alexey; Ryba, T.; Železný, M.; Lazar, Josef; Jungwirth, Pavel

    2015-01-01

    Roč. 119, č. 30 (2015), s. 9706-9716. ISSN 1520-6106 R&D Projects: GA ČR GA13-06181S; GA ČR GA13-10799S Grant ostatní: GA MŠk(CZ) LO1506 Institutional support: RVO:61388963 ; RVO:67179843 Keywords : two-photon polarization microscopy * molecular orientation * absorptivity tensor Subject RIV: CF - Physical ; Theoretical Chemistry ; CE - Biochemistry (UEK-B) Impact factor: 3.302, year: 2014

  11. Molecular classification of melanomas and nevi using gene expression microarray signatures and formalin-fixed and paraffin-embedded tissue.

    Koh, Stephen S; Opel, Michael L; Wei, Jia-Perng J; Yau, Kenneth; Shah, Rashmi; Gorre, Mercedes E; Whitman, Eric; Shitabata, Paul K; Tao, Yong; Cochran, Alistair J; Abrishami, Payam; Binder, Scott W

    2009-04-01

    Melanoma may be difficult to identify histologically and relatively high rates of misdiagnosis leads to many malpractice claims. Currently separation of melanomas from nevi is based primarily on light microscopic interpretation of hematoxylin and eosin stained sections with limited assistance from immunohistology. To increase the accuracy of discrimination of benign and malignant melanocytic lesions we identified DNA microarray-derived gene expression profiles of different melanocytic lesions and evaluated the performance of these gene signatures as molecular diagnostic tools in the molecular classification and separation of melanomas and nevi. Melanocyte-derived cells were isolated by laser capture microdissection from 165 formalin-fixed and paraffin-embedded melanocytic nevi and melanoma tissue sections. RNA was isolated, amplified, labeled, and hybridized to a custom DNA microarray. In all 120 samples were used to identify differentially expressed genes and generate a gene expression classifier capable of distinguishing between melanomas and nevi. These classifiers were tested by the leave-one-out method and in a blinded study. RT-PCR verified the results. Unsupervised hierarchical clustering identified two distinct lesional groups that closely correlated with the histopathologically identified melanomas and nevi. Analysis of gene expression levels identified 36 significant differentially expressed genes. In comparison with nevi, melanomas expressed higher levels of genes promoting signal transduction, transcription, and cell growth. In contrast, expression of L1CAM (homolog) was reduced in melanomas relative to nevi. Genes differentially expressed in melanomas and nevi, on the basis of molecular signal, sub classified a group of unknown melanocytic lesions as melanomas or nevi and had high concordance rates with histopathology. Gene signatures established using DNA microarray gene expression profiling can distinguish melanomas from nevi, indicating the

  12. An accurate and scalable O(N) algorithm for First-Principles Molecular Dynamics computations on petascale computers and beyond

    Osei-Kuffuor, Daniel; Fattebert, Jean-Luc

    2014-03-01

    We present a truly scalable First-Principles Molecular Dynamics algorithm with O(N) complexity and fully controllable accuracy, capable of simulating systems of sizes that were previously impossible with this degree of accuracy. By avoiding global communication, we have extended W. Kohn's condensed matter ``nearsightedness'' principle to a practical computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic wavefunctions are confined, and a cutoff beyond which the components of the overlap matrix can be omitted when computing selected elements of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to 100,000 atoms on 100,000 processors, with a wall-clock time of the order of one minute per molecular dynamics time step. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  13. ICGA-PSO-ELM approach for accurate multiclass cancer classification resulting in reduced gene sets in which genes encoding secreted proteins are highly represented.

    Saraswathi, Saras; Sundaram, Suresh; Sundararajan, Narasimhan; Zimmermann, Michael; Nilsen-Hamilton, Marit

    2011-01-01

    A combination of Integer-Coded Genetic Algorithm (ICGA) and Particle Swarm Optimization (PSO), coupled with the neural-network-based Extreme Learning Machine (ELM), is used for gene selection and cancer classification. ICGA is used with PSO-ELM to select an optimal set of genes, which is then used to build a classifier to develop an algorithm (ICGA_PSO_ELM) that can handle sparse data and sample imbalance. We evaluate the performance of ICGA-PSO-ELM and compare our results with existing methods in the literature. An investigation into the functions of the selected genes, using a systems biology approach, revealed that many of the identified genes are involved in cell signaling and proliferation. An analysis of these gene sets shows a larger representation of genes that encode secreted proteins than found in randomly selected gene sets. Secreted proteins constitute a major means by which cells interact with their surroundings. Mounting biological evidence has identified the tumor microenvironment as a critical factor that determines tumor survival and growth. Thus, the genes identified by this study that encode secreted proteins might provide important insights to the nature of the critical biological features in the microenvironment of each tumor type that allow these cells to thrive and proliferate. PMID:21233525

  14. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

    Hoadley, Katherine A; Yau, Christina; Wolf, Denise M;

    2014-01-01

    on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset......Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform...... of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides...

  15. Photometric brown-dwarf classification. II. A homogeneous sample of 1361 L and T dwarfs brighter than J = 17.5 with accurate spectral types

    Skrzypek, N.; Warren, S. J.; Faherty, J. K.

    2016-04-01

    We present a homogeneous sample of 1361 L and T dwarfs brighter than J = 17.5 (of which 998 are new), from an effective area of 3070 deg2, classified by the photo-type method to an accuracy of one spectral sub-type using izYJHKW1W2 photometry from SDSS+UKIDSS+WISE. Other than a small bias in the early L types, the sample is shown to be effectively complete to the magnitude limit, for all spectral types L0 to T8. The nature of the bias is an incompleteness estimated at 3% because peculiar blue L dwarfs of type L4 and earlier are classified late M. There is a corresponding overcompleteness because peculiar red (likely young) late M dwarfs are classified early L. Contamination of the sample is confirmed to be small: so far spectroscopy has been obtained for 19 sources in the catalogue and all are confirmed to be ultracool dwarfs. We provide coordinates and izYJHKW1W2 photometry of all sources. We identify an apparent discontinuity, Δm ~ 0.4 mag, in the Y - K colour between spectral types L7 and L8. We present near-infrared spectra of nine sources identified by photo-type as peculiar, including a new low-gravity source ULAS J005505.68+013436.0, with spectroscopic classification L2γ. We provide revised izYJHKW1W2 template colours for late M dwarfs, types M7 to M9. The catalogue is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/589/A49

  16. The need for improved identification and accurate classification of stages 3-5 Chronic Kidney Disease in primary care: retrospective cohort study.

    Poorva Jain

    Full Text Available BACKGROUND: Around ten percent of the population have been reported as having Chronic Kidney Disease (CKD, which is associated with increased cardiovascular mortality. Few previous studies have ascertained the chronicity of CKD. In the UK, a payment for performance (P4P initiative incentivizes CKD (stages 3-5 recognition and management in primary care, but the impact of this has not been assessed. METHODS AND FINDINGS: Using data from 426 primary care practices (population 2,707,130, the age standardised prevalence of stages 3-5 CKD was identified using two consecutive estimated Glomerular Filtration Rates (eGFRs seven days apart. Additionally the accuracy of practice CKD registers and the relationship between accurate identification of CKD and the achievement of P4P indicators was determined. Between 2005 and 2009, the prevalence of stages 3-5 CKD increased from 0.3% to 3.9%. In 2009, 30,440 patients (1.1% unadjusted fulfilled biochemical criteria for CKD but were not on a practice CKD register (uncoded CKD and 60,705 patients (2.2% unadjusted were included on a practice CKD register but did not fulfil biochemical criteria (miscoded CKD. For patients with confirmed CKD, inclusion in a practice register was associated with increasing age, male sex, diabetes, hypertension, cardiovascular disease and increasing CKD stage (p<0.0001. Uncoded CKD patients compared to miscoded patients were less likely to achieve performance indicators for blood pressure (OR 0.84, 95% CI 0.82-0.86 p<0.001 or recorded albumin-creatinine ratio (OR 0.73, 0.70-0.76, p<0.001. CONCLUSIONS: The prevalence of stages 3-5 CKD, using two laboratory reported eGFRs, was lower than estimates from previous studies. Clinically significant discrepancies were identified between biochemically defined CKD and appearance on practice registers, with misclassification associated with sub-optimal care for some people with CKD.

  17. A new classification of viviparous brotulas (Bythitidae) - with family status for Dinematichthyidae - based on molecular, morphological and fossil data.

    Møller, Peter Rask; Knudsen, Steen Wilhelm; Schwarzhans, Werner; Nielsen, Jørgen G

    2016-07-01

    The order Ophidiiformes is a large but not very well known group of fishes, unique among teleosts for showing high diversity in both deep sea and shallow reef habitats. The current classification includes more than 500 species, 115 genera and four families, based primarily on mode of reproduction: viviparous Aphyonidae and Bythitidae vs oviparous Carapidae and Ophidiidae. Since 2004 we revised the bythitid tribe Dinematichthyini, described more than 100 new species and noticed that this group has unique morphological characters, perhaps supporting a higher level of classification than the current status. Here we study the viviparous families phylogenetically with partial mitochondrial (nd4, 16s) and nuclear (Rag1) DNA sequences (2194bp). We use a fossil calibration of otolith-based taxa to calibrate the age of the clade comprising bythitid and dinematicththyid representatives, together with fossil calibrations adopted from previous phylogenetic studies. The separation of the order into two major lineages, the viviparous Bythitoidei and the oviparous Ophidioidei is confirmed. At the familial level, however, a new classification is presented for the viviparous clades, placing Aphyonidae as a derived, pedomorphic member of Bythitidae (new diagnosis provided, 33 genera and 118 species). The current subfamily Brosmophycinae is considered polyphyletic and we propose family status for Dinematichthyidae (25 genera, 114 species), supported by unique, morphological synapomorphic characters in the male copulatory apparatus. Previous use of the caudal fin separation or fusion with vertical fins is ambiguous. Age estimates based on calibrated molecular phylogeny agrees with fossil data, giving an origin within the Cretaceous (between 84 and 104mya) for a common ancestor to Ophidiiformes. PMID:27060424

  18. A Molecular Predictor Reassesses Classification of Human Grade II/III Gliomas.

    Thierry Rème

    Full Text Available Diffuse gliomas are incurable brain tumors divided in 3 WHO grades (II; III; IV based on histological criteria. Grade II/III gliomas are clinically very heterogeneous and their prognosis somewhat unpredictable, preventing definition of appropriate treatment. On a cohort of 65 grade II/III glioma patients, a QPCR-based approach allowed selection of a biologically relevant gene list from which a gene signature significantly correlated to overall survival was extracted. This signature clustered the training cohort into two classes of low and high risk of progression and death, and similarly clustered two external independent test cohorts of 104 and 73 grade II/III patients. A 22-gene class predictor of the training clusters optimally distinguished poor from good prognosis patients (median survival of 13-20 months versus over 6 years in the validation cohorts. This classification was stronger at predicting outcome than the WHO grade II/III classification (P≤2.8E-10 versus 0.018. When compared to other prognosis factors (histological subtype and genetic abnormalities in a multivariate analysis, the 22-gene predictor remained significantly associated with overall survival. Early prediction of high risk patients (3% of WHO grade II, and low risk patients (29% of WHO grade III in clinical routine will allow the development of more appropriate follow-up and treatments.

  19. Communication: Rate coefficients of the H + CH4 → H2 + CH3 reaction from ring polymer molecular dynamics on a highly accurate potential energy surface

    The ring polymer molecular dynamics (RPMD) calculations are performed to calculate rate constants for the title reaction on the recently constructed potential energy surface based on permutation invariant polynomial (PIP) neural-network (NN) fitting [J. Li et al., J. Chem. Phys. 142, 204302 (2015)]. By inspecting convergence, 16 beads are used in computing free-energy barriers at 300 K ≤ T ≤ 1000 K, while different numbers of beads are used for transmission coefficients. The present RPMD rates are in excellent agreement with quantum rates computed on the same potential energy surface, as well as with the experimental measurements, demonstrating further that the RPMD is capable of producing accurate rates for polyatomic chemical reactions even at rather low temperatures

  20. Communication: Rate coefficients of the H + CH4 → H2 + CH3 reaction from ring polymer molecular dynamics on a highly accurate potential energy surface

    Meng, Qingyong; Chen, Jun; Zhang, Dong H.

    2015-09-01

    The ring polymer molecular dynamics (RPMD) calculations are performed to calculate rate constants for the title reaction on the recently constructed potential energy surface based on permutation invariant polynomial (PIP) neural-network (NN) fitting [J. Li et al., J. Chem. Phys. 142, 204302 (2015)]. By inspecting convergence, 16 beads are used in computing free-energy barriers at 300 K ≤ T ≤ 1000 K, while different numbers of beads are used for transmission coefficients. The present RPMD rates are in excellent agreement with quantum rates computed on the same potential energy surface, as well as with the experimental measurements, demonstrating further that the RPMD is capable of producing accurate rates for polyatomic chemical reactions even at rather low temperatures.

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

    Berman Jules

    2005-01-01

    Abstract Background For over 150 years, pathologists have relied on histomorphology to classify and diagnose neoplasms. Their success has been stunning, permitting the accurate diagnosis of thousands of different types of neoplasms using only a microscope and a trained eye. In the past two decades, cancer genomics has challenged the supremacy of histomorphology by identifying genetic alterations shared by morphologically diverse tumors and by finding genetic features that distinguish subgroup...

  2. Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics.

    Xu, Xiu-Qin; Leow, Chon K; Lu, Xin; Zhang, Xuegong; Liu, Jun S; Wong, Wing-Hung; Asperger, Arndt; Deininger, Sören; Eastwood Leung, Hon-Chiu

    2004-10-01

    Liver cirrhosis is a worldwide health problem. Reliable, noninvasive methods for early detection of liver cirrhosis are not available. Using a three-step approach, we classified sera from rats with liver cirrhosis following different treatment insults. The approach consisted of: (i) protein profiling using surface-enhanced laser desorption/ionization (SELDI) technology; (ii) selection of a statistically significant serum biomarker set using machine learning algorithms; and (iii) identification of selected serum biomarkers by peptide sequencing. We generated serum protein profiles from three groups of rats: (i) normal (n=8), (ii) thioacetamide-induced liver cirrhosis (n=22), and (iii) bile duct ligation-induced liver fibrosis (n=5) using a weak cation exchanger surface. Profiling data were further analyzed by a recursive support vector machine algorithm to select a panel of statistically significant biomarkers for class prediction. Sensitivity and specificity of classification using the selected protein marker set were higher than 92%. A consistently down-regulated 3495 Da protein in cirrhosis samples was one of the selected significant biomarkers. This 3495 Da protein was purified on-chip and trypsin digested. Further structural characterization of this biomarkers candidate was done by using cross-platform matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) peptide mass fingerprinting (PMF) and matrix-assisted laser desorption/ionization time of flight/time of flight (MALDI-TOF/TOF) tandem mass spectrometry (MS/MS). Combined data from PMF and MS/MS spectra of two tryptic peptides suggested that this 3495 Da protein shared homology to a histidine-rich glycoprotein. These results demonstrated a novel approach to discovery of new biomarkers for early detection of liver cirrhosis and classification of liver diseases. PMID:15378689

  3. Beyond laminar fate: toward a molecular classification of cortical projection/pyramidal neurons.

    Hevner, R.F.; Daza, R.A.; Rubenstein, J.L.; Stunnenberg, H.G.; Olavarria, J.F.; Englund, C.

    2003-01-01

    Cortical projection neurons exhibit diverse morphological, physiological, and molecular phenotypes, but it is unknown how many distinct types exist. Many projection cell phenotypes are associated with laminar fate (radial position), but each layer may also contain multiple types of projection cells.

  4. Choice of adjuvant drug therapy on the basis of the molecular classification of breast cancer

    N. S. Besova

    2014-01-01

    Molecular genetic analysis identified some biological subtypes of breast cancer (BC): luminal A, luminal B, HER2 positive, and basal-like (including triple negative). The surrogate clinical and morphological criteria including the immunohistochemical determination of estrogen and progesterone receptors, the hyperexpression and/or amplification of HER2, Ki-67, or tumor grade (G) are used to identify the biological subtypes of BC in clinical practice. The biological subtypes are distinguished b...

  5. Molecular phylogenetic evaluation of classification and scenarios of character evolution in calcareous sponges (Porifera, Class Calcarea).

    Oliver Voigt; Eilika Wülfing; Gert Wörheide

    2012-01-01

    Calcareous sponges (Phylum Porifera, Class Calcarea) are known to be taxonomically difficult. Previous molecular studies have revealed many discrepancies between classically recognized taxa and the observed relationships at the order, family and genus levels; these inconsistencies question underlying hypotheses regarding the evolution of certain morphological characters. Therefore, we extended the available taxa and character set by sequencing the complete small subunit (SSU) rDNA and the alm...

  6. Molecular classification and pharmacogenetics of primary plasma cell leukemia: an initial approach toward precision medicine

    Vittorio Simeon; Katia Todoerti; Francesco La Rocca; Antonella Caivano; Stefania Trino; Marta Lionetti; Luca Agnelli; Luciana De Luca; Ilaria Laurenzana; Antonino Neri; Pellegrino Musto

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, ...

  7. Ontological realism, concepts and classification in molecular biology: Development and application of the gene ontology

    Mayor, C.; Robinson, L.

    2014-01-01

    Purpose – The purpose of this article is to evaluate the development and use of the gene ontology (GO), a scientific vocabulary widely used in molecular biology databases, with particular reference to the relation between the theoretical basis of the GO, and the pragmatics of its application. Design/methodology/approach – The study uses a combination of bibliometric analysis, content analysis and discourse analysis. These analyses focus on details of the ways in which the terms of the ont...

  8. [Systematic classification and community research techniques of arbuscular mycorrhizal fungi: a review].

    Liu, Yong-Jun; Feng, Hu-Yuan

    2010-06-01

    Arbuscular mycorrhizal fungi (AMF) are an important component of natural ecosystem, being able to form symbiont with plant roots. The traditional AMF classification is mainly based on the morphological identification of soil asexual spores, which has some limitations in the taxonomy of AMF. Advanced molecular techniques make the classification of AMF more accurate and scientific, and can improve the taxonomy of AMF established on the basis of morphological identification. The community research of AMF is mainly based on species classification, and has two kinds of investigation methods, i. e., spores morphological identification and molecular analysis. This paper reviewed the research progress in the systematic classification and community research techniques of AMF, with the focus on the molecular techniques in community analysis of AMF. It was considered that using morphological and molecular methods together would redound to the accurate investigation of AMF community, and also, facilitate the improvement of AMF taxonomy. PMID:20873637

  9. Non-sentinel lymph node metastasis prediction in breast cancer with metastatic sentinel lymph node: impact of molecular subtypes classification.

    Fabien Reyal

    Full Text Available INTRODUCTION: To decipher the interaction between the molecular subtype classification and the probability of a non-sentinel node metastasis in breast cancer patients with a metastatic sentinel lymph-node, we applied two validated predictors (Tenon Score and MSKCC Nomogram on two large independent datasets. MATERIALS AND METHODS: Our datasets consisted of 656 and 574 early-stage breast cancer patients with a metastatic sentinel lymph-node biopsy treated at first by surgery. We applied both predictors on the whole dataset and on each molecular immune-phenotype subgroups. The performances of the two predictors were analyzed in terms of discrimination and calibration. Probability of non-sentinel lymph node metastasis was detailed for each molecular subtype. RESULTS: Similar results were obtained with both predictors. We showed that the performance in terms of discrimination was as expected in ER Positive HER2 negative subgroup in both datasets (MSKCC AUC Dataset 1 = 0.73 [0.69-0.78], MSKCC AUC Dataset 2 = 0.71 (0.65-0.76, Tenon Score AUC Dataset 1 = 0.7 (0.65-0.75, Tenon Score AUC Dataset 2 = 0.72 (0.66-0.76. Probability of non-sentinel node metastatic involvement was slightly under-estimated. Contradictory results were obtained in other subgroups (ER negative HER2 negative, HER2 positive subgroups in both datasets probably due to a small sample size issue. We showed that merging the two datasets shifted the performance close to the ER positive HER2 negative subgroup. DISCUSSION: We showed that validated predictors like the Tenon Score or the MSKCC nomogram built on heterogeneous population of breast cancer performed equally on the different subgroups analyzed. Our present study re-enforce the idea that performing subgroup analysis of such predictors within less than 200 samples subgroup is at major risk of misleading conclusions.

  10. Deceptive desmas: molecular phylogenetics suggests a new classification and uncovers convergent evolution of lithistid demosponges.

    Astrid Schuster

    Full Text Available Reconciling the fossil record with molecular phylogenies to enhance the understanding of animal evolution is a challenging task, especially for taxa with a mostly poor fossil record, such as sponges (Porifera. 'Lithistida', a polyphyletic group of recent and fossil sponges, are an exception as they provide the richest fossil record among demosponges. Lithistids, currently encompassing 13 families, 41 genera and >300 recent species, are defined by the common possession of peculiar siliceous spicules (desmas that characteristically form rigid articulated skeletons. Their phylogenetic relationships are to a large extent unresolved and there has been no (taxonomically comprehensive analysis to formally reallocate lithistid taxa to their closest relatives. This study, based on the most comprehensive molecular and morphological investigation of 'lithistid' demosponges to date, corroborates some previous weakly-supported hypotheses, and provides novel insights into the evolutionary relationships of the previous 'order Lithistida'. Based on molecular data (partial mtDNA CO1 and 28S rDNA sequences, we show that 8 out of 13 'Lithistida' families belong to the order Astrophorida, whereas Scleritodermidae and Siphonidiidae form a separate monophyletic clade within Tetractinellida. Most lithistid astrophorids are dispersed between different clades of the Astrophorida and we propose to formally reallocate them, respectively. Corallistidae, Theonellidae and Phymatellidae are monophyletic, whereas the families Pleromidae and Scleritodermidae are polyphyletic. Family Desmanthidae is polyphyletic and groups within Halichondriidae--we formally propose a reallocation. The sister group relationship of the family Vetulinidae to Spongillida is confirmed and we propose here for the first time to include Vetulina into a new Order Sphaerocladina. Megascleres and microscleres possibly evolved and/or were lost several times independently in different 'lithistid' taxa, and

  11. Molecular identification and classification of Trichophyton mentagrophytes complex strains isolated from humans and selected animal species.

    Ziółkowska, Grażyna; Nowakiewicz, Aneta; Gnat, Sebastian; Trościańczyk, Aleksandra; Zięba, Przemysław; Dziedzic, Barbara Majer

    2015-03-01

    Species differentiation within Trichophyton mentagrophytes complex group currently poses a major diagnostic challenge, with molecular methods increasingly supplementing classical identification based on the morphological and physiological properties of the fungi. Diagnostic and epidemiological research aimed at determining the source and means of transmission of dermatophytoses in both humans and animals requires not only species differentiation of isolates but also differentiation within species. The study was conducted on 24 isolates originating in humans and various animal species with clinical symptoms of dermatophytosis. The analysis included phenotypical identification methods and molecular methods: internal transcribed spacer sequencing and ITS-restriction fragment length polymorphism (RFLP) with multi-enzyme restriction. ITS sequence analysis identified the isolates to species - Trichophyton interdigitale, Arthroderma benhamiae and A. vanbreuseghemii, and ITS-RFLP detected six different genotypes. Genotypes I, II and III characterised strains belonging to A. benhamiae, genotype IV characterised the A. vanbreuseghemii strain, and genotypes V and VI occurred only within the species T. interdigitale. Strains isolated from guinea pigs were dominant within genotype I, while genotype II was found mainly in strains from foxes. Multi-enzyme restriction analysis of this region enables intraspecific differentiation, which may be useful in epidemiological research, particularly in determining the source of infections. PMID:25643744

  12. Molecular Phylogenetic Classification of Streptomycetes Isolated from the Rhizosphere of Tropical Legume (Paraserianthes falcataria (L. Nielsen

    LANGKAH SEMBIRING

    2009-09-01

    Full Text Available Intrageneric diversity of 556 streptomycetes isolated from the rhizosphere of tropical legume was determined by using molecular taxonomic method based on 16S rDNA. A total of 46 isolates were taken to represent 37 colour groups of the isolates. 16S rDNA were amplified and subsequently sequenced and the sequences data were aligned with streptomycete sequences retrieved from the ribosomal data base project (RDP data. Phylogenetic trees were generated by using the PHYLIP software package and the matrix of nucleotide similarity and nucleotide difference were generated by using PHYDIT software. The results confirmed and extended the value of 16S rDNA sequencing in streptomycete systematic. The 16S rDNA sequence data showed that most of the tested colour group representatives formed new centers of taxonomic variation within the genus Streptomyces. The generic assignment of these organisms was underpinned by 16S rDNA sequence data which also suggested that most of the strains represented new centers of taxonomic variation. The taxonomic data indicate that diverse populations of streptomycetes are associated with the roots of tropical legume (P. falcataria. Therefore, the combination of selective isolation and molecular taxonomic procedures used in this study provide a powerful way of uncovering new centers of taxonomic variation within the genus Streptomyces.

  13. Molecular profiling of liver tumors: classification and clinical translation for decision making.

    Pinyol, Roser; Nault, Jean Charles; Quetglas, Iris M; Zucman-Rossi, Jessica; Llovet, Josep M

    2014-11-01

    Hepatocellular carcinoma (HCC) is a complex disease with a dismal prognosis. Consequently, a translational approach is required to personalized clinical decision making to improve survival of HCC patients. Molecular signatures from cirrhotic livers and single nucleotide polymorphism have been linked with HCC occurrence. Identification of high-risk populations will be useful to design chemopreventive trials. In addition, molecular signatures derived from tumor and nontumor samples are associated with early tumor recurrence due to metastasis and late tumor recurrence due to de novo carcinogenesis after curative treatment, respectively. Identification of patients with a high risk of relapse will guide adjuvant randomized trials. The genetic landscape drawn by next-generation sequencing has highlighted the genomic diversity of HCC. Genetic drivers recurrently mutated belong to different signaling pathways including telomere maintenance, cell-cycle regulators, chromatin remodeling, Wnt/b-catenin, RAS/RAF/MAPK kinase, and AKT/mTOR pathway. These cancer genes will be ideally targeted by biotherapies as a paradigm of stratified medicine adapted to tumor biology. PMID:25369299

  14. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine

    Vittorio Simeon

    2015-07-01

    Full Text Available Primary plasma cell leukemia (pPCL is a rare and aggressive variant of multiple myeloma (MM which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL.

  15. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine.

    Simeon, Vittorio; Todoerti, Katia; La Rocca, Francesco; Caivano, Antonella; Trino, Stefania; Lionetti, Marta; Agnelli, Luca; De Luca, Luciana; Laurenzana, Ilaria; Neri, Antonino; Musto, Pellegrino

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL). PMID:26263974

  16. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine

    Simeon, Vittorio; Todoerti, Katia; La Rocca, Francesco; Caivano, Antonella; Trino, Stefania; Lionetti, Marta; Agnelli, Luca; De Luca, Luciana; Laurenzana, Ilaria; Neri, Antonino; Musto, Pellegrino

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL). PMID:26263974

  17. Ring polymer molecular dynamics fast computation of rate coefficients on accurate potential energy surfaces in local configuration space: Application to the abstraction of hydrogen from methane

    Meng, Qingyong; Chen, Jun; Zhang, Dong H.

    2016-04-01

    To fast and accurately compute rate coefficients of the H/D + CH4 → H2/HD + CH3 reactions, we propose a segmented strategy for fitting suitable potential energy surface (PES), on which ring-polymer molecular dynamics (RPMD) simulations are performed. On the basis of recently developed permutation invariant polynomial neural-network approach [J. Li et al., J. Chem. Phys. 142, 204302 (2015)], PESs in local configuration spaces are constructed. In this strategy, global PES is divided into three parts, including asymptotic, intermediate, and interaction parts, along the reaction coordinate. Since less fitting parameters are involved in the local PESs, the computational efficiency for operating the PES routine is largely enhanced by a factor of ˜20, comparing with that for global PES. On interaction part, the RPMD computational time for the transmission coefficient can be further efficiently reduced by cutting off the redundant part of the child trajectories. For H + CH4, good agreements among the present RPMD rates and those from previous simulations as well as experimental results are found. For D + CH4, on the other hand, qualitative agreement between present RPMD and experimental results is predicted.

  18. Comparing implementations of magnetic-resonance-guided fluorescence molecular tomography for diagnostic classification of brain tumors

    Davis, Scott C.; Samkoe, Kimberley S.; O'Hara, Julia A.; Gibbs-Strauss, Summer L.; Paulsen, Keith D.; Pogue, Brian W.

    2010-09-01

    Fluorescence molecular tomography (FMT) systems coupled to conventional imaging modalities such as magnetic resonance imaging (MRI) and computed tomography provide unique opportunities to combine data sets and improve image quality and content. Yet, the ideal approach to combine these complementary data is still not obvious. This preclinical study compares several methods for incorporating MRI spatial prior information into FMT imaging algorithms in the context of in vivo tissue diagnosis. Populations of mice inoculated with brain tumors that expressed either high or low levels of epidermal growth factor receptor (EGFR) were imaged using an EGF-bound near-infrared dye and a spectrometer-based MRI-FMT scanner. All data were spectrally unmixed to extract the dye fluorescence from the tissue autofluorescence. Methods to combine the two data sets were compared using student's t-tests and receiver operating characteristic analysis. Bulk fluorescence measurements that made up the optical imaging data set were also considered in the comparison. While most techniques were able to distinguish EGFR(+) tumors from EGFR(-) tumors and control animals, with area-under-the-curve values=1, only a handful were able to distinguish EGFR(-) tumors from controls. Bulk fluorescence spectroscopy techniques performed as well as most imaging techniques, suggesting that complex imaging algorithms may be unnecessary to diagnose EGFR status in these tissue volumes.

  19. Gastrointestinal B-cell lymphomas: From understanding B-cell physiology to classification and molecular pathology.

    Sagaert, Xavier; Tousseyn, Thomas; Yantiss, Rhonda K

    2012-12-15

    The gut is the most common extranodal site where lymphomas arise. Although all histological lymphoma types may develop in the gut, small and large B-cell lymphomas predominate. The sometimes unexpected finding of a lymphoid lesion in an endoscopic biopsy of the gut may challenge both the clinician (who is not always familiar with lymphoma pathogenesis) and the pathologist (who will often be hampered in his/her diagnostic skill by the limited amount of available tissue). Moreover, the past 2 decades have spawned an avalanche of new data that encompasses both the function of the reactive B-cell as well as the pathogenic pathways that lead to its neoplastic counterpart, the B-cell lymphoma. Therefore, this review aims to offer clinicians an overview of B-cell lymphomas in the gut, and their pertinent molecular features that have led to new insights regarding lymphomagenesis. It addresses the question as how to incorporate all presently available information on normal and neoplastic B-cell differentiation, and how this knowledge can be applied in daily clinical practice (e.g., diagnostic tools, prognostic biomarkers or therapeutic targets) to optimalise the managment of this heterogeneous group of neoplasms. PMID:23443141

  20. Benign hepatocellular nodules: what have we learned using the patho-molecular classification.

    Sempoux, Christine; Chang, Charissa; Gouw, Annette; Chiche, Laurence; Zucman-Rossi, Jessica; Balabaud, Charles; Bioulac-Sage, Paulette

    2013-09-01

    Focal nodular hyperplasia (FNH) and hepatocellular adenoma (HCA) are benign hepatocellular tumors that develop most frequently in females and in non-cirrhotic livers. HCA are prone to bleed and to transform into hepatocellular carcinoma (HCC). Four major subgroups of HCA have been thus far identified: HNF1α mutated HCA, inflammatory HCA (IHCA), β-catenin mutated HCA (b-HCA and b-IHCA), based on mutations in specific oncogenes and tumor suppressors. B-HCA and b-IHCA are strongly associated with HCC transformation. Benign hepatocellular tumors can be classified using immunohistochemistry (LFABP, CRP, GS, b-catenin). Analysis of HCA phenotypes has led to the identification of patients at risk of HCC transformation and therefore improved the indications provided by invasive and non-invasive diagnostic techniques, such as biopsies and MRI. These recent advances have broadened the clinical scope of HCA in various conditions, such as their presence in males, in obese patients, in patients suffering from liver vascular disorders, genetic diseases. However, specific immunohistochemistry has shown limitations particularly for the identification of b-HCA, thereby, outlining the importance of molecular studies to improve the diagnosis/prognosis of HCA. If evaluation of prognosis and treatment has benefited from these advances, much more needs to be done to obtain guidelines for good clinical practice. PMID:23876350

  1. Synergistic Effects of Combining Morphological and Molecular Data in Resolving the Intraspecific Classification in O. basilicum L.

    Zlatko Šatović

    2010-03-01

    Full Text Available High levels of both morphological and chemical variability exist within the O. basilicum L. species. Long-term traditional uses and wide distribution throughout the world, as well as traditional selection and breeding efforts, have contributed to variability within the species. Morphological traits according to UPOV descriptor list and AFLP markers were utilized to define the extent of existing variation in the species analyzing 24 accessions. Phenotypic dissimilarities between pairs of accessions were calculated and the UPGMA dendrogram was constructed. A number of clearly defined clusters have been detected, giving a good representation of traditional taxonomic relationships. Genetic relationships were determined by Neighbour-Joining cluster analysis based on Dice’s distance matrix between accessions. Generally, morphologically similar accessions grouped together and a high congruence between trees was observed. Our analyses revealed a certain degree of correspondence between morphological and molecular data among O. basilicum L. accessions. Both AFLP markers and morphological descriptors can contribute in resolving existing problems concerning intraspecific classification in O. basilicum.

  2. Molecular and metabolic pattern classification for detection of brain glioma progression

    Imani, Farzin, E-mail: imanif@upmc.edu [Department of Radiology, University of Pittsburgh Medical Center, PA (United States); Boada, Fernando E. [Department of Radiology, University of Pittsburgh Medical Center, PA (United States); Lieberman, Frank S. [Department of Neurology, University of Pittsburgh Medical Center, PA (United States); Davis, Denise K.; Mountz, James M. [Department of Radiology, University of Pittsburgh Medical Center, PA (United States)

    2014-02-15

    %. Conclusion: This study suggests that SVM models may improve detection of glioma progression more accurately than single parametric imaging methods. Research support: National Cancer Institute, Cancer Center Support Grant Supplement Award, Imaging Response Assessment Teams.

  3. Molecular and metabolic pattern classification for detection of brain glioma progression

    that SVM models may improve detection of glioma progression more accurately than single parametric imaging methods. Research support: National Cancer Institute, Cancer Center Support Grant Supplement Award, Imaging Response Assessment Teams

  4. Synergistic Effects of Combining Morphological and Molecular Data in Resolving the Intraspecific Classification in O. basilicum L.

    Klaudija Carović-Stanko

    2014-02-01

    Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Obična tablica"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} High levels of both morphological and chemical variability exist within the O. basilicum L. species. Long-term traditional uses and wide distribution throughout the world, as well as traditional selection and breeding efforts, have contributed to variability within the species. Morphological traits according to UPOV descriptor list and AFLP markers were utilized to define the extent of existing variation in the species analyzing 24 accessions. Phenotypic dissimilarities between pairs of accessions were calculated and the UPGMA dendrogram was constructed. A number of clearly defined clusters have been detected, giving a good representation of traditional taxonomic relationships. Genetic relationships were determined by Neighbour-Joining cluster analysis based on Dice’s distance matrix between accessions. Generally, morphologically similar accessions grouped together and a high congruence between trees was observed. Our analyses revealed a certain degree of correspondence between morphological and molecular data among O. basilicum L. accessions. Both AFLP markers and morphological descriptors can contribute in resolving existing problems concerning intraspecific classification in O. basilicum.

  5. Efficient multivariate sequence classification

    Kuksa, Pavel P.

    2014-01-01

    Kernel-based approaches for sequence classification have been successfully applied to a variety of domains, including the text categorization, image classification, speech analysis, biological sequence analysis, time series and music classification, where they show some of the most accurate results. Typical kernel functions for sequences in these domains (e.g., bag-of-words, mismatch, or subsequence kernels) are restricted to {\\em discrete univariate} (i.e. one-dimensional) string data, such ...

  6. Binary classification of chalcone derivatives with LDA or KNN based on their antileishmanial activity and molecular descriptors selected using the Successive Projections Algorithm feature-selection technique.

    Goodarzi, Mohammad; Saeys, Wouter; de Araujo, Mario Cesar Ugulino; Galvão, Roberto Kawakami Harrop; Vander Heyden, Yvan

    2014-01-23

    Chalcones are naturally occurring aromatic ketones, which consist of an α-, β-unsaturated carbonyl system joining two aryl rings. These compounds are reported to exhibit several pharmacological activities, including antiparasitic, antibacterial, antifungal, anticancer, immunomodulatory, nitric oxide inhibition and anti-inflammatory effects. In the present work, a Quantitative Structure-Activity Relationship (QSAR) study is carried out to classify chalcone derivatives with respect to their antileishmanial activity (active/inactive) on the basis of molecular descriptors. For this purpose, two techniques to select descriptors are employed, the Successive Projections Algorithm (SPA) and the Genetic Algorithm (GA). The selected descriptors are initially employed to build Linear Discriminant Analysis (LDA) models. An additional investigation is then carried out to determine whether the results can be improved by using a non-parametric classification technique (One Nearest Neighbour, 1NN). In a case study involving 100 chalcone derivatives, the 1NN models were found to provide better rates of correct classification than LDA, both in the training and test sets. The best result was achieved by a SPA-1NN model with six molecular descriptors, which provided correct classification rates of 97% and 84% for the training and test sets, respectively. PMID:24090733

  7. A molecular phylogeny for the leaf-roller moths (Lepidoptera: Tortricidae) and its implications for classification and life history evolution

    Tortricidae, one of the largest families of small moths, comprise about 10,000 species worldwide, including important pests, biological control agents, and experimental models. Tortricid classification at the subfamily and tribal level has been largely stable for two decades. However, our understand...

  8. Pharmacological Classification and Activity Evaluation of Furan and Thiophene Amide Derivatives Applying Semi-Empirical ab initio Molecular Modeling Methods

    Leszek Bober

    2012-05-01

    Full Text Available Pharmacological and physicochemical classification of the furan and thiophene amide derivatives by multiple regression analysis and partial least square (PLS based on semi-empirical ab initio molecular modeling studies and high-performance liquid chromatography (HPLC retention data is proposed. Structural parameters obtained from the PCM (Polarizable Continuum Model method and the literature values of biological activity (antiproliferative for the A431 cells expressed as LD50 of the examined furan and thiophene derivatives was used to search for relationships. It was tested how variable molecular modeling conditions considered together, with or without HPLC retention data, allow evaluation of the structural recognition of furan and thiophene derivatives with respect to their pharmacological properties.

  9. Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: Using density functional theory to accelerate wavefunction methods

    Kapil, V.; VandeVondele, J.; Ceriotti, M.

    2016-02-01

    The development and implementation of increasingly accurate methods for electronic structure calculations mean that, for many atomistic simulation problems, treating light nuclei as classical particles is now one of the most serious approximations. Even though recent developments have significantly reduced the overhead for modeling the quantum nature of the nuclei, the cost is still prohibitive when combined with advanced electronic structure methods. Here we present how multiple time step integrators can be combined with ring-polymer contraction techniques (effectively, multiple time stepping in imaginary time) to reduce virtually to zero the overhead of modelling nuclear quantum effects, while describing inter-atomic forces at high levels of electronic structure theory. This is demonstrated for a combination of MP2 and semi-local DFT applied to the Zundel cation. The approach can be seamlessly combined with other methods to reduce the computational cost of path integral calculations, such as high-order factorizations of the Boltzmann operator or generalized Langevin equation thermostats.

  10. Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: Using density functional theory to accelerate wavefunction methods

    Kapil, V.; Ceriotti, M., E-mail: michele.ceriotti@epfl.ch [Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne (Switzerland); VandeVondele, J., E-mail: joost.vandevondele@mat.ethz.ch [Department of Materials, ETH Zurich, Wolfgang-Pauli-Strasse 27, CH-8093 Zurich (Switzerland)

    2016-02-07

    The development and implementation of increasingly accurate methods for electronic structure calculations mean that, for many atomistic simulation problems, treating light nuclei as classical particles is now one of the most serious approximations. Even though recent developments have significantly reduced the overhead for modeling the quantum nature of the nuclei, the cost is still prohibitive when combined with advanced electronic structure methods. Here we present how multiple time step integrators can be combined with ring-polymer contraction techniques (effectively, multiple time stepping in imaginary time) to reduce virtually to zero the overhead of modelling nuclear quantum effects, while describing inter-atomic forces at high levels of electronic structure theory. This is demonstrated for a combination of MP2 and semi-local DFT applied to the Zundel cation. The approach can be seamlessly combined with other methods to reduce the computational cost of path integral calculations, such as high-order factorizations of the Boltzmann operator or generalized Langevin equation thermostats.

  11. Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: Using density functional theory to accelerate wavefunction methods

    The development and implementation of increasingly accurate methods for electronic structure calculations mean that, for many atomistic simulation problems, treating light nuclei as classical particles is now one of the most serious approximations. Even though recent developments have significantly reduced the overhead for modeling the quantum nature of the nuclei, the cost is still prohibitive when combined with advanced electronic structure methods. Here we present how multiple time step integrators can be combined with ring-polymer contraction techniques (effectively, multiple time stepping in imaginary time) to reduce virtually to zero the overhead of modelling nuclear quantum effects, while describing inter-atomic forces at high levels of electronic structure theory. This is demonstrated for a combination of MP2 and semi-local DFT applied to the Zundel cation. The approach can be seamlessly combined with other methods to reduce the computational cost of path integral calculations, such as high-order factorizations of the Boltzmann operator or generalized Langevin equation thermostats

  12. Simple and accurate scheme to compute electrostatic interaction: zero-dipole summation technique for molecular system and application to bulk water.

    Fukuda, Ikuo; Kamiya, Narutoshi; Yonezawa, Yasushige; Nakamura, Haruki

    2012-08-01

    The zero-dipole summation method was extended to general molecular systems, and then applied to molecular dynamics simulations of an isotropic water system. In our previous paper [I. Fukuda, Y. Yonezawa, and H. Nakamura, J. Chem. Phys. 134, 164107 (2011)], for evaluating the electrostatic energy of a classical particle system, we proposed the zero-dipole summation method, which conceptually prevents the nonzero-charge and nonzero-dipole states artificially generated by a simple cutoff truncation. Here, we consider the application of this scheme to molecular systems, as well as some fundamental aspects of general cutoff truncation protocols. Introducing an idea to harmonize the bonding interactions and the electrostatic interactions in the scheme, we develop a specific algorithm. As in the previous study, the resulting energy formula is represented by a simple pairwise function sum, enabling facile applications to high-performance computation. The accuracy of the electrostatic energies calculated by the zero-dipole summation method with the atom-based cutoff was numerically investigated, by comparison with those generated by the Ewald method. We obtained an electrostatic energy error of less than 0.01% at a cutoff length longer than 13 Å for a TIP3P isotropic water system, and the errors were quite small, as compared to those obtained by conventional truncation methods. The static property and the stability in an MD simulation were also satisfactory. In addition, the dielectric constants and the distance-dependent Kirkwood factors were measured, and their coincidences with those calculated by the particle mesh Ewald method were confirmed, although such coincidences are not easily attained by truncation methods. We found that the zero damping-factor gave the best results in a practical cutoff distance region. In fact, in contrast to the zero-charge scheme, the damping effect was insensitive in the zero-charge and zero-dipole scheme, in the molecular system we

  13. Efficient segmentation by sparse pixel classification

    Dam, Erik B; Loog, Marco

    2008-01-01

    Segmentation methods based on pixel classification are powerful but often slow. We introduce two general algorithms, based on sparse classification, for optimizing the computation while still obtaining accurate segmentations. The computational costs of the algorithms are derived, and they are...

  14. Multiple sparse representations classification

    Plenge, Esben; Klein, Stefan; Niessen, Wiro; Meijering, Erik

    2015-01-01

    textabstractSparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small...

  15. Multiple Sparse Representations Classification

    Plenge, Esben; Klein, Stefan S.; Niessen, Wiro J.; Meijering, Erik

    2015-01-01

    Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surro...

  16. Nominal classification

    Senft, G.

    2007-01-01

    This handbook chapter summarizes some of the problems of nominal classification in language, presents and illustrates the various systems or techniques of nominal classification, and points out why nominal classification is one of the most interesting topics in Cognitive Linguistics.

  17. Taxonomy of Plant Genetic Resources – Use of Morphological, Molecular and Phytochemical Data in Order to Verify Existing Classifications

    Ulrike Lohwasser

    2010-12-01

    Full Text Available Taxonomy of plant genetic resources is an important input in characterising and evaluating cultivated plants and it is essential for identification and documentation of the diversity of genebank collections. In former times taxonomical determination was based only on morphological characters. Nowadays, new molecular and chemical methods and techniques are available for providing additional information. As examples of the interaction of morphological, molecular and phytochemical data, investigations of a parsley (Petroselinum crispum [Mill.] Nyman, Apiaceae and an opium poppy (Papaver somniferum L., Papaveraceae collection of the German genebank are demonstrated. 220 parsley and 300 opium poppy accessions were cultivated and described morphologically. In addition, the molecular distance and the phylogenetic relationship of the accessions were performed with molecular marker analysis. Essential oil compound and content for parsley and the content of the five main alkaloids (morphine, codeine, thebaine, noscapine, papaverine for opium poppy were measured with GC (gas chromatography and HPLC (high pressure liquid chromatography, respectively. For parsley the results of the three methods support the existing taxonomy partly, a separation of root and leaf parsley was confirmed. However, the taxonomy of opium poppy should be revised because molecular and chemical data do not verify the morphological results. But nevertheless taxonomy of cultivated plants is an important tool to describe the variability of plant genetic resources.

  18. Taxonomy of Plant Genetic Resources – Use of Morphological, Molecular and Phytochemical Data in Order to Verify Existing Classifications

    Ulrike Lohwasser

    2014-02-01

    Full Text Available Taxonomy of plant genetic resources is an important input in characterising and evaluating cultivated plants and it is essential for identification and documentation of the diversity of genebank collections. In former times taxonomical determination was based only on morphological characters. Nowadays, new molecular and chemical methods and techniques are available for providing additional information. As examples of the interaction of morphological, molecular and phytochemical data, investigations of a parsley (Petroselinum crispum [Mill.] Nyman, Apiaceae and an opium poppy (Papaver somniferum L., Papaveraceae collection of the German genebank are demonstrated. 220 parsley and 300 opium poppy accessions were cultivated and described morphologically. In addition, the molecular distance and the phylogenetic relationship of the accessions were performed with molecular marker analysis. Essential oil compound and content for parsley and the content of the five main alkaloids (morphine, codeine, thebaine, noscapine, papaverine for opium poppy were measured with GC (gas chromatography and HPLC (high pressure liquid chromatography, respectively. For parsley the results of the three methods support the existing taxonomy partly, a separation of root and leaf parsley was confirmed. However, the taxonomy of opium poppy should be revised because molecular and chemical data do not verify the morphological results. But nevertheless taxonomy of cultivated plants is an important tool to describe the variability of plant genetic resources.

  19. Elastic collisions between Si and D atoms at low temperatures and accurate analytic potential energy function and molecular constants of the SiD(X2∏) radical

    Shi De-Heng; Zhang Jin-Ping; Sun Jin-Feng; Zhu Zun-Lue

    2009-01-01

    Interaction potential of the SiD(X2∏) radical is constructed by using the CCSD(T) theory in combination with the largest correlation-consistent quintuple basis set augmented with the diffuse functions in the valence range. Using the interaction potential, the spectroscopic parameters are accurately determined. The present D0, De, Re, ωe, αe and Be values are of 3.0956 eV, 3.1863 eV, 0.15223 nm, 1472.894 cm-1, 0.07799 cm-1 and 3.8717 cm-1, respectively,which are in excellent agreement with the measurements. A total of 26 vibrational states is predicted when J = 0 by solving the radial Schr(o)dinger equation of nuclear motion. The complete vibrational levels, classical turning points,initial rotation and centrifugal distortion constants when J = 0 are reported for the first time, which are in good accord with the available experiments. The total and various partial-wave cross sections are calculated for the elastic collisions between Si and D atoms in their ground states at 1.0×10-11-1.0×10-3 a.u. when the two atoms approach each other along the SiD(X2∏) potential energy curve. Four shape resonances are found in the total elastic cross sections, and their resonant energies are of 1.73×10-5, 4.0×10-5, 6.45×10-5 and 5.5×10-4 a.u., respectively. Each shape resonance in the total elastic cross sections is carefully investigated. The results show that the shape of the total elastic cross sections is mainly dominated by the s partial wave at very low temperatures. Because of the weakness of the shape resonances coming from the higher partial waves, most of them are passed into oblivion by the strong s partial-wave elastic cross sections.

  20. Novel, Precise, Accurate Ion-Pairing Method to Determine the Related Substances of the Fondaparinux Sodium Drug Substance: Low-Molecular-Weight Heparin.

    Deshpande, Amol A; Madhavan, P; Deshpande, Girish R; Chandel, Ravi Kumar; Yarbagi, Kaviraj M; Joshi, Alok R; Moses Babu, J; Murali Krishna, R; Rao, I M

    2016-01-01

    Fondaparinux sodium is a synthetic low-molecular-weight heparin (LMWH). This medication is an anticoagulant or a blood thinner, prescribed for the treatment of pulmonary embolism and prevention and treatment of deep vein thrombosis. Its determination in the presence of related impurities was studied and validated by a novel ion-pair HPLC method. The separation of the drug and its degradation products was achieved with the polymer-based PLRPs column (250 mm × 4.6 mm; 5 μm) in gradient elution mode. The mixture of 100 mM n-hexylamine and 100 mM acetic acid in water was used as buffer solution. Mobile phase A and mobile phase B were prepared by mixing the buffer and acetonitrile in the ratio of 90:10 (v/v) and 20:80 (v/v), respectively. Mobile phases were delivered in isocratic mode (2% B for 0-5 min) followed by gradient mode (2-85% B in 5-60 min). An Evaporative Light Scattering Detector (ELSD) was connected to the LC system to detect the responses of chromatographic separation. Further, the drug was subjected to stress studies for acidic, basic, oxidative, photolytic, and thermal degradations as per ICH guidelines and the drug was found to be labile in acid, base hydrolysis, and oxidation, while stable in neutral, thermal, and photolytic degradation conditions. The method provided linear responses over the concentration range of the LOQ to 0.30% for each impurity with respect to the analyte concentration of 12.5 mg/mL, and regression analysis showed a correlation coefficient value (r(2)) of more than 0.99 for all the impurities. The LOD and LOQ were found to be 1.4 µg/mL and 4.1 µg/mL, respectively, for fondaparinux. The developed ion-pair method was validated as per ICH guidelines with respect to accuracy, selectivity, precision, linearity, and robustness. PMID:27110496

  1. Communication: Rate coefficients of the H + CH{sub 4} → H{sub 2} + CH{sub 3} reaction from ring polymer molecular dynamics on a highly accurate potential energy surface

    Meng, Qingyong, E-mail: mengqingyong@dicp.ac.cn; Chen, Jun, E-mail: chenjun@dicp.ac.cn; Zhang, Dong H., E-mail: zhangdh@dicp.ac.cn [State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Zhongshan Road 457, 116023 Dalian (China)

    2015-09-14

    The ring polymer molecular dynamics (RPMD) calculations are performed to calculate rate constants for the title reaction on the recently constructed potential energy surface based on permutation invariant polynomial (PIP) neural-network (NN) fitting [J. Li et al., J. Chem. Phys. 142, 204302 (2015)]. By inspecting convergence, 16 beads are used in computing free-energy barriers at 300 K ≤ T ≤ 1000 K, while different numbers of beads are used for transmission coefficients. The present RPMD rates are in excellent agreement with quantum rates computed on the same potential energy surface, as well as with the experimental measurements, demonstrating further that the RPMD is capable of producing accurate rates for polyatomic chemical reactions even at rather low temperatures.

  2. A revised classification of the family Dasyatidae (Chondrichthyes: Myliobatiformes) based on new morphological and molecular insights.

    Last, Peter R; Naylor, Gavin J P; Manjaji-Matsumoto, B Mabel

    2016-01-01

    The higher-level taxonomy of the stingrays (Dasyatidae) has never been comprehensively reviewed. Recent phylogenetic studies, supported by morphological data, have provided evidence that the group is monophyletic and consists of four major subgroups, the subfamilies Dasyatinae, Neotrygoninae, Urogymninae and Hypolophinae. A morphologically based review of 89 currently recognised species, undertaken for a guide to the world's rays, indicated that most of the currently recognised dasyatid genera are not monophyletic groups. These findings were supported by molecular analyses using the NADH2 gene for about 77 of these species, and this topology is supported by preliminary analyses base on whole mitochondrial genome comparisons. These molecular analyses, based on data generated from the Chondrichthyan Tree of Life project, are the most taxon-rich data available for this family. Material from all of the presently recognised genera (Dasyatis, Pteroplatytrygon and Taeniurops [Dasyatinae]; Neotrygon and Taeniura [Neotrygoninae]; Himantura and Urogymnus [Urogymninae]; and Makararaja and Pastinachus [Hypolophinae]), are included and their validity largely supported. Urogymnus and the two most species rich genera, Dasyatis and Himantura, are not considered to be monophyletic and were redefined based on external morphology. Seven new genus-level taxa are erected (Megatrygon and Telatrygon [Dasyatinae]; Brevitrygon, Fluvitrygon, Fontitrygon, Maculabatis and Pateobatis [Urogymninae], and an additional three (Bathytoshia, Hemitrygon and Hypanus [Dasyatinae]) are resurrected from the synonymy of Dasyatis. The monotypic genus Megatrygon clustered with 'amphi-American Himantura' outside the Dasyatidae, and instead as the sister group of the Potamotrygonidae and Urotrygonidae. Megatrygon is provisionally retained in the Dasyatinae pending further investigation of its internal anatomy. The morphologically divergent groups, Bathytoshia and Pteroplatytrygon, possibly form a single

  3. Accurate Molecular Dimensions from Stearic Acid Monolayers.

    Lane, Charles A.; And Others

    1984-01-01

    Discusses modifications in the fatty acid monolayer experiment to reduce the inaccurate moleculary data students usually obtain. Copies of the experimental procedure used and a Pascal computer program to work up the data are available from the authors. (JN)

  4. PSG-Based Classification of Sleep Phases

    Králík, M.

    2015-01-01

    This work is focused on classification of sleep phases using artificial neural network. The unconventional approach was used for calculation of classification features using polysomnographic data (PSG) of real patients. This approach allows to increase the time resolution of the analysis and, thus, to achieve more accurate results of classification.

  5. Evaluation of the use of partition coefficients and molecular surface properties as predictors of drug absorption: a provisional biopharmaceutical classification of the list of national essential medi

    NU Rahman

    2011-05-01

    Full Text Available Background and the purpose of the study: Partition coefficients (log D and log P and molecular surface area (PSA are potential predictors of the intestinal permeability of drugs. The aim of this investigation was to evaluate and compare these intestinal permeability indicators.   Methods: Aqueous solubility data were obtained from literature or calculated using ACD/Labs and ALOGPS. Permeability data were predicted based on log P, log D at pH 6.0 (log D6.0, and PSA.  Results: Metoprolol's log P, log D6.0 and a PSA of <65 Å correctly predicted 55.9%, 50.8% and 54.2% of permeability classes, respectively. Labetalol's log P, log D6.0, and PSA correctly predicted 54.2%, 64.4% and 61% of permeability classes, respectively. Log D6.0 correlated well (81% with Caco-2 permeability (Papp. Of the list of national essential medicines, 135 orally administered drugs were classified into biopharmaceutical classification system (BCS. Of these, 57 (42.2%, 28 (20.7%, 44 (32.6%, and 6 (4.4% were class I, II, III and IV respectively. Conclusion: Log D6.0 showed better prediction capability than log P. Metoprolol as permeability internal standard was more conservative than labetalol.

  6. Bayesian Classification in Medicine: The Transferability Question *

    Zagoria, Ronald J.; Reggia, James A.; Price, Thomas R.; Banko, Maryann

    1981-01-01

    Using probabilities derived from a geographically distant patient population, we applied Bayesian classification to categorize stroke patients by etiology. Performance was assessed both by error rate and with a new linear accuracy coefficient. This approach to patient classification was found to be surprisingly accurate when compared to classification by two neurologists and to classification by the Bayesian method using “low cost” local and subjective probabilities. We conclude that for some...

  7. Application of Data Mining in Protein Sequence Classification

    Suprativ Saha

    2012-11-01

    Full Text Available Protein sequence classification involves feature selection for accurate classification. Popular protein sequence classification techniques involve extraction of specific features from the sequences. Researchers apply some well-known classification techniques like neural networks, Genetic algorithm, Fuzzy ARTMAP,Rough Set Classifier etc for accurate classification. This paper presents a review is with three different classification models such as neural network model, fuzzy ARTMAP model and Rough set classifier model.This is followed by a new technique for classifying protein sequences. The proposed model is typicallyimplemented with an own designed tool and tries to reduce the computational overheads encountered by earlier approaches and increase the accuracy of classification.

  8. Role of ASXL1 and TP53 mutations in the molecular classification and prognosis of acute myeloid leukemias with myelodysplasia-related changes

    Devillier, Raynier; Prebet, Thomas; Bertoli, Sarah; Brecqueville, Mandy; Arnoulet, Christine; Recher, Christian; Vey, Norbert; Mozziconacci, Marie-Joelle; Delabesse, Eric; Birnbaum, Daniel

    2015-01-01

    Acute myeloid leukemias (AML) with myelodysplasia-related changes (AML-MRC) are defined by the presence of multilineage dysplasia (MLD), and/or myelodysplastic syndrome (MDS)-related cytogenetics, and/or previous MDS. The goal of this study was to identify distinct biological and prognostic subgroups based on mutations of ASXL1, RUNX1, DNMT3A, NPM1, FLT3 and TP53 in 125 AML-MRC patients according to the presence of MLD, cytogenetics and outcome. ASXL1 mutations (n=26, 21%) were associated with a higher proportion of marrow dysgranulopoiesis (mutant vs. wild-type: 75% vs. 55%, p=0.030) and were mostly found in intermediate cytogenetic AML (23/26) in which they predicted inferior 2-year overall survival (OS, mutant vs. wild-type: 14% vs. 37%, p=0.030). TP53 mutations (n=28, 22%) were mostly found in complex karyotype AML (26/28) and predicted poor outcome within unfavorable cytogenetic risk AML (mutant vs. wild-type: 9% vs. 40%, p=0.040). In multivariate analysis, the presence of either ASXL1 or TP53 mutation was the only independent factor associated with shorter OS (HR, 95%CI: 2.53, 1.40-4.60, p=0.002) while MLD, MDS-related cytogenetics and previous MDS history did not influence OS. We conclude that ASXL1 and TP53 mutations identify two molecular subgroups among AML-MRCs, with specific poor prognosis. This could be useful for future diagnostic and prognostic classifications. PMID:25860933

  9. ClassyFlu: Classification of Influenza A Viruses with Discriminatively Trained Profile-HMMs

    Van der Auwera, Sandra; Bulla, Ingo; Ziller, Mario; Pohlmann, Anne; Harder, Timm; Stanke, Mario

    2014-01-01

    Accurate and rapid characterization of influenza A virus (IAV) hemagglutinin (HA) and neuraminidase (NA) sequences with respect to subtype and clade is at the basis of extended diagnostic services and implicit to molecular epidemiologic studies. ClassyFlu is a new tool and web service for the classification of IAV sequences of the HA and NA gene into subtypes and phylogenetic clades using discriminatively trained profile hidden Markov models (HMMs), one for each subtype or clade. ClassyFlu me...

  10. Accurate classification of 17 AGNs detected with Swift/BAT

    Parisi, P; Jimenez-Bailon, E; Chavushyan, V; Malizia, A; Landi, R; Molina, M; Fiocchi, M; Palazzi, E; Bassani, L; Bazzano, A; Bird, A J; Dean, A J; Galaz, G; Mason, E; Minniti, D; Morelli, L; Stephen, J B; Ubertini, P

    2009-01-01

    Through an optical campaign performed at 5 telescopes located in the northern and the southern hemispheres, plus archival data from two on line sky surveys, we have obtained optical spectroscopy for 17 counterparts of suspected or poorly studied hard X-ray emitting active galactic nuclei (AGNs) detected with Swift/BAT in order to determine or better classify their nature. We find that 7 sources of our sample are Type 1 AGNs, 9 are Type 2 AGNs, and 1 object is an X-ray bright optically normal galaxy; the redshifts of these objects lie in a range between 0.012 and 0.286. For all these sources, X-ray data analysis was also performed to estimate their absorption column and to search for possible Compton thick candidates. Among our type 2 objects, we did not find any clear Compton thick AGN, but at least 6 out of 9 of them are highly absorbed (N_H > 10^23 cm^-2), while one does not require intrinsic absorption; i.e., it appears to be a naked Seyfert 2 galaxy.

  11. An Innovative Imputation and Classification Approach for Accurate Disease Prediction

    UshaRani, Yelipe; Sammulal, P.

    2016-01-01

    Imputation of missing attribute values in medical datasets for extracting hidden knowledge from medical datasets is an interesting research topic of interest which is very challenging. One cannot eliminate missing values in medical records. The reason may be because some tests may not been conducted as they are cost effective, values missed when conducting clinical trials, values may not have been recorded to name some of the reasons. Data mining researchers have been proposing various approa...

  12. Accurate mobile malware detection and classification in the cloud

    Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

    2015-01-01

    As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new op...

  13. Molecular-based classification of acute myeloid leukemia and its role in directing rational therapy: personalized medicine for profoundly promiscuous proliferations.

    Wertheim, Gerald B W; Hexner, Elizabeth; Bagg, Adam

    2012-12-01

    Acute myeloid leukemia (AML) is not a single pathologic entity but represents a heterogeneous group of malignancies. This heterogeneity is exemplified by the variable clinical outcomes that are observed in patients with AML, and it is largely the result of diverse mutations within the leukemic cells. These mutations range from relatively large genetic alterations, such as gains, losses, and translocations of chromosomes, to single nucleotide changes. Detection of many of these mutations is required for accurate diagnosis, prognosis, and treatment of patients with AML. As such, many testing modalities have been developed and are currently employed in clinical laboratories to ascertain mutational status at prognostically and therapeutically critical loci. The assays include those that specifically identify large chromosomal alterations, such as conventional metaphase analysis and fluorescence in situ hybridization, and methods that are geared more toward analysis of small mutations, such as PCR with allele-specific oligonucleotide primers. Furthermore, newer tests, including array analysis and next-generation sequencing, which can simultaneously probe numerous molecular aberrancies within tumor cells, are likely to become commonplace in AML diagnostics. Each testing method clearly has advantages and disadvantages, an understanding of which should influence the choice of test in various clinical circumstances. To aid such understanding, this review discusses both genetic mutations in AML and the clinical tests-including their pros and cons-that may be used to probe these abnormalities. Additionally, we highlight the significance of genetic testing by describing cases in which results of genetic testing significantly influence clinical management of patients with AML. PMID:23184342

  14. 过滤特征基因选择及演化硬件急性白血病分型%Molecular Classification of Acute Leukemia Using EHW with Filter-Based Gene Selection

    王进; 丁凌; 孙开伟; 李钟浩

    2012-01-01

    A virtual reconfigurable architecture-based intrinsic evolvable hardware (EHW) is proposed for the molecular classification of cancer. To efficiently process DNA microarray datasets and cooperate with the hardware realization of EHW, five different filter-based gene selection methods are compared and discussed in this paper. The EHW classification system handles the selected informative genes through two stages: system learning and system classification. Empirical studies on a human acute leukemia dataset demonstrate that classification accuracy of the gene selection scheme based on signal-to-noise ratio outperforms its competitors. Classification accuracy of the proposed EHW is high comparable with other state-of-the-art pattern recognition methods. The system recognition time is reduced to 0.12 μs.%提出一种基于虚拟可重构结构的内部演化硬件癌症分子分型方法.为有效处理DNA微阵列数据和便于硬件实现,对比研究了5种基于过滤模式的信息基因选择方法.演化硬件通过系统学习和系统分类两个阶段对经过特征选择的信息基因进行处理,对急性白血病数据集的实验结果表明,基于信噪比信息基因选择方法的演化硬件分类器识别率最高.演化硬件具有和其他传统模式识别方法可比的识别率,识别时间仅需0.12μs.

  15. Accurate Finite Difference Algorithms

    Goodrich, John W.

    1996-01-01

    Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

  16. Multiple Sparse Representations Classification.

    Plenge, Esben; Klein, Stefan; Klein, Stefan S; Niessen, Wiro J; Meijering, Erik

    2015-01-01

    Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surrounding it. Using these patches, a dictionary is trained for each class in a supervised fashion. Commonly, redundant/overcomplete dictionaries are trained and image patches are sparsely represented by a linear combination of only a few of the dictionary elements. Given a set of trained dictionaries, a new patch is sparse coded using each of them, and subsequently assigned to the class whose dictionary yields the minimum residual energy. We propose a generalization of this scheme. The method, which we call multiple sparse representations classification (mSRC), is based on the observation that an overcomplete, class specific dictionary is capable of generating multiple accurate and independent estimates of a patch belonging to the class. So instead of finding a single sparse representation of a patch for each dictionary, we find multiple, and the corresponding residual energies provides an enhanced statistic which is used to improve classification. We demonstrate the efficacy of mSRC for three example applications: pixelwise classification of texture images, lumen segmentation in carotid artery magnetic resonance imaging (MRI), and bifurcation point detection in carotid artery MRI. We compare our method with conventional SRC, K-nearest neighbor, and support vector machine classifiers. The results show that mSRC outperforms SRC and the other reference methods. In addition, we present an extensive evaluation of the effect of the main mSRC parameters: patch size, dictionary size, and

  17. Molecular phylogeny of advanced snakes (Serpentes, Caenophidia with an emphasis on South American Xenodontines: a revised classification and descriptions of new taxa

    Hussam Zaher

    2009-01-01

    Full Text Available We present a molecular phylogenetic analysis of caenophidian (advanced snakes using sequences from two mitochondrial genes (12S and 16S rRNA and one nuclear (c-mos gene (1681 total base pairs, and with 131 terminal taxa sampled from throughout all major caenophidian lineages but focussing on Neotropical xenodontines. Direct optimization parsimony analysis resulted in a well-resolved phylogenetic tree, which corroborates some clades identified in previous analyses and suggests new hypotheses for the composition and relationships of others. The major salient points of our analysis are: (1 placement of Acrochordus, Xenodermatids, and Pareatids as successive outgroups to all remaining caenophidians (including viperids, elapids, atractaspidids, and all other "colubrid" groups; (2 within the latter group, viperids and homalopsids are sucessive sister clades to all remaining snakes; (3 the following monophyletic clades within crown group caenophidians: Afro-Asian psammophiids (including Mimophis from Madagascar, Elapidae (including hydrophiines but excluding Homoroselaps, Pseudoxyrhophiinae, Colubrinae, Natricinae, Dipsadinae, and Xenodontinae. Homoroselaps is associated with atractaspidids. Our analysis suggests some taxonomic changes within xenodontines, including new taxonomy for Alsophis elegans, Liophis amarali, and further taxonomic changes within Xenodontini and the West Indian radiation of xenodontines. Based on our molecular analysis, we present a revised classification for caenophidians and provide morphological diagnoses for many of the included clades; we also highlight groups where much more work is needed. We name as new two higher taxonomic clades within Caenophidia, one new subfamily within Dipsadidae, and, within Xenodontinae five new tribes, six new genera and two resurrected genera. We synonymize Xenoxybelis and Pseudablabes with Philodryas; Erythrolamprus with Liophis; and Lystrophis and Waglerophis with Xenodon.Este trabalho

  18. Strategic Classification

    Hardt, Moritz; Megiddo, Nimrod; Papadimitriou, Christos; Wootters, Mary

    2015-01-01

    Machine learning relies on the assumption that unseen test instances of a classification problem follow the same distribution as observed training data. However, this principle can break down when machine learning is used to make important decisions about the welfare (employment, education, health) of strategic individuals. Knowing information about the classifier, such individuals may manipulate their attributes in order to obtain a better classification outcome. As a result of this behavior...

  19. HYBRID INTERNET TRAFFIC CLASSIFICATION TECHNIQUE1

    Li Jun; Zhang Shunyi; Lu Yanqing; Yan Junrong

    2009-01-01

    Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classification system, compared with the one-step Machine Learning (ML) approach.

  20. Towards Automatic Classification of Neurons

    Armañanzas, Rubén; Ascoli, Giorgio A.

    2015-01-01

    The classification of neurons into types has been much debated since the inception of modern neuroscience. Recent experimental advances are accelerating the pace of data collection. The resulting information growth of morphological, physiological, and molecular properties encourages efforts to automate neuronal classification by powerful machine learning techniques. We review state-of-the-art analysis approaches and availability of suitable data and resources, highlighting prominent challenge...

  1. Text Classification using Artificial Intelligence

    Kamruzzaman, S M

    2010-01-01

    Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Existing supervised learning algorithms for classifying text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification using artificial intelligence technique that requires fewer documents for training. Instead of using words, word relation i.e. association rules from these words is used to derive feature set from pre-classified text documents. The concept of na\\"ive Bayes classifier is then used on derived features and finally only a single concept of genetic algorithm has been added for final classification. A syste...

  2. Text Classification using Data Mining

    Kamruzzaman, S M; Hasan, Ahmed Ryadh

    2010-01-01

    Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Existing supervised learning algorithms to automatically classify text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification using data mining that requires fewer documents for training. Instead of using words, word relation i.e. association rules from these words is used to derive feature set from pre-classified text documents. The concept of Naive Bayes classifier is then used on derived features and finally only a single concept of Genetic Algorithm has been added for final classification. A system based on the...

  3. Transporter Classification Database (TCDB)

    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)...

  4. Histologic classification of gliomas.

    Perry, Arie; Wesseling, Pieter

    2016-01-01

    Gliomas form a heterogeneous group of tumors of the central nervous system (CNS) and are traditionally classified based on histologic type and malignancy grade. Most gliomas, the diffuse gliomas, show extensive infiltration in the CNS parenchyma. Diffuse gliomas can be further typed as astrocytic, oligodendroglial, or rare mixed oligodendroglial-astrocytic of World Health Organization (WHO) grade II (low grade), III (anaplastic), or IV (glioblastoma). Other gliomas generally have a more circumscribed growth pattern, with pilocytic astrocytomas (WHO grade I) and ependymal tumors (WHO grade I, II, or III) as the most frequent representatives. This chapter provides an overview of the histology of all glial neoplasms listed in the WHO 2016 classification, including the less frequent "nondiffuse" gliomas and mixed neuronal-glial tumors. For multiple decades the histologic diagnosis of these tumors formed a useful basis for assessment of prognosis and therapeutic management. However, it is now fully clear that information on the molecular underpinnings often allows for a more robust classification of (glial) neoplasms. Indeed, in the WHO 2016 classification, histologic and molecular findings are integrated in the definition of several gliomas. As such, this chapter and Chapter 6 are highly interrelated and neither should be considered in isolation. PMID:26948349

  5. Insights into the classification of small GTPases

    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

  6. Tissue Classification

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are no...... software packages such as SPM, FSL, and FreeSurfer....

  7. Classifying Classification

    Novakowski, Janice

    2009-01-01

    This article describes the experience of a group of first-grade teachers as they tackled the science process of classification, a targeted learning objective for the first grade. While the two-year process was not easy and required teachers to teach in a new, more investigation-oriented way, the benefits were great. The project helped teachers and…

  8. A genus-level classification of the family Thraupidae (Class Aves: Order Passeriformes).

    Burns, Kevin J; Unitt, Philip; Mason, Nicholas A

    2016-01-01

    The tanagers (Thraupidae) are a major component of the Neotropical avifauna, and vary in plumage colors, behaviors, morphologies, and ecologies. Globally, they represent nearly 4% of all avian species and are the largest family of songbirds. However, many currently used tanager genera are not monophyletic, based on analyses of molecular data that have accumulated over the past 25 years. Current genus-level classifications of tanagers have not been revised according to newly documented relationships of tanagers for various reasons: 1) the lack of a comprehensive phylogeny, 2) reluctance to lump existing genera into larger groups, and 3) the lack of available names for newly defined smaller groups. Here, we present two alternative classifications based on a newly published comprehensive phylogeny of tanagers. One of these classifications uses existing generic names, but defines them broadly. The other, which we advocate and follow here, provides new generic names for more narrowly defined groups. Under the latter, we propose eleven new genera (Asemospiza, Islerothraupis, Maschalethraupis, Chrysocorypha, Kleinothraupis, Castanozoster, Ephippiospingus, Chionodacryon, Pseudosaltator, Poecilostreptus, Stilpnia), and resurrect several generic names to form monophyletic taxa. Either of these classifications would allow taxonomic authorities to reconcile classification with current understanding of tanager phylogenetic relationships. Having a more phylogenetically accurate classification for tanagers will facilitate the study and conservation of this important Neotropical radiation of songbirds. PMID:27394344

  9. Improving enzyme regulatory protein classification by means of SVM-RFE feature selection.

    Fernandez-Lozano, Carlos; Fernández-Blanco, Enrique; Dave, Kirtan; Pedreira, Nieves; Gestal, Marcos; Dorado, Julián; Munteanu, Cristian R

    2014-05-01

    Enzyme regulation proteins are very important due to their involvement in many biological processes that sustain life. The complexity of these proteins, the impossibility of identifying direct quantification molecular properties associated with the regulation of enzymatic activities, and their structural diversity creates the necessity for new theoretical methods that can predict the enzyme regulatory function of new proteins. The current work presents the first classification model that predicts protein enzyme regulators using the Markov mean properties. These protein descriptors encode the topological information of the amino acid into contact networks based on amino acid distances and physicochemical properties. MInD-Prot software calculated these molecular descriptors for 2415 protein chains (350 enzyme regulators) using five atom physicochemical properties (Mulliken electronegativity, Kang-Jhon polarizability, vdW area, atom contribution to P) and the protein 3D regions. The best classification models to predict enzyme regulators have been obtained with machine learning algorithms from Weka using 18 features. K* has been demonstrated to be the most accurate algorithm for this protein function classification. Wrapper Subset Evaluator and SVM-RFE approaches were used to perform a feature subset selection with the best results obtained from SVM-RFE. Classification performance employing all the available features can be reached using only the 8 most relevant features selected by SVM-RFE. Thus, the current work has demonstrated the possibility of predicting new molecular targets involved in enzyme regulation using fast theoretical algorithms. PMID:24556806

  10. Molecular classification of anaplastic oligodendroglioma using next-generation sequencing: A report of the prospective randomized EORTC Brain Tumor Group 26951 phase III trial

    H.J. Dubbink (Erik Jan); P.N. Atmodimedjo; J.M. Kros (Johan); P.J. French (Pim); M. Sanson (Marc); A. Idbaih (Ahmed); P. Wesseling (Pieter); R. Enting (Roelien); W.G.M. Spliet (Wim); C.C. Tijssen (Cees); W.N.M. Dinjens (Winand); T.S. Gorlia (Thierry); M.J. van den Bent (Martin)

    2016-01-01

    textabstractBackground Histopathological diagnosis of diffuse gliomas is subject to interobserver variation and correlates modestly with major prognostic and predictive molecular abnormalities. We investigated a series of patients with locally diagnosed anaplastic oligodendroglial tumors included in

  11. Neuromuscular disease classification system

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

    2013-06-01

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

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

    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.

  13. Molecular Diagnostics

    Choe, Hyonmin; Deirmengian, Carl A; Hickok, Noreen J.; Morrison, Tiffany N.; Tuan, Rocky S.

    2015-01-01

    Orthopaedic infections are complex conditions that require immediate diagnosis and accurate identification of the causative organisms to facilitate appropriate management. Conventional methodologies for diagnosis of these infections sometimes lack accuracy or sufficient rapidity. Current molecular diagnostics are an emerging area of bench-to-bedside research in orthopaedic infections. Examples of promising molecular diagnostics include measurement of a specific biomarker in the synovial fluid...

  14. Vehicle Classification by Lane Allowance

    Vishakha Gaikwad

    2014-12-01

    Full Text Available Classification of vehicles from video is used for analysis of traffic, self-driving systems or security systems. This analysis is based on shape, size, velocity and track of vehicles. These features characterize vehicle in background subtraction and feature extraction methods. Extraction is done by active contours and morphological operations. Extracted vehicles are classified by applying various classification techniques. The combination of features and classification techniques varies with the application. Proposed system, Uses combination of K Nearest Neighbor (KNN and Decision Tree techniques to overcome constraints. These constraints are instances of an object, overlapping of objects, and scaling factor. KNN is utilized to classify vehicle by size and lane. Decision tree manipulates the combination of these two features to classify accurately which results increased performance. This system classifies objects into three classes. These classes are four wheeler, bikers and heavy duty vehicle extracted from video.

  15. Automatic web services classification based on rough set theory

    陈立; 张英; 宋自林; 苗壮

    2013-01-01

    With development of web services technology, the number of existing services in the internet is growing day by day. In order to achieve automatic and accurate services classification which can be beneficial for service related tasks, a rough set theory based method for services classification was proposed. First, the services descriptions were preprocessed and represented as vectors. Elicited by the discernibility matrices based attribute reduction in rough set theory and taking into account the characteristic of decision table of services classification, a method based on continuous discernibility matrices was proposed for dimensionality reduction. And finally, services classification was processed automatically. Through the experiment, the proposed method for services classification achieves approving classification result in all five testing categories. The experiment result shows that the proposed method is accurate and could be used in practical web services classification.

  16. Proteomic classification of breast cancer.

    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.

  17. Molecular Tools for Rapid and Accurate Detection of Black Truffle (Tuber melanosporum Vitt. in Inoculated Nursery Plants and Commercial Plantations in Chile Uso de Marcadores Moleculares para la Detección Rápida y Precisa de Trufa Negra (Tuber melanosporum Vitt. en Plantas de Vivero y Plantaciones Comerciales de Chile

    Cecilia Cordero

    2011-09-01

    Full Text Available Truffle (Tuber melanosporum Vitt. culture is an agroforestry sector in Chile of increasing interest due to the high prices that truffles fetch in the national market and the recent evidence that its commercial production is possible in Chilean climatic and soil conditions. In this study, the efficiency of three methods of DNA extraction from a mix of 5 g of soil and roots from both nursery and field plants of Quercus ilex L. mycorrhized with T. melanosporum were evaluated, and a simple and reproducible protocol was established. Detection of T. melanosporum was performed by the technique of cleaved amplified polymorphic sequence (CAPS from amplicons generated with the primers ADL1 (5´-GTAACGATAAAGGCCATCTATAGG-3´ and ADL3 (5´-CGTTTTTCCTGAACTCTTCATCAC-3`, where a restriction fragment of 160 bp specific for T. melanosporum was generated, which allows the discrimination of this species from the rest of the species belonging to the Tuber sp. genus. Direct detection of T. melanosporum in one step was also obtained by polymerase chain reaction (PCR from total DNA isolated from mycorrhized roots and with the primers ITSML (5´-TGGCCATGTGTCAGATTTAGTA-3´ and ITSLNG (5´-TGATATGCTTAAGTTCAGCGGG-3´, generating a single amplicon of 440 bp. The molecular detection of T. melanosporum by the methods presented here will allow the rapid and accurate detection of mycorrhization of trees, both under nursery and field conditions. This technology will also provide more security to farmers by controlling the quality of the mycorrhized trees they will plant and also by following the mycorrhization status of established orchards.

  18. Molecular phylogeny of advanced snakes (Serpentes, Caenophidia) with an emphasis on South American Xenodontines: a revised classification and descriptions of new taxa

    Hussam Zaher; Felipe Gobbi Grazziotin; John E. Cadle; Robert W Murphy; Julio Cesar de Moura-Leite; Sandro L. Bonatto

    2009-01-01

    We present a molecular phylogenetic analysis of caenophidian (advanced) snakes using sequences from two mitochondrial genes (12S and 16S rRNA) and one nuclear (c-mos) gene (1681 total base pairs), and with 131 terminal taxa sampled from throughout all major caenophidian lineages but focussing on Neotropical xenodontines. Direct optimization parsimony analysis resulted in a well-resolved phylogenetic tree, which corroborates some clades identified in previous analyses and suggests new hypothes...

  19. Classification in Australia.

    McKinlay, John

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

  20. Classification in context

    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 cla...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  1. Multi-borders classification

    Mills, Peter

    2014-01-01

    The number of possible methods of generalizing binary classification to multi-class classification increases exponentially with the number of class labels. Often, the best method of doing so will be highly problem dependent. Here we present classification software in which the partitioning of multi-class classification problems into binary classification problems is specified using a recursive control language.

  2. Accurate phase-shift velocimetry in rock

    Shukla, Matsyendra Nath; Vallatos, Antoine; Phoenix, Vernon R.; Holmes, William M.

    2016-06-01

    Spatially resolved Pulsed Field Gradient (PFG) velocimetry techniques can provide precious information concerning flow through opaque systems, including rocks. This velocimetry data is used to enhance flow models in a wide range of systems, from oil behaviour in reservoir rocks to contaminant transport in aquifers. Phase-shift velocimetry is the fastest way to produce velocity maps but critical issues have been reported when studying flow through rocks and porous media, leading to inaccurate results. Combining PFG measurements for flow through Bentheimer sandstone with simulations, we demonstrate that asymmetries in the molecular displacement distributions within each voxel are the main source of phase-shift velocimetry errors. We show that when flow-related average molecular displacements are negligible compared to self-diffusion ones, symmetric displacement distributions can be obtained while phase measurement noise is minimised. We elaborate a complete method for the production of accurate phase-shift velocimetry maps in rocks and low porosity media and demonstrate its validity for a range of flow rates. This development of accurate phase-shift velocimetry now enables more rapid and accurate velocity analysis, potentially helping to inform both industrial applications and theoretical models.

  3. Interactive multiclass segmentation using superpixel classification

    Mathieu, Bérengère; Crouzil, Alain; Puel, Jean-Baptiste

    2015-01-01

    This paper adresses the problem of interactive multiclass segmentation. We propose a fast and efficient new interactive segmentation method called Superpixel Classification-based Interactive Segmentation (SCIS). From a few strokes drawn by a human user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SCIS uses superpixel over-segmentation and support vector machine classification. In this paper, we demonstrate that SCIS sig...

  4. Classification and knowledge

    Kurtz, Michael J.

    1989-01-01

    Automated procedures to classify objects are discussed. The classification problem is reviewed, and the relation of epistemology and classification is considered. The classification of stellar spectra and of resolved images of galaxies is addressed.

  5. Hazard classification methodology

    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

  6. Remote Sensing Information Classification

    Rickman, Douglas L.

    2008-01-01

    This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

  7. Texture Classification Based on Texton Features

    U Ravi Babu

    2012-08-01

    Full Text Available Texture Analysis plays an important role in the interpretation, understanding and recognition of terrain, biomedical or microscopic images. To achieve high accuracy in classification the present paper proposes a new method on textons. Each texture analysis method depends upon how the selected texture features characterizes image. Whenever a new texture feature is derived it is tested whether it precisely classifies the textures. Here not only the texture features are important but also the way in which they are applied is also important and significant for a crucial, precise and accurate texture classification and analysis. The present paper proposes a new method on textons, for an efficient rotationally invariant texture classification. The proposed Texton Features (TF evaluates the relationship between the values of neighboring pixels. The proposed classification algorithm evaluates the histogram based techniques on TF for a precise classification. The experimental results on various stone textures indicate the efficacy of the proposed method when compared to other methods.

  8. Classification and Analysis of Computer Network Traffic

    Bujlow, Tomasz

    2014-01-01

    of traffic for academic purposes. We define the objective of this thesis as finding a way to evaluate the performance of various applications in a high-speed Internet infrastructure. To satisfy the objective, we needed to answer a number of research questions. The biggest extent of them concern techniques...... classification (as by using transport layer port numbers, Deep Packet Inspection (DPI), statistical classification) and assessed their usefulness in particular areas. We found that the classification techniques based on port numbers are not accurate anymore as most applications use dynamic port numbers, while...

  9. A new classification of viviparous brotulas (Bythitidae) – with family status for Dinematichthyidae – based on molecular, morphological and fossil data

    Møller, Peter Rask; Knudsen, Steen Wilhelm; Schwarzhans, Werner;

    2016-01-01

    in the male copulatory apparatus. Previous use of the caudal fin separation or fusion with vertical fins is ambiguous. Age estimates based on calibrated molecular phylogeny agrees with fossil data, giving an origin within the Cretaceous (between 84 and 104 mya) for a common ancestor to Ophidiiformes.......The order Ophidiiformes is a large but not very well known group of fishes, unique among teleosts for showing high diversity in both deep sea and shallow reef habitats. The current classification includes more than 500 species, 115 genera and four families, based primarily on mode of reproduction...... status. Here we study the viviparous families phylogenetically with partial mitochondrial (nd4, 16s) and nuclear(Rag1) DNA sequences (2194 bp). We use a fossil calibration of otolith-based taxa to calibrate the age of the clade comprising bythitid and dinematicththyid representatives, together...

  10. How many molecular subtypes? Implications of the unique tumor principle in personalized medicine

    Ogino, Shuji; FUCHS, CHARLES S.; Giovannucci, Edward

    2012-01-01

    Cancers are complex multifactorial diseases. For centuries, conventional organ-based classification system (i.e., breast cancer, lung cancer, colon cancer, colorectal cancer, prostate cancer, lymphoma, leukemia, and so on) has been utilized. Recently, molecular diagnostics has become an essential component in clinical decision-making. However, tumor evolution and behavior cannot accurately be predicted, despite numerous research studies reporting promising tumor biomarkers. To advance molecul...

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

    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.

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

    Verscheure M.; Lognay G.; Marlier M.

    2002-01-01

    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.

  13. Revue bibliographique: les methodes chimiques d'identification et de classification des champignons.

    Verscheure, M.; Lognay, Georges; Marlier, M.

    2002-01-01

    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.

  14. Clasificación en subtipos moleculares de tumores de mama de pequeños animales mediante métodos inmunohistoquímicos Classification in molecular subtypes of breast tumors of small animals through immunohistochemical methods

    Mª V. Ortega García

    2013-03-01

    Full Text Available Antecedentes y Objetivos: Aplicar un panel de anticuerpos (anti -receptor de progesterona, -receptor de estrógenos, -receptor del factor de crecimiento epidérmico humano 2 y -citoqueratina 14 utilizando métodos inmunohistoquímicos en tumores mamarios de pequeños animales para analizar su clasificación en subtipos moleculares y su asociación con la invasión, el grado y el tipo histológico de las neoplasias. Material y Métodos: Muestras de tumores mamarios malignos, 10 de la especie canina y 3 de la felina. Control positivo interno: glándula mamaria no tumoral adyacente a las neoplasias. Resultados: El 23% (3/13 de los tumores fueron del subtipo luminal B, el 23% (3/13 fueron HER2 positivos, el 46% (6/13 fueron basales y el 7,6% (1/13 no se pudieron clasificar porque no expresaron ninguno de los marcadores tumorales analizados. Ningún caso fue del subtipo luminal A. Los 6 tumores basales fueron de grado II o III y presentaban o infiltración de solo el estroma o también invasión vascular. Dos tercios de los tumores HER2 positivos presentaban infiltración del estroma y 1/2 tumores resultó ser de grado II. Los tumores luminal B, 2/3 fueron de grado II o III. Todos los controles internos fueron positivos. No se encontraron diferencias significativas en la distribución de los subtipos moleculares entre los diferentes grupos de las variables invasión (p-valor=0,26, ni grado de malignidad (p-valor=0,42. Sí hubo diferencias en el límite de la significación estadística en la distribución de los subtipos moleculares entre los diferentes grupos de la variable tipo histológico (p=0,08. Conclusiones: La aplicación del panel de anticuerpos ha permitido descubrir 4 (luminal B, HER2, basal y sin clasificar de los 5 subtipos moleculares posibles.Antecedents and objectives: to apply an antibodies panel (anti-progesterone receptor -estrogen receptor, -human epidermal growth factor receptor 2 and cytokeratin 14 using immunohistochemical

  15. Accurate determination of multiple sets of single molecular conductance of Au/1,6-hexanedithiol/Au break junctions by ultra-high vacuum-scanning tunneling microscope and analyses of individual current-separation curves

    The effect of the binding sites of the terminal groups -S on gold on currents through a single molecular junction (MJ) of Au/1,6-hexanedithiol/Au was studied by measuring current-separation (i-s) curves during repeated formation of a break junction in UHV-STM. Three different single molecular conductance (SMC) values (i.e. Gm(HC), Gm(MC) and Gm(LC)) were found by a careful analysis of corrected current histograms for background tunneling currents using a previously developed robust statistical analysis. Here, HC, MC and LC represent a single MJ with high, medium and low conductance, respectively. These three SMC values are attributed to three different contact modes (i.e. strong-strong, strong-weak (or weak-strong) and weak-weak bindings at the two ends). In addition to these three SMC values due to the different contacts, another lower SMC value was newly observed in the corrected histogram. The presence of the fourth SMC is specific to MJs of alkanedithiols and is attributable to LC of a single alkylene chain with gauche rich conformation, which has a lower SMC value than that of LC with all-trans conformation as proposed previously (Fujihira M et al 2006 Phys. Chem. Chem. Phys. 8 3876). Due to the effects of the contact and the conformational change, it was difficult to determine six different SMC values corresponding to two different conformations (i.e. gauche-rich versus all-trans) with three different contacts (i.e. HC, MC and LC). In addition to this complexity, the current steps corresponding to HC, MC and LC almost always appeared in this order in measured i-s curves during separation. The current step observed here could not only be a contribution from a single molecule, but also contributions from a few groups of molecules that happen to link gold atoms of the substrate with those of the tip apex. Therefore, the SMC value for HC obtained as a peak or a set of peaks in the current histogram could be based upon the sum of the current of HC and those of MCs

  16. Improving the accuracy of gene expression profile classification with Lorenz curves and Gini ratios.

    Tran, Quoc-Nam

    2011-01-01

    Microarrays are a new technology with great potential to provide accurate medical diagnostics, help to find the right treatment for many diseases such as cancers, and provide a detailed genome-wide molecular portrait of cellular states. In this chapter, we show how Lorenz Curves and Gini Ratios can be modified to improve the accuracy of gene expression profile classification. Experimental results with different classification algorithms using additional techniques and strategies for improving the accuracy such as the principal component analysis, the correlation-based feature subset selection, and the consistency subset evaluation technique for the task of classifying lung adenocarcinomas from gene expression show that our method find more optimal genes than SAM. PMID:21431549

  17. Molecular Morphology

    Donath, Alexander

    2011-01-01

    A fundamental problem in biology is the reconstruction of the relatedness of all (extant) species. Traditionally, systematists employ visually recognizable characters of organisms for classification and evolutionary analysis. Recent developments in molecular and computational biology, however, lead to a whole different perspective on how to address the problem of inferring relatedness. The discovery of molecules, carrying genetic information, and the comparison of their primary structure h...

  18. Classification of the web

    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...

  19. Classification of neocortical interneurons using affinity propagation

    Santana, Roberto; McGarry, Laura M.; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neu...

  20. Classification of neocortical interneurons using affinity propagation

    Roberto eSantana; Laura eMcGarry; Concha eBielza; Pedro eLarrañaga; Rafael eYuste

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbi...

  1. Towards functional classification of neuronal types

    Sharpee, Tatyana O.

    2014-01-01

    How many types of neurons are there in the brain? This basic neuroscience question remains unsettled despite many decades of research. Classification schemes have been proposed based on anatomical, electrophysiological or molecular properties. However, different schemes do not always agree with each other. This raises the question of whether one can classify neurons based on their function directly. For example, among sensory neurons, can a classification scheme be devised that is based on th...

  2. Clasificación en subtipos moleculares de tumores de mama de pequeños animales mediante métodos inmunohistoquímicos Classification in molecular subtypes of breast tumors of small animals through immunohistochemical methods

    Mª V. Ortega García; J.A. Galán Torres; Y. Millán Ruiz; R. Sánchez Céspedes; J. Martín de las Mulas González-Albo

    2013-01-01

    Antecedentes y Objetivos: Aplicar un panel de anticuerpos (anti -receptor de progesterona, -receptor de estrógenos, -receptor del factor de crecimiento epidérmico humano 2 y -citoqueratina 14) utilizando métodos inmunohistoquímicos en tumores mamarios de pequeños animales para analizar su clasificación en subtipos moleculares y su asociación con la invasión, el grado y el tipo histológico de las neoplasias. Material y Métodos: Muestras de tumores mamarios malignos, 10 de la especie canina y 3...

  3. Towards accurate emergency response behavior

    Nuclear reactor operator emergency response behavior has persisted as a training problem through lack of information. The industry needs an accurate definition of operator behavior in adverse stress conditions, and training methods which will produce the desired behavior. Newly assembled information from fifty years of research into human behavior in both high and low stress provides a more accurate definition of appropriate operator response, and supports training methods which will produce the needed control room behavior. The research indicates that operator response in emergencies is divided into two modes, conditioned behavior and knowledge based behavior. Methods which assure accurate conditioned behavior, and provide for the recovery of knowledge based behavior, are described in detail

  4. Towards the automatic classification of neurons.

    Armañanzas, Rubén; Ascoli, Giorgio A

    2015-05-01

    The classification of neurons into types has been much debated since the inception of modern neuroscience. Recent experimental advances are accelerating the pace of data collection. The resulting growth of information about morphological, physiological, and molecular properties encourages efforts to automate neuronal classification by powerful machine learning techniques. We review state-of-the-art analysis approaches and the availability of suitable data and resources, highlighting prominent challenges and opportunities. The effective solution of the neuronal classification problem will require continuous development of computational methods, high-throughput data production, and systematic metadata organization to enable cross-laboratory integration. PMID:25765323

  5. Scalable metagenomic taxonomy classification using a reference genome database

    Ames, Sasha K.; Hysom, David A.; Shea N. Gardner; Lloyd, G. Scott; Gokhale, Maya B.; Allen, Jonathan E.

    2013-01-01

    Motivation: Deep metagenomic sequencing of biological samples has the potential to recover otherwise difficult-to-detect microorganisms and accurately characterize biological samples with limited prior knowledge of sample contents. Existing metagenomic taxonomic classification algorithms, however, do not scale well to analyze large metagenomic datasets, and balancing classification accuracy with computational efficiency presents a fundamental challenge. Results: A method is presented to shift...

  6. Accurate determination of antenna directivity

    Dich, Mikael

    1997-01-01

    The derivation of a formula for accurate estimation of the total radiated power from a transmitting antenna for which the radiated power density is known in a finite number of points on the far-field sphere is presented. The main application of the formula is determination of directivity from power...

  7. Texture Classification based on Gabor Wavelet

    Amandeep Kaur

    2012-07-01

    Full Text Available This paper presents the comparison of Texture classification algorithms based on Gabor Wavelets. The focus of this paper is on feature extraction scheme for texture classification. The texture feature for an image can be classified using texture descriptors. In this paper we have used Homogeneous texture descriptor that uses Gabor Wavelets concept. For texture classification, we have used online texture database that is Brodatz’s database and three advanced well known classifiers: Support Vector Machine, K-nearest neighbor method and decision tree induction method. The results shows that classification using Support vector machines gives better results as compare to the other classifiers. It can accurately discriminate between a testing image data and training data.

  8. La LC classification come linked data

    Kevin Ford

    2013-01-01

    Full Text Available In 2009 and in 2011, the Library of Congress made two of its largest authority files – Subject Headings and Names – available as linked data via LC’s Linked Data Service, ID.LOC.GOV. Both are offered in MADS/RDF and SKOS. It is LC’s objective, in 2012, to publish another of its largest authority files as linked data: LC Classification. Whereas the source records for Subject Headings and Names are encoded in the MARC Authority format, from which there is a relatively straightforward mapping to MADS/RDF and SKOS, LC Classification records rely on the MARC Classification format. Mapping from LC Classification to MADS/RDF or SKOS has been a little more challenging. For example, records that represent classification ranges, which are not Concepts intended to be assigned, are not easily accommodated in SKOS. This presents additional problems when needing to accurately represent the relationships in RDF for LC Classification. With comparison to the publication of LCSH and Names at ID.LOC.GOV, this paper will examine issues encountered – and how those challenges were addressed – during the conversion of LC Classification to MADS/RDF and SKOS for release as linked data at ID.LOC.GOV.

  9. Typology, classification and systematization of innovative projects and initiatives in the company

    Baklanova Julia O.

    2012-04-01

    Full Text Available The author presents a comparison of definitions of typology, classification and systematization, and treats them as an example of innovative projects and initiatives of the company. The basis of typology and classification laid methodical Benko K., Mc Farlan. In order to obtain a more accurate result it is necessary to integrate the task typology, classification and systematization.

  10. Molecular classification of non-muscle-invasive bladder cancer (pTa low-grade, pT1 low-grade, and pT1 high-grade subgroups) using methylation of tumor-suppressor genes.

    Sacristan, Raquel; Gonzalez, Carolina; Fernández-Gómez, Jesus M; Fresno, Florentino; Escaf, Safwan; Sánchez-Carbayo, Marta

    2014-09-01

    The role of epigenetics in distinguishing pathological and clinical subgroups in bladder cancer is not fully characterized. We evaluated whether methylation of tumor-suppressor genes (TSGs) would classify non-muscle-invasive (NMI) bladder cancer subgroups and predict outcome. A retrospective design included the following paraffin-embedded primary NMI tumor types (n = 251): pTa low grade (LG) (n = 79), pT1LG (n = 81), and pT1 high grade (HG) (n = 91). Methylation of 25 TSGs was measured using methylation-specific, multiplex, ligation-dependent probe amplification. The TSGs most frequently methylated in the overall series were STK11 (96.8%), MGMT2 (64.5%), RARB (63.0%), and GATA5 (63.0%). TSG methylation correlated to clinicopathological variables in each subgroup and in the overall NMI series. Methylation of RARB, CD44, PAX5A, GSTP1, IGSF4 (CADM1), PYCARD, CDH13, TP53, and GATA5 classified pTa versus pT1 tumors whereas RARB, CD44, GSTP1, IGSF4, CHFR, PYCARD, TP53, STK11, and GATA5 distinguished LG versus HG tumors. Multivariate analyses indicated that PAX5A, WT1, and BRCA1 methylation independently predicted recurrence in pTaLG, PAX6, ATM, CHFR, and RB1 in pT1LG disease; PYCARD, in pT1HG disease; and PAX5A and RB1, in the overall series. Methylation of TSGs provided a molecular classification of NMI disease according to clinicopathological factors. Furthermore, TSG methylation predicted recurrence in NMI subgroups. PMID:24998186

  11. On the importance of having accurate data for astrophysical modelling

    Lique, Francois

    2016-06-01

    The Herschel telescope and the ALMA and NOEMA interferometers have opened new windows of observation for wavelengths ranging from far infrared to sub-millimeter with spatial and spectral resolutions previously unmatched. To make the most of these observations, an accurate knowledge of the physical and chemical processes occurring in the interstellar and circumstellar media is essential.In this presentation, I will discuss what are the current needs of astrophysics in terms of molecular data and I will show that accurate molecular data are crucial for the proper determination of the physical conditions in molecular clouds.First, I will focus on collisional excitation studies that are needed for molecular lines modelling beyond the Local Thermodynamic Equilibrium (LTE) approach. In particular, I will show how new collisional data for the HCN and HNC isomers, two tracers of star forming conditions, have allowed solving the problem of their respective abundance in cold molecular clouds. I will also present the last collisional data that have been computed in order to analyse new highly resolved observations provided by the ALMA interferometer.Then, I will present the calculation of accurate rate constants for the F+H2 → HF+H and Cl+H2 ↔ HCl+H reactions, which have allowed a more accurate determination of the physical conditions in diffuse molecular clouds. I will also present the recent work on the ortho-para-H2 conversion due to hydrogen exchange that allow more accurate determination of the ortho-to-para-H2 ratio in the universe and that imply a significant revision of the cooling mechanism in astrophysical media.

  12. Accurate Kirkwood-Buff Integrals from Molecular Dynamics Simulations

    Wedberg, Nils Hejle Rasmus Ingemar; O'Connell, John P.; Peters, Günther H.J.;

    2010-01-01

    theoretical limiting behaviour on the corresponding direct correlation function. The method is evaluated for the pure Lennard-Jones and Stockmayer fluids. The results are verified by comparing pure fluid isothermal compressibilities obtained from the KB integrals with values from derivatives of equations of...

  13. Hand eczema classification

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

    2008-01-01

    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...... classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  14. Small Sample Issues for Microarray-Based Classification

    Dougherty, Edward R

    2006-01-01

    In order to study the molecular biological differences between normal and diseased tissues, it is desirable to perform classification among diseases and stages of disease using microarray-based gene-expression values. Owing to the limited number of microarrays typically used in these studies, serious issues arise with respect to the design, performance and analysis of classifiers based on microarray data. This paper reviews some fundamental issues facing small-sample classification: classific...

  15. Classification of follicular cell-derived thyroid cancer by global RNA profiling

    Rossing, Maria

    2013-01-01

    classification will not only contribute to our biological insight but also improve clinical and pathological examinations, thus advancing thyroid tumour diagnosis and ultimately preventing superfluous surgery. This review evaluates the status of classification and biological insights gained from molecular...... classifiers that may differentiate malignant from benign thyroid nodules. Molecular classification models based on global RNA profiles from fine-needle aspirations are currently being evaluated; results are preliminary and lack validation in prospective clinical trials. There is no doubt that molecular...

  16. Classification of articulators.

    Rihani, A

    1980-03-01

    A simple classification in familiar terms with definite, clear characteristics can be adopted. This classification system is based on the number of records used and the adjustments necessary for the articulator to accept these records. The classification divides the articulators into nonadjustable, semiadjustable, and fully adjustable articulators (Table I). PMID:6928204

  17. Aircraft Operations Classification System

    Harlow, Charles; Zhu, Weihong

    2001-01-01

    Accurate data is important in the aviation planning process. In this project we consider systems for measuring aircraft activity at airports. This would include determining the type of aircraft such as jet, helicopter, single engine, and multiengine propeller. Some of the issues involved in deploying technologies for monitoring aircraft operations are cost, reliability, and accuracy. In addition, the system must be field portable and acceptable at airports. A comparison of technologies was conducted and it was decided that an aircraft monitoring system should be based upon acoustic technology. A multimedia relational database was established for the study. The information contained in the database consists of airport information, runway information, acoustic records, photographic records, a description of the event (takeoff, landing), aircraft type, and environmental information. We extracted features from the time signal and the frequency content of the signal. A multi-layer feed-forward neural network was chosen as the classifier. Training and testing results were obtained. We were able to obtain classification results of over 90 percent for training and testing for takeoff events.

  18. Cirrhosis classification based on texture classification of random features.

    Liu, Hui; Shao, Ying; Guo, Dongmei; Zheng, Yuanjie; Zhao, Zuowei; Qiu, Tianshuang

    2014-01-01

    Accurate staging of hepatic cirrhosis is important in investigating the cause and slowing down the effects of cirrhosis. Computer-aided diagnosis (CAD) can provide doctors with an alternative second opinion and assist them to make a specific treatment with accurate cirrhosis stage. MRI has many advantages, including high resolution for soft tissue, no radiation, and multiparameters imaging modalities. So in this paper, multisequences MRIs, including T1-weighted, T2-weighted, arterial, portal venous, and equilibrium phase, are applied. However, CAD does not meet the clinical needs of cirrhosis and few researchers are concerned with it at present. Cirrhosis is characterized by the presence of widespread fibrosis and regenerative nodules in the hepatic, leading to different texture patterns of different stages. So, extracting texture feature is the primary task. Compared with typical gray level cooccurrence matrix (GLCM) features, texture classification from random features provides an effective way, and we adopt it and propose CCTCRF for triple classification (normal, early, and middle and advanced stage). CCTCRF does not need strong assumptions except the sparse character of image, contains sufficient texture information, includes concise and effective process, and makes case decision with high accuracy. Experimental results also illustrate the satisfying performance and they are also compared with typical NN with GLCM. PMID:24707317

  19. Fast and accurate estimation for astrophysical problems in large databases

    Richards, Joseph W.

    2010-10-01

    A recent flood of astronomical data has created much demand for sophisticated statistical and machine learning tools that can rapidly draw accurate inferences from large databases of high-dimensional data. In this Ph.D. thesis, methods for statistical inference in such databases will be proposed, studied, and applied to real data. I use methods for low-dimensional parametrization of complex, high-dimensional data that are based on the notion of preserving the connectivity of data points in the context of a Markov random walk over the data set. I show how this simple parameterization of data can be exploited to: define appropriate prototypes for use in complex mixture models, determine data-driven eigenfunctions for accurate nonparametric regression, and find a set of suitable features to use in a statistical classifier. In this thesis, methods for each of these tasks are built up from simple principles, compared to existing methods in the literature, and applied to data from astronomical all-sky surveys. I examine several important problems in astrophysics, such as estimation of star formation history parameters for galaxies, prediction of redshifts of galaxies using photometric data, and classification of different types of supernovae based on their photometric light curves. Fast methods for high-dimensional data analysis are crucial in each of these problems because they all involve the analysis of complicated high-dimensional data in large, all-sky surveys. Specifically, I estimate the star formation history parameters for the nearly 800,000 galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 7 spectroscopic catalog, determine redshifts for over 300,000 galaxies in the SDSS photometric catalog, and estimate the types of 20,000 supernovae as part of the Supernova Photometric Classification Challenge. Accurate predictions and classifications are imperative in each of these examples because these estimates are utilized in broader inference problems

  20. Accurate Image Super-Resolution Using Very Deep Convolutional Networks

    Kim, Jiwon; Lee, Jung Kwon; Lee, Kyoung Mu

    2015-01-01

    We present a highly accurate single-image super-resolution (SR) method. Our method uses a very deep convolutional network inspired by VGG-net used for ImageNet classification \\cite{simonyan2015very}. We find increasing our network depth shows a significant improvement in accuracy. Our final model uses 20 weight layers. By cascading small filters many times in a deep network structure, contextual information over large image regions is exploited in an efficient way. With very deep networks, ho...

  1. Automatic classification of blank substrate defects

    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

  2. Quality-Oriented Classification of Aircraft Material Based on SVM

    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.

  3. Accurate ab initio spin densities

    Boguslawski, Katharina; Legeza, Örs; Reiher, Markus

    2012-01-01

    We present an approach for the calculation of spin density distributions for molecules that require very large active spaces for a qualitatively correct description of their electronic structure. Our approach is based on the density-matrix renormalization group (DMRG) algorithm to calculate the spin density matrix elements as basic quantity for the spatially resolved spin density distribution. The spin density matrix elements are directly determined from the second-quantized elementary operators optimized by the DMRG algorithm. As an analytic convergence criterion for the spin density distribution, we employ our recently developed sampling-reconstruction scheme [J. Chem. Phys. 2011, 134, 224101] to build an accurate complete-active-space configuration-interaction (CASCI) wave function from the optimized matrix product states. The spin density matrix elements can then also be determined as an expectation value employing the reconstructed wave function expansion. Furthermore, the explicit reconstruction of a CA...

  4. Accurate Modeling of Advanced Reflectarrays

    Zhou, Min

    of the incident field, the choice of basis functions, and the technique to calculate the far-field. Based on accurate reference measurements of two offset reflectarrays carried out at the DTU-ESA Spherical NearField Antenna Test Facility, it was concluded that the three latter factors are particularly important...... to the conventional phase-only optimization technique (POT), the geometrical parameters of the array elements are directly optimized to fulfill the far-field requirements, thus maintaining a direct relation between optimization goals and optimization variables. As a result, better designs can be obtained compared...... using the GDOT to demonstrate its capabilities. To verify the accuracy of the GDOT, two offset contoured beam reflectarrays that radiate a high-gain beam on a European coverage have been designed and manufactured, and subsequently measured at the DTU-ESA Spherical Near-Field Antenna Test Facility...

  5. Accurate thickness measurement of graphene

    Shearer, Cameron J.; Slattery, Ashley D.; Stapleton, Andrew J.; Shapter, Joseph G.; Gibson, Christopher T.

    2016-03-01

    Graphene has emerged as a material with a vast variety of applications. The electronic, optical and mechanical properties of graphene are strongly influenced by the number of layers present in a sample. As a result, the dimensional characterization of graphene films is crucial, especially with the continued development of new synthesis methods and applications. A number of techniques exist to determine the thickness of graphene films including optical contrast, Raman scattering and scanning probe microscopy techniques. Atomic force microscopy (AFM), in particular, is used extensively since it provides three-dimensional images that enable the measurement of the lateral dimensions of graphene films as well as the thickness, and by extension the number of layers present. However, in the literature AFM has proven to be inaccurate with a wide range of measured values for single layer graphene thickness reported (between 0.4 and 1.7 nm). This discrepancy has been attributed to tip-surface interactions, image feedback settings and surface chemistry. In this work, we use standard and carbon nanotube modified AFM probes and a relatively new AFM imaging mode known as PeakForce tapping mode to establish a protocol that will allow users to accurately determine the thickness of graphene films. In particular, the error in measuring the first layer is reduced from 0.1-1.3 nm to 0.1-0.3 nm. Furthermore, in the process we establish that the graphene-substrate adsorbate layer and imaging force, in particular the pressure the tip exerts on the surface, are crucial components in the accurate measurement of graphene using AFM. These findings can be applied to other 2D materials.

  6. Recursive heuristic classification

    Wilkins, David C.

    1994-01-01

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

  7. Security classification of information

    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.

  8. A More Accurate Fourier Transform

    Courtney, Elya

    2015-01-01

    Fourier transform methods are used to analyze functions and data sets to provide frequencies, amplitudes, and phases of underlying oscillatory components. Fast Fourier transform (FFT) methods offer speed advantages over evaluation of explicit integrals (EI) that define Fourier transforms. This paper compares frequency, amplitude, and phase accuracy of the two methods for well resolved peaks over a wide array of data sets including cosine series with and without random noise and a variety of physical data sets, including atmospheric $\\mathrm{CO_2}$ concentrations, tides, temperatures, sound waveforms, and atomic spectra. The FFT uses MIT's FFTW3 library. The EI method uses the rectangle method to compute the areas under the curve via complex math. Results support the hypothesis that EI methods are more accurate than FFT methods. Errors range from 5 to 10 times higher when determining peak frequency by FFT, 1.4 to 60 times higher for peak amplitude, and 6 to 10 times higher for phase under a peak. The ability t...

  9. Classification of different patterns of pulmonary adenocarcinomas.

    Truini, Anna; Santos Pereira, Poliana; Cavazza, Alberto; Spagnolo, Paolo; Nosseir, Sofia; Longo, Lucia; Jukna, Agita; Lococo, Filippo; Vincenzi, Giada; Bogina, Giuseppe; Tiseo, Marcello; Rossi, Giulio

    2015-10-01

    The epidemic increase of adenocarcinoma histology accounting for more than 50% of primary lung malignancies and the advent of effective molecular targeted-therapies against specific gene alterations characterizing this tumor type have led to the reconsideration of the pathologic classification of lung cancer. The new 2015 WHO classification provided the basis for a multidisciplinary approach emphasizing the close correlation among clinical, radiologic and molecular characteristics and histopathologic pattern of lung adenocarcinoma. The terms 'bronchioloalveolar carcinoma' and 'mixed adenocarcinoma' have been eliminated, introducing the concepts of 'adenocarcinoma in situ', 'minimally invasive adenocarcinoma' and the use of descriptive predominant patterns in invasive adenocarcinomas (lepidic, acinar, papillary, solid and micropapillary patterns). 'Invasive mucinous adenocarcinoma' is the new definition for mucinous bronchioloalveolar carcinoma, and some variants of invasive adenocarcinoma have been included, namely colloid, enteric and fetal-type adenocarcinomas. A concise update of the immunomorphologic, radiological and molecular characteristics of the different histologic patterns of lung adenocarcinoma is reported here. PMID:26313326

  10. Classiology and soil classification

    Rozhkov, V. A.

    2012-03-01

    Classiology can be defined as a science studying the principles and rules of classification of objects of any nature. The development of the theory of classification and the particular methods for classifying objects are the main challenges of classiology; to a certain extent, they are close to the challenges of pattern recognition. The methodology of classiology integrates a wide range of methods and approaches: from expert judgment to formal logic, multivariate statistics, and informatics. Soil classification assumes generalization of available data and practical experience, formalization of our notions about soils, and their representation in the form of an information system. As an information system, soil classification is designed to predict the maximum number of a soil's properties from the position of this soil in the classification space. The existing soil classification systems do not completely satisfy the principles of classiology. The violation of logical basis, poor structuring, low integrity, and inadequate level of formalization make these systems verbal schemes rather than classification systems sensu stricto. The concept of classification as listing (enumeration) of objects makes it possible to introduce the notion of the information base of classification. For soil objects, this is the database of soil indices (properties) that might be applied for generating target-oriented soil classification system. Mathematical methods enlarge the prognostic capacity of classification systems; they can be applied to assess the quality of these systems and to recognize new soil objects to be included in the existing systems. The application of particular principles and rules of classiology for soil classification purposes is discussed in this paper.

  11. Efficient Pairwise Multilabel Classification

    Loza Mencía, Eneldo

    2013-01-01

    Multilabel classification learning is the task of learning a mapping between objects and sets of possibly overlapping classes and has gained increasing attention in recent times. A prototypical application scenario for multilabel classification is the assignment of a set of keywords to a document, a frequently encountered problem in the text classification domain. With upcoming Web 2.0 technologies, this domain is extended by a wide range of tag suggestion tasks and the trend definitely...

  12. Classifier in Age classification

    B. Santhi; R.Seethalakshmi

    2012-01-01

    Face is the important feature of the human beings. We can derive various properties of a human by analyzing the face. The objective of the study is to design a classifier for age using facial images. Age classification is essential in many applications like crime detection, employment and face detection. The proposed algorithm contains four phases: preprocessing, feature extraction, feature selection and classification. The classification employs two class labels namely child and Old. This st...

  13. Text Classification Using Sentential Frequent Itemsets

    Shi-Zhu Liu; He-Ping Hu

    2007-01-01

    Text classification techniques mostly rely on single term analysis of the document data set, while more concepts,especially the specific ones, are usually conveyed by set of terms. To achieve more accurate text classifier, more informative feature including frequent co-occurring words in the same sentence and their weights are particularly important in such scenarios. In this paper, we propose a novel approach using sentential frequent itemset, a concept comes from association rule mining, for text classification, which views a sentence rather than a document as a transaction, and uses a variable precision rough set based method to evaluate each sentential frequent itemset's contribution to the classification. Experiments over the Reuters and newsgroup corpus are carried out, which validate the practicability of the proposed system.

  14. AGN Zoo and Classifications of Active Galaxies

    Mickaelian, Areg M.

    2015-07-01

    We review the variety of Active Galactic Nuclei (AGN) classes (so-called "AGN zoo") and classification schemes of galaxies by activity types based on their optical emission-line spectrum, as well as other parameters and other than optical wavelength ranges. A historical overview of discoveries of various types of active galaxies is given, including Seyfert galaxies, radio galaxies, QSOs, BL Lacertae objects, Starbursts, LINERs, etc. Various kinds of AGN diagnostics are discussed. All known AGN types and subtypes are presented and described to have a homogeneous classification scheme based on the optical emission-line spectra and in many cases, also other parameters. Problems connected with accurate classifications and open questions related to AGN and their classes are discussed and summarized.

  15. An Ensemble Classification Algorithm for Hyperspectral Images

    K.Kavitha

    2014-04-01

    Full Text Available Hyperspectral image analysis has been used for many purposes in environmental monitoring, remote sensing, vegetation research and also for land cover classification. A hyperspectral image consists of many layers in which each layer represents a specific wavelength. The layers stack on top of one another making a cube-like image for entire spectrum. This work aims to classify the hyperspectral images and to produce a thematic map accurately. Spatial information of hyperspectral images is collected by applying morphological profile and local binary pattern. Support vector machine is an efficient classification algorithm for classifying the hyperspectral images. Genetic algorithm is used to obtain the best feature subjected for classification. Selected features are classified for obtaining the classes and to produce a thematic map. Experiment is carried out with AVIRIS Indian Pines and ROSIS Pavia University. Proposed method produces accuracy as 93% for Indian Pines and 92% for Pavia University.

  16. Aspects de la classification

    Mari, Jean-François; Napoli, Amedeo

    1996-01-01

    Les techniques de classification numérique ont toujours été présentes en reconnaissance des formes. Les réseaux de neurones montrent chaque jour leurs (très ?) bonnes propriétés de classification, et la classification se fait de plus en plus présente en représentation des connaissances. Ainsi, ce rapport présente, simplement dans un but introductif, les aspects mathématiques, statistiques, neuromimétiques et cognitifs de la classification.

  17. Ontologies vs. Classification Systems

    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....

  18. Acute pancreatitis - severity classification, complications and outcome

    Andersson, Bodil

    2010-01-01

    Acute pancreatitis, with an annual incidence of approximately 35 per 100 000 inhabitants in Sweden, is in most cases mild and self-limiting. Severe acute pancreatitis, affecting 10-15% of the cases is, however, associated with severe complications and even death. The optimal management of acute pancreatitis includes accurate early prediction of the disease severity. The aims of this thesis were to investigate early severity classification, complications and outcome in acute pancreatitis patie...

  19. Ensemble methods for noise in classification problems

    Verbaeten, Sofie; Van Assche, Anneleen

    2003-01-01

    Ensemble methods combine a set of classifiers to construct a new classifier that is (often) more accurate than any of its component classifiers. In this paper, we use ensemble methods to identify noisy training examples. More precisely, we consider the problem of mislabeled training examples in classification tasks, and address this problem by pre-processing the training set, i.e. by identifying and removing outliers from the training set. We study a number of filter techniques that are based...

  20. BIOPHARMACEUTICAL CLASSIFICATION SYSTEM AND BIOWAVER: AN OVERVIEW

    Puranik Prashant K; Kasar Sagar Ashok; Gadade Deepak Dilip; Mali Prabha R

    2011-01-01

    The biopharmaceutical classification system (BCS) has been developed to provide a scientific approach for classifying drug compounds based on solubility as related to dose and intestinal permeability in combination with the dissolution properties of the oral immediate release dosage form. BCS is to provide a regulatory tool for replacing certain bioequivalence (BE) studies by accurate in vitro dissolution tests. This review gives three dimensionless numbers which are used in BCS are absorptio...

  1. Protein structure database search and evolutionary classification

    Yang, Jinn-Moon; Tung, Chi-Hua

    2006-01-01

    As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using...

  2. Concepts of Classification and Taxonomy. Phylogenetic Classification

    Fraix-Burnet, Didier

    2016-01-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works. 1 Why phylogenetic tools in astrophysics? 1.1 History of classification The need for classifying living organisms is very ancient, and the first classification system can be dated back to the Greeks. The goal was very practical since it was intended to distinguish between eatable and toxic aliments, or kind and dangerous animals. Simple resemblance was used and has been used for centuries. Basically, until the XVIIIth...

  3. A jackknife-like method for classification and uncertainty assessment of multi-category tumor samples using gene expression information

    Bertrand Keith

    2010-04-01

    Full Text Available Abstract Background The use of gene expression profiling for the classification of human cancer tumors has been widely investigated. Previous studies were successful in distinguishing several tumor types in binary problems. As there are over a hundred types of cancers, and potentially even more subtypes, it is essential to develop multi-category methodologies for molecular classification for any meaningful practical application. Results A jackknife-based supervised learning method called paired-samples test algorithm (PST, coupled with a binary classification model based on linear regression, was proposed and applied to two well known and challenging datasets consisting of 14 (GCM dataset and 9 (NC160 dataset tumor types. The results showed that the proposed method improved the prediction accuracy of the test samples for the GCM dataset, especially when t-statistic was used in the primary feature selection. For the NCI60 dataset, the application of PST improved prediction accuracy when the numbers of used genes were relatively small (100 or 200. These improvements made the binary classification method more robust to the gene selection mechanism and the size of genes to be used. The overall prediction accuracies were competitive in comparison to the most accurate results obtained by several previous studies on the same datasets and with other methods. Furthermore, the relative confidence R(T provided a unique insight into the sources of the uncertainty shown in the statistical classification and the potential variants within the same tumor type. Conclusion We proposed a novel bagging method for the classification and uncertainty assessment of multi-category tumor samples using gene expression information. The strengths were demonstrated in the application to two bench datasets.

  4. Independent Comparison of Popular DPI Tools for Traffic Classification

    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...

  5. Library Classification 2020

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

  6. Musings on galaxy classification

    Classification schemes and their utility are discussed with a number of examples, particularly for cD galaxies. Data suggest that primordial turbulence rather than tidal torques is responsible for most of the presently observed angular momentum of galaxies. Finally, some of the limitations on present-day schemes for galaxy classification are pointed out. 54 references, 4 figures, 3 tables

  7. A survey of feature selection models for classification

    B. Kalpana

    2012-01-01

    Full Text Available The success of a machine learning algorithm depends on quality of data .The data given for classification, should not contain irrelevant or redundant attributes. This increases the processing time. The data set, selected for classification should contain the right attributes for accurate results. Feature selection is an essential data processing step, prior to applying a learning algorithm. Here we discuss some basic feature selection models and evaluation function. Experimental results are compared for individual datasets with filter and wrapper model.

  8. Multi-Organ Cancer Classification and Survival Analysis

    Bauer, Stefan; Carion, Nicolas; Schüffler, Peter; Fuchs, Thomas; Wild, Peter; Buhmann, Joachim M.

    2016-01-01

    Accurate and robust cell nuclei classification is the cornerstone for a wider range of tasks in digital and Computational Pathology. However, most machine learning systems require extensive labeling from expert pathologists for each individual problem at hand, with no or limited abilities for knowledge transfer between datasets and organ sites. In this paper we implement and evaluate a variety of deep neural network models and model ensembles for nuclei classification in renal cell cancer (RC...

  9. A proposal for the morphological classification and nomenclature of neurons

    Rong Jiang; Qiang Liu; Quan Liu; Shenquan Liu

    2011-01-01

    The morphological and functional characteristics of neurons are quite varied and complex. There is a need for a comprehensive approach for distinguishing and classifying neurons. Similar to the biological species classification system, this study proposes a morphological classification system for neurons based on principal component analysis. Based on four principal components of neuronal morphology derived from principal component analysis, a nomenclature system for neurons was obtained. This system can accurately distinguish between the same type of neuron from different species.

  10. Robust Eye Localization by Combining Classification and Regression Methods

    Pak Il Nam; Ri Song Jin; Peter Peer

    2014-01-01

    Eye localization is an important part in face recognition system, because its precision closely affects the performance of the system. In this paper we analyze the limitations of classification and regression methods and propose a robust and accurate eye localization method combining these two methods. The classification method in eye localization is robust, but its precision is not so high, while the regression method is sensitive to the initial position, but in case the initial position is ...

  11. A Novel Fault Classification Scheme Based on Least Square SVM

    Dubey, Harishchandra; Tiwari, A. K.; Nandita; Ray, P. K.; Mohanty, S. R.; Kishor, Nand

    2016-01-01

    This paper presents a novel approach for fault classification and section identification in a series compensated transmission line based on least square support vector machine. The current signal corresponding to one-fourth of the post fault cycle is used as input to proposed modular LS-SVM classifier. The proposed scheme uses four binary classifier; three for selection of three phases and fourth for ground detection. The proposed classification scheme is found to be accurate and reliable in ...

  12. Enhancing Accuracy of Plant Leaf Classification Techniques

    C. S. Sumathi

    2014-03-01

    Full Text Available Plants have become an important source of energy, and are a fundamental piece in the puzzle to solve the problem of global warming. Living beings also depend on plants for their food, hence it is of great importance to know about the plants growing around us and to preserve them. Automatic plant leaf classification is widely researched. This paper investigates the efficiency of learning algorithms of MLP for plant leaf classification. Incremental back propagation, Levenberg–Marquardt and batch propagation learning algorithms are investigated. Plant leaf images are examined using three different Multi-Layer Perceptron (MLP modelling techniques. Back propagation done in batch manner increases the accuracy of plant leaf classification. Results reveal that batch training is faster and more accurate than MLP with incremental training and Levenberg– Marquardt based learning for plant leaf classification. Various levels of semi-batch training used on 9 species of 15 sample each, a total of 135 instances show a roughly linear increase in classification accuracy.

  13. Photometric Supernova Classification with Machine Learning

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

    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.

  14. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

    Wang Lily

    2008-07-01

    Full Text Available Abstract Background Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate classification algorithms available for microarray gene expression data is a critical ingredient in order to develop the best possible molecular signatures for patient care. As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classification of such data. Recent work, however, suggests that random forest classifiers may outperform support vector machines in this domain. Results In the present paper we identify methodological biases of prior work comparing random forests and support vector machines and conduct a new rigorous evaluation of the two algorithms that corrects these limitations. Our experiments use 22 diagnostic and prognostic datasets and show that support vector machines outperform random forests, often by a large margin. Our data also underlines the importance of sound research design in benchmarking and comparison of bioinformatics algorithms. Conclusion We found that both on average and in the majority of microarray datasets, random forests are outperformed by support vector machines both in the settings when no gene selection is performed and when several popular gene selection methods are used.

  15. 38 CFR 4.46 - Accurate measurement.

    2010-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2010-07-01 2010-07-01 false Accurate measurement. 4... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate measurement of the length of stumps, excursion of joints, dimensions and location of scars with respect...

  16. The Evolution of Tumor Classification: A Role for Genomics?

    Bunn, Paul A.; Franklin, Wilbur; Doebele, Robert C.

    2013-01-01

    Lung cancers are divided into four types according to their histologic appearance. Therapeutic decisions are partly based on histology. A recent study indicates that certain molecular alterations associate with histology and therapies directed to these molecular changes improve outcome, indicating that genomic information should be incorporated into future tumor classification.

  17. Behavior Based Social Dimensions Extraction for Multi-Label Classification.

    Le Li

    Full Text Available Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes' behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA to model the network generation process, nodes' connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions.

  18. Behavior Based Social Dimensions Extraction for Multi-Label Classification.

    Li, Le; Xu, Junyi; Xiao, Weidong; Ge, Bin

    2016-01-01

    Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes' behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes' connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. PMID:27049849

  19. Behavior Based Social Dimensions Extraction for Multi-Label Classification

    Li, Le; Xu, Junyi; Xiao, Weidong; Ge, Bin

    2016-01-01

    Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes’ behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes’ connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. PMID:27049849

  20. Hyperspectral Data Classification Using Factor Graphs

    Makarau, A.; Müller, R.; Palubinskas, G.; Reinartz, P.

    2012-07-01

    Accurate classification of hyperspectral data is still a competitive task and new classification methods are developed to achieve desired tasks of hyperspectral data use. The objective of this paper is to develop a new method for hyperspectral data classification ensuring the classification model properties like transferability, generalization, probabilistic interpretation, etc. While factor graphs (undirected graphical models) are unfortunately not widely employed in remote sensing tasks, these models possess important properties such as representation of complex systems to model estimation/decision making tasks. In this paper we present a new method for hyperspectral data classification using factor graphs. Factor graph (a bipartite graph consisting of variables and factor vertices) allows factorization of a more complex function leading to definition of variables (employed to store input data), latent variables (allow to bridge abstract class to data), and factors (defining prior probabilities for spectral features and abstract classes; input data mapping to spectral features mixture and further bridging of the mixture to an abstract class). Latent variables play an important role by defining two-level mapping of the input spectral features to a class. Configuration (learning) on training data of the model allows calculating a parameter set for the model to bridge the input data to a class. The classification algorithm is as follows. Spectral bands are separately pre-processed (unsupervised clustering is used) to be defined on a finite domain (alphabet) leading to a representation of the data on multinomial distribution. The represented hyperspectral data is used as input evidence (evidence vector is selected pixelwise) in a configured factor graph and an inference is run resulting in the posterior probability. Variational inference (Mean field) allows to obtain plausible results with a low calculation time. Calculating the posterior probability for each class

  1. Cluster Based Text Classification Model

    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...... 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...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  2. Hierarchical Markov random-field modeling for texture classification in chest radiographs

    Vargas-Voracek, Rene; Floyd, Carey E., Jr.; Nolte, Loren W.; McAdams, Page

    1996-04-01

    A hierarchical Markov random field (MRF) modeling approach is presented for the classification of textures in selected regions of interest (ROIs) of chest radiographs. The procedure integrates possible texture classes and their spatial definition with other components present in an image such as noise and background trend. Classification is performed as a maximum a-posteriori (MAP) estimation of texture class and involves an iterative Gibbs- sampling technique. Two cases are studied: classification of lung parenchyma versus bone and classification of normal lung parenchyma versus miliary tuberculosis (MTB). Accurate classification was obtained for all examined cases showing the potential of the proposed modeling approach for texture analysis of radiographic images.

  3. Pitch Based Sound Classification

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U.

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classif...

  4. Markov mean properties for cell death-related protein classification.

    Fernandez-Lozano, Carlos; Gestal, Marcos; González-Díaz, Humberto; Dorado, Julián; Pazos, Alejandro; Munteanu, Cristian R

    2014-05-21

    The cell death (CD) is a dynamic biological function involved in physiological and pathological processes. Due to the complexity of CD, there is a demand for fast theoretical methods that can help to find new CD molecular targets. The current work presents the first classification model to predict CD-related proteins based on Markov Mean Properties. These protein descriptors have been calculated with the MInD-Prot tool using the topological information of the amino acid contact networks of the 2423 protein chains, five atom physicochemical properties and the protein 3D regions. The Machine Learning algorithms from Weka were used to find the best classification model for CD-related protein chains using all 20 attributes. The most accurate algorithm to solve this problem was K*. After several feature subset methods, the best model found is based on only 11 variables and is characterized by the Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.992 and the true positive rate (TP Rate) of 88.2% (validation set). 7409 protein chains labeled with "unknown function" in the PDB Databank were analyzed with the best model in order to predict the CD-related biological activity. Thus, several proteins have been predicted to have CD-related function in Homo sapiens: 3DRX-involved in virus-host interaction biological process, protein homooligomerization; 4DWF-involved in cell differentiation, chromatin modification, DNA damage response, protein stabilization; 1IUR-involved in ATP binding, chaperone binding; 1J7D-involved in DNA double-strand break processing, histone ubiquitination, nucleotide-binding oligomerization; 1UTU-linked with DNA repair, regulation of transcription; 3EEC-participating to the cellular membrane organization, egress of virus within host cell, class mediator resulting in cell cycle arrest, negative regulation of ubiquitin-protein ligase activity involved in mitotic cell cycle and apoptotic process. Other proteins from bacteria predicted as

  5. [Eosinophilia--pathogenesis, classification and therapy

    Andersen, C.L.; Vestergaard, H.; Norgaard, P.;

    2009-01-01

    Eosinophilia represents a complex clinical problem, the management of which is based on case history and clinical examination. Allergy, parasitic infection or inflammation may then be identified or malignancy suspected. In some cases, representing a haematologic disorder, clonality is demonstrated...... only by specific tests. The diagnostic and therapeutic approach, including a new classification for eosinophilia, is reviewed, and the importance of molecular biological technique is highlighted. Unexplained eosinophilia should be managed in collaboration with a haematology department Udgivelsesdato...

  6. Learning Apache Mahout classification

    Gupta, Ashish

    2015-01-01

    If you are a data scientist who has some experience with the Hadoop ecosystem and machine learning methods and want to try out classification on large datasets using Mahout, this book is ideal for you. Knowledge of Java is essential.

  7. Classification in Medical Imaging

    Chen, Chen

    detection in a cardiovascular disease study. The third focus is to deepen the understanding of classification mechanism by visualizing the knowledge learned by a classifier. More specifically, to build the most typical patterns recognized by the Fisher's linear discriminant rule with applications......Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition......, a good metric is required to measure distance or similarity between feature points so that the classification becomes feasible. Furthermore, in order to build a successful classifier, one needs to deeply understand how classifiers work. This thesis focuses on these three aspects of classification...

  8. Hierarchical classification of glycoside hydrolases.

    Naumoff, D G

    2011-06-01

    This review deals with structural and functional features of glycoside hydrolases, a widespread group of enzymes present in almost all living organisms. Their catalytic domains are grouped into 120 amino acid sequence-based families in the international classification of the carbohydrate-active enzymes (CAZy database). At a higher hierarchical level some of these families are combined in 14 clans. Enzymes of the same clan have common evolutionary origin of their genes and share the most important functional characteristics such as composition of the active center, anomeric configuration of cleaved glycosidic bonds, and molecular mechanism of the catalyzed reaction (either inverting, or retaining). There are now extensive data in the literature concerning the relationship between glycoside hydrolase families belonging to different clans and/or included in none of them, as well as information on phylogenetic protein relationship within particular families. Summarizing these data allows us to propose a multilevel hierarchical classification of glycoside hydrolases and their homologs. It is shown that almost the whole variety of the enzyme catalytic domains can be brought into six main folds, large groups of proteins having the same three-dimensional structure and the supposed common evolutionary origin. PMID:21639842

  9. Inhibition in multiclass classification

    Huerta, Ramón; Vembu, Shankar; Amigó, José M.; Nowotny, Thomas; Elkan, Charles

    2012-01-01

    The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and ...

  10. Twitter content classification

    Dann, Stephen

    2010-01-01

    This paper delivers a new Twitter content classification framework based sixteen existing Twitter studies and a grounded theory analysis of a personal Twitter history. It expands the existing understanding of Twitter as a multifunction tool for personal, profession, commercial and phatic communications with a split level classification scheme that offers broad categorization and specific sub categories for deeper insight into the real world application of the service.

  11. Text classification method review

    Mahinovs, Aigars; Tiwari, Ashutosh; Roy, Rajkumar; Baxter, David

    2007-01-01

    With the explosion of information fuelled by the growth of the World Wide Web it is no longer feasible for a human observer to understand all the data coming in or even classify it into categories. With this growth of information and simultaneous growth of available computing power automatic classification of data, particularly textual data, gains increasingly high importance. This paper provides a review of generic text classification process, phases of that process and met...

  12. Automatic Arabic Text Classification

    Al-harbi, S; Almuhareb, A.; Al-Thubaity , A; Khorsheed, M. S.; Al-Rajeh, A.

    2008-01-01

    Automated document classification is an important text mining task especially with the rapid growth of the number of online documents present in Arabic language. Text classification aims to automatically assign the text to a predefined category based on linguistic features. Such a process has different useful applications including, but not restricted to, e-mail spam detection, web page content filtering, and automatic message routing. This paper presents the results of experiments on documen...

  13. Classification of Sleep Disorders

    Michael J. Thorpy

    2012-01-01

    The classification of sleep disorders is necessary to discriminate between disorders and to facilitate an understanding of symptoms, etiology, and pathophysiology that allows for appropriate treatment. The earliest classification systems, largely organized according to major symptoms (insomnia, excessive sleepiness, and abnormal events that occur during sleep), were unable to be based on pathophysiology because the cause of most sleep disorders was unknown. These 3 symptom-based categories ar...

  14. Latent classification models

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions of...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  15. Classifications of Software Transfers

    Wohlin, Claes; Smite, Darja

    2012-01-01

    Many companies have development sites around the globe. This inevitably means that development work may be transferred between the sites. This paper defines a classification of software transfer types; it divides transfers into three main types: full, partial and gradual transfers to describe the context of a transfer. The differences between transfer types, and hence the need for a classification, are illustrated with staffing curves for two different transfer types. The staffing curves are ...

  16. A New Classification Approach Based on Multiple Classification Rules

    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...

  17. Supernova Photometric Lightcurve Classification

    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).

  18. Progressive Classification Using Support Vector Machines

    Wagstaff, Kiri; Kocurek, Michael

    2009-01-01

    An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user

  19. Hierarchical classification of social groups

    Витковская, Мария

    2001-01-01

    Classification problems are important for every science, and for sociology as well. Social phenomena, examined from the aspect of classification of social groups, can be examined deeper. At present one common classification of groups does not exist. This article offers the hierarchical classification of social group.

  20. Iris Image Classification Based on Hierarchical Visual Codebook.

    Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

    2014-06-01

    Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection. PMID:26353275

  1. Multiclass cancer classification based on gene expression comparison

    Yang Sitan; Naiman Daniel Q.

    2014-01-01

    As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analyses, microarray-based cancer classification comprising multiple discriminatory molecular markers is an emerging trend. Such multiclass classification problems pose new methodological and computational challenges for developing novel and effective statistical approaches. In this paper, we introduce a new approach for classifying multiple disease states associated with cancer based on gene expre...

  2. A Novel Vehicle Classification Using Embedded Strain Gauge Sensors

    Qi Wang

    2008-11-01

    Full Text Available Abstract: This paper presents a new vehicle classification and develops a traffic monitoring detector to provide reliable vehicle classification to aid traffic management systems. The basic principle of this approach is based on measuring the dynamic strain caused by vehicles across pavement to obtain the corresponding vehicle parameters – wheelbase and number of axles – to then accurately classify the vehicle. A system prototype with five embedded strain sensors was developed to validate the accuracy and effectiveness of the classification method. According to the special arrangement of the sensors and the different time a vehicle arrived at the sensors one can estimate the vehicle’s speed accurately, corresponding to the estimated vehicle wheelbase and number of axles. Because of measurement errors and vehicle characteristics, there is a lot of overlap between vehicle wheelbase patterns. Therefore, directly setting up a fixed threshold for vehicle classification often leads to low-accuracy results. Using the machine learning pattern recognition method to deal with this problem is believed as one of the most effective tools. In this study, support vector machines (SVMs were used to integrate the classification features extracted from the strain sensors to automatically classify vehicles into five types, ranging from small vehicles to combination trucks, along the lines of the Federal Highway Administration vehicle classification guide. Test bench and field experiments will be introduced in this paper. Two support vector machines classification algorithms (one-against-all, one-against-one are used to classify single sensor data and multiple sensor combination data. Comparison of the two classification method results shows that the classification accuracy is very close using single data or multiple data. Our results indicate that using multiclass SVM-based fusion multiple sensor data significantly improves

  3. Challenging of Facial Expressions Classification Systems: Survey, Critical Considerations and Direction of Future Work

    Amir Jamshidnezhad; M.D. Jan Nordin

    2012-01-01

    The main purpose of this study is analysis of the parameters and the affects of those on the performance of the facial expressions classification systems. In recent years understanding of emotions is a basic requirement in the development of Human Computer Interaction (HCI) systems. Therefore, an HCI is highly depended on accurate understanding of facial expression. Classification module is the main part of facial expressions recognition system. Numerous classification techniques were propose...

  4. Product Classification in Supply Chain

    Xing, Lihong; Xu, Yaoxuan

    2010-01-01

    Oriflame is a famous international direct sale cosmetics company with complicated supply chain operation but it lacks of a product classification system. It is vital to design a product classification method in order to support Oriflame global supply planning and improve the supply chain performance. This article is aim to investigate and design the multi-criteria of product classification, propose the classification model, suggest application areas of product classification results and intro...

  5. A Fuzzy Logic Based Sentiment Classification

    J.I.Sheeba

    2014-07-01

    Full Text Available Sentiment classification aims to detect information such as opinions, explicit , implicit feelings expressed in text. The most existing approaches are able to detect either explicit expressions or implicit expressions of sentiments in the text separately. In this proposed framework it will detect both Implicit and Explicit expressions available in the meeting transcripts. It will classify the Positive, Negative, Neutral words and also identify the topic of the particular meeting transcripts by using fuzzy logic. This paper aims to add some additional features for improving the classification method. The quality of the sentiment classification is improved using proposed fuzzy logic framework .In this fuzzy logic it includes the features like Fuzzy rules and Fuzzy C-means algorithm.The quality of the output is evaluated using the parameters such as precision, recall, f-measure. Here Fuzzy C-means Clustering technique measured in terms of Purity and Entropy. The data set was validated using 10-fold cross validation method and observed 95% confidence interval between the accuracy values .Finally, the proposed fuzzy logic method produced more than 85 % accurate results and error rate is very less compared to existing sentiment classification techniques.

  6. POPULAR MOLECULAR MARKERS IN BACTERIA

    Weilong, Liu; Lv, Li; MD. ASADUZZAMAN KHAN AND FEIZHOU ZHU

    2012-01-01

    Molecular markers are defined as the fragments of DNA sequence associated with a genome, which are used to identify a particular DNA sequence. Nowadays, with the explosive growth of genetic research and bacterial classification, molecular marker is an important tool to identify bacterial species. Taking account to its significant roles in clinic, medicine and food industry, in this review article, we summarize the traditional research and new development about molecular markers (also called g...

  7. Concepts of Classification and Taxonomy Phylogenetic Classification

    Fraix-Burnet, D.

    2016-05-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works.

  8. Refinements in Sarcoma Classification in the Current 2013 World Health Organization Classification of Tumours of Soft Tissue and Bone.

    Jo, Vickie Y; Doyle, Leona A

    2016-10-01

    The fourth edition of the World Health Organization (WHO) Classification of Tumours of Soft Tissue and Bone was published in February 2013. The 2013 WHO volume provides an updated classification scheme and reproducible diagnostic criteria, which are based on recent clinicopathologic studies and genetic and molecular data that facilitated refined definition of established tumor types, recognition of novel entities, and the development of novel diagnostic markers. This article reviews updates and changes in the classification of bone and soft tissue tumors from the 2002 volume. PMID:27591490

  9. Search techniques in intelligent classification systems

    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...

  10. Prediction and classification of respiratory motion

    Lee, Suk Jin

    2014-01-01

    This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin. In the first chapter following the Introduction  to this book, we...

  11. Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework

    Dahl, Christian M.; Croonenbroeck, Carsten

    2014-01-01

    -term forecasts, which are especially necessary for practitioners in the forward electricity markets of many power trading places; for example, NASDAQ OMX Commodities (formerly Nord Pool OMX Commodities) in northern Europe. We show that our model produces turbine-specific forecasts that are significantly more...

  12. Can Procalcitonin Be an Accurate Diagnostic Marker for the Classification of Diabetic Foot Ulcers?

    Jonaidi Jafari, Nematollah; Safaee Firouzabadi, Mahdi; Izadi, Morteza; Safaee Firouzabadi, Mohammad Sadegh; Saburi, Amin

    2014-01-01

    Background: The differentiation of infected diabetic foot ulcers (IDFU) from non infected diabetic foot ulcers (NIDFU) is a challenging issue for clinicians. Objectives: Recently, procalcitonin (PCT) was introduced as a remarkable inflammatory marker. We aimed to evaluate the accuracy of PCT in comparison to other inflammatory markers for distinguishing IDFU from NIDFU. Materials and Methods: We evaluated PCT serum level as a marker of bacterial infection in patients with diabetic foot ulcers...

  13. Convolutional Neural Networks for patient-specific ECG classification.

    Kiranyaz, Serkan; Ince, Turker; Hamila, Ridha; Gabbouj, Moncef

    2015-08-01

    We propose a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system using an adaptive implementation of 1D Convolutional Neural Networks (CNNs) that can fuse feature extraction and classification into a unified learner. In this way, a dedicated CNN will be trained for each patient by using relatively small common and patient-specific training data and thus it can also be used to classify long ECG records such as Holter registers in a fast and accurate manner. Alternatively, such a solution can conveniently be used for real-time ECG monitoring and early alert system on a light-weight wearable device. The experimental results demonstrate that the proposed system achieves a superior classification performance for the detection of ventricular ectopic beats (VEB) and supraventricular ectopic beats (SVEB). PMID:26736826

  14. The paradox of atheoretical classification

    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 and...

  15. Information gathering for CLP classification

    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.

  16. Vertebral fracture classification

    de Bruijne, Marleen; Pettersen, Paola C.; Tankó, László B.; Nielsen, Mads

    2007-03-01

    A novel method for classification and quantification of vertebral fractures from X-ray images is presented. Using pairwise conditional shape models trained on a set of healthy spines, the most likely unfractured shape is estimated for each of the vertebrae in the image. The difference between the true shape and the reconstructed normal shape is an indicator for the shape abnormality. A statistical classification scheme with the two shapes as features is applied to detect, classify, and grade various types of deformities. In contrast with the current (semi-)quantitative grading strategies this method takes the full shape into account, it uses a patient-specific reference by combining population-based information on biological variation in vertebra shape and vertebra interrelations, and it provides a continuous measure of deformity. Good agreement with manual classification and grading is demonstrated on 204 lateral spine radiographs with in total 89 fractures.

  17. Classification problem in CBIR

    Tatiana Jaworska

    2013-04-01

    Full Text Available At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR. Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results of fuzzy rule-based classification in our CBIR. Further-more, these results are used to construct a search engine taking into account data mining.

  18. Supernova Photometric Classification Challenge

    Kessler, Richard; Jha, Saurabh; Kuhlmann, Stephen

    2010-01-01

    We have publicly released a blinded mix of simulated SNe, with types (Ia, Ib, Ic, II) selected in proportion to their expected rate. The simulation is realized in the griz filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point spread function and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non-Ia type SNe are based on spectroscopically confirmed light curves that include unpublished non-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). We challenge scientists to run their classification algorithms and report a type for each SN. A spectroscopically confirmed subset is provided for training. The goals of this challenge are to (1) learn the relative strengths and weaknesses of the different classification algorithms, (2) use the results to improve classification algorithms, and (3) understand what spectroscopically confirmed sub-...

  19. Bosniak classification system

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens;

    2016-01-01

    BACKGROUND: The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings...... at MR and CEUS imaging and those at CT. PURPOSE: To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. MATERIAL AND METHODS: From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by...... three readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. RESULTS: CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could...

  20. Acoustic classification of dwellings

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on sound...... insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms of...... descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal “acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO work item. This paper...

  1. Automatic classification of time-variable X-ray sources

    Lo, Kitty K; Murphy, Tara; Gaensler, B M

    2014-01-01

    To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the second \\textit{XMM-Newton} serendipitous source catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10-fold cross validation accuracy of the training data is ${\\sim}$97% on a seven-class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest der...

  2. Land Cover Classification Using ALOS Imagery For Penang, Malaysia

    This paper presents the potential of integrating optical and radar remote sensing data to improve automatic land cover mapping. The analysis involved standard image processing, and consists of spectral signature extraction and application of a statistical decision rule to identify land cover categories. A maximum likelihood classifier is utilized to determine different land cover categories. Ground reference data from sites throughout the study area are collected for training and validation. The land cover information was extracted from the digital data using PCI Geomatica 10.3.2 software package. The variations in classification accuracy due to a number of radar imaging processing techniques are studied. The relationship between the processing window and the land classification is also investigated. The classification accuracies from the optical and radar feature combinations are studied. Our research finds that fusion of radar and optical significantly improved classification accuracies. This study indicates that the land cover/use can be mapped accurately by using this approach

  3. Ensemble polarimetric SAR image classification based on contextual sparse representation

    Zhang, Lamei; Wang, Xiao; Zou, Bin; Qiao, Zhijun

    2016-05-01

    Polarimetric SAR image interpretation has become one of the most interesting topics, in which the construction of the reasonable and effective technique of image classification is of key importance. Sparse representation represents the data using the most succinct sparse atoms of the over-complete dictionary and the advantages of sparse representation also have been confirmed in the field of PolSAR classification. However, it is not perfect, like the ordinary classifier, at different aspects. So ensemble learning is introduced to improve the issue, which makes a plurality of different learners training and obtained the integrated results by combining the individual learner to get more accurate and ideal learning results. Therefore, this paper presents a polarimetric SAR image classification method based on the ensemble learning of sparse representation to achieve the optimal classification.

  4. Classification problem in CBIR

    Tatiana Jaworska

    2013-01-01

    At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR). Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results ...

  5. Classification of syringomyelia.

    Milhorat, T H

    2000-01-01

    Syringomyelia poses special challenges for the clinician because of its complex symptomatology, uncertain pathogenesis, and multiple options of treatment. The purpose of this study was to classify intramedullary cavities according to their most salient pathological and clinical features. Pathological findings obtained in 175 individuals with tubular cavitations of the spinal cord were correlated with clinical and magnetic resonance (MR) imaging findings in a database of 927 patients. A classification system was developed in which the morbid anatomy, cause, and pathogenesis of these lesions are emphasized. The use of a disease-based classification of syringomyelia facilitates diagnosis and the interpretation of MR imaging findings and provides a guide to treatment. PMID:16676921

  6. Classification des rongeurs

    Mignon, Jacques; Hardouin, Jacques

    2003-01-01

    Les lecteurs du Bulletin BEDIM semblent parfois avoir des difficultés avec la classification scientifique des animaux connus comme "rongeurs" dans le langage courant. Vu les querelles existant encore aujourd'hui dans la mise en place de cette classification, nous ne nous en étonnerons guère. La brève synthèse qui suit concerne les animaux faisant ou susceptibles de faire partie du mini-élevage. The note aims at providing the main characteristics of the principal families of rodents relevan...

  7. Accurate studies on dissociation energies of diatomic molecules

    SUN; WeiGuo; FAN; QunChao

    2007-01-01

    The molecular dissociation energies of some electronic states of hydride and N2 molecules were studied using a parameter-free analytical formula suggested in this study and the algebraic method (AM) proposed recently. The results show that the accurate AM dissociation energies DeAM agree excellently with experimental dissociation energies Deexpt, and that the dissociation energy of an electronic state such as the 23△g state of 7Li2 whose experimental value is not available can be predicted using the new formula.

  8. Classification of neocortical interneurons using affinity propagation

    Roberto eSantana

    2013-12-01

    Full Text Available In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbiased identification of distinct neuronal subtypes. However, better and more robust classification methods are needed for increasingly complex and larger datasets. We explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. In fact, using a combined anatomical/physiological dataset, our algorithm differentiated parvalbumin from somatostatin interneurons in 49 out of 50 cases. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

  9. Spectral classification using convolutional neural networks

    Hála, Pavel

    2014-01-01

    There is a great need for accurate and autonomous spectral classification methods in astrophysics. This thesis is about training a convolutional neural network (ConvNet) to recognize an object class (quasar, star or galaxy) from one-dimension spectra only. Author developed several scripts and C programs for datasets preparation, preprocessing and postprocessing of the data. EBLearn library (developed by Pierre Sermanet and Yann LeCun) was used to create ConvNets. Application on dataset of more than 60000 spectra yielded success rate of nearly 95%. This thesis conclusively proved great potential of convolutional neural networks and deep learning methods in astrophysics.

  10. Laboratory Building for Accurate Determination of Plutonium

    2008-01-01

    <正>The accurate determination of plutonium is one of the most important assay techniques of nuclear fuel, also the key of the chemical measurement transfer and the base of the nuclear material balance. An

  11. Improved Surgical Site Infection (SSI) rate through accurately assessed surgical wounds

    John, Honeymol; Nimeri, Abdelrahman; Ellahham, Samer

    2015-01-01

    Sheikh Khalifa Medical City's (SKMC) Surgery Institute was identified as a high outlier in Surgical Site Infections (SSI) based on the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) - Semi-Annual Report (SAR) in January 2012. The aim of this project was to improve SSI rates through accurate wound classification. We identified SSI rate reduction as a performance improvement and safety priority at SKMC, a tertiary referral center. We used the American Col...

  12. Application of kernel functions for accurate similarity search in large chemical databases

    2010-01-01

    Background Similaritysearch in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screening among others. It is widely believed that structure based methods provide an efficient way to do the query. Recently various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models, graph kernel functions...

  13. A method for accurate, non-destructive diagnosis of congenital heart defects from heart specimens

    Schleich, Jean-Marc; Abdulla, Tariq; Houyel, Lucile; Paul, Jean-François; Summers, Ron; Dillenseger, Jean-Louis

    2013-01-01

    International audience The accurate analysis of congenital heart defect (CHD) specimens is often difficult and up to now required the opening of the heart. The objective of this study is to define a non-destructive method that allows for the precise analysis of each specimen and its different cardiac components in order to improve classification of the defect and thus provide an indication of underpinning causal mechanisms. We propose a method in which the heart volume is acquired by a CT ...

  14. Pitch Based Sound Classification

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft...

  15. Shark Teeth Classification

    Brown, Tom; Creel, Sally; Lee, Velda

    2009-01-01

    On a recent autumn afternoon at Harmony Leland Elementary in Mableton, Georgia, students in a fifth-grade science class investigated the essential process of classification--the act of putting things into groups according to some common characteristics or attributes. While they may have honed these skills earlier in the week by grouping their own…

  16. Classification system: Netherlands

    Hartemink, A.E.

    2006-01-01

    Although people have always classified soils, it is only since the mid 19th century that soil classification emerged as an important topic within soil science. It forced soil scientists to think systematically about soils and its genesis and developed to facilitate communication between soil scienti

  17. Text document classification

    Novovičová, Jana

    č. 62 (2005), s. 53-54. ISSN 0926-4981 R&D Projects: GA AV ČR IAA2075302; GA AV ČR KSK1019101; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : document representation * categorization * classification Subject RIV: BD - Theory of Information

  18. Automated Stellar Spectral Classification

    Bailer-Jones, Coryn; Irwin, Mike; von Hippel, Ted

    1996-05-01

    Stellar classification has long been a useful tool for probing important astrophysical phenomena. Beyond simply categorizing stars it yields fundamental stellar parameters, acts as a probe of galactic abundance distributions and gives a first foothold on the cosmological distance ladder. The MK system in particular has survived on account of its robustness to changes in the calibrations of the physical parameters. Nonetheless, if stellar classification is to continue as a useful tool in stellar surveys, then it must adapt to keep pace with the large amounts of data which will be acquired as magnitude limits are pushed ever deeper. We are working on a project to automate the multi-parameter classification of visual stellar spectra, using artificial neural networks and other techniques. Our techniques have been developed with 10,000 spectra (B Analysis as a front-end compression of the data. Our continuing work also looks at the application of synthetic spectra to the direct classification of spectra in terms of the physical parameters of Teff, log g, and [Fe/H].

  19. Classification of waste packages

    Mueller, H.P.; Sauer, M.; Rojahn, T. [Versuchsatomkraftwerk GmbH, Kahl am Main (Germany)

    2001-07-01

    A barrel gamma scanning unit has been in use at the VAK for the classification of radioactive waste materials since 1998. The unit provides the facility operator with the data required for classification of waste barrels. Once these data have been entered into the AVK data processing system, the radiological status of raw waste as well as pre-treated and processed waste can be tracked from the point of origin to the point at which the waste is delivered to a final storage. Since the barrel gamma scanning unit was commissioned in 1998, approximately 900 barrels have been measured and the relevant data required for classification collected and analyzed. Based on the positive results of experience in the use of the mobile barrel gamma scanning unit, the VAK now offers the classification of barrels as a service to external users. Depending upon waste quantity accumulation, this measurement unit offers facility operators a reliable and time-saving and cost-effective means of identifying and documenting the radioactivity inventory of barrels scheduled for final storage. (orig.)

  20. The Classification Conundrum.

    Granger, Charles R.

    1983-01-01

    Argues against the five-kingdom scheme of classification as using inconsistent criteria, ending up with divisions that are forced, not natural. Advocates an approach using cell type/complexity and modification of the metabolic machinery, recommending the five-kingdom scheme as starting point for class discussion on taxonomy and its conceptual…

  1. Improving Student Question Classification

    Heiner, Cecily; Zachary, Joseph L.

    2009-01-01

    Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…

  2. Classifications in popular music

    A. van Venrooij; V. Schmutz

    2015-01-01

    The categorical system of popular music, such as genre categories, is a highly differentiated and dynamic classification system. In this article we present work that studies different aspects of these categorical systems in popular music. Following the work of Paul DiMaggio, we focus on four questio

  3. Dynamic Latent Classification Model

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre;

    possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics in...

  4. Classification of myocardial infarction

    Saaby, Lotte; Poulsen, Tina Svenstrup; Hosbond, Susanne Elisabeth;

    2013-01-01

    The classification of myocardial infarction into 5 types was introduced in 2007 as an important component of the universal definition. In contrast to the plaque rupture-related type 1 myocardial infarction, type 2 myocardial infarction is considered to be caused by an imbalance between demand and...

  5. Changing Histopathological Diagnostics by Genome-Based Tumor Classification

    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.

  6. [Classification of primary bone tumors].

    Dominok, G W; Frege, J

    1986-01-01

    An expanded classification for bone tumors is presented based on the well known international classification as well as earlier systems. The current status and future trends in this area are discussed. PMID:3461626

  7. Efficient Fingercode Classification

    Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

    In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

  8. Oral epithelial dysplasia classification systems

    Warnakulasuriya, S; Reibel, J; Bouquot, J;

    2008-01-01

    report, we review the oral epithelial dysplasia classification systems. The three classification schemes [oral epithelial dysplasia scoring system, squamous intraepithelial neoplasia and Ljubljana classification] were presented and the Working Group recommended epithelial dysplasia grading for routine....... Several studies have shown great interexaminer and intraexaminer variability in the assessment of the presence or absence and the grade of oral epithelial dysplasia. The Working Group considered the two class classification (no/questionable/ mild - low risk; moderate or severe - implying high risk) and...

  9. Many accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery

    Grate Leslie R

    2005-04-01

    Full Text Available Abstract Background Molecular profiling generates abundance measurements for thousands of gene transcripts in biological samples such as normal and tumor tissues (data points. Given such two-class high-dimensional data, many methods have been proposed for classifying data points into one of the two classes. However, finding very small sets of features able to correctly classify the data is problematic as the fundamental mathematical proposition is hard. Existing methods can find "small" feature sets, but give no hint how close this is to the true minimum size. Without fundamental mathematical advances, finding true minimum-size sets will remain elusive, and more importantly for the microarray community there will be no methods for finding them. Results We use the brute force approach of exhaustive search through all genes, gene pairs (and for some data sets gene triples. Each unique gene combination is analyzed with a few-parameter linear-hyperplane classification method looking for those combinations that form training error-free classifiers. All 10 published data sets studied are found to contain predictive small feature sets. Four contain thousands of gene pairs and 6 have single genes that perfectly discriminate. Conclusion This technique discovered small sets of genes (3 or less in published data that form accurate classifiers, yet were not reported in the prior publications. This could be a common characteristic of microarray data, thus making looking for them worth the computational cost. Such small gene sets could indicate biomarkers and portend simple medical diagnostic tests. We recommend checking for small gene sets routinely. We find 4 gene pairs and many gene triples in the large hepatocellular carcinoma (HCC, Liver cancer data set of Chen et al. The key component of these is the "placental gene of unknown function", PLAC8. Our HMM modeling indicates PLAC8 might have a domain like part of lP59's crystal structure (a Non

  10. The paradox of atheoretical classification

    Hjørland, Birger

    2016-01-01

    sometimes termed “descriptive” classifications). 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. On the...

  11. Etiologic Classification in Ischemic Stroke

    Hakan Ay

    2011-01-01

    Ischemic stroke is an etiologically heterogenous disorder. Classification of ischemic stroke etiology into categories with discrete phenotypic, therapeutic, and prognostic features is indispensible to generate consistent information from stroke research. In addition, a functional classification of stroke etiology is critical to ensure unity among physicians and comparability among studies. There are two major approaches to etiologic classification in stroke. Phenotypic systems define subtypes...

  12. Machine learning of parameters for accurate semiempirical quantum chemical calculations

    We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempirical OM2 method using a set of 6095 constitutional isomers C7H10O2, for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules

  13. Invariant Image Watermarking Using Accurate Zernike Moments

    Ismail A. Ismail

    2010-01-01

    Full Text Available problem statement: Digital image watermarking is the most popular method for image authentication, copyright protection and content description. Zernike moments are the most widely used moments in image processing and pattern recognition. The magnitudes of Zernike moments are rotation invariant so they can be used just as a watermark signal or be further modified to carry embedded data. The computed Zernike moments in Cartesian coordinate are not accurate due to geometrical and numerical error. Approach: In this study, we employed a robust image-watermarking algorithm using accurate Zernike moments. These moments are computed in polar coordinate, where both approximation and geometric errors are removed. Accurate Zernike moments are used in image watermarking and proved to be robust against different kind of geometric attacks. The performance of the proposed algorithm is evaluated using standard images. Results: Experimental results show that, accurate Zernike moments achieve higher degree of robustness than those approximated ones against rotation, scaling, flipping, shearing and affine transformation. Conclusion: By computing accurate Zernike moments, the embedded bits watermark can be extracted at low error rate.

  14. Sequence Classification: 890247 [

    Full Text Available cient and accurate synthesis of DNA opposite cyclobutane pyrimidine dimers; homolog of human POLH and bacterial DinB proteins; Rad30p || http://www.ncbi.nlm.nih.gov/protein/6320627 ...

  15. Ovarian Cancer Classification based on Mass Spectrometry Analysis of Sera

    Baolin Wu

    2006-01-01

    Full Text Available In our previous study [1], we have compared the performance of a number of widely used discrimination methods for classifying ovarian cancer using Matrix Assisted Laser Desorption Ionization (MALDI mass spectrometry data on serum samples obtained from Reflectron mode. Our results demonstrate good performance with a random forest classifier. In this follow-up study, to improve the molecular classification power of the MALDI platform for ovarian cancer disease, we expanded the mass range of the MS data by adding data acquired in Linear mode and evaluated the resultant decrease in classification error. A general statistical framework is proposed to obtain unbiased classification error estimates and to analyze the effects of sample size and number of selected m/z features on classification errors. We also emphasize the importance of combining biological knowledge and statistical analysis to obtain both biologically and statistically sound results. Our study shows improvement in classification accuracy upon expanding the mass range of the analysis. In order to obtain the best classification accuracies possible, we found that a relatively large training sample size is needed to obviate the sample variations. For the ovarian MS dataset that is the focus of the current study, our results show that approximately 20-40 m/z features are needed to achieve the best classification accuracy from MALDI-MS analysis of sera. Supplementary information can be found at http://bioinformatics.med.yale.edu/proteomics/BioSupp2.html.

  16. [Molecular Subtypes of Gastric Cancer].

    Hatogai, Ken; Doi, Toshihiko

    2016-03-01

    Gastric cancer has been classified based on the pathological characteristics including microscopic configuration and growth pattern. Although these classifications have been used in studies investigating prognosis and recurrence pattern, they are not considered for decisions regarding the therapeutic strategy. In the ToGA study, trastuzumab, an anti-HER2 monoclonal antibody, demonstrated clinical efficacy for gastric cancer with HER2 overexpression or HER2 gene amplification. Based on these findings of the ToGA study, the definition of HER2-positive gastric cancer was established. Thereafter, several molecular targeted agents, including agents targeting other receptor tyrosine kinases, have been investigated in gastric cancer. However, to date no biomarker, except HER2, has been established. Based on the recent technological development in the field of gene analysis, a comprehensive molecular evaluation of gastric cancer was performed as part of The Cancer Genome Atlas (TCGA)project, and a new molecular classification was proposed that divided gastric cancer into the following 4 subtypes: tumors positive for Epstein-Barr virus, microsatellite instability tumors, genomically stable tumors, and tumors with chromosomal instability. Each subtype has specific molecular alterations including gene mutation and amplification, DNA methylation, and protein overexpression. Additionally, some subtypes were suggested to be correlated with the clinicopathological characteristics or as targets of some molecular targeted agents that are currently under development. The new molecular classification is expected to be a roadmap for patient stratification and clinical trials on molecular targeted therapies in gastric cancer. PMID:27067842

  17. Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach.

    Andre F Marquand

    Full Text Available Progressive supranuclear palsy (PSP, multiple system atrophy (MSA and idiopathic Parkinson's disease (IPD can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs. An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i a subcortical motor network; (ii each of its component regions and (iii the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process.

  18. Utility of molecular tests in cytopathology

    Arthur David Somoza

    2014-01-01

    Full Text Available With the popularity of interventional radiology, diagnostic material obtained can be limited requiring critical decisions on making the best use of it. Molecular testing using nanogram amounts of tissue can add useful diagnostic information by improving sensitivity and/or specificity of the diagnosis. This review examines the use of molecular tests in cervical cytology, "indeterminate" thyroid cytology specimens, pancreatic cyst fluid, urinary tract and pulmonary adenocarcinoma cytologic material. Molecular human papillomavirus (HPV testing combined with cervical cytology increases sensitivity of detection of high grade lesions. In cytologically negative cases, the HPV negative predictive value endorses longer screening intervals. With the high prevalence of benign thyroid nodules, cytology plays a vital role in screening. However, 10-40% of the specimens obtained are cytologically indeterminate. Molecular analysis of these specimens can predict the malignant risk in these cases. Increased detection of pancreatic cysts has necessitated accurate pre-operative diagnosis delineating non-mucinous from mucinous cysts, which have a potential for progression to adenocarcinoma. Multimodal diagnosis of pancreatic cysts and molecular analysis help to clarify neoplastic risk; and in cases of limited fluid, may be the only available diagnostic information. Urothelial carcinoma (UC of the bladder, a common cancer with frequent recurrences, requires lifelong surveillance. The UroVysion ™ test kit can increase the sensitivity of detection of UC especially in cases of residual/recurrent carcinoma after therapy. Subsets of lung adenocarcinomas are now commonly targeted by therapies based on molecular mutation results of epidermal growth factor receptor, KRAS or echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase re-arrangements. The move toward standardization of reporting of cytology specimens commencing with cervical smears and more

  19. A possibilistic approach to target classification

    This chapter describes an alternative to the Bayesian approach to target classification that is based on possibility theory. A possibilistic classifier minimizes the maximum cost of the classification decision taking into account the a posteriori possibilities of the target classes given the measured target attributes. The advantage of a possibilistic classifier when compared with a Bayesian classifier is that it requires only an ordinal ranking of the costs associated with the classification decisions and the uncertainty about the target class. Owing to its qualitative character, a possibilistic classifier is less sensitive to inaccuracies in a priori knowledge than a Bayesian classifier at the expense of a degraded performance in situations where accurate a priori knowledge is available. This robustness of the possibilistic classifier to inaccuracies in a priori knowledge is demonstrated in a case study where an average cost criterion is used to compare the performance of a possibilistic and a Bayesian classifier. It is shown that when the characteristics of the measured target attributes deviate strongly from the expected characteristics, the possibilistic classifier provides a lower average cost than a Bayesian classifier. (orig.)

  20. Fast Image Texture Classification Using Decision Trees

    Thompson, David R.

    2011-01-01

    Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

  1. Nominated Texture Based Cervical Cancer Classification

    Edwin Jayasingh Mariarputham

    2015-01-01

    Full Text Available Accurate classification of Pap smear images becomes the challenging task in medical image processing. This can be improved in two ways. One way is by selecting suitable well defined specific features and the other is by selecting the best classifier. This paper presents a nominated texture based cervical cancer (NTCC classification system which classifies the Pap smear images into any one of the seven classes. This can be achieved by extracting well defined texture features and selecting best classifier. Seven sets of texture features (24 features are extracted which include relative size of nucleus and cytoplasm, dynamic range and first four moments of intensities of nucleus and cytoplasm, relative displacement of nucleus within the cytoplasm, gray level cooccurrence matrix, local binary pattern histogram, tamura features, and edge orientation histogram. Few types of support vector machine (SVM and neural network (NN classifiers are used for the classification. The performance of the NTCC algorithm is tested and compared to other algorithms on public image database of Herlev University Hospital, Denmark, with 917 Pap smear images. The output of SVM is found to be best for the most of the classes and better results for the remaining classes.

  2. Subphenotyping and Classification of Orofacial Clefts: Need for Orofacial Cleft Subphenotyping Calls for Revised Classification.

    McBride, W A; McIntyre, G T; Carroll, K; Mossey, P A

    2016-09-01

    Nonsyndromic orofacial clefting (OFC) describes a range of phenotypes that represent the most common craniofacial birth defects in humans, with an overall birth prevalence of 1:700 live births. Because of the lifelong negative implications on health and well-being associated with OFC and the numbers of people affected, quality research into its etiology, diagnosis, treatment outcomes, and preventative strategies is essential. A range of different methods is used for recording and classifying OFC subphenotypes, one of which is the International Classification of Diseases (ICD) system. However, there is a general perception that research is being hampered by a lack of sensitivity and specificity in grouping those with OFC into subphenotypes, with potential heterogeneity and confounding in epidemiologic, genetic, and genotype-phenotype correlation studies. This article provides a background to the necessity of OFC research, discusses current controversies within cleft subphenotyping, and provides a brief overview of current OFC classifications as well as their limitations. The LAHSHAL classification is described in the context of a potentially useful tool for OFC that could complement the ICD-10/ICD-11 Beta coding systems to become a simply understood, universally accepted, clinically friendly, and research-sensitive instrument. Empowering registries, clinicians, and researchers to use a common classification system would have significant implications for OFC research across the world at a time when accurate subphenotyping is crucial and health care research is becoming increasingly tailored toward the individual. PMID:26171570

  3. Sound classification of dwellings

    Rasmussen, Birgit

    2012-01-01

    needed, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", has been established and runs 2009-2013, one of the main objectives being to prepare a proposal for a European sound classification scheme with a number of quality......National schemes for sound classification of dwellings exist in more than ten countries in Europe, typically published as national standards. The schemes define quality classes reflecting different levels of acoustical comfort. Main criteria concern airborne and impact sound insulation between...... dwellings, facade sound insulation and installation noise. The schemes have been developed, implemented and revised gradually since the early 1990s. However, due to lack of coordination between countries, there are significant discrepancies, and new standards and revisions continue to increase the diversity...

  4. Soil Classification Using GATree

    Bhargavi, P

    2010-01-01

    This paper details the application of a genetic programming framework for classification of decision tree of Soil data to classify soil texture. The database contains measurements of soil profile data. We have applied GATree for generating classification decision tree. GATree is a decision tree builder that is based on Genetic Algorithms (GAs). The idea behind it is rather simple but powerful. Instead of using statistic metrics that are biased towards specific trees we use a more flexible, global metric of tree quality that try to optimize accuracy and size. GATree offers some unique features not to be found in any other tree inducers while at the same time it can produce better results for many difficult problems. Experimental results are presented which illustrate the performance of generating best decision tree for classifying soil texture for soil data set.

  5. Short Text Classification: A Survey

    Ge Song

    2014-05-01

    Full Text Available With the recent explosive growth of e-commerce and online communication, a new genre of text, short text, has been extensively applied in many areas. So many researches focus on short text mining. It is a challenge to classify the short text owing to its natural characters, such as sparseness, large-scale, immediacy, non-standardization. It is difficult for traditional methods to deal with short text classification mainly because too limited words in short text cannot represent the feature space and the relationship between words and documents. Several researches and reviews on text classification are shown in recent times. However, only a few of researches focus on short text classification. This paper discusses the characters of short text and the difficulty of short text classification. Then we introduce the existing popular works on short text classifiers and models, including short text classification using sematic analysis, semi-supervised short text classification, ensemble short text classification, and real-time classification. The evaluations of short text classification are analyzed in our paper. Finally we summarize the existing classification technology and prospect for development trend of short text classification

  6. Estuary Classification Revisited

    Guha, Anirban; Lawrence, Gregory A.

    2012-01-01

    This paper presents the governing equations of a tidally-averaged, width-averaged, rectangular estuary in completely nondimensionalized forms. Subsequently, we discover that the dynamics of an estuary is entirely controlled by only two variables: (i) the Estuarine Froude number, and (ii) a nondimensional number related to the Estuarine Aspect ratio and the Tidal Froude number. Motivated by this new observation, the problem of estuary classification is re-investigated. Our analysis shows that ...

  7. Classification of Arabic Documents

    Elbery, Ahmed

    2012-01-01

    Arabic language is a very rich language with complex morphology, so it has a very different and difficult structure than other languages. So it is important to build an Arabic Text Classifier (ATC) to deal with this complex language. The importance of text or document classification comes from its wide variety of application domains such as text indexing, document sorting, text filtering, and Web page categorization. Due to the immense amount of Arabic documents as well as the number of inter...

  8. Qatar content classification

    Handosa, Mohamed

    2014-01-01

    Short title: Qatar content classification. Long title: Develop methods and software for classifying Arabic texts into a taxonomy using machine learning. Contact person and their contact information: Tarek Kanan, . Project description: Starting 4/1/2012, and running through 12/31/2015, is a project to advance digital libraries in the country of Qatar. This is led by VT, but also involves Penn State, Texas A&M, and Qatar University. Tarek is a GRA on this effort. His di...

  9. Application of ant colony optimization in NPP classification fault location

    Nuclear Power Plant is a highly complex structural system with high safety requirements. Fault location appears to be particularly important to enhance its safety. Ant Colony Optimization is a new type of optimization algorithm, which is used in the fault location and classification of nuclear power plants in this paper. Taking the main coolant system of the first loop as the study object, using VB6.0 programming technology, the NPP fault location system is designed, and is tested against the related data in the literature. Test results show that the ant colony optimization can be used in the accurate classification fault location in the nuclear power plants. (authors)

  10. Maximum mutual information regularized classification

    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.

  11. SYSTEMA NATURAE OR THE OUTLINE OF LIVING WORLD CLASSIFICATION

    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.

  12. Automatic workflow for the classification of local DNA conformations

    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

  13. Classification of mitocans, anti-cancer drugs acting on mitochondria

    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

  14. Classification of mitocans, anti-cancer drugs acting on mitochondria

    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

  15. Classification of Meteorological Drought

    Zhang Qiang; Zou Xukai; Xiao Fengjin; Lu Houquan; Liu Haibo; Zhu Changhan; An Shunqing

    2011-01-01

    Background The national standard of the Classification of Meteorological Drought (GB/T 20481-2006) was developed by the National Climate Center in cooperation with Chinese Academy of Meteorological Sciences,National Meteorological Centre and Department of Forecasting and Disaster Mitigation under the China Meteorological Administration (CMA),and was formally released and implemented in November 2006.In 2008,this Standard won the second prize of the China Standard Innovation and Contribution Awards issued by SAC.Developed through independent innovation,it is the first national standard published to monitor meteorological drought disaster and the first standard in China and around the world specifying the classification of drought.Since its release in 2006,the national standard of Classification of Meteorological Drought has been used by CMA as the operational index to monitor and drought assess,and gradually used by provincial meteorological sureaus,and applied to the drought early warning release standard in the Methods of Release and Propagation of Meteorological Disaster Early Warning Signal.

  16. Energy functions for protein design I: Efficient and accurate continuum electrostatics and solvation

    Pokala, Navin; Handel, Tracy M.

    2004-01-01

    Electrostatics and solvation energies are important for defining protein stability, structural specificity, and molecular recognition. Because these energies are difficult to compute quickly and accurately, they are often ignored or modeled very crudely in computational protein design. To address this problem, we have developed a simple, fast, and accurate approximation for calculating Born radii in the context of protein design calculations. When these approximate Born radii are used with th...

  17. Systematic analysis of 18F-FDG PET and metabolism, proliferation and hypoxia markers for classification of head and neck tumors

    Quantification of molecular cell processes is important for prognostication and treatment individualization of head and neck cancer (HNC). However, individual tumor comparison can show discord in upregulation similarities when analyzing multiple biological mechanisms. Elaborate tumor characterization, integrating multiple pathways reflecting intrinsic and microenvironmental properties, may be beneficial to group most uniform tumors for treatment modification schemes. The goal of this study was to systematically analyze if immunohistochemical (IHC) assessment of molecular markers, involved in treatment resistance, and 18F-FDG PET parameters could accurately distinguish separate HNC tumors. Several imaging parameters and texture features for 18F-FDG small-animal PET and immunohistochemical markers related to metabolism, hypoxia, proliferation and tumor blood perfusion were assessed within groups of BALB/c nu/nu mice xenografted with 14 human HNC models. Classification methods were used to predict tumor line based on sets of parameters. We found that 18F-FDG PET could not differentiate between the tumor lines. On the contrary, combined IHC parameters could accurately allocate individual tumors to the correct model. From 9 analyzed IHC parameters, a cluster of 6 random parameters already classified 70.3% correctly. Combining all PET/IHC characteristics resulted in the highest tumor line classification accuracy (81.0%; cross validation 82.0%), which was just 2.2% higher (p = 5.2×10-32) than the performance of the IHC parameter/feature based model. With a select set of IHC markers representing cellular processes of metabolism, proliferation, hypoxia and perfusion, one can reliably distinguish between HNC tumor lines. Addition of 18F-FDG PET improves classification accuracy of IHC to a significant yet minor degree. These results may form a basis for development of tumor characterization models for treatment allocation purposes

  18. Accurate atomic data for industrial plasma applications

    Griesmann, U.; Bridges, J.M.; Roberts, J.R.; Wiese, W.L.; Fuhr, J.R. [National Inst. of Standards and Technology, Gaithersburg, MD (United States)

    1997-12-31

    Reliable branching fraction, transition probability and transition wavelength data for radiative dipole transitions of atoms and ions in plasma are important in many industrial applications. Optical plasma diagnostics and modeling of the radiation transport in electrical discharge plasmas (e.g. in electrical lighting) depend on accurate basic atomic data. NIST has an ongoing experimental research program to provide accurate atomic data for radiative transitions. The new NIST UV-vis-IR high resolution Fourier transform spectrometer has become an excellent tool for accurate and efficient measurements of numerous transition wavelengths and branching fractions in a wide wavelength range. Recently, the authors have also begun to employ photon counting techniques for very accurate measurements of branching fractions of weaker spectral lines with the intent to improve the overall accuracy for experimental branching fractions to better than 5%. They have now completed their studies of transition probabilities of Ne I and Ne II. The results agree well with recent calculations and for the first time provide reliable transition probabilities for many weak intercombination lines.

  19. More accurate picture of human body organs

    Computerized tomography and nucler magnetic resonance tomography (NMRT) are revolutionary contributions to radiodiagnosis because they allow to obtain a more accurate image of human body organs. The principles are described of both methods. Attention is mainly devoted to NMRT which has clinically only been used for three years. It does not burden the organism with ionizing radiation. (Ha)

  20. The European Clinical, Molecular, and Pathological (ECMP) Criteria and the 2007/2008 Revisions of the World Health Organization for the Diagnosis, Classification, and Staging of Prefibrotic Myeloproliferative Neoplasms Carrying the JAK2V617F Mutation

    Jan Jacques Michiels; Fibo Ten Kate; Lam, King H.; Wilfried Schroyens; Zwi Berneman; Hendrik De Raeve

    2014-01-01

    OBJECTIVE: The prefibrotic stages of JAK2V617F essential thrombocythemia (ET) and JAK2V617F polycythemia vera (PV) can easily be diagnosed clinically without use of bone marrow biopsy histology. We assessed the 2008 WHO and European Clinical, Molecular, and Pathological (ECMP) criteria for the diagnosis of myeloproliferative neoplasms (MPNs). METHODS: Studied patients included 6 JAK2V617F-mutated ET and 4 PV patients during long-term follow-up in view of critical analysis of the literature...

  1. Exploiting multi-context analysis in semantic image classification

    TIAN Yong-hong; HUANG Tie-jun; GAO Wen

    2005-01-01

    As the popularity of digital images is rapidly increasing on the Internet, research on technologies for semantic image classification has become an important research topic. However, the well-known content-based image classification methods do not overcome the so-called semantic gap problem in which low-level visual features cannot represent the high-level semantic content of images. Image classification using visual and textual information often performs poorly since the extracted textual features are often too limited to accurately represent the images. In this paper, we propose a semantic image classification approach using multi-context analysis. For a given image, we model the relevant textual information as its multi-modal context, and regard the related images connected by hyperlinks as its link context. Two kinds of context analysis models, i.e., cross-modal correlation analysis and link-based correlation model, are used to capture the correlation among different modals of features and the topical dependency among images induced by the link structure. We propose a new collective classification model called relational support vector classifier (RSVC) based on the well-known Support Vector Machines (SVMs) and the link-based correlation model. Experiments showed that the proposed approach significantly improved classification accuracy over that of SVM classifiers using visual and/or textual features.

  2. Polarimetric Synthetic Aperture Radar Image Classification by a Hybrid Method

    Kamran Ullah Khan; YANG Jian

    2007-01-01

    Different methods proposed so far for accurate classification of land cover types in polarimetric synthetic aperture radar (SAR) image are data specific and no general method is available. A novel hybrid framework for this classification was developed in this work. A set of effective features derived from the coherence matrix of polarimetric SARdata was proposed.Constituents of the feature set are wavelet,texture,and nonlinear features.The proposed feature set has a strong discrimination power. A neural network was used as the classification engine in a unique way. By exploiting the speed of the conjugate gradient method and the convergence rate of the Levenberg-Marquardt method (near the optimal point), an overall speed up of the classification procedure was achieved. Principal component analysis(PCA)was used to shrink the dimension of the feature vector without sacrificing much of the classification accuracy. The proposed approach is compared with the maximum likelihood estimator (MLE)based on the complex Wishart distribution and the results show the superiority of the proposed method,with the average classification accuracy by the proposed method(95.4%)higher than that of the MLE(93.77%). Use of PCA to reduce the dimensionality of the feature vector helps reduce the memory requirements and computational cost, thereby enhancing the speed of the process.

  3. LABEL: fast and accurate lineage assignment with assessment of H5N1 and H9N2 influenza A hemagglutinins.

    Samuel S Shepard

    Full Text Available The evolutionary classification of influenza genes into lineages is a first step in understanding their molecular epidemiology and can inform the subsequent implementation of control measures. We introduce a novel approach called Lineage Assignment By Extended Learning (LABEL to rapidly determine cladistic information for any number of genes without the need for time-consuming sequence alignment, phylogenetic tree construction, or manual annotation. Instead, LABEL relies on hidden Markov model profiles and support vector machine training to hierarchically classify gene sequences by their similarity to pre-defined lineages. We assessed LABEL by analyzing the annotated hemagglutinin genes of highly pathogenic (H5N1 and low pathogenicity (H9N2 avian influenza A viruses. Using the WHO/FAO/OIE H5N1 evolution working group nomenclature, the LABEL pipeline quickly and accurately identified the H5 lineages of uncharacterized sequences. Moreover, we developed an updated clade nomenclature for the H9 hemagglutinin gene and show a similarly fast and reliable phylogenetic assessment with LABEL. While this study was focused on hemagglutinin sequences, LABEL could be applied to the analysis of any gene and shows great potential to guide molecular epidemiology activities, accelerate database annotation, and provide a data sorting tool for other large-scale bioinformatic studies.

  4. Producing Accurate Stereographic Images with a Flashlight and Layers of Glass: A Source for Stereopsis via Slides or Overhead Projection.

    Strauss, Michael J.; Levine, Shellie H.

    1985-01-01

    Describes an extremely simple technique (using only Dreiding or Framework molecular models, a flashlight, small sheets of glass, and a piece of cardboard) which produces extremely accurate line drawings of stereoscopic images. Advantages of using the system are noted. (JN)

  5. Biomarker Selection and Classification of “-Omics” Data Using a Two-Step Bayes Classification Framework

    Anunchai Assawamakin

    2013-01-01

    Full Text Available Identification of suitable biomarkers for accurate prediction of phenotypic outcomes is a goal for personalized medicine. However, current machine learning approaches are either too complex or perform poorly. Here, a novel two-step machine-learning framework is presented to address this need. First, a Naïve Bayes estimator is used to rank features from which the top-ranked will most likely contain the most informative features for prediction of the underlying biological classes. The top-ranked features are then used in a Hidden Naïve Bayes classifier to construct a classification prediction model from these filtered attributes. In order to obtain the minimum set of the most informative biomarkers, the bottom-ranked features are successively removed from the Naïve Bayes-filtered feature list one at a time, and the classification accuracy of the Hidden Naïve Bayes classifier is checked for each pruned feature set. The performance of the proposed two-step Bayes classification framework was tested on different types of -omics datasets including gene expression microarray, single nucleotide polymorphism microarray (SNParray, and surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF proteomic data. The proposed two-step Bayes classification framework was equal to and, in some cases, outperformed other classification methods in terms of prediction accuracy, minimum number of classification markers, and computational time.

  6. Classification of LiDAR Data with Point Based Classification Methods

    Yastikli, N.; Cetin, Z.

    2016-06-01

    LiDAR is one of the most effective systems for 3 dimensional (3D) data collection in wide areas. Nowadays, airborne LiDAR data is used frequently in various applications such as object extraction, 3D modelling, change detection and revision of maps with increasing point density and accuracy. The classification of the LiDAR points is the first step of LiDAR data processing chain and should be handled in proper way since the 3D city modelling, building extraction, DEM generation, etc. applications directly use the classified point clouds. The different classification methods can be seen in recent researches and most of researches work with the gridded LiDAR point cloud. In grid based data processing of the LiDAR data, the characteristic point loss in the LiDAR point cloud especially vegetation and buildings or losing height accuracy during the interpolation stage are inevitable. In this case, the possible solution is the use of the raw point cloud data for classification to avoid data and accuracy loss in gridding process. In this study, the point based classification possibilities of the LiDAR point cloud is investigated to obtain more accurate classes. The automatic point based approaches, which are based on hierarchical rules, have been proposed to achieve ground, building and vegetation classes using the raw LiDAR point cloud data. In proposed approaches, every single LiDAR point is analyzed according to their features such as height, multi-return, etc. then automatically assigned to the class which they belong to. The use of un-gridded point cloud in proposed point based classification process helped the determination of more realistic rule sets. The detailed parameter analyses have been performed to obtain the most appropriate parameters in the rule sets to achieve accurate classes. The hierarchical rule sets were created for proposed Approach 1 (using selected spatial-based and echo-based features) and Approach 2 (using only selected spatial-based features

  7. On the Classification of Psychology in General Library Classification Schemes.

    Soudek, Miluse

    1980-01-01

    Holds that traditional library classification systems are inadequate to handle psychological literature, and advocates the establishment of new theoretical approaches to bibliographic organization. (FM)

  8. Fast and Accurate Large-Scale Detection of β-Lactamase Genes Conferring Antibiotic Resistance

    Lee, Jae Jin; Lee, Jung Hun; Kwon, Dae Beom; Jeon, Jeong Ho; Park, Kwang Seung; Lee, Chang-Ro; Lee, Sang Hee

    2015-01-01

    Fast detection of β-lactamase (bla) genes allows improved surveillance studies and infection control measures, which can minimize the spread of antibiotic resistance. Although several molecular diagnostic methods have been developed to detect limited bla gene types, these methods have significant limitations, such as their failure to detect almost all clinically available bla genes. We developed a fast and accurate molecular method to overcome these limitations using 62 primer pairs, which we...

  9. Feedback about more accurate versus less accurate trials: differential effects on self-confidence and activation.

    Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

    2012-06-01

    One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected byfeedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On day 1, participants performed a golf putting task under one of two conditions: one group received feedback on the most accurate trials, whereas another group received feedback on the least accurate trials. On day 2, participants completed an anxiety questionnaire and performed a retention test. Shin conductance level, as a measure of arousal, was determined. The results indicated that feedback about more accurate trials resulted in more effective learning as well as increased self-confidence. Also, activation was a predictor of performance. PMID:22808705

  10. How Accurate is inv(A)*b?

    Druinsky, Alex

    2012-01-01

    Several widely-used textbooks lead the reader to believe that solving a linear system of equations Ax = b by multiplying the vector b by a computed inverse inv(A) is inaccurate. Virtually all other textbooks on numerical analysis and numerical linear algebra advise against using computed inverses without stating whether this is accurate or not. In fact, under reasonable assumptions on how the inverse is computed, x = inv(A)*b is as accurate as the solution computed by the best backward-stable solvers. This fact is not new, but obviously obscure. We review the literature on the accuracy of this computation and present a self-contained numerical analysis of it.

  11. Accurate guitar tuning by cochlear implant musicians.

    Thomas Lu

    Full Text Available Modern cochlear implant (CI users understand speech but find difficulty in music appreciation due to poor pitch perception. Still, some deaf musicians continue to perform with their CI. Here we show unexpected results that CI musicians can reliably tune a guitar by CI alone and, under controlled conditions, match simultaneously presented tones to <0.5 Hz. One subject had normal contralateral hearing and produced more accurate tuning with CI than his normal ear. To understand these counterintuitive findings, we presented tones sequentially and found that tuning error was larger at ∼ 30 Hz for both subjects. A third subject, a non-musician CI user with normal contralateral hearing, showed similar trends in performance between CI and normal hearing ears but with less precision. This difference, along with electric analysis, showed that accurate tuning was achieved by listening to beats rather than discriminating pitch, effectively turning a spectral task into a temporal discrimination task.

  12. Accurate guitar tuning by cochlear implant musicians.

    Lu, Thomas; Huang, Juan; Zeng, Fan-Gang

    2014-01-01

    Modern cochlear implant (CI) users understand speech but find difficulty in music appreciation due to poor pitch perception. Still, some deaf musicians continue to perform with their CI. Here we show unexpected results that CI musicians can reliably tune a guitar by CI alone and, under controlled conditions, match simultaneously presented tones to <0.5 Hz. One subject had normal contralateral hearing and produced more accurate tuning with CI than his normal ear. To understand these counterintuitive findings, we presented tones sequentially and found that tuning error was larger at ∼ 30 Hz for both subjects. A third subject, a non-musician CI user with normal contralateral hearing, showed similar trends in performance between CI and normal hearing ears but with less precision. This difference, along with electric analysis, showed that accurate tuning was achieved by listening to beats rather than discriminating pitch, effectively turning a spectral task into a temporal discrimination task. PMID:24651081

  13. SPORT FOOD ADDITIVE CLASSIFICATION

    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.

  14. Classification of Emergency Scenarios

    Muench, Mathieu

    2011-01-01

    In most of today's emergency scenarios information plays a crucial role. Therefore, information has to be constantly collected and shared among all rescue team members and this requires new innovative technologies. In this paper a classification of emergency scenarios is presented, describing their special characteristics and common strategies employed by rescue units to handle them. Based on interviews with professional firefighters, requirements for new systems are listed. The goal of this article is to support developers designing new systems by providing them a deeper look into the work of first responders.

  15. Classification of hand eczema

    Agner, T; Aalto-Korte, K; Andersen, K E;

    2015-01-01

    recruited from nine different tertiary referral centres. All patients underwent examination by specialists in dermatology and were checked using relevant allergy testing. Patients were classified into one of the six diagnostic subgroups of HE: allergic contact dermatitis, irritant contact dermatitis, atopic......%) could not be classified. 38% had one additional diagnosis and 26% had two or more additional diagnoses. Eczema on feet was found in 30% of the patients, statistically significantly more frequently associated with hyperkeratotic and vesicular endogenous eczema. CONCLUSION: We find that the classification...

  16. Classification of smooth Fano polytopes

    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 ....

  17. Accurate Finite Difference Methods for Option Pricing

    Persson, Jonas

    2006-01-01

    Stock options are priced numerically using space- and time-adaptive finite difference methods. European options on one and several underlying assets are considered. These are priced with adaptive numerical algorithms including a second order method and a more accurate method. For American options we use the adaptive technique to price options on one stock with and without stochastic volatility. In all these methods emphasis is put on the control of errors to fulfill predefined tolerance level...

  18. Accurate, reproducible measurement of blood pressure.

    Campbell, N. R.; Chockalingam, A; Fodor, J. G.; McKay, D. W.

    1990-01-01

    The diagnosis of mild hypertension and the treatment of hypertension require accurate measurement of blood pressure. Blood pressure readings are altered by various factors that influence the patient, the techniques used and the accuracy of the sphygmomanometer. The variability of readings can be reduced if informed patients prepare in advance by emptying their bladder and bowel, by avoiding over-the-counter vasoactive drugs the day of measurement and by avoiding exposure to cold, caffeine con...

  19. Accurate variational forms for multiskyrmion configurations

    Jackson, A.D.; Weiss, C.; Wirzba, A.; Lande, A.

    1989-04-17

    Simple variational forms are suggested for the fields of a single skyrmion on a hypersphere, S/sub 3/(L), and of a face-centered cubic array of skyrmions in flat space, R/sub 3/. The resulting energies are accurate at the level of 0.2%. These approximate field configurations provide a useful alternative to brute-force solutions of the corresponding Euler equations.

  20. Efficient Accurate Context-Sensitive Anomaly Detection

    2007-01-01

    For program behavior-based anomaly detection, the only way to ensure accurate monitoring is to construct an efficient and precise program behavior model. A new program behavior-based anomaly detection model,called combined pushdown automaton (CPDA) model was proposed, which is based on static binary executable analysis. The CPDA model incorporates the optimized call stack walk and code instrumentation technique to gain complete context information. Thereby the proposed method can detect more attacks, while retaining good performance.

  1. Towards accurate modeling of moving contact lines

    Holmgren, Hanna

    2015-01-01

    The present thesis treats the numerical simulation of immiscible incompressible two-phase flows with moving contact lines. The conventional Navier–Stokes equations combined with a no-slip boundary condition leads to a non-integrable stress singularity at the contact line. The singularity in the model can be avoided by allowing the contact line to slip. Implementing slip conditions in an accurate way is not straight-forward and different regularization techniques exist where ad-hoc procedures ...

  2. Active Learning for Text Classification

    Hu, Rong

    2011-01-01

    Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...

  3. Random Forests for Poverty Classification

    Ruben Thoplan

    2014-01-01

    This paper applies a relatively novel method in data mining to address the issue of poverty classification in Mauritius. The random forests algorithm is applied to the census data in view of improving classification accuracy for poverty status. The analysis shows that the numbers of hours worked, age, education and sex are the most important variables in the classification of the poverty status of an individual. In addition, a clear poverty-gender gap is identified as women have higher chance...

  4. The Revised Classification of Eukaryotes

    Adl, Sina M; Simpson, Alastair G.B.; Lane, Christopher E.; Lukeš, Julius; Bass, David; Bowser, Samuel S.; Brown, Matthew W.; Burki, Fabien; Dunthorn, Micah; Hampl, Vladimir; Heiss, Aaron; Hoppenrath, Mona; Lara, Enrique; Le Gall, Line; Lynn, Denis H.

    2013-01-01

    This revision of the classification of eukaryotes, which updates that of Adl et al. [J. Eukaryot. Microbiol. 52 (2005) 399], retains an emphasis on the protists and incorporates changes since 2005 that have resolved nodes and branches in phylogenetic trees. Whereas the previous revision was successful in re-introducing name stability to the classification, this revision provides a classification for lineages that were then still unresolved. The supergroups have withstood phylogenetic hypothes...

  5. DCC Briefing Paper: Genre classification

    Abbott, Daisy; Kim, Yunhyong

    2008-01-01

    Genre classification is the process of grouping objects together based on defined similarities such as subject, format, style, or purpose. Genre classification as a means of managing information is already established in music (e.g. folk, blues, jazz) and text and is used, alongside topic classification, to organise materials in the commercial sector (the children's section of a bookshop) and intellectually (for example, in the Usenet newsgroup directory hierarchy). However, in the case o...

  6. Classification and Labelling for Biocides

    Rubbiani, Maristella

    2015-01-01

    CLP and biocides The EU Regulation (EC) No 1272/2008 on Classification, Labelling and Packaging of Substances and Mixtures, the CLP-Regulation, entered into force on 20th January, 2009. Since 1st December, 2010 the classification, labelling and packaging of substances has to comply with this Regulation. For mixtures, the rules of this Regulation are mandatory from 1st June, 2015; this means that until this date classification, labelling and packaging could either be carried out according to D...

  7. Classification of Pulse Waveforms Using Edit Distance with Real Penalty

    Zhang Dongyu

    2010-01-01

    Full Text Available Abstract Advances in sensor and signal processing techniques have provided effective tools for quantitative research in traditional Chinese pulse diagnosis (TCPD. Because of the inevitable intraclass variation of pulse patterns, the automatic classification of pulse waveforms has remained a difficult problem. In this paper, by referring to the edit distance with real penalty (ERP and the recent progress in -nearest neighbors (KNN classifiers, we propose two novel ERP-based KNN classifiers. Taking advantage of the metric property of ERP, we first develop an ERP-induced inner product and a Gaussian ERP kernel, then embed them into difference-weighted KNN classifiers, and finally develop two novel classifiers for pulse waveform classification. The experimental results show that the proposed classifiers are effective for accurate classification of pulse waveform.

  8. Robust tissue classification for reproducible wound assessment in telemedicine environments

    Wannous, Hazem; Treuillet, Sylvie; Lucas, Yves

    2010-04-01

    In telemedicine environments, a standardized and reproducible assessment of wounds, using a simple free-handled digital camera, is an essential requirement. However, to ensure robust tissue classification, particular attention must be paid to the complete design of the color processing chain. We introduce the key steps including color correction, merging of expert labeling, and segmentation-driven classification based on support vector machines. The tool thus developed ensures stability under lighting condition, viewpoint, and camera changes, to achieve accurate and robust classification of skin tissues. Clinical tests demonstrate that such an advanced tool, which forms part of a complete 3-D and color wound assessment system, significantly improves the monitoring of the healing process. It achieves an overlap score of 79.3 against 69.1% for a single expert, after mapping on the medical reference developed from the image labeling by a college of experts.

  9. AdaBoost for Improved Voice-Band Signal Classification

    2007-01-01

    A good voice-band signal classification can not only enable the safe application of speech coding techniques,the implementation of a Digital Signal Interpolation (DSI)system, but also facilitate network administration and planning by providing accurate voice-band traffic analysis.A new method is proposed to detect and classify the presence of various voice-band signals on the General Switched Telephone Network ( GSTN ). The method uses a combination of simple base classifiers through the AdaBoost algorithm. The conventional classification features for voiceband data classification are combined and optimized by the AdaBoost algorithm and spectral subtraction method.Experiments show the simpleness, effectiveness, efficiency and flexibility of the method.

  10. Data cache organization for accurate timing analysis

    Schoeberl, Martin; Huber, Benedikt; Puffitsch, Wolfgang

    2013-01-01

    Caches are essential to bridge the gap between the high latency main memory and the fast processor pipeline. Standard processor architectures implement two first-level caches to avoid a structural hazard in the pipeline: an instruction cache and a data cache. For tight worst-case execution times...... it is important to classify memory accesses as either cache hit or cache miss. The addresses of instruction fetches are known statically and static cache hit/miss classification is possible for the instruction cache. The access to data that is cached in the data cache is harder to predict statically. Several...... different data areas, such as stack, global data, and heap allocated data, share the same cache. Some addresses are known statically, other addresses are only known at runtime. With a standard cache organization all those different data areas must be considered by worst-case execution time analysis...

  11. Sequence Classification: 894861 [

    Full Text Available ial component of the MIND kinetochore complex (Mtw1p Including Nnf1p-Nsl1p-Dsn1p) which joins kinetochore subunits contact...ing DNA to those contacting microtubules; required for accurate chromosome segregation; Nnf1p || http://www.ncbi.nlm.nih.gov/protein/6322572 ...

  12. Sequence Classification: 893607 [

    Full Text Available ial component of the MIND kinetochore complex (Mtw1p Including Nnf1p-Nsl1p-Dsn1p) which joins kinetochore subunits contact...ing DNA to those contacting microtubules; required for accurate chromosome segregation; Nsl1p || http://www.ncbi.nlm.nih.gov/protein/6325023 ...

  13. Accurate macroscale modelling of spatial dynamics in multiple dimensions

    Roberts, A ~J; Bunder, J ~E

    2011-01-01

    Developments in dynamical systems theory provides new support for the macroscale modelling of pdes and other microscale systems such as Lattice Boltzmann, Monte Carlo or Molecular Dynamics simulators. By systematically resolving subgrid microscale dynamics the dynamical systems approach constructs accurate closures of macroscale discretisations of the microscale system. Here we specifically explore reaction-diffusion problems in two spatial dimensions as a prototype of generic systems in multiple dimensions. Our approach unifies into one the modelling of systems by a type of finite elements, and the `equation free' macroscale modelling of microscale simulators efficiently executing only on small patches of the spatial domain. Centre manifold theory ensures that a closed model exist on the macroscale grid, is emergent, and is systematically approximated. Dividing space either into overlapping finite elements or into spatially separated small patches, the specially crafted inter-element\\slash patch coupling als...

  14. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

    2005-01-01

    High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

  15. Classification & Structure of Blood Vessels

    ... Thyroid & Parathyroid Glands Adrenal Gland Pancreas Gonads Other Endocrine Glands Review Quiz Cardiovascular System Heart Structure of the Heart Physiology of the Heart Blood Classification & Structure of Blood ...

  16. Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

    Dimitris G. Stavrakoudis

    2014-07-01

    Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

  17. Use of manual densitometry in land cover classification

    Jordan, D. C.; Graves, D. H.; Hammetter, M. C.

    1978-01-01

    Through use of manual spot densitometry values derived from multitemporal 1:24,000 color infrared aircraft photography, areas as small as one hectare in the Cumberland Plateau in Kentucky were accurately classified into one of eight ground cover groups. If distinguishing between undisturbed and disturbed forest areas is the sole criterion of interest, classification results are highly accurate if based on imagery taken during foliated ground cover conditions. Multiseasonal imagery analysis was superior to single data analysis, and transparencies from prefoliated conditions gave better separation of conifers and hardwoods than did those from foliated conditions.

  18. Correction of Alar Retraction Based on Frontal Classification.

    Kim, Jae Hoon; Song, Jin Woo; Park, Sung Wan; Bartlett, Erica; Nguyen, Anh H

    2015-11-01

    Among the various types of alar deformations in Asians, alar retraction not only has the highest occurrence rate, but is also very complicated to treat because the ala is supported only by cartilage and its soft tissue envelope cannot be easily stretched. As patients' knowledge of aesthetic procedures is becoming more extensive due to increased information dissemination through various media, doctors must give more accurate, logical explanations of the procedures to be performed and their anticipated results, with an emphasis on relevant anatomical features, accurate diagnoses, detailed classifications, and various appropriate methods of surgery. PMID:26648808

  19. The European Clinical, Molecular, and Pathological (ECMP Criteria and the 2007/2008 Revisions of the World Health Organization for the Diagnosis, Classification, and Staging of Prefibrotic Myeloproliferative Neoplasms Carrying the JAK2V617F Mutation

    Jan Jacques Michiels

    2014-09-01

    Full Text Available OBJECTIVE: The prefibrotic stages of JAK2V617F essential thrombocythemia (ET and JAK2V617F polycythemia vera (PV can easily be diagnosed clinically without use of bone marrow biopsy histology. We assessed the 2008 WHO and European Clinical, Molecular, and Pathological (ECMP criteria for the diagnosis of myeloproliferative neoplasms (MPNs. METHODS: Studied patients included 6 JAK2V617F-mutated ET and 4 PV patients during long-term follow-up in view of critical analysis of the literature. The bone marrow biopsy histology diagnosis without use of clinical data was PV in 7 (of which 3 were cases of ET with features of early prodromal PV and classical PV in 4. RESULTS: The ECMP criteria distinguish 3 sequential phenotypes (1, 2, or 3 of JAK2V617F-mutated ET: normocellular ET-1; ET-2, with clinical and bone marrow features of PV (prodromal PV, and ET-3, with hypercellular dysmorphic megakaryocytic and granulocytic myeloproliferation (ET.MGM. The 3 patients with ET-2 or prodromal PV developed slow-onset PV after a follow-up of about 10 years. Bone marrow biopsy histology differentiates MPNs of various molecular etiologies from all variants of primary or secondary erythrocytoses and thrombocytoses with sensitivity and specificity of near 100%. CONCLUSION: Normocellular ET (WHO-ET, prodromal PV, and classical PV show overlapping bone marrow biopsy histology features with similar pleomorphic clustered megakaryocytes in the prefibrotic stages of JAK2V617F mutated MPN. Erythrocytes are below 6x1012/L in normocellular ET and prodromal PV, and are consistently above 6x1012/L in classical PV and at the time of transition from prodromal PV into classical PV. Red cell count at a cut-off level of 6x1012/L separates ET from PV and obviates the need for red cell mass measurement when bone marrow histology and JAK2V617F mutation screening are included in the diagnostic work-up of MPNs.

  20. Hydrologic landscape regionalisation using deductive classification and random forests.

    Stuart C Brown

    Full Text Available Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic

  1. Isomerism of Cyanomethanimine: Accurate Structural, Energetic, and Spectroscopic Characterization.

    Puzzarini, Cristina

    2015-11-25

    The structures, relative stabilities, and rotational and vibrational parameters of the Z-C-, E-C-, and N-cyanomethanimine isomers have been evaluated using state-of-the-art quantum-chemical approaches. Equilibrium geometries have been calculated by means of a composite scheme based on coupled-cluster calculations that accounts for the extrapolation to the complete basis set limit and core-correlation effects. The latter approach is proved to provide molecular structures with an accuracy of 0.001-0.002 Å and 0.05-0.1° for bond lengths and angles, respectively. Systematically extrapolated ab initio energies, accounting for electron correlation through coupled-cluster theory, including up to single, double, triple, and quadruple excitations, and corrected for core-electron correlation and anharmonic zero-point vibrational energy, have been used to accurately determine relative energies and the Z-E isomerization barrier with an accuracy of about 1 kJ/mol. Vibrational and rotational spectroscopic parameters have been investigated by means of hybrid schemes that allow us to obtain rotational constants accurate to about a few megahertz and vibrational frequencies with a mean absolute error of ∼1%. Where available, for all properties considered, a very good agreement with experimental data has been observed. PMID:26529434

  2. Accurate rest frequencies of methanol maser and dark cloud lines

    Müller, H S P; Maeder, H

    2004-01-01

    We report accurate laboratory measurements of selected methanol transition frequencies between 0.834 and 230 GHz in order to facilitate astronomical velocity analyses. New data have been obtained between 10 and 27 GHz and between 60 and 119 GHz. Emphasis has been put on known or potential interstellar maser lines as well as on transitions suitable for the investigation of cold dark clouds. Because of the narrow line widths (<0.5 kms-1) of maser lines and lines detected in dark molecular clouds, accurate frequencies are needed for comparison of the velocities of different methanol lines with each other as well as with lines from other species. In particular, frequencies for a comprehensive set of transitions are given which, because of their low level energies (< 20 cm-1 or 30 K) are potentially detectable in cold clouds. Global Hamiltonian fits generally do not yet yield the required accuracy. Additionally, we report transition frequencies for other lines that may be used to test and to improve existing...

  3. 78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

    2013-11-18

    ...-Doxey data into the cotton futures classification process in March 2012 (77 FR 5379). When verified by a... October 9, 2013 (78 FR 54970). AMS received two comments: one from a national trade organization... Agricultural Marketing Service 7 CFR Part 27 RIN 0581-AD33 Cotton Futures Classification:...

  4. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    2013-09-09

    ... process in March 2012 (77 FR 5379). When verified by a futures classification, Smith-Doxey data serves as...; ] DEPARTMENT OF AGRICULTURE Agricultural Marketing Service 7 CFR Part 27 RIN 0581-AD33 Cotton Futures... for the addition of an optional cotton futures classification procedure--identified and known...

  5. Reconstruction-classification method for quantitative photoacoustic tomography

    Malone, Emma; Cox, Ben T; Arridge, Simon R

    2015-01-01

    We propose a combined reconstruction-classification method for simultaneously recovering absorption and scattering in turbid media from images of absorbed optical energy. This method exploits knowledge that optical parameters are determined by a limited number of classes to iteratively improve their estimate. Numerical experiments show that the proposed approach allows for accurate recovery of absorption and scattering in 2 and 3 dimensions, and delivers superior image quality with respect to traditional reconstruction-only approaches.

  6. SPIDERz: SuPport vector classification for IDEntifying Redshifts

    Jones, Evan; Singal, J.

    2016-08-01

    SPIDERz (SuPport vector classification for IDEntifying Redshifts) applies powerful support vector machine (SVM) optimization and statistical learning techniques to custom data sets to obtain accurate photometric redshift (photo-z) estimations. It is written for the IDL environment and can be applied to traditional data sets consisting of photometric band magnitudes, or alternatively to data sets with additional galaxy parameters (such as shape information) to investigate potential correlations between the extra galaxy parameters and redshift.

  7. IMAGE RECONSTRUCTION AND OBJECT CLASSIFICATION IN CT IMAGING SYSTEM

    张晓明; 蒋大真; 等

    1995-01-01

    By obtaining a feasible filter function,reconstructed images can be got with linear interpolation and filtered backoprojection techniques.Considering the gray and spatial correlation neighbour informations of each pixel,a new supervised classification method is put forward for the reconstructed images,and an experiment with noise image is done,the result shows that the method is feasible and accurate compared with ideal phantoms.

  8. Automated Feature Design for Time Series Classification by Genetic Programming

    Harvey, Dustin Yewell

    2014-01-01

    Time series classification (TSC) methods discover and exploit patterns in time series and other one-dimensional signals. Although many accurate, robust classifiers exist for multivariate feature sets, general approaches are needed to extend machine learning techniques to make use of signal inputs. Numerous applications of TSC can be found in structural engineering, especially in the areas of structural health monitoring and non-destructive evaluation. Additionally, the fields of process contr...

  9. 14 CFR 1203.412 - Classification guides.

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Classification guides. 1203.412 Section 1203.412 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION INFORMATION SECURITY PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification...

  10. 22 CFR 9.4 - Original classification.

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Original classification. 9.4 Section 9.4... classification. (a) Definition. Original classification is the initial determination that certain information... classification. (b) Classification levels. (1) Top Secret shall be applied to information the...

  11. 22 CFR 9.6 - Derivative classification.

    2010-04-01

    ... CFR 2001.22. (c) Department of State Classification Guide. The Department of State Classification... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Derivative classification. 9.6 Section 9.6... classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating...

  12. 32 CFR 2400.15 - Classification guides.

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2400.15 Section 2400.15... 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...

  13. 15 CFR 2008.9 - Classification guides.

    2010-01-01

    ... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Classification guides. 2008.9 Section... REPRESENTATIVE Derivative Classification § 2008.9 Classification guides. Classification guides shall be issued by... direct derivative classification, shall identify the information to be protected in specific and...

  14. Identification of Microorganisms by High Resolution Tandem Mass Spectrometry with Accurate Statistical Significance

    Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Suffredini, Anthony F.; Sacks, David B.; Yu, Yi-Kuo

    2016-02-01

    Correct and rapid identification of microorganisms is the key to the success of many important applications in health and safety, including, but not limited to, infection treatment, food safety, and biodefense. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is challenging correct microbial identification because of the large number of choices present. To properly disentangle candidate microbes, one needs to go beyond apparent morphology or simple `fingerprinting'; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptidome profiles of microbes to better separate them and by designing an analysis method that yields accurate statistical significance. Here, we present an analysis pipeline that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using MS/MS data of 81 samples, each composed of a single known microorganism, that the proposed pipeline can correctly identify microorganisms at least at the genus and species levels. We have also shown that the proposed pipeline computes accurate statistical significances, i.e., E-values for identified peptides and unified E-values for identified microorganisms. The proposed analysis pipeline has been implemented in MiCId, a freely available software for Microorganism Classification and Identification. MiCId is available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

  15. Accurate vibrational energy spectra and dissociationenergies of some diatomic electronic states

    Wei-guo SUN; Xiu-ying LIU; Yu-jie WANG; Yan ZHAN; Qun-chao FAN

    2008-01-01

    An algebraic method (AM) used to study the full vibrational spectra of diatomic systems, and an analytical formula used to calculate accurate molecular dissociation energies are applied to study the full vi-brational spectra and molecular dissociation energies of some electronic states of homonuclear and heteronuclear diatomic molecules and diatomic ions. Studies show that the AM method and the analytical expression are reli-able and economical physical methods for studying full vibrational spectra and molecular dissociation energies of diatomic electronic systems theoretically. They are par-ticularly useful for those diatomic systems whose high-lying vibrational energies may not be available.

  16. Niche Genetic Algorithm with Accurate Optimization Performance

    LIU Jian-hua; YAN De-kun

    2005-01-01

    Based on crowding mechanism, a novel niche genetic algorithm was proposed which can record evolutionary direction dynamically during evolution. After evolution, the solutions's precision can be greatly improved by means of the local searching along the recorded direction. Simulation shows that this algorithm can not only keep population diversity but also find accurate solutions. Although using this method has to take more time compared with the standard GA, it is really worth applying to some cases that have to meet a demand for high solution precision.

  17. How accurately can we calculate thermal systems?

    The objective was to determine how accurately simple reactor lattice integral parameters can be determined, considering user input, differences in the methods, source data and the data processing procedures and assumptions. Three simple square lattice test cases with different fuel to moderator ratios were defined. The effect of the thermal scattering models were shown to be important and much bigger than the spread in the results. Nevertheless, differences of up to 0.4% in the K-eff calculated by continuous energy Monte Carlo codes were observed even when the same source data were used. (author)

  18. Accurate diagnosis is essential for amebiasis

    2004-01-01

    @@ Amebiasis is one of the three most common causes of death from parasitic disease, and Entamoeba histolytica is the most widely distributed parasites in the world. Particularly, Entamoeba histolytica infection in the developing countries is a significant health problem in amebiasis-endemic areas with a significant impact on infant mortality[1]. In recent years a world wide increase in the number of patients with amebiasis has refocused attention on this important infection. On the other hand, improving the quality of parasitological methods and widespread use of accurate tecniques have improved our knowledge about the disease.

  19. Investigations on Accurate Analysis of Microstrip Reflectarrays

    Zhou, Min; Sørensen, S. B.; Kim, Oleksiy S.;

    2011-01-01

    An investigation on accurate analysis of microstrip reflectarrays is presented. Sources of error in reflectarray analysis are examined and solutions to these issues are proposed. The focus is on two sources of error, namely the determination of the equivalent currents to calculate the radiation...... pattern, and the inaccurate mutual coupling between array elements due to the lack of periodicity. To serve as reference, two offset reflectarray antennas have been designed, manufactured and measured at the DTUESA Spherical Near-Field Antenna Test Facility. Comparisons of simulated and measured data are...

  20. Genotype phenotype classification of hepatocellular adenoma

    Paulette Bioulac-Sage; Jean Frédéric Blanc; Sandra Rebouissou; Charles Balabaud; Jessica Zucman-Rossi

    2007-01-01

    Studies that compare tumor genotype with phenotype have provided the basis of a new histological/molecular classification of hepatocellular adenomas. Based on two molecular criteria (presence of a TCF1/HNF1α or β-catenin mutation), and an additional histological criterion (presence or absence of an inflammatory infiltrate), subgroups of hepatocellular adenoma can be defined and distinguished from focal nodular hyperplasia. Analysis of 96 hepatocellular adenomas performed by a French collaborative network showed that they can be divided into four broad subgroups: the first one is defined by the presence of mutations in TCF1 gene inactivating the hepatocyte nuclear factor 1 (HNF1α); the second by the presence of β-catenin activating mutations; the category without mutations of HNF1α or β-catenin is further divided into 2 subgroups depending on the presence or absence of inflammation. Therefore, the approach to the diagnosis of problematic benign hepatocytic nodules may be entering a new era directed by new molecular information. It is hoped that immunohistological tools will improve significantly diagnosis of liver biopsy in our ability to distinguish hepatocellular adenoma from focal nodular hyperplasia (FNH), and to delineate clinically meaningful entities within each group to define the best clinical management. The optimal care of patients with a liver nodule will benefit from the recent knowledge coming from molecular biology and the combined expertise of hepatologists, pathologists, radiologists, and surgeons.

  1. Invasive breast cancer molecular classification and the choice of adjuvant chemotherapy regimens%浸润性乳腺癌分子分型与辅助化疗方案选择

    陈嘉健; 柳光宇

    2011-01-01

    随着基因表达谱与基因芯片技术的开展,乳腺癌在分子水平上表现出的高度异质性也逐渐受到关注.不同分子分型的乳腺癌,其流行病学危险因素、疾病自然进展过程以及对全身或局部治疗的反应性都不尽相同;对于乳腺癌的准确分型能够较为精确地反映肿瘤的生物学行为,对于判断预后、制定更具个体化的治疗策略具有深刻的意义.2011年的St.Gallen共识已针对不同的乳腺癌分子分型给出了原则性的治疗建议,标志着乳腺癌的治疗已逐步进入了在规范化多学科综合治疗模式的基础上,倡导个体化治疗的时代.%With the adoption and development of gene expression technique, the heterogeneity at the molecular level of the breast cancer has attracted attention gradually. The different breast cancer subtypes have different epidemiological risk factors, different natural histories and different responses to systemic and local therapies. To identify the exact subtype of the breast cancer has profound significance on making individualized therapies. The consensus of St. Gallen BreastCancer Conference 2011 has provided different treatment suggestions according to different subtypes, which indicates that the management of breast cancer has entered the age of advocating individualized treatment on the basis of the standardization multi-disciplinary treatment gradually.

  2. Seismic texture classification. Final report

    Vinther, R.

    1997-12-31

    The seismic texture classification method, is a seismic attribute that can both recognize the general reflectivity styles and locate variations from these. The seismic texture classification performs a statistic analysis for the seismic section (or volume) aiming at describing the reflectivity. Based on a set of reference reflectivities the seismic textures are classified. The result of the seismic texture classification is a display of seismic texture categories showing both the styles of reflectivity from the reference set and interpolations and extrapolations from these. The display is interpreted as statistical variations in the seismic data. The seismic texture classification is applied to seismic sections and volumes from the Danish North Sea representing both horizontal stratifications and salt diapers. The attribute succeeded in recognizing both general structure of successions and variations from these. Also, the seismic texture classification is not only able to display variations in prospective areas (1-7 sec. TWT) but can also be applied to deep seismic sections. The seismic texture classification is tested on a deep reflection seismic section (13-18 sec. TWT) from the Baltic Sea. Applied to this section the seismic texture classification succeeded in locating the Moho, which could not be located using conventional interpretation tools. The seismic texture classification is a seismic attribute which can display general reflectivity styles and deviations from these and enhance variations not found by conventional interpretation tools. (LN)

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

    Chinsu Lin; Chao-Cheng Wu; Khongor Tsogt; Yen-Chieh Ouyang; Chein-I Chang

    2015-01-01

    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...

  4. Classification of coronary artery bifurcation lesions and treatments: Time for a consensus!

    Louvard, Yves; Thomas, Martyn; Dzavik, Vladimir;

    2007-01-01

    , heterogeneity, and inadequate description of techniques implemented. Methods: The aim is to propose a consensus established by the European Bifurcation Club (EBC), on the definition and classification of bifurcation lesions and treatments implemented with the purpose of allowing comparisons between techniques...... proposes a new classification of bifurcation lesions and their treatments to permit accurate comparisons of well described techniques in homogeneous lesion groups. (c) 2008 Wiley-Liss, Inc. Udgivelsesdato: 2007-Nov-5...

  5. Dynamic Ensemble Selection Approach for Hyperspectral Image Classification With Joint Spectral and Spatial Information

    Damodaran, Bharath Bhushan; Rao Nidamanuri, Rama; Tarabalka, Yuliya

    2015-01-01

    Accurate generation of a land cover map using hyperspectral data is an important application of remote sensing. Multiple classifier system (MCS) is an effective tool for hyperspec-tral image classification. However, most of the research in MCS addressed the problem of classifier combination, while the potential of selecting classifiers dynamically is least explored for hyper-spectral image classification. The goal of this paper is to assess the potential of dynamic classifier selection/dynami...

  6. Classification of Ancient Mammal Individuals Using Dental Pulp MALDI-TOF MS Peptide Profiling

    Thi-Nguyen-Ny Tran; Gérard Aboudharam; Armelle Gardeisen; Bernard Davoust; Jean-Pierre Bocquet-Appel; Christophe Flaudrops; Maya Belghazi; Didier Raoult; Michel Drancourt

    2011-01-01

    BACKGROUND: The classification of ancient animal corpses at the species level remains a challenging task for forensic scientists and anthropologists. Severe damage and mixed, tiny pieces originating from several skeletons may render morphological classification virtually impossible. Standard approaches are based on sequencing mitochondrial and nuclear targets. METHODOLOGY/PRINCIPAL FINDINGS: We present a method that can accurately classify mammalian species using dental pulp and mass spectrom...

  7. Classification of daily-life postural transitions using trunk-worn wearable barometric pressure sensor

    Massé, Fabien; Bourke, Alan Kevin; Ionescu, Anisoara; Aminian, Kamiar

    2013-01-01

    Distinguishing sedentary from dynamic behavior is essential in addressing disease conditions that are influenced by mobility. Event-based activity recognition algorithms essentially rely on accurate classification of siting and standing postural transitions to distinguish whether the subject is sitting or standing. In this paper, the use of barometric pressure, to estimate altitude, is investigated. It enabled a correct classification of postural transitions with a sensitivity of 92.31% and s...

  8. Estuary Classification Revisited

    Guha, Anirban

    2012-01-01

    The governing equations of a tidally averaged, width averaged, rectangular estuary has been investigated. It's theoretically shown that the dynamics of an estuary is entirely controlled by three parameters: (i) the Estuarine Froude number, (ii) the Tidal Froude number and (iii) the Estuarine Aspect ratio. The momentum, salinity and integral salt balance equations can be completely expressed in terms of these control variables. The estuary classification problem has also been reinvestigated. It's found that these three control variables can completely specify the estuary type. Comparison with real estuary data shows very good match. Additionally, we show that the well accepted leading order estuarine integral salt balance equation is inconsitent with the leading order salinity equation in an order of magnitude sense.

  9. Classification of enterprise expenditures

    Tatiana Ostapenko

    2013-05-01

    Full Text Available The need to diversify share of costs is grounded. It is proposed to classify expenditures by types of income (loss of current activity (covered and uncovered expenditures, by the level of costs to its planned size (planned cost; costs that exceed the planned size; costs that are lower than the planned size, with the aim to influence the activity result (effective and ineffective expenditures, by the period of their appearance (intermediate and annual expenditures.The existing classification of expenditures by kinds of activity is improved through emphasizing such feature: by ability to increase enterprise cost (essential and unessential expenditures. The traditional definition of exhausted (consumed and unexhausted (not consumed expenditures that helped to separate expenses in their structure which don’t ensure formation of exhausted and unexhausted expenditures (management costs is criticized

  10. Nonlinear estimation and classification

    Hansen, Mark; Holmes, Christopher; Mallick, Bani; Yu, Bin

    2003-01-01

    Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of different fields Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future

  11. Classification of radioactive waste

    Radioactive wastes are generated in a number of different kinds of facilities and arise in a wide range of concentrations of radioactive materials and in a variety of physical and chemical forms. To simplify their management, a number of schemes have evolved for classifying radioactive waste according to the physical, chemical and radiological properties of significance to those facilities managing this waste. These schemes have led to a variety of terminologies, differing from country to country and even between facilities in the same country. This situation makes it difficult for those concerned to communicate with one another regarding waste management practices. This document revises and updates earlier IAEA references on radioactive waste classification systems given in IAEA Technical Reports Series and Safety Series. Guidance regarding exemption of materials from regulatory control is consistent with IAEA Safety Series and the RADWASS documents published under IAEA Safety Series. 11 refs, 2 figs, 2 tab

  12. Classification-based reasoning

    Gomez, Fernando; Segami, Carlos

    1991-01-01

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

  13. Predictive Classification Trees

    Dlugosz, Stephan; Müller-Funk, Ulrich

    CART (Breiman et al., Classification and Regression Trees, Chapman and Hall, New York, 1984) and (exhaustive) CHAID (Kass, Appl Stat 29:119-127, 1980) figure prominently among the procedures actually used in data based management, etc. CART is a well-established procedure that produces binary trees. CHAID, in contrast, admits multiple splittings, a feature that allows to exploit the splitting variable more extensively. On the other hand, that procedure depends on premises that are questionable in practical applications. This can be put down to the fact that CHAID relies on simultaneous Chi-Square- resp. F-tests. The null-distribution of the second test statistic, for instance, relies on the normality assumption that is not plausible in a data mining context. Moreover, none of these procedures - as implemented in SPSS, for instance - take ordinal dependent variables into account. In the paper we suggest an alternative tree-algorithm that: Requires explanatory categorical variables

  14. Accurate radiative transfer calculations for layered media.

    Selden, Adrian C

    2016-07-01

    Simple yet accurate results for radiative transfer in layered media with discontinuous refractive index are obtained by the method of K-integrals. These are certain weighted integrals applied to the angular intensity distribution at the refracting boundaries. The radiative intensity is expressed as the sum of the asymptotic angular intensity distribution valid in the depth of the scattering medium and a transient term valid near the boundary. Integrated boundary equations are obtained, yielding simple linear equations for the intensity coefficients, enabling the angular emission intensity and the diffuse reflectance (albedo) and transmittance of the scattering layer to be calculated without solving the radiative transfer equation directly. Examples are given of half-space, slab, interface, and double-layer calculations, and extensions to multilayer systems are indicated. The K-integral method is orders of magnitude more accurate than diffusion theory and can be applied to layered scattering media with a wide range of scattering albedos, with potential applications to biomedical and ocean optics. PMID:27409700

  15. Accurate basis set truncation for wavefunction embedding

    Barnes, Taylor A.; Goodpaster, Jason D.; Manby, Frederick R.; Miller, Thomas F.

    2013-07-01

    Density functional theory (DFT) provides a formally exact framework for performing embedded subsystem electronic structure calculations, including DFT-in-DFT and wavefunction theory-in-DFT descriptions. In the interest of efficiency, it is desirable to truncate the atomic orbital basis set in which the subsystem calculation is performed, thus avoiding high-order scaling with respect to the size of the MO virtual space. In this study, we extend a recently introduced projection-based embedding method [F. R. Manby, M. Stella, J. D. Goodpaster, and T. F. Miller III, J. Chem. Theory Comput. 8, 2564 (2012)], 10.1021/ct300544e to allow for the systematic and accurate truncation of the embedded subsystem basis set. The approach is applied to both covalently and non-covalently bound test cases, including water clusters and polypeptide chains, and it is demonstrated that errors associated with basis set truncation are controllable to well within chemical accuracy. Furthermore, we show that this approach allows for switching between accurate projection-based embedding and DFT embedding with approximate kinetic energy (KE) functionals; in this sense, the approach provides a means of systematically improving upon the use of approximate KE functionals in DFT embedding.

  16. Accurate pose estimation for forensic identification

    Merckx, Gert; Hermans, Jeroen; Vandermeulen, Dirk

    2010-04-01

    In forensic authentication, one aims to identify the perpetrator among a series of suspects or distractors. A fundamental problem in any recognition system that aims for identification of subjects in a natural scene is the lack of constrains on viewing and imaging conditions. In forensic applications, identification proves even more challenging, since most surveillance footage is of abysmal quality. In this context, robust methods for pose estimation are paramount. In this paper we will therefore present a new pose estimation strategy for very low quality footage. Our approach uses 3D-2D registration of a textured 3D face model with the surveillance image to obtain accurate far field pose alignment. Starting from an inaccurate initial estimate, the technique uses novel similarity measures based on the monogenic signal to guide a pose optimization process. We will illustrate the descriptive strength of the introduced similarity measures by using them directly as a recognition metric. Through validation, using both real and synthetic surveillance footage, our pose estimation method is shown to be accurate, and robust to lighting changes and image degradation.

  17. Accurate determination of characteristic relative permeability curves

    Krause, Michael H.; Benson, Sally M.

    2015-09-01

    A recently developed technique to accurately characterize sub-core scale heterogeneity is applied to investigate the factors responsible for flowrate-dependent effective relative permeability curves measured on core samples in the laboratory. The dependency of laboratory measured relative permeability on flowrate has long been both supported and challenged by a number of investigators. Studies have shown that this apparent flowrate dependency is a result of both sub-core scale heterogeneity and outlet boundary effects. However this has only been demonstrated numerically for highly simplified models of porous media. In this paper, flowrate dependency of effective relative permeability is demonstrated using two rock cores, a Berea Sandstone and a heterogeneous sandstone from the Otway Basin Pilot Project in Australia. Numerical simulations of steady-state coreflooding experiments are conducted at a number of injection rates using a single set of input characteristic relative permeability curves. Effective relative permeability is then calculated from the simulation data using standard interpretation methods for calculating relative permeability from steady-state tests. Results show that simplified approaches may be used to determine flowrate-independent characteristic relative permeability provided flow rate is sufficiently high, and the core heterogeneity is relatively low. It is also shown that characteristic relative permeability can be determined at any typical flowrate, and even for geologically complex models, when using accurate three-dimensional models.

  18. Accurate shear measurement with faint sources

    Zhang, Jun; Foucaud, Sebastien [Center for Astronomy and Astrophysics, Department of Physics and Astronomy, Shanghai Jiao Tong University, 955 Jianchuan road, Shanghai, 200240 (China); Luo, Wentao, E-mail: betajzhang@sjtu.edu.cn, E-mail: walt@shao.ac.cn, E-mail: foucaud@sjtu.edu.cn [Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Nandan Road 80, Shanghai, 200030 (China)

    2015-01-01

    For cosmic shear to become an accurate cosmological probe, systematic errors in the shear measurement method must be unambiguously identified and corrected for. Previous work of this series has demonstrated that cosmic shears can be measured accurately in Fourier space in the presence of background noise and finite pixel size, without assumptions on the morphologies of galaxy and PSF. The remaining major source of error is source Poisson noise, due to the finiteness of source photon number. This problem is particularly important for faint galaxies in space-based weak lensing measurements, and for ground-based images of short exposure times. In this work, we propose a simple and rigorous way of removing the shear bias from the source Poisson noise. Our noise treatment can be generalized for images made of multiple exposures through MultiDrizzle. This is demonstrated with the SDSS and COSMOS/ACS data. With a large ensemble of mock galaxy images of unrestricted morphologies, we show that our shear measurement method can achieve sub-percent level accuracy even for images of signal-to-noise ratio less than 5 in general, making it the most promising technique for cosmic shear measurement in the ongoing and upcoming large scale galaxy surveys.

  19. A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification

    Mehdi Khashei

    2015-09-01

    Full Text Available Risk management is one of the most important branches of business and finance. Classification models are the most popular and widely used analytical group of data mining approaches that can greatly help financial decision makers and managers to tackle credit risk problems. However, the literature clearly indicates that, despite proposing numerous classification models, credit scoring is often a difficult task. On the other hand, there is no universal credit-scoring model in the literature that can be accurately and explanatorily used in all circumstances. Therefore, the research for improving the efficiency of credit-scoring models has never stopped. In this paper, a hybrid soft intelligent classification model is proposed for credit-scoring problems. In the proposed model, the unique advantages of the soft computing techniques are used in order to modify the performance of the traditional artificial neural networks in credit scoring. Empirical results of Australian credit card data classifications indicate that the proposed hybrid model outperforms its components, and also other classification models presented for credit scoring. Therefore, the proposed model can be considered as an appropriate alternative tool for binary decision making in business and finance, especially in high uncertainty conditions.

  20. Performance-scalable volumetric data classification for online industrial inspection

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

    2002-03-01

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

  1. Cardiac arrhythmia classification using multi-modal signal analysis.

    Kalidas, V; Tamil, L S

    2016-08-01

    In this paper, as a contribution to the Physionet/Computing in Cardiology 2015 Challenge, we present individual algorithms to accurately classify five different life threatening arrhythmias with the goal of suppressing false alarm generation in intensive care units. Information obtained by analysing electrocardiogram, photoplethysmogram and arterial blood pressure signals was utilized to develop the classification models. Prior to classification, the signals were subject to a signal pre-processing stage for quality analysis. Classification was performed using a combination of support vector machine based machine learning approach and logical analysis techniques. The predicted result for a certain arrhythmia classification model was verified by logical analysis to aid in reduction of false alarms. Separate feature vectors were formed for predicting the presence or absence of each arrhythmia, using both spectral and time-domain information. The training and test data were obtained from the Physionet/CinC Challenge 2015 database. Classification algorithms were written for two different categories of data, namely real-time and retrospective, whose data lengths were 10 s and an additional 30 s, respectively. For the real-time test dataset, sensitivity of 94% and specificity of 82% were obtained. Similarly, for the retrospective test dataset, sensitivity of 94% and specificity of 86% were obtained. PMID:27454417

  2. USING GOOGLE’S KEYWORD RELATION IN MULTIDOMAIN DOCUMENT CLASSIFICATION

    Ping-I Chen

    2013-07-01

    Full Text Available People can collect all kinds of knowledge from search engines to improve the quality of decision making, and use document classification systems to manage the knowledge repository. Document classification systems always need to construct a keyword vector, which always contains thousands of words, to represent the knowledge domain. Thus, the computation complexity of the classification algorithm is very high. Also, users need to download all the documents before extracting the keywords and classifying the documents. In our previous work, we described a new algorithm called “Word AdHoc Network” (WANET and used it to extract the most important sequences of keywords for each document. In this paper, we adapt the WANET system to make it more precise. We will also use a new similarity measurement algorithm, called “Google Purity,” to calculate the similarity between the extracted keyword sequences to classify similar documents together. By using this system, we can easily classify the information in different knowledge domains at the same time, and all the executions are without any pre-established keyword repository. Our experiments show that the classification results are very accurate and useful. This new system can improve the efficiency of document classification and make it more usable in Web-based information management.

  3. Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks

    Martin Längkvist

    2016-04-01

    Full Text Available The availability of high-resolution remote sensing (HRRS data has opened up the possibility for new interesting applications, such as per-pixel classification of individual objects in greater detail. This paper shows how a convolutional neural network (CNN can be applied to multispectral orthoimagery and a digital surface model (DSM of a small city for a full, fast and accurate per-pixel classification. The predicted low-level pixel classes are then used to improve the high-level segmentation. Various design choices of the CNN architecture are evaluated and analyzed. The investigated land area is fully manually labeled into five categories (vegetation, ground, roads, buildings and water, and the classification accuracy is compared to other per-pixel classification works on other land areas that have a similar choice of categories. The results of the full classification and segmentation on selected segments of the map show that CNNs are a viable tool for solving both the segmentation and object recognition task for remote sensing data.

  4. Automatic classification of time-variable X-ray sources

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

  5. Classification of Rainbows

    Ricard, J. L.; Peter, A. L.; Barckicke, J.

    2015-12-01

    CLASSIFICATION OF RAINBOWS Jean Louis Ricard,1,2,* Peter Adams ,2 and Jean Barckicke 2,3 1CNRM, Météo-France,42 Avenue Gaspard Coriolis, 31057 Toulouse, France 2CEPAL, 148 Himley Road, Dudley, West Midlands DY1 2QH, United Kingdom 3DP/Compas,Météo-France,42 Avenue Gaspard Coriolis, 31057 Toulouse, France *Corresponding author: Dr_Jean_Ricard@yahoo,co,ukRainbows are the most beautiful and most spectacular optical atmospheric phenomenon. Humphreys (1964) pointedly noted that "the "explanations" generally given of the rainbow [ in textbooks] may well be said to explain beautifully that which does not occur, and to leave unexplained which does" . . . "The records of close observations of rainbows soon show that not even the colors are always the same". Textbooks stress that the main factor affecting the aspect of the rainbow is the radius of the water droplets. In his well-known textbook entitled "the nature of light & colour in the open air", Minnaert (1954) gives the chief features of the rainbow depending on the diameter of the drops producing it. For this study, we have gathered hundreds of pictures of primary bows. We sort out the pictures into classes. The classes are defined in a such way that rainbows belonging to the same class look similar. Our results are surprising and do not confirm Minnaert's classification. In practice, the size of the water droplets is only a minor factor controlling the overall aspect of the rainbow. The main factor appears to be the height of the sun above the horizon. At sunset, the width of the red band increases, while the width of the other bands of colours decreases. The orange, the violet, the blue and the green bands disappear completely in this order. At the end, the primary bow is mainly red and slightly yellow. Picture = Contrast-enhanced photograph of a primary bow picture (prepared by Andrew Dunn).

  6. An accurate and simple quantum model for liquid water.

    Paesani, Francesco; Zhang, Wei; Case, David A; Cheatham, Thomas E; Voth, Gregory A

    2006-11-14

    The path-integral molecular dynamics and centroid molecular dynamics methods have been applied to investigate the behavior of liquid water at ambient conditions starting from a recently developed simple point charge/flexible (SPC/Fw) model. Several quantum structural, thermodynamic, and dynamical properties have been computed and compared to the corresponding classical values, as well as to the available experimental data. The path-integral molecular dynamics simulations show that the inclusion of quantum effects results in a less structured liquid with a reduced amount of hydrogen bonding in comparison to its classical analog. The nuclear quantization also leads to a smaller dielectric constant and a larger diffusion coefficient relative to the corresponding classical values. Collective and single molecule time correlation functions show a faster decay than their classical counterparts. Good agreement with the experimental measurements in the low-frequency region is obtained for the quantum infrared spectrum, which also shows a higher intensity and a redshift relative to its classical analog. A modification of the original parametrization of the SPC/Fw model is suggested and tested in order to construct an accurate quantum model, called q-SPC/Fw, for liquid water. The quantum results for several thermodynamic and dynamical properties computed with the new model are shown to be in a significantly better agreement with the experimental data. Finally, a force-matching approach was applied to the q-SPC/Fw model to derive an effective quantum force field for liquid water in which the effects due to the nuclear quantization are explicitly distinguished from those due to the underlying molecular interactions. Thermodynamic and dynamical properties computed using standard classical simulations with this effective quantum potential are found in excellent agreement with those obtained from significantly more computationally demanding full centroid molecular dynamics

  7. Vietnamese Document Representation and Classification

    Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

    Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

  8. Small-scale classification schemes

    Hertzum, Morten

    2004-01-01

    important means of discretely balancing the contractual aspect of requirements engineering against facilitating the users in an open-ended search for their system requirements. The requirements classification is analysed in terms of the complementary concepts of boundary objects and coordination mechanisms......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...

  9. Agriculture classification using POLSAR data

    Skriver, Henning; Dall, Jørgen; Ferro-Famil, Laurent;

    2005-01-01

    data, and a very important class of algorithms is the knowledge-based approaches. Here, generic characteristics of different cover types are derived by combining physical reasoning with the available empirical evidence. These are then used to define classification rules. Because of their emphasis on...... the physical content of the SAR data they attempt to generate robust, widely applicable methods, which are nonetheless capable of taking local conditions into account. In this paper a classification approach is presented, that uses a knowledge-based approach, where the crops are first classified into...... crops. This part of the classification process is not as well established as the first part, and both a supervised approach and a knowledge-based approach have been evaluated. Both POLSAR and PolInSAR data may be included in the classification scheme. The classification approach has been evaluated using...

  10. Automated identification of 2612 late-k and M dwarfs in the LAMOST commissioining data using the classification template fits

    Zhong, Jing; Hou, Jinliang; Shen, Shyin; Yuan, Haibo; Huo, Zhiying; Zhang, Huihua; Xiang, Maosheng; Zhang, Huawai; Liu, Xiaowe

    2015-01-01

    We develop a template-fit method to automatically identify and classify late-type K and M dwarfs in spectra from the LAMOST. A search of the commissioning data, acquired in 2009-2010, yields the identification of 2612 late-K and M dwarfs. The template fit method also provides spectral classification to half a subtype, classifies the stars along the dwarf-subdwarf metallicity sequence, and provides improved metallicity/gravity information on a finer scale. The automated search and classification is performed using a set of cool star templates assembled from the Sloan Digital Sky Survey spectroscopic database. We show that the stars can be efficiently classified despite shortcomings in the LAMOST commissioning data which include bright sky lines in the red. In particular we find that the absolute and relative strengths of the critical TiO and CaH molecular bands around 7000A are cleanly measured, which provides accurate spectral typing from late-K to mid-M, and makes it possible to estimate metallicities in a w...

  11. Molecular physics

    Williams, Dudley

    2013-01-01

    Methods of Experimental Physics, Volume 3: Molecular Physics focuses on molecular theory, spectroscopy, resonance, molecular beams, and electric and thermodynamic properties. The manuscript first considers the origins of molecular theory, molecular physics, and molecular spectroscopy, as well as microwave spectroscopy, electronic spectra, and Raman effect. The text then ponders on diffraction methods of molecular structure determination and resonance studies. Topics include techniques of electron, neutron, and x-ray diffraction and nuclear magnetic, nuclear quadropole, and electron spin reson

  12. Using support vector classification for SAR of fentanyl derivatives

    Ning DONG; Wen-cong LU; Nian-yi CHEN; You-cheng ZHU; Kai-xian CHEN

    2005-01-01

    Aim: To discriminate between fentanyl derivatives with high and low activities.Methods: The support vector classification (SVC) method, a novel approach,was employed to investigate structure-activity relationship (SAR) of fentanyl derivatives based on the molecular descriptors, which were quantum parameters including △E [energy difference between highest occupied molecular orbital energy (HOMO) and lowest empty molecular orbital energy (LUMO)], MR(molecular refractivity) and Mr (molecular weight). Results: By using leave-oneout cross-validation test, the accuracies of prediction for activities of fentanyl derivatives in SVC, principal component analysis (PCA), artificial neural network (ANN) and K-nearest neighbor (KNN) models were 93%, 86%, 57%, and 71%, respectively. The results indicated that the performance of the SVC model was better than those of PCA, ANN, and KNN models for this data. Conclusion:SVC can be used to investigate SAR of fentanyl derivatives and could be a promising tool in the field of SAR research.

  13. [Classification and clinicopathological characteristics of gastroenteropancreatic neuroendocrine neoplasms].

    Zengshan, L I

    2016-05-25

    Gastroenteropancreatic neuroendocrine neoplasms are a rare, heterogeneous group of neoplasms. The incidence has increased greatly during the past 40 years, partially due to the advanced endoscopic and imaging techniques. As a type of neoplasm with the specific morphology and immunophenotype, its nomenclature and classification have also been changed considerably over the past 40 years, from the past "carcinoid" to the current "neuroendocrine neoplasm". WHO currently recommends two-tiered classification, neuroendocrine tumors and neuroendocrine cancer, according to the differentiation, morphology and proliferation index. However, the neoplasms from different sites have different phenotypes, biological behaviors, and accordingly the different staging systems for the indication on prognosis and therapy selection. Recent research indicates that the tumor from different sites could express different molecular markers which are useful for the further study of molecular features, as well as the evaluation of the site of primary tumor. Along with the progress of the research on molecular mechanisms, including signal transduction, epigenetics and tumor microenviroment, the mode of diagnosis and treatment would also be changed accordingly. In this article, new advances in classification, clinical and pathological features and molecular mechanism of gastroenteropancreatic neuroendocrine neoplasms will be reviewed. PMID:27045236

  14. On the classification of Yang Mills fields

    A scheme of Classification for Yang Mills fields analogous to the Petrov Classification in general relativity is discussed. It is also shown how such a classification is used to obtain explicit solutions of the equations of motion. (author)

  15. 75 FR 10529 - Mail Classification Change

    2010-03-08

    ... Mail Classification Change AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The... Classification Schedule. The change affects a change in terminology. This notice addresses procedural steps....90 et seq. concerning a change in classification which reflects a change in terminology from...

  16. Sleep Stage Classification Using Unsupervised Feature Learning

    Martin Längkvist

    2012-01-01

    Full Text Available Most attempts at training computers for the difficult and time-consuming task of sleep stage classification involve a feature extraction step. Due to the complexity of multimodal sleep data, the size of the feature space can grow to the extent that it is also necessary to include a feature selection step. In this paper, we propose the use of an unsupervised feature learning architecture called deep belief nets (DBNs and show how to apply it to sleep data in order to eliminate the use of handmade features. Using a postprocessing step of hidden Markov model (HMM to accurately capture sleep stage switching, we compare our results to a feature-based approach. A study of anomaly detection with the application to home environment data collection is also presented. The results using raw data with a deep architecture, such as the DBN, were comparable to a feature-based approach when validated on clinical datasets.

  17. [The study of M dwarf spectral classification].

    Yi, Zhen-Ping; Pan, Jing-Chang; Luo, A-Li

    2013-08-01

    As the most common stars in the galaxy, M dwarfs can be used to trace the structure and evolution of the Milky Way. Besides, investigating M dwarfs is important for searching for habitability of extrasolar planets orbiting M dwarfs. Spectral classification of M dwarfs is a fundamental work. The authors used DR7 M dwarf sample of SLOAN to extract important features from the range of 600-900 nm by random forest method. Compared to the features used in Hammer Code, the authors added three new indices. Our test showed that the improved Hammer with new indices is more accurate. Our method has been applied to classify M dwarf spectra of LAMOST. PMID:24159887

  18. Explosives Classifications Tracking System User Manual

    Genoni, R.P.

    1993-10-01

    The Explosives Classification Tracking System (ECTS) presents information and data for U.S. Department of Energy (DOE) explosives classifications of interest to EM-561, Transportation Management Division, other DOE facilities, and contractors. It is intended to be useful to the scientist, engineer, and transportation professional, who needs to classify or transport explosives. This release of the ECTS reflects upgrading of the software which provides the user with an environment that makes comprehensive retrieval of explosives related information quick and easy. Quarterly updates will be provided to the ECTS throughout its development in FY 1993 and thereafter. The ECTS is a stand alone, single user system that contains unclassified, publicly available information, and administrative information (contractor names, product descriptions, transmittal dates, EX-Numbers, etc.) information from many sources for non-decisional engineering and shipping activities. The data is the most up-to-date and accurate available to the knowledge of the system developer. The system is designed to permit easy revision and updating as new information and data become available. These, additions and corrections are welcomed by the developer. This user manual is intended to help the user install, understand, and operate the system so that the desired information may be readily obtained, reviewed, and reported.

  19. On Machine-Learned Classification of Variable Stars with Sparse and Noisy Time-Series Data

    Richards, Joseph W; Butler, Nathaniel R; Bloom, Joshua S; Brewer, John M; Crellin-Quick, Arien; Higgins, Justin; Kennedy, Rachel; Rischard, Maxime

    2011-01-01

    With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly-observed variables based on a small number of time-series measurements. In this paper, we introduce a methodology for variable-star classification, drawing from modern machine-learning techniques. We describe how to homogenize the information gleaned from light curves by selection and computation of real-numbered metrics ("feature"), detail methods to robustly estimate periodic light-curve features, introduce tree-ensemble methods for accurate variable star classification, and show how to rigorously evaluate the classification results using cross validation. On a 25-class data set of 1542 well-studied variable stars, we achieve a 22.8% overall classification error using the random forest classifier; this represents a 24% improvement over the best previous classifier on these data. This methodology is effective for identifying sam...

  20. FPGA Coprocessor for Accelerated Classification of Images

    Pingree, Paula J.; Scharenbroich, Lucas J.; Werne, Thomas A.

    2008-01-01

    An effort related to that described in the preceding article focuses on developing a spaceborne processing platform for fast and accurate onboard classification of image data, a critical part of modern satellite image processing. The approach again has been to exploit the versatility of recently developed hybrid Virtex-4FX field-programmable gate array (FPGA) to run diverse science applications on embedded processors while taking advantage of the reconfigurable hardware resources of the FPGAs. In this case, the FPGA serves as a coprocessor that implements legacy C-language support-vector-machine (SVM) image-classification algorithms to detect and identify natural phenomena such as flooding, volcanic eruptions, and sea-ice break-up. The FPGA provides hardware acceleration for increased onboard processing capability than previously demonstrated in software. The original C-language program demonstrated on an imaging instrument aboard the Earth Observing-1 (EO-1) satellite implements a linear-kernel SVM algorithm for classifying parts of the images as snow, water, ice, land, or cloud or unclassified. Current onboard processors, such as on EO-1, have limited computing power, extremely limited active storage capability and are no longer considered state-of-the-art. Using commercially available software that translates C-language programs into hardware description language (HDL) files, the legacy C-language program, and two newly formulated programs for a more capable expanded-linear-kernel and a more accurate polynomial-kernel SVM algorithm, have been implemented in the Virtex-4FX FPGA. In tests, the FPGA implementations have exhibited significant speedups over conventional software implementations running on general-purpose hardware.

  1. Accurate Telescope Mount Positioning with MEMS Accelerometers

    Mészáros, László; Pál, András; Csépány, Gergely

    2014-01-01

    This paper describes the advantages and challenges of applying microelectromechanical accelerometer systems (MEMS accelerometers) in order to attain precise, accurate and stateless positioning of telescope mounts. This provides a completely independent method from other forms of electronic, optical, mechanical or magnetic feedback or real-time astrometry. Our goal is to reach the sub-arcminute range which is well smaller than the field-of-view of conventional imaging telescope systems. Here we present how this sub-arcminute accuracy can be achieved with very cheap MEMS sensors and we also detail how our procedures can be extended in order to attain even finer measurements. In addition, our paper discusses how can a complete system design be implemented in order to be a part of a telescope control system.

  2. Accurate estimation of indoor travel times

    Prentow, Thor Siiger; Blunck, Henrik; Stisen, Allan;

    2014-01-01

    the InTraTime method for accurately estimating indoor travel times via mining of historical and real-time indoor position traces. The method learns during operation both travel routes, travel times and their respective likelihood---both for routes traveled as well as for sub-routes thereof. InTraTime...... allows to specify temporal and other query parameters, such as time-of-day, day-of-week or the identity of the traveling individual. As input the method is designed to take generic position traces and is thus interoperable with a variety of indoor positioning systems. The method's advantages include...... a minimal-effort setup and self-improving operations due to unsupervised learning---as it is able to adapt implicitly to factors influencing indoor travel times such as elevators, rotating doors or changes in building layout. We evaluate and compare the proposed InTraTime method to indoor adaptions...

  3. Accurate sky background modelling for ESO facilities

    Full text: Ground-based measurements like e.g. high resolution spectroscopy are heavily influenced by several physical processes. Amongst others, line absorption/ emission, air glow by OH molecules, and scattering of photons within the earth's atmosphere make observations in particular from facilities like the future European extremely large telescope a challenge. Additionally, emission from unresolved extrasolar objects, the zodiacal light, the moon and even thermal emission from the telescope and the instrument contribute significantly to the broad band background over a wide wavelength range. In our talk we review these influences and give an overview on how they can be accurately modeled for increasing the overall precision of spectroscopic and imaging measurements. (author)

  4. Toward Accurate and Quantitative Comparative Metagenomics.

    Nayfach, Stephen; Pollard, Katherine S

    2016-08-25

    Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. PMID:27565341

  5. Accurate valence band width of diamond

    An accurate width is determined for the valence band of diamond by imaging photoelectron momentum distributions for a variety of initial- and final-state energies. The experimental result of 23.0±0.2 eV2 agrees well with first-principles quasiparticle calculations (23.0 and 22.88 eV) and significantly exceeds the local-density-functional width, 21.5±0.2 eV2. This difference quantifies effects of creating an excited hole state (with associated many-body effects) in a band measurement vs studying ground-state properties treated by local-density-functional calculations. copyright 1997 The American Physical Society

  6. TOWARDS MORE ACCURATE CLUSTERING METHOD BY USING DYNAMIC TIME WARPING

    Khadoudja Ghanem

    2013-03-01

    Full Text Available An intrinsic problem of classifiers based on machine learning (ML methods is that their learning time grows as the size and complexity of the training dataset increases. For this reason, it is important to have efficient computational methods and algorithms that can be applied on large datasets, such that it is still possible to complete the machine learning tasks in reasonable time. In this context, we present in this paper a more accurate simple process to speed up ML methods. An unsupervised clustering algorithm is combined with Expectation, Maximization (EM algorithm to develop an efficient Hidden Markov Model (HMM training. The idea of the proposed process consists of two steps. In the first step, training instances with similar inputs are clustered and a weight factor which represents the frequency of these instances is assigned to each representative cluster. Dynamic Time Warping technique is used as a dissimilarity function to cluster similar examples. In the second step, all formulas in the classical HMM training algorithm (EM associated with the number of training instances are modified to include the weight factor in appropriate terms. This process significantly accelerates HMM training while maintaining the same initial, transition and emission probabilities matrixes as those obtained with the classical HMM training algorithm. Accordingly, the classification accuracy is preserved. Depending on the size of the training set, speedups of up to 2200 times is possible when the size is about 100.000 instances. The proposed approach is not limited to training HMMs, but it can be employed for a large variety of MLs methods.

  7. Towards More Accurate Clutering Method by Using Dynamic Time Warping

    Khadoudja Ghanem

    2013-04-01

    Full Text Available An intrinsic problem of classifiers based on machine learning (ML methods is that their learning timegrows as the size and complexity of the training dataset increases. For this reason, it is important to have efficient computational methods and algorithms that can be applied on large datasets, such that it is still possible to complete the machine learning tasks in reasonable time. In this context, we present in this paper a more accurate simple process to speed up ML methods. An unsupervised clustering algorithm is combined with Expectation, Maximization (EM algorithm to develop an efficient Hidden Markov Model (HMM training. The idea of the proposed process consists of two steps. In the first step, training instances with similar inputs are clustered and a weight factor which represents the frequency of these instances is assigned to each representative cluster. Dynamic Time Warping technique is used as a dissimilarity function to cluster similar examples. In the second step, all formulas in the classical HMM training algorithm (EM associated with the number of training instances are modified to include the weight factor in appropriate terms. This process significantly accelerates HMM training while maintaining the same initial, transition and emission probabilities matrixes as those obtained with the classical HMM training algorithm. Accordingly, the classification accuracy is preserved. Depending on the size of the training set, speedups of up to 2200 times is possible when the size is about 100.000 instances. The proposed approach is not limited to training HMMs, but it can be employed for a large variety of MLs methods

  8. Accurate Weather Forecasting for Radio Astronomy

    Maddalena, Ronald J.

    2010-01-01

    The NRAO Green Bank Telescope routinely observes at wavelengths from 3 mm to 1 m. As with all mm-wave telescopes, observing conditions depend upon the variable atmospheric water content. The site provides over 100 days/yr when opacities are low enough for good observing at 3 mm, but winds on the open-air structure reduce the time suitable for 3-mm observing where pointing is critical. Thus, to maximum productivity the observing wavelength needs to match weather conditions. For 6 years the telescope has used a dynamic scheduling system (recently upgraded; www.gb.nrao.edu/DSS) that requires accurate multi-day forecasts for winds and opacities. Since opacity forecasts are not provided by the National Weather Services (NWS), I have developed an automated system that takes available forecasts, derives forecasted opacities, and deploys the results on the web in user-friendly graphical overviews (www.gb.nrao.edu/ rmaddale/Weather). The system relies on the "North American Mesoscale" models, which are updated by the NWS every 6 hrs, have a 12 km horizontal resolution, 1 hr temporal resolution, run to 84 hrs, and have 60 vertical layers that extend to 20 km. Each forecast consists of a time series of ground conditions, cloud coverage, etc, and, most importantly, temperature, pressure, humidity as a function of height. I use the Liebe's MWP model (Radio Science, 20, 1069, 1985) to determine the absorption in each layer for each hour for 30 observing wavelengths. Radiative transfer provides, for each hour and wavelength, the total opacity and the radio brightness of the atmosphere, which contributes substantially at some wavelengths to Tsys and the observational noise. Comparisons of measured and forecasted Tsys at 22.2 and 44 GHz imply that the forecasted opacities are good to about 0.01 Nepers, which is sufficient for forecasting and accurate calibration. Reliability is high out to 2 days and degrades slowly for longer-range forecasts.

  9. Comparative Study of Classification Techniques on Breast Cancer FNA Biopsy Data

    George Rumbe

    2010-12-01

    Full Text Available Accurate diagnostic detection of the cancerous cells in a patient is critical and may alter the subsequent treatment and increase the chances of survival rate. Machine learning techniques have been instrumental in disease detection and are currently being used in various classification problems due to their accurate prediction performance. Various techniques may provide different desired accuracies and it is therefore imperative to use the most suitable method which provides the best desired results. This research seeks to provide comparative analysis of Support Vector Machine, Bayesian classifier and other Artificial neural network classifiers (Backpropagation, linear programming, Learning vector quantization, and K nearest neighborhood on the Wisconsin breast cancer classification problem.

  10. Accurate simulation of optical properties in dyes.

    Jacquemin, Denis; Perpète, Eric A; Ciofini, Ilaria; Adamo, Carlo

    2009-02-17

    Since Antiquity, humans have produced and commercialized dyes. To this day, extraction of natural dyes often requires lengthy and costly procedures. In the 19th century, global markets and new industrial products drove a significant effort to synthesize artificial dyes, characterized by low production costs, huge quantities, and new optical properties (colors). Dyes that encompass classes of molecules absorbing in the UV-visible part of the electromagnetic spectrum now have a wider range of applications, including coloring (textiles, food, paintings), energy production (photovoltaic cells, OLEDs), or pharmaceuticals (diagnostics, drugs). Parallel to the growth in dye applications, researchers have increased their efforts to design and synthesize new dyes to customize absorption and emission properties. In particular, dyes containing one or more metallic centers allow for the construction of fairly sophisticated systems capable of selectively reacting to light of a given wavelength and behaving as molecular devices (photochemical molecular devices, PMDs).Theoretical tools able to predict and interpret the excited-state properties of organic and inorganic dyes allow for an efficient screening of photochemical centers. In this Account, we report recent developments defining a quantitative ab initio protocol (based on time-dependent density functional theory) for modeling dye spectral properties. In particular, we discuss the importance of several parameters, such as the methods used for electronic structure calculations, solvent effects, and statistical treatments. In addition, we illustrate the performance of such simulation tools through case studies. We also comment on current weak points of these methods and ways to improve them. PMID:19113946

  11. Approaching system equilibrium with accurate or not accurate feedback information in a two-route system

    Zhao, Xiao-mei; Xie, Dong-fan; Li, Qi

    2015-02-01

    With the development of intelligent transport system, advanced information feedback strategies have been developed to reduce traffic congestion and enhance the capacity. However, previous strategies provide accurate information to travelers and our simulation results show that accurate information brings negative effects, especially in delay case. Because travelers prefer to the best condition route with accurate information, and delayed information cannot reflect current traffic condition but past. Then travelers make wrong routing decisions, causing the decrease of the capacity and the increase of oscillations and the system deviating from the equilibrium. To avoid the negative effect, bounded rationality is taken into account by introducing a boundedly rational threshold BR. When difference between two routes is less than the BR, routes have equal probability to be chosen. The bounded rationality is helpful to improve the efficiency in terms of capacity, oscillation and the gap deviating from the system equilibrium.

  12. A Unified Methodology for Computing Accurate Quaternion Color Moments and Moment Invariants.

    Karakasis, Evangelos G; Papakostas, George A; Koulouriotis, Dimitrios E; Tourassis, Vassilios D

    2014-02-01

    In this paper, a general framework for computing accurate quaternion color moments and their corresponding invariants is proposed. The proposed unified scheme arose by studying the characteristics of different orthogonal polynomials. These polynomials are used as kernels in order to form moments, the invariants of which can easily be derived. The resulted scheme permits the usage of any polynomial-like kernel in a unified and consistent way. The resulted moments and moment invariants demonstrate robustness to noisy conditions and high discriminative power. Additionally, in the case of continuous moments, accurate computations take place to avoid approximation errors. Based on this general methodology, the quaternion Tchebichef, Krawtchouk, Dual Hahn, Legendre, orthogonal Fourier-Mellin, pseudo Zernike and Zernike color moments, and their corresponding invariants are introduced. A selected paradigm presents the reconstruction capability of each moment family, whereas proper classification scenarios evaluate the performance of color moment invariants. PMID:24216719

  13. Formaldehyde in Absorption: Tracing Molecular Gas in Early-Type Galaxies

    Dollhopf, Niklaus M.; Donovan Meyer, Jennifer

    2016-01-01

    Early-Type Galaxies (ETGs) have been long-classified as the red, ellipsoidal branch of the classic Hubble tuning fork diagram of galactic structure. In part with this classification, ETGs are thought to be molecular and atomic gas-poor with little to no recent star formation. However, recent efforts have questioned this ingrained classification. Most notably, the ATLAS3D survey of 260 ETGs within ~40 Mpc found 22% contain CO, a common tracer for molecular gas. The presence of cold molecular gas also implies the possibility for current star formation within these galaxies. Simulations do not accurately predict the recent observations and further studies are necessary to understand the mechanisms of ETGs.CO traces molecular gas starting at densities of ~102 cm-3, which makes it a good tracer of bulk molecular gas, but does little to constrain the possible locations of star formation within the cores of dense molecular gas clouds. Formaldehyde (H2CO) traces molecular gas on the order of ~104 cm-3, providing a further constraint on the location of star-forming gas, while being simple enough to possibly be abundant in gas-poor ETGs. In cold molecular clouds at or above ~104 cm-3 densities, the structure of formaldehyde enables a phenomenon in which rotational transitions have excitation temperatures driven below the temperature of the cosmic microwave background (CMB), ~2.7 K. Because the CMB radiates isotropically, formaldehyde can be observed in absorption, independent of distance, as a tracer of moderately-dense molecular clouds and star formation.This novel observation technique of formaldehyde was incorporated for observations of twelve CO-detected ETGs from the ATLAS3D sample, including NGC 4710 and PGC 8815, to investigate the presence of cold molecular gas, and possible star formation, in ETGs. We present images from the Very Large Array, used in its C-array configuration, of the J = 11,0 - 11,1 transition of formaldehyde towards these sources. We report our

  14. Nonparametric Bayesian Classification

    Coram, M A

    2002-01-01

    A Bayesian approach to the classification problem is proposed in which random partitions play a central role. It is argued that the partitioning approach has the capacity to take advantage of a variety of large-scale spatial structures, if they are present in the unknown regression function $f_0$. An idealized one-dimensional problem is considered in detail. The proposed nonparametric prior uses random split points to partition the unit interval into a random number of pieces. This prior is found to provide a consistent estimate of the regression function in the $\\L^p$ topology, for any $1 \\leq p < \\infty$, and for arbitrary measurable $f_0:[0,1] \\rightarrow [0,1]$. A Markov chain Monte Carlo (MCMC) implementation is outlined and analyzed. Simulation experiments are conducted to show that the proposed estimate compares favorably with a variety of conventional estimators. A striking resemblance between the posterior mean estimate and the bagged CART estimate is noted and discussed. For higher dimensions, a ...

  15. Classification of titanium dioxide

    In this work the X-ray diffraction (XRD), Scanning Electron Microscopy (Sem) and the X-ray Dispersive Energy Spectroscopy techniques are used with the purpose to achieve a complete identification of phases and mixture of phases of a crystalline material as titanium dioxide. The problem for solving consists of being able to distinguish a sample of titanium dioxide being different than a titanium dioxide pigment. A standard sample of titanium dioxide with NIST certificate is used, which indicates a purity of 99.74% for the TiO2. The following way is recommended to proceed: a)To make an analysis by means of X-ray diffraction technique to the sample of titanium dioxide pigment and on the standard of titanium dioxide waiting not find differences. b) To make a chemical analysis by the X-ray Dispersive Energy Spectroscopy via in a microscope, taking advantage of the high vacuum since it is oxygen which is analysed and if it is concluded that the aluminium oxide appears in a greater proportion to 1% it is established that is a titanium dioxide pigment, but if it is lesser then it will be only titanium dioxide. This type of analysis is an application of the nuclear techniques useful for the tariff classification of merchandise which is considered as of difficult recognition. (Author)

  16. Natural zeolites: structures, classification, origin, occurrence and importance

    Zeolite are hydrated aluminosilicates composed of SiO/sub 4/ and AlO/sub 4/ tetrahedra. The aluminosilicate frameworks contain well defined channels (pores) and cavities . The cavities contain exchangeable cation, in particular sodium, potasium, magnesium, calcium and barium. The dehydrated zeolite behaves like molecular sieve. The zeolites occur both as minerals and as material synthesized in laboratory and on industrial scale. The old classification of recognized species of zeolites was based on morphological properties. A modified classification in based on secondary building units of frameworks. There are different opinions about the origin and occurrence of zeolite minerals. The zeolites have gained much importance as molecular sieves and catalysts. They are also very important for their unique structural properties. (authors)

  17. A simple and rapid molecular method for Leptospira species identification

    A. Ahmed; R.M. Anthony; R.A. Hartskeerl

    2010-01-01

    Serological and DNA-based classification systems only have little correlation. Currently serological and molecular methods for characterizing Leptospira are complex and costly restricting their world-wide distribution and use. Ligation mediated amplification combined with microarray analysis avoidsm

  18. Satellite image classification methods and Landsat 5TM bands

    Tamouk, Jamshid; Farmanbar, Mina

    2013-01-01

    This paper attempts to find the most accurate classification method among parallelepiped, minimum distance and chain methods. Moreover, this study also challenges to find the suitable combination of bands, which can lead to better results in case combinations of bands occur. After comparing these three methods, the chain method over perform the other methods with 79% overall accuracy. Hence, it is more accurate than minimum distance with 67% and parallelepiped with 65%. On the other hand, based on bands features, and also by combining several researchers' findings, a table was created which includes the main objects on the land and the suitable combination of the bands for accurately detecting of landcover objects. During this process, it was observed that band 4 (out of 7 bands of Landsat 5TM) is the band, which can be used for increasing the accuracy of the combined bands in detecting objects on the land.

  19. Recent advances in high-throughput molecular marker identification for superficial and invasive bladder cancers

    Andersen, Lars Dyrskjøt; Zieger, Karsten; Ørntoft, Torben Falck

    2007-01-01

    individually contributed to the management of the disease. However, the development of high-throughput techniques for simultaneous assessment of a large number of markers has allowed classification of tumors into clinically relevant molecular subgroups beyond those possible by pathological classification. Here......, we review the recent advances in high-throughput molecular marker identification for superficial and invasive bladder cancers....

  20. Fast and Provably Accurate Bilateral Filtering.

    Chaudhury, Kunal N; Dabhade, Swapnil D

    2016-06-01

    The bilateral filter is a non-linear filter that uses a range filter along with a spatial filter to perform edge-preserving smoothing of images. A direct computation of the bilateral filter requires O(S) operations per pixel, where S is the size of the support of the spatial filter. In this paper, we present a fast and provably accurate algorithm for approximating the bilateral filter when the range kernel is Gaussian. In particular, for box and Gaussian spatial filters, the proposed algorithm can cut down the complexity to O(1) per pixel for any arbitrary S . The algorithm has a simple implementation involving N+1 spatial filterings, where N is the approximation order. We give a detailed analysis of the filtering accuracy that can be achieved by the proposed approximation in relation to the target bilateral filter. This allows us to estimate the order N required to obtain a given accuracy. We also present comprehensive numerical results to demonstrate that the proposed algorithm is competitive with the state-of-the-art methods in terms of speed and accuracy. PMID:27093722

  1. Accurate adiabatic correction in the hydrogen molecule

    Pachucki, Krzysztof, E-mail: krp@fuw.edu.pl [Faculty of Physics, University of Warsaw, Pasteura 5, 02-093 Warsaw (Poland); Komasa, Jacek, E-mail: komasa@man.poznan.pl [Faculty of Chemistry, Adam Mickiewicz University, Umultowska 89b, 61-614 Poznań (Poland)

    2014-12-14

    A new formalism for the accurate treatment of adiabatic effects in the hydrogen molecule is presented, in which the electronic wave function is expanded in the James-Coolidge basis functions. Systematic increase in the size of the basis set permits estimation of the accuracy. Numerical results for the adiabatic correction to the Born-Oppenheimer interaction energy reveal a relative precision of 10{sup −12} at an arbitrary internuclear distance. Such calculations have been performed for 88 internuclear distances in the range of 0 < R ⩽ 12 bohrs to construct the adiabatic correction potential and to solve the nuclear Schrödinger equation. Finally, the adiabatic correction to the dissociation energies of all rovibrational levels in H{sub 2}, HD, HT, D{sub 2}, DT, and T{sub 2} has been determined. For the ground state of H{sub 2} the estimated precision is 3 × 10{sup −7} cm{sup −1}, which is almost three orders of magnitude higher than that of the best previous result. The achieved accuracy removes the adiabatic contribution from the overall error budget of the present day theoretical predictions for the rovibrational levels.

  2. Accurate fission data for nuclear safety

    Solders, A; Jokinen, A; Kolhinen, V S; Lantz, M; Mattera, A; Penttila, H; Pomp, S; Rakopoulos, V; Rinta-Antila, S

    2013-01-01

    The Accurate fission data for nuclear safety (AlFONS) project aims at high precision measurements of fission yields, using the renewed IGISOL mass separator facility in combination with a new high current light ion cyclotron at the University of Jyvaskyla. The 30 MeV proton beam will be used to create fast and thermal neutron spectra for the study of neutron induced fission yields. Thanks to a series of mass separating elements, culminating with the JYFLTRAP Penning trap, it is possible to achieve a mass resolving power in the order of a few hundred thousands. In this paper we present the experimental setup and the design of a neutron converter target for IGISOL. The goal is to have a flexible design. For studies of exotic nuclei far from stability a high neutron flux (10^12 neutrons/s) at energies 1 - 30 MeV is desired while for reactor applications neutron spectra that resembles those of thermal and fast nuclear reactors are preferred. It is also desirable to be able to produce (semi-)monoenergetic neutrons...

  3. Classification, staging and prognosis of lung cancer

    Lung cancer has increased in incidence throughout the twentieth century and is now the most common cancer in the Western World. It has a poor prognosis, only 10-15% of patients survive 5 years or longer. Outcome is dependent on clinical stage and cancer cell type. Lung cancer is broadly subclassified on the basis of histological features into squamous cell carcinoma, adenocarcinoma, large cell carcinoma and small cell carcinoma. The histopathological type of lung cancer correlates with tumour behaviour and prognosis. Staging based on prognosis is essential in clinical trials comparing different management strategies, and enables universal communication regarding the efficacy of different treatments in specific patient groups. The anatomic extent of disease determined either preoperatively using imaging supplemented by invasive procedures such as mediastinoscopy, and anterior mediastinotomy or following resection are described according to the T-primary tumour, N-regional lymph nodes, M-distant metastasis classification. The International System for Staging Lung Cancer attempts to group together patients with similar prognosis and treatment options. Various combinations of T, N, and M define different clinical or surgical-pathological stages (IA-IV) characterised by different survival characteristics. Refinements in staging based on imaging findings have enabled clinical staging to more accurately reflect the surgical-pathological stage and therefore more accurately predict prognosis. Recent advances including the use of positron emission tomography in combination with conventional staging promises to increase the accuracy of staging and therefore to reduce the number of invasive staging procedures and inappropriate thoracotomies

  4. Proposal for a revised classification of the Demospongiae (Porifera)

    Morrow, Christine; Cardenas, Paco

    2015-01-01

    Background: Demospongiae is the largest sponge class including 81% of all living sponges with nearly 7,000 species worldwide. Systema Porifera (2002) was the result of a large international collaboration to update the Demospongiae higher taxa classification, essentially based on morphological data. Since then, an increasing number of molecular phylogenetic studies have considerably shaken this taxonomic framework, with numerous polyphyletic groups revealed or confirmed and new clades discover...

  5. Understanding Acupuncture Based on ZHENG Classification from System Perspective

    Junwei Fang; Ningning Zheng; Yang Wang; Huijuan Cao; Shujun Sun; Jianye Dai; Qianhua Li; Yongyu Zhang

    2013-01-01

    Acupuncture is an efficient therapy method originated in ancient China, the study of which based on ZHENG classification is a systematic research on understanding its complexity. The system perspective is contributed to understand the essence of phenomena, and, as the coming of the system biology era, broader technology platforms such as omics technologies were established for the objective study of traditional chinese medicine (TCM). Omics technologies could dynamically determine molecular c...

  6. Classification of ductal carcinoma in situ by gene expression profiling

    Hannemann, Juliane; Velds, Arno; Halfwerk, Johannes BG; Kreike, Bas; Johannes L. Peterse; van de Vijver, Marc J

    2006-01-01

    Introduction Ductal carcinoma in situ (DCIS) is characterised by the intraductal proliferation of malignant epithelial cells. Several histological classification systems have been developed, but assessing the histological type/grade of DCIS lesions is still challenging, making treatment decisions based on these features difficult. To obtain insight in the molecular basis of the development of different types of DCIS and its progression to invasive breast cancer, we have studied differences in...

  7. Fast rule-based bioactivity prediction using associative classification mining

    Yu Pulan; Wild David J

    2012-01-01

    Abstract Relating chemical features to bioactivities is critical in molecular design and is used extensively in the lead discovery and optimization process. A variety of techniques from statistics, data mining and machine learning have been applied to this process. In this study, we utilize a collection of methods, called associative classification mining (ACM), which are popular in the data mining community, but so far have not been applied widely in cheminformatics. More specifically, class...

  8. Classification and Phylogenetics of Myxozoa

    Fiala, Ivan; Bartošová-Sojková, Pavla; Whipps, C. M.

    Cham: Springer International Publishing, 2015 - (Okamura, B.; Gruhl, A.; Bartholomew, J.), s. 85-110 ISBN 978-3-319-14752-9 Institutional support: RVO:60077344 Keywords : Taxonomy * Classification * Myxosporea * Actinosporea * Spore * Phylogeny Subject RIV: EG - Zoology

  9. CLASSIFICATION FRAMEWORK FOR COASTAL SYSTEMS

    U.S. Environmental Protection Agency. Classification Framework for Coastal Systems. EPA/600/R-04/061. U.S. Environmental Protection Agency, National Health and Environmental Effects Research Laboratory, Atlantic Ecology Division, Narragansett, RI, Gulf Ecology Division, Gulf Bree...

  10. Classification of Building Object Types

    Jørgensen, Kaj Asbjørn

    2011-01-01

    Development of the existing classification systems has been very difficult and time consuming tasks, where many considerations have been taken and many compromises have been made. The results reveal that, although the theoretical foundation was clarified, many deviations and shortcuts have been...... made. This is certainly the case in the Danish development. Based on the theories about these abstraction mechanisms, the basic principles for classification systems are presented and the observed misconceptions are analyses and explained. Furthermore, it is argued that the purpose of classification...... systems has changed and that new opportunities should be explored. Some proposals for new applications are presented and carefully aligned with IT opportunities. Especially, the use of building modelling will give new benefits and many of the traditional uses of classification systems will instead be...

  11. Classification of Magnetic Nanoparticle Systems

    Bogren, Sara; Fornara, Andrea; Ludwig, Frank;

    2015-01-01

    This study presents classification of different magnetic single- and multi-core particle systems using their measured dynamic magnetic properties together with their nanocrystal and particle sizes. The dynamic magnetic properties are measured with AC (dynamical) susceptometry and magnetorelaxometry...

  12. The classification on short message

    2007-01-01

    This paper discusses the importance of the classification of short message, and details some key technologies related. Through implementing a fundamental prototype, some basic models and technical references are provided.

  13. Biogeography based Satellite Image Classification

    Panchal, V K; Kaur, Navdeep; Kundra, Harish

    2009-01-01

    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternative strategies for satellite image classification so that they may be prepared to select the most appropriate technique for the feature extraction task in hand. This paper is focused on classification of the satellite image of a particular land cover using the theory of Biogeography based Optimization. The original BBO algorithm does not have the inbuilt property of clustering which is required during image classification. Hence modifications have been proposed to the original algorithm and...

  14. The future of general classification

    Mai, Jens Erik

    2013-01-01

    Discusses problems related to accessing multiple collections using a single retrieval language. Surveys the concepts of interoperability and switching language. Finds that mapping between more indexing languages always will be an approximation. Surveys the issues related to general classification...

  15. Ocean acoustic hurricane classification.

    Wilson, Joshua D; Makris, Nicholas C

    2006-01-01

    Theoretical and empirical evidence are combined to show that underwater acoustic sensing techniques may be valuable for measuring the wind speed and determining the destructive power of a hurricane. This is done by first developing a model for the acoustic intensity and mutual intensity in an ocean waveguide due to a hurricane and then determining the relationship between local wind speed and underwater acoustic intensity. From this it is shown that it should be feasible to accurately measure the local wind speed and classify the destructive power of a hurricane if its eye wall passes directly over a single underwater acoustic sensor. The potential advantages and disadvantages of the proposed acoustic method are weighed against those of currently employed techniques. PMID:16454274

  16. Evaluation of the contribution of LiDAR data and postclassification procedures to object-based classification accuracy

    Styers, Diane M.; Moskal, L. Monika; Richardson, Jeffrey J.; Halabisky, Meghan A.

    2014-01-01

    Object-based image analysis (OBIA) is becoming an increasingly common method for producing land use/land cover (LULC) classifications in urban areas. In order to produce the most accurate LULC map, LiDAR data and postclassification procedures are often employed, but their relative contributions to accuracy are unclear. We examined the contribution of LiDAR data and postclassification procedures to increase classification accuracies over using imagery alone and assessed sources of error along an ecologically complex urban-to-rural gradient in Olympia, Washington. Overall classification accuracy and user's and producer's accuracies for individual classes were evaluated. The addition of LiDAR data to the OBIA classification resulted in an 8.34% increase in overall accuracy, while manual postclassification to the imagery+LiDAR classification improved accuracy only an additional 1%. Sources of error in this classification were largely due to edge effects, from which multiple different types of errors result.

  17. Incremental classification of invoice documents

    Hamza, Hatem; Belaïd, Yolande; Belaïd, Abdel; Chaudhuri, Bidyut Baran

    2008-01-01

    ISBN : 978-1-4244-2174-9 International audience This paper deals with incremental classification and its particular application to invoice classification. An improved version of an already existant incremental neural network called IGNG (Incremental Growing Neural Gas) is used for this purpose . This neural network tries to cover the space of data by adding or deleting neurons as data is fed to the system. The improved version of the IGNG, called I2GNG used local thresholds in order to ...

  18. Focal mechanism estimation by classification

    Lasscock, Ben G.; Hall, Brendon J.; Glinsky, Michael E.

    2014-01-01

    A classification technique for identifying focal mechanism type and fault plane orientation based on the polarity of P-wave "first motion" data is derived. A support vector machine is used to classify the polarity data in the space of spherical harmonic functions. The classification is non-parametric in the sense that there is no requirement to make a priori assumptions source mechanism. A metric of similarity potentially able to distinguish shear versus tensile dislocation without requiring ...

  19. Optimizing classification in intelligence processing

    Costica, Yinon

    2010-01-01

    Approved for public release; distribution is unlimited The intelligence making process, often described as the intelligence cycle, consists of phases. Congestion may be experienced in phases that require time consuming tasks such as translation, processing and analysis. To ameliorate the performance of those timeconsuming phases, a preliminary classification of intelligence items regarding their relevance and value to an intelligence request is performed. This classification is subject to ...

  20. Psychiatric classification and subjective experience

    Cooper, Rachel

    2012-01-01

    This article does not directly consider the feelings and emotions that occur in mental illness. Rather, it concerns a higher level methodological question: To what extent is an analysis of feelings and felt emotions of importance for psychiatric classification? Some claim that producing a phenomenologically informed descriptive psychopathology is a prerequisite for serious taxonomic endeavor. Others think that classifications of mental disorders may ignore subjective experience. A middle view...