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  1. Generating Interpretable Fuzzy Systems for Classification Problems

    Directory of Open Access Journals (Sweden)

    Juan A. Contreras-Montes

    2009-12-01

    Full Text Available This paper presents a new method to generate interpretable fuzzy systems from training data to deal with classification problems. The antecedent partition uses triangular sets with 0.5 interpolations avoiding the presence of complex overlapping that happens in another method. Singleton consequents are generated form the projection of the modal values of each triangular membership function into the output space. Least square method is used to adjust the consequents. The proposed method gets a higher average classification accuracy rate than the existing methods with a reduced number of rules andparameters and without sacrificing the fuzzy system interpretability. The proposed approach is applied to two classical classification problems: Iris data and the Wisconsin Breast Cancer classification problem.

  2. Using Genetic Algorithms for Texts Classification Problems

    Directory of Open Access Journals (Sweden)

    A. A. Shumeyko

    2009-01-01

    Full Text Available The avalanche quantity of the information developed by mankind has led to concept of automation of knowledge extraction – Data Mining ([1]. This direction is connected with a wide spectrum of problems - from recognition of the fuzzy set to creation of search machines. Important component of Data Mining is processing of the text information. Such problems lean on concept of classification and clustering ([2]. Classification consists in definition of an accessory of some element (text to one of in advance created classes. Clustering means splitting a set of elements (texts on clusters which quantity are defined by localization of elements of the given set in vicinities of these some natural centers of these clusters. Realization of a problem of classification initially should lean on the given postulates, basic of which – the aprioristic information on primary set of texts and a measure of affinity of elements and classes.

  3. Problems with 'Internet addiction' diagnosis and classification.

    Science.gov (United States)

    Hinić, Darko

    2011-06-01

    Owing to the fact that the Internet is spreading rapidly and influencing all aspects of everyday life, a task is assigned to the academic and clinical circles to establish a diagnosis and provide treatment for disorders brought about by its dysfunctional use. This paper presents a review of the most frequent problems and difficulties in dealing with individuals complaining of the symptoms of Internet use disorder, as well as some suggestions for overcoming and alleviating these problems. For the diagnostic criteria problem, a solution can be provided in the form of behavioural addictions category in order to solve the problem of the classification of not only this disorder but also other forms, such as pathological gambling, compulsive shopping etc. However, since there are obvious similarities with the compulsive behaviour, we suggest the term Internet Use Disorder, which appears most acceptable in terms of avoiding beforehand the indecisiveness of this disorder nature. Certainly, in the practical work with each client, by means of a precise and complex clinical interview, it would be further determined which subtype is under question and whether the mechanism of its realisation is more that of a compulsive or addictive nature. We also suggest an approach of defining a set of minimal key symptoms and manifestations of this problem, rather than singling out the personality profiles of individuals who constitute the population at risk. By prevention, the attentiveness of the public would be in that way directed towards the critical aspects of behaviour, and not towards a vague picture which causes panic and doubt, rather than reasonable ways of the problem solution.

  4. Some debatable problems of stratigraphic classification

    Science.gov (United States)

    Gladenkov, Yury

    2014-05-01

    Russian geologists perform large-scale geological mapping in Russia and abroad. Therefore we urge unification of legends of geological maps compiled in different countries. It seems important to continuously organize discussions on problems of stratigraphic classification. 1. The stratigraphic schools (conventionally called "European" and "American") define "stratigraphy" in different ways. The former prefers "single" stratigraphy that uses data proved by many methods. The latter divides stratigraphy into several independent stratigraphers (litho-, bio-, magneto- and others). Russian geologists classify stratigraphic units into general (chronostratigraphic) and special (in accordance with a method applied). 2. There exist different interpretations of chronostratigraphy. Some stratigraphers suppose that a chronostratigraphic unit corresponds to rock strata formed during a certain time interval (it is somewhat formalistic because a length of interval is frequently unspecified). Russian specialists emphasize the historical-geological background of chronostratigraphic units. Every stratigraphic unit (global and regional) reflects a stage of geological evolution of biosphere and stratisphere. 3. In the view of Russian stratigraphers, the main stratigraphic units may have different extent: a) global (stage), b) regional (regional stage,local zone), and c) local (suite). There is no such hierarchy in the ISG. 4. Russian specialists think that local "lithostratigraphic" units (formations) which may have diachronous boundaries are not chronostratigraphic ones in strict sense (actually they are lithological bodies). In this case "lithostratigraphy" can be considered as "prostratigraphy" and employed in initial studies of sequences. Therefore, a suite is a main local unit of the Russian Code and differs from a formation, although it is somewhat similar. It does not mean that lithostratigraphy is unnecessary. Usage of marker horizons, members and other bodies is of great help

  5. Classification of Ship Routing and Scheduling Problems in Liner Shipping

    DEFF Research Database (Denmark)

    Kjeldsen, Karina Hjortshøj

    2011-01-01

    This article provides a classification scheme for ship routing and scheduling problems in liner shipping in line with the current and future operational conditions of the liner shipping industry. Based on the classification, the literature is divided into groups whose main characteristics...... are described. The literature within each group is reviewed, much of it for the first time....

  6. PROBLEMS AND CLASSIFICATION OF FORMER MILITARY AREAS

    Directory of Open Access Journals (Sweden)

    Svirezhev C.A.

    2014-09-01

    Full Text Available Integration of the Russian Federation in the international community, to find the most effective ways to implement the military and land reforms require a comprehensive study. The paper identifies the main problems that hinder the effective implementation of the reform of the conversion, the ways of their solutions, including use of the experience of the advanced countries of the European Union. Identified military objects to be conversion, shown combining them into groups according to various criteria. Proposed a typology of ex-military territories. Notes the role of the organization of effective land use conversion in the areas of land use planning, identifies the main documents required for the implementation of planned activities. The problems of land use planning conversion ex-military territories.

  7. Congenital muscular dystrophies--problems of classification.

    Science.gov (United States)

    Lenard, H G

    1991-04-01

    The classification of congenital muscular dystrophies (CMD), based on perceived clinical and morphological similarities or differences, is controversial. CMD without cerebral involvement has sometimes been divided into a mild and a severe form. This distinction is, however, arbitrary and not uncontested. Whether Ullrich's disease, formerly called atonic-sclerotic dystrophy, is a disease entity and if so, whether it is a primary muscle disorder, is uncertain. CMD without cerebral involvement is inherited in an autosomal recessive fashion in the great majority of cases. CMDs with cerebral involvement are usually classified into at least three forms: the Fukuyama type of CMD, occurring almost exclusively in Japanese patients; CMD with hypomyelination, sometimes also called the occidental type of cerebromuscular dystrophy; and Walker-Warburg syndrome. Muscle-eye-brain disease, described in a number of Finnish patients, may or may not belong in this last category. In CMD with cerebral involvement inheritance is also autosomal recessive. It is possible that single sporadic cases are phenocopies due to infectious or other exogenous causes. Reports of clinical and morphological findings from an increasing number of patients show a high degree of variability within and, on the other hand, certain similarities between the forms of CMD with cerebral involvement. In addition, neuroradiological changes are also found with increasing frequency in CMD patients without clinical neuropsychological abnormalities. It is not unreasonable to speculate that molecular genetic techniques will reveal in the near future a variable defect in one gene locus or defects in a few gene loci as the cause of the various clinical forms of CMDs.

  8. THE PROBLEMS OF FIXED ASSETS CLASSIFICATION FOR ACCOUNTING

    OpenAIRE

    Kafka, Sophiia

    2017-01-01

    This article provides a critical analysis of research in accounting of fixed assets; the basic issues of fixed assets accounting that have been developed by the Ukrainian scientists during 1999-2016 have been determined. It is established that the problems of non-current assets taxation and their classification are the most noteworthy. In the dissertations the issues of fixed assets classification are of exclusively particular branch nature, so its improvement is important. The purpose of th...

  9. Predicting Assignment Submissions in a Multiclass Classification Problem

    Directory of Open Access Journals (Sweden)

    Bogdan Drăgulescu

    2015-08-01

    Full Text Available Predicting student failure is an important task that can empower educators to counteract the factors that affect student performance. In this paper, a part of the bigger problem of predicting student failure is addressed: predicting the students that do not complete their assignment tasks. For solving this problem, real data collected by our university’s educational platform was used. Because the problem consisted of predicting one of three possible classes (multi-class classification, the appropriate algorithms and methods were selected. Several experiments were carried out to find the best approach for this prediction problem and the used data set. An approach of time segmentation is proposed in order to facilitate the prediction from early on. Methods that address the problems of high dimensionality and imbalanced data were also evaluated. The outcome of each approach is shown and compared in order to select the best performing classification algorithm for the problem at hand.

  10. CLASSIFICATION PROBLEMS OF THE MODERN INDUSTRIAL ENTERPRISES ON RESOURCE GROUNDS

    Directory of Open Access Journals (Sweden)

    G. V. Bushmeleva

    2014-06-01

    Full Text Available Purpose: classification problems of the industrial enterprises on resource grounds for increase of a management efficiency.Methodology: theoretical, generalization, compare.Results: were used in development of theoretical provisions of adaptive management of the industrial enterprises.Practical implications: classification of problems of industrial enterprises were used for developing scientific and mathematical recommendations for management of industrial enterprises based on management analysis which was used in the system of adaptive management.Purchase on Elibrary.ru > Buy nowDOI: http://dx.doi.org/10.12731/2070-7568-2014-3-3

  11. THE PROBLEMS OF FIXED ASSETS CLASSIFICATION FOR ACCOUNTING

    Directory of Open Access Journals (Sweden)

    Sophiia Kafka

    2016-06-01

    Full Text Available This article provides a critical analysis of research in accounting of fixed assets; the basic issues of fixed assets accounting that have been developed by the Ukrainian scientists during 1999-2016 have been determined. It is established that the problems of non-current assets taxation and their classification are the most noteworthy. In the dissertations the issues of fixed assets classification are of exclusively particular branch nature, so its improvement is important. The purpose of the article is developing science-based classification of fixed assets for accounting purposes since their composition is quite diverse. The classification of fixed assets for accounting purposes have been summarized and developed in Figure 1 according to the results of the research. The accomplished analysis of existing approaches to classification of fixed assets has made it possible to specify its basic types and justify the classification criteria of fixed assets for the main objects of fixed assets. Key words: non-current assets, fixed assets, accounting, valuation, classification of the fixed assets. JEL:G M41  

  12. Morphological classification of plant cell deaths

    DEFF Research Database (Denmark)

    van Doorn, W.G.; Beers, E.P.; Dangl, J.L.

    2011-01-01

    Programmed cell death (PCD) is an integral part of plant development and of responses to abiotic stress or pathogens. Although the morphology of plant PCD is, in some cases, well characterised and molecular mechanisms controlling plant PCD are beginning to emerge, there is still confusion about...... the classification of PCD in plants. Here we suggest a classification based on morphological criteria. According to this classification, the use of the term 'apoptosis' is not justified in plants, but at least two classes of PCD can be distinguished: vacuolar cell death and necrosis. During vacuolar cell death......, the cell contents are removed by a combination of autophagy-like process and release of hydrolases from collapsed lytic vacuoles. Necrosis is characterised by early rupture of the plasma membrane, shrinkage of the protoplast and absence of vacuolar cell death features. Vacuolar cell death is common during...

  13. A classification of clinical fat grafting: different problems, different solutions.

    Science.gov (United States)

    Del Vecchio, Daniel; Rohrich, Rod J

    2012-09-01

    Fat grafting has reemerged from a highly variable procedure to a technique with vast reconstructive and cosmetic potential. Largely because of a more disciplined and scientific approach to fat grafting as a transplantation event, early adopters of fat transplantation have begun to approach fat grafting as a process, using sound surgical transplantation principles: recipient preparation, controlled donor harvest, time-efficient transplantation, and proper postoperative care. Despite these principles, different fat grafting techniques yield impressive clinical outcomes. The essential variables of four types of fat grafting cases were identified and compared: harvesting, methods of cell processing, methods of transplantation, and management of the recipient site. Each case differed for most of the variables analyzed. The two clinical drivers that most impacted these differences were the volume demands of the recipient site and whether the recipient site was healthy tissue or pathologic tissue. After these two drivers, a matrix classification of small-volume versus large-volume and regenerative versus nonregenerative cases yields four distinct categories. Not all fat grafting is the same. Fat grafting, once thought to be a simple technique with variable results, is a much more complex procedure with at least four definable subtypes. By defining the essential differences in the recipient site, the key driver in fat transplantation, the proper selection of technique can be best chosen. In fat transplantation, different problems require different solutions.

  14. Fuel cells: Problems and prospects

    OpenAIRE

    Shukla, AK; Ramesh, KV; Kannan, AM

    1986-01-01

    n recent years, fuel cell technology has advanced significantly. Field trials on certain types of fuel cells have shown promise for electrical use. This article reviews the electrochemistry, problems and prospects of fuel cell systems.

  15. An Efficient Optimization Method for Solving Unsupervised Data Classification Problems

    Directory of Open Access Journals (Sweden)

    Parvaneh Shabanzadeh

    2015-01-01

    Full Text Available Unsupervised data classification (or clustering analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.

  16. Oriented Shape Index Histograms for Cell Classification

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo; Dahl, Anders Bjorholm; Larsen, Rasmus

    2015-01-01

    evaluate our new feature descriptor using a public dataset consisting of HEp-2 cell images from indirect immunoflourescence lighting. Our results show that we can improve classification performance significantly when including the shape index orientation. Notably, we show that shape index orientation...

  17. [To the problem of parapsoriasis: classification problems (literature review and personal observations)].

    Science.gov (United States)

    Kozlovskaia, V V; Khaĭkova, E A

    2012-01-01

    In the presented article we discuss the problems of lichenoid and plaque parapsoriasis. The difference in Russian and English classifications are discussed in the historical aspect, as well as review of the literature, and personal authors' observations of nine patients with "small plaque parapsoriasis".

  18. Comparison of four approaches to a rock facies classification problem

    Science.gov (United States)

    Dubois, M.K.; Bohling, Geoffrey C.; Chakrabarti, S.

    2007-01-01

    In this study, seven classifiers based on four different approaches were tested in a rock facies classification problem: classical parametric methods using Bayes' rule, and non-parametric methods using fuzzy logic, k-nearest neighbor, and feed forward-back propagating artificial neural network. Determining the most effective classifier for geologic facies prediction in wells without cores in the Panoma gas field, in Southwest Kansas, was the objective. Study data include 3600 samples with known rock facies class (from core) with each sample having either four or five measured properties (wire-line log curves), and two derived geologic properties (geologic constraining variables). The sample set was divided into two subsets, one for training and one for testing the ability of the trained classifier to correctly assign classes. Artificial neural networks clearly outperformed all other classifiers and are effective tools for this particular classification problem. Classical parametric models were inadequate due to the nature of the predictor variables (high dimensional and not linearly correlated), and feature space of the classes (overlapping). The other non-parametric methods tested, k-nearest neighbor and fuzzy logic, would need considerable improvement to match the neural network effectiveness, but further work, possibly combining certain aspects of the three non-parametric methods, may be justified. ?? 2006 Elsevier Ltd. All rights reserved.

  19. Classification of cell signalling in tissue development.

    Science.gov (United States)

    Platt, Craig Charles; Nicholls, Clare; Brookes, Chris; Wood, Ian

    2011-02-01

    The traditional classification of signalling in biological systems is insufficient and outdated and novel efforts must take into account advances in systems theory, information theory and linguistics. We present some of the classification systems currently used both within and outside of the biological field and discuss some specific aspects of the nature of signalling in tissue development. The analytical methods used in understanding non-biological networks provide a valuable vocabulary, which requires integration and a system of classification to further facilitate development.

  20. Spatial-spectral blood cell classification with microscopic hyperspectral imagery

    Science.gov (United States)

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

    2017-10-01

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

  1. HEp-2 Cell Image Classification With Deep Convolutional Neural Networks.

    Science.gov (United States)

    Gao, Zhimin; Wang, Lei; Zhou, Luping; Zhang, Jianjia

    2017-03-01

    Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of many autoimmune diseases. This paper proposes an automatic framework for this classification task, by utilizing the deep convolutional neural networks (CNNs) which have recently attracted intensive attention in visual recognition. In addition to describing the proposed classification framework, this paper elaborates several interesting observations and findings obtained by our investigation. They include the important factors that impact network design and training, the role of rotation-based data augmentation for cell images, the effectiveness of cell image masks for classification, and the adaptability of the CNN-based classification system across different datasets. Extensive experimental study is conducted to verify the above findings and compares the proposed framework with the well-established image classification models in the literature. The results on benchmark datasets demonstrate that 1) the proposed framework can effectively outperform existing models by properly applying data augmentation, 2) our CNN-based framework has excellent adaptability across different datasets, which is highly desirable for cell image classification under varying laboratory settings. Our system is ranked high in the cell image classification competition hosted by ICPR 2014.

  2. Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem.

    Science.gov (United States)

    Fan, Xitao; Wang, Lin

    The Monte Carlo study compared the performance of predictive discriminant analysis (PDA) and that of logistic regression (LR) for the two-group classification problem. Prior probabilities were used for classification, but the cost of misclassification was assumed to be equal. The study used a fully crossed three-factor experimental design (with…

  3. Identification the Relation between Active Basketball Classification Referees' Empathetic Tendencies and Their Problem Solving Abilities

    Science.gov (United States)

    Karaçam, Aydin; Pulur, Atilla

    2016-01-01

    This study aims to determine the relation between basketball classification referees' problem solving ability and empathetic tendencies. Research model of the study is relational screening model. Sampling of the study is constituted by 124 male and 18 female basketball classification referees who made active refereeing within Turkish Basketball…

  4. Chemometric classification techniques as a tool for solving problems in analytical chemistry.

    Science.gov (United States)

    Bevilacqua, Marta; Nescatelli, Riccardo; Bucci, Remo; Magrì, Andrea D; Magrì, Antonio L; Marini, Federico

    2014-01-01

    Supervised pattern recognition (classification) techniques, i.e., the family of chemometric methods whose aim is the prediction of a qualitative response on a set of samples, represent a very important assortment of tools for solving problems in several areas of applied analytical chemistry. This paper describes the theory behind the chemometric classification techniques most frequently used in analytical chemistry together with some examples of their application to real-world problems.

  5. Automatic music genres classification as a pattern recognition problem

    Science.gov (United States)

    Ul Haq, Ihtisham; Khan, Fauzia; Sharif, Sana; Shaukat, Arsalan

    2013-12-01

    Music genres are the simplest and effect descriptors for searching music libraries stores or catalogues. The paper compares the results of two automatic music genres classification systems implemented by using two different yet simple classifiers (K-Nearest Neighbor and Naïve Bayes). First a 10-12 second sample is selected and features are extracted from it, and then based on those features results of both classifiers are represented in the form of accuracy table and confusion matrix. An experiment carried out on test 60 taken from middle of a song represents the true essence of its genre as compared to the samples taken from beginning and ending of a song. The novel techniques have achieved an accuracy of 91% and 78% by using Naïve Bayes and KNN classifiers respectively.

  6. Educational Environment Risks: Problems of Identification and Classification

    Science.gov (United States)

    Kayumova, Leysan R.; Zakirova, Venera G.

    2016-01-01

    The relevance of the research problem is determined by the multidimensionality of educational environment, that is the system of business and interpersonal relationships of educational process subjects. The maintenance of these relations defines quality and nature of risks for teachers and their pupils. The article aims to identify and justify the…

  7. A Method for the Classification and Retrieval Problem of Reusable Software Resources.

    Science.gov (United States)

    Kim, Yongbeom

    1997-01-01

    Discussion of software reusability focuses on classification and retrieval problems and proposes a method based on encoding semantic information to help solve those problems. Highlights include representation of semantic information; quiddity; the SRM (software resource model) and SRD (software resource diagram); and results of experiments with…

  8. Lymphoma classification update: B-cell non-Hodgkin lymphomas.

    Science.gov (United States)

    Jiang, Manli; Bennani, N Nora; Feldman, Andrew L

    2017-05-01

    Lymphomas are classified based on the normal counterpart, or cell of origin, from which they arise. Because lymphocytes have physiologic immune functions that vary both by lineage and by stage of differentiation, the classification of lymphomas arising from these normal lymphoid populations is complex. Recent genomic data have contributed additional complexity. Areas covered: Lymphoma classification follows the World Health Organization (WHO) system, which reflects international consensus and is based on pathological, genetic, and clinical factors. A 2016 revision to the WHO classification of lymphoid neoplasms recently was reported. The present review focuses on B-cell non-Hodgkin lymphomas, the most common group of lymphomas, and summarizes recent changes most relevant to hematologists and other clinicians who care for lymphoma patients. Expert commentary: Lymphoma classification is a continually evolving field that needs to be responsive to new clinical, pathological, and molecular understanding of lymphoid neoplasia. Among the entities covered in this review, the 2016 revision of the WHO classification particularly impact the subclassification and genetic stratification of diffuse large B-cell lymphoma and high-grade B-cell lymphomas, and reflect evolving criteria and nomenclature for indolent B-cell lymphomas and lymphoproliferative disorders.

  9. Mathematical programming models for classification problems with applications to credit scoring

    OpenAIRE

    Falangis, Konstantinos

    2013-01-01

    Mathematical programming (MP) can be used for developing classification models for the two–group classification problem. An MP model can be used to generate a discriminant function that separates the observations in a training sample of known group membership into the specified groups optimally in terms of a group separation criterion. The simplest models for MP discriminant analysis are linear programming models in which the group separation measure is generally based on th...

  10. Density-conserving affine continuous cellular automata solving the relaxed density classification problem

    International Nuclear Information System (INIS)

    Wolnik, Barbara; Dembowski, Marcin; Bołt, Witold; Baetens, Jan M; De Baets, Bernard

    2017-01-01

    The focus of this paper is on the density classification problem in the context of affine continuous cellular automata. Although such cellular automata cannot solve this problem in the classical sense, most density-conserving affine continuous cellular automata with a unit neighborhood radius are valid solutions of a slightly relaxed version of this problem. This result follows from a detailed study of the dynamics of the density-conserving affine continuous cellular automata that we introduce. (paper)

  11. Comparison of Naive Bayes and Decision Tree on Feature Selection Using Genetic Algorithm for Classification Problem

    Science.gov (United States)

    Rahmadani, S.; Dongoran, A.; Zarlis, M.; Zakarias

    2018-03-01

    This paper discusses the problem of feature selection using genetic algorithms on a dataset for classification problems. The classification model used is the decicion tree (DT), and Naive Bayes. In this paper we will discuss how the Naive Bayes and Decision Tree models to overcome the classification problem in the dataset, where the dataset feature is selectively selected using GA. Then both models compared their performance, whether there is an increase in accuracy or not. From the results obtained shows an increase in accuracy if the feature selection using GA. The proposed model is referred to as GADT (GA-Decision Tree) and GANB (GA-Naive Bayes). The data sets tested in this paper are taken from the UCI Machine Learning repository.

  12. Deep Learning in Label-free Cell Classification

    Science.gov (United States)

    Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

    2016-03-01

    Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

  13. Classification of cancer cell death with spectral dimensionality reduction and generalized eigenvalues.

    Science.gov (United States)

    Guarracino, Mario R; Xanthopoulos, Petros; Pyrgiotakis, Georgios; Tomaino, Vera; Moudgil, Brij M; Pardalos, Panos M

    2011-10-01

    Accurate cell death discrimination is a time consuming and expensive process that can only be performed in biological laboratories. Nevertheless, it is very useful and arises in many biological and medical applications. Raman spectra are collected for 84 samples of A549 cell line (human lung cancer epithelia cells) that has been exposed to toxins to simulate the necrotic and apoptotic death. The proposed data mining approach for the multiclass cell death discrimination problem uses a multiclass regularized generalized eigenvalue algorithm for classification (multiReGEC), together with a dimensionality reduction algorithm based on spectral clustering. The proposed algorithmic scheme can classify A549 lung cancer cells from three different classes (apoptotic death, necrotic death and control cells) with 97.78%± 0.047 accuracy versus 92.22 ± 0.095 without the proposed feature selection preprocessing. The spectrum areas depicted by the algorithm corresponds to the 〉C O bond from the lipids and the lipid bilayer. This chemical structure undergoes different change of state based on cell death type. Further evidence of the validity of the technique is obtained through the successful classification of 7 cell spectra that undergo hyperthermic treatment. In this study we propose a fast and automated way of processing Raman spectra for cell death discrimination, using a feature selection algorithm that not only enhances the classification accuracy, but also gives more insight in the undergoing cell death process. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. PROBLEMS OF CLASSIFICATION AND FORMATION LAND OF AVIATION TRANSPORT

    Directory of Open Access Journals (Sweden)

    Novakovska I. O.

    2017-08-01

    territories. Land-use restrictions on aviation transport on adjacent airport territories cover large areas of land. Formation of aviation land-use and ecologically safe use of land of aviation transport is an extremely topical subject of scientific research in modern conditions. The main task is the development of scientific bases and methodological provisions for the formation, operation and regulation of the use of land potential of the aviation industry and methodological recommendations of land management of objects of aviation transport. The indicated problems were almost not investigated by Ukrainian scientists. The separation of land and property of airports of state, communal and private property is the serious problem in modern time. Due to the violation of the principle that an aerodrome is a strategic object that is not able to privatized, and a terminal is an investment object, including private property, only in 5 years it was possible to return the communal property to the Odessa airport, which in 2011 was transferred to offshore investors. The registration of land occupied has not been completed by other airports, and the corresponding legal documents have been issued to them. In accordance with the State Target Program for the Development of Airports, it is planned to implement a range of appropriate measures to ensure the construction, reconstruction and modernization of facilities. It is necessary to reflect in the State Land Cadastre the data on the registration of aerodrome territories as restrictions on land use associated with the operation of aviation transport, to make necessary changes to the Law of Ukraine "On State Land Cadastre" and the Procedure for State Land Cadastre.

  15. B-cell waste classification sampling plan

    Energy Technology Data Exchange (ETDEWEB)

    HOBART, R.L.

    1999-11-20

    This report documents the methods used to collect samples and analyze data necessary to verify and/or determine the radionuclide content of the 324 Facility B-Cell decontamination and decommissioning waste stream.

  16. The Problems of the Literary-historical Classification of Kafka's Texts

    Directory of Open Access Journals (Sweden)

    Mateja Clara Jelenčič

    2015-12-01

    Full Text Available Attempts at the literary classification of Kafka's texts often prove to be problematic. Most authors are at a loss, so they propose more than classification. The problem of the literary classification of Kafka's texts is treated only in a few German literary encyclopedias and in interpretations and analyses of his texts. In the interpretations and literary analyses Kafka is mostly classified as a Modernist, but some authors see him as a Postmodernist. Most German literary historians and encyclopedia writers are caught in a dilemma about this subject and so propose more than one literary classification: Kafka is assigned to Expressionism and also proclaimed as a representative of the Existentialism, Surrealism or Magic realism. However most German literary historians often assign Kafka to the Expressionism on historical grounds.

  17. Morphological classification of plant cell deaths

    NARCIS (Netherlands)

    Doorn, van W.G.; Beers, E.P.; Dangl, J.L.; Franklin-Tong, V.E.; Woltering, E.J.

    2011-01-01

    Programmed cell death (PCD) is an integral part of plant development and of responses to abiotic stress or pathogens. Although the morphology of plant PCD is, in some cases, well characterised and molecular mechanisms controlling plant PCD are beginning to emerge, there is still confusion about the

  18. Knowledge acquisition from natural language for expert systems based on classification problem-solving methods

    Science.gov (United States)

    Gomez, Fernando

    1989-01-01

    It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM.

  19. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

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

  20. Stock Market Index Data and indicators for Day Trading as a Binary Classification problem.

    Science.gov (United States)

    Bruni, Renato

    2017-02-01

    Classification is the attribution of labels to records according to a criterion automatically learned from a training set of labeled records. This task is needed in a huge number of practical applications, and consequently it has been studied intensively and several classification algorithms are available today. In finance, a stock market index is a measurement of value of a section of the stock market. It is often used to describe the aggregate trend of a market. One basic financial issue would be forecasting this trend. Clearly, such a stochastic value is very difficult to predict. However, technical analysis is a security analysis methodology developed to forecast the direction of prices through the study of past market data. Day trading consists in buying and selling financial instruments within the same trading day. In this case, one interesting problem is the automatic individuation of favorable days for trading. We model this problem as a binary classification problem, and we provide datasets containing daily index values, the corresponding values of a selection of technical indicators, and the class label, which is 1 if the subsequent time period is favorable for day trading and 0 otherwise. These datasets can be used to test the behavior of different approaches in solving the day trading problem.

  1. Stock Market Index Data and indicators for Day Trading as a Binary Classification problem

    Directory of Open Access Journals (Sweden)

    Renato Bruni

    2017-02-01

    Full Text Available Classification is the attribution of labels to records according to a criterion automatically learned from a training set of labeled records. This task is needed in a huge number of practical applications, and consequently it has been studied intensively and several classification algorithms are available today. In finance, a stock market index is a measurement of value of a section of the stock market. It is often used to describe the aggregate trend of a market. One basic financial issue would be forecasting this trend. Clearly, such a stochastic value is very difficult to predict. However, technical analysis is a security analysis methodology developed to forecast the direction of prices through the study of past market data. Day trading consists in buying and selling financial instruments within the same trading day. In this case, one interesting problem is the automatic individuation of favorable days for trading. We model this problem as a binary classification problem, and we provide datasets containing daily index values, the corresponding values of a selection of technical indicators, and the class label, which is 1 if the subsequent time period is favorable for day trading and 0 otherwise. These datasets can be used to test the behavior of different approaches in solving the day trading problem.

  2. A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

    Directory of Open Access Journals (Sweden)

    Zekić-Sušac Marijana

    2014-09-01

    Full Text Available Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART classification trees, support vector machines, and k-nearest neighbour on the same dataset in order to compare their efficiency in the sense of classification accuracy. The performance of each method was compared on ten subsamples in a 10-fold cross-validation procedure in order to assess computing sensitivity and specificity of each model. Results: The artificial neural network model based on multilayer perceptron yielded a higher classification rate than the models produced by other methods. The pairwise t-test showed a statistical significance between the artificial neural network and the k-nearest neighbour model, while the difference among other methods was not statistically significant. Conclusions: Tested machine learning methods are able to learn fast and achieve high classification accuracy. However, further advancement can be assured by testing a few additional methodological refinements in machine learning methods.

  3. A Cost-Sensitive Sparse Representation Based Classification for Class-Imbalance Problem

    Directory of Open Access Journals (Sweden)

    Zhenbing Liu

    2016-01-01

    Full Text Available Sparse representation has been successfully used in pattern recognition and machine learning. However, most existing sparse representation based classification (SRC methods are to achieve the highest classification accuracy, assuming the same losses for different misclassifications. This assumption, however, may not hold in many practical applications as different types of misclassification could lead to different losses. In real-world application, much data sets are imbalanced of the class distribution. To address these problems, we propose a cost-sensitive sparse representation based classification (CSSRC for class-imbalance problem method by using probabilistic modeling. Unlike traditional SRC methods, we predict the class label of test samples by minimizing the misclassification losses, which are obtained via computing the posterior probabilities. Experimental results on the UCI databases validate the efficacy of the proposed approach on average misclassification cost, positive class misclassification rate, and negative class misclassification rate. In addition, we sampled test samples and training samples with different imbalance ratio and use F-measure, G-mean, classification accuracy, and running time to evaluate the performance of the proposed method. The experiments show that our proposed method performs competitively compared to SRC, CSSVM, and CS4VM.

  4. KIPSE1: A Knowledge-based Interactive Problem Solving Environment for data estimation and pattern classification

    Science.gov (United States)

    Han, Chia Yung; Wan, Liqun; Wee, William G.

    1990-01-01

    A knowledge-based interactive problem solving environment called KIPSE1 is presented. The KIPSE1 is a system built on a commercial expert system shell, the KEE system. This environment gives user capability to carry out exploratory data analysis and pattern classification tasks. A good solution often consists of a sequence of steps with a set of methods used at each step. In KIPSE1, solution is represented in the form of a decision tree and each node of the solution tree represents a partial solution to the problem. Many methodologies are provided at each node to the user such that the user can interactively select the method and data sets to test and subsequently examine the results. Otherwise, users are allowed to make decisions at various stages of problem solving to subdivide the problem into smaller subproblems such that a large problem can be handled and a better solution can be found.

  5. Classification of Traffic Related Short Texts to Analyse Road Problems in Urban Areas

    Science.gov (United States)

    Saldana-Perez, A. M. M.; Moreno-Ibarra, M.; Tores-Ruiz, M.

    2017-09-01

    The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media's publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

  6. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

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

  7. A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

    OpenAIRE

    Zekić-Sušac, Marijana; Pfeifer, Sanja; Šarlija, Nataša

    2014-01-01

    Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART ...

  8. Performance of the majority voting rule in solving the density classification problem in high dimensions

    Energy Technology Data Exchange (ETDEWEB)

    Gomez Soto, Jose Manuel [Unidad Academica de Matematicas, Universidad Autonoma de Zacatecas, Calzada Solidaridad entronque Paseo a la Bufa, Zacatecas, Zac. (Mexico); Fuks, Henryk, E-mail: jmgomezgoo@gmail.com, E-mail: hfuks@brocku.ca [Department of Mathematics, Brock University, St. Catharines, ON (Canada)

    2011-11-04

    The density classification problem (DCP) is one of the most widely studied problems in the theory of cellular automata. After it was shown that the DCP cannot be solved perfectly, the research in this area has been focused on finding better rules that could solve the DCP approximately. In this paper, we argue that the majority voting rule in high dimensions can achieve high performance in solving the DCP, and that its performance increases with dimension. We support this conjecture with arguments based on the mean-field approximation and direct computer simulations. (paper)

  9. CLASSIFICATION OF RESTRAINTS IN THE OPTIMIZATION PROBLEM OF A COLD-FORMED PROFILE

    Directory of Open Access Journals (Sweden)

    Agnieszka Łukowicz

    2015-11-01

    Full Text Available This work describes the restraints in the optimization problem. This is an important and complicated issue because it requires taking into account a vast range of information related to the design and production. In order to describe the relations of a specific optimization problem, it is essential to adopt appropriate criteria and to collect information on all kinds of restraints, i.e. boundary conditions. The following paper verifies the various restraints and defines three subsets: design assumptions, technological limitations and standard conditions. The provided classification was made with reference to the analysis of the construction applicability of the newly patented cold-formed profile.

  10. Automated cell type discovery and classification through knowledge transfer

    Science.gov (United States)

    Lee, Hao-Chih; Kosoy, Roman; Becker, Christine E.

    2017-01-01

    Abstract Motivation: Recent advances in mass cytometry allow simultaneous measurements of up to 50 markers at single-cell resolution. However, the high dimensionality of mass cytometry data introduces computational challenges for automated data analysis and hinders translation of new biological understanding into clinical applications. Previous studies have applied machine learning to facilitate processing of mass cytometry data. However, manual inspection is still inevitable and becoming the barrier to reliable large-scale analysis. Results: We present a new algorithm called Automated Cell-type Discovery and Classification (ACDC) that fully automates the classification of canonical cell populations and highlights novel cell types in mass cytometry data. Evaluations on real-world data show ACDC provides accurate and reliable estimations compared to manual gating results. Additionally, ACDC automatically classifies previously ambiguous cell types to facilitate discovery. Our findings suggest that ACDC substantially improves both reliability and interpretability of results obtained from high-dimensional mass cytometry profiling data. Availability and Implementation: A Python package (Python 3) and analysis scripts for reproducing the results are availability on https://bitbucket.org/dudleylab/acdc. Contact: brian.kidd@mssm.edu or joel.dudley@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28158442

  11. Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    Dürr, Oliver; Sick, Beate

    2016-10-01

    Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning methods to high-content screening-based phenotype classification. We trained a deep learning classifier in the form of convolutional neural networks with approximately 40,000 publicly available single-cell images from samples treated with compounds from four classes known to lead to different phenotypes. The input data consisted of multichannel images. The construction of appropriate feature definitions was part of the training and carried out by the convolutional network, without the need for expert knowledge or handcrafted features. We compare our results against the recent state-of-the-art pipeline in which predefined features are extracted from each cell using specialized software and then fed into various machine learning algorithms (support vector machine, Fisher linear discriminant, random forest) for classification. The performance of all classification approaches is evaluated on an untouched test image set with known phenotype classes. Compared to the best reference machine learning algorithm, the misclassification rate is reduced from 8.9% to 6.6%. © 2016 Society for Laboratory Automation and Screening.

  12. Image classification of unlabeled malaria parasites in red blood cells.

    Science.gov (United States)

    Zheng Zhang; Ong, L L Sharon; Kong Fang; Matthew, Athul; Dauwels, Justin; Ming Dao; Asada, Harry

    2016-08-01

    This paper presents a method to detect unlabeled malaria parasites in red blood cells. The current "gold standard" for malaria diagnosis is microscopic examination of thick blood smear, a time consuming process requiring extensive training. Our goal is to develop an automate process to identify malaria infected red blood cells. Major issues in automated analysis of microscopy images of unstained blood smears include overlapping cells and oddly shaped cells. Our approach creates robust templates to detect infected and uninfected red cells. Histogram of Oriented Gradients (HOGs) features are extracted from templates and used to train a classifier offline. Next, the ViolaJones object detection framework is applied to detect infected and uninfected red cells and the image background. Results show our approach out-performs classification approaches with PCA features by 50% and cell detection algorithms applying Hough transforms by 24%. Majority of related work are designed to automatically detect stained parasites in blood smears where the cells are fixed. Although it is more challenging to design algorithms for unstained parasites, our methods will allow analysis of parasite progression in live cells under different drug treatments.

  13. Intraoperative neuropathology of glioma recurrence: cell detection and classification

    Science.gov (United States)

    Abas, Fazly S.; Gokozan, Hamza N.; Goksel, Behiye; Otero, Jose J.; Gurcan, Metin N.

    2016-03-01

    Intraoperative neuropathology of glioma recurrence represents significant visual challenges to pathologists as they carry significant clinical implications. For example, rendering a diagnosis of recurrent glioma can help the surgeon decide to perform more aggressive resection if surgically appropriate. In addition, the success of recent clinical trials for intraoperative administration of therapies, such as inoculation with oncolytic viruses, may suggest that refinement of the intraoperative diagnosis during neurosurgery is an emerging need for pathologists. Typically, these diagnoses require rapid/STAT processing lasting only 20-30 minutes after receipt from neurosurgery. In this relatively short time frame, only dyes, such as hematoxylin and eosin (H and E), can be implemented. The visual challenge lies in the fact that these patients have undergone chemotherapy and radiation, both of which induce cytological atypia in astrocytes, and pathologists are unable to implement helpful biomarkers in their diagnoses. Therefore, there is a need to help pathologists differentiate between astrocytes that are cytologically atypical due to treatment versus infiltrating, recurrent, neoplastic astrocytes. This study focuses on classification of neoplastic versus non-neoplastic astrocytes with the long term goal of providing a better neuropathological computer-aided consultation via classification of cells into reactive gliosis versus recurrent glioma. We present a method to detect cells in H and E stained digitized slides of intraoperative cytologic preparations. The method uses a combination of the `value' component of the HSV color space and `b*' component of the CIE L*a*b* color space to create an enhanced image that suppresses the background while revealing cells on an image. A composite image is formed based on the morphological closing of the hue-luminance combined image. Geometrical and textural features extracted from Discrete Wavelet Frames and combined to classify

  14. The classification problem in machine learning: an overview with study cases in emotion recognition and music-speech differentiation

    OpenAIRE

    Rodríguez Cadavid, Santiago

    2015-01-01

    This work addresses the well-known classification problem in machine learning -- The goal of this study is to approach the reader to the methodological aspects of the feature extraction, feature selection and classifier performance through simple and understandable theoretical aspects and two study cases -- Finally, a very good classification performance was obtained for the emotion recognition from speech

  15. Feature Importance for Human Epithelial (HEp-2 Cell Image Classification

    Directory of Open Access Journals (Sweden)

    Vibha Gupta

    2018-02-01

    Full Text Available Indirect Immuno-Fluorescence (IIF microscopy imaging of human epithelial (HEp-2 cells is a popular method for diagnosing autoimmune diseases. Considering large data volumes, computer-aided diagnosis (CAD systems, based on image-based classification, can help in terms of time, effort, and reliability of diagnosis. Such approaches are based on extracting some representative features from the images. This work explores the selection of the most distinctive features for HEp-2 cell images using various feature selection (FS methods. Considering that there is no single universally optimal feature selection technique, we also propose hybridization of one class of FS methods (filter methods. Furthermore, the notion of variable importance for ranking features, provided by another type of approaches (embedded methods such as Random forest, Random uniform forest is exploited to select a good subset of features from a large set, such that addition of new features does not increase classification accuracy. In this work, we have also, with great consideration, designed class-specific features to capture morphological visual traits of the cell patterns. We perform various experiments and discussions to demonstrate the effectiveness of FS methods along with proposed and a standard feature set. We achieve state-of-the-art performance even with small number of features, obtained after the feature selection.

  16. New fuzzy support vector machine for the class imbalance problem in medical datasets classification.

    Science.gov (United States)

    Gu, Xiaoqing; Ni, Tongguang; Wang, Hongyuan

    2014-01-01

    In medical datasets classification, support vector machine (SVM) is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM) for the class imbalance problem (called FSVM-CIP) is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP.

  17. New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification

    Directory of Open Access Journals (Sweden)

    Xiaoqing Gu

    2014-01-01

    Full Text Available In medical datasets classification, support vector machine (SVM is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM for the class imbalance problem (called FSVM-CIP is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP.

  18. Tight bounds on the size of neural networks for classification problems

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V. [Los Alamos National Lab., NM (United States); Pauw, T. de [Universite Catholique de Louvain, Louvain-la-Neuve (Belgium). Dept. de Mathematique

    1997-06-01

    This paper relies on the entropy of a data-set (i.e., number-of-bits) to prove tight bounds on the size of neural networks solving a classification problem. First, based on a sequence of geometrical steps, the authors constructively compute an upper bound of O(mn) on the number-of-bits for a given data-set - here m is the number of examples and n is the number of dimensions (i.e., R{sup n}). This result is used further in a nonconstructive way to bound the size of neural networks which correctly classify that data-set.

  19. Health problems among detainees in Switzerland: a study using the ICPC-2 classification

    Directory of Open Access Journals (Sweden)

    Bertrand Dominique

    2011-04-01

    Full Text Available Abstract Background Little is known about the health status of prisoners in Switzerland. The aim of this study was to provide a detailed description of the health problems presented by detainees in Switzerland's largest remand prison. Methods In this retrospective cross-sectional study we reviewed the health records of all detainees leaving Switzerland's largest remand prison in 2007. The health problems were coded using the International Classification for Primary Care (ICPC-2. Analyses were descriptive, stratified by gender. Results A total of 2195 health records were reviewed. Mean age was 29.5 years (SD 9.5; 95% were male; 87.8% were migrants. Mean length of stay was 80 days (SD 160. Illicit drug use (40.2% and mental health problems (32.6% were frequent, but most of these detainees (57.6% had more generic primary care problems, such as skin (27.0%, infectious diseases (23.5%, musculoskeletal (19.2%, injury related (18.3%, digestive (15.0% or respiratory problems (14.0%. Furthermore, 7.9% reported exposure to violence during arrest by the police. Conclusion Morbidity is high in this young, predominantly male population of detainees, in particular in relation to substance abuse. Other health problems more commonly seen in general practice are also frequent. These findings support the further development of coordinated primary care and mental health services within detention centers.

  20. Mapping online transportation service quality and multiclass classification problem solving priorities

    Science.gov (United States)

    Alamsyah, Andry; Rachmadiansyah, Imam

    2018-03-01

    Online transportation service is known for its accessibility, transparency, and tariff affordability. These points make online transportation have advantages over the existing conventional transportation service. Online transportation service is an example of disruptive technology that change the relationship between customers and companies. In Indonesia, there are high competition among online transportation provider, hence the companies must maintain and monitor their service level. To understand their position, we apply both sentiment analysis and multiclass classification to understand customer opinions. From negative sentiments, we can identify problems and establish problem-solving priorities. As a case study, we use the most popular online transportation provider in Indonesia: Gojek and Grab. Since many customers are actively give compliment and complain about company’s service level on Twitter, therefore we collect 61,721 tweets in Bahasa during one month observations. We apply Naive Bayes and Support Vector Machine methods to see which model perform best for our data. The result reveal Gojek has better service quality with 19.76% positive and 80.23% negative sentiments than Grab with 9.2% positive and 90.8% negative. The Gojek highest problem-solving priority is regarding application problems, while Grab is about unusable promos. The overall result shows general problems of both case study are related to accessibility dimension which indicate lack of capability to provide good digital access to the end users.

  1. The cell method for electrical engineering and multiphysics problems an introduction

    CERN Document Server

    Alotto, Piergiorgio; Repetto, Maurizio; Rosso, Carlo

    2013-01-01

    This book presents a numerical scheme for the solution of field problems governed by partial differential equations: the cell method. The technique lends itself naturally to the solution of multiphysics problems with several interacting phenomena. The Cell Method, based on a space-time tessellation, is intimately related to the work of Tonti and to his ideas of classification diagrams or, as they are nowadays called, Tonti diagrams: a graphical representation of the problem's equations made possible by a suitable selection of a space-time framework relating physical variables to each other. The main features of the cell method are presented and links with many other discrete numerical methods (finite integration techniques, finite difference time domain, finite volumes, mimetic finite differences, etc.) are discussed. After outlining the theoretical basis of the method, a set of physical problems which have been solved with the cell method is described. These single and multiphysics problems stem from the aut...

  2. Rapid acquisition of mean Raman spectra of eukaryotic cells for a robust single cell classification.

    Science.gov (United States)

    Schie, Iwan W; Kiselev, Roman; Krafft, Christoph; Popp, Jürgen

    2016-11-14

    Raman spectroscopy has previously been used to identify eukaryotic and prokaryotic cells. While prokaryotic cells are small in size and can be assessed by a single Raman spectrum, the larger size of eukaryotic cells and their complex organization requires the acquisition of multiple Raman spectra to properly characterize them. A Raman spectrum from a diffraction-limited spot at an arbitrary location within a cell results in spectral variations that affect classification approaches. To probe whole cells with Raman imaging at high spatial resolution is time consuming, because a large number of Raman spectra need to be collected, resulting in low cell throughput and impairing statistical analysis due to low cell numbers. Here we propose a method to overcome the effects of cellular heterogeneity by acquiring integrated Raman spectra covering a large portion of a cell. The acquired spectrum represents the mean macromolecular composition of a cell with an exposure time that is comparable to acquisition of a single Raman spectrum. Data sets were collected from T lymphocyte Jurkat cells, and pancreatic cell lines Capan1 and MiaPaca2. Cell classification by support vector machines was compared for single spectra, spectra of images and integrated Raman spectra of cells. The integrated approach provides better and more stable prediction for individual cells, and in the current implementation, the mean macromolecular information of a cell can be acquired faster than with the acquisition of individual spectra from a comparable region. It is expected that this approach will have a major impact on the implementation of Raman based cell classification.

  3. Automated cell type discovery and classification through knowledge transfer.

    Science.gov (United States)

    Lee, Hao-Chih; Kosoy, Roman; Becker, Christine E; Dudley, Joel T; Kidd, Brian A

    2017-06-01

    Recent advances in mass cytometry allow simultaneous measurements of up to 50 markers at single-cell resolution. However, the high dimensionality of mass cytometry data introduces computational challenges for automated data analysis and hinders translation of new biological understanding into clinical applications. Previous studies have applied machine learning to facilitate processing of mass cytometry data. However, manual inspection is still inevitable and becoming the barrier to reliable large-scale analysis. We present a new algorithm called utomated ell-type iscovery and lassification (ACDC) that fully automates the classification of canonical cell populations and highlights novel cell types in mass cytometry data. Evaluations on real-world data show ACDC provides accurate and reliable estimations compared to manual gating results. Additionally, ACDC automatically classifies previously ambiguous cell types to facilitate discovery. Our findings suggest that ACDC substantially improves both reliability and interpretability of results obtained from high-dimensional mass cytometry profiling data. A Python package (Python 3) and analysis scripts for reproducing the results are availability on https://bitbucket.org/dudleylab/acdc . brian.kidd@mssm.edu or joel.dudley@mssm.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

  4. Caco-2 cells, biopharmaceutics classification system (BCS) and biowaiver.

    Science.gov (United States)

    Smetanová, Libuse; Stĕtinová, Vĕra; Svoboda, Zbynek; Kvetina, Jaroslav

    2011-01-01

    Almost all orally administered drugs are absorbed across the intestinal mucosa. The Caco-2 monolayers are used as an in vitro model to predict drug absorption in humans and to explore mechanism of drug absorption. The Caco-2 cells are derived from a human colon adenocarcinoma and spontaneously differentiate to form confluent monolayer of polarized cells structurally and functionally resembling the small intestinal epithelium. For studying drug permeability, Caco-2 cells are seeded onto the Transwell inserts with semipermeable membrane and grown to late confluence (21 days). After determination of cell viability, the integrity of monolayer is checked by phenol red permeability and by 14C-mannitol permeability. The transport from apical to basolateral (AP-BL) and basolateral to apical (BL-AP) is studied by adding the diluted drug on the apical or basolateral side and withdrawing the samples from the opposite compartment, respectively, for HPLC analysis or liquid scintillation spectrometry. Ca2+ -free transport medium is used to determine paracellular component of the drug transport. On the basis of permeability and solubility, drugs can be categorized into four classes of Biopharmaceutics Classification System (BCS). For certain drugs, the BCS-based biowaiver approach can be used which enables to reduce in vivo bioequivalence studies.

  5. Classification

    Science.gov (United States)

    Oza, Nikunj C.

    2011-01-01

    A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. In supervised learning, a set of training examples---examples with known output values---is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate's measurements. This chapter discusses methods to perform machine learning, with examples involving astronomy.

  6. Giant cell arteritis. Part I. Terminology, classification, clinical manifestations, diagnosis

    Directory of Open Access Journals (Sweden)

    Azamat Makhmudovich Satybaldyev

    2012-01-01

    Full Text Available Giant cell arteritis (GCA is a vasculitis affecting mainly large and medium-sized arteries, which the classification of systemic vasculitides refers to as those mainly involving the large vessels. GCA is typified by the involvement of extracranial aortic branches and intracranial vessels, the aorta and its large vessels are being affected most frequently. The paper considers the terminology, classification, prevalence, major pathogenic mechanisms, and morphology of GCA. A broad spectrum of its clinical subtypes is due to target vessel stenosis caused by intimal hyperplasia. In 40% of cases, GCA is shown to be accompanied by polymyalgia rheumatica that may either precede or manifest simultaneously with GCA, or follow this disease. The menacing complications of GCA may be visual loss or ischemic strokes at various sites depending on the location of the occluded vessel. Along with the gold standard verification of the diagnosis of GCA, namely temporal artery biopsy, the author indicates other (noninvasive methods for detection of vascular lesions: color Doppler ultrasonography of the temporal arteries, fluorescein angiography of the retina, mag-netic resonance angiography, magnetic resonance imaging, and computed tomography to rule out aortic aneurysm. Dynamic 18F positron emission tomography is demonstrated to play a role in the evaluation of therapeutic effectiveness.

  7. An active learning based classification strategy for the minority class problem: application to histopathology annotation

    Directory of Open Access Journals (Sweden)

    Doyle Scott

    2011-10-01

    the number of annotations necessary to obtain balanced classes. The accuracy of our prediction is verified by empirically-observed costs. Finally, we find that over-sampling the minority class yields a marginal improvement in classifier accuracy but the improved performance comes at the expense of greater annotation cost. Conclusions We have combined AL with class balancing to yield a general training strategy applicable to most supervised classification problems where the dataset is expensive to obtain and which suffers from the minority class problem. An intelligent training strategy is a critical component of supervised classification, but the integration of AL and intelligent choice of class ratios, as well as the application of a general cost model, will help researchers to plan the training process more quickly and effectively.

  8. A Novel SMOTE-Based Classification Approach to Online Data Imbalance Problem

    Directory of Open Access Journals (Sweden)

    Chunlin Gong

    2016-01-01

    Full Text Available In many practical engineering applications, data are usually collected in online pattern. However, if the classes of these data are severely imbalanced, the classification performance will be restricted. In this paper, a novel classification approach is proposed to solve the online data imbalance problem by integrating a fast and efficient learning algorithm, that is, Extreme Learning Machine (ELM, and a typical sampling strategy, that is, the synthetic minority oversampling technique (SMOTE. To reduce the severe imbalance, the granulation division for major-class samples is made according to the samples’ distribution characteristic, and the original samples are replaced by the obtained granule core to prepare a balanced sample set. In online stage, we firstly make granulation division for minor-class and then conduct oversampling using SMOTE in the region around granule core and granule border. Therefore, the training sample set is gradually balanced and the online ELM model is dynamically updated. We also theoretically introduce fuzzy information entropy to prove that the proposed approach has the lower bound of model reliability after undersampling. Numerical experiments are conducted on two different kinds of datasets, and the results demonstrate that the proposed approach outperforms some state-of-the-art methods in terms of the generalization performance and numerical stability.

  9. Proposals for Paraphilic Disorders in the International Classification of Diseases and Related Health Problems, Eleventh Revision (ICD-11)

    OpenAIRE

    Krueger, Richard B.; Reed, Geoffrey M.; First, Michael B.; Marais, Adele; Kismodi, Eszter; Briken, Peer

    2017-01-01

    The World Health Organization is currently developing the 11th revision of the International Classifications of Diseases and Related Health Problems (ICD-11), with approval of the ICD-11 by the World Health Assembly anticipated in 2018. The Working Group on the Classification of Sexual Disorders and Sexual Health (WGSDSH) was created and charged with reviewing and making recommendations for categories related to sexuality that are contained in the chapter of Mental and Behavioural Disorders i...

  10. An investigation of membership functions on performance of ANFIS for solving classification problems

    Science.gov (United States)

    Talpur, Noureen; Salleh, Mohd Najib Mohd; Hussain, Kashif

    2017-08-01

    Adaptive neuro-fuzzy inference system (ANFIS) is one of the efficient machine learning techniques, which has been successfully employed in wide variety of applications. The performance of ANFIS depends on the selection of the number and shape of membership functions as these two factors influence the most on computational complexity and accuracy of the designed ANFIS-based model. Mostly, an expert knowledge is required in this regard. However, there is an immense need of an investigative study for helping researchers make better decision on the number and shape of membership functions for thier ANFIS models. Hence, this study examines the role of four popular shapes of membership functions on the performance of ANFIS while solving various classification problems. According to experiments, Gaussian membership function demonstrated higher degree of accuracy with lesser computational complexity as compared to the counterparts.

  11. An adaptive weighted Lp metric with application to optical remote sensing classification problems

    Science.gov (United States)

    Pratiher, Sawon; Krishnamoorthy, Vigneshram; Bhattacharya, Paritosh

    2017-06-01

    In this contribution, a novel metric learning framework by jointly optimizing the feature space structural coherence manifested by the Cosine similarity measure and the error contribution induced by the Minkowski metric is presented with a loss function involving Mahalanobis distance measure governing the outlier robustness for maximal inter-sample and minimal intra-sample separation of the feature space vectors. The outlier's robustness and scale variation sensitivity of the proposed measure by exploiting the prior statistical entropy of the correlated feature components in weighing the different feature dimensions according to their degree of cohesion within the data clusters and the conceptual architecture for the optimality criterion in terms of the optimal Minkowski exponent, `poptimal' through semi-definite convex optimization with its lower and upper bounds of the proposed distance function have been discussed. Classification results involving special cases of the proposed distance measure on publicly available datasets validates the adequacy of the proposed methodology in remote sensing problems.

  12. New Dandelion Algorithm Optimizes Extreme Learning Machine for Biomedical Classification Problems

    Directory of Open Access Journals (Sweden)

    Xiguang Li

    2017-01-01

    Full Text Available Inspired by the behavior of dandelion sowing, a new novel swarm intelligence algorithm, namely, dandelion algorithm (DA, is proposed for global optimization of complex functions in this paper. In DA, the dandelion population will be divided into two subpopulations, and different subpopulations will undergo different sowing behaviors. Moreover, another sowing method is designed to jump out of local optimum. In order to demonstrate the validation of DA, we compare the proposed algorithm with other existing algorithms, including bat algorithm, particle swarm optimization, and enhanced fireworks algorithm. Simulations show that the proposed algorithm seems much superior to other algorithms. At the same time, the proposed algorithm can be applied to optimize extreme learning machine (ELM for biomedical classification problems, and the effect is considerable. At last, we use different fusion methods to form different fusion classifiers, and the fusion classifiers can achieve higher accuracy and better stability to some extent.

  13. Statistical-mechanics analysis of Gaussian labeled-unlabeled classification problems

    International Nuclear Information System (INIS)

    Tanaka, Toshiyuki

    2013-01-01

    The labeled-unlabeled classification problem in semi-supervised learning is studied via statistical-mechanics approach. We analytically investigate performance of a learner with an equal-weight mixture of two symmetrically-located Gaussians, performing posterior mean estimation of the parameter vector on the basis of a dataset consisting of labeled and unlabeled data generated from the same probability model as that assumed by the learner. Under the assumption of replica symmetry, we have analytically obtained a set of saddle-point equations, which allows us to numerically evaluate performance of the learner. On the basis of the analytical result we have observed interesting phenomena, in particular the coexistence of good and bad solutions, which may happen when the number of unlabeled data is relatively large compared with that of labeled data

  14. Spatial Statistics for Tumor Cell Counting and Classification

    Science.gov (United States)

    Wirjadi, Oliver; Kim, Yoo-Jin; Breuel, Thomas

    To count and classify cells in histological sections is a standard task in histology. One example is the grading of meningiomas, benign tumors of the meninges, which requires to assess the fraction of proliferating cells in an image. As this process is very time consuming when performed manually, automation is required. To address such problems, we propose a novel application of Markov point process methods in computer vision, leading to algorithms for computing the locations of circular objects in images. In contrast to previous algorithms using such spatial statistics methods in image analysis, the present one is fully trainable. This is achieved by combining point process methods with statistical classifiers. Using simulated data, the method proposed in this paper will be shown to be more accurate and more robust to noise than standard image processing methods. On the publicly available SIMCEP benchmark for cell image analysis algorithms, the cell count performance of the present paper is significantly more accurate than results published elsewhere, especially when cells form dense clusters. Furthermore, the proposed system performs as well as a state-of-the-art algorithm for the computer-aided histological grading of meningiomas when combined with a simple k-nearest neighbor classifier for identifying proliferating cells.

  15. Global case studies of soft-sediment deformation structures (SSDS: Definitions, classifications, advances, origins, and problems

    Directory of Open Access Journals (Sweden)

    G. Shanmugam

    2017-10-01

    Problems that hinder our understanding of SSDS still remain. They are: (1 vague definitions of the phrase “soft-sediment deformation”; (2 complex factors that govern the origin of SSDS; (3 omission of vital empirical data in documenting vertical changes in facies using measured sedimentological logs; (4 difficulties in distinguishing depositional processes from tectonic events; (5 a model-driven interpretation of SSDS (i.e., earthquake being the singular cause; (6 routine application of the genetic term “seismites” to the “SSDS”, thus undermining the basic tenet of process sedimentology (i.e., separation of interpretation from observation; (7 the absence of objective criteria to differentiate 21 triggering mechanisms of liquefaction and related SSDS; (8 application of the process concept “high-density turbidity currents”, a process that has never been documented in modern oceans; (9 application of the process concept “sediment creep” with a velocity connotation that cannot be inferred from the ancient record; (10 classification of pockmarks, which are hollow spaces (i.e., without sediments as SSDS, with their problematic origins by fluid expulsion, sediment degassing, fish activity, etc.; (11 application of the Earth's climate-change model; and most importantly, (12 an arbitrary distinction between depositional process and sediment deformation. Despite a profusion of literature on SSDS, our understanding of their origin remains muddled. A solution to the chronic SSDS problem is to utilize the robust core dataset from scientific drilling at sea (DSDP/ODP/IODP with a constrained definition of SSDS.

  16. Revisiting Classification of Eating Disorders-toward Diagnostic and Statistical Manual of Mental Disorders-5 and International Statistical Classification of Diseases and Related Health Problems-11.

    Science.gov (United States)

    Goyal, Shrigopal; Balhara, Yatan Pal Singh; Khandelwal, S K

    2012-07-01

    Two of the most commonly used nosological systems- International Statistical Classification of Diseases and Related Health Problems (ICD)-10 and Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV are under revision. This process has generated a lot of interesting debates with regards to future of the current diagnostic categories. In fact, the status of categorical approach in the upcoming versions of ICD and DSM is also being debated. The current article focuses on the debate with regards to the eating disorders. The existing classification of eating disorders has been criticized for its limitations. A host of new diagnostic categories have been recommended for inclusion in the upcoming revisions. Also the structure of the existing categories has also been put under scrutiny.

  17. Cell classification using big data analytics plus time stretch imaging (Conference Presentation)

    Science.gov (United States)

    Jalali, Bahram; Chen, Claire L.; Mahjoubfar, Ata

    2016-09-01

    We show that blood cells can be classified with high accuracy and high throughput by combining machine learning with time stretch quantitative phase imaging. Our diagnostic system captures quantitative phase images in a flow microscope at millions of frames per second and extracts multiple biophysical features from individual cells including morphological characteristics, light absorption and scattering parameters, and protein concentration. These parameters form a hyperdimensional feature space in which supervised learning and cell classification is performed. We show binary classification of T-cells against colon cancer cells, as well classification of algae cell strains with high and low lipid content. The label-free screening averts the negative impact of staining reagents on cellular viability or cell signaling. The combination of time stretch machine vision and learning offers unprecedented cell analysis capabilities for cancer diagnostics, drug development and liquid biopsy for personalized genomics.

  18. Automatic approach to solve the morphological galaxy classification problem using the sparse representation technique and dictionary learning

    Science.gov (United States)

    Diaz-Hernandez, R.; Ortiz-Esquivel, A.; Peregrina-Barreto, H.; Altamirano-Robles, L.; Gonzalez-Bernal, J.

    2016-06-01

    The observation of celestial objects in the sky is a practice that helps astronomers to understand the way in which the Universe is structured. However, due to the large number of observed objects with modern telescopes, the analysis of these by hand is a difficult task. An important part in galaxy research is the morphological structure classification based on the Hubble sequence. In this research, we present an approach to solve the morphological galaxy classification problem in an automatic way by using the Sparse Representation technique and dictionary learning with K-SVD. For the tests in this work, we use a database of galaxies extracted from the Principal Galaxy Catalog (PGC) and the APM Equatorial Catalogue of Galaxies obtaining a total of 2403 useful galaxies. In order to represent each galaxy frame, we propose to calculate a set of 20 features such as Hu's invariant moments, galaxy nucleus eccentricity, gabor galaxy ratio and some other features commonly used in galaxy classification. A stage of feature relevance analysis was performed using Relief-f in order to determine which are the best parameters for the classification tests using 2, 3, 4, 5, 6 and 7 galaxy classes making signal vectors of different length values with the most important features. For the classification task, we use a 20-random cross-validation technique to evaluate classification accuracy with all signal sets achieving a score of 82.27 % for 2 galaxy classes and up to 44.27 % for 7 galaxy classes.

  19. Text classification

    OpenAIRE

    Deveikis, Karolis

    2016-01-01

    This paper investigates the problem of text classification. The task of text classification is to assign a piece of text to one of several categories based on its content. Text classification is one of the tasks of natural language processing. Like the others, it is often solved using machine learning algorithms. There are many algorithms suitable for text classification. As a result, a problem of choice arises. In an effort to solve this problem, this paper analyzes various feature extractio...

  20. A unified 35-gene signature for both subtype classification and survival prediction in diffuse large B-cell lymphomas.

    Directory of Open Access Journals (Sweden)

    Yu-Dong Cai

    Full Text Available Cancer subtype classification and survival prediction both relate directly to patients' specific treatment plans, making them fundamental medical issues. Although the two factors are interrelated learning problems, most studies tackle each separately. In this paper, expression levels of genes are used for both cancer subtype classification and survival prediction. We considered 350 diffuse large B-cell lymphoma (DLBCL subjects, taken from four groups of patients (activated B-cell-like subtype dead, activated B-cell-like subtype alive, germinal center B-cell-like subtype dead, and germinal center B-cell-like subtype alive. As classification features, we used 11,271 gene expression levels of each subject. The features were first ranked by mRMR (Maximum Relevance Minimum Redundancy principle and further selected by IFS (Incremental Feature Selection procedure. Thirty-five gene signatures were selected after the IFS procedure, and the patients were divided into the above mentioned four groups. These four groups were combined in different ways for subtype prediction and survival prediction, specifically, the activated versus the germinal center and the alive versus the dead. Subtype prediction accuracy of the 35-gene signature was 98.6%. We calculated cumulative survival time of high-risk group and low-risk groups by the Kaplan-Meier method. The log-rank test p-value was 5.98e-08. Our methodology provides a way to study subtype classification and survival prediction simultaneously. Our results suggest that for some diseases, especially cancer, subtype classification may be used to predict survival, and, conversely, survival prediction features may shed light on subtype features.

  1. Support Vector Machine and Parametric Wavelet-Based Texture Classification of Stem Cell Images

    National Research Council Canada - National Science Library

    Jeffreys, Christopher

    2004-01-01

    .... Since colony texture is a major discriminating feature in determining quality, we introduce a non-invasive, semi-automated texture-based stem cell colony classification methodology to aid researchers...

  2. Automatic classification of atypical lymphoid B cells using digital blood image processing.

    Science.gov (United States)

    Alférez, S; Merino, A; Mujica, L E; Ruiz, M; Bigorra, L; Rodellar, J

    2014-08-01

    There are automated systems for digital peripheral blood (PB) cell analysis, but they operate most effectively in nonpathological blood samples. The objective of this work was to design a methodology to improve the automatic classification of abnormal lymphoid cells. We analyzed 340 digital images of individual lymphoid cells from PB films obtained in the CellaVision DM96:150 chronic lymphocytic leukemia (CLL) cells, 100 hairy cell leukemia (HCL) cells, and 90 normal lymphocytes (N). We implemented the Watershed Transformation to segment the nucleus, the cytoplasm, and the peripheral cell region. We extracted 44 features and then the clustering Fuzzy C-Means (FCM) was applied in two steps for the lymphocyte classification. The images were automatically clustered in three groups, one of them with 98% of the HCL cells. The set of the remaining cells was clustered again using FCM and texture features. The two new groups contained 83.3% of the N cells and 71.3% of the CLL cells, respectively. The approach has been able to automatically classify with high precision three types of lymphoid cells. The addition of more descriptors and other classification techniques will allow extending the classification to other classes of atypical lymphoid cells. © 2013 John Wiley & Sons Ltd.

  3. Assessing the Psychosocial Problems In Parenting Sickle-Cell ...

    African Journals Online (AJOL)

    Aim: To assess the psycho social problems encountered in parenting sickle-cell children in Enugu. Method: The subjects include all parents, guardian, foster parents of sickle cell children who have the responsibility of caring for sickle-cell children and who have attended the sickle-cell clinic of the UNTH between June to ...

  4. Standardization of UV-visible data in a food adulteration classification problem.

    Science.gov (United States)

    Di Anibal, Carolina V; Ruisánchez, Itziar; Fernández, Mailén; Forteza, Rafel; Cerdà, Victor; Pilar Callao, M

    2012-10-15

    This study evaluates the performance of multivariate calibration transfer methods in a classification context. The spectral variation caused by some experimental conditions can worsen the performance of the initial multivariate classification model but this situation can be solved by implementing standardization methods such as Piecewise Direct Standardization (PDS). This study looks at the adulteration of culinary spices with banned dyes such as Sudan I, II, III and IV. The samples are characterised by their UV-visible spectra and Partial Least Squares-Discriminant Analysis (PLS-DA) is used to discriminate between unadulterated samples and samples adulterated with any of the four Sudan dyes. Two different datasets that need to be standardised are presented. The standardization process yields positive classification results comparable to those obtained from the initial PLS-DA model, in which high classification performance was achieved. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. Screening for problem gambling within mental health services: a comparison of the classification accuracy of brief instruments.

    Science.gov (United States)

    Dowling, Nicki A; Merkouris, Stephanie S; Manning, Victorian; Volberg, Rachel; Lee, Stuart J; Rodda, Simone N; Lubman, Dan I

    2017-12-23

    Despite the over-representation of people with gambling problems in mental health populations, there is limited information available to guide the selection of brief screening instruments within mental health services. The primary aim was to compare the classification accuracy of nine brief problem gambling screening instruments (two to five items) with a reference standard among patients accessing mental health services. The classification accuracy of nine brief screening instruments was compared with multiple cut-off scores on a reference standard. Eight mental health services in Victoria, Australia. A total of 837 patients were recruited consecutively between June 2015 and January 2016. The brief screening instruments were the Lie/Bet Questionnaire, Brief Problem Gambling Screen (BPGS) (two- to five-item versions), NODS-CLiP, NODS-CLiP2, Brief Biosocial Gambling Screen (BBGS) and NODS-PERC. The Problem Gambling Severity Index (PGSI) was the reference standard. The five-item BPGS was the only instrument displaying satisfactory classification accuracy in detecting any level of gambling problem (low-risk, moderate-risk or problem gambling) (sensitivity = 0.803, specificity = 0.982, diagnostic efficiency = 0.943). Several shorter instruments adequately detected both problem and moderate-risk, but not low-risk, gambling: two three-item instruments (NODS-CLiP, three-item BPGS) and two four-item instruments (NODS-PERC, four-item BPGS) (sensitivity = 0.854-0.966, specificity = 0.901-0.954, diagnostic efficiency = 0.908-0.941). The four-item instruments, however, did not provide any considerable advantage over the three-item instruments. Similarly, the very brief (two-item) instruments (Lie/Bet and two-item BPGS) adequately detected problem gambling (sensitivity = 0.811-0.868, specificity = 0.938-0.943, diagnostic efficiency = 0.933-0.934), but not moderate-risk or low-risk gambling. The optimal brief screening instrument for mental health services

  6. [Classification of cell-based medicinal products and legal implications: An overview and an update].

    Science.gov (United States)

    Scherer, Jürgen; Flory, Egbert

    2015-11-01

    In general, cell-based medicinal products do not represent a uniform class of medicinal products, but instead comprise medicinal products with diverse regulatory classification as advanced-therapy medicinal products (ATMP), medicinal products (MP), tissue preparations, or blood products. Due to the legal and scientific consequences of the development and approval of MPs, classification should be clarified as early as possible. This paper describes the legal situation in Germany and highlights specific criteria and concepts for classification, with a focus on, but not limited to, ATMPs and non-ATMPs. Depending on the stage of product development and the specific application submitted to a competent authority, legally binding classification is done by the German Länder Authorities, Paul-Ehrlich-Institut, or European Medicines Agency. On request by the applicants, the Committee for Advanced Therapies may issue scientific recommendations for classification.

  7. A deep convolutional neural network for classification of red blood cells in sickle cell anemia.

    Science.gov (United States)

    Xu, Mengjia; Papageorgiou, Dimitrios P; Abidi, Sabia Z; Dao, Ming; Zhao, Hong; Karniadakis, George Em

    2017-10-01

    Sickle cell disease (SCD) is a hematological disorder leading to blood vessel occlusion accompanied by painful episodes and even death. Red blood cells (RBCs) of SCD patients have diverse shapes that reveal important biomechanical and bio-rheological characteristics, e.g. their density, fragility, adhesive properties, etc. Hence, having an objective and effective way of RBC shape quantification and classification will lead to better insights and eventual better prognosis of the disease. To this end, we have developed an automated, high-throughput, ex-vivo RBC shape classification framework that consists of three stages. First, we present an automatic hierarchical RBC extraction method to detect the RBC region (ROI) from the background, and then separate touching RBCs in the ROI images by applying an improved random walk method based on automatic seed generation. Second, we apply a mask-based RBC patch-size normalization method to normalize the variant size of segmented single RBC patches into uniform size. Third, we employ deep convolutional neural networks (CNNs) to realize RBC classification; the alternating convolution and pooling operations can deal with non-linear and complex patterns. Furthermore, we investigate the specific shape factor quantification for the classified RBC image data in order to develop a general multiscale shape analysis. We perform several experiments on raw microscopy image datasets from 8 SCD patients (over 7,000 single RBC images) through a 5-fold cross validation method both for oxygenated and deoxygenated RBCs. We demonstrate that the proposed framework can successfully classify sickle shape RBCs in an automated manner with high accuracy, and we also provide the corresponding shape factor analysis, which can be used synergistically with the CNN analysis for more robust predictions. Moreover, the trained deep CNN exhibits good performance even for a deoxygenated dataset and distinguishes the subtle differences in texture alteration

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

    Science.gov (United States)

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

    2017-08-01

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

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

    Science.gov (United States)

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

    2017-08-01

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

  10. Learning semantic histopathological representation for basal cell carcinoma classification

    Science.gov (United States)

    Gutiérrez, Ricardo; Rueda, Andrea; Romero, Eduardo

    2013-03-01

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

  11. A modified decision tree algorithm based on genetic algorithm for mobile user classification problem.

    Science.gov (United States)

    Liu, Dong-sheng; Fan, Shu-jiang

    2014-01-01

    In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity.

  12. Spectral Classification of Similar Materials using the Tetracorder Algorithm: The Calcite-Epidote-Chlorite Problem

    Science.gov (United States)

    Dalton, J. Brad; Bove, Dana; Mladinich, Carol; Clark, Roger; Rockwell, Barnaby; Swayze, Gregg; King, Trude; Church, Stanley

    2001-01-01

    Recent work on automated spectral classification algorithms has sought to distinguish ever-more similar materials. From modest beginnings separating shade, soil, rock and vegetation to ambitious attempts to discriminate mineral types and specific plant species, the trend seems to be toward using increasingly subtle spectral differences to perform the classification. Rule-based expert systems exploiting the underlying physics of spectroscopy such as the US Geological Society Tetracorder system are now taking advantage of the high spectral resolution and dimensionality of current imaging spectrometer designs to discriminate spectrally similar materials. The current paper details recent efforts to discriminate three minerals having absorptions centered at the same wavelength, with encouraging results.

  13. Compound classification by computer treatment of low resolution mass spectra - Application to geochemical and environmental problems.

    Science.gov (United States)

    Smith, D. H.; Eglinton, G.

    1972-01-01

    A description is given of a development of computer analysis of low-resolution chromatographic-mass spectrometric data, which provides a preliminary classification of an unknown spectrum as a listing of candidate classes of compounds. This procedure, referred to as COMSOC (Classification of Mass Spectra on Computers), operates by converting an incoming unknown mass spectrum into a simplified key word which is then compared with each of the key words held in its reference file. The advantages of COMSOC in characterizing complex mixtures are emphasized.

  14. Conceptual process models and quantitative analysis of classification problems in Scrum software development practices

    NARCIS (Netherlands)

    Helwerda, L.S.; Niessink, F.; Verbeek, F.J.

    2017-01-01

    We propose a novel classification method that integrates into existing agile software development practices by collecting data records generated by software and tools used in the development process. We extract features from the collected data and create visualizations that provide insights,

  15. Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology

    Science.gov (United States)

    Sharma, Harshita; Zerbe, Norman; Heim, Daniel; Wienert, Stephan; Lohmann, Sebastian; Hellwich, Olaf; Hufnagl, Peter

    2016-03-01

    This paper describes a novel graph-based method for efficient representation and subsequent classification in histological whole slide images of gastric cancer. Her2/neu immunohistochemically stained and haematoxylin and eosin stained histological sections of gastric carcinoma are digitized. Immunohistochemical staining is used in practice by pathologists to determine extent of malignancy, however, it is laborious to visually discriminate the corresponding malignancy levels in the more commonly used haematoxylin and eosin stain, and this study attempts to solve this problem using a computer-based method. Cell nuclei are first isolated at high magnification using an automatic cell nuclei segmentation strategy, followed by construction of cell nuclei attributed relational graphs of the tissue regions. These graphs represent tissue architecture comprehensively, as they contain information about cell nuclei morphology as vertex attributes, along with knowledge of neighborhood in the form of edge linking and edge attributes. Global graph characteristics are derived and ensemble learning is used to discriminate between three types of malignancy levels, namely, non-tumor, Her2/neu positive tumor and Her2/neu negative tumor. Performance is compared with state of the art methods including four texture feature groups (Haralick, Gabor, Local Binary Patterns and Varma Zisserman features), color and intensity features, and Voronoi diagram and Delaunay triangulation. Texture, color and intensity information is also combined with graph-based knowledge, followed by correlation analysis. Quantitative assessment is performed using two cross validation strategies. On investigating the experimental results, it can be concluded that the proposed method provides a promising way for computer-based analysis of histopathological images of gastric cancer.

  16. HEp-2 cell image classification method based on very deep convolutional networks with small datasets

    Science.gov (United States)

    Lu, Mengchi; Gao, Long; Guo, Xifeng; Liu, Qiang; Yin, Jianping

    2017-07-01

    Human Epithelial-2 (HEp-2) cell images staining patterns classification have been widely used to identify autoimmune diseases by the anti-Nuclear antibodies (ANA) test in the Indirect Immunofluorescence (IIF) protocol. Because manual test is time consuming, subjective and labor intensive, image-based Computer Aided Diagnosis (CAD) systems for HEp-2 cell classification are developing. However, methods proposed recently are mostly manual features extraction with low accuracy. Besides, the scale of available benchmark datasets is small, which does not exactly suitable for using deep learning methods. This issue will influence the accuracy of cell classification directly even after data augmentation. To address these issues, this paper presents a high accuracy automatic HEp-2 cell classification method with small datasets, by utilizing very deep convolutional networks (VGGNet). Specifically, the proposed method consists of three main phases, namely image preprocessing, feature extraction and classification. Moreover, an improved VGGNet is presented to address the challenges of small-scale datasets. Experimental results over two benchmark datasets demonstrate that the proposed method achieves superior performance in terms of accuracy compared with existing methods.

  17. Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems

    Directory of Open Access Journals (Sweden)

    DimitrisG. Stavrakoudis

    2012-04-01

    Full Text Available This paper introduces the Fast Iterative Rule-based Linguistic Classifier (FaIRLiC, a Genetic Fuzzy Rule-Based Classification System (GFRBCS which targets at reducing the structural complexity of the resulting rule base, as well as its learning algorithm's computational requirements, especially when dealing with high-dimensional feature spaces. The proposed methodology follows the principles of the iterative rule learning (IRL approach, whereby a rule extraction algorithm (REA is invoked in an iterative fashion, producing one fuzzy rule at a time. The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the previously selected subset of features. The performance of the classifier is finally optimized through a genetic tuning post-processing stage. Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing and compact fuzzy rule-based classifiers, even for very high-dimensional feature spaces.

  18. Molecular and Translational Classifications of DAMPs in Immunogenic Cell Death

    Directory of Open Access Journals (Sweden)

    Abhishek D Garg

    2015-11-01

    Full Text Available The immunogenicity of malignant cells has recently been acknowledged as a critical determinant of efficacy in cancer therapy. Thus, besides developing direct immunostimulatory regimens including dendritic cell-based vaccines, checkpoint-blocking therapies, and adoptive T-cell transfer, researchers have started to focus on the overall immunobiology of neoplastic cells. It is now clear that cancer cells can succumb to some anticancer therapies by undergoing a peculiar form of cell death that is characterized by an increased immunogenic potential, owing to the emission of so-called damage-associated molecular patterns (DAMPs. The emission of DAMPs and other immunostimulatory factors by cells succumbing to immunogenic cell death (ICD favors the establishment of a productive interface with the immune system. This results in the elicitation of tumor-targeting immune responses associated with the elimination of residual, treatment-resistant cancer cells, as well as with the establishment of immunological memory. Although ICD has been characterized with increased precision since its discovery, several questions remain to be addressed. Here, we summarize and tabulate the main molecular, immunological, preclinical and clinical aspects of ICD, in an attempt to capture the essence of this clinically relevant phenomenon, and identify future challenges for this rapidly expanding field of investigation.

  19. Magnetic tomography for fuel cells-current status and problems

    International Nuclear Information System (INIS)

    Hauer, Karl-Heinz; Potthast, Roland

    2007-01-01

    We provide a survey about the status and open problems for magnetic tomography for fuel cells. A number of papers are reviewed which develop the subject including theory of simulation and inversion, uniqueness questions, reconstruction algorithms and real data applications. In particular, this work describes a number of yet unpublished results and experiments. Our goal is to provide a complete picture of the status-quo of magnetic tomography for fuel cells which includes the recent scientific and engineering results as well as an introduction into open questions and upcoming developments. We believe that magnetic tomography as an ill-posed and non-unique inverse source problem reflects key problems of many applied inverse problems. In particular, the challenges of real data applications reflect the challenges of the area of inverse problems as a whole and provide inside into generic problems of this important area of applied mathematics

  20. Correlation between patients' reasons for encounters/health problems and population density in Japan: a systematic review of observational studies coded by the International Classification of Health Problems in Primary Care (ICHPPC) and the International Classification of Primary care (ICPC).

    Science.gov (United States)

    Kaneko, Makoto; Ohta, Ryuichi; Nago, Naoki; Fukushi, Motoharu; Matsushima, Masato

    2017-09-13

    The Japanese health care system has yet to establish structured training for primary care physicians; therefore, physicians who received an internal medicine based training program continue to play a principal role in the primary care setting. To promote the development of a more efficient primary health care system, the assessment of its current status in regard to the spectrum of patients' reasons for encounters (RFEs) and health problems is an important step. Recognizing the proportions of patients' RFEs and health problems, which are not generally covered by an internist, can provide valuable information to promote the development of a primary care physician-centered system. We conducted a systematic review in which we searched six databases (PubMed, the Cochrane Library, Google Scholar, Ichushi-Web, JDreamIII and CiNii) for observational studies in Japan coded by International Classification of Health Problems in Primary Care (ICHPPC) and International Classification of Primary Care (ICPC) up to March 2015. We employed population density as index of accessibility. We calculated Spearman's rank correlation coefficient to examine the correlation between the proportion of "non-internal medicine-related" RFEs and health problems in each study area in consideration of the population density. We found 17 studies with diverse designs and settings. Among these studies, "non-internal medicine-related" RFEs, which was not thought to be covered by internists, ranged from about 4% to 40%. In addition, "non-internal medicine-related" health problems ranged from about 10% to 40%. However, no significant correlation was found between population density and the proportion of "non-internal medicine-related" RFEs and health problems. This is the first systematic review on RFEs and health problems coded by ICHPPC and ICPC undertaken to reveal the diversity of health problems in Japanese primary care. These results suggest that primary care physicians in some rural areas of Japan

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

    DEFF Research Database (Denmark)

    Rossing, Maria

    2013-01-01

    The incidence of thyroid cancer is increasing worldwide and thyroid nodules are a frequent clinical finding. Diagnosing follicular cell-derived cancers is, however, challenging both histopathologically and especially cytopathologically. The advent of high-throughput molecular technologies has...... profiling of follicular cell-derived thyroid cancers....... 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...

  2. Improved classification, diagnosis and prognosis of canine round cell tumours

    NARCIS (Netherlands)

    Cangul, Taci

    2001-01-01

    As the name suggests, canine round cell tumour (RCTs) are composed of cells with a round morphology. There is some discrepancy amongst authors as to which tumours belong to this category, but most designate lymphomas, melanomas, plasmacytomas, transmissible venereal tumours (TVTs), histiocytomas,

  3. Multiparametric classification links tumor microenvironments with tumor cell phenotype.

    Directory of Open Access Journals (Sweden)

    Bojana Gligorijevic

    2014-11-01

    Full Text Available While it has been established that a number of microenvironment components can affect the likelihood of metastasis, the link between microenvironment and tumor cell phenotypes is poorly understood. Here we have examined microenvironment control over two different tumor cell motility phenotypes required for metastasis. By high-resolution multiphoton microscopy of mammary carcinoma in mice, we detected two phenotypes of motile tumor cells, different in locomotion speed. Only slower tumor cells exhibited protrusions with molecular, morphological, and functional characteristics associated with invadopodia. Each region in the primary tumor exhibited either fast- or slow-locomotion. To understand how the tumor microenvironment controls invadopodium formation and tumor cell locomotion, we systematically analyzed components of the microenvironment previously associated with cell invasion and migration. No single microenvironmental property was able to predict the locations of tumor cell phenotypes in the tumor if used in isolation or combined linearly. To solve this, we utilized the support vector machine (SVM algorithm to classify phenotypes in a nonlinear fashion. This approach identified conditions that promoted either motility phenotype. We then demonstrated that varying one of the conditions may change tumor cell behavior only in a context-dependent manner. In addition, to establish the link between phenotypes and cell fates, we photoconverted and monitored the fate of tumor cells in different microenvironments, finding that only tumor cells in the invadopodium-rich microenvironments degraded extracellular matrix (ECM and disseminated. The number of invadopodia positively correlated with degradation, while the inhibiting metalloproteases eliminated degradation and lung metastasis, consistent with a direct link among invadopodia, ECM degradation, and metastasis. We have detected and characterized two phenotypes of motile tumor cells in vivo, which

  4. Peripheral T-cell lymphomas: an evaluation of reproducibility of the updated Kiel classification.

    Science.gov (United States)

    Hastrup, N; Hamilton-Dutoit, S; Ralfkiaer, E; Pallesen, G

    1991-02-01

    Haematoxylin and eosin, and Giemsa stained sections from 100 peripheral T-cell lymphomas were examined blind on two occasions by four experienced haematopathologists in order to evaluate the inter- and intra-observer reproducibility of the updated Kiel classification for these malignancies. In all cases, the T-cell phenotype had been established previously in frozen section using a panel of monoclonal antibodies. Analysis by kappa statistics showed poor reproducibility, both overall and for most subtypes, with the exception of large cell anaplastic lymphoma. The distinction between low- and high-grade lymphomas was also unsatisfactory. These results indicate the need for improved precision in the definition of histological categories of peripheral T-cell lymphoma. The reproducibility of the update Kiel classification for peripheral T-cell lymphomas in its present form is inadequate.

  5. Study of Image Analysis Algorithms for Segmentation, Feature Extraction and Classification of Cells

    Directory of Open Access Journals (Sweden)

    Margarita Gamarra

    2017-08-01

    Full Text Available Recent advances in microcopy and improvements in image processing algorithms have allowed the development of computer-assisted analytical approaches in cell identification. Several applications could be mentioned in this field: Cellular phenotype identification, disease detection and treatment, identifying virus entry in cells and virus classification; these applications could help to complement the opinion of medical experts. Although many surveys have been presented in medical image analysis, they focus mainly in tissues and organs and none of the surveys about image cells consider an analysis following the stages in the typical image processing: Segmentation, feature extraction and classification. The goal of this study is to provide comprehensive and critical analyses about the trends in each stage of cell image processing. In this paper, we present a literature survey about cell identification using different image processing techniques.

  6. Breast cancer cell nuclei classification in histopathology images using deep neural networks.

    Science.gov (United States)

    Feng, Yangqin; Zhang, Lei; Yi, Zhang

    2018-02-01

    Cell nuclei classification in breast cancer histopathology images plays an important role in effective diagnose since breast cancer can often be characterized by its expression in cell nuclei. However, due to the small and variant sizes of cell nuclei, and heavy noise in histopathology images, traditional machine learning methods cannot achieve desirable recognition accuracy. To address this challenge, this paper aims to present a novel deep neural network which performs representation learning and cell nuclei recognition in an end-to-end manner. The proposed model hierarchically maps raw medical images into a latent space in which robustness is achieved by employing a stacked denoising autoencoder. A supervised classifier is further developed to improve the discrimination of the model by maximizing inter-subject separability in the latent space. The proposed method involves a cascade model which jointly learns a set of nonlinear mappings and a classifier from the given raw medical images. Such an on-the-shelf learning strategy makes obtaining discriminative features possible, thus leading to better recognition performance. Extensive experiments with benign and malignant breast cancer datasets are conducted to verify the effectiveness of the proposed method. Better performance was obtained when compared with other feature extraction methods, and higher recognition rate was achieved when compared with other seven classification methods. We propose an end-to-end DNN model for cell nuclei and non-nuclei classification of histopathology images. It demonstrates that the proposed method can achieve promising performance in cell nuclei classification, and the proposed method is suitable for the cell nuclei classification task.

  7. [Psychiatry of the future: multidimensionality of the problems of modern psychiatry and development of classification systems].

    Science.gov (United States)

    Makushkin, E V; Oskolkova, S N; Fastovtsov, G A

    The success and achievements in the area of neurosciences due to the development of neuroimaging, neurochemical and genome studies provide tasks for psychiatry determined by the necessity to develop new classifications of mental diseases, primarily ICD-11, specify clinical diagnostic criteria and rethink the essence of some mental disorders. In spite of the multiple direction of scientific opinions on the discussed issues, the development of modern psychiatry is characterized by intensive search of biological background of psychiatric disorders and elaboration of effective approaches to the diagnosis and treatment of mental diseases, including medical rehabilitation of patients.

  8. B-Cell waste classification sampling and analysis plan

    International Nuclear Information System (INIS)

    HOBART, R.L.

    1999-01-01

    This report documents the methods used to collect and analyze samples to obtain data necessary to verify and/or determine the radionuclide content of the 324 Facility B-Cell decontamination and decommissioning waste stream

  9. New Application of Hyperspectral Imaging for Bacterial Cell Classification

    Science.gov (United States)

    Hyperspectral microscopy has shown potential as a method for rapid detection of foodborne pathogenic bacteria with spectral characteristics from bacterial cells. Hyperspectral microscope images (HMIs) are collected from broiler chicken isolates of Salmonella serotypes Enteritidis, Typhimurium, Infa...

  10. Complexity classifications for different equivalence and audit problems for Boolean circuits

    OpenAIRE

    Böhler, Elmar; Creignou, Nadia; Galota, Matthias; Reith, Steffen; Schnoor, Henning; Vollmer, Heribert

    2010-01-01

    We study Boolean circuits as a representation of Boolean functions and conskier different equivalence, audit, and enumeration problems. For a number of restricted sets of gate types (bases) we obtain efficient algorithms, while for all other gate types we show these problems are at least NP-hard.

  11. Optimizing Ship Classification in the Arctic Ocean: A Case Study of Multi-Disciplinary Problem Solving

    Directory of Open Access Journals (Sweden)

    Mark Rahmes

    2014-08-01

    Full Text Available We describe a multi-disciplinary system model for determining decision making strategies based upon the ability to perform data mining and pattern discovery utilizing open source actionable information to prepare for specific events or situations from multiple information sources. We focus on combining detection theory with game theory for classifying ships in Arctic Ocean to verify ship reporting. More specifically, detection theory is used to determine probability of deciding if a ship or certain ship class is present or not. We use game theory to fuse information for optimal decision making on ship classification. Hierarchy game theory framework enables complex modeling of data in probabilistic modeling. However, applicability to big data is complicated by the difficulties of inference in complex probabilistic models, and by computational constraints. We provide a framework for fusing sensor inputs to help compare if the information of a ship matches its AIS reporting requirements using mixed probabilities from game theory. Our method can be further applied to optimizing other choke point scenarios where a decision is needed for classification of ground assets or signals. We model impact on decision making on accuracy by adding more parameters or sensors to the decision making process as sensitivity analysis.

  12. New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems.

    Science.gov (United States)

    Thomas, Minta; De Brabanter, Kris; De Moor, Bart

    2014-05-10

    DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history of almost a decade. Disease class predictors can be designed for known disease cases and provide diagnostic confirmation or clarify abnormal cases. The main input to this class predictors are high dimensional data with many variables and few observations. Dimensionality reduction of these features set significantly speeds up the prediction task. Feature selection and feature transformation methods are well known preprocessing steps in the field of bioinformatics. Several prediction tools are available based on these techniques. Studies show that a well tuned Kernel PCA (KPCA) is an efficient preprocessing step for dimensionality reduction, but the available bandwidth selection method for KPCA was computationally expensive. In this paper, we propose a new data-driven bandwidth selection criterion for KPCA, which is related to least squares cross-validation for kernel density estimation. We propose a new prediction model with a well tuned KPCA and Least Squares Support Vector Machine (LS-SVM). We estimate the accuracy of the newly proposed model based on 9 case studies. Then, we compare its performances (in terms of test set Area Under the ROC Curve (AUC) and computational time) with other well known techniques such as whole data set + LS-SVM, PCA + LS-SVM, t-test + LS-SVM, Prediction Analysis of Microarrays (PAM) and Least Absolute Shrinkage and Selection Operator (Lasso). Finally, we assess the performance of the proposed strategy with an existing KPCA parameter tuning algorithm by means of two additional case studies. We propose, evaluate, and compare several mathematical/statistical techniques, which apply feature transformation/selection for subsequent classification, and consider its application in medical diagnostics. Both feature selection and feature

  13. Multiloculated hydrocephalus: a review of current problems in classification and treatment

    DEFF Research Database (Denmark)

    Andresen, Morten; Juhler, Marianne

    2012-01-01

    PURPOSE: Loculated hydrocephalus is a condition in which discrete fluid-filled compartments form in or in relation to the ventricular system of the brain. Both uni- and multiloculated variants exist, with marked differences in outcome. However, several competing and seemingly interchangeable...... of Systematic Reviews, and the U.S. NIH ClinicalTrials.gov database was carried out with the search terms: "multicystic," "multiloculated," "multicompartment," "uniloculated," and "loculated." All were used in conjunction with the search term "hydrocephalus." RESULTS: A single study with a control group......, evidence is in favor of the neuroendoscopic approach. CONCLUSIONS: In order to ensure a consistent nomenclature as well as to guide future research, we propose a new system of classification for loculated hydrocephalus. It acknowledges the differences between uniloculated and multiloculated hydrocephalus...

  14. AUTOMATIC SEGMENTATION AND CLASSIFICATION OF CELLS FROM BRONCHO ALVEOLAR LAVAGE

    Directory of Open Access Journals (Sweden)

    Olivier Lezoray

    2011-05-01

    Full Text Available Broncho alveolar lavage is the most commonly used diagnostic tool for confirming alveolar hemorrhage. Golde has introduced a ranking score, based on the hemosiderin content of macrophages which enables ranking cells from 0 to 4 based on the degree of Prussian blue stain. We propose a complete image analysis scheme to automatically perform both the extraction of the cellular objects and the ranking of each cell according to the Golde score. The image analysis techniques used mainly involve clustering and mathematical morphology. A 2D histogram is clustered to extract the main cellular components, a color watershed is used to determine and refine the regions. Finally, the cellular components of interest are firstly classified according to their hue and secondly according to their staining repartition. The proposed image analysis technique is very fast and produces reliable and accurate results.

  15. Surface-enhanced Raman spectroscopy of cell lysates mixed with silver nanoparticles for tumor classification

    Directory of Open Access Journals (Sweden)

    Mohamed Hassoun

    2017-06-01

    Full Text Available The throughput of spontaneous Raman spectroscopy for cell identification applications is limited to the range of one cell per second because of the relatively low sensitivity. Surface-enhanced Raman scattering (SERS is a widespread way to amplify the intensity of Raman signals by several orders of magnitude and, consequently, to improve the sensitivity and throughput. SERS protocols using immuno-functionalized nanoparticles turned out to be challenging for cell identification because they require complex preparation procedures. Here, a new SERS strategy is presented for cell classification using non-functionalized silver nanoparticles and potassium chloride to induce aggregation. To demonstrate the principle, cell lysates were prepared by ultrasonication that disrupts the cell membrane and enables interaction of released cellular biomolecules to nanoparticles. This approach was applied to distinguish four cell lines – Capan-1, HepG2, Sk-Hep1 and MCF-7 – using SERS at 785 nm excitation. Six independent batches were prepared per cell line to check the reproducibility. Principal component analysis was applied for data reduction and assessment of spectral variations that were assigned to proteins, nucleotides and carbohydrates. Four principal components were selected as input for classification models based on support vector machines. Leave-three-batches-out cross validation recognized four cell lines with sensitivities, specificities and accuracies above 96%. We conclude that this reproducible and specific SERS approach offers prospects for cell identification using easily preparable silver nanoparticles.

  16. Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach.

    Science.gov (United States)

    Karakaya, Gulsah; Galelli, Stefano; Ahipasaoglu, Selin Damla; Taormina, Riccardo

    2016-06-01

    An emerging trend in feature selection is the development of two-objective algorithms that analyze the tradeoff between the number of features and the classification performance of the model built with these features. Since these two objectives are conflicting, a typical result stands in a set of Pareto-efficient subsets, each having a different cardinality and a corresponding discriminating power. However, this approach overlooks the fact that, for a given cardinality, there can be several subsets with similar information content. The study reported here addresses this problem, and introduces a novel multiobjective feature selection approach conceived to identify: 1) a subset that maximizes the performance of a given classifier and 2) a set of subsets that are quasi equally informative, i.e., have almost same classification performance, to the performance maximizing subset. The approach consists of a wrapper [Wrapper for Quasi Equally Informative Subset Selection (W-QEISS)] built on the formulation of a four-objective optimization problem, which is aimed at maximizing the accuracy of a classifier, minimizing the number of features, and optimizing two entropy-based measures of relevance and redundancy. This allows conducting the search in a larger space, thus enabling the wrapper to generate a large number of Pareto-efficient solutions. The algorithm is compared against the mRMR algorithm, a two-objective wrapper and a computationally efficient filter [Filter for Quasi Equally Informative Subset Selection (F-QEISS)] on 24 University of California, Irvine, (UCI) datasets including both binary and multiclass classification. Experimental results show that W-QEISS has the capability of evolving a rich and diverse set of Pareto-efficient solutions, and that their availability helps in: 1) studying the tradeoff between multiple measures of classification performance and 2) understanding the relative importance of each feature. The quasi equally informative subsets are

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

    Directory of Open Access Journals (Sweden)

    Goran N. Jovanovic

    2007-01-01

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

  18. On Feature Selection and Rule Extraction for High Dimensional Data: A Case of Diffuse Large B-Cell Lymphomas Microarrays Classification

    Directory of Open Access Journals (Sweden)

    Narissara Eiamkanitchat

    2015-01-01

    Full Text Available Neurofuzzy methods capable of selecting a handful of useful features are very useful in analysis of high dimensional datasets. A neurofuzzy classification scheme that can create proper linguistic features and simultaneously select informative features for a high dimensional dataset is presented and applied to the diffuse large B-cell lymphomas (DLBCL microarray classification problem. The classification scheme is the combination of embedded linguistic feature creation and tuning algorithm, feature selection, and rule-based classification in one neural network framework. The adjustable linguistic features are embedded in the network structure via fuzzy membership functions. The network performs the classification task on the high dimensional DLBCL microarray dataset either by the direct calculation or by the rule-based approach. The 10-fold cross validation is applied to ensure the validity of the results. Very good results from both direct calculation and logical rules are achieved. The results show that the network can select a small set of informative features in this high dimensional dataset. By a comparison to other previously proposed methods, our method yields better classification performance.

  19. Proposals for Paraphilic Disorders in the International Classification of Diseases and Related Health Problems, Eleventh Revision (ICD-11).

    Science.gov (United States)

    Krueger, Richard B; Reed, Geoffrey M; First, Michael B; Marais, Adele; Kismodi, Eszter; Briken, Peer

    2017-07-01

    The World Health Organization is currently developing the 11th revision of the International Classifications of Diseases and Related Health Problems (ICD-11), with approval of the ICD-11 by the World Health Assembly anticipated in 2018. The Working Group on the Classification of Sexual Disorders and Sexual Health (WGSDSH) was created and charged with reviewing and making recommendations for categories related to sexuality that are contained in the chapter of Mental and Behavioural Disorders in ICD-10 (World Health Organization 1992a). Among these categories was the ICD-10 grouping F65, Disorders of sexual preference, which describes conditions now widely referred to as Paraphilic Disorders. This article reviews the evidence base, rationale, and recommendations for the proposed revisions in this area for ICD-11 and compares them with DSM-5. The WGSDSH recommended that the grouping, Disorders of sexual preference, be renamed to Paraphilic Disorders and be limited to disorders that involve sexual arousal patterns that focus on non-consenting others or are associated with substantial distress or direct risk of injury or death. Consistent with this framework, the WGSDSH also recommended that the ICD-10 categories of Fetishism, Fetishistic Transvestism, and Sadomasochism be removed from the classification and new categories of Coercive Sexual Sadism Disorder, Frotteuristic Disorder, Other Paraphilic Disorder Involving Non-Consenting Individuals, and Other Paraphilic Disorder Involving Solitary Behaviour or Consenting Individuals be added. The WGSDSH's proposals for Paraphilic Disorders in ICD-11 are based on the WHO's role as a global public health agency and the ICD's function as a public health reporting tool.

  20. Classification of Hydrogels Based on Their Source: A Review and Application in Stem Cell Regulation

    Science.gov (United States)

    Khansari, Maziyar M.; Sorokina, Lioudmila V.; Mukherjee, Prithviraj; Mukhtar, Farrukh; Shirdar, Mostafa Rezazadeh; Shahidi, Mahnaz; Shokuhfar, Tolou

    2017-08-01

    Stem cells are recognized by their self-renewal ability and can give rise to specialized progeny. Hydrogels are an established class of biomaterials with the ability to control stem cell fate via mechanotransduction. They can mimic various physiological conditions to influence the fate of stem cells and are an ideal platform to support stem cell regulation. This review article provides a summary of recent advances in the application of different classes of hydrogels based on their source (e.g., natural, synthetic, or hybrid). This classification is important because the chemistry of substrate affects stem cell differentiation and proliferation. Natural and synthetic hydrogels have been widely used in stem cell regulation. Nevertheless, they have limitations that necessitate a new class of material. Hybrid hydrogels obtained by manipulation of the natural and synthetic ones can potentially overcome these limitations and shape the future of research in application of hydrogels in stem cell regulation.

  1. Automated classification of bone marrow cells in microscopic images for diagnosis of leukemia: a comparison of two classification schemes with respect to the segmentation quality

    Science.gov (United States)

    Krappe, Sebastian; Benz, Michaela; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

    2015-03-01

    The morphological analysis of bone marrow smears is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually with the use of bright field microscope. This is a time consuming, partly subjective and tedious process. Furthermore, repeated examinations of a slide yield intra- and inter-observer variances. For this reason an automation of morphological bone marrow analysis is pursued. This analysis comprises several steps: image acquisition and smear detection, cell localization and segmentation, feature extraction and cell classification. The automated classification of bone marrow cells is depending on the automated cell segmentation and the choice of adequate features extracted from different parts of the cell. In this work we focus on the evaluation of support vector machines (SVMs) and random forests (RFs) for the differentiation of bone marrow cells in 16 different classes, including immature and abnormal cell classes. Data sets of different segmentation quality are used to test the two approaches. Automated solutions for the morphological analysis for bone marrow smears could use such a classifier to pre-classify bone marrow cells and thereby shortening the examination duration.

  2. Solving Classification Problems for Large Sets of Protein Sequences with the Example of Hox and ParaHox Proteins

    Directory of Open Access Journals (Sweden)

    Stefanie D. Hueber

    2016-02-01

    Full Text Available Phylogenetic methods are key to providing models for how a given protein family evolved. However, these methods run into difficulties when sequence divergence is either too low or too high. Here, we provide a case study of Hox and ParaHox proteins so that additional insights can be gained using a new computational approach to help solve old classification problems. For two (Gsx and Cdx out of three ParaHox proteins the assignments differ between the currently most established view and four alternative scenarios. We use a non-phylogenetic, pairwise-sequence-similarity-based method to assess which of the previous predictions, if any, are best supported by the sequence-similarity relationships between Hox and ParaHox proteins. The overall sequence-similarities show Gsx to be most similar to Hox2–3, and Cdx to be most similar to Hox4–8. The results indicate that a purely pairwise-sequence-similarity-based approach can provide additional information not only when phylogenetic inference methods have insufficient information to provide reliable classifications (as was shown previously for central Hox proteins, but also when the sequence variation is so high that the resulting phylogenetic reconstructions are likely plagued by long-branch-attraction artifacts.

  3. Segmentation and Classification of Bone Marrow Cells Images Using Contextual Information for Medical Diagnosis of Acute Leukemias.

    Directory of Open Access Journals (Sweden)

    Carolina Reta

    Full Text Available Morphological identification of acute leukemia is a powerful tool used by hematologists to determine the family of such a disease. In some cases, experienced physicians are even able to determine the leukemia subtype of the sample. However, the identification process may have error rates up to 40% (when classifying acute leukemia subtypes depending on the physician's experience and the sample quality. This problem raises the need to create automatic tools that provide hematologists with a second opinion during the classification process. Our research presents a contextual analysis methodology for the detection of acute leukemia subtypes from bone marrow cells images. We propose a cells separation algorithm to break up overlapped regions. In this phase, we achieved an average accuracy of 95% in the evaluation of the segmentation process. In a second phase, we extract descriptive features to the nucleus and cytoplasm obtained in the segmentation phase in order to classify leukemia families and subtypes. We finally created a decision algorithm that provides an automatic diagnosis for a patient. In our experiments, we achieved an overall accuracy of 92% in the supervised classification of acute leukemia families, 84% for the lymphoblastic subtypes, and 92% for the myeloblastic subtypes. Finally, we achieved accuracies of 95% in the diagnosis of leukemia families and 90% in the diagnosis of leukemia subtypes.

  4. Segmentation and Classification of Bone Marrow Cells Images Using Contextual Information for Medical Diagnosis of Acute Leukemias.

    Science.gov (United States)

    Reta, Carolina; Altamirano, Leopoldo; Gonzalez, Jesus A; Diaz-Hernandez, Raquel; Peregrina, Hayde; Olmos, Ivan; Alonso, Jose E; Lobato, Ruben

    2015-01-01

    Morphological identification of acute leukemia is a powerful tool used by hematologists to determine the family of such a disease. In some cases, experienced physicians are even able to determine the leukemia subtype of the sample. However, the identification process may have error rates up to 40% (when classifying acute leukemia subtypes) depending on the physician's experience and the sample quality. This problem raises the need to create automatic tools that provide hematologists with a second opinion during the classification process. Our research presents a contextual analysis methodology for the detection of acute leukemia subtypes from bone marrow cells images. We propose a cells separation algorithm to break up overlapped regions. In this phase, we achieved an average accuracy of 95% in the evaluation of the segmentation process. In a second phase, we extract descriptive features to the nucleus and cytoplasm obtained in the segmentation phase in order to classify leukemia families and subtypes. We finally created a decision algorithm that provides an automatic diagnosis for a patient. In our experiments, we achieved an overall accuracy of 92% in the supervised classification of acute leukemia families, 84% for the lymphoblastic subtypes, and 92% for the myeloblastic subtypes. Finally, we achieved accuracies of 95% in the diagnosis of leukemia families and 90% in the diagnosis of leukemia subtypes.

  5. Cyclic flow shop scheduling problem with two-machine cells

    Directory of Open Access Journals (Sweden)

    Bożejko Wojciech

    2017-06-01

    Full Text Available In the paper a variant of cyclic production with setups and two-machine cell is considered. One of the stages of the problem solving consists of assigning each operation to the machine on which it will be carried out. The total number of such assignments is exponential. We propose a polynomial time algorithm finding the optimal operations to machines assignment.

  6. A new formulation for the problem of fuel cell homogenization

    International Nuclear Information System (INIS)

    Chao, Y.-A.; Martinez, A.S.

    1982-01-01

    A new homogenization method for reactor cells is described. This new method consists in eliminating the NR approximation for the fuel resonance and the Wigner approximation for the resonance escape probability; the background cross section is then redefined and the problem studied is reanalyzed. (E.G.) [pt

  7. The problems of hygienic classification of radioactive waste under restoration of contaminated areas

    International Nuclear Information System (INIS)

    Savkin, M.; Shandala, N.; Novikova, N.; Petukhova, E.; Shishkin, V.; Egorov, B.; Ziborov, A.

    2002-01-01

    Experience on restoration of contaminated areas in the past ten years reveals a specific problem in the general problem of solid radioactive waste management as a result of decontamination of the settlements. That specific problem concerns conventionally radioactive waste (CRW), which might be to some extent dangerous for human being. In the documents of IAEA and ICRP the approaches aimed at exemption or exclusion insignificant amount of radioactive wastes from regulatory control are actively being developed. In turn, Russia does not have so far either methodic or regulatory documents on management of very low level radioactive waste. Two approaches are considered in the paper under development of derived levels for CRW in case of restoration of contaminated areas. The first one is based on restriction of individual risk at level about 10 -6 per year (negligible level). The second one accounts for global man-made background and uses acceptable factor of excess of that background as a criterion.Under the first approach (restriction of individual risk) the lowest boundary of CRW is estimated to be equal to 3 Bq kg -1 for 239 Pu; 30 Bq kg -1 for 90 Sr; and 300 Bq kg -1 for 137 Cs, respectively. Those levels of specific activity approximately correspond to the areas contaminated by the above mentioned radionuclides 0.3 kBq m -2 , 3 kBq m -2 , and 30 kBq m -2 , respectively. Under the second approach if one accepts factor of 3 of excess of global man-made background, than the levels of specific activity will be 0.05 kBq m -2 for 239 Pu; 2.5 kBq m -2 for 90 Sr, and 7.2 kBq m -2 for 137 Cs. Comparison of the levels obtained according to the second approach shows that they will be several times lower than that according to the first approach. (author)

  8. Geometrical Modification of Learning Vector Quantization Method for Solving Classification Problems

    Directory of Open Access Journals (Sweden)

    Korhan GÜNEL

    2016-09-01

    Full Text Available In this paper, a geometrical scheme is presented to show how to overcome an encountered problem arising from the use of generalized delta learning rule within competitive learning model. It is introduced a theoretical methodology for describing the quantization of data via rotating prototype vectors on hyper-spheres.The proposed learning algorithm is tested and verified on different multidimensional datasets including a binary class dataset and two multiclass datasets from the UCI repository, and a multiclass dataset constructed by us. The proposed method is compared with some baseline learning vector quantization variants in literature for all domains. Large number of experiments verify the performance of our proposed algorithm with acceptable accuracy and macro f1 scores.

  9. Cell heterogeneity problems in the analysis of zero power experiments

    International Nuclear Information System (INIS)

    Grimstone, M.J.; Stevenson, J.M.

    1979-01-01

    Methods are described for treating plate and pin cell heterogeneity in the preparation of broad group cross-sections used in the analysis of zero power fast reactor experiments. Methods used at Karlsruhe and Winfrith are summarised and compared, with particular reference to the treatment of resonance shielding, the calculation of broad group spatial fine structure, the treatment of leakage and the calculation of anisotropic diffusion coefficients. The problems of cells near boundaries such as core-breeder interfaces and of singularities such as control rods are also considered briefly. Numerical studies carried out to investigate approximations in the methods are described. These include tests of the accuracy of one-dimensional cell modelling techniques, and the validation by Monte Carlo of methods for treating streaming in the calculation of diffusion coefficients. Comparisons are shown between the heterogeneity effects calculated by the Karlsruhe and Winfrith methods for typical pin and plate cells used in the BIZET experimental programme, and their effect in a whole reactor calculation is indicated. Comparisons are given with measurements which provide tests of the heterogeneity calculations. These include reaction rate scans within pin and plate cells, and reaction rate measurements across sectors of pin and plate fuel, where the flux tilt is determined by the relative reactivity of the pin and plate cells. Finally, the heterogeneity problems arising in the interpretation of reaction rate measurements are discussed. (author)

  10. Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

    Science.gov (United States)

    Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

    2016-03-01

    Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

  11. Cell phone use and behavioural problems in young children.

    Science.gov (United States)

    Divan, Hozefa A; Kheifets, Leeka; Obel, Carsten; Olsen, Jørn

    2012-06-01

    Potential health effects of cell phone use in children have not been adequately examined. As children are using cell phones at earlier ages, research among this group has been identified as the highest priority by both national and international organisations. The authors previously reported results from the Danish National Birth Cohort (DNBC), which looked at prenatal and postnatal exposure to cell phone use and behavioural problems at age 7 years. Exposure to cell phones prenatally, and to a lesser degree postnatally, was associated with more behavioural difficulties. The original analysis included nearly 13 000 children who reached age 7 years by November 2006. To see if a larger, separate group of DNBC children would produce similar results after considering additional confounders, children of mothers who might better represent current users of cell phones were analysed. This 'new' dataset consisted of 28 745 children with completed Age-7 Questionnaires to December 2008. The highest OR for behavioural problems were for children who had both prenatal and postnatal exposure to cell phones compared with children not exposed during either time period. The adjusted effect estimate was 1.5 (95% CI 1.4 to 1.7). The findings of the previous publication were replicated in this separate group of participants demonstrating that cell phone use was associated with behavioural problems at age 7 years in children, and this association was not limited to early users of the technology. Although weaker in the new dataset, even with further control for an extended set of potential confounders, the associations remained.

  12. Traffic Management as a Service: The Traffic Flow Pattern Classification Problem

    Directory of Open Access Journals (Sweden)

    Carlos T. Calafate

    2015-01-01

    Full Text Available Intelligent Transportation System (ITS technologies can be implemented to reduce both fuel consumption and the associated emission of greenhouse gases. However, such systems require intelligent and effective route planning solutions to reduce travel time and promote stable traveling speeds. To achieve such goal these systems should account for both estimated and real-time traffic congestion states, but obtaining reliable traffic congestion estimations for all the streets/avenues in a city for the different times of the day, for every day in a year, is a complex task. Modeling such a tremendous amount of data can be time-consuming and, additionally, centralized computation of optimal routes based on such time-dependencies has very high data processing requirements. In this paper we approach this problem through a heuristic to considerably reduce the modeling effort while maintaining the benefits of time-dependent traffic congestion modeling. In particular, we propose grouping streets by taking into account real traces describing the daily traffic pattern. The effectiveness of this heuristic is assessed for the city of Valencia, Spain, and the results obtained show that it is possible to reduce the required number of daily traffic flow patterns by a factor of 4210 while maintaining the essence of time-dependent modeling requirements.

  13. Identification of health problems in patients with acute inflammatory arthritis, using the International Classification of Functioning, Disability and Health (ICF).

    Science.gov (United States)

    Zochling, J; Grill, E; Scheuringer, M; Liman, W; Stucki, G; Braun, J

    2006-01-01

    To identify the most common health problems experienced by patients with acute inflammatory arthritis using the International Classification of Functioning, Disability and Health (ICF), and to provide empirical data for the development of an ICF Core Set for acute inflammatory arthritis. Cross-sectional survey of patients with acute inflammatory arthritis of two or more joints requiring admission to an acute hospital. The second level categories of the ICF were used to collect information on patients' health problems. Relative frequencies of impairments, limitations and restrictions in the study population were reported for the ICF components Body Functions, Body Structures, and Activities and Participations. For the component Environmental Factors absolute and relative frequencies of perceived barriers or facilitators were reported. In total, 130 patients were included in the survey. The mean age of the population was 59.9 years (median age 63.0 years), 75% of the patients were female. Most had rheumatoid arthritis (57%) or early inflammatory polyarthritis (22%). Fifty-four second-level ICF categories had a prevalence of 30% or more: 3 (8%) belonged to the component Body Structures and 10 (13%) to the component Body Functions. Most categories were identified in the components Activities and Participation (19; 23%) and Environmental Factors (22; 56%). Patients with acute inflammatory arthritis can be well described by ICF categories and components. This study is the first step towards the development of an ICF Core Set for patients with acute inflammatory arthritis.

  14. Data quality objectives for the B-Cell waste stream classification sampling

    International Nuclear Information System (INIS)

    Barnett, J.M.

    1998-01-01

    This document defines the data quality objectives, (DQOS) for sampling the B-Cell racks waste stream. The sampling effort is concentrated on determining a ratio of Cs-137 to Sr-90 and Cs-137 to transuranics (TRU). Figure 1.0 shows the logic path of sampling effort. The flow chart begins with sample and data acquisition and progresses toward (a) statistical confidence and waste classification boundaries, (b) management decisions based on the input parameters and technical methods available, and (c) grout container volume/weight limits and radiation limits. The end result will be accurately classifying the B-Cell rack waste stream

  15. Automatic Cell Segmentation Using a Shape-Classification Model in Immunohistochemically Stained Cytological Images

    Science.gov (United States)

    Shah, Shishir

    This paper presents a segmentation method for detecting cells in immunohistochemically stained cytological images. A two-phase approach to segmentation is used where an unsupervised clustering approach coupled with cluster merging based on a fitness function is used as the first phase to obtain a first approximation of the cell locations. A joint segmentation-classification approach incorporating ellipse as a shape model is used as the second phase to detect the final cell contour. The segmentation model estimates a multivariate density function of low-level image features from training samples and uses it as a measure of how likely each image pixel is to be a cell. This estimate is constrained by the zero level set, which is obtained as a solution to an implicit representation of an ellipse. Results of segmentation are presented and compared to ground truth measurements.

  16. The Time Is Right for a New Classification System for Diabetes: Rationale and Implications of the β-Cell-Centric Classification Schema.

    Science.gov (United States)

    Schwartz, Stanley S; Epstein, Solomon; Corkey, Barbara E; Grant, Struan F A; Gavin, James R; Aguilar, Richard B

    2016-02-01

    The current classification system presents challenges to the diagnosis and treatment of patients with diabetes mellitus (DM), in part due to its conflicting and confounding definitions of type 1 DM, type 2 DM, and latent autoimmune diabetes of adults (LADA). The current schema also lacks a foundation that readily incorporates advances in our understanding of the disease and its treatment. For appropriate and coherent therapy, we propose an alternate classification system. The β-cell-centric classification of DM is a new approach that obviates the inherent and unintended confusions of the current system. The β-cell-centric model presupposes that all DM originates from a final common denominator-the abnormal pancreatic β-cell. It recognizes that interactions between genetically predisposed β-cells with a number of factors, including insulin resistance (IR), susceptibility to environmental influences, and immune dysregulation/inflammation, lead to the range of hyperglycemic phenotypes within the spectrum of DM. Individually or in concert, and often self-perpetuating, these factors contribute to β-cell stress, dysfunction, or loss through at least 11 distinct pathways. Available, yet underutilized, treatments provide rational choices for personalized therapies that target the individual mediating pathways of hyperglycemia at work in any given patient, without the risk of drug-related hypoglycemia or weight gain or imposing further burden on the β-cells. This article issues an urgent call for the review of the current DM classification system toward the consensus on a new, more useful system. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

  17. Automatic Detection of Cervical Cancer Cells by a Two-Level Cascade Classification System

    Directory of Open Access Journals (Sweden)

    Jie Su

    2016-01-01

    Full Text Available We proposed a method for automatic detection of cervical cancer cells in images captured from thin liquid based cytology slides. We selected 20,000 cells in images derived from 120 different thin liquid based cytology slides, which include 5000 epithelial cells (normal 2500, abnormal 2500, lymphoid cells, neutrophils, and junk cells. We first proposed 28 features, including 20 morphologic features and 8 texture features, based on the characteristics of each cell type. We then used a two-level cascade integration system of two classifiers to classify the cervical cells into normal and abnormal epithelial cells. The results showed that the recognition rates for abnormal cervical epithelial cells were 92.7% and 93.2%, respectively, when C4.5 classifier or LR (LR: logical regression classifier was used individually; while the recognition rate was significantly higher (95.642% when our two-level cascade integrated classifier system was used. The false negative rate and false positive rate (both 1.44% of the proposed automatic two-level cascade classification system are also much lower than those of traditional Pap smear review.

  18. Quantitative Cell Cycle Analysis Based on an Endogenous All-in-One Reporter for Cell Tracking and Classification

    Directory of Open Access Journals (Sweden)

    Thomas Zerjatke

    2017-05-01

    Full Text Available Cell cycle kinetics are crucial to cell fate decisions. Although live imaging has provided extensive insights into this relationship at the single-cell level, the limited number of fluorescent markers that can be used in a single experiment has hindered efforts to link the dynamics of individual proteins responsible for decision making directly to cell cycle progression. Here, we present fluorescently tagged endogenous proliferating cell nuclear antigen (PCNA as an all-in-one cell cycle reporter that allows simultaneous analysis of cell cycle progression, including the transition into quiescence, and the dynamics of individual fate determinants. We also provide an image analysis pipeline for automated segmentation, tracking, and classification of all cell cycle phases. Combining the all-in-one reporter with labeled endogenous cyclin D1 and p21 as prime examples of cell-cycle-regulated fate determinants, we show how cell cycle and quantitative protein dynamics can be simultaneously extracted to gain insights into G1 phase regulation and responses to perturbations.

  19. Gallium arsenide solar cell efficiency: Problems and potential

    Science.gov (United States)

    Weizer, V. G.; Godlewski, M. P.

    1985-01-01

    Under ideal conditions the GaAs solar cell should be able to operate at an AMO efficiency exceeding 27 percent, whereas to date the best measured efficiencies barely exceed 19 percent. Of more concern is the fact that there has been no improvement in the past half decade, despite the expenditure of considerable effort. State-of-the-art GaAs efficiency is analyzed in an attempt to determine the feasibility of improving on the status quo. The possible gains to be had in the planar cell. An attempt is also made to predict the efficiency levels that could be achieved with a grating geometry. Both the N-base and the P-base BaAs cells in their planar configurations have the potential to operate at AMO efficiencies between 23 and 24 percent. For the former the enabling technology is essentially in hand, while for the latter the problem of passivating the emitter surface remains to be solved. In the dot grating configuration, P-base efficiencies approaching 26 percent are possible with minor improvements in existing technology. N-base grating cell efficiencies comparable to those predicted for the P-base cell are achievable if the N surface can be sufficiently passivated.

  20. Periodic cells for large-scale problem initialization

    Directory of Open Access Journals (Sweden)

    Ciantia Matteo O.

    2017-01-01

    Full Text Available In geotechnical applications the success of the discrete element method (DEM in simulating fundamental aspects of soil behaviour has increased the interest in applications for direct simulation of engineering scale boundary value problems (BVP’s. The main problem is that the method remains relatively expensive in terms of computational cost. A non-negligible part of that cost is related to specimen creation and initialization. As the response of soil is strongly dependant on its initial state (stress and porosity, attaining a specified initial state is a crucial part of a DEM model. Different procedures for controlled sample generation are available. However, applying the existing REV-oriented initialization procedures to such models is inefficient in terms of computational cost and challenging in terms of sample homogeneity. In this work a simple but efficient procedure to initialize large-scale DEM models is presented. Periodic cells are first generated with a sufficient number of particles matching a desired particle size distribution (PSD. The cells are then equilibrated at low-level isotropic stress at target porosity. Once the cell is in equilibrium, it is replicated in space in order to fill the model domain. After the domain is thus filled a few mechanical cycles are needed to re-equilibrate the large domain. The result is a large, homogeneous sample, equilibrated under prescribed stress at the desired porosity. The method is applicable to both isotropic and anisotropic initial stress states, with stress magnitude varying in space.

  1. Proteomic analysis of human acute leukemia cells: insight into their classification.

    Science.gov (United States)

    Cui, Jiu-Wei; Wang, Jie; He, Kun; Jin, Bao-Feng; Wang, Hong-Xia; Li, Wei; Kang, Li-Hua; Hu, Mei-Ru; Li, Hui-Yan; Yu, Ming; Shen, Bei-Fen; Wang, Guan-Jun; Zhang, Xue-Min

    2004-10-15

    French-American-British (FAB) classification of acute leukemia with genetic heterogeneity is important for treatment and prognosis. However, the distinct protein profiles that contribute to the subtypes and facilitate molecular definition of acute leukemia classification are still unclear. The proteins of leukemic cells from 61 cases of acute leukemia characterized by FAB classification were separated by two-dimensional electrophoresis, and the differentially expressed protein spots were identified by both matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometry (MALDI-TOF-MS) and tandem electrospray ionization MS (ESI-MS/MS). The distinct protein profiles of acute leukemia FAB types or subtypes were successfully explored, including acute myeloid leukemia (AML), its subtypes (M2, M3, and M5) and acute lymphoid leukemia (ALL), which were homogeneous within substantial samples of the respective subgroups but clearly differed from all other subgroups. We found a group of proteins that were highly expressed in M2 and M3, rather than other subtypes. Among them, myeloid-related proteins 8 and 14 were first reported to mark AML differentiation and to differentiate AML from ALL. Heat shock 27 kDa protein 1 and other proteins that are highly expressed in ALL may play important roles in clinically distinguishing AML from ALL. Another set of proteins up-regulated was restricted to granulocytic lineage leukemia. High-level expression of NM23-H1 was found in all but the M3a subtype, with favorable prognosis. These data have implications in delineating the pathways of aberrant gene expression underlying the pathogenesis of acute leukemia and could facilitate molecular definition of FAB classification. The extension of the present analysis to currently less well-defined acute leukemias will identify additional subgroups.

  2. Cell shape characterization and classification with discrete Fourier transforms and self-organizing maps.

    Science.gov (United States)

    Kriegel, Fabian L; Köhler, Ralf; Bayat-Sarmadi, Jannike; Bayerl, Simon; Hauser, Anja E; Niesner, Raluca; Luch, Andreas; Cseresnyes, Zoltan

    2018-03-01

    Cells in their natural environment often exhibit complex kinetic behavior and radical adjustments of their shapes. This enables them to accommodate to short- and long-term changes in their surroundings under physiological and pathological conditions. Intravital multi-photon microscopy is a powerful tool to record this complex behavior. Traditionally, cell behavior is characterized by tracking the cells' movements, which yields numerous parameters describing the spatiotemporal characteristics of cells. Cells can be classified according to their tracking behavior using all or a subset of these kinetic parameters. This categorization can be supported by the a priori knowledge of experts. While such an approach provides an excellent starting point for analyzing complex intravital imaging data, faster methods are required for automated and unbiased characterization. In addition to their kinetic behavior, the 3D shape of these cells also provide essential clues about the cells' status and functionality. New approaches that include the study of cell shapes as well may also allow the discovery of correlations amongst the track- and shape-describing parameters. In the current study, we examine the applicability of a set of Fourier components produced by Discrete Fourier Transform (DFT) as a tool for more efficient and less biased classification of complex cell shapes. By carrying out a number of 3D-to-2D projections of surface-rendered cells, the applied method reduces the more complex 3D shape characterization to a series of 2D DFTs. The resulting shape factors are used to train a Self-Organizing Map (SOM), which provides an unbiased estimate for the best clustering of the data, thereby characterizing groups of cells according to their shape. We propose and demonstrate that such shape characterization is a powerful addition to, or a replacement for kinetic analysis. This would make it especially useful in situations where live kinetic imaging is less practical or not

  3. Classification of blood cells and tumor cells using label-free ultrasound and photoacoustics.

    Science.gov (United States)

    Strohm, Eric M; Kolios, Michael C

    2015-08-01

    A label-free method that can identify cells in a blood sample using high frequency photoacoustic and ultrasound signals is demonstrated. When the wavelength of the ultrasound or photoacoustic wave is similar to the size of a single cell (frequencies of 100-500 MHz), unique periodic features occur within the ultrasound and photoacoustic power spectrum that depend on the cell size, structure, and morphology. These spectral features can be used to identify different cell types present in blood, such as red blood cells (RBCs), white blood cells (WBCs), and circulating tumor cells. Circulating melanoma cells are ideal for photoacoustic detection due to their endogenous optical absorption properties. Using a 532 nm pulsed laser and a 375 MHz transducer, the ultrasound and photoacoustic signals from RBCs, WBCs, and melanoma cells were individually measured in an acoustic microscope to examine how the signals change between cell types. A photoacoustic and ultrasound signal was detected from RBCs and melanoma cells; only an ultrasound signal was detected from WBCs. The different cell types were distinctly separated using the ultrasound and photoacoustic signal amplitude and power spectral periodicity. The size of each cell was also estimated from the spectral periodicity. For the first time, sound waves generated using pulse-echo ultrasound and photoacoustics have been used to identify and size single cells, with applications toward counting and identifying cells, including circulating melanoma cells. © 2015 International Society for Advancement of Cytometry.

  4. Classification of patients with myelodysplastic syndromes according to the FAB co-operative group's proposals. Proposals for a redefinition of blast cell type II.

    Science.gov (United States)

    Nielsen, B; Thiede, T; Sundström, C; Hagberg, H

    1984-05-01

    53 patients with the myelodysplastic syndromes (MDS) were classified according to the proposals of the FAB cooperative group 1982. 29 patients had refractory anaemia (RA), 10 refractory anaemia with excess of blasts ( RAEB ), 5 RAEB in transformation, 7 RA with ringed sideroblasts and 2 chronic myelomonocytic leukaemia ( CMML ). Counting blast cells type I and II involved no difficulties. 4 of 15 patients who developed acute myeloid leukaemia (AML) according to the FAB classification of 1976 did not fulfill the new 1982 criteria for AML. A redefinition of the blast cell type II to include a more granulated blast cells, without the characteristics of promyelocytes, would solve this problem. We conclude that a redefinition of the blast cell type II might turn out to be useful.

  5. Artificial neural networks for classification in metabolomic studies of whole cells using 1H nuclear magnetic resonance.

    LENUS (Irish Health Repository)

    Brougham, D F

    2011-01-01

    We report the successful classification, by artificial neural networks (ANNs), of (1)H NMR spectroscopic data recorded on whole-cell culture samples of four different lung carcinoma cell lines, which display different drug resistance patterns. The robustness of the approach was demonstrated by its ability to classify the cell line correctly in 100% of cases, despite the demonstrated presence of operator-induced sources of variation, and irrespective of which spectra are used for training and for validation. The study demonstrates the potential of ANN for lung carcinoma classification in realistic situations.

  6. CellProfiler Analyst: interactive data exploration, analysis and classification of large biological image sets.

    Science.gov (United States)

    Dao, David; Fraser, Adam N; Hung, Jane; Ljosa, Vebjorn; Singh, Shantanu; Carpenter, Anne E

    2016-10-15

    CellProfiler Analyst allows the exploration and visualization of image-based data, together with the classification of complex biological phenotypes, via an interactive user interface designed for biologists and data scientists. CellProfiler Analyst 2.0, completely rewritten in Python, builds on these features and adds enhanced supervised machine learning capabilities (Classifier), as well as visualization tools to overview an experiment (Plate Viewer and Image Gallery). CellProfiler Analyst 2.0 is free and open source, available at http://www.cellprofiler.org and from GitHub (https://github.com/CellProfiler/CellProfiler-Analyst) under the BSD license. It is available as a packaged application for Mac OS X and Microsoft Windows and can be compiled for Linux. We implemented an automatic build process that supports nightly updates and regular release cycles for the software. anne@broadinstitute.orgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  7. TO THE PROBLEM OF LEGAL SYSTEM CLASSIFICATION: CIVILIZED APPROACH. TENDENCIES OF LEGAL FAMILIES APPROACHING IN THE CONDITIONS OF GLOBALIZATION

    OpenAIRE

    Rasskazov L. P.

    2015-01-01

    The article discusses various criteria for the classification of legal systems. Special attention is drawn to the civilizational approach, which can be effectively used in the classification of legal systems. In accordance with the civilizational approach in the world there are many civilizations, developing according to its own laws (for example, the Scythian civilization, ancient Egyptian, etc.). In accordance with this approach the history of mankind is a history of the development of civi...

  8. Incorporating age into International Germ Cell Consensus Classification (IGCCC): a time to move forward?

    Science.gov (United States)

    Abdel-Rahman, Omar

    2018-01-01

    Older age is a poor prognostic indicator among patients with germ cell tumors. The current study evaluates an age-integrated international germ cell consensus classification (IGCCC) for advanced germ cell tumors. SEER database (2004-2014) was accessed through SEER*Stat program and both IGCCC and age-integrated IGCCC were calculated based on site of the primary, site of the metastasis and level of tumor markers. Overall survival analyses according to IGCCC and age-integrated IGCCC were conducted through Kaplan-Meier analysis. Overall survival was compared according to IGCCC and age-integrated IGCCC for patients with seminoma and Non-seminomatous germ cell tumors (NSGCTs). P values were significant (P <0.001) for all scenarios. c-index for seminoma for IGCCC was 0.553; c-index for seminoma for age-integrated IGCCC was 0.664;c-index for NSGCTs for IGCCC was 0.729; and c-index for NSGCTs for age-integrated IGCCC was 0.738. A Cox-regression multivariate model of factors affecting cancer-specific survival (adjusted for race and surgical treatment) was conducted. All P values for pair wise comparisons (among different age-integrated IGCCC categories) were significant for both seminoma and NSGCTs (P<0.01). Compared to traditional IGCCC, age-integrated IGCCC is more discriminatory and the new risk groups introduced within it are prognostically relevant.

  9. Automated morphological analysis of bone marrow cells in microscopic images for diagnosis of leukemia: nucleus-plasma separation and cell classification using a hierarchical tree model of hematopoesis

    Science.gov (United States)

    Krappe, Sebastian; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

    2016-03-01

    The morphological differentiation of bone marrow is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually under the use of bright field microscopy. This is a time-consuming, subjective, tedious and error-prone process. Furthermore, repeated examinations of a slide may yield intra- and inter-observer variances. For that reason a computer assisted diagnosis system for bone marrow differentiation is pursued. In this work we focus (a) on a new method for the separation of nucleus and plasma parts and (b) on a knowledge-based hierarchical tree classifier for the differentiation of bone marrow cells in 16 different classes. Classification trees are easily interpretable and understandable and provide a classification together with an explanation. Using classification trees, expert knowledge (i.e. knowledge about similar classes and cell lines in the tree model of hematopoiesis) is integrated in the structure of the tree. The proposed segmentation method is evaluated with more than 10,000 manually segmented cells. For the evaluation of the proposed hierarchical classifier more than 140,000 automatically segmented bone marrow cells are used. Future automated solutions for the morphological analysis of bone marrow smears could potentially apply such an approach for the pre-classification of bone marrow cells and thereby shortening the examination time.

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

    CERN Document Server

    Mahjoubfar, Ata; Jalali, Bahram

    2017-01-01

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

  11. Laboratory diagnosis of anemia: are the old and new red cell parameters useful in classification and treatment, how?

    Science.gov (United States)

    Buttarello, M

    2016-05-01

    Anemia is a global problem affecting the population in both developing and developed countries, and there is a debate on which hemoglobin level limit should be used to define anemia in general population and particularly in the elderly. We present herein a laboratory approach to diagnosing the possible causes of anemia based on traditional and new erythroid parameters. In this article, we provide practical diagnostic algorithms that address to differential diagnosis of anemia. Based on both morphological and kinetic classifications, three patterns were considered: microcytic, normocytic, and macrocytic. Main interest is on the clinical usefulness of old and new parameters such as mean cell volume (MCV), red blood cell distribution width (RDW), hypochromic and microcytic erythrocytes, immature reticulocyte fraction (IRF), and some reticulocyte indices such as reticulocyte hemoglobin content and mean reticulocyte volume. The pathophysiologic basis is reviewed in terms of bone marrow erythropoiesis, evaluated by reticulocyte count (increased or normal/decreased) and IRF. The utility of reticulocyte indices in the diagnosis of iron-deficient erythropoiesis (absolute or functional) and in monitoring of response to treatment in nutritional anemia (iron and cobalamin) was also investigated. For each parameter, the availability, the possible clinical applications, and the limitations were evaluated. A discussion on intraindividual biological variation and its implication on the usefulness of conventional reference intervals and in longitudinal monitoring of the patients was also reported. Red cell parameters and reticulocyte indices play an essential role in differential diagnosis of anemia and in its treatment. More efforts are needed in harmonizing parameters whose results are still too different when produced by different analyzers. © 2016 John Wiley & Sons Ltd.

  12. North American vegetation model for land-use planning in a changing climate: A solution to large classification problems

    Science.gov (United States)

    Gerald E. Rehfeldt; Nicholas L. Crookston; Cuauhtemoc Saenz-Romero; Elizabeth M. Campbell

    2012-01-01

    Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of...

  13. Prognostic factors and risk classifications for patients with metastatic renal cell carcinoma.

    Science.gov (United States)

    Shinohara, Nobuo; Abe, Takashige

    2015-10-01

    The introduction of molecular-targeted therapy has made dramatical changes to treatment for metastatic renal cell carcinoma. Currently, there are four vascular endothelial growth factor receptor-tyrosine kinase inhibitors and two mammalian target of rapamycin inhibitors in Japan. For the appropriate clinical use of these molecular-targeted drugs, the identification of prognostic and/or predictive factors in patients who received these drugs is required. Although molecular biological and genetic factors that determine the prognosis of patients with metastatic renal cell carcinoma have been reported, most of these factors are problematic in that the number of patients analyzed was small. In contrast, clinicopathological prognostic factors, including the practice of cytoreductive nephrectomy, pathological findings, metastatic sites and metastasectomy, and abnormal inflammatory response, have been identified by analyzing a relatively large number of patients. Several prognostic classification models that were developed by combining these clinicopathological factors are widely used in not only clinical trials, but also routine clinical practice. However, the quality of these prognostic models is considered to be insufficient regarding prognostic prediction of metastatic renal cell carcinoma patients and, thus, requires further improvements. Recently, basic and clinical studies have been extensively carried out for the identification of promising informative markers and for understanding molecular mechanisms of resistance to molecular-targeted drugs in metastatic renal cell carcinoma patients. The present review considers ongoing translational research efforts on clinicopathological, molecular biological, and genetic prognostic and/or predictive factors for metastatic renal cell carcinoma patients in the era of molecular-targeted therapy, and discusses the clinical implications of these findings. © 2015 The Japanese Urological Association.

  14. Cell-based product classification procedure: What can be done differently to improve decisions on borderline products?

    Science.gov (United States)

    Izeta, Ander; Herrera, Concha; Mata, Rosario; Astori, Giuseppe; Giordano, Rosaria; Hernández, Carmen; Leyva, Laura; Arias, Salvador; Oyonarte, Salvador; Carmona, Gloria; Cuende, Natividad

    2016-07-01

    In June 2015, European Medicines Agency/Committee for Advanced Therapies (CAT) released the new version of the reflection paper on classification of advanced therapy medicinal products (ATMPs) established to address questions of borderline cases in which classification of a product based on genes, cells or tissues is unclear. The paper shows CAT's understanding of substantial manipulation and essential function(s) criteria that define the legal scope of cell-based medicinal products. This article aims to define the authors' viewpoint on the reflection paper. ATMP classification has intrinsic weaknesses derived from the lack of clarity of the evolving concepts of substantial manipulation and essential function(s) as stated in the EU Regulation, leading to the risk of differing interpretations and misclassification. This might result in the broadening of ATMP scope at the expense of other products such as cell/tissue transplants and blood products, or even putting some present and future clinical practice at risk of being classified as ATMP. Because of the major organizational, economic and regulatory implications of product classification, we advocate for increased interaction between CAT and competent authorities (CAs) for medicines, blood and blood components and tissues and cells or for the creation of working groups including representatives of all parties as recently suggested by several CAs. Copyright © 2016 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

  15. Polarimetry based partial least square classification of ex vivo healthy and basal cell carcinoma human skin tissues.

    Science.gov (United States)

    Ahmad, Iftikhar; Ahmad, Manzoor; Khan, Karim; Ikram, Masroor

    2016-06-01

    Optical polarimetry was employed for assessment of ex vivo healthy and basal cell carcinoma (BCC) tissue samples from human skin. Polarimetric analyses revealed that depolarization and retardance for healthy tissue group were significantly higher (ppolarimetry together with PLS statistics hold promise for automated pathology classification. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Tumours of histiocytes and accessory dendritic cells : an immunohistochemical approach to classification from the International Lymphoma Study Group based on 61 cases

    NARCIS (Netherlands)

    Pileri, SA; Grogan, TM; Harris, NL; Banks, P; Campo, E; Chan, JKC; Favera, RD; Delsol, G; De Wolf-Peeters, C; Falini, B; Gascoyne, RD; Gaulard, P; Gatter, KC; Isaacson, PG; Jaffe, ES; Kluin, P; Knowles, DM; Mason, DY; Mori, S; Muller-Hermelink, HK; Piris, MA; Ralfkiaer, E; Stein, H; Su, IJ; Warnke, RA; Weiss, LM

    Neoplasms of histiocytes and dendritic cells are rare, and their phenotypic and biological definition is incomplete. Seeking to identify antigens detectable in paraffin-embedded sections that might allow a more complete, rational immunophenotypic classification of histiocytic/dendritic cell

  17. Molecular classification of basal cell carcinoma of skin by gene expression profiling.

    Science.gov (United States)

    Jee, Byul A; Lim, Hyoseob; Kwon, So Mee; Jo, Yuna; Park, Myong Chul; Lee, Il Jae; Woo, Hyun Goo

    2015-12-01

    Non-melanoma skin cancers (NMSC) including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are more common kinds of skin cancer. Although these tumors share common pathological and clinical features, their similarity and heterogeneity at molecular levels are not fully elaborated yet. Here, by performing comparative analysis of gene expression profiling of BCC, SCC, and normal skin tissues, we could classify the BCC into three subtypes of classical, SCC-like, and normal-like BCCs. Functional enrichment and pathway analyses revealed the molecular characteristics of each subtype. The classical BCC showed the enriched expression and transcription signature with the activation of Wnt and Hedgehog signaling pathways, which were well known key features of BCC. By contrast, the SCC-like BCC was enriched with immune-response genes and oxidative stress-related genes. Network analysis revealed the PLAU/PLAUR as a key regulator of SCC-like BCC. The normal-like BCC showed prominent activation of metabolic processes particularly the fatty acid metabolism. The existence of these molecular subtypes could be validated in an independent dataset, which demonstrated the three subgroups of BCC with distinct functional enrichment. In conclusion, we suggest a novel molecular classification of BCC providing insights on the heterogeneous progression of BCC. © 2014 Wiley Periodicals, Inc.

  18. A Population Classification Evolution Algorithm for the Parameter Extraction of Solar Cell Models

    Directory of Open Access Journals (Sweden)

    Yiqun Zhang

    2016-01-01

    Full Text Available To quickly and precisely extract the parameters for solar cell models, inspired by simplified bird mating optimizer (SBMO, a new optimization technology referred to as population classification evolution (PCE is proposed. PCE divides the population into two groups, elite and ordinary, to reach a better compromise between exploitation and exploration. For the evolution of elite individuals, we adopt the idea of parthenogenesis in nature to afford a fast exploitation. For the evolution of ordinary individuals, we adopt an effective differential evolution strategy and a random movement of small probability is added to strengthen the ability to jump out of a local optimum, which affords a fast exploration. The proposed PCE is first estimated on 13 classic benchmark functions. The experimental results demonstrate that PCE yields the best results on 11 functions by comparing it with six evolutional algorithms. Then, PCE is applied to extract the parameters for solar cell models, that is, the single diode and the double diode. The experimental analyses demonstrate that the proposed PCE is superior when comparing it with other optimization algorithms for parameter identification. Moreover, PCE is tested using three different sources of data with good accuracy.

  19. Using Spores for Fusarium spp. Classification by MALDI-Based Intact Cell/Spore Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Wolfgang Winkler

    2012-01-01

    Full Text Available Fusarium is a widespread genus of filamentous fungi and a member of the soil microbial community. Certain subspecies are health threatening because of their mycotoxin production that affects the human and animal food chain. Thus, for early and effective pest control, species identification is of particular interest; however, differentiation on the subspecies level is challenging and time-consuming for this fungus. In the present study, we show the possibilities of intact cell mass spectrometry for spore analysis of 22 different Fusarium strains belonging to six Fusarium subspecies. We found that species differentiation is possible if mass spectrometric analyses are performed under well-defined conditions with fixed parameters. A critical point for analysis is a proper sample preparation of spores, which increases the quality of mass spectra with respect to signal intensity and m/z value variations. It was concluded that data acquistion has to be performed automatically; otherwise, user-specific variations are introduced generating data which cannot fit the existing datasets. Data that show clearly that matrix-assisted laser desorption ionization-based intact cell/intact spore mass spectrometry (IC/ISMS can be applied to differentiate closely related Fusarium spp. are presented. Results show a potential to build a database on Fusarium species for accurate species identification, for fast response in the case of infections in the cornfield. We furthermore demonstrate the high precision of our approach in classification of intact Fusarium species according to the location of their collection.

  20. A phased SNP-based classification of sickle cell anemia HBB haplotypes.

    Science.gov (United States)

    Shaikho, Elmutaz M; Farrell, John J; Alsultan, Abdulrahman; Qutub, Hatem; Al-Ali, Amein K; Figueiredo, Maria Stella; Chui, David H K; Farrer, Lindsay A; Murphy, George J; Mostoslavsky, Gustavo; Sebastiani, Paola; Steinberg, Martin H

    2017-08-11

    Sickle cell anemia causes severe complications and premature death. Five common β-globin gene cluster haplotypes are each associated with characteristic fetal hemoglobin (HbF) levels. As HbF is the major modulator of disease severity, classifying patients according to haplotype is useful. The first method of haplotype classification used restriction fragment length polymorphisms (RFLPs) to detect single nucleotide polymorphisms (SNPs) in the β-globin gene cluster. This is labor intensive, and error prone. We used genome-wide SNP data imputed to the 1000 Genomes reference panel to obtain phased data distinguishing parental alleles. We successfully haplotyped 813 sickle cell anemia patients previously classified by RFLPs with a concordance >98%. Four SNPs (rs3834466, rs28440105, rs10128556, and rs968857) marking four different restriction enzyme sites unequivocally defined most haplotypes. We were able to assign a haplotype to 86% of samples that were either partially or misclassified using RFLPs. Phased data using only four SNPs allowed unequivocal assignment of a haplotype that was not always possible using a larger number of RFLPs. Given the availability of genome-wide SNP data, our method is rapid and does not require high computational resources.

  1. The diagnosis and management of pre-invasive breast disease: Pathological diagnosis – problems with existing classifications

    International Nuclear Information System (INIS)

    Van de Vijver, Marc J; Peterse, Hans

    2003-01-01

    In this review, we comment on the reasons for disagreement in the concepts, diagnosis and classifications of pre-invasive intraductal proliferations. In view of these disagreements, our proposal is to distinguish epithelial hyperplasia, lobular carcinoma in situ and ductal carcinoma in situ, and to abandon the use of poorly reproducible categories, such as atypical ductal hyperplasia or ductal intraepithelial neoplasia, followed by a number to indicate the degree of proliferation and atypia, as these are not practical for clinical decision making, nor for studies aimed at improving the understanding of breast cancer development. If there is doubt about the classification of an intraductal proliferation, a differential diagnosis and the reason for and degree of uncertainty should be given, rather than categorizing a proliferation as atypical

  2. Resolution of the Poincare problem and nonexistence of algebraic limit cycles in family (I) of Chinese classification

    International Nuclear Information System (INIS)

    Chavarriga, Javier; Garcia, Isaac A.; Sorolla, Jordi

    2005-01-01

    Any quadratic system with limit cycles can be written in one of the three families stated by the Chinese classification. In this paper we consider family (I), i.e., x-bar =δx-y+-bar x2+mxy+ny2,y-bar =x. We show that the degree of its real irreducible invariant algebraic curves is bounded by 3. By the way, we prove that there is not any algebraic limit cycle for this family

  3. The 2-Body Cytoskeleton Problem: Studying Cell-Cell Fusion Mechanics in Osteoclasts with Multiscale Imaging

    Science.gov (United States)

    Silverberg, Jesse; Ng, Pei Ying; Baron, Roland; Yin, Peng

    Most research on in vivocytoskeletal mechanics focuses on what happens in a single cell context. This foundational work has opened up new avenues to study higher-order problems, such as what happens when cells physically interact. For example, osteoclasts, one of the cell types responsible for maintaining healthy skeletal structure, are formed when 10 or more mononuclear cells fuse into a multinuclear behemoth. But how does the cytoskeleton of two or more cells fuse? And what is the role of mechanics in understanding the resulting cytoskeletal organization? In this work, we use the multiscale multiplexed Molecular Atlas Platform to image and study the cytoskeletal mechanics of cell-cell fusion. Our work documents the processes involved and uses observed structures to infer mechanical events during these interactions. Broadly this work takes a technology-driven approach to perform fundamental exploratory work, and uses current state-of-the-art cytoskeletal mechanical modeling to interpret our observations. National Cancer Institute of the National Institutes of Health under Award Number F32CA204038.

  4. Inter-observer variability in the classification of ovarian cancer cell type using microscopy: a pilot study

    Science.gov (United States)

    Gavrielides, Marios A.; Ronnett, Brigitte M.; Vang, Russell; Seidman, Jeffrey D.

    2015-03-01

    Studies have shown that different cell types of ovarian carcinoma have different molecular profiles, exhibit different behavior, and that patients could benefit from typespecific treatment. Different cell types display different histopathology features, and different criteria are used for each cell type classification. Inter-observer variability for the task of classifying ovarian cancer cell types is an under-examined area of research. This study served as a pilot study to quantify observer variability related to the classification of ovarian cancer cell types and to extract valuable data for designing a validation study of digital pathology (DP) for this task. Three observers with expertise in gynecologic pathology reviewed 114 cases of ovarian cancer with optical microscopy, with specific guidelines for classifications into distinct cell types. For 93 cases all 3 pathologists agreed on the same cell type, for 18 cases 2 out of 3 agreed, and for 3 cases there was no agreement. Across cell types with a minimum sample size of 10 cases, agreement between all three observers was {91.1%, 80.0%, 90.0%, 78.6%, 100.0%, 61.5%} for the high grade serous carcinoma, low grade serous carcinoma, endometrioid, mucinous, clear cell, and carcinosarcoma cell types respectively. These results indicate that unanimous agreement varied over a fairly wide range. However, additional research is needed to determine the importance of these differences in comparison studies. These results will be used to aid in the design and sizing of such a study comparing optical and digital pathology. In addition, the results will help in understanding the potential role computer-aided diagnosis has in helping to improve the agreement of pathologists for this task.

  5. Nanog Fluctuations in Embryonic Stem Cells Highlight the Problem of Measurement in Cell Biology.

    Science.gov (United States)

    Smith, Rosanna C G; Stumpf, Patrick S; Ridden, Sonya J; Sim, Aaron; Filippi, Sarah; Harrington, Heather A; MacArthur, Ben D

    2017-06-20

    A number of important pluripotency regulators, including the transcription factor Nanog, are observed to fluctuate stochastically in individual embryonic stem cells. By transiently priming cells for commitment to different lineages, these fluctuations are thought to be important to the maintenance of, and exit from, pluripotency. However, because temporal changes in intracellular protein abundances cannot be measured directly in live cells, fluctuations are typically assessed using genetically engineered reporter cell lines that produce a fluorescent signal as a proxy for protein expression. Here, using a combination of mathematical modeling and experiment, we show that there are unforeseen ways in which widely used reporter strategies can systematically disturb the dynamics they are intended to monitor, sometimes giving profoundly misleading results. In the case of Nanog, we show how genetic reporters can compromise the behavior of important pluripotency-sustaining positive feedback loops, and induce a bifurcation in the underlying dynamics that gives rise to heterogeneous Nanog expression patterns in reporter cell lines that are not representative of the wild-type. These findings help explain the range of published observations of Nanog variability and highlight the problem of measurement in live cells. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  6. Fuzzy Expert System based on a Novel Hybrid Stem Cell (HSC) Algorithm for Classification of Micro Array Data.

    Science.gov (United States)

    Vijay, S Arul Antran; GaneshKumar, P

    2018-02-21

    In the growing scenario, microarray data is extensively used since it provides a more comprehensive understanding of genetic variants among diseases. As the gene expression samples have high dimensionality it becomes tedious to analyze the samples manually. Hence an automated system is needed to analyze these samples. The fuzzy expert system offers a clear classification when compared to the machine learning and statistical methodologies. In fuzzy classification, knowledge acquisition would be a major concern. Despite several existing approaches for knowledge acquisition much effort is necessary to enhance the learning process. This paper proposes an innovative Hybrid Stem Cell (HSC) algorithm that utilizes Ant Colony optimization and Stem Cell algorithm for designing fuzzy classification system to extract the informative rules to form the membership functions from the microarray dataset. The HSC algorithm uses a novel Adaptive Stem Cell Optimization (ASCO) to improve the points of membership function and Ant Colony Optimization to produce the near optimum rule set. In order to extract the most informative genes from the large microarray dataset a method called Mutual Information is used. The performance results of the proposed technique evaluated using the five microarray datasets are simulated. These results prove that the proposed Hybrid Stem Cell (HSC) algorithm produces a precise fuzzy system than the existing methodologies.

  7. Apparatus and fast method for cancer cell classification based on high harmonic coherent diffraction imaging in reflection geometry

    Science.gov (United States)

    Zürch, Michael; Foertsch, Stefan; Matzas, Mark; Pachmann, Katharina; Kuth, Rainer; Spielmann, Christian

    2014-03-01

    In cancer treatment it is highly desirable to identify and /or classify individual cancer cells in real time. Nowadays, the standard method is PCR which is costly and time-consuming. Here we present a different approach to rapidly classify cell types: we measure the pattern of coherently diffracted extreme ultraviolet radiation (XUV radiation at 38nm wavelength), allowing to distinguish different single breast cancer cell types. The output of our laser driven XUV light source is focused onto a single unstained and unlabeled cancer cell, and the resulting diffraction pattern is measured in reflection geometry. As we will further show, the outer shape of the object can be retrieved from the diffraction pattern with sub-micron resolution. For classification it is often not necessary to retrieve the image, it is only necessary to compare the diffraction patterns which can be regarded as a spatial fingerprint of the specimen. For a proof-of-principle experiment MCF7 and SKBR3 breast cancer cells were pipetted on gold-coated silica slides. From illuminating each single cell and measuring a diffraction pattern we could distinguish between them. Owing to the short bursts of coherent soft x-ray light, one could also image temporal changes of the specimen, i.e. studying changes upon drug application once the desired specimen is found by the classification method. Using a more powerful laser, even classifying circulating tumor cells (CTC) at a high throughput seems possible. This lab-sized equipment will allow fast classification of any kind of cells, bacteria or even viruses in the near future.

  8. Classification problem for exactly integrable embeddings of two-dimensional manifolds and coefficients of the third fundametal forms

    International Nuclear Information System (INIS)

    Saveliev, M.V.

    1983-01-01

    A method is proposed for classification of exactly and completely integrable embeddings of two dimensional manifoilds into Riemann or non-Riemann enveloping space, which are based on the algebraic approach to the integration of nonlinear dynamical systems.Here the grading conditions and spectral structure of the Lax-pair operators taking the values in a graded Lie algebra that pick out the integrable class of nonlinear systems are formulated 1n terms of a structure of the 3-d fundamental form tensors. Corresponding to every embedding of three-dimensional subalgebra sb(2) into a simple finite-dimensional (infinite-dimensional of finite growth) Lie algebra L is a definite class of exactly (completely) integrable embeddings of two dimensional manifold into the corresponding enveloping space supplied with the structure of L

  9. Linking self-determined functional problems of patients with neck pain to the International Classification of Functioning, Disability, and Health (ICF

    Directory of Open Access Journals (Sweden)

    Andelic N

    2012-10-01

    Full Text Available Nada Andelic,1 Jan Borre Johansen,1 Erik Bautz-Holter,1,2 Anne Marit Mengshoel,3 Eva Bakke,3 Cecilie Roe1,21Department of Physical Medicine and Rehabilitation, Oslo University Hospital, Oslo, Norway; 2Faculty of Medicine, University of Oslo, Oslo, Norway; 3Department of Health Sciences, Institute of Health and Society, University of Oslo, Oslo, NorwayObjective: To describe commonly reported self-determined functional problems in patients with neck pain and to evaluate their fit to the components of the International Classification of Functioning, Disability, and Health (ICF.Methods: Overall, 249 patients were included in this cross-sectional study that comprised patients with neck pain referred to the outpatient clinic at Oslo University Hospital (2007–2009. Patients were asked to report their three most significant functional problems on the Patient-Specific Functional Scale, a self-determined measure of function. The ICF was used as a tool for analysis. Meaningful concepts within the functional problems were identified, coded, and linked to second-level categories within the components of “body functions,” and “activities and participation.” Two researchers performed coding and linking independently. The ICF categories were presented by percentage of the total number of functional problems linked to the ICF.Results: Of 628 reported functional problems, 13 meaningful ICF domains were identified: four domains belonging to the body functions component (b and nine domains belonging to activities and participation components (d. Within the 88 second-level ICF classification categories of body functions, the most frequently reported items were sleep function (b134; 27% and mobility of joint functions (b710; 26%. Within the 538 second-level categories of activities and participation, remunerative employment was reported as the most frequent item (d850; 15%, closely followed by doing housework (d640; 14%, and recreation and leisure

  10. Radiolabeled red blood cells: status, problems, and prospects

    International Nuclear Information System (INIS)

    Srivastava, S.C.

    1983-01-01

    Radionuclidic labels for red cells can be divided into two main categories - cohort or pulse labels, and random labels. The random labels are incorporated into circulating cells of all ages and the labeling process is usually carried out in vitro. The red cell labels in predominant use involve random labeling and employ technetium-99m, chromium-51, indium-111, and gallium-68, roughly in that order. The extent of usefulness depends on the properties of the label such as the half-life, decay mode, and in-vivo stability, etc. Labeled cells can be used for red cell survival measurements when the half-life of the radionuclide is sufficiently long. The major portion of this article deals with random labels

  11. The Total Least Squares Problem in AX approximate to B: A New Classification with the Relationship to the Classical Works

    Czech Academy of Sciences Publication Activity Database

    Hnětynková, I.; Plešinger, Martin; Sima, D.M.; Strakoš, Z.; Huffel van, S.

    2011-01-01

    Roč. 32, č. 3 (2011), s. 748-770 ISSN 0895-4798 R&D Projects: GA AV ČR IAA100300802 Grant - others:GA ČR(CZ) GA201/09/0917 Program:GA Institutional research plan: CEZ:AV0Z10300504 Keywords : total least squares * multiple right-hand sides * linear approximation problems * orthogonally invariant problems * orthogonal regression * errors-in-variables modeling Subject RIV: BA - General Mathematics Impact factor: 1.368, year: 2011

  12. Broadening the scope on health problems among the chronically neurologically ill with the International Classification of Functioning (ICF)

    NARCIS (Netherlands)

    Wynia, K.; Middel, B.; van Dijk, J.P.; de Ruiter, H.; Lok, W.; de Keyser, J.H.A.; Reijneveld, S.A.

    2006-01-01

    Purpose. The aim of this study was to determine ICF items indicating health problems for patients with a chronic neurological disorder such as multiple sclerosis, Parkinson's disease and neuromuscular disease. Method. A Delphi study using three disease-specific panels composed of patients and

  13. Personality Traits of Expert Teachers of Students with Behavioural Problems: A Review and Classification of the Literature

    Science.gov (United States)

    Buttner, Svenja; Pijl, Sip Jan; Bijstra, Jan; van den Bosch, Els

    2015-01-01

    Teaching students with behavioural problems is a challenge for many teachers but other teachers are able to bring out the best in these students. Much research has been done to find out what differentiates expert teachers from their less skilled colleagues. Recent evidence points to personality as an underlying core factor influencing teacher…

  14. Sickle cell disease in Sierra Leone: a neglected problem | Roberts ...

    African Journals Online (AJOL)

    Eleven (2.4%) were Sickle Cell-HbC disease, median age 14 years. Patients demonstrated many of the typical features of SCD. The most common reason for hospital admission was bone pain crisis associated with an infection, followed by severe anemia. Aseptic necrosis of the femoral head, leg ulcers, septic osteomyelitis ...

  15. [Ethical problems raised by new reproductive biotechnologies and stem cells].

    Science.gov (United States)

    Le Douarin, Nicole M

    2015-01-01

    Research about the hormonal mechanisms controlling reproduction in mammals has soared during the first half of the 20th century. It has produced a series of discoveries with important outcomes, not only scientific, but also impacting the ways of life. Besides the advent of the contraceptive pill, it has permitted to isolate and cultivate in vitro the female gamete, to fertilize it, thus obtaining a zygote that continues to develop until the blastocyst stage outside the maternal organism. The embryo, transferred into a foster-mother, develops normally until term: the first "test-tube baby" was born in this way in 1978. But the only fact of being able to cultivate the human egg in vitro was to open other possibilities and allow further biological advances: embryonic stem cells (ES cells) obtained from blastocysts and, more recently, from induced Pluripotent Stem cells (iPS), which can potentially be derived from all types of differentiated cell types obtained from adult individuals. From then on, the advent of a new medicine could be anticipated, regenerative because able to replace deficient or absent cells within the organism. As each of these steps was reached, scientists have encountered vigorous opposition from the people: the new potentials disturbed the conceptions that man had of his relationship to nature, in particular in two sensitive domains: sexuality and reproduction. The progress of science has however been accepted by most as soon as it was understood that humanity could anticipate advantages from these advances. Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.

  16. Special regulatory T cell review: The suppression problem!

    Science.gov (United States)

    Waldmann, Herman

    2008-01-01

    The concept of T-cell mediated suppression evolved more than 30 years ago. At that time it spawned many claims that have not stood the test of time. The rediscovery of suppression phenomena and regulatory T cells over the past 15 years created schizophrenic responses amongst immunologists. Some claimed that the new proponents of suppression were, once again, bringing immunology into disrepute, whilst others have embraced the field with great enthusiasm and novel approaches to clarification. Without faithful repetition of the "old" experiments, it is difficult to establish what was right and what was wrong. Nevertheless, immunologists must now accept that a good number of the old claims were overstated, and reflected poor scientific discipline. "I speak not to disprove what Brutus spoke, But here I am to speak what I do know" Shakespeare. Julius Caesar Act 3, Scene 2.

  17. Large-scale tracking and classification for automatic analysis of cell migration and proliferation, and experimental optimization of high-throughput screens of neuroblastoma cells.

    Science.gov (United States)

    Harder, Nathalie; Batra, Richa; Diessl, Nicolle; Gogolin, Sina; Eils, Roland; Westermann, Frank; König, Rainer; Rohr, Karl

    2015-06-01

    Computational approaches for automatic analysis of image-based high-throughput and high-content screens are gaining increased importance to cope with the large amounts of data generated by automated microscopy systems. Typically, automatic image analysis is used to extract phenotypic information once all images of a screen have been acquired. However, also in earlier stages of large-scale experiments image analysis is important, in particular, to support and accelerate the tedious and time-consuming optimization of the experimental conditions and technical settings. We here present a novel approach for automatic, large-scale analysis and experimental optimization with application to a screen on neuroblastoma cell lines. Our approach consists of cell segmentation, tracking, feature extraction, classification, and model-based error correction. The approach can be used for experimental optimization by extracting quantitative information which allows experimentalists to optimally choose and to verify the experimental parameters. This involves systematically studying the global cell movement and proliferation behavior. Moreover, we performed a comprehensive phenotypic analysis of a large-scale neuroblastoma screen including the detection of rare division events such as multi-polar divisions. Major challenges of the analyzed high-throughput data are the relatively low spatio-temporal resolution in conjunction with densely growing cells as well as the high variability of the data. To account for the data variability we optimized feature extraction and classification, and introduced a gray value normalization technique as well as a novel approach for automatic model-based correction of classification errors. In total, we analyzed 4,400 real image sequences, covering observation periods of around 120 h each. We performed an extensive quantitative evaluation, which showed that our approach yields high accuracies of 92.2% for segmentation, 98.2% for tracking, and 86.5% for

  18. Sourcing human embryos for embryonic stem cell lines: Problems & perspectives

    Directory of Open Access Journals (Sweden)

    Rajvi H Mehta

    2014-01-01

    Full Text Available The ability to successfully derive human embryonic stem cells (hESC lines from human embryos following in vitro fertilization (IVF opened up a plethora of potential applications of this technique. These cell lines could have been successfully used to increase our understanding of human developmental biology, transplantation medicine and the emerging science of regenerative medicine. The main source for human embryos has been ′discarded′ or ′spare′ fresh or frozen human embryos following IVF. It is a common practice to stimulate the ovaries of women undergoing any of the assisted reproductive technologies (ART and retrieve multiple oocytes which subsequently lead to multiple embryos. Of these, only two or maximum of three embryos are transferred while the rest are cryopreserved as per the decision of the couple. In case a couple does not desire to ′cryopreserve′ their embryos then all the embryos remaining following embryo transfer can be considered ′spare′ or if a couple is no longer in need of the ′cryopreserved′ embryos then these also can be considered as ′spare′. But, the question raised by the ethicists is, "what about ′slightly′ over-stimulating a woman to get a few extra eggs and embryos? The decision becomes more difficult when it comes to ′discarded′ embryos. As of today, the quality of the embryos is primarily assessed based on morphology and the rate of development mainly judged by single point assessment. Despite many criteria described in the literature, the quality assessment is purely subjective. The question that arises is on the decision of ′discarding′ embryos. What would be the criteria for discarding embryos and the potential ′use′ of ESC derived from the ′abnormal appearing′ embryos? This paper discusses some of the newer methods to procure embryos for the derivation of embryonic stem cell lines which will respect the ethical concerns but still provide the source material.

  19. Sourcing human embryos for embryonic stem cell lines: problems & perspectives.

    Science.gov (United States)

    Mehta, Rajvi H

    2014-11-01

    The ability to successfully derive human embryonic stem cells (hESC) lines from human embryos following in vitro fertilization (IVF) opened up a plethora of potential applications of this technique. These cell lines could have been successfully used to increase our understanding of human developmental biology, transplantation medicine and the emerging science of regenerative medicine. The main source for human embryos has been 'discarded' or 'spare' fresh or frozen human embryos following IVF. It is a common practice to stimulate the ovaries of women undergoing any of the assisted reproductive technologies (ART) and retrieve multiple oocytes which subsequently lead to multiple embryos. Of these, only two or maximum of three embryos are transferred while the rest are cryopreserved as per the decision of the couple. in case a couple does not desire to 'cryopreserve' their embryos then all the embryos remaining following embryo transfer can be considered 'spare' or if a couple is no longer in need of the 'cryopreserved' embryos then these also can be considered as 'spare'. But, the question raised by the ethicists is, "what about 'slightly' over-stimulating a woman to get a few extra eggs and embryos? The decision becomes more difficult when it comes to 'discarded' embryos. As of today, the quality of the embryos is primarily assessed based on morphology and the rate of development mainly judged by single point assessment. Despite many criteria described in the literature, the quality assessment is purely subjective. The question that arises is on the decision of 'discarding' embryos. What would be the criteria for discarding embryos and the potential 'use' of ESC derived from the 'abnormal appearing' embryos? This paper discusses some of the newer methods to procure embryos for the derivation of embryonic stem cell lines which will respect the ethical concerns but still provide the source material.

  20. A problem-oriented approach to nodular complications from hyaluronic acid and calcium hydroxylapatite fillers: classification and recommendations for treatment.

    Science.gov (United States)

    Cassuto, Daniel; Sundaram, Hema

    2013-10-01

    Hyaluronic acid and calcium hydroxylapatite fillers are generally safe, efficacious, and well tolerated. However, complications are inevitable, as with any medical procedure. Nodules at the site of filler implantation may pose the greatest challenge, as treatment is often empiric and can be influenced by misconceptions. Hyaluronic acid and calcium hydroxylapatite filler nodules, with or without inflammation, may form at various times during and after injection. The probable causes of these complications are described. Clinicians can benefit from a problem-oriented approach to their diagnosis and management. The need to consider common causes--notably, infection--before rare ones, such as hypersensitivity to filler material, is discussed. Better understanding of the possible causes of hyaluronic acid and calcium hydroxylapatite filler nodules effectively guides treatment and prevents underestimation of the role of contamination-including mycobacteria-in the pathogenesis of inflammatory nodules. It can also inform preventative strategies. The authors advocate ultrasonographic imaging for patients with persistent nodules, to help determine the precise nature and location of the implanted materials. When used appropriately, hyaluronic acid and calcium hydroxylapatite fillers have low complication rates. Filler nodules are often treated without full evaluation of possible causes. A problem-oriented approach that does not overlook the most common causes could improve the outcome of these unfortunate events and help prevent their occurrence and/or recurrence. Complications from currently available hyaluronic acid and calcium hydroxylapatite fillers are typically related to aspects of the injection procedure, such as suboptimal technique and bacterial contamination, rather than to the products themselves.

  1. Systemic Problems: A perspective on stem cell aging and rejuvenation.

    Science.gov (United States)

    Conboy, Irina M; Conboy, Michael J; Rebo, Justin

    2015-10-01

    This review provides balanced analysis of the advances in systemic regulation of young and old tissue stem cells and suggests strategies for accelerating development of therapies to broadly combat age-related tissue degenerative pathologies. Many highlighted recent reports on systemic tissue rejuvenation combine parabiosis with a "silver bullet" putatively responsible for the positive effects. Attempts to unify these papers reflect the excitement about this experimental approach and add value in reproducing previous work. At the same time, defined molecular approaches, which are "beyond parabiosis" for the rejuvenation of multiple old organs represent progress toward attenuating or even reversing human tissue aging.

  2. Recursive heuristic classification

    Science.gov (United States)

    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.

  3. Adjacent-cell Preconditioners for solving optically thick neutron transport problems

    International Nuclear Information System (INIS)

    Azmy, Y.Y.

    1994-01-01

    We develop, analyze, and test a new acceleration scheme for neutron transport methods, the Adjacent-cell Preconditioner (AP) that is particularly suited for solving optically thick problems. Our method goes beyond Diffusion Synthetic Acceleration (DSA) methods in that it's spectral radius vanishes with increasing cell thickness. In particular, for the ID case the AP method converges immediately, i.e. in one iteration, to 10 -4 pointwise relative criterion in problems with dominant cell size of 10 mfp or thicker. Also the AP has a simple formalism and is cell-centered hence, multidimensional and high order extensions are easier to develop, and more efficient to implement

  4. Histologic subtypes of ovarian carcinoma: selected diagnostic and classification problems in Bulgaria: is low hospital volume an issue?

    Science.gov (United States)

    Ivanova, Vesela; Dikov, Tihomir; Dimitrova, Nadya

    2017-03-24

    To provide an overview of the morphologic subtypes of ovarian carcinomas in Bulgaria in relation to current healthcare organization using Bulgarian National Cancer Registry data. Further, we investigated hospital volume as a factor influencing the quality of care for patients with ovarian cancer. Bulgarian National Cancer Registry ovarian carcinoma data were retrieved (2009-2011) and distribution of histologic types was analyzed. Cases were divided and compared with respect to main treatment: no surgery, surgery at hospitals dealing with ≥30 ovarian cancer patients/year (high volume), and surgery at hospitals dealing with ovarian cancer patients/year (low volume). We then estimated the odds of being diagnosed with adenocarcinoma and carcinoma not otherwise specified (NOS) vs specified morphologies (serous, endometrioid, clear cell, and mucinous), including age, grade, stage, and hospital volume, in a logistic regression model. A total of 2,041 ovarian carcinomas were distributed as follows: serous 47.7%, mucinous 11.9%, endometrioid 5.8%, clear cell 1.8%, and adenocarcinoma and carcinoma NOS 32.5%. More than half of cancer patients (n = 1,100, 53.9%) were surgically treated in low-volume hospitals and they had a larger proportion of cases with adenocarcinoma and carcinoma NOS: 33.3%, in comparison with 24.0% in high-volume hospitals (povarian cancer in Bulgaria.

  5. Analytical solution and experimental validation of the energy management problem for fuel cell hybrid vehicles

    NARCIS (Netherlands)

    P.P.J. van den Bosch; Edwin Tazelaar; M. Grimminck; Stijn Hoppenbrouwers; Bram Veenhuizen

    2011-01-01

    The objective of an energy management strategy for fuel cell hybrid propulsion systems is to minimize the fuel needed to provide the required power demand. This minimization is defined as an optimization problem. Methods such as dynamic programming numerically solve this optimization problem.

  6. A class discovery and class prediction approach to histopathological classification of mammographic screen detected columnar cell lesions of the breast.

    Science.gov (United States)

    Pathmanathan, Nirmala; Salisbury, Elizabeth L; Provan, Pamela J; Bilous, A Michael; Byth, Karen; Milliken, Jane S; Clarke, Christine L; Balleine, Rosemary L

    2010-01-01

    Columnar cell lesions (CCLs) of the breast have been increasingly recognised in biopsies taken to investigate mammographic screen detected microcalcification. The aim of this study was to identify distinct CCL subtypes by systematic analysis of histopathology. Hierarchical cluster analysis was performed based on the profile of histopathological features in 102 screen detected CCLs. Features assessed included nuclear morphology, acinar dilatation, epithelial cell hyperplasia, cell crowding, apical snout formation and intraluminal secretion. The stability of this classification was tested in an independent cohort of 32 cases. The histopathology of screen detected CCLs was extremely variable. Hierarchical cluster analysis identified two subclasses: Class 1 (34/102, 33%) characterised by absence of nuclear atypia and less pronounced hyperplasia; and Class 2 (68/102, 67%) that were generally more atypical. Ki-67 scores were significantly lower for Class 1 CCLs (p Class 1 cases were clearly distinguished from Class 2, indicating that these were stable phenotypes amongst screen detected CCLs. The histopathological features of CCLs diagnosed at screening are extremely heterogeneous. Using a systematic approach, we have devised a broad classification system that delineates a category of less atypical CCLs that could form a basis for future studies.

  7. Scientific problems in the regulation of red blood cell products.

    Science.gov (United States)

    Hess, John R

    2012-08-01

    For the past 30 years, red blood cell (RBC) storage systems have been licensed in the United States based on the demonstration that 24-hour in vivo recovery was greater than 75% and hemolysis was less than 1%. Now additional requirements for storage system licensure have being added. The meaning and value of these new requirements have been questioned. The literature regarding the performance of present and suggested new tests for RBC licensure was reviewed. (51) Cr 24-hr in vivo recovery has an intrinsic 4% error of measurement whereas the error in measures of hemolysis is less than 0.1%. Both measures have large donor-dependent end-of-storage variability; nevertheless, they have successfully guided RBC storage system development for six decades. Adenosine 5'-triphosphate and 2,3-diphosphoglycerate are difficult to measure accurately and international shared-sample studies suggest 6 and 11% coefficients of variation across laboratories. There is no readily available way to measure the oxygen equilibrium curve accurately. The new failure criteria provide no useful information and randomly fail good products. Attempts to expand the useful regulatory requirements for RBC storage system licensure are limited by poor understanding of the storage lesion and its effect of RBC performance. Measures of (51) Cr 24-hour in vivo recovery remain critical and resources for this measure are limiting. The interaction between limited testing resources and large donor variability remains a major limit on RBC storage system development. It is important that new required tests contribute meaningful information and not make development and licensure of better products more difficult. © 2012 American Association of Blood Banks.

  8. Maternal cell phone use during pregnancy and child behavioral problems in five birth cohorts

    NARCIS (Netherlands)

    Birks, Laura; Guxens, Mònica; Papadopoulou, Eleni; Alexander, Jan; Ballester, Ferran; Estarlich, Marisa; Gallastegi, Mara; Ha, Mina; Haugen, Margaretha; Huss, Anke; Kheifets, Leeka; Lim, Hyungryul; Olsen, Jørn; Santa-Marina, Loreto; Sudan, Madhuri; Vermeulen, Roel; Vrijkotte, Tanja; Cardis, Elisabeth; Vrijheid, Martine

    2017-01-01

    Previous studies have reported associations between prenatal cell phone use and child behavioral problems, but findings have been inconsistent and based on retrospective assessment of cell phone use. This study aimed to assess this association in a multi-national analysis, using data from three

  9. Maternal cell phone use during pregnancy and child behavioral problems in five birth cohorts

    NARCIS (Netherlands)

    Birks, Laura; Guxens, Mònica; Papadopoulou, Eleni; Alexander, Jan; Ballester, Ferran; Estarlich, Marisa; Gallastegi, Mara; Ha, Mina; Haugen, Margaretha; Huss, Anke; Kheifets, Leeka; Lim, Hyungryul; Olsen, Jørn; Santa-Marina, Loreto; Sudan, Madhuri; Vermeulen, Roel; Vrijkotte, Tanja; Cardis, Elisabeth; Vrijheid, Martine

    INTRODUCTION: Previous studies have reported associations between prenatal cell phone use and child behavioral problems, but findings have been inconsistent and based on retrospective assessment of cell phone use. This study aimed to assess this association in a multi-national analysis, using data

  10. Classification and structural analysis of live and dead Salmonella cells using Fourier transform infrared spectroscopy and principal component analysis.

    Science.gov (United States)

    Sundaram, Jaya; Park, Bosoon; Hinton, Arthur; Yoon, Seung Chul; Windham, William R; Lawrence, Kurt C

    2012-02-01

    Fourier transform infrared spectroscopy (FT-IR) was used to detect Salmonella Typhimurium and Salmonella Enteritidis food-borne bacteria and to distinguish between live and dead cells of both serotypes. Bacteria cells were prepared in 10(8) cfu/mL concentration, and 1 mL of each bacterium was loaded individually on the ZnSe attenuated total reflection (ATR) crystal surface (45° ZnSe, 10 bounces, and 48 mm × 5 mm effective area of analysis on the crystal) and scanned for spectral data collection from 4000 to 650 cm(-1) wavenumber. Analysis of spectral signatures of Salmonella isolates was conducted using principal component analysis (PCA). Spectral data were divided into three regions such as 900-1300, 1300-1800, and 3000-2200 cm(-1) based on their spectral signatures. PCA models were developed to differentiate the serotypes and live and dead cells of each serotype. Maximum classification accuracy of 100% was obtained for serotype differentiation as well as for live and dead cells differentiation. Soft independent modeling of class analogy (SIMCA) analysis was carried out on the PCA model and applied to validation sample sets. It gave a predicted classification accuracy of 100% for both the serotypes and its live and dead cells differentiation. The Mahalanobis distance calculated in three different spectral regions showed maximum distance for the 1800-1300 cm(-1) region, followed by the 3000-2200 cm(-1) region, and then by the 1300-900 cm(-1) region. It showed that both of the serotypes have maximum differences in their nucleic acids, DNA/RNA backbone structures, protein, and amide I and amide II bands.

  11. A note on the stability and discriminability of graph-based features for classification problems in digital pathology

    Science.gov (United States)

    Cruz-Roa, Angel; Xu, Jun; Madabhushi, Anant

    2015-01-01

    Nuclear architecture or the spatial arrangement of individual cancer nuclei on histopathology images has been shown to be associated with different grades and differential risk for a number of solid tumors such as breast, prostate, and oropharyngeal. Graph-based representations of individual nuclei (nuclei representing the graph nodes) allows for mining of quantitative metrics to describe tumor morphology. These graph features can be broadly categorized into global and local depending on the type of graph construction method. While a number of local graph (e.g. Cell Cluster Graphs) and global graph (e.g. Voronoi, Delaunay Triangulation, Minimum Spanning Tree) features have been shown to associated with cancer grade, risk, and outcome for different cancer types, the sensitivity of the preceding segmentation algorithms in identifying individual nuclei can have a significant bearing on the discriminability of the resultant features. This therefore begs the question as to which features while being discriminative of cancer grade and aggressiveness are also the most resilient to the segmentation errors. These properties are particularly desirable in the context of digital pathology images, where the method of slide preparation, staining, and type of nuclear segmentation algorithm employed can all dramatically affect the quality of the nuclear graphs and corresponding features. In this paper we evaluated the trade off between discriminability and stability of both global and local graph-based features in conjunction with a few different segmentation algorithms and in the context of two different histopathology image datasets of breast cancer from whole-slide images (WSI) and tissue microarrays (TMA). Specifically in this paper we investigate a few different performance measures including stability, discriminability and stability vs discriminability trade off, all of which are based on p-values from the Kruskal-Wallis one-way analysis of variance for local and global

  12. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

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

  13. Genome-wide copy number variation pattern analysis and a classification signature for non-small cell lung cancer.

    Science.gov (United States)

    Qiu, Zhe-Wei; Bi, Jia-Hao; Gazdar, Adi F; Song, Kai

    2017-07-01

    The accurate classification of non-small cell lung carcinoma (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is essential for both clinical practice and lung cancer research. Although the standard WHO diagnosis of NSCLC on biopsy material is rapid and economic, more than 13% of NSCLC tumors in the USA are not further classified. The purpose of this study was to analyze the genome-wide pattern differences in copy number variations (CNVs) and to develop a CNV signature as an adjunct test for the routine histopathologic classification of NSCLCs. We investigated the genome-wide CNV differences between these two tumor types using three independent patient datasets. Approximately half of the genes examined exhibited significant differences between LUAD and LUSC tumors and the corresponding non-malignant tissues. A new classifier was developed to identify signature genes out of 20 000 genes. Thirty-three genes were identified as a CNV signature of NSCLC. Using only their CNV values, the classification model separated the LUADs from the LUSCs with an accuracy of 0.88 and 0.84, respectively, in the training and validation datasets. The same signature also classified NSCLC tumors from their corresponding non-malignant samples with an accuracy of 0.96 and 0.98, respectively. We also compared the CNV patterns of NSCLC tumors with those of histologically similar tumors arising at other sites, such as the breast, head, and neck, and four additional tumors. Of greater importance, the significant differences between these tumors may offer the possibility of identifying the origin of tumors whose origin is unknown. © 2017 Wiley Periodicals, Inc.

  14. Maternal cell phone use during pregnancy and child behavioral problems in five birth cohorts.

    Science.gov (United States)

    Birks, Laura; Guxens, Mònica; Papadopoulou, Eleni; Alexander, Jan; Ballester, Ferran; Estarlich, Marisa; Gallastegi, Mara; Ha, Mina; Haugen, Margaretha; Huss, Anke; Kheifets, Leeka; Lim, Hyungryul; Olsen, Jørn; Santa-Marina, Loreto; Sudan, Madhuri; Vermeulen, Roel; Vrijkotte, Tanja; Cardis, Elisabeth; Vrijheid, Martine

    2017-07-01

    Previous studies have reported associations between prenatal cell phone use and child behavioral problems, but findings have been inconsistent and based on retrospective assessment of cell phone use. This study aimed to assess this association in a multi-national analysis, using data from three cohorts with prospective data on prenatal cell phone use, together with previously published data from two cohorts with retrospectively collected cell phone use data. We used individual participant data from 83,884 mother-child pairs in the five cohorts from Denmark (1996-2002), Korea (2006-2011), the Netherlands (2003-2004), Norway (2004-2008), and Spain (2003-2008). We categorized cell phone use into none, low, medium, and high, based on frequency of calls during pregnancy reported by the mothers. Child behavioral problems (reported by mothers using the Strengths and Difficulties Questionnaire or Child Behavior Checklist) were classified in the borderline/clinical and clinical ranges using validated cut-offs in children aged 5-7years. Cohort specific risk estimates were meta-analyzed. Overall, 38.8% of mothers, mostly from the Danish cohort, reported no cell phone use during pregnancy and these mothers were less likely to have a child with overall behavioral, hyperactivity/inattention or emotional problems. Evidence for a trend of increasing risk of child behavioral problems through the maternal cell phone use categories was observed for hyperactivity/inattention problems (OR for problems in the clinical range: 1.11, 95%CI 1.01, 1.22; 1.28, 95%CI 1.12, 1.48, among children of medium and high users, respectively). This association was fairly consistent across cohorts and between cohorts with retrospectively and prospectively collected cell phone use data. Maternal cell phone use during pregnancy may be associated with an increased risk for behavioral problems, particularly hyperactivity/inattention problems, in the offspring. The interpretation of these results is unclear

  15. Automated Arabidopsis plant root cell segmentation based on SVM classification and region merging.

    Science.gov (United States)

    Marcuzzo, Monica; Quelhas, Pedro; Campilho, Ana; Mendonça, Ana Maria; Campilho, Aurélio

    2009-09-01

    To obtain development information of individual plant cells, it is necessary to perform in vivo imaging of the specimen under study, through time-lapse confocal microscopy. Automation of cell detection/marking process is important to provide research tools in order to ease the search for special events, such as cell division. In this paper we discuss an automatic cell detection approach for Arabidopsis thaliana based on segmentation, which selects the best cell candidates from a starting watershed-based image segmentation and improves the result by merging adjacent regions. The selection of individual cells is obtained using a support vector machine (SVM) classifier, based on a cell descriptor constructed from the shape and edge strength of the cells' contour. In addition we proposed a novel cell merging criterion based on edge strength along the line that connects adjacent cells' centroids, which is a valuable tool in the reduction of cell over-segmentation. The result is largely pruned of badly segmented and over-segmented cells, thus facilitating the study of cells. When comparing the results after merging with the basic watershed segmentation, we obtain 1.5% better coverage (increase in F-measure) and up to 27% better precision in correct cell segmentation.

  16. Precision automation of cell type classification and sub-cellular fluorescence quantification from laser scanning confocal images

    Directory of Open Access Journals (Sweden)

    Hardy Craig Hall

    2016-02-01

    Full Text Available While novel whole-plant phenotyping technologies have been successfully implemented into functional genomics and breeding programs, the potential of automated phenotyping with cellular resolution is largely unexploited. Laser scanning confocal microscopy has the potential to close this gap by providing spatially highly resolved images containing anatomic as well as chemical information on a subcellular basis. However, in the absence of automated methods, the assessment of the spatial patterns and abundance of fluorescent markers with subcellular resolution is still largely qualitative and time-consuming. Recent advances in image acquisition and analysis, coupled with improvements in microprocessor performance, have brought such automated methods within reach, so that information from thousands of cells per image for hundreds of images may be derived in an experimentally convenient time-frame. Here, we present a MATLAB-based analytical pipeline to 1 segment radial plant organs into individual cells, 2 classify cells into cell type categories based upon random forest classification, 3 divide each cell into sub-regions, and 4 quantify fluorescence intensity to a subcellular degree of precision for a separate fluorescence channel. In this research advance, we demonstrate the precision of this analytical process for the relatively complex tissues of Arabidopsis hypocotyls at various stages of development. High speed and robustness make our approach suitable for phenotyping of large collections of stem-like material and other tissue types.

  17. Cell segmentation in phase contrast microscopy images via semi-supervised classification over optics-related features.

    Science.gov (United States)

    Su, Hang; Yin, Zhaozheng; Huh, Seungil; Kanade, Takeo

    2013-10-01

    Phase-contrast microscopy is one of the most common and convenient imaging modalities to observe long-term multi-cellular processes, which generates images by the interference of lights passing through transparent specimens and background medium with different retarded phases. Despite many years of study, computer-aided phase contrast microscopy analysis on cell behavior is challenged by image qualities and artifacts caused by phase contrast optics. Addressing the unsolved challenges, the authors propose (1) a phase contrast microscopy image restoration method that produces phase retardation features, which are intrinsic features of phase contrast microscopy, and (2) a semi-supervised learning based algorithm for cell segmentation, which is a fundamental task for various cell behavior analysis. Specifically, the image formation process of phase contrast microscopy images is first computationally modeled with a dictionary of diffraction patterns; as a result, each pixel of a phase contrast microscopy image is represented by a linear combination of the bases, which we call phase retardation features. Images are then partitioned into phase-homogeneous atoms by clustering neighboring pixels with similar phase retardation features. Consequently, cell segmentation is performed via a semi-supervised classification technique over the phase-homogeneous atoms. Experiments demonstrate that the proposed approach produces quality segmentation of individual cells and outperforms previous approaches. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Gender trouble: The World Health Organization, the International Statistical Classification of Diseases and Related Health Problems (ICD)-11 and the trans kids.

    Science.gov (United States)

    Winter, Sam

    2017-10-01

    The World Health Organization (WHO) is revising its diagnostic manual, the International Statistical Classification of Diseases and Related Health Problems (ICD). At the time of writing, and based on recommendations from its ICD Working Group on Sexual Disorders and Sexual Health, WHO is proposing a new ICD chapter titled Conditions Related to Sexual Health, and that the gender incongruence diagnoses (replacements for the gender identity disorder diagnoses used in ICD-10) should be placed in that chapter. WHO is proposing that there should be a Gender incongruence of childhood (GIC) diagnosis for children below the age of puberty. This last proposal has come under fire. Trans community groups, as well as many healthcare professionals and others working for transgender health and wellbeing, have criticised the proposal on the grounds that the pathologisation of gender diversity at such a young age is inappropriate, unnecessary, harmful and inconsistent with WHO's approach in regard to other aspects of development in childhood and youth. Counter proposals have been offered that do not pathologise gender diversity and instead make use of Z codes to frame and document any contacts that young gender diverse children may have with health services. The author draws on his involvement in the ICD revision process, both as a member of the aforementioned WHO Working Group and as one of its critics, to put the case against the GIC proposal, and to recommend an alternative approach for ICD in addressing the needs of gender diverse children.

  19. Classification of phytoplankton cells as live or dead using the vital stains fluorescein diacetate and 5-chloromethylfluorescein diacetate.

    Science.gov (United States)

    MacIntyre, Hugh L; Cullen, John J

    2016-08-01

    Regulations for ballast water treatment specify limits on the concentrations of living cells in discharge water. The vital stains fluorescein diacetate (FDA) and 5-chloromethylfluorescein diacetate (CMFDA) in combination have been recommended for use in verification of ballast water treatment technology. We tested the effectiveness of FDA and CMFDA, singly and in combination, in discriminating between living and heat-killed populations of 24 species of phytoplankton from seven divisions, verifying with quantitative growth assays that uniformly live and dead populations were compared. The diagnostic signal, per-cell fluorescence intensity, was measured by flow cytometry and alternate discriminatory thresholds were defined statistically from the frequency distributions of the dead or living cells. Species were clustered by staining patterns: for four species, the staining of live versus dead cells was distinct, and live-dead classification was essentially error free. But overlap between the frequency distributions of living and heat-killed cells in the other taxa led to unavoidable errors, well in excess of 20% in many. In 4 very weakly staining taxa, the mean fluorescence intensity in the heat-killed cells was higher than that of the living cells, which is inconsistent with the assumptions of the method. Applying the criteria of ≤5% false negative plus ≤5% false positive errors, and no significant loss of cells due to staining, FDA and FDA+CMFDA gave acceptably accurate results for only 8-10 of 24 species (i.e., 33%-42%). CMFDA was the least effective stain and its addition to FDA did not improve the performance of FDA alone. © 2016 The Authors. Journal of Phycology published by Wiley Periodicals, Inc. on behalf of Phycological Society of America.

  20. Classification of biological cells using a sound wave based flow cytometer

    Science.gov (United States)

    Strohm, Eric M.; Gnyawali, Vaskar; Van De Vondervoort, Mia; Daghighi, Yasaman; Tsai, Scott S. H.; Kolios, Michael C.

    2016-03-01

    A flow cytometer that uses sound waves to determine the size of biological cells is presented. In this system, a microfluidic device made of polydimethylsiloxane (PDMS) was developed to hydrodynamically flow focus cells in a single file through a target area. Integrated into the microfluidic device was an ultrasound transducer with a 375 MHz center frequency, aligned opposite the transducer was a pulsed 532 nm laser focused into the device by a 10x objective. Each passing cell was insonfied with a high frequency ultrasound pulse, and irradiated with the laser. The resulting ultrasound and photoacoustic waves from each cell were analyzed using signal processing methods, where features in the power spectra were compared to theoretical models to calculate the cell size. Two cell lines with different size distributions were used to test the system: acute myeloid leukemia cells (AML) and melanoma cells. Over 200 cells were measured using this system. The average calculated diameter of the AML cells was 10.4 +/- 2.5 μm using ultrasound, and 11.4 +/- 2.3 μm using photoacoustics. The average diameter of the melanoma cells was 16.2 +/- 2.9 μm using ultrasound, and 18.9 +/- 3.5 μm using photoacoustics. The cell sizes calculated using ultrasound and photoacoustic methods agreed with measurements using a Coulter Counter, where the AML cells were 9.8 +/- 1.8 μm and the melanoma cells were 16.0 +/- 2.5 μm. These results demonstrate a high speed method of assessing cell size using sound waves, which is an alternative method to traditional flow cytometry techniques.

  1. Classification of Five Uremic Solutes according to Their Effects on Renal Tubular Cells

    Directory of Open Access Journals (Sweden)

    Takeo Edamatsu

    2014-01-01

    Full Text Available Background/Aims. Uremic solutes, which are known to be retained in patients with chronic kidney disease, are considered to have deleterious effects on disease progression. Among these uremic solutes, indoxyl sulfate (IS has been extensively studied, while other solutes have been studied less to state. We conducted a comparative study to examine the similarities and differences between IS, p-cresyl sulfate (PCS, phenyl sulfate (PhS, hippuric acid (HA, and indoleacetic acid (IAA. Methods. We used LLC-PK1 cells to evaluate the effects of these solutes on viable cell number, cell cycle progression, and cell death. Results. All the solutes reduced viable cell number after 48-hour incubation. N-Acetyl-L-cysteine inhibited this effect induced by all solutes except HA. At the concentration that reduced the cell number to almost 50% of vehicle control, IAA induced apoptosis but not cell cycle delay, whereas other solutes induced delay in cell cycle progression with marginal impact on apoptosis. Phosphorylation of p53 and Chk1 and expression of ATF4 and CHOP genes were detected in IS-, PCS-, and PhS-treated cells, but not in IAA-treated cells. Conclusions. Taken together, the adverse effects of PCS and PhS on renal tubular cells are similar to those of IS, while those of HA and IAA differ.

  2. Classification of inflammatory bowel diseases by means of Raman spectroscopic imaging of epithelium cells

    Science.gov (United States)

    Bielecki, Christiane; Bocklitz, Thomas W.; Schmitt, Michael; Krafft, Christoph; Marquardt, Claudio; Gharbi, Akram; Knösel, Thomas; Stallmach, Andreas; Popp, Juergen

    2012-07-01

    We report on a Raman microspectroscopic characterization of the inflammatory bowel diseases (IBD) Crohn's disease (CD) and ulcerative colitis (UC). Therefore, Raman maps of human colon tissue sections were analyzed by utilizing innovative chemometric approaches. First, support vector machines were applied to highlight the tissue morphology (=Raman spectroscopic histopathology). In a second step, the biochemical tissue composition has been studied by analyzing the epithelium Raman spectra of sections of healthy control subjects (n=11), subjects with CD (n=14), and subjects with UC (n=13). These three groups exhibit significantly different molecular specific Raman signatures, allowing establishment of a classifier (support-vector-machine). By utilizing this classifier it was possible to separate between healthy control patients, patients with CD, and patients with UC with an accuracy of 98.90%. The automatic design of both classification steps (visualization of the tissue morphology and molecular classification of IBD) paves the way for an objective clinical diagnosis of IBD by means of Raman spectroscopy in combination with chemometric approaches.

  3. Ontogenic, Phenotypic, and Functional Characterization of XCR1+ Dendritic Cells Leads to a Consistent Classification of Intestinal Dendritic Cells Based on the Expression of XCR1 and SIRPα

    Science.gov (United States)

    Becker, Martina; Güttler, Steffen; Bachem, Annabell; Hartung, Evelyn; Mora, Ahmed; Jäkel, Anika; Hutloff, Andreas; Henn, Volker; Mages, Hans Werner; Gurka, Stephanie; Kroczek, Richard A.

    2014-01-01

    In the past, lack of lineage markers confounded the classification of dendritic cells (DC) in the intestine and impeded a full understanding of their location and function. We have recently shown that the chemokine receptor XCR1 is a lineage marker for cross-presenting DC in the spleen. Now, we provide evidence that intestinal XCR1+ DC largely, but not fully, overlap with CD103+ CD11b− DC, the hypothesized correlate of “cross-presenting DC” in the intestine, and are selectively dependent in their development on the transcription factor Batf3. XCR1+ DC are located in the villi of the lamina propria of the small intestine, the T cell zones of Peyer’s patches, and in the T cell zones and sinuses of the draining mesenteric lymph node. Functionally, we could demonstrate for the first time that XCR1+/CD103+ CD11b− DC excel in the cross-presentation of orally applied antigen. Together, our data show that XCR1 is a lineage marker for cross-presenting DC also in the intestinal immune system. Further, extensive phenotypic analyses reveal that expression of the integrin SIRPα consistently demarcates the XCR1− DC population. We propose a simplified and consistent classification system for intestinal DC based on the expression of XCR1 and SIRPα. PMID:25120540

  4. Small-Cell Lung Cancer: Clinical Management and Unmet Needs New Perspectives for an Old Problem.

    Science.gov (United States)

    Lo Russo, Giuseppe; Macerelli, Marianna; Platania, Marco; Zilembo, Nicoletta; Vitali, Milena; Signorelli, Diego; Proto, Claudia; Ganzinelli, Monica; Gallucci, Rosaria; Agustoni, Francesco; Fasola, Gianpiero; de Braud, Filippo; Garassino, Marina Chiara

    2017-01-01

    Small cell lung cancer is a highly aggressive, difficult to treat neoplasm. Among all lung tumors, small cell lung cancers account for about 20%. Patients typically include heavy smokers in 70s age group, presenting with symptoms such as intrathoracic tumors growth, distant spread or paraneoplastic syndromes at the time of diagnosis. A useful and functional classification divides small cell lung cancers into limited disease and extensive disease. Concurrent chemo-radiotherapy is the standard treatment for limited disease, with improved survival when combined with prophylactic cranial irradiation. Platinum compounds (cisplatin/carboplatin) plus etoposide remain the cornerstone for extensive disease. Nevertheless, despite high chemo- and radio-sensitivity of this cancer, nearly all patients relapse within the first two years and the prognosis is extremely poor. A deeper understanding about small cell lung cancer carcinogenesis led to develop and test a considerable number of new and targeted agents but the results are currently weak or insufficient. To date, small cell lung cancer is still a challenge for researchers. In this review, key aspects of small cell lung cancer management and controversial points of standard and new treatments will be discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  5. Convergence of Cell Based Finite Volume Discretizations for Problems of Control in the Conduction Coefficients

    DEFF Research Database (Denmark)

    Evgrafov, Anton; Gregersen, Misha Marie; Sørensen, Mads Peter

    2011-01-01

    We present a convergence analysis of a cell-based finite volume (FV) discretization scheme applied to a problem of control in the coefficients of a generalized Laplace equation modelling, for example, a steady state heat conduction. Such problems arise in applications dealing with geometric optimal......, whereas the convergence of the coefficients happens only with respect to the "volumetric" Lebesgue measure. Additionally, depending on whether the stationarity conditions are stated for the discretized or the original continuous problem, two distinct concepts of stationarity at a discrete level arise. We...... provide characterizations of limit points, with respect to FV mesh size, of globally optimal solutions and two types of stationary points to the discretized problems. We illustrate the practical behaviour of our cell-based FV discretization algorithm on a numerical example....

  6. Physiological problems in patients undergoing autologous and allogeneic hematopoietic stem cell transplantation

    Directory of Open Access Journals (Sweden)

    Sevgisun Kapucu

    2014-01-01

    Full Text Available Objective: Stem cell transplantation is usually performed in an effort to extend the patient′s life span and to improve their quality of life. This study was conducted to determine the postoperative physiological effects experienced by patients who had undergone autologous and allogeneic stem cell transplantation. Methods: The research is a descriptive study conducted with a sample of 60 patients at Stem Cell Transplantation Units in Ankara. Percentile calculation and chi-square tests were used to evaluate the data. Results: When a comparison was made between patients who had undergone allogeneic Hematopoietic stem cell transplantation (HSCT and those who had undergone autologous HSCT, results indicated that problems occurred more often for the allogeneic HSCT patients. The problems included: Digestion (94.3%, dermatological (76.7%, cardiac and respiratory (66.7%, neurological (66.7%, eye (56.7%, infections (26.7% and Graft Versus Host Disease (5 patients. Furthermore, the problems with pain (50%, numbness and tingling (40%, and speech disorders (3 patients were observed more often in autologous BMT patients. Conclusion: Autologous and allogeneic patients experienced most of physical problems due to they receive high doses of chemotherapy. Therefore, it is recommended that an interdisciplinary support team approach should be usedtohelp reduce and manage the problems that may arise during patient care.

  7. Quantifying co-cultured cell phenotypes in high-throughput using pixel-based classification.

    Science.gov (United States)

    Logan, David J; Shan, Jing; Bhatia, Sangeeta N; Carpenter, Anne E

    2016-03-01

    Biologists increasingly use co-culture systems in which two or more cell types are grown in cell culture together in order to better model cells' native microenvironments. Co-cultures are often required for cell survival or proliferation, or to maintain physiological functioning in vitro. Having two cell types co-exist in culture, however, poses several challenges, including difficulties distinguishing the two populations during analysis using automated image analysis algorithms. We previously analyzed co-cultured primary human hepatocytes and mouse fibroblasts in a high-throughput image-based chemical screen, using a combination of segmentation, measurement, and subsequent machine learning to score each cell as hepatocyte or fibroblast. While this approach was successful in counting hepatocytes for primary screening, segmentation of the fibroblast nuclei was less accurate. Here, we present an improved approach that more accurately identifies both cell types. Pixel-based machine learning (using the software ilastik) is used to seed segmentation of each cell type individually (using the software CellProfiler). This streamlined and accurate workflow can be carried out using freely available and open source software. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. A microarray platform-independent classification tool for cell of origin class allows comparative analysis of gene expression in diffuse large B-cell lymphoma.

    Directory of Open Access Journals (Sweden)

    Matthew A Care

    Full Text Available Cell of origin classification of diffuse large B-cell lymphoma (DLBCL identifies subsets with biological and clinical significance. Despite the established nature of the classification existing studies display variability in classifier implementation, and a comparative analysis across multiple data sets is lacking. Here we describe the validation of a cell of origin classifier for DLBCL, based on balanced voting between 4 machine-learning tools: the DLBCL automatic classifier (DAC. This shows superior survival separation for assigned Activated B-cell (ABC and Germinal Center B-cell (GCB DLBCL classes relative to a range of other classifiers. DAC is effective on data derived from multiple microarray platforms and formalin fixed paraffin embedded samples and is parsimonious, using 20 classifier genes. We use DAC to perform a comparative analysis of gene expression in 10 data sets (2030 cases. We generate ranked meta-profiles of genes showing consistent class-association using ≥6 data sets as a cut-off: ABC (414 genes and GCB (415 genes. The transcription factor ZBTB32 emerges as the most consistent and differentially expressed gene in ABC-DLBCL while other transcription factors such as ARID3A, BATF, and TCF4 are also amongst the 24 genes associated with this class in all datasets. Analysis of enrichment of 12323 gene signatures against meta-profiles and all data sets individually confirms consistent associations with signatures of molecular pathways, chromosomal cytobands, and transcription factor binding sites. We provide DAC as an open access Windows application, and the accompanying meta-analyses as a resource.

  9. A framework for image-based classification of mitotic cells in asynchronous populations.

    Science.gov (United States)

    Slattery, Scott D; Newberg, Justin Y; Szafran, Adam T; Hall, Rebecca M; Brinkley, Bill R; Mancini, Michael A

    2012-04-01

    High content screening (HCS) has emerged an important tool for drug discovery because it combines rich readouts of cellular responses in a single experiment. Inclusion of cell cycle analysis into HCS is essential to identify clinically suitable anticancer drugs that disrupt the aberrant mitotic activity of cells. One challenge for integration of cell cycle analysis into HCS is that cells must be chemically synchronized to specific phases, adding experimental complexity to high content screens. To address this issue, we have developed a rules-based method that utilizes mitotic phosphoprotein monoclonal 2 (MPM-2) marker and works consistently in different experimental conditions and in asynchronous populations. Further, the performance of the rules-based method is comparable to established machine learning approaches for classifying cell cycle data, indicating the robustness of the features we use in the framework. As such, we suggest the use of MPM-2 analysis and its associated expressive features for integration into HCS approaches.

  10. The morphological classification of normal and abnormal red blood cell using Self Organizing Map

    Science.gov (United States)

    Rahmat, R. F.; Wulandari, F. S.; Faza, S.; Muchtar, M. A.; Siregar, I.

    2018-02-01

    Blood is an essential component of living creatures in the vascular space. For possible disease identification, it can be tested through a blood test, one of which can be seen from the form of red blood cells. The normal and abnormal morphology of the red blood cells of a patient is very helpful to doctors in detecting a disease. With the advancement of digital image processing technology can be used to identify normal and abnormal blood cells of a patient. This research used self-organizing map method to classify the normal and abnormal form of red blood cells in the digital image. The use of self-organizing map neural network method can be implemented to classify the normal and abnormal form of red blood cells in the input image with 93,78% accuracy testing.

  11. Issues and Ethical Problems of Stem Cell Therapy – Where is Hippocrates?

    Directory of Open Access Journals (Sweden)

    Lucie Rousková

    2008-01-01

    Full Text Available Stem cells and their therapeutic use present many questions associated with ethical problems in medicine. There is great effort on the part of physicians to help millions of patients while there are ethical problems with the use of new methods and technologies and all of these are affected by economic and political influences. How will the current generation deal with these problems? Medicine, in this begard, is experiencing a stormy evolution of human culture in the relationships between disease, patient and doctor. Philosophy approaches the same juncture of human culture, but seemingly from the other side. Both disciplines are facing a great problem: How to unite the content of current human morality and the desire for health? Both philosophers and physicians perceive this deficit in human culture as it does not provide immediately usable normatives, which the living generation of healthy and ill is waiting for. It may be said that medicine, as many times before, has reached a stage where it cannot rely only on the proved axiologic values from the past, ethical normatives or cultivated moral sense of its subjects. Medicine has no other alternative than to take an active part in resolution of interdisciplinary problems originating from philosophic-biologic or philosophic-medical inquiries of axiologic, ethical, and moral issues. Our paper indicates some ways of the search in forming ethical principles of the stem-cell therapy from the view of biologists and physicians. New ways are recommended in theoretical-methodological interdisciplinary research, especially, in theoretical and experimental biology, and theoretical and clinical medicine, as well as philosophy. In this paper important ethical problems are pointed out in order to find answers to some key problems connected with cell therapy and the use of stem cells.

  12. Classification of bladder cancer cell lines using Raman spectroscopy: a comparison of excitation wavelength, sample substrate and statistical algorithms

    Science.gov (United States)

    Kerr, Laura T.; Adams, Aine; O'Dea, Shirley; Domijan, Katarina; Cullen, Ivor; Hennelly, Bryan M.

    2014-05-01

    Raman microspectroscopy can be applied to the urinary bladder for highly accurate classification and diagnosis of bladder cancer. This technique can be applied in vitro to bladder epithelial cells obtained from urine cytology or in vivo as an optical biopsy" to provide results in real-time with higher sensitivity and specificity than current clinical methods. However, there exists a high degree of variability across experimental parameters which need to be standardised before this technique can be utilized in an everyday clinical environment. In this study, we investigate different laser wavelengths (473 nm and 532 nm), sample substrates (glass, fused silica and calcium fluoride) and multivariate statistical methods in order to gain insight into how these various experimental parameters impact on the sensitivity and specificity of Raman cytology.

  13. Criteria which determine meronymy of the denotatum 'house' in the phase of selection and classification of research material: Problems and dilemmas

    Directory of Open Access Journals (Sweden)

    Dilparić Branislava M.

    2014-01-01

    Full Text Available This paper presents some of the problems and dilemmas which the author was faced with in the preparatory phase of selection and -classification of lexical material for the study on the semantic field of -house and its parts or, more precisely, its realizations (lexical fields in two languages, English and Serbian. The lexical fields, based on the semantic relation of meronymy (or part-whole relation and thus also called meronomies, belong to a type of the (branching lexical hierarchies, having as its highest member or global holonym (that is a noun denoting the largest whole in a meronomy the lexeme house in -English and kuća in Serbian, and as its lower members, the so-called meronyms, all the English / Serbian lexemes that denote some part of this whole. However, due to the fact that there is still no consensus on the characterization of the concepts of 'part' and 'whole', as well as the relation(s between them, one of the first dilemmas concerning the selection of English and Serbian meronyms for the study was related to how to interprete 'a house taken as a whole' and, therefore, what types of entities to consider as its parts. To be more precise, is 'a house taken as a whole' seen only as a (main building (on the property area composed of its characteristic segmental and systemic parts, e.g. a roof, walls, doors, windows, rooms, plumbing, wiring, etc., or could it be interpreted in a wider sense to also include a large variety of entities which are, due to its function, typically found in it, e.g. furnishings, appliances, dishes, etc., and/or close to it, e.g. -out-buildings, a fence, a yard, a garden, etc.? Furthermore, a great number of problems and dilemmas this time concerning not only the selection, but also the classification of the meronyms appeared even in a case when 'a house as a whole' was seen only as a 3-D hollow object and the criteria which determine meronymy of the denotatum 'house' according to Cruse (1995; 2002; 2004a

  14. The Many Elements of Traditional Fire Knowledge: Synthesis, Classification, and Aids to Cross-cultural Problem Solving in Fire-dependent Systems Around the World

    Directory of Open Access Journals (Sweden)

    Mary R. Huffman

    2013-12-01

    Full Text Available I examined the hypothesis that traditional social-ecological fire systems around the world include common elements of traditional fire knowledge (TFK. I defined TFK as fire-related knowledge, beliefs, and practices that have been developed and applied on specific landscapes for specific purposes by long time inhabitants. In all, 69 distinct elements of TFK were documented in 35 studies, including accounts from 27 countries on 6 continents. On all 6 continents, 21 elements (30% were recorded, and 46 elements (67% were recorded on 4 or more continents. The top 12 most commonly reported elements, which were included in > 50 % of the studies, were fire effects on vegetation; season of the year; fire effects on animals; moisture of live or dead fuels; the onset or end of rainy season, dry season, or timing of rain; burning illegal or regulated by central government; fire intensity, heat output, i.e., hot or cool fire; frequency, return interval, time since fire; fire control; firebreaks, barriers; consequences of not burning; and plant or animal phenology. Traditional fire knowledge was multifaceted: 13 studies included more than 25 elements. Practicing traditional fire management also entails understanding the ways in which multiple elements interact and influence one another. Three classification systems provide insight into TFK systems, including typologies of agro-ecological type, pre- and postindustrial anthropological fire regimes, and viability status. The longevity of traditional fire knowledge and practice faces serious threats at precisely the time when climate change promises disruptions in fire activity that will be problematic for indigenous and nonindigenous societies alike. Central governments tend to adopt the pathological response of command and control during times of fire increase, further constraining traditional fire management. The opposite is needed: to seriously engage traditional practitioners in solving fire problems of

  15. Classification of large circulating tumor cells isolated with ultra-high throughput microfluidic Vortex technology

    Science.gov (United States)

    Che, James; Yu, Victor; Dhar, Manjima; Renier, Corinne; Matsumoto, Melissa; Heirich, Kyra; Garon, Edward B.; Goldman, Jonathan; Rao, Jianyu; Sledge, George W.; Pegram, Mark D.; Sheth, Shruti; Jeffrey, Stefanie S.; Kulkarni, Rajan P.; Sollier, Elodie; Di Carlo, Dino

    2016-01-01

    Circulating tumor cells (CTCs) are emerging as rare but clinically significant non-invasive cellular biomarkers for cancer patient prognosis, treatment selection, and treatment monitoring. Current CTC isolation approaches, such as immunoaffinity, filtration, or size-based techniques, are often limited by throughput, purity, large output volumes, or inability to obtain viable cells for downstream analysis. For all technologies, traditional immunofluorescent staining alone has been employed to distinguish and confirm the presence of isolated CTCs among contaminating blood cells, although cells isolated by size may express vastly different phenotypes. Consequently, CTC definitions have been non-trivial, researcher-dependent, and evolving. Here we describe a complete set of objective criteria, leveraging well-established cytomorphological features of malignancy, by which we identify large CTCs. We apply the criteria to CTCs enriched from stage IV lung and breast cancer patient blood samples using the High Throughput Vortex Chip (Vortex HT), an improved microfluidic technology for the label-free, size-based enrichment and concentration of rare cells. We achieve improved capture efficiency (up to 83%), high speed of processing (8 mL/min of 10x diluted blood, or 800 μL/min of whole blood), and high purity (avg. background of 28.8±23.6 white blood cells per mL of whole blood). We show markedly improved performance of CTC capture (84% positive test rate) in comparison to previous Vortex designs and the current FDA-approved gold standard CellSearch assay. The results demonstrate the ability to quickly collect viable and pure populations of abnormal large circulating cells unbiased by molecular characteristics, which helps uncover further heterogeneity in these cells. PMID:26863573

  16. Problem-Solving Test: RNA and Protein Synthesis in Bacteriophage-Infected "E. coli" Cells

    Science.gov (United States)

    Szeberenyi, Jozsef

    2008-01-01

    The classic experiment presented in this problem-solving test was designed to identify the template molecules of translation by analyzing the synthesis of phage proteins in "Escherichia coli" cells infected with bacteriophage T4. The work described in this test led to one of the most seminal discoveries of early molecular biology: it dealt a…

  17. [The advantages and problems of implementation of the globally harmonized system (GHS) of classification and labelling of chemicals in the practice of the national preventive toxicology and hygiene].

    Science.gov (United States)

    Khamidulina, Kh Kh; Rabikova, D N

    2013-01-01

    GHS, aimed at unifying and objective assessment of risk has significant differences from current classifications of toxicity and danger applied in the Russian Federation. However, the need to implement the international commitments of the Russian Federation, the reluctance of the Russian industry twice classify and label products for the domestic and international market demand introduction of the International Classification into the practice of national preventive toxicology.

  18. Routing, Disjoint Paths, and Classification

    National Research Council Canada - National Science Library

    Zhou, Shuheng

    2006-01-01

    .... The third part of this thesis concerns a type of classification problem that is motivated by a computational biology problem, where it is desirable that a small amount of genotype data from each...

  19. Competence classification of cumulus and granulosa cell transcriptome in embryos matched by morphology and female age

    DEFF Research Database (Denmark)

    Borup, Rehannah; Thuesen, Lea Langhoff; Andersen, Claus Yding

    2016-01-01

    OBJECTIVE: By focussing on differences in the mural granulosa cell (MGC) and cumulus cell (CC) transcriptomes from follicles resulting in competent (live birth) and non-competent (no pregnancy) oocytes the study aims on defining a competence classifier expression profile in the two cellular...... compartments. DESIGN: A case-control study. SETTING: University based facilities for clinical services and research. PATIENTS: MGC and CC samples from 60 women undergoing IVF treatment following the long GnRH-agonist protocol were collected. Samples from 16 oocytes where live birth was achieved and 16 age...... classifier signature that could classify live birth with accuracy above random chance level. CONCLUSION: We have developed a cumulus cell classifier, which showed a promising performance on external data. This suggests that the gene signature at least partly include genes that relates to competence...

  20. Microarray-based classification of diffuse large B-cell lymphoma

    DEFF Research Database (Denmark)

    Poulsen, Christian Bjørn; Borup, Rehannah; Nielsen, Finn Cilius

    2005-01-01

    OBJECTIVE: Hierarchical clusterings of diffuse large B-cell lymphoma (DLBCL) based on gene expression signatures have previously been used to classify DLBCL into Germinal Center B-cell (GCB) and Activated B-cell (ABC) types. To examine if it was feasible to perform a cross-platform validation...... for hierarchical clustering. In this way, three subtypes, including the GCB type (n = 20), the ABC type (n = 25) and an intermediate group, Type-3 (n = 5), were distinguished. The CD10 and Bcl-6 expression as well as t(14;18) translocation were prevalent, but not exclusive to the GCB type. By contrast, MUM1......;103:1862-1868) to exhibit a higher specificity than the original gene lists. CONCLUSION: We conclude that gene expression profiling with Affymetrix Genechips is efficient to distinguish between GCB and ABC types of DLBCL and that these are likely to represent separate biological entities. The Genechip platform is highly...

  1. HEp-2 Cell Classification Using Shape Index Histograms With Donut-Shaped Spatial Pooling

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo; Vestergaard, Jacob Schack; Larsen, Rasmus

    2014-01-01

    introduce a spatial decomposition scheme which is radially symmetric and suitable for cell images. The spatial decomposition is performed using donut-shaped pooling regions of varying sizes when gathering histogram contributions. We evaluate our method using both the ICIP 2013 and the ICPR 2012 competition...

  2. Dismantling papillary renal cell carcinoma classification: The heterogeneity of genetic profiles suggests several independent diseases.

    Science.gov (United States)

    Marsaud, Alexandre; Dadone, Bérengère; Ambrosetti, Damien; Baudoin, Christian; Chamorey, Emmanuel; Rouleau, Etienne; Lefol, Cédrick; Roussel, Jean-François; Fabas, Thibault; Cristofari, Gaël; Carpentier, Xavier; Michiels, Jean-François; Amiel, Jean; Pedeutour, Florence

    2015-06-01

    Papillary renal cell carcinoma (pRCC) is the second most frequent renal cell carcinoma (RCC) after clear cell RCC. In contrast to clear cell RCC, there is no consensual protocol using targeted therapy for metastatic pRCC. Moreover, diagnosis of some pRCC, especially pRCC of type 2 (pRCC2) may be challenging. Our aim was to identify molecular biomarkers that could be helpful for the diagnosis and treatment of pRCC. We studied the clinical, histological, immunohistological, and comprehensive genetic features of a series of 31 pRCC including 15 pRCC1 and 16 pRCC2. We aimed to determine whether pRCC represents a unique entity or several diseases. In addition, we compared the genetic features of pRCC2 to those of eight RCC showing various degrees of tubulo-papillary architecture, including three TFE-translocation RCC and five unclassified RCC. We demonstrate that pRCC is a heterogeneous group of tumors with distinct evolution. While most pRCC2 had genetic profiles similar to pRCC1, some shared genomic features, such as loss of 3p and loss of chromosome 14, with clear cell RCC, TFE-translocation RCC, and unclassified RCC. We identified variants of the MET gene in three pRCC1. A mutation in the BRAF gene was also identified in one pRCC1. In addition, using next-generation sequencing (NGS), we identified several variant genes. Genomic profiling completed by NGS allowed us to classify pRCC2 in several groups and to identify novel mutations. Our findings provide novel information on the pathogenesis of pRCC that allow insights for personalized treatment. © 2015 Wiley Periodicals, Inc.

  3. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

    Directory of Open Access Journals (Sweden)

    Abdullah M. Iliyasu

    2017-12-01

    Full Text Available A quantum hybrid (QH intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN algorithm (known simply as the Q-Fuzzy approach is proposed for efficient feature selection and classification of cells in cervical smeared (CS images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach. In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

  4. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection.

    Science.gov (United States)

    Iliyasu, Abdullah M; Fatichah, Chastine

    2017-12-19

    A quantum hybrid (QH) intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO) method with the intuitionistic rationality of traditional fuzzy k -nearest neighbours (Fuzzy k -NN) algorithm (known simply as the Q-Fuzzy approach) is proposed for efficient feature selection and classification of cells in cervical smeared (CS) images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles) that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection) and another hybrid technique combining the standard PSO algorithm with the Fuzzy k -NN technique (P-Fuzzy approach). In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k -NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

  5. STL-based analysis of TRAIL-induced apoptosis challenges the notion of type I/type II cell line classification.

    Directory of Open Access Journals (Sweden)

    Szymon Stoma

    Full Text Available Extrinsic apoptosis is a programmed cell death triggered by external ligands, such as the TNF-related apoptosis inducing ligand (TRAIL. Depending on the cell line, the specific molecular mechanisms leading to cell death may significantly differ. Precise characterization of these differences is crucial for understanding and exploiting extrinsic apoptosis. Cells show distinct behaviors on several aspects of apoptosis, including (i the relative order of caspases activation, (ii the necessity of mitochondria outer membrane permeabilization (MOMP for effector caspase activation, and (iii the survival of cell lines overexpressing Bcl2. These differences are attributed to the activation of one of two pathways, leading to classification of cell lines into two groups: type I and type II. In this work we challenge this type I/type II cell line classification. We encode the three aforementioned distinguishing behaviors in a formal language, called signal temporal logic (STL, and use it to extensively test the validity of a previously-proposed model of TRAIL-induced apoptosis with respect to experimental observations made on different cell lines. After having solved a few inconsistencies using STL-guided parameter search, we show that these three criteria do not define consistent cell line classifications in type I or type II, and suggest mutants that are predicted to exhibit ambivalent behaviors. In particular, this finding sheds light on the role of a feedback loop between caspases, and reconciliates two apparently-conflicting views regarding the importance of either upstream or downstream processes for cell-type determination. More generally, our work suggests that these three distinguishing behaviors should be merely considered as type I/II features rather than cell-type defining criteria. On the methodological side, this work illustrates the biological relevance of STL-diagrams, STL population data, and STL-guided parameter search implemented in the

  6. STL-based analysis of TRAIL-induced apoptosis challenges the notion of type I/type II cell line classification.

    Science.gov (United States)

    Stoma, Szymon; Donzé, Alexandre; Bertaux, François; Maler, Oded; Batt, Gregory

    2013-01-01

    Extrinsic apoptosis is a programmed cell death triggered by external ligands, such as the TNF-related apoptosis inducing ligand (TRAIL). Depending on the cell line, the specific molecular mechanisms leading to cell death may significantly differ. Precise characterization of these differences is crucial for understanding and exploiting extrinsic apoptosis. Cells show distinct behaviors on several aspects of apoptosis, including (i) the relative order of caspases activation, (ii) the necessity of mitochondria outer membrane permeabilization (MOMP) for effector caspase activation, and (iii) the survival of cell lines overexpressing Bcl2. These differences are attributed to the activation of one of two pathways, leading to classification of cell lines into two groups: type I and type II. In this work we challenge this type I/type II cell line classification. We encode the three aforementioned distinguishing behaviors in a formal language, called signal temporal logic (STL), and use it to extensively test the validity of a previously-proposed model of TRAIL-induced apoptosis with respect to experimental observations made on different cell lines. After having solved a few inconsistencies using STL-guided parameter search, we show that these three criteria do not define consistent cell line classifications in type I or type II, and suggest mutants that are predicted to exhibit ambivalent behaviors. In particular, this finding sheds light on the role of a feedback loop between caspases, and reconciliates two apparently-conflicting views regarding the importance of either upstream or downstream processes for cell-type determination. More generally, our work suggests that these three distinguishing behaviors should be merely considered as type I/II features rather than cell-type defining criteria. On the methodological side, this work illustrates the biological relevance of STL-diagrams, STL population data, and STL-guided parameter search implemented in the tool Breach

  7. Cellular image classification

    CERN Document Server

    Xu, Xiang; Lin, Feng

    2017-01-01

    This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical...

  8. Modern problems of DNA repair in mammalian cells and some unsettled questions

    International Nuclear Information System (INIS)

    Gaziev, A.I.

    1978-01-01

    A comparison of DNA repair process in the cells of mammals and E. coli revealed no principal differences in the enzymic mechanisms of DNA repair in the cells of higher and lower organisms. It has been found that when given is the same number of impairments in the section of DNA chain in the cells of mammals and bacteria the regeneration in the former occurs more slowly than in the latter. Low rate elimination of impairments of DNA in the cells of mammals is due to a more complex intracellular and permolecular organization. It is stressed that the investigation into the mechanisms of fixing impairments in case of postreplication DNA repair is a very important and unresolved problem, especially in terms of radiation mutagenesis and cancerogenesis. Much thought is given to the problem of repairing double stranded ruptures of DNA. It is proposed that DNA repair should be considered not only in terms of functioning of enzymes in DNA metabolism, but also permolecular organization of genome in the cell

  9. Red cell indices in classification and treatment of anemias: from M.M. Wintrobes's original 1934 classification to the third millennium.

    Science.gov (United States)

    Brugnara, Carlo; Mohandas, Narla

    2013-05-01

    Measurements of red cell volume, hemoglobin (Hb) concentration and Hb content continue to play a crucial role in the differential diagnosis of anemias 80 years after the publication of Wintrobe's seminal work. Modern hematology analyzers provide additional data on the heterogeneity of these parameters (distribution width) and quantify similar parameters of reticulocytes as well. Red cell and reticulocyte cellular indices are widely used in the diagnosis and monitoring of hematological diseases. Quantification of hypochromic cells is valuable in the differential diagnosis of thalassemia trait and iron deficiency, and in monitoring therapeutic response to erythropoietic stimulating agents, while hyperchromic cells are an essential diagnostic component for hereditary spherocytosis and may correlate with hemolytic parameters in sickle cell disease. Values for these parameters however depend on the technology used. Red cell clearance is associated with a reduction in both Hb content and cell volume: normal cells are likely to be removed by the time they reach a volume of 72 fl. Reticulocyte parameters such as Hb content (CHr or ret-He) or maturity index (RMI) have shown value in a variety of hematological conditions. New findings from genetic association studies have identified several potential novel genes affecting red cell indices, which are not mediated by changes in iron availability. Red cell indices continue to provide an essential support to the diagnosis and monitoring of hematological diseases.

  10. Human embryonic stem cell research, justice, and the problem of unequal biological access

    Directory of Open Access Journals (Sweden)

    Moller Mark S

    2008-09-01

    Full Text Available Abstract In 2003, Ruth Faden and eighteen other colleagues argued that a "problem of unequal biological access" is likely to arise in access to therapies resulting from human embryonic stem cell research. They showed that unless deliberate steps are taken in the United States to ensure that the human embryonic stem cell lines available to researchers mirrors the genetic diversity of the general population, white Americans will likely receive the benefits of these therapies to the relative exclusion of minority ethnic groups. Over the past five years the problem of unequal biological access has not received much attention from politicians, bioethicists and even many researchers in the United States, in spite of the widely held belief in the country that there is an obligation to prevent and correct ethnic disparities in access to medical care. The purpose of this paper is to increase awareness of the problem of unequal biological access and of the need to do more than is currently being done to ensure that ethnic disparities in access to human embryonic stem cell-based therapies do not arise. Specifically, this paper explains why the problem of unequal biological access will likely arise in the United States in such a way that white Americans will disproportionately receive most of the benefits of the therapies resulting from human embryonic stem cell research. It also argues for why there is an obligation to prevent these ethnic disparities in access from happening and outlines four steps that need to be taken towards meeting this obligation.

  11. Inverse problem analysis of pluripotent stem cell aggregation dynamics in stirred-suspension cultures

    Science.gov (United States)

    Rostami, Mahboubeh Rahmati; Wu, Jincheng; Tzanakakis, Emmanuel S.

    2015-01-01

    The cultivation of stem cells as aggregates in scalable bioreactor cultures is an appealing modality for the large-scale manufacturing of stem cell products. Aggregation phenomena are central to such bioprocesses affecting the viability, proliferation and differentiation trajectory of stem cells but a quantitative framework is currently lacking. A population balance equation (PBE) model was used to describe the temporal evolution of the embryonic stem cell (ESC) cluster size distribution by considering collision-induced aggregation and cell proliferation in a stirred-suspension vessel. For ESC cultures at different agitation rates, the aggregation kernel representing the aggregation dynamics was successfully recovered as a solution of the inverse problem. The rate of change of the average aggregate size was greater at the intermediate rate tested suggesting a trade-off between increased collisions and agitation-induced shear. Results from forward simulation with obtained aggregation kernels were in agreement with transient aggregate size data from experiments. We conclude that the framework presented here can complement mechanistic studies offering insights into relevant stem cell clustering processes. More importantly from a process development standpoint, this strategy can be employed in the design and control of bioreactors for the generation of stem cell derivatives for drug screening, tissue engineering and regenerative medicine. PMID:26036699

  12. Efficient Parallel Sorting for Migrating Birds Optimization When Solving Machine-Part Cell Formation Problems

    Directory of Open Access Journals (Sweden)

    Ricardo Soto

    2016-01-01

    Full Text Available The Machine-Part Cell Formation Problem (MPCFP is a NP-Hard optimization problem that consists in grouping machines and parts in a set of cells, so that each cell can operate independently and the intercell movements are minimized. This problem has largely been tackled in the literature by using different techniques ranging from classic methods such as linear programming to more modern nature-inspired metaheuristics. In this paper, we present an efficient parallel version of the Migrating Birds Optimization metaheuristic for solving the MPCFP. Migrating Birds Optimization is a population metaheuristic based on the V-Flight formation of the migrating birds, which is proven to be an effective formation in energy saving. This approach is enhanced by the smart incorporation of parallel procedures that notably improve performance of the several sorting processes performed by the metaheuristic. We perform computational experiments on 1080 benchmarks resulting from the combination of 90 well-known MPCFP instances with 12 sorting configurations with and without threads. We illustrate promising results where the proposal is able to reach the global optimum in all instances, while the solving time with respect to a nonparallel approach is notably reduced.

  13. A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem

    Science.gov (United States)

    Moradgholi, Mostafa; Paydar, Mohammad Mahdi; Mahdavi, Iraj; Jouzdani, Javid

    2016-05-01

    Nowadays, with the increasing pressure of the competitive business environment and demand for diverse products, manufacturers are force to seek for solutions that reduce production costs and rise product quality. Cellular manufacturing system (CMS), as a means to this end, has been a point of attraction to both researchers and practitioners. Limitations of cell formation problem (CFP), as one of important topics in CMS, have led to the introduction of virtual CMS (VCMS). This research addresses a bi-objective dynamic virtual cell formation problem (DVCFP) with the objective of finding the optimal formation of cells, considering the material handling costs, fixed machine installation costs and variable production costs of machines and workforce. Furthermore, we consider different skills on different machines in workforce assignment in a multi-period planning horizon. The bi-objective model is transformed to a single-objective fuzzy goal programming model and to show its performance; numerical examples are solved using the LINGO software. In addition, genetic algorithm (GA) is customized to tackle large-scale instances of the problems to show the performance of the solution method.

  14. A reliable Raman-spectroscopy-based approach for diagnosis, classification and follow-up of B-cell acute lymphoblastic leukemia

    Science.gov (United States)

    Managò, Stefano; Valente, Carmen; Mirabelli, Peppino; Circolo, Diego; Basile, Filomena; Corda, Daniela; de Luca, Anna Chiara

    2016-04-01

    Acute lymphoblastic leukemia type B (B-ALL) is a neoplastic disorder that shows high mortality rates due to immature lymphocyte B-cell proliferation. B-ALL diagnosis requires identification and classification of the leukemia cells. Here, we demonstrate the use of Raman spectroscopy to discriminate normal lymphocytic B-cells from three different B-leukemia transformed cell lines (i.e., RS4;11, REH, MN60 cells) based on their biochemical features. In combination with immunofluorescence and Western blotting, we show that these Raman markers reflect the relative changes in the potential biological markers from cell surface antigens, cytoplasmic proteins, and DNA content and correlate with the lymphoblastic B-cell maturation/differentiation stages. Our study demonstrates the potential of this technique for classification of B-leukemia cells into the different differentiation/maturation stages, as well as for the identification of key biochemical changes under chemotherapeutic treatments. Finally, preliminary results from clinical samples indicate high consistency of, and potential applications for, this Raman spectroscopy approach.

  15. A hybrid approach to solving the problem of design of nuclear fuel cells

    International Nuclear Information System (INIS)

    Montes T, J. L.; Perusquia del C, R.; Ortiz S, J. J.; Castillo, A.

    2015-09-01

    An approach to solving the problem of fuel cell design for BWR power reactor is presented. For this purpose the hybridization of a method based in heuristic knowledge rules called S15 and the advantages of a meta-heuristic method is proposed. The synergy of potentialities of both techniques allows finding solutions of more quality. The quality of each solution is obtained through a multi-objective function formed from the main cell parameters that are provided or obtained during the simulation with the CASMO-4 code. To evaluate this alternative of solution nuclear fuel cells of reference of nuclear power plant of Laguna Verde were used. The results show that in a systematic way the results improve when both methods are coupled. As a result of the hybridization process of the mentioned techniques an improvement is achieved in a range of 2% with regard to the achieved results in an independent way by the S15 method. (Author)

  16. Thin Film CIGS Solar Cells, Photovoltaic Modules, and the Problems of Modeling

    Directory of Open Access Journals (Sweden)

    Antonino Parisi

    2013-01-01

    Full Text Available Starting from the results regarding a nonvacuum technique to fabricate CIGS thin films for solar cells by means of single-step electrodeposition, we focus on the methodological problems of modeling at cell structure and photovoltaic module levels. As a matter of fact, electrodeposition is known as a practical alternative to costly vacuum-based technologies for semiconductor processing in the photovoltaic device sector, but it can lead to quite different structural and electrical properties. For this reason, a greater effort is required to ensure that the perspectives of the electrical engineer and the material scientist are given an opportunity for a closer comparison and a common language. Derived parameters from ongoing experiments have been used for simulation with the different approaches, in order to develop a set of tools which can be used to put together modeling both at single cell structure and complete module levels.

  17. Five-group cytogenetic risk classification, monosomal karyotype, and outcome after hematopoietic cell transplantation for MDS or acute leukemia evolving from MDS

    Science.gov (United States)

    Scott, Bart L.; Fang, Min; Shulman, Howard M.; Gyurkocza, Boglarka; Myerson, David; Pagel, John M.; Platzbecker, Uwe; Ramakrishnan, Aravind; Radich, Jerald P.; Sandmaier, Brenda M.; Sorror, Mohamed; Stirewalt, Derek L.; Wilson, Wendy A.; Storb, Rainer; Appelbaum, Frederick R.; Gooley, Ted

    2012-01-01

    Clonal cytogenetic abnormalities are a major risk factor for relapse after hematopoietic cell transplantation (HCT) for myelodysplastic syndrome (MDS). We determined the impact of the recently established 5-group cytogenetic classification of MDS on outcome after HCT. Results were compared with the impact of the International Prognostic Scoring System (IPSS) 3 cytogenetic risk groups, and the additional effect of a monosomal karyotype was assessed. The study included data on 1007 patients, 1-75 years old (median 45 years), transplanted from related (n = 547) or unrelated (n = 460) donors. Various conditioning regimens were used, and marrow, peripheral blood, or cord blood served as stem cell source. Both IPSS and 5-group cytogenetic risk classifications were significantly associated with post-HCT relapse and mortality, but the 5-group classification discriminated more clearly among the lowest- and highest-risk patients. A monosomal karyotype tended to further increase the rates of relapse and mortality, even after considering the IPSS or 5-group classifications. In addition, the pathologic disease category correlated with both relapse and mortality. Mortality was also impacted by patient age, donor type, conditioning regimen, platelet count, and etiology of MDS. Although mortality declined significantly in recent years, novel strategies are needed to overcome the barrier of high-risk cytogenetics. PMID:22767498

  18. Usefulness of High-Frequency Ultrasound in the Classification of Histologic Subtypes of Primary Basal Cell Carcinoma.

    Science.gov (United States)

    Hernández-Ibáñez, C; Blazquez-Sánchez, N; Aguilar-Bernier, M; Fúnez-Liébana, R; Rivas-Ruiz, F; de Troya-Martín, M

    Incisional biopsy may not always provide a correct classification of histologic subtypes of basal cell carcinoma (BCC). High-frequency ultrasound (HFUS) imaging of the skin is useful for the diagnosis and management of this tumor. The main aim of this study was to compare the diagnostic value of HFUS compared with punch biopsy for the correct classification of histologic subtypes of primary BCC. We also analyzed the influence of tumor size and histologic subtype (single subtype vs. mixed) on the diagnostic yield of HFUS and punch biopsy. Retrospective observational study of primary BCCs treated by the Dermatology Department of Hospital Costa del Sol in Marbella, Spain, between october 2013 and may 2014. Surgical excision was preceded by HFUS imaging (Dermascan C © , 20-MHz linear probe) and a punch biopsy in all cases. We compared the overall diagnostic yield and accuracy (sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) of HFUS and punch biopsy against the gold standard (excisional biopsy with serial sections) for overall and subgroup results. We studied 156 cases. The overall diagnostic yield was 73.7% for HFUS (sensitivity, 74.5%; specificity, 73%) and 79.9% for punch biopsy (sensitivity, 76%; specificity, 82%). In the subgroup analyses, HFUS had a PPV of 93.3% for superficial BCC (vs. 92% for punch biopsy). In the analysis by tumor size, HFUS achieved an overall diagnostic yield of 70.4% for tumors measuring 40mm 2 or less and 77.3% for larger tumors; the NPV was 82% in both size groups. Punch biopsy performed better in the diagnosis of small lesions (overall diagnostic yield of 86.4% for lesions ≤40mm 2 vs. 72.6% for lesions >40mm 2 ). HFUS imaging was particularly useful for ruling out infiltrating BCCs, diagnosing simple, superficial BCCs, and correctly classifying BCCs larger than 40mm 2 . Copyright © 2016 AEDV. Publicado por Elsevier España, S.L.U. All rights reserved.

  19. Supervised Machine Learning for Classification of the Electrophysiological Effects of Chronotropic Drugs on Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes.

    Science.gov (United States)

    Heylman, Christopher; Datta, Rupsa; Sobrino, Agua; George, Steven; Gratton, Enrico

    2015-01-01

    Supervised machine learning can be used to predict which drugs human cardiomyocytes have been exposed to. Using electrophysiological data collected from human cardiomyocytes with known exposure to different drugs, a supervised machine learning algorithm can be trained to recognize and classify cells that have been exposed to an unknown drug. Furthermore, the learning algorithm provides information on the relative contribution of each data parameter to the overall classification. Probabilities and confidence in the accuracy of each classification may also be determined by the algorithm. In this study, the electrophysiological effects of β-adrenergic drugs, propranolol and isoproterenol, on cardiomyocytes derived from human induced pluripotent stem cells (hiPS-CM) were assessed. The electrophysiological data were collected using high temporal resolution 2-photon microscopy of voltage sensitive dyes as a reporter of membrane voltage. The results demonstrate the ability of our algorithm to accurately assess, classify, and predict hiPS-CM membrane depolarization following exposure to chronotropic drugs.

  20. Multi-level hp-finite cell method for embedded interface problems with application in biomechanics.

    Science.gov (United States)

    Elhaddad, Mohamed; Zander, Nils; Bog, Tino; Kudela, László; Kollmannsberger, Stefan; Kirschke, Jan; Baum, Thomas; Ruess, Martin; Rank, Ernst

    2017-12-19

    This work presents a numerical discretization technique for solving 3-dimensional material interface problems involving complex geometry without conforming mesh generation. The finite cell method (FCM), which is a high-order fictitious domain approach, is used for the numerical approximation of the solution without a boundary-conforming mesh. Weak discontinuities at material interfaces are resolved by using separate FCM meshes for each material sub-domain and weakly enforcing the interface conditions between the different meshes. Additionally, a recently developed hierarchical hp-refinement scheme is used to locally refine the FCM meshes to resolve singularities and local solution features at the interfaces. Thereby, higher convergence rates are achievable for nonsmooth problems. A series of numerical experiments with 2- and 3-dimensional benchmark problems is presented, showing that the proposed hp-refinement scheme in conjunction with the weak enforcement of the interface conditions leads to a significant improvement of the convergence rates, even in the presence of singularities. Finally, the proposed technique is applied to simulate a vertebra-implant model. The application showcases the method's potential as an accurate simulation tool for biomechanical problems involving complex geometry, and it demonstrates its flexibility in dealing with different types of geometric description. Copyright © 2017 John Wiley & Sons, Ltd.

  1. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-07

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

  2. Experience in local Glyciphon chemotherapy of basal cell carcinoma of the problem face areas

    Directory of Open Access Journals (Sweden)

    S. O. Podvyaznikov

    2017-01-01

    Full Text Available Basal cell carcinoma (BCC is the most common type of malignant skin tumors, characterized by selective localization on the head and neck. Currently there is a variety of treatment methods for this disease, but some of them are not feasible due to patients’ age, cancer localization, morphological type, size, or number of tumor lesions. In that respect, local chemotherapy of BCC, especially for the problem face areas, can serve as a good alternative. Clinical and experimental trials have shown a high treatment effect for 30 % Glyciphon ointment in patients with BCC. In this article we present successful examples of treatment of patients with BCC on the problem face areas using Glyciphon.

  3. Pattern classification for incomplete data

    OpenAIRE

    Gabrys, Bogdan

    2000-01-01

    The problem of pattern classification for inputs with missing values is considered. A general fuzzy min-max (GFMM) neural network utilising hyperbox fuzzy sets as a representation of data cluster prototypes is used. It is shown how a classification decisions can be carried out on a subspace of high dimensional input data. No substitution scheme for missing values is utilised. The result is a classification procedure that reduces a number of viable class alternatives on the basis of available ...

  4. Parent reported sleep problems in preschool children with sickle cell anemia and controls in East London.

    Science.gov (United States)

    Downes, Michelle; de Haan, Michelle; Kirkham, Fenella J; Telfer, Paul T

    2017-06-01

    Snoring and poor sleep may affect cognition, particularly in young children with chronic conditions. Parents of London preschoolers with sickle cell anemia (SCA; n = 22), matched controls (n = 24), and unselected typically developing (n = 142) preschoolers completed sleep questionnaires. Preschoolers with SCA had significantly more sleep problems when compared to matched controls and the larger population. Snoring occurred at least one to two nights a week for 79% of the SCA group. This is compared with 25% of matched controls and 33% of larger population. Randomized controlled trials to improve sleep in young children with SCA already at-risk for cognitive dysfunction should be considered. © 2016 Wiley Periodicals, Inc.

  5. Global Expression-Based Classification of Lymph Node Metastasis and Extracapsular Spread of Oral Tongue Squamous Cell Carcinoma

    Directory of Open Access Journals (Sweden)

    Xiaofeng Zhou

    2006-11-01

    Full Text Available Regional lymph node metastasis is a critical event in oral tongue squamous cell carcinoma (OTSCC progression. The identification of biomarkers associated with the metastatic process would provide critical prognostic information to facilitate clinical decision making for improved management of OTSCC patients. Global expressional profiles were obtained for 25 primary OTSCCs, where 11 cases showed lymph node metastasis (pN+ histologically and 14 cases were nonmetastatic (pN-. Seven of pN+ cases also exhibited extracapsular spread (ECS of metastatic nodes. Multiple expression indices were used to generate signature gene sets for pN+/- and ECS+/- cases. Selected genes from signature gene sets were validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR. The classification powers of these genes were then evaluated using a logistic model, receiver operating characteristic curve analysis, leave-oneout cross-validation. qRT-PCR validation data showed that differences at RNA levels are either statistically significant (P<.05 or suggestive (P< .1 for six of eight genes tested (BMP2, CTTN, EEF1A1, GTSE1, MMP9, EGFR for pN+/- cases, for five of eight genes tested (BMP2, CTTN, EEF1A1, MMP9, EGFR for ECS+/- cases. Logistic models with specific combinations of genes (CTTN+MMP9+EGFR for pN and CTTN+EEFIA1+MMP9 for ECS achieved perfect specificity and sensitivity. Leave-one-out cross-validation showed overall accuracy rates of 85% for both pN and ECS prediction models. Our results demonstrated that the pN and the ECS of OTSCCs can be predicted by gene expression analyses of primary tumors.

  6. Medical imbalanced data classification

    Directory of Open Access Journals (Sweden)

    Sara Belarouci

    2017-04-01

    Full Text Available In general, the imbalanced dataset is a problem often found in health applications. In medical data classification, we often face the imbalanced number of data samples where at least one of the classes constitutes only a very small minority of the data. In the same time, it represent a difficult problem in most of machine learning algorithms. There have been many works dealing with classification of imbalanced dataset. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS algorithm that penalizes errors of different samples with different weights and some rules of thumb to determine those weights. After the balancing phase, we apply the different techniques (Support Vector Machine [SVM], K- Nearest Neighbor [K-NN] and Multilayer perceptron [MLP] for the balanced datasets. We have also compared the obtained results before and after balancing method. We have obtained best results compared to literature with a classification accuracy of 100%.

  7. The study of electrochemical cell taught by problem-based learning

    Science.gov (United States)

    Srichaitung, Paisan

    2018-01-01

    According to the teaching activity of Chemistry, researcher found that students were not able to seek self knowledge even applied knowledge to their everyday life. Therefore, the researcher is interested in creating an activity to have students constructed their knowledge, science process skills, and can apply knowledge in their everyday life. The researcher presented form of teaching activity of electrochemical cell by using problem-based learning for Mathayom five students of Thai Christian School. The teaching activity focused on electron transfer in galvanic cell. In this activity, the researcher assigned students to design the electron transfer in galvanic cell using any solution that could light up the bulb. Then students were separated into a group of two, which were total seven groups. Each group of students searched the information about the electron transfer in galvanic cell from books, internet, or other sources of information. After students received concepts, or knowledge they searched for, Students designed and did the experiment. Finally, the students in each groups had twenty minutes to give a presentation in front of the classroom about the electron transfer in galvanic using any solution to light up the bulb with showing the experiment, and five minutes to answer their classmates' questions. Giving the presentation took four periods with total seven groups. After students finished their presentation, the researcher had students discussed and summarized the teaching activity's main idea of electron transfer in galvanic. Then, researcher observed students' behavior in each group found that 85.7 percentages of total students developed science process skills, and transferred their knowledge through presentation completely. When students done the post test, the researcher found that 92.85 percentages of total students were able to explain the concept of galvanic cell, described the preparation and the selection of experimental equipment. Furthermore

  8. Giant cell tumors of lower end of the radius : Problems and solutions

    Directory of Open Access Journals (Sweden)

    Dhammi I

    2005-01-01

    Full Text Available Background: Giant cell tumors of bone are aggressive, potentially malignant lesions. Juxtaarticular giant cell tumours of lower end radius are common and present a special problem of reconstruction after tumor excision. Out of the various reconstructive procedures described, use of nonvascularised fibular autograft has been widely used with satisfactory functional results. Methods: Sixteen patients with a mean age of 20.2 years, with either Campanacci grade II or III histologically proven giant cell tumours of lower end radius were treated with wide excision and reconstruction with ipsilateral nonvascularised proximal fibular autograft. Host graft junction was fixed with intramedullary nail in 12 cases and DCP in last 4 cases. Wrist ligament reconstruction and fixation of the head of fibula with carpal bones using K-wires and primary cancellous iliac crest grafting at graft host junction with DCP was done in last 2 cases. Results: The follow up ranges from 2 - 5 years (mean 3.5 years. At last follow up, the average combined range of motion was 110° with range varying from 60-125°. The average grip strength was 39% in comparison to the contralateral side (range 21-88%. The average union time was 8 months (range 4-12 months. Sound union occurred in 5 months, where DCPs were used. There were 5 nonunions, one resorption of graft, 10 wrist subluxations (2 painful, one recurrence, 3 superficial infections, one wound dehiscence and one amputation. There was no case of graft fracture, metastasis, death or significant donor site morbidity. A total of 10 secondary procedures were required. Conclusions: Enbloc resection of giant cell tumours of lower end radius is a widely accepted method. Reconstruction with nonvascularised fibular graft, internal fixation with DCP with primary corticocancellous bone grafting with transfixation of the fibular head and wrist ligament reconstruction minimizes the problem and gives satisfactory functional results.

  9. Some applications of particle-in-cell codes to problems of high intensity beams

    Energy Technology Data Exchange (ETDEWEB)

    Herrmannsfeldt, W.B.

    1986-04-01

    The technique of using the ''particle-in-cell'' method was developed in the field of plasma physics. Borrowed for problems of intense beams, it becomes an especially powerful tool because such problems frequently use single species ''plasmas'' and so pose a less severe requirement on the computer. Several problems are examined in which the PIC code method has been useful. The first is the classical Pierce gun in a transient or short pulse mode. Here the transverse beam optics are strongly affected by the time dependence of the current. The second is a study of high power klystrons searching for the source of an instability. The third is the high power rf source called the ''lasertron'' which is under development at SLAC. The interesting new development for the lasertron simulation is the introduction of a double gap output cavity for improved efficiency. The lasertron and klystron simulations are steady state solutions to rf problems with high-Q cavities. In order to limit the computation to a realistic time, these simulations use an external equivalent circuit which can communicate with the beam tunnel through ports placed at the locations of the rf cavities. Applications for electron beams generally require using a fully relativistic electromagnetic code such as MASK. In some applications, the computation can be speeded up by limiting the solution of the fields to the electrostatic conditions. This can be especially helpful if the degree of precision required demands very large numbers of macroparticles. An example of such an application is shown for a problem involving emittance growth for a high intensity beam for heavy ion fusion.

  10. Some applications of particle-in-cell codes to problems of high intensity beams

    International Nuclear Information System (INIS)

    Herrmannsfeldt, W.B.

    1986-04-01

    The technique of using the ''particle-in-cell'' method was developed in the field of plasma physics. Borrowed for problems of intense beams, it becomes an especially powerful tool because such problems frequently use single species ''plasmas'' and so pose a less severe requirement on the computer. Several problems are examined in which the PIC code method has been useful. The first is the classical Pierce gun in a transient or short pulse mode. Here the transverse beam optics are strongly affected by the time dependence of the current. The second is a study of high power klystrons searching for the source of an instability. The third is the high power rf source called the ''lasertron'' which is under development at SLAC. The interesting new development for the lasertron simulation is the introduction of a double gap output cavity for improved efficiency. The lasertron and klystron simulations are steady state solutions to rf problems with high-Q cavities. In order to limit the computation to a realistic time, these simulations use an external equivalent circuit which can communicate with the beam tunnel through ports placed at the locations of the rf cavities. Applications for electron beams generally require using a fully relativistic electromagnetic code such as MASK. In some applications, the computation can be speeded up by limiting the solution of the fields to the electrostatic conditions. This can be especially helpful if the degree of precision required demands very large numbers of macroparticles. An example of such an application is shown for a problem involving emittance growth for a high intensity beam for heavy ion fusion

  11. Single-Cell Behavior and Population Heterogeneity: Solving an Inverse Problem to Compute the Intrinsic Physiological State Functions

    OpenAIRE

    Spetsieris, Konstantinos; Zygourakis, Kyriacos

    2011-01-01

    The dynamics of isogenic cell populations can be described by cell population balance models that account for phenotypic heterogeneity. To utilize the predictive power of these models, however, we must know the rates of single-cell reaction and division and the bivariate partition probability density function. These three intrinsic physiological state (IPS) functions can be obtained by solving an inverse problem that requires knowledge of the phenotypic distributions for the overall cell popu...

  12. Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

    Directory of Open Access Journals (Sweden)

    David L Gibbs

    2017-06-01

    Full Text Available The Influence Maximization Problem (IMP aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

  13. Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle

    Science.gov (United States)

    Shmulevich, Ilya

    2017-01-01

    The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf. PMID:28628618

  14. Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

    Science.gov (United States)

    Gibbs, David L; Shmulevich, Ilya

    2017-06-01

    The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

  15. A microarray gene expressions with classification using extreme learning machine

    Directory of Open Access Journals (Sweden)

    Yasodha M.

    2015-01-01

    Full Text Available In the present scenario, one of the dangerous disease is cancer. It spreads through blood or lymph to other location of the body, it is a set of cells display uncontrolled growth, attack and destroy nearby tissues, and occasionally metastasis. In cancer diagnosis and molecular biology, a utilized effective tool is DNA microarrays. The dominance of this technique is recognized, so several open doubt arise regarding proper examination of microarray data. In the field of medical sciences, multicategory cancer classification plays very important role. The need for cancer classification has become essential because the number of cancer sufferers is increasing. In this research work, to overcome problems of multicategory cancer classification an improved Extreme Learning Machine (ELM classifier is used. It rectify problems faced by iterative learning methods such as local minima, improper learning rate and over fitting and the training completes with high speed.

  16. MYC/BCL2 Co-Expression Is a Stronger Prognostic Factor Compared With the Cell-of-Origin Classification in Primary CNS DLBCL.

    Science.gov (United States)

    Shi, Qian-Yun; Feng, Xiao; Bao, Wei; Ma, Jie; Lv, Jing-Huan; Wang, Xuan; Rao, Qiu; Shi, Qun-Li

    2017-11-01

    Primary central nervous system (CNS) diffuse large B-cell lymphoma (DLBCL) is a subtype of DLBCL with an unfavorable prognosis and a poor response to the treatment. As we know, DLBCL is stratified into germinal center B-cell (GCB)-like and activated B-cell (ABC)-like subtypes with different prognosis according to their gene-expression characteristics. In this study, we analyzed a case series of 77 patients with primary CNS DLBCL. A difference in prognosis of GCB-like and ABC-like subtypes was noticed, but no statistical significance was found. However, significant prognostic value of MYC/BCL2 co-expression was shown. The cases with MYC/BCL2 co-expression did not show any predominance of the 2 subtypes in our cases. Furthermore, patients with MYC/BCL2 co-expression had significantly worse overall survival for both cell of origin (COO) subtypes. We conjecture that MYC/BCL2 co-expression is associated with a poorer prognosis and is independent of COO classification. Moreover, the data suggest that MYC/BCL2 co-expression is superior to COO classification assessed by immunohistochemical analysis in patients with primary CNS DLBCL. © 2017 American Association of Neuropathologists, Inc. All rights reserved.

  17. [Modern problems of the application of sanitary regulations concerning sanitary protection zones and sanitary classification of enterprises, buildings and other facilities].

    Science.gov (United States)

    Lomtev, A Iu; Eremin, G B; Mozzhukhina, N A; Kombarova, M Iu; Mel'tser, A V; Giul'mamedov, É Iu

    2013-01-01

    In this paper there was performed an analysis of the application of sanitary norms and rules concerning sanitary protective zones and sanitary classification of enterprises, buildings and other facilities, including requirements for the sufficiency and accuracy of information in the performance of projects in sanitary protection zone (SPZ). There is presented an analysis of regulations that set requirements for implementation of mapping works in drafting the SPZ. The design of the SPZ was shown to be, on the one hand, the element of territorial planning subjects of the Russian Federation, on the other hand, the object of capital construction. The substantiations of requirements for graphic and text content, structure, and composition of data, sources of their obtaining, methods of data convergence are reported. There are revealed inconsistencies in Sanitary Regulations and Norms (SanPins) and in their relationship with the Town Planning and Land Code and other laws, and regulations adopted in their development.

  18. Minimum Error Entropy Classification

    CERN Document Server

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

    2013-01-01

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

  19. Clasificaciones de lesiones en pie diabético: Un problema no resuelto Classifications of injuries on diabetic foot: A non-solved problem

    Directory of Open Access Journals (Sweden)

    Héctor González de la Torre

    2012-06-01

    Full Text Available La necesidad de unificar criterios empleando un mismo lenguaje que favorezca la comunicación y el intercambio de conocimientos unido al desconocimiento existente en cuanto a las distintas formas de clasificación de las heridas crónicas, ha motivado a los autores para llevar a cabo esta revisión bibliográfica en la que se analizan quince sistemas de clasificación de lesiones de pie diabético y se abordan entre otros, aspectos como la metodología, facilidad de utilización, grado de conocimiento, utilidad de la información aportada y limitaciones de cada uno de ellos. Con ello, los autores no pretenden sino facilitar que los profesionales implicados en el cuidado de las úlceras diabéticas conozcan las distintas formas de estadiaje existentes en el pie diabético y en general en las heridas crónicas.The need of unify criterions using a same idiom contributing communication and interchanging knowledge together with ignorance existing in relation to the different ways of classificating chronic wounds is the reason for the authors to carry out this review analyzing fifteen classification systems in diabetic foot wounds dealing with subjects such as methodology, simplicity of use, grade of knowledge, usefulness of the information provided and limitations of each one. And so the authors pretend helping that those professionals taking care of diabetic foot ulcers can get to know different ways of staging diabetic foot wounds and chronic wounds in general.

  20. Maternal cell phone and cordless phone use during pregnancy and behaviour problems in 5-year-old children

    NARCIS (Netherlands)

    Guxens, M.; van Eijsden, M.; Vermeulen, R.; Loomans, E.M.; Vrijkotte, T.G.M.; Komhout, H.; van Strien, H.; Huss, A.

    2013-01-01

    Background A previous study found an association between maternal cell phone use during pregnancy and maternal-reported child behaviour problems at age 7. Together with cell phones, cordless phones represent the main exposure source of radiofrequency-electromagnetic fields to the head. Therefore, we

  1. Maternal cell phone and cordless phone use during pregnancy and behaviour problems in 5-year-old children

    NARCIS (Netherlands)

    Guxens, Mònica; van Eijsden, Manon; Vermeulen, Roel; Loomans, Eva; Vrijkotte, Tanja G. M.; Komhout, Hans; van Strien, Rob T.; Huss, Anke

    2013-01-01

    A previous study found an association between maternal cell phone use during pregnancy and maternal-reported child behaviour problems at age 7. Together with cell phones, cordless phones represent the main exposure source of radiofrequency-electromagnetic fields to the head. Therefore, we assessed

  2. Maternal cell phone and cordless phone use during pregnancy and behaviour problems in 5-year-old children

    NARCIS (Netherlands)

    Guxens, M.; van Eijsden, M.; Vermeulen, R.; Loomans, E.; Vrijkotte, T.G.M.; Komhout, H.; van Strien, R.T.; Huss, A.

    2013-01-01

    Background: A previous study found an association between maternal cell phone use during pregnancy and maternal-reported child behaviour problems at age 7. Together with cell phones, cordless phones represent the main exposure source of radiofrequency-electromagnetic fields to the head. Therefore,

  3. A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selection and classification.

    Science.gov (United States)

    Wei, Ning; Flaschel, Erwin; Friehs, Karl; Nattkemper, Tim Wilhelm

    2008-10-21

    Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnological applications. Conventional methods for extracting information about cell viability usually need reagents to be applied on the targeted cells. These reagent-based techniques are reliable and versatile, however, some of them might be invasive and even toxic to the target cells. In support of automated noninvasive assessment of cell viability, a machine vision system has been developed. This system is based on supervised learning technique. It learns from images of certain kinds of cell populations and trains some classifiers. These trained classifiers are then employed to evaluate the images of given cell populations obtained via dark field microscopy. Wavelet decomposition is performed on the cell images. Energy and entropy are computed for each wavelet subimage as features. A feature selection algorithm is implemented to achieve better performance. Correlation between the results from the machine vision system and commonly accepted gold standards becomes stronger if wavelet features are utilized. The best performance is achieved with a selected subset of wavelet features. The machine vision system based on dark field microscopy in conjugation with supervised machine learning and wavelet feature selection automates the cell viability assessment, and yields comparable results to commonly accepted methods. Wavelet features are found to be suitable to describe the discriminative properties of the live and dead cells in viability classification. According to the analysis, live cells exhibit morphologically more details and are intracellularly more organized than dead ones, which display more homogeneous and diffuse gray values throughout the cells. Feature selection increases the system's performance. The reason lies in the fact that feature selection plays a role of excluding redundant or misleading

  4. A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selection and classification

    Directory of Open Access Journals (Sweden)

    Friehs Karl

    2008-10-01

    Full Text Available Abstract Background Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnological applications. Conventional methods for extracting information about cell viability usually need reagents to be applied on the targeted cells. These reagent-based techniques are reliable and versatile, however, some of them might be invasive and even toxic to the target cells. In support of automated noninvasive assessment of cell viability, a machine vision system has been developed. Results This system is based on supervised learning technique. It learns from images of certain kinds of cell populations and trains some classifiers. These trained classifiers are then employed to evaluate the images of given cell populations obtained via dark field microscopy. Wavelet decomposition is performed on the cell images. Energy and entropy are computed for each wavelet subimage as features. A feature selection algorithm is implemented to achieve better performance. Correlation between the results from the machine vision system and commonly accepted gold standards becomes stronger if wavelet features are utilized. The best performance is achieved with a selected subset of wavelet features. Conclusion The machine vision system based on dark field microscopy in conjugation with supervised machine learning and wavelet feature selection automates the cell viability assessment, and yields comparable results to commonly accepted methods. Wavelet features are found to be suitable to describe the discriminative properties of the live and dead cells in viability classification. According to the analysis, live cells exhibit morphologically more details and are intracellularly more organized than dead ones, which display more homogeneous and diffuse gray values throughout the cells. Feature selection increases the system's performance. The reason lies in the fact that feature

  5. Maternal cell phone and cordless phone use during pregnancy and behaviour problems in 5-year-old children.

    Science.gov (United States)

    Guxens, Mònica; van Eijsden, Manon; Vermeulen, Roel; Loomans, Eva; Vrijkotte, Tanja G M; Komhout, Hans; van Strien, Rob T; Huss, Anke

    2013-05-01

    A previous study found an association between maternal cell phone use during pregnancy and maternal-reported child behaviour problems at age 7. Together with cell phones, cordless phones represent the main exposure source of radiofrequency-electromagnetic fields to the head. Therefore, we assessed the association between maternal cell phone and cordless phone use during pregnancy and teacher-reported and maternal-reported child behaviour problems at age 5. The study was embedded in the Amsterdam Born Children and their Development study, a population-based birth cohort study in Amsterdam, the Netherlands (2003-2004). Teachers and mothers reported child behaviour problems using the Strength and Difficulties Questionnaire at age 5. Maternal cell phone and cordless phone use during pregnancy was asked when children were 7 years old. A total of 2618 children were included. As compared to non-users, those exposed to prenatal cell phone use showed an increased but non-significant association of having teacher-reported overall behaviour problems, although without dose-response relationship with the number of calls (OR=2.12 (95% CI 0.95 to 4.74) for phone use were below 1 or close to unity. Associations of maternal cell phone and cordless phone use with maternal-reported overall behaviour problems remained non-significant. Non-significant associations were found for the specific behaviour problem subscales. Our results do not suggest that maternal cell phone or cordless phone use during pregnancy increases the odds of behaviour problems in their children.

  6. CP-CHARM: segmentation-free image classification made accessible.

    Science.gov (United States)

    Uhlmann, Virginie; Singh, Shantanu; Carpenter, Anne E

    2016-01-27

    Automated classification using machine learning often relies on features derived from segmenting individual objects, which can be difficult to automate. WND-CHARM is a previously developed classification algorithm in which features are computed on the whole image, thereby avoiding the need for segmentation. The algorithm obtained encouraging results but requires considerable computational expertise to execute. Furthermore, some benchmark sets have been shown to be subject to confounding artifacts that overestimate classification accuracy. We developed CP-CHARM, a user-friendly image-based classification algorithm inspired by WND-CHARM in (i) its ability to capture a wide variety of morphological aspects of the image, and (ii) the absence of requirement for segmentation. In order to make such an image-based classification method easily accessible to the biological research community, CP-CHARM relies on the widely-used open-source image analysis software CellProfiler for feature extraction. To validate our method, we reproduced WND-CHARM's results and ensured that CP-CHARM obtained comparable performance. We then successfully applied our approach on cell-based assay data and on tissue images. We designed these new training and test sets to reduce the effect of batch-related artifacts. The proposed method preserves the strengths of WND-CHARM - it extracts a wide variety of morphological features directly on whole images thereby avoiding the need for cell segmentation, but additionally, it makes the methods easily accessible for researchers without computational expertise by implementing them as a CellProfiler pipeline. It has been demonstrated to perform well on a wide range of bioimage classification problems, including on new datasets that have been carefully selected and annotated to minimize batch effects. This provides for the first time a realistic and reliable assessment of the whole image classification strategy.

  7. Static micro-array isolation, dynamic time series classification, capture and enumeration of spiked breast cancer cells in blood: the nanotube-CTC chip

    Science.gov (United States)

    Khosravi, Farhad; Trainor, Patrick J.; Lambert, Christopher; Kloecker, Goetz; Wickstrom, Eric; Rai, Shesh N.; Panchapakesan, Balaji

    2016-11-01

    We demonstrate the rapid and label-free capture of breast cancer cells spiked in blood using nanotube-antibody micro-arrays. 76-element single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (anti-EpCAM), Anti-human epithelial growth factor receptor 2 (anti-Her2) and non-specific IgG antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester. Following device functionalization, blood spiked with SKBR3, MCF7 and MCF10A cells (100/1000 cells per 5 μl per device, 170 elements totaling 0.85 ml of whole blood) were adsorbed on to the nanotube device arrays. Electrical signatures were recorded from each device to screen the samples for differences in interaction (specific or non-specific) between samples and devices. A zone classification scheme enabled the classification of all 170 elements in a single map. A kernel-based statistical classifier for the ‘liquid biopsy’ was developed to create a predictive model based on dynamic time warping series to classify device electrical signals that corresponded to plain blood (control) or SKBR3 spiked blood (case) on anti-Her2 functionalized devices with ˜90% sensitivity, and 90% specificity in capture of 1000 SKBR3 breast cancer cells in blood using anti-Her2 functionalized devices. Screened devices that gave positive electrical signatures were confirmed using optical/confocal microscopy to hold spiked cancer cells. Confocal microscopic analysis of devices that were classified to hold spiked blood based on their electrical signatures confirmed the presence of cancer cells through staining for DAPI (nuclei), cytokeratin (cancer cells) and CD45 (hematologic cells) with single cell sensitivity. We report 55%-100% cancer cell capture yield depending on the active device area for blood adsorption with mean of 62% (˜12 500 captured off 20 000 spiked cells in 0.1 ml

  8. Deep Learning for ECG Classification

    Science.gov (United States)

    Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

    2017-10-01

    The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

  9. Classification of nanoparticle diffusion processes in vital cells by a multifeature random forests approach: application to simulated data, darkfield, and confocal laser scanning microscopy

    Science.gov (United States)

    Wagner, Thorsten; Kroll, Alexandra; Wiemann, Martin; Lipinski, Hans-Gerd

    2016-04-01

    Darkfield and confocal laser scanning microscopy both allow for a simultaneous observation of live cells and single nanoparticles. Accordingly, a characterization of nanoparticle uptake and intracellular mobility appears possible within living cells. Single particle tracking makes it possible to characterize the particle and the surrounding cell. In case of free diffusion, the mean squared displacement for each trajectory of a nanoparticle can be measured which allows computing the corresponding diffusion coefficient and, if desired, converting it into the hydrodynamic diameter using the Stokes-Einstein equation and the viscosity of the fluid. However, within the more complex system of a cell's cytoplasm unrestrained diffusion is scarce and several other types of movements may occur. Thus, confined or anomalous diffusion (e.g. diffusion in porous media), active transport, and combinations thereof were described by several authors. To distinguish between these types of particle movement we developed an appropriate classification method, and simulated three types of particle motion in a 2D plane using a Monte Carlo approach: (1) normal diffusion, using random direction and step-length, (2) subdiffusion, using confinements like a reflective boundary with defined radius or reflective objects in the closer vicinity, and (3) superdiffusion, using a directed flow added to the normal diffusion. To simulate subdiffusion we devised a new method based on tracks of different length combined with equally probable obstacle interaction. Next we estimated the fractal dimension, elongation and the ratio of long-time / short-time diffusion coefficients. These features were used to train a random forests classification algorithm. The accuracy for simulated trajectories with 180 steps was 97% (95%-CI: 0.9481-0.9884). The balanced accuracy was 94%, 99% and 98% for normal-, sub- and superdiffusion, respectively. Nanoparticle tracking analysis was used with 100 nm polystyrene particles

  10. Some physical problems in biology: Aspects of the origin and structure of the first cell

    International Nuclear Information System (INIS)

    Chela Flores, J.

    1995-01-01

    A review is presented within the framework of the theory of evolution, after it has been extrapolated from the population level to the cellular and molecular levels. From Darwin's seminal and persuasive insight - the theory of common descent - we assume, with him, that ''probably all the organic beings which have ever lived on this earth have descended from some one primordial form, into which life was first breathed''. We are now aware that his primordial cell may have been a protocyanobacterium, but it has often been called 'a last universal ancestor', a 'breakthrough organism', or a 'progenote', a term introduced by Woese which has gained wide acceptance. Strictly speaking, in the 'intermediate period', ranging from the first living cell to the progenote, life may have evolved in the absence of significant diversity, effectively as a single phylum, incorporating organisms whose genetic systems were already based on DNA. Earlier still, prior to the encapsulation of nucleic acids in microspheres, evolution may already have been at work on RNA molecules (the 'RNA world'). This takes our discussion into the period of chemical evolution, a concept first put forward by Oparin, whose principal merit is to have formulated the underlying problem in clear scientific terms. This review does not attempt to be comprehensive. It is mainly devoted to the discussion of certain concepts that may have played a relevant role in the pathway that led to the origin and evolution of the progenote. We do not dwell on the main events of the intermediate period. The topic that we have chosen to include are: the origin of chirality of protein amino acids, the origin of translation, and the origin of the genome. We conclude with some comments on one further aspect of the evolutionary process - the development of biodiversity - by considering the origin of the first eukaryotic cell, an event which, according to the fossil record, may have preceded the evolutionary radiation in the early

  11. Classification of neocortical interneurons using affinity propagation

    Science.gov (United States)

    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 neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, 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. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits. PMID:24348339

  12. Classification of neocortical interneurons using affinity propagation

    Directory of Open Access Journals (Sweden)

    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.

  13. Cytogenetic risk grouping by the monosomal karyotype classification is superior in predicting the outcome of acute myeloid leukemia undergoing allogeneic stem cell transplantation in complete remission.

    Science.gov (United States)

    Hemmati, Philipp G; Schulze-Luckow, Anthea; Terwey, Theis H; le Coutre, Philipp; Vuong, Lam G; Dörken, Bernd; Arnold, Renate

    2014-02-01

    We retrospectively analyzed the impact of cytogenetic abnormalities grouped according to the monosomal karyotype (MK) classification or the Southwest Oncology/Eastern Cooperative Oncology Group (SWOG/ECOG) definition in 263 patients with acute myeloid leukemia (AML) who underwent allogeneic stem cell transplantation (alloSCT) in complete remission (CR) at our center. Risk grouping using the MK criteria shows a highly significant difference in 5-yr overall survival (OS) ranging between 67%, for the most favorable, and 32%, for the poorest risk group (P = 0.001). Although similarly precise in predicting OS, the MK scheme better separates patients with respect to relapse incidence as compared to the SWOG/ECOG grouping (P = 0.0001 vs. P = 0.01). Notably, patients displaying non-MK abnormalities (MK-) had a 5-yr relapse incidence identical to those cytogenetically normal (CN), that is 24%. Multivariate analysis revealed that the MK classification is an independent prognosticator and superior in predicting OS (hazard ratios, HR 3.74, P = 0.01) and relapse incidence (HR 3.74, P = 0.005) as compared to the SWOG/ECOG criteria. Finally, subgroup analysis revealed that the prognostic capacity of the MK classification is highly significant in patients treated with standard myeloablative conditioning prior to alloSCT (P = 0.0011 for OS, P = 0.0007 for relapse). In contrast, the MK grouping failed to predict OS or relapse incidence in patients treated with reduced intensity conditioning. Taken together, these results indicate that the MK classification is superior in predicting the overall outcome of patients with AML undergoing alloSCT in CR. Furthermore, our data suggest that the genetic risk profile of MK- and CN patients is mostly overlapping in this setting. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  14. How to solve mathematical problems

    CERN Document Server

    Wickelgren, Wayne A

    1995-01-01

    Seven problem-solving techniques include inference, classification of action sequences, subgoals, contradiction, working backward, relations between problems, and mathematical representation. Also, problems from mathematics, science, and engineering with complete solutions.

  15. High-Grade B-Cell Neoplasm with Surface Light Chain Restriction and Tdt Coexpression Evolved in a MYC-Rearranged Diffuse Large B-Cell Lymphoma: A Dilemma in Classification

    Directory of Open Access Journals (Sweden)

    Dina Sameh Soliman

    2017-01-01

    Full Text Available According to World Health Organization (WHO classification (2008, B-cell neoplasms are classified into precursor B-cell or a mature B-cell phenotype and this classification was also kept in the latest WHO revision (2016. We are reporting a male patient in his fifties, with tonsillar swelling diagnosed as diffuse large B-cell lymphoma (DLBCL, germinal center. He received 6 cycles of RCHOP and showed complete metabolic response. Two months later, he presented with severe CNS symptoms. Flow cytometry on bone marrow (BM showed infiltration by CD10-positive Kappa-restricted B-cells with loss of CD20 and CD19, and downregulation of CD79b. Moreover, the malignant population showed Tdt expression. BM Cytogenetics revealed t(8;14(q24;q32 within a complex karyotype. Retrospectively, MYC and Tdt immunostains performed on original diagnostic tissue and came negative for Tdt and positive for MYC. It has been rarely reported that mature B-cell neoplasms present with features of immaturity; however the significance of Tdt acquisition during disease course was not addressed before. What is unique in this case is that the emerging disease has acquired an immaturity marker while retaining some features of the original mature clone. No definitive WHO category would adopt high-grade neoplasms that exhibit significant overlapping features between mature and immature phenotypes.

  16. A multivariate insight into the in vitro antitumour screen database of the National Cancer Institute: classification of compounds, similarities among cell lines and the influence of molecular targets

    Science.gov (United States)

    Musumarra, Giuseppe; Condorelli, Daniele F.; Costa, Alessandro S.; Fichera, Maria

    2001-03-01

    A multivariate insight into the in vitro antitumour screen database of the NCI by means of the SIMCA package allows to propose hypotheses on the mechanism of action of novel anticancer compounds. As an example, the application of multivariate analysis to the NCI standard database provided clues to the classification of drugs whose mechanism is either unknown or controversial. Moreover, the influence of intrinsic biochemical cell line properties (molecular targets) on the sensitivity to drug treatment could be evaluated simultaneously for classes of compounds which act by the same mechanism. Interestingly, the present approach can also provide a correlation between the molecular targets and the therapeutical fingerprint of novel active compounds thus suggesting specific biochemical studies for the investigation of new mechanisms of drug action and resistance. The statistical approach reported here represents a valuable tool for handling the enormous data sets deriving from recent genome-wide investigations of gene expression in the NCI cell lines.

  17. Xenolog classification.

    Science.gov (United States)

    Darby, Charlotte A; Stolzer, Maureen; Ropp, Patrick J; Barker, Daniel; Durand, Dannie

    2017-03-01

    Orthology analysis is a fundamental tool in comparative genomics. Sophisticated methods have been developed to distinguish between orthologs and paralogs and to classify paralogs into subtypes depending on the duplication mechanism and timing, relative to speciation. However, no comparable framework exists for xenologs: gene pairs whose history, since their divergence, includes a horizontal transfer. Further, the diversity of gene pairs that meet this broad definition calls for classification of xenologs with similar properties into subtypes. We present a xenolog classification that uses phylogenetic reconciliation to assign each pair of genes to a class based on the event responsible for their divergence and the historical association between genes and species. Our classes distinguish between genes related through transfer alone and genes related through duplication and transfer. Further, they separate closely-related genes in distantly-related species from distantly-related genes in closely-related species. We present formal rules that assign gene pairs to specific xenolog classes, given a reconciled gene tree with an arbitrary number of duplications and transfers. These xenology classification rules have been implemented in software and tested on a collection of ∼13 000 prokaryotic gene families. In addition, we present a case study demonstrating the connection between xenolog classification and gene function prediction. The xenolog classification rules have been implemented in N otung 2.9, a freely available phylogenetic reconciliation software package. http://www.cs.cmu.edu/~durand/Notung . Gene trees are available at http://dx.doi.org/10.7488/ds/1503 . durand@cmu.edu. Supplementary data are available at Bioinformatics online.

  18. Transporter Classification Database (TCDB)

    Data.gov (United States)

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

  19. Tissue Classification

    DEFF Research Database (Denmark)

    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 now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification....... Although other methods exist, we concentrate on Bayesian modeling approaches, in which generative image models are constructed and subsequently ‘inverted’ to obtain automated segmentations. This general framework encompasses a large number of segmentation methods, including those implemented in widely used...

  20. Comparative Study of Classification Techniques on Breast Cancer FNA Biopsy Data

    Directory of Open Access Journals (Sweden)

    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.

  1. A comprehensive quadratic assignment problem for an integrated layout design of final assembly line and manufacturing feeder cells

    Directory of Open Access Journals (Sweden)

    Masoud Rabbani

    2017-04-01

    Full Text Available Assembly lines and cellular manufacturing systems (CMSs design have been widely used in the literature. However the integration of these manufacturing concepts is neglected in an environment where parts need to be assembled after production in different shops. In this paper, a comprehensive quadratic assignment problem is developed for the assignment of machines of each part manufacturing cell, sub-assembly tasks of each sub-assembly cell as well as the assignment of different cells and final assembly tasks within the shop floor in their relevant predetermined locations. A genetic algorithm (GA as well as a memetic algorithm (MA consisting of the proposed GA and Tabu search (TS algorithm are proposed and implemented on different size numerical examples. The obtained results show the efficiency of both algorithms to reach near optimal solutions compared to the optimal solution of small-sized problems.

  2. Combination of cytogenetic classification and MRD status correlates with outcome of autologous versus allogeneic stem cell transplantation in adults with primary acute myeloid leukemia in first remission.

    Science.gov (United States)

    Yao, Jianfeng; Zhang, Guixin; Liang, Chen; Li, Gang; Chen, Xin; Ma, Qiaoling; Zhai, Weihua; Yang, Donglin; He, Yi; Jiang, Erlie; Feng, Sizhou; Han, Mingzhe

    2017-04-01

    Both autologous and allogeneic stem cell transplantation (auto- and allo-SCT) are treatment choice for adults with acute myeloid leukemia (AML) after complete remission (CR). However, the decision-making remains controversial in some situations. To figure out the treatment choice, we retrospectively investigated 172 consecutive patients with primary AML who received auto- (n=46) or allo-SCT (n=126) from a single transplant center. Auto- and allo-SCT group demonstrated comparable overall survival (OS) and disease-free survival (DFS) (P=0.616, P=0.559, respectively). Cytogenetic classification and minimal residual disease (MRD) after one course of consolidation were identified as independent risk factors for DFS (hazard ratio (HR), 1.800; 95% CI, 1.172-2.763; P=0.007; HR, 2.042; 95%CI, 1.003-4.154; P=0.049; respectively). We subsequently found that auto- and allo-SCT offered comparable DFS to patients with favorable or intermediate risk and were tested MRD neg after one course of consolidation (P=0.270) otherwise auto-SCT were inferior due to increased risk of leukemia relapse. Our study indicated that the combination of cytogenetic classification and MRD monitoring correlated with outcome of auto- versus allo-SCT and might help the choice between the two types of SCT for adults with primary AML, which is of significance for patients with expected intermediate prognosis in the current scenario. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Classifications of track structures

    International Nuclear Information System (INIS)

    Paretzke, H.G.

    1984-01-01

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

  4. Does the Comprehensive International Classification of Functioning, Disability and Health (ICF) Core Set for Breast Cancer capture the problems in functioning treated by physiotherapists in women with breast cancer?

    Science.gov (United States)

    Glaessel, Andrea; Kirchberger, Inge; Stucki, Gerold; Cieza, Alarcos

    2011-03-01

    The Comprehensive International Classification of Functioning, Disability and Health (ICF) Core Set for Breast Cancer is an application of the ICF, and represents the typical spectrum of problems in functioning and contextual factors that may influence functioning of patients with breast cancer. The objective of this study was to examine the content validity of this ICF core set from the perspective of physiotherapists. Physiotherapists from around the world experienced in the treatment of patients with breast cancer were interviewed about patients' problems, patients' resources and environmental aspects that physiotherapists take care of in a three-round survey using the Delphi technique. The responses were linked to the ICF. The degree of agreement was calculated by means of the Kappa statistic. Physiotherapists experienced in breast cancer treatment. Fifty-nine physiotherapists from 19 countries named 769 problems treated by physiotherapists in patients with breast cancer. One hundred and sixty-six ICF categories were linked to these answers. Nineteen ICF categories reached >75% agreement among the physiotherapists but are not represented in the Comprehensive ICF Core Set for Breast Cancer. Ten concepts were linked to the not-yet-classified personal factors component. Eleven concepts are not covered by the ICF. The Kappa coefficient for the agreement between the two persons who performed the linking was 0.66 (95% bootstrapped confidence interval 0.63 to 0.68). The content validity of the Comprehensive ICF Core Set for Breast Cancer was largely supported by the physiotherapists. However, several issues were raised which were not covered and these need to be investigated further. Copyright © 2010 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  5. Single-cell behavior and population heterogeneity: solving an inverse problem to compute the intrinsic physiological state functions.

    Science.gov (United States)

    Spetsieris, Konstantinos; Zygourakis, Kyriacos

    2012-04-15

    The dynamics of isogenic cell populations can be described by cell population balance models that account for phenotypic heterogeneity. To utilize the predictive power of these models, however, we must know the rates of single-cell reaction and division and the bivariate partition probability density function. These three intrinsic physiological state (IPS) functions can be obtained by solving an inverse problem that requires knowledge of the phenotypic distributions for the overall cell population, the dividing cell subpopulation and the newborn cell subpopulation. We present here a robust computational procedure that can accurately estimate the IPS functions for heterogeneous cell populations. A detailed parametric analysis shows how the accuracy of the inverse solution is affected by discretization parameters, the type of non-parametric estimators used, the qualitative characteristics of phenotypic distributions and the unknown partitioning probability density function. The effect of finite sampling and measurement errors on the accuracy of the recovered IPS functions is also assessed. Finally, we apply the procedure to estimate the IPS functions of an E. coli population carrying an IPTG-inducible genetic toggle network. This study completes the development of an integrated experimental and computational framework that can become a powerful tool for quantifying single-cell behavior using measurements from heterogeneous cell populations. Copyright © 2011 Elsevier B.V. All rights reserved.

  6. Refined diagnostic criteria and classification of mast cell leukemia (MCL) and myelomastocytic leukemia (MML) : a consensus proposal

    NARCIS (Netherlands)

    Valent, P.; Sotlar, K.; Sperr, W. R.; Escribano, L.; Yavuz, S.; Reiter, A.; George, T. I.; Kluin-Nelemans, H. C.; Hermine, O.; Butterfield, J. H.; Hagglund, H.; Ustun, C.; Hornick, J. L.; Triggiani, M.; Radia, D.; Akin, C.; Hartmann, K.; Gotlib, J.; Schwartz, L. B.; Verstovsek, S.; Orfao, A.; Metcalfe, D. D.; Arock, M.; Horny, H. -P.

    Mast cell leukemia (MCL), the leukemic manifestation of systemic mastocytosis (SM), is characterized by leukemic expansion of immature mast cells (MCs) in the bone marrow (BM) and other internal organs; and a poor prognosis. In a subset of patients, circulating MCs are detectable. A major

  7. NEW CLASSIFICATION OF ECOPOLICES

    Directory of Open Access Journals (Sweden)

    VOROBYOV V. V.

    2016-09-01

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

  8. Positron Emission Tomography/Computed Tomography Assessment After Immunochemotherapy and Irradiation Using the Lugano Classification Criteria in the IELSG-26 Study of Primary Mediastinal B-Cell Lymphoma

    Energy Technology Data Exchange (ETDEWEB)

    Ceriani, Luca, E-mail: luca.ceriani@eoc.ch [Nuclear Medicine and PET-CT Center, Oncology Institute of Southern Switzerland, Bellinzona (Switzerland); Martelli, Maurizio [Department of Cellular Biotechnologies and Hematology, Sapienza University, Rome (Italy); Gospodarowicz, Maria K. [Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Ricardi, Umberto [Department of Oncology, University of Torino, Torino (Italy); Ferreri, Andrés J.M. [Unit of Lymphoid Malignancies, Department of Onco-Hematology, Istituto Di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milano (Italy); Chiappella, Annalisa [Hematology, Azienda Ospedaliera Universitaria Città della Salute e della Scienza, Torino (Italy); Stelitano, Caterina [Hematology, Azienda Ospedaliera Bianchi-Melacrino-Morelli, Reggio Calabria (Italy); Balzarotti, Monica [Hematology, IRCCS Humanitas Cancer Center, Rozzano, Milan (Italy); Cabrera, Maria E. [Hematology, Hospital del Salvador, Universidad de Chile, Santiago (Chile); Cunningham, David [Department of Medicine, The Royal Marsden National Health Service Foundation Trust, London and Surrey (United Kingdom); Guarini, Attilio [Hematology Unit, Istituto Nazionale Tumori Giovanni Paolo II IRCCS, Bari (Italy); Zinzani, Pier Luigi [Institute of Hematology and Medical Oncology, Policlinico S.Orsola-Malpighi, Bologna (Italy); Giovanella, Luca [Nuclear Medicine and PET-CT Center, Oncology Institute of Southern Switzerland, Bellinzona (Switzerland); Johnson, Peter W.M. [Cancer Research UK Centre, University of Southampton, Southampton (United Kingdom); Zucca, Emanuele [Oncology Department, Oncology Institute of Southern Switzerland, Bellinzona (Switzerland)

    2017-01-01

    Purpose: To assess the predictive value of {sup 18}F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) for disease recurrence after immunochemotherapy (R-CHT) and mediastinal irradiation (RT), using the recently published criteria of the Lugano classification to predict outcomes for patients with primary mediastinal large B-cell lymphoma. Methods and Materials: Among 125 patients prospectively enrolled in the IELSG-26 study, 88 were eligible for central review of PET/CT scans after completion of RT. Responses were evaluated using the 5-point Deauville scale at the end of induction R-CHT and after consolidation RT. According to the Lugano classification, a complete metabolic response (CMR) was defined by a Deauville score (DS) ≤3. Results: The CMR (DS1, -2, or -3) rate increased from 74% (65 patients) after R-CHT to 89% (78 patients) after consolidation RT. Among the 10 patients (11%) with persistently positive scans, the residual uptake after RT was slightly higher than the liver uptake in 6 patients (DS4; 7%) and markedly higher in 4 patients (DS5; 4%): these patients had a significantly poorer 5-year progression-free survival and overall survival. At a median follow-up of 60 months (range, 35-107 months), no patients with a CMR after RT have relapsed. Among the 10 patients who did not reach a CMR, 3 of the 4 patients (positive predictive value, 75%) with DS5 after RT had subsequent disease progression (within the RT volume in all cases) and died. All patients with DS4 had good outcomes without recurrence. Conclusions: All the patients obtaining a CMR defined as DS ≤3 remained progression-free at 5 years, confirming the excellent negative predictive value of the Lugano classification criteria in primary mediastinal large B-cell lymphoma patients. The few patients with DS4 also had an excellent outcome, suggesting that they do not necessarily require additional therapy, because the residual {sup 18}F-fluorodeoxyglucose uptake may

  9. Positron Emission Tomography/Computed Tomography Assessment After Immunochemotherapy and Irradiation Using the Lugano Classification Criteria in the IELSG-26 Study of Primary Mediastinal B-Cell Lymphoma.

    Science.gov (United States)

    Ceriani, Luca; Martelli, Maurizio; Gospodarowicz, Maria K; Ricardi, Umberto; Ferreri, Andrés J M; Chiappella, Annalisa; Stelitano, Caterina; Balzarotti, Monica; Cabrera, Maria E; Cunningham, David; Guarini, Attilio; Zinzani, Pier Luigi; Giovanella, Luca; Johnson, Peter W M; Zucca, Emanuele

    2017-01-01

    To assess the predictive value of 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) for disease recurrence after immunochemotherapy (R-CHT) and mediastinal irradiation (RT), using the recently published criteria of the Lugano classification to predict outcomes for patients with primary mediastinal large B-cell lymphoma. Among 125 patients prospectively enrolled in the IELSG-26 study, 88 were eligible for central review of PET/CT scans after completion of RT. Responses were evaluated using the 5-point Deauville scale at the end of induction R-CHT and after consolidation RT. According to the Lugano classification, a complete metabolic response (CMR) was defined by a Deauville score (DS) ≤3. The CMR (DS1, -2, or -3) rate increased from 74% (65 patients) after R-CHT to 89% (78 patients) after consolidation RT. Among the 10 patients (11%) with persistently positive scans, the residual uptake after RT was slightly higher than the liver uptake in 6 patients (DS4; 7%) and markedly higher in 4 patients (DS5; 4%): these patients had a significantly poorer 5-year progression-free survival and overall survival. At a median follow-up of 60 months (range, 35-107 months), no patients with a CMR after RT have relapsed. Among the 10 patients who did not reach a CMR, 3 of the 4 patients (positive predictive value, 75%) with DS5 after RT had subsequent disease progression (within the RT volume in all cases) and died. All patients with DS4 had good outcomes without recurrence. All the patients obtaining a CMR defined as DS ≤3 remained progression-free at 5 years, confirming the excellent negative predictive value of the Lugano classification criteria in primary mediastinal large B-cell lymphoma patients. The few patients with DS4 also had an excellent outcome, suggesting that they do not necessarily require additional therapy, because the residual 18 F-fluorodeoxyglucose uptake may not reflect persistent lymphoma. Copyright © 2016 Elsevier Inc

  10. Positron Emission Tomography/Computed Tomography Assessment After Immunochemotherapy and Irradiation Using the Lugano Classification Criteria in the IELSG-26 Study of Primary Mediastinal B-Cell Lymphoma

    International Nuclear Information System (INIS)

    Ceriani, Luca; Martelli, Maurizio; Gospodarowicz, Maria K.; Ricardi, Umberto; Ferreri, Andrés J.M.; Chiappella, Annalisa; Stelitano, Caterina; Balzarotti, Monica; Cabrera, Maria E.; Cunningham, David; Guarini, Attilio; Zinzani, Pier Luigi; Giovanella, Luca; Johnson, Peter W.M.; Zucca, Emanuele

    2017-01-01

    Purpose: To assess the predictive value of 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) for disease recurrence after immunochemotherapy (R-CHT) and mediastinal irradiation (RT), using the recently published criteria of the Lugano classification to predict outcomes for patients with primary mediastinal large B-cell lymphoma. Methods and Materials: Among 125 patients prospectively enrolled in the IELSG-26 study, 88 were eligible for central review of PET/CT scans after completion of RT. Responses were evaluated using the 5-point Deauville scale at the end of induction R-CHT and after consolidation RT. According to the Lugano classification, a complete metabolic response (CMR) was defined by a Deauville score (DS) ≤3. Results: The CMR (DS1, -2, or -3) rate increased from 74% (65 patients) after R-CHT to 89% (78 patients) after consolidation RT. Among the 10 patients (11%) with persistently positive scans, the residual uptake after RT was slightly higher than the liver uptake in 6 patients (DS4; 7%) and markedly higher in 4 patients (DS5; 4%): these patients had a significantly poorer 5-year progression-free survival and overall survival. At a median follow-up of 60 months (range, 35-107 months), no patients with a CMR after RT have relapsed. Among the 10 patients who did not reach a CMR, 3 of the 4 patients (positive predictive value, 75%) with DS5 after RT had subsequent disease progression (within the RT volume in all cases) and died. All patients with DS4 had good outcomes without recurrence. Conclusions: All the patients obtaining a CMR defined as DS ≤3 remained progression-free at 5 years, confirming the excellent negative predictive value of the Lugano classification criteria in primary mediastinal large B-cell lymphoma patients. The few patients with DS4 also had an excellent outcome, suggesting that they do not necessarily require additional therapy, because the residual 18 F-fluorodeoxyglucose uptake may not

  11. GA Based Optimal Feature Extraction Method for Functional Data Classification

    OpenAIRE

    Jun Wan; Zehua Chen; Yingwu Chen; Zhidong Bai

    2010-01-01

    Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper...

  12. Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach

    OpenAIRE

    Yamamoto, Yoichiro; Saito, Akira; Tateishi, Ayako; Shimojo, Hisashi; Kanno, Hiroyuki; Tsuchiya, Shinichi; Ito, Ken-ichi; Cosatto, Eric; Graf, Hans Peter; Moraleda, Rodrigo R.; Eils, Roland; Grabe, Niels

    2017-01-01

    Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade du...

  13. A Simple New Classification for Diabetic Foot Ulcers

    OpenAIRE

    C Jain, Amit Kumar

    2015-01-01

    AbstractGangrene, infections like abscesses and ulcers are some of the common diabetic foot complications. Of all these, diabetic foot ulcers pose a major public health problem. Around 80% of all the lower limb amputations are preceded by a foot ulcer. There are various classifications for diabetic foot ulcers out of which the two commonly used classifications are Wagner’s ulcer classification and the classification of University of Texas. The author proposes another simple new classification...

  14. Problems and potentialities of cultured plant cells in retrospect and prospect

    Science.gov (United States)

    Steward, F. C.; Krikorian, A. D.

    1979-01-01

    The past, present and expected future accomplishments and limitations of plant cell and tissue culture are reviewed. Consideration is given to the pioneering insights of Haberlandt in 1902, the development of culture techniques, and past work on cell division, cell and tissue growth and development, somatic embryogenesis, and metabolism and respiration. Current activity in culture media and technique development for plant regions, organs, tissues, cells, protoplasts, organelles and embryos, totipotency, somatic embryogenesis and clonal propagation under normal and space conditions, biochemical potentialities, and genetic engineering is surveyed. Prospects for the investigation of the induced control of somatic cell division, the division of isolated protoplasts, the improvement of haploid cell cultures, liquid cultures for somatic embryogenesis, and the genetic control of development are outlined.

  15. A Sokhotski-Plemelj problem related to a renewable T-cell

    African Journals Online (AJOL)

    2005-08-08

    Aug 8, 2005 ... dar (1970)). In this paper we consider a T-cell, subjected to random inspections and perfect repair. Note that our T-cell is less general with regard to the structure of the e-system presented by Dieulle (2002) and Mazumdar (1970). On the other hand, the statistical structure of our T-cell is less restrictive, since ...

  16. An Old Idea Tackling a New Problem: Targeted Toxins Specific for Cancer Stem Cells

    Directory of Open Access Journals (Sweden)

    Daniel A. Vallera

    2013-01-01

    Full Text Available Targeting and killing specific cells discriminately has been the goal of targeted therapy dating back to the era of Paul Ehrlich. The discovery of cancer stem cells has caused a paradigm shift within the cancer field and provided an opportunity to use targeted therapies such as targeted toxins to bind and kill these cells selectively. A number of targeted toxins have been developed against recently identified cancer stem cell markers. In this review we discuss the development and current status of these exciting novel drugs and their potential use to combat drug-refractory relapse.

  17. Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach

    Science.gov (United States)

    Yamamoto, Yoichiro; Saito, Akira; Tateishi, Ayako; Shimojo, Hisashi; Kanno, Hiroyuki; Tsuchiya, Shinichi; Ito, Ken-ichi; Cosatto, Eric; Graf, Hans Peter; Moraleda, Rodrigo R.; Eils, Roland; Grabe, Niels

    2017-01-01

    Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade ductal carcinoma in situ (DCIS). Using a machine learning system, we succeeded in classifying the four histological types with 90.9% accuracy. Electron microscopy observations suggested that the activity of typical myoepithelial cells in DCIS was lowered. Through these observations as well as meta-analytic database analyses, we developed a paracrine cross-talk-based biological mechanism of DCIS progressing to invasive cancer. Our observations support novel approaches in clinical computational diagnostics as well as in therapy development against progression. PMID:28440283

  18. Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.

    Science.gov (United States)

    Yamamoto, Yoichiro; Saito, Akira; Tateishi, Ayako; Shimojo, Hisashi; Kanno, Hiroyuki; Tsuchiya, Shinichi; Ito, Ken-Ichi; Cosatto, Eric; Graf, Hans Peter; Moraleda, Rodrigo R; Eils, Roland; Grabe, Niels

    2017-04-25

    Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade ductal carcinoma in situ (DCIS). Using a machine learning system, we succeeded in classifying the four histological types with 90.9% accuracy. Electron microscopy observations suggested that the activity of typical myoepithelial cells in DCIS was lowered. Through these observations as well as meta-analytic database analyses, we developed a paracrine cross-talk-based biological mechanism of DCIS progressing to invasive cancer. Our observations support novel approaches in clinical computational diagnostics as well as in therapy development against progression.

  19. Density Based Support Vector Machines for Classification

    OpenAIRE

    Zahra Nazari; Dongshik Kang

    2015-01-01

    Support Vector Machines (SVM) is the most successful algorithm for classification problems. SVM learns the decision boundary from two classes (for Binary Classification) of training points. However, sometimes there are some less meaningful samples amongst training points, which are corrupted by noises or misplaced in wrong side, called outliers. These outliers are affecting on margin and classification performance, and machine should better to discard them. SVM as a popular and widely used cl...

  20. Effective Exchange Rate Classifications and Growth

    OpenAIRE

    Justin M. Dubas; Byung-Joo Lee; Nelson C. Mark

    2005-01-01

    We propose an econometric procedure for obtaining de facto exchange rate regime classifications which we apply to study the relationship between exchange rate regimes and economic growth. Our classification method models the de jure regimes as outcomes of a multinomial logit choice problem conditional on the volatility of a country's effective exchange rate, a bilateral exchange rate and international reserves. An `effective' de facto exchange rate regime classification is then obtained by as...

  1. Classification of Lactococcus lactis cell envelope proteinase based on gene sequencing, peptides formed after hydrolysis of milk, and computer modeling

    DEFF Research Database (Denmark)

    Børsting, Mette Winther; Qvist, K.B.; Brockmann, E.

    2015-01-01

    Lactococcus lactis strains depend on a proteolytic system for growth in milk to release essential AA from casein. The cleavage specificities of the cell envelope proteinase (CEP) can vary between strains and environments and whether the enzyme is released or bound to the cell wall. Thirty-eight Lc....... lactis strains were grouped according to their CEP AA sequences and according to identified peptides after hydrolysis of milk. Finally, AA positions in the substrate binding region were suggested by the use of a new CEP template based on Streptococcus C5a CEP. Aligning the CEP AA sequences of 38 strains...

  2. Problem-Based Test: Replication of Mitochondrial DNA during the Cell Cycle

    Science.gov (United States)

    Setalo, Gyorgy, Jr.

    2013-01-01

    Terms to be familiar with before you start to solve the test: cell cycle, generation time, S-phase, cell culture synchronization, isotopic pulse-chase labeling, density labeling, equilibrium density-gradient centrifugation, buoyant density, rate-zonal centrifugation, nucleoside, nucleotide, kinase enzymes, polymerization of nucleic acids,…

  3. Segmentation and Classification of Bone Marrow Cells Images Using Contextual Information for Medical Diagnosis of Acute Leukemias

    OpenAIRE

    Reta, Carolina; Altamirano, Leopoldo; Gonzalez, Jesus A.; Diaz-Hernandez, Raquel; Peregrina, Hayde; Olmos, Ivan; Alonso, Jose E.; Lobato, Ruben

    2015-01-01

    Morphological identification of acute leukemia is a powerful tool used by hematologists to determine the family of such a disease. In some cases, experienced physicians are even able to determine the leukemia subtype of the sample. However, the identification process may have error rates up to 40% (when classifying acute leukemia subtypes) depending on the physician's experience and the sample quality. This problem raises the need to create automatic tools that provide hematologists with a se...

  4. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

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

    Monitoring a complex process often involves keeping an eye on hundreds or thousands of sensors to determine whether or not the process is under control. We have been working with dynamic data from an oil production facility in the North sea, where unstable situations should be identified as soon...... as 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 the process as well as modeling dependences between attributes....

  5. The classification problem for von Neumann factors

    DEFF Research Database (Denmark)

    Sasyk, R.; Törnquist, Asger Dag

    2009-01-01

    We prove that it is not possible to classify separable von Neumann factors of types II, II or III, 0 ≤ λ ≤ 1, up to isomorphism by a Borel measurable assignment of "countable structures" as invariants. In particular the isomorphism relation of type II factors is not smooth. We also prove...... that the isomorphism relation for von Neumann II factors is analytic, but is not Borel....

  6. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  7. Optimal ABC inventory classification using interval programming

    Science.gov (United States)

    Rezaei, Jafar; Salimi, Negin

    2015-08-01

    Inventory classification is one of the most important activities in inventory management, whereby inventories are classified into three or more classes. Several inventory classifications have been proposed in the literature, almost all of which have two main shortcomings in common. That is, the previous methods mainly rely on an expert opinion to derive the importance of the classification criteria which results in subjective classification, and they need precise item parameters before implementing the classification. While the problem has been predominantly considered as a multi-criteria, we examine the problem from a different perspective, proposing a novel optimisation model for ABC inventory classification in the form of an interval programming problem. The proposed interval programming model has two important features compared to the existing methods: it provides optimal results instead of an expert-based classification and it does not require precise values of item parameters, which are not almost always available before classification. Finally, by illustrating the proposed classification model in the form of numerical example, conclusion and suggestions for future works are presented.

  8. Gender, Race, and Survival: A Study in Non-Small-Cell Lung Cancer Brain Metastases Patients Utilizing the Radiation Therapy Oncology Group Recursive Partitioning Analysis Classification

    International Nuclear Information System (INIS)

    Videtic, Gregory M.M.; Reddy, Chandana A.; Chao, Samuel T.; Rice, Thomas W.; Adelstein, David J.; Barnett, Gene H.; Mekhail, Tarek M.; Vogelbaum, Michael A.; Suh, John H.

    2009-01-01

    Purpose: To explore whether gender and race influence survival in non-small-cell lung cancer (NSCLC) in patients with brain metastases, using our large single-institution brain tumor database and the Radiation Therapy Oncology Group recursive partitioning analysis (RPA) brain metastases classification. Methods and materials: A retrospective review of a single-institution brain metastasis database for the interval January 1982 to September 2004 yielded 835 NSCLC patients with brain metastases for analysis. Patient subsets based on combinations of gender, race, and RPA class were then analyzed for survival differences. Results: Median follow-up was 5.4 months (range, 0-122.9 months). There were 485 male patients (M) (58.4%) and 346 female patients (F) (41.6%). Of the 828 evaluable patients (99%), 143 (17%) were black/African American (B) and 685 (83%) were white/Caucasian (W). Median survival time (MST) from time of brain metastasis diagnosis for all patients was 5.8 months. Median survival time by gender (F vs. M) and race (W vs. B) was 6.3 months vs. 5.5 months (p = 0.013) and 6.0 months vs. 5.2 months (p = 0.08), respectively. For patients stratified by RPA class, gender, and race, MST significantly favored BFs over BMs in Class II: 11.2 months vs. 4.6 months (p = 0.021). On multivariable analysis, significant variables were gender (p = 0.041, relative risk [RR] 0.83) and RPA class (p < 0.0001, RR 0.28 for I vs. III; p < 0.0001, RR 0.51 for II vs. III) but not race. Conclusions: Gender significantly influences NSCLC brain metastasis survival. Race trended to significance in overall survival but was not significant on multivariable analysis. Multivariable analysis identified gender and RPA classification as significant variables with respect to survival.

  9. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

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

  10. Classification using Bayesian neural nets

    NARCIS (Netherlands)

    J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)

    1995-01-01

    textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to

  11. Data Augmentation for Plant Classification

    NARCIS (Netherlands)

    Pawara, Pornntiwa; Okafor, Emmanuel; Schomaker, Lambertus; Wiering, Marco

    2017-01-01

    Data augmentation plays a crucial role in increasing the number of training images, which often aids to improve classification performances of deep learning techniques for computer vision problems. In this paper, we employ the deep learning framework and determine the effects of several

  12. INVENTORY CLASSIFICATION WITH ABC ANALYSIS

    OpenAIRE

    Kıyak, Erkan; Timuş, Oğuz Han; Karayel, Mehmet

    2015-01-01

    For a substantial organization, managing the expansive inventory is a serious problem. One of the methods to solve this problem used widely is classifying the inventory according to some criteria and managing inventory according to this classisifation. In this study, ABC classification methods are researched and Ng's model, which is one of the most widely used, selected for further investigation. An illustrative example is presented to show the usability of the Ng's method.

  13. Sleep Problem Risk for Adolescents With Sickle Cell Disease: Sociodemographic, Physical, and Disease-related Correlates.

    Science.gov (United States)

    Valrie, Cecelia R; Trout, Krystal L; Bond, Kayzandra E; Ladd, Rebecca J; Huber, Nichelle L; Alston, Kristen J; Sufrinko, Alicia M; Everhart, Erik; Fuh, Beng R

    2018-03-01

    The aims of the current study were to investigate whether SCD incurs an additional risk for poor sleep over and above the influence of sociodemographic factors (ie, race and sex) during adolescence, and to explore the relationships between sociodemographic, physical (ie, age and pubertal status), and disease-related factors (ie, SCD genotype and hydroxyurea use) on sleep problem risk during adolescence. Black adolescents (age, 12 to 17 y) with SCD (n=53) were recruited from regional pediatric SCD clinics in the southeast and a sample of healthy black adolescents (n=160) were recruited from middle and high schools. Regression analyses indicated that SCD was uniquely related to sleeping more, and worse sleep quality over and above the influence of sociodemographic factors. Having a more severe SCD genotype was related to worse sleep quality and higher pubertal status was related to sleeping longer during the week. Results indicate the need for systematic assessments of sleep problems, with more a focus on youth with more severe genotypes and higher pubertal status. Future research should focus on characterizing trajectories of sleep problems in this population, identifying key risk factors, and elucidating mechanisms linking risk factors to sleep problem risk to aid in tailoring interventions for this population.

  14. Hazard classification methodology

    International Nuclear Information System (INIS)

    Brereton, S.J.

    1996-01-01

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

  15. Representation learning for cross-modality classification

    NARCIS (Netherlands)

    G. van Tulder (Gijs); M. de Bruijne (Marleen)

    2017-01-01

    textabstractDifferences in scanning parameters or modalities can complicate image analysis based on supervised classification. This paper presents two representation learning approaches, based on autoencoders, that address this problem by learning representations that are similar across domains.

  16. High throughput assessment of cells and tissues: Bayesian classification of spectral metrics from infrared vibrational spectroscopic imaging data.

    Science.gov (United States)

    Bhargava, Rohit; Fernandez, Daniel C; Hewitt, Stephen M; Levin, Ira W

    2006-07-01

    Vibrational spectroscopy allows a visualization of tissue constituents based on intrinsic chemical composition and provides a potential route to obtaining diagnostic markers of diseases. Characterizations utilizing infrared vibrational spectroscopy, in particular, are conventionally low throughput in data acquisition, generally lacking in spatial resolution with the resulting data requiring intensive numerical computations to extract information. These factors impair the ability of infrared spectroscopic measurements to represent accurately the spatial heterogeneity in tissue, to incorporate robustly the diversity introduced by patient cohorts or preparative artifacts and to validate developed protocols in large population studies. In this manuscript, we demonstrate a combination of Fourier transform infrared (FTIR) spectroscopic imaging, tissue microarrays (TMAs) and fast numerical analysis as a paradigm for the rapid analysis, development and validation of high throughput spectroscopic characterization protocols. We provide an extended description of the data treatment algorithm and a discussion of various factors that may influence decision-making using this approach. Finally, a number of prostate tissue biopsies, arranged in an array modality, are employed to examine the efficacy of this approach in histologic recognition of epithelial cell polarization in patients displaying a variety of normal, malignant and hyperplastic conditions. An index of epithelial cell polarization, derived from a combined spectral and morphological analysis, is determined to be a potentially useful diagnostic marker.

  17. Stem cell therapy for joint problems using the horse as a clinically relevant animal model

    DEFF Research Database (Denmark)

    Koch, Thomas Gadegaard; Betts, Dean H.

    2007-01-01

    of the developmental biology of synovial joints and their pathologies. Before human clinical trials are undertaken, stem cell-based therapies for non-life-threatening disorders should be evaluated for their safety and efficacy using animal models of spontaneous disease and not solely by the existing laboratory models...... of experimentally induced lesions. The horse lends itself as a good animal model of spontaneous joint disorders that are clinically relevant to similar human disorders. Equine stem cell and tissue engineering studies may be financially feasible to principal investigators and small biotechnology companies...

  18. Problem-Solving Test: Analysis of DNA Damage Recognizing Proteins in Yeast and Human Cells

    Science.gov (United States)

    Szeberenyi, Jozsef

    2013-01-01

    The experiment described in this test was aimed at identifying DNA repair proteins in human and yeast cells. Terms to be familiar with before you start to solve the test: DNA repair, germline mutation, somatic mutation, inherited disease, cancer, restriction endonuclease, radioactive labeling, [alpha-[superscript 32]P]ATP, [gamma-[superscript…

  19. Immaturity of human stem-cell-derived cardiomyocytes in culture: fatal flaw or soluble problem?

    NARCIS (Netherlands)

    Veerman, Christiaan C.; Kosmidis, Georgios; Mummery, Christine L.; Casini, Simona; Verkerk, Arie O.; Bellin, Milena

    2015-01-01

    Cardiomyocytes from human pluripotent stem cells (hPSC-CMs) are increasingly used to model cardiac disease, test drug efficacy and for safety pharmacology. Nevertheless, a major hurdle to more extensive use is their immaturity and similarity to fetal rather than adult cardiomyocytes. Here, we

  20. A multi-objective procedure for labour assignments and grouping in capacitated cell formation problems

    NARCIS (Netherlands)

    Suresh, NC; Slomp, J

    2001-01-01

    A hierarchical methodology for the design of manufacturing cells is proposed, which includes labour-grouping considerations in addition to part-machine grouping. It is empirically driven and designed for an interactive decision environment, with an emphasis on fast execution times. The method

  1. Characterizing the DNA Damage Response by Cell Tracking Algorithms and Cell Features Classification Using High-Content Time-Lapse Analysis.

    Directory of Open Access Journals (Sweden)

    Walter Georgescu

    Full Text Available Traditionally, the kinetics of DNA repair have been estimated using immunocytochemistry by labeling proteins involved in the DNA damage response (DDR with fluorescent markers in a fixed cell assay. However, detailed knowledge of DDR dynamics across multiple cell generations cannot be obtained using a limited number of fixed cell time-points. Here we report on the dynamics of 53BP1 radiation induced foci (RIF across multiple cell generations using live cell imaging of non-malignant human mammary epithelial cells (MCF10A expressing histone H2B-GFP and the DNA repair protein 53BP1-mCherry. Using automatic extraction of RIF imaging features and linear programming techniques, we were able to characterize detailed RIF kinetics for 24 hours before and 24 hours after exposure to low and high doses of ionizing radiation. High-content-analysis at the single cell level over hundreds of cells allows us to quantify precisely the dose dependence of 53BP1 protein production, RIF nuclear localization and RIF movement after exposure to X-ray. Using elastic registration techniques based on the nuclear pattern of individual cells, we could describe the motion of individual RIF precisely within the nucleus. We show that DNA repair occurs in a limited number of large domains, within which multiple small RIFs form, merge and/or resolve with random motion following normal diffusion law. Large foci formation is shown to be mainly happening through the merging of smaller RIF rather than through growth of an individual focus. We estimate repair domain sizes of 7.5 to 11 µm2 with a maximum number of ~15 domains per MCF10A cell. This work also highlights DDR which are specific to doses larger than 1 Gy such as rapid 53BP1 protein increase in the nucleus and foci diffusion rates that are significantly faster than for spontaneous foci movement. We hypothesize that RIF merging reflects a "stressed" DNA repair process that has been taken outside physiological conditions when

  2. HIV classification using coalescent theory

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Ming [Los Alamos National Laboratory; Letiner, Thomas K [Los Alamos National Laboratory; Korber, Bette T [Los Alamos National Laboratory

    2008-01-01

    Algorithms for subtype classification and breakpoint detection of HIV-I sequences are based on a classification system of HIV-l. Hence, their quality highly depend on this system. Due to the history of creation of the current HIV-I nomenclature, the current one contains inconsistencies like: The phylogenetic distance between the subtype B and D is remarkably small compared with other pairs of subtypes. In fact, it is more like the distance of a pair of subsubtypes Robertson et al. (2000); Subtypes E and I do not exist any more since they were discovered to be composed of recombinants Robertson et al. (2000); It is currently discussed whether -- instead of CRF02 being a recombinant of subtype A and G -- subtype G should be designated as a circulating recombination form (CRF) nd CRF02 as a subtype Abecasis et al. (2007); There are 8 complete and over 400 partial HIV genomes in the LANL-database which belong neither to a subtype nor to a CRF (denoted by U). Moreover, the current classification system is somehow arbitrary like all complex classification systems that were created manually. To this end, it is desirable to deduce the classification system of HIV systematically by an algorithm. Of course, this problem is not restricted to HIV, but applies to all fast mutating and recombining viruses. Our work addresses the simpler subproblem to score classifications of given input sequences of some virus species (classification denotes a partition of the input sequences in several subtypes and CRFs). To this end, we reconstruct ancestral recombination graphs (ARG) of the input sequences under restrictions determined by the given classification. These restritions are imposed in order to ensure that the reconstructed ARGs do not contradict the classification under consideration. Then, we find the ARG with maximal probability by means of Markov Chain Monte Carlo methods. The probability of the most probable ARG is interpreted as a score for the classification. To our

  3. Alloimmunization to red cells in thalassemics: emerging problem and future strategies.

    Science.gov (United States)

    Gupta, Richa; Singh, Deepak Kumar; Singh, Bharat; Rusia, Usha

    2011-10-01

    To evaluate the magnitude of red cell alloimmunization in regularly transfused patients with thalassemia major and analyse factors responsible for development of antibodies. This cross sectional study was conducted on 116 thalassemics receiving regular transfusions. All the patients underwent antibody screening. Patients with positive antibody screen were further tested for antibody identification. The data was analysed to find out the frequency, pattern and factors influencing red cell alloimmunization secondary to multiple transfusions. Mean age of the patients was 14 years (range 1.5-27 years). Red cell alloantibodies were found in 11 patients (9.48%). In four (36%) patients first transfusion was given before 6 months of age and in seven (64%) patients, first transfusion was given after two years of age. The interval between consecutive transfusions varied from 18 to 35 days. The most common antibody was Anti-E found in 4 (36.4%) patients, followed by Anti-K (three patients, 27.2%), Anti-Kp(a) (two patients, 18.2%) and Anti-C(w) (two patients, 18.2%). The interval from first transfusion to antibody development varied from 1.5 to 14 years. None of the eight out of 116 patients, who underwent splenectomy showed any antibody development. The rate of red cell alloimmunization was found to be 9.48% in thalassemics receiving regular transfusions. The incidence of alloantibody development was higher if first transfusion was received at more than 2 years of age. Early institution of red cell transfusions and Rh and Kell phenotyping followed by provision of matched blood could prevent alloimmunization. Copyright © 2011 Elsevier Ltd. All rights reserved.

  4. Impact of FAB classification on predicting outcome in acute myeloid leukemia, not otherwise specified, patients undergoing allogeneic stem cell transplantation in CR1: An analysis of 1690 patients from the acute leukemia working party of EBMT.

    Science.gov (United States)

    Canaani, Jonathan; Beohou, Eric; Labopin, Myriam; Socié, Gerard; Huynh, Anne; Volin, Liisa; Cornelissen, Jan; Milpied, Noel; Gedde-Dahl, Tobias; Deconinck, Eric; Fegueux, Nathalie; Blaise, Didier; Mohty, Mohamad; Nagler, Arnon

    2017-04-01

    The French, American, and British (FAB) classification system for acute myeloid leukemia (AML) is extensively used and is incorporated into the AML, not otherwise specified (NOS) category in the 2016 WHO edition of myeloid neoplasm classification. While recent data proposes that FAB classification does not provide additional prognostic information for patients for whom NPM1 status is available, it is unknown whether FAB still retains a current prognostic role in predicting outcome of AML patients undergoing allogeneic stem cell transplantation. Using the European Society of Blood and Bone Marrow Transplantation registry we analyzed outcome of 1690 patients transplanted in CR1 to determine if FAB classification provides additional prognostic value. Multivariate analysis revealed that M6/M7 patients had decreased leukemia free survival (hazard ratio (HR) of 1.41, 95% confidence interval (CI), 1.01-1.99; P = .046) in addition to increased nonrelapse mortality (NRM) rates (HR, 1.79; 95% CI, 1.06-3.01; P = .028) compared with other FAB types. In the NPM1 wt AML, NOS cohort, FAB M6/M7 was also associated with increased NRM (HR, 2.17; 95% CI, 1.14-4.16; P = .019). Finally, in FLT3-ITD + patients, multivariate analyses revealed that specific FAB types were tightly associated with adverse outcome. In conclusion, FAB classification may predict outcome following transplantation in AML, NOS patients. © 2017 Wiley Periodicals, Inc.

  5. Pattern classification

    CERN Document Server

    Duda, Richard O; Stork, David G

    2001-01-01

    The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

  6. Proceedings of the workshop on hydrocarbon processing mixing and scale-up problems. [Fuels processing for fuel cells

    Energy Technology Data Exchange (ETDEWEB)

    Gabor, J. D. [ed.

    1978-01-01

    A workshop was convened by the Division of Fossil Fuel Utilization of the US Department of Energy in cooperation with the Particulate and Multiphase Process Program of the National Science Foundation to identify needs for fundamental engineering support for the design of chemical reactors for processing heavy hydrocarbon liquids. The problems associated with dispersing liquid hydrocarbons in a reacting gas and mixing within the gas phase are of primary concern. The transactions of the workshop begin with an introduction to the immediate goals of the Department of Energy. Fuel cell systems and current research and development are reviewed. Modeling of combustion and the problems of soot formation and deposits in hydrocarbon fuels are next considered. The fluid mechanics of turbulent mixing and its effect on chemical reactions are then presented. Current experimental work and process development provide an update on the present state-of-the-art.

  7. Classification Accuracy Is Not Enough

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    A recent review of the research literature evaluating music genre recognition (MGR) systems over the past two decades shows that most works (81\\%) measure the capacity of a system to recognize genre by its classification accuracy. We show here, by implementing and testing three categorically...... different state-of-the-art MGR systems, that classification accuracy does not necessarily reflect the capacity of a system to recognize genre in musical signals. We argue that a more comprehensive analysis of behavior at the level of the music is needed to address the problem of MGR, and that measuring...

  8. Proteomic classification of breast cancer.

    LENUS (Irish Health Repository)

    Kamel, Dalia

    2012-11-01

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

  9. Human error classification and data collection

    International Nuclear Information System (INIS)

    1990-01-01

    Analysis of human error data requires human error classification. As the human factors/reliability subject has developed so too has the topic of human error classification. The classifications vary considerably depending on whether it has been developed from a theoretical psychological approach to understanding human behavior or error, or whether it has been based on an empirical practical approach. This latter approach is often adopted by nuclear power plants that need to make practical improvements as soon as possible. This document will review aspects of human error classification and data collection in order to show where potential improvements could be made. It will attempt to show why there are problems with human error classification and data collection schemes and that these problems will not be easy to resolve. The Annex of this document contains the papers presented at the meeting. A separate abstract was prepared for each of these 12 papers. Refs, figs and tabs

  10. Fractional variational problems and particle in cell gyrokinetic simulations with fuzzy logic approach for tokamaks

    Directory of Open Access Journals (Sweden)

    Rastović Danilo

    2009-01-01

    Full Text Available In earlier Rastovic's papers [1] and [2], the effort was given to analyze the stochastic control of tokamaks. In this paper, the deterministic control of tokamak turbulence is investigated via fractional variational calculus, particle in cell simulations, and fuzzy logic methods. Fractional integrals can be considered as approximations of integrals on fractals. The turbulent media could be of the fractal structure and the corresponding equations should be changed to include the fractal features of the media.

  11. Comparison of the permeability of metoprolol and labetalol in rat, mouse, and Caco-2 cells: use as a reference standard for BCS classification.

    Science.gov (United States)

    Incecayir, Tuba; Tsume, Yasuhiro; Amidon, Gordon L

    2013-03-04

    The purpose of this study was to investigate labetalol as a potential high permeability reference standard for the application of Biopharmaceutics Classification Systems (BCS). Permeabilities of labetalol and metoprolol were investigated in animal intestinal perfusion models and Caco-2 cell monolayers. After isolating specific intestinal segments, in situ single-pass intestinal perfusions (SPIP) were performed in rats and mice. The effective permeabilities (Peff) of labetalol and metoprolol, an FDA standard for the low/high Peff class boundary, were investigated in two different segments of rat intestine (proximal jejunum and distal ileum) and in the proximal jejunum of mouse. No significant difference was found between Peff of metoprolol and labetalol in the jejunum and ileum of rat (0.33 ± 0.11 × 10(-4) vs 0.38 ± 0.06 × 10(-4) and 0.57 ± 0.17 × 10(-4) vs 0.64 ± 0.30 × 10(-4) cm/s, respectively) and in the jejunum of mouse (0.55 ± 0.05 × 10(-4) vs 0.59 ± 0.13 × 10(-4) cm/s). However, Peff of metoprolol and labetalol were 1.7 and 1.6 times higher in the jejunum of mouse, compared to the jejunum of rat, respectively. Metoprolol and labetalol showed segmental-dependent permeability through the rat intestine, with increased Peff in the distal ileum in comparison to the proximal jejunum. Most significantly, Peff of labetalol was found to be concentration-dependent. Decreasing concentrations of labetalol in the perfusate resulted in decreased Peff compared to Peff of metoprolol. The intestinal epithelial permeability of labetalol was lower than that of metoprolol in Caco-2 cells at both apical pH 6.5 and 7.5 (5.96 ± 1.96 × 10(-6) vs 9.44 ± 3.44 × 10(-6) and 15.9 ± 2.2 × 10(-6) vs 23.2 ± 7.1 × 10(-6) cm/s, respectively). Labetalol exhibited higher permeability in basolateral to apical (BL-AP) compared to AP-BL direction in Caco-2 cells at 0.1 times the highest dose strength (HDS) (46.7 ± 6.5 × 10(-6) vs 14.2 ± 1.5 × 10(-6) cm/s). The P

  12. Bacteriophages as vehicles for gene delivery into mammalian cells: prospects and problems.

    Science.gov (United States)

    Bakhshinejad, Babak; Sadeghizadeh, Majid

    2014-10-01

    The identification of more efficient gene delivery vehicles (GDVs) is essential to fulfill the expectations of clinical gene therapy. Bacteriophages, due to their excellent safety profile, extreme stability under a variety of harsh environmental conditions and the capability for being genetically manipulated, have drawn a flurry of interest to be applied as a newly arisen category of gene delivery platforms. The incessant evolutionary interaction of bacteriophages with human cells has turned them into a part of our body's natural ecosystem. However, these carriers represent several barriers to gene transduction of mammalian cells. The lack of evolvement of specialized machinery for targeted cellular internalization, endosomal, lysosomal and proteasomal escape, cytoplasmic entry, nuclear localization and intranuclear transcription poses major challenges to the expression of the phage-carried gene. In this review, we describe pros and cons of bacteriophages as GDVs, provide an insight into numerous barriers that bacteriophages face for entry into and subsequent trafficking inside mammalian cells and elaborate on the strategies used to bypass these barriers. Tremendous genetic flexibility of bacteriophages to undergo numerous surface modifications through phage display technology has proven to be a turning point in the uncompromising efforts to surmount the limitations of phage-mediated gene expression. The revelatory outcomes of the studies undertaken within the recent years have been promising for phage-mediated gene delivery to move from concept to reality.

  13. Myeloid-derived suppressor cells in cancer cachexia syndrome: a new explanation for an old problem.

    Science.gov (United States)

    Winfield, Robert D; Delano, Matthew J; Pande, Kalyan; Scumpia, Philip O; Laface, Drake; Moldawer, Lyle L

    2008-01-01

    Cachexia accompanies many chronic inflammatory diseases, including cancer. Lean tissue wasting is only one component of the cancer cachexia response, which also includes anemia, anorexia, a hepatic acute phase protein response, and increased susceptibility to secondary infections. The etiologies of cancer cachexia are multifactorial and include an overproduction of inflammatory mediators, including cytokines produced by inappropriate activation of innate immunity. However, anticytokine therapies have generally not been seriously considered for cancer cachexia, in large part because of the overlapping activities of several inflammatory cytokines and the inability to prospectively identify the contributions of individual mediators. In contrast, recent evidence has focused on an immature myeloid cell population that expands dramatically in the tumors and secondary lymphoid organs of animals with some actively growing tumors. These immature GR-1(+)CD11b(+) cells are metabolically active and secrete large quantities of inflammatory cytokines and chemokines with the potential to produce cachexia. Their expansion is temporally associated with the development of cachexia. Future studies are required to determine whether therapeutic efforts intended to block the expansion of these cells can prevent the lean tissue wasting that accompanies active tumor growth.

  14. Learning features for tissue classification with the classification restricted Boltzmann machine

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    2014-01-01

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

  15. Diagnostic problems among chronic lymphocytic leukemia and other indolent B-cell leukemias in a Japanese population.

    Science.gov (United States)

    Isobe, Yasushi; Tomomatsu, Junichi; Tsukune, Yutaka; Tsukada, Nobuhiro; Sasaki, Makoto; Sugimoto, Koichi; Komatsu, Norio

    2012-01-01

    Japanese chronic lymphocytic leukemia (CLL) provides a diagnostic dilemma due to the low incidence and the heterogeneity shown in its morphology and immunophenotype. We clarified the diagnostic problems in Japanese CLL through our retrospective observation. Between 2006 and 2011, we found a total of 48 cases with CLL and other indolent B-cell leukemias. We made a diagnosis of true CLL based on clinical, laboratory, immunophenotypic and cytogenetic data. Among the 48 cases, only 28 cases (58.3%) were diagnosed with true CLL. Morphologic evaluation using a forced-air dried preparation alone is not helpful to distinguish CLL from other indolent B-cell leukemias, including hairy cell leukemia, mantle cell lymphoma, lymphoplasmacytic lymphoma, and splenic marginal zone lymphoma. CLL immunophenotypic score should be more strictly applied in Japan than in Western countries. Fluorescence in situ hybridization for CCND1/IGH, the presence of leukocytosis and lymphadenopathy at diagnosis, and the morphological evaluation using naturally air dried preparations are important clues to make a correct diagnosis of Japanese CLL.

  16. Realising new health technologies: problems of regulating human stem cells in the USA.

    Science.gov (United States)

    Warren-Jones, Amanda

    2012-01-01

    Stem cell technology holds the promise of radically changing medicine through the provision of better disease models; the creation of tissue, cells, and organs for therapeutic uses; and the increased personalisation of healthcare. However, the degree to which any of these developments can be realised in the USA rests upon how effective the regulatory environment is in nurturing the technology to market. This article assesses the regulation in terms of its ability to minimise factors which erode the public interest in developing medical innovations (abuse) and promoting them to the market. This requires an overarching review of patent law (and how it fits with anti-trust and contract law); as well as the general regulation of innovation through ethical review, clinical trials, market authorisation, post-market oversight; government lead regulation of stem cells; and finally incorporating the impact of self-regulation by industry. From this assessment, it becomes possible to appreciate that the optimal system of regulation is reliant upon the gentle tweaking of many factors, rather than the wholesale revision of only a few. It also becomes possible to identify that individual tools of regulation have varying impacts. For example, the patent system may be the most open to abuse by individual companies, but as a regulatory framework it has the most mechanisms for dealing with such abuses. However, the biggest impact upon curtailing abuse derives from the self-regulation of the industry. Conversely, government led regulation is open to abuse from political agendas, but it has the greatest capacity to nurture innovation productively.

  17. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

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

  18. Technical problems to be solved before the solid oxide fuel cell will be commercialized

    Energy Technology Data Exchange (ETDEWEB)

    Bagger, C.; Hendriksen, P.V.; Mogensen, M. [Riso National Lab., Roskilde (Denmark)

    1996-12-31

    The problems which must be solved before SOFC-systems are competitive with todays power production technology are of both technical and economical nature. The cost of SOFC stacks at the 25 kW level of today is about 30,000 ECU/kW and it is bound to come down to about 500 ECU/kW. The allowable cost of a SOFC system is anticipated to be around 1500 ECU/kW. As part of the Danish SOFC program (DK-SOFC) a 0.5 kW stack was built and tested during the second half of 1995. Based upon the experience gained, an economic analysis has been made. The tools required to approach an economically acceptable solution are outlined below.

  19. Applications of Transport/Reaction Codes to Problems in Cell Modeling; TOPICAL

    International Nuclear Information System (INIS)

    MEANS, SHAWN A.; RINTOUL, MARK DANIEL; SHADID, JOHN N.

    2001-01-01

    We demonstrate two specific examples that show how our exiting capabilities in solving large systems of partial differential equations associated with transport/reaction systems can be easily applied to outstanding problems in computational biology. First, we examine a three-dimensional model for calcium wave propagation in a Xenopus Laevis frog egg and verify that a proposed model for the distribution of calcium release sites agrees with experimental results as a function of both space and time. Next, we create a model of the neuron's terminus based on experimental observations and show that the sodium-calcium exchanger is not the route of sodium's modulation of neurotransmitter release. These state-of-the-art simulations were performed on massively parallel platforms and required almost no modification of existing Sandia codes

  20. The survey of large-scale query classification

    Science.gov (United States)

    Zhou, Sanduo; Cheng, Kefei; Men, Lijun

    2017-04-01

    In recent years, a lot of researches have been done on query classification. The paper introduces the recent researches on query classification in detail, mainly including the source of query log, the category systems, the feature extraction methods, classification methods and the evaluation methodology. Then it discusses the issues of large-scale query classification and the solved methods combined with big data analysis systems. The research result shows there still are several problems and challenges, such as lack of authoritative classification system and evaluation methodology, efficiency of the feature extraction method, uncertainty of the performance on large-scale query log and the further query classification on the big data platform, etc.

  1. Learning to recognise : A study on one-class classification and active learning

    NARCIS (Netherlands)

    Juszczak, P.

    2006-01-01

    The thesis treats classification problems which are undersampled or where there exist an unbalance between classes in the sampling. The thesis is divided into three parts. The first two parts treat the problem of one-class classification. In the one-class classification problem, it is assumed that

  2. [Classification of periprosthetic shoulder fractures].

    Science.gov (United States)

    Kirchhoff, C; Kirchhoff, S; Biberthaler, P

    2016-04-01

    The key targets in the treatment of periprosthetic humeral fractures (PHF) are the preservation of bone, successful bony consolidation and provision of a stable anchoring of the prosthesis with the major goal of restoring the shoulder-arm function. A substantial problem of periprosthetic shoulder fractures is the fact that treatment is determined not only by the fracture itself but also by the implanted prosthesis and its function. Consequently, the exact preoperative shoulder function and, in the case of an implanted anatomical prosthesis, the status and function of the rotator cuff need to be assessed in order to clarify the possibility of a secondarily occurring malfunction. Of equal importance in this context is the type of implanted prosthesis. The existing classification systems of Wright and Cofield, Campbell et al., Groh et al. and Worland et al. have several drawbacks from a shoulder surgeon's point of view, such as a missing reference to the great variability of the available prostheses and the lack of an evaluation of rotator cuff function. The presented 6‑stage classification for the evaluation of periprosthetic fractures of the shoulder can be considered just as simple or complex to understand as the classification of the working group for osteosynthesis problems (AO, Arbeitsgemeinschaft für Osteosynthesefragen), depending on the viewpoint. From our point of view the classification presented here encompasses the essential points of the existing classification systems and also covers the otherwise missing points, which should be considered in the assessment of such periprosthetic fractures. The classification presented here should provide helpful assistance in the daily routine to find the most convenient form of therapy.

  3. Cell Phones ≠ Self and Other Problems with Big Data Detection and Containment during Epidemics.

    Science.gov (United States)

    Erikson, Susan L

    2018-03-08

    Evidence from Sierra Leone reveals the significant limitations of big data in disease detection and containment efforts. Early in the 2014-2016 Ebola epidemic in West Africa, media heralded HealthMap's ability to detect the outbreak from newsfeeds. Later, big data-specifically, call detail record data collected from millions of cell phones-was hyped as useful for stopping the disease by tracking contagious people. It did not work. In this article, I trace the causes of big data's containment failures. During epidemics, big data experiments can have opportunity costs: namely, forestalling urgent response. Finally, what counts as data during epidemics must include that coming from anthropological technologies because they are so useful for detection and containment. © 2018 The Authors Medical Anthropology Quarterly published by Wiley Periodicals, Inc. on behalf of American Anthropological Association.

  4. Cell-free DNA as a biomarker in stroke: Current status, problems and perspectives.

    Science.gov (United States)

    Glebova, Kristina V; Veiko, Natalya N; Nikonov, Aleksey A; Porokhovnik, Lev N; Kostuyk, Svetlana V

    2018-01-01

    There is currently no proposed stroke biomarker with consistent application in clinical practice. A number of studies have examined cell-free DNA (cfDNA), which circulates in biological fluids during stroke, as a potential biomarker of this disease. The data available suggest that dynamically-determined levels of blood cfDNA may provide new prognostic information for assessment of stroke severity and outcome. However, such an approach has its own difficulties and limitations. This review covers the potential role of cfDNA as a biomarker in stroke, and includes evidence from both animal models and clinical studies, protocols used to analyze cfDNA, and hypotheses on the origin of cfDNA.

  5. Functional studies of microRNAs in neural stem cells: problems and perspectives.

    Directory of Open Access Journals (Sweden)

    Malin eÅkerblom

    2012-02-01

    Full Text Available In adult mammals, neural stem cells (NSCs are found in two niches of the brain; the subventricular zone at the lateral ventricle and the subgranular zone of the dentate gyrus in the hippocampus. Neurogenesis is a complex process that is tightly controlled on a molecular level. Recently, microRNAs (miRNAs have been implicated to play a central role in the regulation of NCSs. miRNAs are small, endogenously expressed RNAs that regulate gene expression at the post-transcriptional level. However, functional studies of miRNAs are complicated due to current technical limitations. In this review we describe recent findings about miRNAs in NSCs looking closely at miR-124, miR-9 and let-7. We also highlight technical strategies used to investigate miRNA function, accentuating limitations and potentials.

  6. Scientific and General Subject Classifications in the Digital World

    CERN Document Server

    De Robbio, Antonella; Marini, A

    2001-01-01

    In the present work we discuss opportunities, problems, tools and techniques encountered when interconnecting discipline-specific subject classifications, primarily organized as search devices in bibliographic databases, with general classifications originally devised for book shelving in public libraries. We first state the fundamental distinction between topical (or subject) classifications and object classifications. Then we trace the structural limitations that have constrained subject classifications since their library origins, and the devices that were used to overcome the gap with genuine knowledge representation. After recalling some general notions on structure, dynamics and interferences of subject classifications and of the objects they refer to, we sketch a synthetic overview on discipline-specific classifications in Mathematics, Computing and Physics, on one hand, and on general classifications on the other. In this setting we present The Scientific Classifications Page, which collects groups of...

  7. Texture classification using logical operators.

    Science.gov (United States)

    Manian, V; Vasquez, R; Katiyar, P

    2000-01-01

    In this paper, a new algorithm for texture classification based on logical operators is presented. Operators constructed from logical building blocks are convolved with texture images. An optimal set of six operators are selected based on their texture discrimination ability. The responses are then converted to standard deviation matrices computed over a sliding window. Zonal sampling features are computed from these matrices. A feature selection process is applied and the new set of features are used for texture classification. Classification of several natural and synthetic texture images are presented demonstrating the excellent performance of the logical operator method. The computational superiority and classification accuracy of the algorithm is demonstrated by comparison with other popular methods. Experiments with different classifiers and feature normalization are also presented. The Euclidean distance classifier is found to perform best with this algorithm. The algorithm involves only convolutions and simple arithmetic in the various stages which allows faster implementations. The algorithm is applicable to different types of classification problems which is demonstrated by segmentation of remote sensing images, compressed and reconstructed images and industrial images.

  8. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

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

    2015-01-01

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

  9. CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. B. Popova

    2016-01-01

    Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

  10. [D-cells of the gastroenteropancreatic system: development, structure, function and regeneration (history and current state of the problem)].

    Science.gov (United States)

    Ivanova, V F; Kostiukevich, S V

    2015-01-01

    The present review summarizes the literature data and the results of authors' own research on the development, structure, function and regeneration of D-endocrinocytes of gastroenteropancreatic (GEP) system. The history of the research of these cells is reviewed and its current state of the problem is discussed. The information on the difference of somatostatin-producing D-endocrinocytes from other types of endocrine cells of GAP system is presented, namely, the prevalence of these cells in all the organs of the digestive system (stomach, small and large intestine, pancreas) and other systems of the body, the peculiarities of their structure and regeneration in various species of vertebrate animals and humans in embryonic development, under conditions of normal functioning and in various types of pathology. On the basis of the data on the early differentiation of D-endocrinocytes and their secretion of hormones during embryonic development, structure, cytophysiology and relationships within the general endocrinocyte population, it is suggested that D-endocrinocytes play an important role in the morpho-functional state of GEP system.

  11. Nonlinear estimation and classification

    CERN Document Server

    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

  12. State of the art: Multi-fuel reformers for automotive fuel cell applications. Problem identification and research needs

    Energy Technology Data Exchange (ETDEWEB)

    Westerholm, R. [Stockholm Univ. (Sweden). Dept. of Analytical Chemistry; Pettersson, L.J. [Royal Inst. of Tech., Stockholm (Sweden). Dept. of Chemical Engineering and Technology

    1999-12-01

    On an assignment from the Transport and Communications Research Board (KFB) a literature study and a study trip to the USA and Great Britain have been performed. The literature study and the study trip was made during late spring and autumn 1999.The purpose of the project was to collect available information about the chemical composition of the product gas from a multi-fuel reformer for a fuel cell vehicle. It was furthermore to identify problems and research needs. The report recommends directions for future major research efforts. The results of the literature study and the study trip led to the following general conclusions: With the technology available today it does not seem feasible to develop a highly efficient and reliable multi-fuel reformer for automotive applications, i. e. for applications where all types of fuels ranging from natural gas to heavy diesel fuels can be used. The potential for developing a durable and reliable system is considerably higher if dedicated fuel reformers are used.The authors propose that petroleum-derived fuels should be designed for potential use in mobile fuel cell applications. In the present literature survey and the site visit discussions we found that there are relatively low emissions from fuel cell engines compared to internal combustion engines. However, the major research work on reformers/fuel cells have been performed during steady-state operation. Emissions during start-up, shutdown and transient operation are basically unknown and must be investigated in more detail. The conclusions and findings in this report are based on open/available information, such as discussions at site visits, reports, scientific publications and symposium proceedings.

  13. BIOCAT: a pattern recognition platform for customizable biological image classification and annotation.

    Science.gov (United States)

    Zhou, Jie; Lamichhane, Santosh; Sterne, Gabriella; Ye, Bing; Peng, Hanchuan

    2013-10-04

    Pattern recognition algorithms are useful in bioimage informatics applications such as quantifying cellular and subcellular objects, annotating gene expressions, and classifying phenotypes. To provide effective and efficient image classification and annotation for the ever-increasing microscopic images, it is desirable to have tools that can combine and compare various algorithms, and build customizable solution for different biological problems. However, current tools often offer a limited solution in generating user-friendly and extensible tools for annotating higher dimensional images that correspond to multiple complicated categories. We develop the BIOimage Classification and Annotation Tool (BIOCAT). It is able to apply pattern recognition algorithms to two- and three-dimensional biological image sets as well as regions of interest (ROIs) in individual images for automatic classification and annotation. We also propose a 3D anisotropic wavelet feature extractor for extracting textural features from 3D images with xy-z resolution disparity. The extractor is one of the about 20 built-in algorithms of feature extractors, selectors and classifiers in BIOCAT. The algorithms are modularized so that they can be "chained" in a customizable way to form adaptive solution for various problems, and the plugin-based extensibility gives the tool an open architecture to incorporate future algorithms. We have applied BIOCAT to classification and annotation of images and ROIs of different properties with applications in cell biology and neuroscience. BIOCAT provides a user-friendly, portable platform for pattern recognition based biological image classification of two- and three- dimensional images and ROIs. We show, via diverse case studies, that different algorithms and their combinations have different suitability for various problems. The customizability of BIOCAT is thus expected to be useful for providing effective and efficient solutions for a variety of biological

  14. Reduction of Dimensionality for Classification

    OpenAIRE

    Cuevas-Covarrubias, Carlos; Riccomagno, Eva

    2017-01-01

    We present an algorithm for the reduction of dimensionality useful in statistical classification problems where observations from two multivariate normal distributions are discriminated. It is based on Principal Components Analysis and consists of a simultaneous diagonalization of two covariance matrices. The criterion for reduction of dimensionality is given by the contribution of each principal component to the area under the ROC curve of a discriminant function. Linear and quadratic scores...

  15. Classification Using Extreme Learning Machine

    OpenAIRE

    Soumya Sahoo; Sunil Kumar Mohapatra; Bijayalaxmi Panda

    2013-01-01

    Extreme Learning Machine (ELM) has become popular for solving classification problem due to its fast speed. The performance of ELM often relies on random input hidden node parameters. Neural network also uses artificial intelligence by adjusting weights and minimizing the error. The learning speed of feedforward neural network is very slow. Due to two slow gradient-based learning algorithms and iterative tuning of various parameters. This paper presents a comparative study of back...

  16. Models for warehouse management: Classification and examples

    NARCIS (Netherlands)

    van den Berg, J.P.; van den Berg, J.P.; Zijm, Willem H.M.

    1999-01-01

    In this paper we discuss warehousing systems and present a classification of warehouse management problems. We start with a typology and a brief description of several types of warehousing systems. Next, we present a hierarchy of decision problems encountered in setting up warehousing systems,

  17. Global Optimization Ensemble Model for Classification Methods

    Directory of Open Access Journals (Sweden)

    Hina Anwar

    2014-01-01

    Full Text Available Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity.

  18. Classification of cultivated plants.

    NARCIS (Netherlands)

    Brandenburg, W.A.

    1986-01-01

    Agricultural practice demands principles for classification, starting from the basal entity in cultivated plants: the cultivar. In establishing biosystematic relationships between wild, weedy and cultivated plants, the species concept needs re-examination. Combining of botanic classification, based

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

    Science.gov (United States)

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

    1990-01-01

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

  20. Classification of Pemphigus

    Directory of Open Access Journals (Sweden)

    Ayşe Akman

    2008-08-01

    Full Text Available Clinical classification of pemphigus is not yet complete. The classic classification based on clinical and histologic features. Because of the progress in the pathogenesis of pemphigus, the current classifications based on accumulating analyses of antigen molecules and subclasses of immunoglobulins and etiologic aspects of pemphigus as weel as the clinical, histologic features. The aim of this paper is to review classification of pemphigus.

  1. A Method for Selecting between Linear and Quadratic Classification Models in Discriminant Analysis.

    Science.gov (United States)

    Meshbane, Alice; Morris, John D.

    1995-01-01

    A method for comparing the cross-validated classification accuracies of linear and quadratic classification rules is presented under varying data conditions for the "k"-group classification problem. Separate-group and total-group proportions of correct classifications can be compared for the two rules, as is illustrated. (Author/SLD)

  2. Basis of Criminalistic Classification of a Person in Republic Kazakhstan and Republic Mongolia

    Science.gov (United States)

    Abdilov, Kanat S.; Zusbaev, Baurzan T.; Naurysbaev, Erlan A.; Nukiev, Berik A.; Nurkina, Zanar B.; Myrzahanov, Erlan N.; Urazalin, Galym T.

    2016-01-01

    In this article reviewed problems of the criminalistic classification building of a person. In the work were used legal formal, logical, comparative legal methods. The author describes classification kinds. Reveal the meaning of classification in criminalistic systematics. Shows types of grounds of criminalistic classification of a person.…

  3. Neural network technologies for image classification

    Science.gov (United States)

    Korikov, A. M.; Tungusova, A. V.

    2015-11-01

    We analyze the classes of problems with an objective necessity to use neural network technologies, i.e. representation and resolution problems in the neural network logical basis. Among these problems, image recognition takes an important place, in particular the classification of multi-dimensional data based on information about textural characteristics. These problems occur in aerospace and seismic monitoring, materials science, medicine and other. We reviewed different approaches for the texture description: statistical, structural, and spectral. We developed a neural network technology for resolving a practical problem of cloud image classification for satellite snapshots from the spectroradiometer MODIS. The cloud texture is described by the statistical characteristics of the GLCM (Gray Level Co- Occurrence Matrix) method. From the range of neural network models that might be applied for image classification, we chose the probabilistic neural network model (PNN) and developed an implementation which performs the classification of the main types and subtypes of clouds. Also, we chose experimentally the optimal architecture and parameters for the PNN model which is used for image classification.

  4. On music genre classification via compressive sampling

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    Recent work \\cite{Chang2010} combines low-level acoustic features and random projection (referred to as ``compressed sensing'' in \\cite{Chang2010}) to create a music genre classification system showing an accuracy among the highest reported for a benchmark dataset. This not only contradicts...... previous findings that suggest low-level features are inadequate for addressing high-level musical problems, but also that a random projection of features can improve classification. We reproduce this work and resolve these contradictions....

  5. Support Vector Machines for Pattern Classification

    CERN Document Server

    Abe, Shigeo

    2010-01-01

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

  6. New Approach to Analyzing Physics Problems: A Taxonomy of Introductory Physics Problems

    Science.gov (United States)

    Teodorescu, Raluca E.; Bennhold, Cornelius; Feldman, Gerald; Medsker, Larry

    2013-01-01

    This paper describes research on a classification of physics problems in the context of introductory physics courses. This classification, called the Taxonomy of Introductory Physics Problems (TIPP), relates physics problems to the cognitive processes required to solve them. TIPP was created in order to design educational objectives, to develop…

  7. Tumor classification ranking from microarray data

    Directory of Open Access Journals (Sweden)

    Kijsanayothin Phongphun

    2008-09-01

    Full Text Available Abstract Background Gene expression profiles based on microarray data are recognized as potential diagnostic indices of cancer. Molecular tumor classifications resulted from these data and learning algorithms have advanced our understanding of genetic changes associated with cancer etiology and development. However, classifications are not always perfect and in such cases the classification rankings (likelihoods of correct class predictions can be useful for directing further research (e.g., by deriving inferences about predictive indicators or prioritizing future experiments. Classification ranking is a challenging problem, particularly for microarray data, where there is a huge number of possible regulated genes with no known rating function. This study investigates the possibility of making tumor classification more informative by using a method for classification ranking that requires no additional ranking analysis and maintains relatively good classification accuracy. Results Microarray data of 11 different types and subtypes of cancer were analyzed using MDR (Multi-Dimensional Ranker, a recently developed boosting-based ranking algorithm. The number of predictor genes in all of the resulting classification models was at most nine, a huge reduction from the more than 12 thousands genes in the majority of the expression samples. Compared to several other learning algorithms, MDR gives the greatest AUC (area under the ROC curve for the classifications of prostate cancer, acute lymphoblastic leukemia (ALL and four ALL subtypes: BCR-ABL, E2A-PBX1, MALL and TALL. SVM (Support Vector Machine gives the highest AUC for the classifications of lung, lymphoma, and breast cancers, and two ALL subtypes: Hyperdiploid > 50 and TEL-AML1. MDR gives highly competitive results, producing the highest average AUC, 91.01%, and an average overall accuracy of 90.01% for cancer expression analysis. Conclusion Using the classification rankings from MDR is a simple

  8. Galaxy Classifications with Deep Learning

    Science.gov (United States)

    Lukic, Vesna; Brüggen, Marcus

    2017-06-01

    Machine learning techniques have proven to be increasingly useful in astronomical applications over the last few years, for example in object classification, estimating redshifts and data mining. One example of object classification is classifying galaxy morphology. This is a tedious task to do manually, especially as the datasets become larger with surveys that have a broader and deeper search-space. The Kaggle Galaxy Zoo competition presented the challenge of writing an algorithm to find the probability that a galaxy belongs in a particular class, based on SDSS optical spectroscopy data. The use of convolutional neural networks (convnets), proved to be a popular solution to the problem, as they have also produced unprecedented classification accuracies in other image databases such as the database of handwritten digits (MNIST †) and large database of images (CIFAR ‡). We experiment with the convnets that comprised the winning solution, but using broad classifications. The effect of changing the number of layers is explored, as well as using a different activation function, to help in developing an intuition of how the networks function and to see how they can be applied to radio galaxy images.

  9. Unsupervised classification of variable stars

    Science.gov (United States)

    Valenzuela, Lucas; Pichara, Karim

    2018-03-01

    During the past 10 years, a considerable amount of effort has been made to develop algorithms for automatic classification of variable stars. That has been primarily achieved by applying machine learning methods to photometric data sets where objects are represented as light curves. Classifiers require training sets to learn the underlying patterns that allow the separation among classes. Unfortunately, building training sets is an expensive process that demands a lot of human efforts. Every time data come from new surveys; the only available training instances are the ones that have a cross-match with previously labelled objects, consequently generating insufficient training sets compared with the large amounts of unlabelled sources. In this work, we present an algorithm that performs unsupervised classification of variable stars, relying only on the similarity among light curves. We tackle the unsupervised classification problem by proposing an untraditional approach. Instead of trying to match classes of stars with clusters found by a clustering algorithm, we propose a query-based method where astronomers can find groups of variable stars ranked by similarity. We also develop a fast similarity function specific for light curves, based on a novel data structure that allows scaling the search over the entire data set of unlabelled objects. Experiments show that our unsupervised model achieves high accuracy in the classification of different types of variable stars and that the proposed algorithm scales up to massive amounts of light curves.

  10. Saving our science from ourselves: the plight of biological classification

    Directory of Open Access Journals (Sweden)

    Malte C. Ebach

    2011-06-01

    Full Text Available Saving our science from ourselves: the plight of biological classification. Biological classification ( nomenclature, taxonomy, and systematics is being sold short. The desire for new technologies, faster and cheaper taxonomic descriptions, identifications, and revisions is symptomatic of a lack of appreciation and understanding of classification. The problem of gadget-driven science, a lack of best practice and the inability to accept classification as a descriptive and empirical science are discussed. The worst cases scenario is a future in which classifications are purely artificial and uninformative.

  11. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

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

  12. Efficient Generation and Selection of Combined Features for Improved Classification

    KAUST Repository

    Shono, Ahmad N.

    2014-05-01

    This study contributes a methodology and associated toolkit developed to allow users to experiment with the use of combined features in classification problems. Methods are provided for efficiently generating combined features from an original feature set, for efficiently selecting the most discriminating of these generated combined features, and for efficiently performing a preliminary comparison of the classification results when using the original features exclusively against the results when using the selected combined features. The potential benefit of considering combined features in classification problems is demonstrated by applying the developed methodology and toolkit to three sample data sets where the discovery of combined features containing new discriminating information led to improved classification results.

  13. Marginal zone B-cell lymphoma with multiple extranodal locations in a patient with Sjögren’s syndrome – a diagnostic problem

    Directory of Open Access Journals (Sweden)

    Marta Domżalska

    2014-09-01

    Full Text Available Sjögren’s syndrome is a chronic autoimmune disease characterized by the presence of lymphocytic infiltrates in exocrine glands, mainly salivary and lacrimal glands, which result in xerophthalmia and xerostomia. About half of the patients develop systemic complications, including lymphoproliferative disorders. We report a case of a 27-year-old woman with a diagnosis of Sjögren’s syndrome and a suspicion of respiratory system involvement in the course of granulomatosis with polyangiitis. Histopathological examination of a skin lesion suggested marginal zone B-cell lymphoma. After pathological and immunohistochemical evaluation of all available previous biopsy samples and the medical documentation the diagnosis of extranodal marginal zone B-cell lymphoma stage IV according to the Ann Arbor classification was rendered. The patient was referred to the Department of Haematology and was treated with R-CVP (cyclophosphamide, vincristine, prednisone, rituximab.

  14. Classification and risk assessment of individuals with familial polyposis, Gardner's syndrome, and familial non-polyposis colon cancer from [3H]thymidine labeling patterns in colonic epithelial cells

    International Nuclear Information System (INIS)

    Lipkin, M.; Blattner, W.A.; Gardner, E.J.; Burt, R.W.; Lynch, H.; Deschner, E.; Winawer, S.; Fraumeni, J.F. Jr.

    1984-01-01

    A probabilistic analysis has been developed to assist the binary classification and risk assessment of members of familial colon cancer kindreds. The analysis is based on the microautoradiographic observation of [ 3 H]thymidine-labeled epithelial cells in colonic mucosa of the kindred members. From biopsies of colonic mucosa which are labeled with [ 3 H]thymidine in vitro, the degree of similarity of each subject's cell-labeling pattern measured over entire crypts was automatically compared to the labeling patterns of high-risk and low-risk reference populations. Each individual was then presumptively classified and assigned to one of the reference populations, and a degree of risk for the classification was provided. In carrying out the analysis, a linear score was calculated for each individual relative to each of the reference populations, and the classification was based on the polarity of the score difference; the degree of risk was then quantitated from the magnitude of the score difference. When the method was applied to kindreds having either familial polyposis or familial non-polyposis colon cancer, it effectively segregated individuals affected with disease from others at low risk, with sensitivity and specificity ranging from 71 to 92%. Further application of the method to asymptomatic family members believed to be at 50% risk on the basis of pedigree evaluation revealed a biomodal distribution to nearly zero or full risk. The accuracy and simplicity of this approach and its capability of revealing early stages of abnormal colonic epithelial cell development indicate potential for preclinical screening of subjects at risk in cancer-prone kindreds and for assisting the analysis of modes of inheritance

  15. An Independent Validation of 2010 Tumor-Node-Metastasis Classification for Renal Cell Carcinoma: A Multi-center Study by the Urooncology Association of Turkey Renal Cancer-Study Group

    Directory of Open Access Journals (Sweden)

    Tayyar Alp Özkan

    2017-06-01

    Full Text Available Objective: The American Joint Committee on Cancer tumor-node-metastasis (TNM classification has been updated by the 7th edition in 2010. The objective of the study was to evaluate cancer-specific survival (CSS in patients with renal cell carcinoma (RCC and assess the concordance of 2002 and novel 2010 TNM primary tumor classifications. Materials and Methods: A retrospective analysis of RCC registries from 25 institutions of the Urooncology Association of Turkey Renal Cancer-Study Group was performed. Patients with RCC had a radical or partial nephrectomy. The database consisted of 1889 patients. Results: Median follow-up time was 25 months (interquartile range: 11.2-47.8. The 5-year CSS rate for pT1a, pT1b, pT2a, pT2b, pT3a and pT4 tumors were 97% [95% confidence interval (CI: 0.93-0.99], 94% (95% CI: 0.91-0.97, 88% (95% CI: 0.81-0.93, 77% (95% CI: 0.64-0.86 74% (95% CI: 0.65-0.81 and 66% (95% CI: 0.51-0.77, respectively according to the 2010 TNM classification (p<0.001. CSS comparisons between pT1a-pT1b (p=0.022, pT1b-pT2a (p=0.030, pT3a-pT3b (p<0.001 and pT3b-pT4 (p=0.020 were statistically significant. Conversely, pT2a-pT2b (p=0.070 and pT2b-pT3a (p=0.314 were not statistically significant. Multivariable analyses revealed the pT stage in the 2010 TNM classification as an independent prognostic factor for CSS (p for trend=0.002. C-indexes for 2002 and 2010 TNM classifications were 0.8683 and 0.8706, respectively. Conclusion: Subdividing pT2 does not have a CSS advantage. Moving adrenal involvement to pT4 yielded a more accurate prognosis prediction. T stage and LNI are independent prognostic factors for CSS in RCC. Overall, the novel 2010 TNM classification is slightly improved over the former one. However, shown by C-index values, this improvement is not sufficient to state that 2010 TNM outperforms the 2002 TNM.

  16. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

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

  17. Classification of Flotation Frothers

    Directory of Open Access Journals (Sweden)

    Jan Drzymala

    2018-02-01

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

  18. Wrapper Feature Extraction for Time Series Classification Using Singular Value Decomposition

    OpenAIRE

    Hui, Zhang; Tu, Bao Ho; Kawasaki, Saori

    2005-01-01

    Time series classification is an important aspect of time series mining. Recently, time series classification has attracted increasing interests in various domains. However, the high dimensionality property of time series makes time series classification a difficult problem. The so-called curse of dimensionality not only slows down the process of classification but also decreases the classification quality. Many dimensionality reduction techniques have been proposed to circumvent the curse of...

  19. Classification of titanium dioxide

    International Nuclear Information System (INIS)

    Macias B, L.R.; Garcia C, R.M.; Maya M, M.E.; Ita T, A. De; Palacios G, J.

    2002-01-01

    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 TiO 2 . 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)

  20. Weakly supervised classification in high energy physics

    Science.gov (United States)

    Dery, Lucio Mwinmaarong; Nachman, Benjamin; Rubbo, Francesco; Schwartzman, Ariel

    2017-05-01

    As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations. This paper presents a new approach called weakly supervised classification in which class proportions are the only input into the machine learning algorithm. Using one of the most challenging binary classification tasks in high energy physics — quark versus gluon tagging — we show that weakly supervised classification can match the performance of fully supervised algorithms. Furthermore, by design, the new algorithm is insensitive to any mis-modeling of discriminating features in the data by the simulation. Weakly supervised classification is a general procedure that can be applied to a wide variety of learning problems to boost performance and robustness when detailed simulations are not reliable or not available.

  1. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

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

  2. Sentiment classification technology based on Markov logic networks

    Science.gov (United States)

    He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

    2016-07-01

    With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

  3. Handling Imbalanced Data Sets in Multistage Classification

    Science.gov (United States)

    López, M.

    Multistage classification is a logical approach, based on a divide-and-conquer solution, for dealing with problems with a high number of classes. The classification problem is divided into several sequential steps, each one associated to a single classifier that works with subgroups of the original classes. In each level, the current set of classes is split into smaller subgroups of classes until they (the subgroups) are composed of only one class. The resulting chain of classifiers can be represented as a tree, which (1) simplifies the classification process by using fewer categories in each classifier and (2) makes it possible to combine several algorithms or use different attributes in each stage. Most of the classification algorithms can be biased in the sense of selecting the most populated class in overlapping areas of the input space. This can degrade a multistage classifier performance if the training set sample frequencies do not reflect the real prevalence in the population. Several techniques such as applying prior probabilities, assigning weights to the classes, or replicating instances have been developed to overcome this handicap. Most of them are designed for two-class (accept-reject) problems. In this article, we evaluate several of these techniques as applied to multistage classification and analyze how they can be useful for astronomy. We compare the results obtained by classifying a data set based on Hipparcos with and without these methods.

  4. Voice based gender classification using machine learning

    Science.gov (United States)

    Raahul, A.; Sapthagiri, R.; Pankaj, K.; Vijayarajan, V.

    2017-11-01

    Gender identification is one of the major problem speech analysis today. Tracing the gender from acoustic data i.e., pitch, median, frequency etc. Machine learning gives promising results for classification problem in all the research domains. There are several performance metrics to evaluate algorithms of an area. Our Comparative model algorithm for evaluating 5 different machine learning algorithms based on eight different metrics in gender classification from acoustic data. Agenda is to identify gender, with five different algorithms: Linear Discriminant Analysis (LDA), K-Nearest Neighbour (KNN), Classification and Regression Trees (CART), Random Forest (RF), and Support Vector Machine (SVM) on basis of eight different metrics. The main parameter in evaluating any algorithms is its performance. Misclassification rate must be less in classification problems, which says that the accuracy rate must be high. Location and gender of the person have become very crucial in economic markets in the form of AdSense. Here with this comparative model algorithm, we are trying to assess the different ML algorithms and find the best fit for gender classification of acoustic data.

  5. Optimization models for cancer classification: extracting gene interaction information from microarray expression data.

    Science.gov (United States)

    Antonov, Alexey V; Tetko, Igor V; Mader, Michael T; Budczies, Jan; Mewes, Hans W

    2004-03-22

    Microarray data appear particularly useful to investigate mechanisms in cancer biology and represent one of the most powerful tools to uncover the genetic mechanisms causing loss of cell cycle control. Recently, several different methods to employ microarray data as a diagnostic tool in cancer classification have been proposed. These procedures take changes in the expression of particular genes into account but do not consider disruptions in certain gene interactions caused by the tumor. It is probable that some genes participating in tumor development do not change their expression level dramatically. Thus, they cannot be detected by simple classification approaches used previously. For these reasons, a classification procedure exploiting information related to changes in gene interactions is needed. We propose a MAximal MArgin Linear Programming (MAMA) method for the classification of tumor samples based on microarray data. This procedure detects groups of genes and constructs models (features) that strongly correlate with particular tumor types. The detected features include genes whose functional relations are changed for particular cancer types. The proposed method was tested on two publicly available datasets and demonstrated a prediction ability superior to previously employed classification schemes. The MAMA system was developed using the linear programming system LINDO http://www.lindo.com. A Perl script that specifies the optimization problem for this software is available upon request from the authors.

  6. Eukaryotic Cell Cycle as a Test Case for Modeling Cellular Regulation in a Collaborative Problem-Solving Environment

    Science.gov (United States)

    2007-03-01

    regulatory networks in living cells, and (2) an integrated set of models of cell cycle regulation in bacteria , yeasts, and metazoans that are accurate...26 3.3 Mutants used to derive the model and specify the parameter values 27 3.4 Numbers of molecules (per haploid yeast cell) for several cell cycle...molecular machinery governing DNA synthesis and cell division in bacteria is completely different from the machinery in eukaryotes. The control

  7. Some sequential, distribution-free pattern classification procedures with applications

    Science.gov (United States)

    Poage, J. L.

    1971-01-01

    Some sequential, distribution-free pattern classification techniques are presented. The decision problem to which the proposed classification methods are applied is that of discriminating between two kinds of electroencephalogram responses recorded from a human subject: spontaneous EEG and EEG driven by a stroboscopic light stimulus at the alpha frequency. The classification procedures proposed make use of the theory of order statistics. Estimates of the probabilities of misclassification are given. The procedures were tested on Gaussian samples and the EEG responses.

  8. Inter Genre Similarity Modelling For Automatic Music Genre Classification

    OpenAIRE

    Bagci, Ulas; Erzin, Engin

    2009-01-01

    Music genre classification is an essential tool for music information retrieval systems and it has been finding critical applications in various media platforms. Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modelling (IGS) to improve the performance of automatic music genre classification. Inter-genre similarity information is extracted over the mis-classified feature population....

  9. Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning

    Directory of Open Access Journals (Sweden)

    Tanel Pärnamaa

    2017-05-01

    Full Text Available High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy.

  10. Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning.

    Science.gov (United States)

    Pärnamaa, Tanel; Parts, Leopold

    2017-05-05

    High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy. Copyright © 2017 Parnamaa and Parts.

  11. Accurate and interpretable classification of microspectroscopy pixels using artificial neural networks.

    Science.gov (United States)

    Manescu, Petru; Jong Lee, Young; Camp, Charles; Cicerone, Marcus; Brady, Mary; Bajcsy, Peter

    2017-04-01

    This paper addresses the problem of classifying materials from microspectroscopy at a pixel level. The challenges lie in identifying discriminatory spectral features and obtaining accurate and interpretable models relating spectra and class labels. We approach the problem by designing a supervised classifier from a tandem of Artificial Neural Network (ANN) models that identify relevant features in raw spectra and achieve high classification accuracy. The tandem of ANN models is meshed with classification rule extraction methods to lower the model complexity and to achieve interpretability of the resulting model. The contribution of the work is in designing each ANN model based on the microspectroscopy hypothesis about a discriminatory feature of a certain target class being composed of a linear combination of spectra. The novelty lies in meshing ANN and decision rule models into a tandem configuration to achieve accurate and interpretable classification results. The proposed method was evaluated using a set of broadband coherent anti-Stokes Raman scattering (BCARS) microscopy cell images (600 000  pixel-level spectra) and a reference four-class rule-based model previously created by biochemical experts. The generated classification rule-based model was on average 85% accurate measured by the DICE pixel label similarity metric, and on average 96% similar to the reference rules measured by the vector cosine metric. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Ranking Cases with Classification Rules

    Science.gov (United States)

    Zhang, Jianping; Bala, Jerzy W.; Hadjarian, Ali; Han, Brent

    Many real-world machine learning applications require a ranking of cases, in addition to their classification. While classification rules are not a good representation for ranking, the human comprehensibility aspect of rules makes them an attractive option for many ranking problems where such model transparency is desired. There have been numerous studies on ranking with decision trees, but not many on ranking with decision rules. Although rules are similar to decision trees in many respects, there are important differences between them when used for ranking. In this chapter, we propose a framework for ranking with rules. The framework extends and substantially improves on the reported methods for ranking with decision trees. It introduces three types of rule-based ranking methods: post analysis of rules, hybrid methods, and multiple rule set analysis. We also study the impact of rule learning bias on the ranking performance. While traditional measures used for ranking performance evaluation tend to focus on the entire rank ordered list, the aim of many ranking applications is to optimize the performance on only a small portion of the top ranked cases. Accordingly, we propose a simple method for measuring the performance of a classification or ranking algorithm that focuses on these top ranked cases. Empirical studies have been conducted to evaluate some of the proposed methods.

  13. Linear Classification Functions.

    Science.gov (United States)

    Huberty, Carl J.; Smith, Jerry D.

    Linear classification functions (LCFs) arise in a predictive discriminant analysis for the purpose of classifying experimental units into criterion groups. The relative contribution of the response variables to classification accuracy may be based on LCF-variable correlations for each group. It is proved that, if the raw response measures are…

  14. Classification, confusion and misclassification

    African Journals Online (AJOL)

    Classifications change and in that process, we can see that someone or some group has recognise that a previous classification hindered understanding or moulded ... to a pathologist's ability to distinguish, had led to confusion and mismanagement by gynaecologists. What is worrying if not the word. 'complex'? But this is ...

  15. Spectroscopic classification of transients

    DEFF Research Database (Denmark)

    Stritzinger, M. D.; Fraser, M.; Hummelmose, N. N.

    2017-01-01

    We report the spectroscopic classification of several transients based on observations taken with the Nordic Optical Telescope (NOT) equipped with ALFOSC, over the nights 23-25 August 2017.......We report the spectroscopic classification of several transients based on observations taken with the Nordic Optical Telescope (NOT) equipped with ALFOSC, over the nights 23-25 August 2017....

  16. Library Classification 2020

    Science.gov (United States)

    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…

  17. Colombia: Territorial classification

    International Nuclear Information System (INIS)

    Mendoza Morales, Alberto

    1998-01-01

    The article is about the approaches of territorial classification, thematic axes, handling principles and territorial occupation, politician and administrative units and administration regions among other topics. Understanding as Territorial Classification the space distribution on the territory of the country, of the geographical configurations, the human communities, the political-administrative units and the uses of the soil, urban and rural, existent and proposed

  18. Selected issues relating to classification of mountain organic soils in Poland according to the Polish Soil Classification (2011

    Directory of Open Access Journals (Sweden)

    Glina Bartłomiej

    2016-12-01

    Full Text Available Despite a large number of organic soil types and subtypes in the Polish Soil Classification the problems of organic soils classification are still very common. In relation to mountain organic soils, in particular. The aim of this paper is to discuss the most common problems related to mountain organic soils classification according to the Polish Soil Classification. Based on authors’ own research and literature studies mentioned problem was described. This work allows to define some new proposals, which should be considered during developing of the next update of the Polish Soil Classification (PSC. The most important proposals related to: criteria for organic materials and organic soils, taxonomy position and criteria for shallow organic soils and new definition of mineral material admixture in organic soils.

  19. DOE LLW classification rationale

    International Nuclear Information System (INIS)

    Flores, A.Y.

    1991-01-01

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

  20. High dimensional classification with combined adaptive sparse PLS and logistic regression.

    Science.gov (United States)

    Durif, Ghislain; Modolo, Laurent; Michaelsson, Jakob; Mold, Jeff E; Lambert-Lacroix, Sophie; Picard, Franck

    2018-02-01

    The high dimensionality of genomic data calls for the development of specific classification methodologies, especially to prevent over-optimistic predictions. This challenge can be tackled by compression and variable selection, which combined constitute a powerful framework for classification, as well as data visualization and interpretation. However, current proposed combinations lead to unstable and non convergent methods due to inappropriate computational frameworks. We hereby propose a computationally stable and convergent approach for classification in high dimensional based on sparse Partial Least Squares (sparse PLS). We start by proposing a new solution for the sparse PLS problem that is based on proximal operators for the case of univariate responses. Then we develop an adaptive version of the sparse PLS for classification, called logit-SPLS, which combines iterative optimization of logistic regression and sparse PLS to ensure computational convergence and stability. Our results are confirmed on synthetic and experimental data. In particular, we show how crucial convergence and stability can be when cross-validation is involved for calibration purposes. Using gene expression data, we explore the prediction of breast cancer relapse. We also propose a multicategorial version of our method, used to predict cell-types based on single-cell expression data. Our approach is implemented in the plsgenomics R-package. ghislain.durif@inria.fr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  1. Nanodevices and a new approach to the problem of recognition and destruction of cancer cells in vivo

    Energy Technology Data Exchange (ETDEWEB)

    Namiot, V.A., E-mail: vnamiot@gmail.com

    2013-11-22

    We suggest for recognition and destruction of cancer cells in vivo to introduce into an organism simultaneously two different interacting nanodevices. Only one of the nanodevices has to be able to recognize cancer cell and mark it. The second nanodevice has to be able to destroy the marked cancer cell. Such process allows increasing the reliability of the cancer cell recognition process and making the process of their destruction rather safe for an organism.

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

    Science.gov (United States)

    Maurer, Bradley Gerald

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

  3. On-line probabilistic classification with particle filters

    DEFF Research Database (Denmark)

    Højen-Sørensen, Pedro; de Freitas, N.; Fog, Torben L.

    2000-01-01

    We apply particle filters to the problem of on-line classification with possibly overlapping classes. This allows us to compute the probabilities of class membership as the classes evolve. Although we adopt neural network classifiers, the work can be extended to any other parametric classification...

  4. CIN classification and prediction using machine learning methods

    Science.gov (United States)

    Chirkina, Anastasia; Medvedeva, Marina; Komotskiy, Evgeny

    2017-06-01

    The aim of this paper is a comparison of the existing classification algorithms with different parameters, and selection those ones, which allows solving the problem of primary diagnosis of cervical intraepithelial neoplasia (CIN), as it characterizes the condition of the body in the precancerous stage. The paper describes a feature selection process, as well as selection of the best models for a multiclass classification.

  5. Classification in mathematics, discrete metric spaces, and approximation by trees

    NARCIS (Netherlands)

    M. Hazewinkel (Michiel)

    1995-01-01

    textabstractThis is partly an introductory survey paper to clustering and classification problems with particular emphasis on the classification of lists of key words and phrases from a given scientific domain such as mathematics. In addition the paper contains a number of new concepts and results;

  6. Designing a Classification System for Internet Offenders: Doing Cognitive Distortions

    Science.gov (United States)

    Hundersmarck, Steven F.; Durkin, Keith F.; Delong, Ronald L.

    2007-01-01

    Televised features such as NBC's "To Catch a Predator" have highlighted the growing problem posed by Internet sexual predators. This paper reports on the authors' attempts in designing a classification system for Internet offenders. The classification system was designed based on existing theory, understanding the nature of Internet offenders and…

  7. Prototype Selection for Classification in Standard and Generalized Dissimilarity Spaces

    NARCIS (Netherlands)

    Plasencia Calaña, Y.

    2015-01-01

    Automatic pattern classification for a given problem domain aims at assigning a class or category membership to a new unseen object from the same domain. This is performed in three main stages: data preprocessing, representation and classification. The data preprocessing highly depends on the data

  8. National School Debate: Banning Cell Phones in Public Schools: Analyzing a National School and Community Relations Problem

    Science.gov (United States)

    Johnson, Clarence; Kritsonis, William Allan

    2007-01-01

    School systems in America face many critical challenges pertaining to regulating cell phone use by students in today's schools. School executives and classroom teachers face challenges daily relative to how to effectively deal with student's using cell phones. There are many drawbacks and benefits for cell phone use by students. The authors…

  9. Ear Problems

    Science.gov (United States)

    ... Infants and Children Chest Pain, Acute Chest Pain, Chronic Cold and Flu Cough Diarrhea Ear Problems Elimination Problems Elimination Problems in Infants and Children Eye Problems Facial Swelling Feeding Problems in Infants ...

  10. Urination Problems

    Science.gov (United States)

    ... Infants and Children Chest Pain, Acute Chest Pain, Chronic Cold and Flu Cough Diarrhea Ear Problems Elimination Problems Elimination Problems in Infants and Children Eye Problems Facial Swelling Feeding Problems in Infants ...

  11. VOCAL SEGMENT CLASSIFICATION IN POPULAR MUSIC

    DEFF Research Database (Denmark)

    Feng, Ling; Nielsen, Andreas Brinch; Hansen, Lars Kai

    2008-01-01

    This paper explores the vocal and non-vocal music classification problem within popular songs. A newly built labeled database covering 147 popular songs is announced. It is designed for classifying signals from 1sec time windows. Features are selected for this particular task, in order to capture...

  12. High-throughput time-stretch imaging flow cytometry for multi-class classification of phytoplankton.

    Science.gov (United States)

    Lai, Queenie T K; Lee, Kelvin C M; Tang, Anson H L; Wong, Kenneth K Y; So, Hayden K H; Tsia, Kevin K

    2016-12-12

    Time-stretch imaging has been regarded as an attractive technique for high-throughput imaging flow cytometry primarily owing to its real-time, continuous ultrafast operation. Nevertheless, two key challenges remain: (1) sufficiently high time-stretch image resolution and contrast is needed for visualizing sub-cellular complexity of single cells, and (2) the ability to unravel the heterogeneity and complexity of the highly diverse population of cells - a central problem of single-cell analysis in life sciences - is required. We here demonstrate an optofluidic time-stretch imaging flow cytometer that enables these two features, in the context of high-throughput multi-class (up to 14 classes) phytoplantkton screening and classification. Based on the comprehensive feature extraction and selection procedures, we show that the intracellular texture/morphology, which is revealed by high-resolution time-stretch imaging, plays a critical role of improving the accuracy of phytoplankton classification, as high as 94.7%, based on multi-class support vector machine (SVM). We also demonstrate that high-resolution time-stretch images, which allows exploitation of various feature domains, e.g. Fourier space, enables further sub-population identification - paving the way toward deeper learning and classification based on large-scale single-cell images. Not only applicable to biomedical diagnostic, this work is anticipated to find immediate applications in marine and biofuel research.

  13. Kappa Coefficients for Circular Classifications

    NARCIS (Netherlands)

    Warrens, Matthijs J.; Pratiwi, Bunga C.

    2016-01-01

    Circular classifications are classification scales with categories that exhibit a certain periodicity. Since linear scales have endpoints, the standard weighted kappas used for linear scales are not appropriate for analyzing agreement between two circular classifications. A family of kappa

  14. Oral epithelial dysplasia classification systems

    DEFF Research Database (Denmark)

    Warnakulasuriya, S; Reibel, J; Bouquot, J

    2008-01-01

    . In this 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...

  15. Borel reductibility and classification of von neumann algebras

    DEFF Research Database (Denmark)

    Sasyk, R.; Törnquist, Asger Dag

    2009-01-01

    We announce some new results regarding the classification problem for separable von Neumann algebras. Our results are obtained by applying the notion of Borel reducibility and Hjorth's theory of turbulence to the isomorphism relation for separable von Neumann algebras....

  16. Comparing complete and partial classification for identifying customers at risk

    NARCIS (Netherlands)

    Bloemer, J.M.M.; Brijs, T.; Swinnen, S.P.; Vanhoof, K.

    2003-01-01

    This paper evaluates complete versus partial classification for the problem of identifying customers at risk. We define customers at risk as customers reporting overall satisfaction, but these customers also possess characteristics that are strongly associated with dissatisfied customers. This

  17. A comparative evaluation of sequence classification programs

    Directory of Open Access Journals (Sweden)

    Bazinet Adam L

    2012-05-01

    Full Text Available Abstract Background A fundamental problem in modern genomics is to taxonomically or functionally classify DNA sequence fragments derived from environmental sampling (i.e., metagenomics. Several different methods have been proposed for doing this effectively and efficiently, and many have been implemented in software. In addition to varying their basic algorithmic approach to classification, some methods screen sequence reads for ’barcoding genes’ like 16S rRNA, or various types of protein-coding genes. Due to the sheer number and complexity of methods, it can be difficult for a researcher to choose one that is well-suited for a particular analysis. Results We divided the very large number of programs that have been released in recent years for solving the sequence classification problem into three main categories based on the general algorithm they use to compare a query sequence against a database of sequences. We also evaluated the performance of the leading programs in each category on data sets whose taxonomic and functional composition is known. Conclusions We found significant variability in classification accuracy, precision, and resource consumption of sequence classification programs when used to analyze various metagenomics data sets. However, we observe some general trends and patterns that will be useful to researchers who use sequence classification programs.

  18. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

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

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases......, the 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....

  19. Software support for irregular and loosely synchronous problems

    Science.gov (United States)

    Choudhary, A.; Fox, G.; Hiranandani, S.; Kennedy, K.; Koelbel, C.; Ranka, S.; Saltz, J.

    1992-01-01

    A large class of scientific and engineering applications may be classified as irregular and loosely synchronous from the perspective of parallel processing. We present a partial classification of such problems. This classification has motivated us to enhance FORTRAN D to provide language support for irregular, loosely synchronous problems. We present techniques for parallelization of such problems in the context of FORTRAN D.

  20. Classification of hand eczema

    DEFF Research Database (Denmark)

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

    2015-01-01

    BACKGROUND: Classification of hand eczema (HE) is mandatory in epidemiological and clinical studies, and also important in clinical work. OBJECTIVES: The aim was to test a recently proposed classification system of HE in clinical practice in a prospective multicentre study. METHODS: Patients were......%) 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...

  1. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    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 classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic...

  2. Two problems in multiphase biological flows: Blood flow and particulate transport in microvascular network, and pseudopod-driven motility of amoeboid cells

    Science.gov (United States)

    Bagchi, Prosenjit

    2016-11-01

    In this talk, two problems in multiphase biological flows will be discussed. The first is the direct numerical simulation of whole blood and drug particulates in microvascular networks. Blood in microcirculation behaves as a dense suspension of heterogeneous cells. The erythrocytes are extremely deformable, while inactivated platelets and leukocytes are nearly rigid. A significant progress has been made in recent years in modeling blood as a dense cellular suspension. However, many of these studies considered the blood flow in simple geometry, e.g., straight tubes of uniform cross-section. In contrast, the architecture of a microvascular network is very complex with bifurcating, merging and winding vessels, posing a further challenge to numerical modeling. We have developed an immersed-boundary-based method that can consider blood cell flow in physiologically realistic and complex microvascular network. In addition to addressing many physiological issues related to network hemodynamics, this tool can be used to optimize the transport properties of drug particulates for effective organ-specific delivery. Our second problem is pseudopod-driven motility as often observed in metastatic cancer cells and other amoeboid cells. We have developed a multiscale hydrodynamic model to simulate such motility. We study the effect of cell stiffness on motility as the former has been considered as a biomarker for metastatic potential. Funded by the National Science Foundation.

  3. Problems of Chernobyl

    International Nuclear Information System (INIS)

    Shcherbyin, V.M.

    1998-01-01

    The collection comprises the materials of working meeting 'The Development of Technologies of the 'Ukrytie' Radioactive Waste Management', held on May 20-21, 1997 in Chernobyl. The results of research work of the experts of Ukraine and other countries directed on solving problems, concerning removal of fuel containing materials and other radioactive waste from destroyed Unit 4 of Chernobyl NPP are given. The data on waste quantities, their location and classification, strategy of waste management and some technologies are described

  4. A Comparison of a Standard Genetic Algorithm with a Hybrid Genetic Algorithm Applied to Cell Formation Problem

    Directory of Open Access Journals (Sweden)

    Waqas Javaid

    2014-09-01

    Full Text Available Though there are a number of benefits associated with cellular manufacturing systems, its implementation (identification of part families and corresponding machine groups for real life problems is still a challenging task. To handle the complexity of optimizing multiple objectives and larger size of the problem, most of the researchers in the past two decades or so have focused on developing genetic algorithm (GA based techniques. Recently this trend has shifted from standard GA to hybrid GA (HGA based approaches in the quest for greater effectiveness as far as convergence on to the optimum solution is concerned. In order to prove the point, that HGAs possess better convergence abilities than standard GAs, a methodology, initially based on standard GA and later on hybridized with a local search heuristic (LSH, has been developed during this research. Computational experience shows that HGA maintains its accuracy level with increase in problem size, whereas standard GA looses its effectiveness as the problem size grows.

  5. Morphological Neuron Classification Using Machine Learning

    Science.gov (United States)

    Vasques, Xavier; Vanel, Laurent; Villette, Guillaume; Cif, Laura

    2016-01-01

    Classification and quantitative characterization of neuronal morphologies from histological neuronal reconstruction is challenging since it is still unclear how to delineate a neuronal cell class and which are the best features to define them by. The morphological neuron characterization represents a primary source to address anatomical comparisons, morphometric analysis of cells, or brain modeling. The objectives of this paper are (i) to develop and integrate a pipeline that goes from morphological feature extraction to classification and (ii) to assess and compare the accuracy of machine learning algorithms to classify neuron morphologies. The algorithms were trained on 430 digitally reconstructed neurons subjectively classified into layers and/or m-types using young and/or adult development state population of the somatosensory cortex in rats. For supervised algorithms, linear discriminant analysis provided better classification results in comparison with others. For unsupervised algorithms, the affinity propagation and the Ward algorithms provided slightly better results. PMID:27847467

  6. Problems in problem analysis

    DEFF Research Database (Denmark)

    Almegaard, Henrik

    2014-01-01

    The majority of literature on engineering design methods is focused on the processes of fulfilling the design goals as efficiently as possible. This paper will focus on - and discuss - the processes of determining the design goals: the specifications. The purpose is to draw attention to the inher...... to the inherent problems, dilemmas and possibilities in these processes bearing in mind that that the most important decisions in a design project are taken in the beginning of the project....

  7. An efficient abnormal cervical cell detection system based on multi-instance extreme learning machine

    Science.gov (United States)

    Zhao, Lili; Yin, Jianping; Yuan, Lihuan; Liu, Qiang; Li, Kuan; Qiu, Minghui

    2017-07-01

    Automatic detection of abnormal cells from cervical smear images is extremely demanded in annual diagnosis of women's cervical cancer. For this medical cell recognition problem, there are three different feature sections, namely cytology morphology, nuclear chromatin pathology and region intensity. The challenges of this problem come from feature combination s and classification accurately and efficiently. Thus, we propose an efficient abnormal cervical cell detection system based on multi-instance extreme learning machine (MI-ELM) to deal with above two questions in one unified framework. MI-ELM is one of the most promising supervised learning classifiers which can deal with several feature sections and realistic classification problems analytically. Experiment results over Herlev dataset demonstrate that the proposed method outperforms three traditional methods for two-class classification in terms of well accuracy and less time.

  8. Latent Classification Models for Binary Data

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2009-01-01

    the class of that instance. To relax this independence assumption, we have in previous work proposed a family of models, called latent classification models (LCMs). LCMs are defined for continuous domains and generalize the naive Bayes model by using latent variables to model class-conditional dependencies...... between the attributes. In addition to providing good classification accuracy, the LCM model has several appealing properties, including a relatively small parameter space making it less susceptible to over-fitting. In this paper we take a first-step towards generalizing LCMs to hybrid domains...... of different domains, including the problem of recognizing symbols in black and white images....

  9. [Clinical aspects and classification of echinococcosis].

    Science.gov (United States)

    Nabokov, Sh A; Vasil'ev, R Kh

    1978-04-01

    350 cases of alveococcosis were examined with the use of clinical and generally available methods of laboratory analysis. This study helped to find out the characteristic symptoms of the disease and their incidence rate. A clinico-anatomical classification of alveoccoccosis, based on local and general manifestations, localization of a primary focus, anatomic form of the growth of an alveococcal node and the degree of its propagation in the liver parenchima, has been developed. The suggested classification promotes a correct construction of a detailed clinical diagnosis and complete solution of the problems of therapeutic tactics.

  10. CLASSIFICATION OF VIRUSES

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. CLASSIFICATION OF VIRUSES. On basis of morphology. On basis of chemical composition. On basis of structure of genome. On basis of mode of replication. Notes:

  11. Update on diabetes classification.

    Science.gov (United States)

    Thomas, Celeste C; Philipson, Louis H

    2015-01-01

    This article highlights the difficulties in creating a definitive classification of diabetes mellitus in the absence of a complete understanding of the pathogenesis of the major forms. This brief review shows the evolving nature of the classification of diabetes mellitus. No classification scheme is ideal, and all have some overlap and inconsistencies. The only diabetes in which it is possible to accurately diagnose by DNA sequencing, monogenic diabetes, remains undiagnosed in more than 90% of the individuals who have diabetes caused by one of the known gene mutations. The point of classification, or taxonomy, of disease, should be to give insight into both pathogenesis and treatment. It remains a source of frustration that all schemes of diabetes mellitus continue to fall short of this goal. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Learning Apache Mahout classification

    CERN Document Server

    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.

  13. AN Information Text Classification Algorithm Based on DBN

    Directory of Open Access Journals (Sweden)

    LU Shu-bao

    2017-04-01

    Full Text Available Aiming at the problem of low categorization accuracy and uneven distribution of the traditional text classification algorithms,a text classification algorithm based on deep learning has been put forward. Deep belief networks have very strong feature learning ability,which can be extracted from the high dimension of the original feature,so that the text classification can not only be considered,but also can be used to train classification model. The formula of TF-IDF is used to compute text eigenvalues,and the deep belief networks are used to construct the classifier. The experimental results show that compared with the commonly used classification algorithms such as support vector machine,neural network and extreme learning machine,the algorithm has higher accuracy and practicability,and it has opened up new ideas for the research of text classification.

  14. Feature fusion using locally linear embedding for classification.

    Science.gov (United States)

    Sun, Bing-Yu; Zhang, Xiao-Ming; Li, Jiuyong; Mao, Xue-Min

    2010-01-01

    In most complex classification problems, many types of features have been captured or extracted. Feature fusion is used to combine features for better classification and to reduce data dimensionality. Kernel-based feature fusion methods are very effective for classification, but they do not reduce data dimensionality. In this brief, we propose an effective feature fusion method using locally linear embedding (LLE). The proposed method overcomes the limitations of LLE, which could not handle different types of features and is inefficient for classification. We propose an efficient algorithm to solve the optimization problem in obtaining weights of different features, and design an efficient method for LLE-based classification. In comparison to other kernel-based feature fusion methods, the proposed method fuses features to a significantly lower dimensional feature space with the same discriminant power. We have conducted experiments to demonstrate the effectiveness of the proposed feature fusion method.

  15. Latent classification models

    DEFF Research Database (Denmark)

    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...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  16. Multilingual News Article Classification

    OpenAIRE

    Skjennum, Patrick L

    2016-01-01

    News is an ever-growing and global resource, reliant on robust distribution networks to spread information. This thesis investigates how exploiting semantic, contextual and ontological information may form a basis for a language independent news article classification system. In light of the above, a scalable multi-label news article classification system, based exclusively on extracted DBpedia entities, and a predetermined standardized set of fixed-size IPTC Media Topic categories, is p...

  17. Balance Problems

    Science.gov (United States)

    ... often, it could be a sign of a balance problem. Balance problems can make you feel unsteady. You may ... related injuries, such as a hip fracture. Some balance problems are due to problems in the inner ...

  18. Knowledge base image classification using P-trees

    Science.gov (United States)

    Seetha, M.; Ravi, G.

    2010-02-01

    Image Classification is the process of assigning classes to the pixels in remote sensed images and important for GIS applications, since the classified image is much easier to incorporate than the original unclassified image. To resolve misclassification in traditional parametric classifier like Maximum Likelihood Classifier, the neural network classifier is implemented using back propagation algorithm. The extra spectral and spatial knowledge acquired from the ancillary information is required to improve the accuracy and remove the spectral confusion. To build knowledge base automatically, this paper explores a non-parametric decision tree classifier to extract knowledge from the spatial data in the form of classification rules. A new method is proposed using a data structure called Peano Count Tree (P-tree) for decision tree classification. The Peano Count Tree is a spatial data organization that provides a lossless compressed representation of a spatial data set and facilitates efficient classification than other data mining techniques. The accuracy is assessed using the parameters overall accuracy, User's accuracy and Producer's accuracy for image classification methods of Maximum Likelihood Classification, neural network classification using back propagation, Knowledge Base Classification, Post classification and P-tree Classifier. The results reveal that the knowledge extracted from decision tree classifier and P-tree data structure from proposed approach remove the problem of spectral confusion to a greater extent. It is ascertained that the P-tree classifier surpasses the other classification techniques.

  19. Exact smooth classification of Hamiltonian vector fields on symplectic 2-manifolds

    International Nuclear Information System (INIS)

    Krouglikov, B.S.

    1994-10-01

    Complete exact classification of Hamiltonian systems with one degree of freedom and Morse Hamiltonian is carried out. As it is a main part of trajectory classification of integrable Hamiltonian systems with two degrees of freedom, the corresponding generalization is considered. The dual problem of classification of symplectic form together with Morse foliation is carried out as well. (author). 10 refs, 16 figs

  20. Classification of Small UAVs and Birds by Micro-Doppler Signatures

    NARCIS (Netherlands)

    Molchanov, P.; Egiazarian, K.; Astola, J.; Harmanny, R.I.A.; Wit, J.J.M. de

    2013-01-01

    The problem of unmanned aerial vehicles classification using continuous wave radar is considered in this paper. Classification features are extracted from micro-Doppler signature. Before the classification, the micro-Doppler signature is filtered and aligned to compensate the Doppler shift caused by

  1. Combining decision trees and stochastic curtailment for assessment length reduction of test batteries used for classification.

    NARCIS (Netherlands)

    Fokkema, M.; Smits, N.; Kelderman, H.; Carlier, I.V.E.; van Hemert, A.M.

    2014-01-01

    For classification problems in psychology (e.g., clinical diagnosis), batteries of tests are often administered. However, not every test or item may be necessary for accurate classification. In the current article, a combination of classification and regression trees (CART) and stochastic

  2. Molecular Biology of the Cell, Sixth Edition; ISBN: 9780815344643; and Molecular Biology of the Cell, Sixth Edition, The Problems Book; ISBN 9780815344537

    Directory of Open Access Journals (Sweden)

    Stephen Bustin

    2015-11-01

    Full Text Available The latest edition maintains the excellence and appeal of the previous editions. Its clear text and outstanding illustrations, together with the complementary problems book make this an essential companion for students and lecturers alike.

  3. [Population problem, comprehension problem].

    Science.gov (United States)

    Tallon, F

    1993-08-01

    Overpopulation of developing countries in general, and Rwanda in particular, is not just their problem but a problem for developed countries as well. Rapid population growth is a key factor in the increase of poverty in sub-Saharan Africa. Population growth outstrips food production. Africa receives more and more foreign food, economic, and family planning aid each year. The Government of Rwanda encourages reduced population growth. Some people criticize it, but this criticism results in mortality and suffering. One must combat this ignorance, but attitudes change slowly. Some of these same people find the government's acceptance of family planning an invasion of their privacy. Others complain that rich countries do not have campaigns to reduce births, so why should Rwanda do so? The rate of schooling does not increase in Africa, even though the number of children in school increases, because of rapid population growth. Education is key to improvements in Africa's socioeconomic growth. Thus, Africa, is underpopulated in terms of potentiality but overpopulated in terms of reality, current conditions, and possibilities of overexploitation. Africa needs to invest in human resources. Families need to save, and to so, they must refrain from having many children. Africa should resist the temptation to waste, as rich countries do, and denounce it. Africa needs to become more independent of these countries, but structural adjustment plans, growing debt, and rapid population growth limit national independence. Food aid is a means for developed countries to dominate developing countries. Modernization through foreign aid has had some positive effects on developing countries (e.g., improved hygiene, mortality reduction), but these also sparked rapid population growth. Rwandan society is no longer traditional, but it is also not yet modern. A change in mentality to fewer births, better quality of life for living infants, better education, and less burden for women must occur

  4. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

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

  5. Classification of Dynamic Vehicle Routing Systems

    DEFF Research Database (Denmark)

    Larsen, Allan; Madsen, Oli B.G.; Solomon, Marius M.

    2007-01-01

    This chapter discusses important characteristics seen within dynamic vehicle routing problems. We discuss the differences between the traditional static vehicle routing problems and its dynamic counterparts. We give an in-depth introduction to the degree of dynamism measure which can be used...... to classify dynamic vehicle routing systems. Methods for evaluation of the performance of algorithms that solve on-line routing problems are discussed and we list some of the most important issues to include in the system objective. Finally, we provide a three-echelon classification of dynamic vehicle routing...... systems based on their degree of dynamism and the system objective....

  6. Known TCP Implementation Problems

    Science.gov (United States)

    Paxson, Vern (Editor); Allman, Mark; Dawson, Scott; Fenner, William; Griner, Jim; Heavens, Ian; Lahey, K.; Semke, J.; Volz, B.

    1999-01-01

    This memo catalogs a number of known TCP implementation problems. The goal in doing so is to improve conditions in the existing Internet by enhancing the quality of current TCP/IP implementations. It is hoped that both performance and correctness issues can be resolved by making implementors aware of the problems and their solutions. In the long term, it is hoped that this will provide a reduction in unnecessary traffic on the network, the rate of connection failures due to protocol errors, and load on network servers due to time spent processing both unsuccessful connections and retransmitted data. This will help to ensure the stability of the global Internet. Each problem is defined as follows: Name of Problem The name associated with the problem. In this memo, the name is given as a subsection heading. Classification one or more problem categories for which the problem is classified: "congestion control", "performance", "reliability", "resource management". Description A definition of the problem, succinct but including necessary background material. Significance A brief summary of the sorts of environments for which the problem is significant.

  7. A hybrid approach to solving the problem of design of nuclear fuel cells; Un enfoque hibrido para la solucion del problema del diseno de celdas de combustible nuclear

    Energy Technology Data Exchange (ETDEWEB)

    Montes T, J. L.; Perusquia del C, R.; Ortiz S, J. J.; Castillo, A., E-mail: joseluis.montes@inin.gob.mx [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)

    2015-09-15

    An approach to solving the problem of fuel cell design for BWR power reactor is presented. For this purpose the hybridization of a method based in heuristic knowledge rules called S15 and the advantages of a meta-heuristic method is proposed. The synergy of potentialities of both techniques allows finding solutions of more quality. The quality of each solution is obtained through a multi-objective function formed from the main cell parameters that are provided or obtained during the simulation with the CASMO-4 code. To evaluate this alternative of solution nuclear fuel cells of reference of nuclear power plant of Laguna Verde were used. The results show that in a systematic way the results improve when both methods are coupled. As a result of the hybridization process of the mentioned techniques an improvement is achieved in a range of 2% with regard to the achieved results in an independent way by the S15 method. (Author)

  8. A hierarchical classification of first-order recurrent neural networks.

    Science.gov (United States)

    Cabessa, Jérémie; Vill, Alessandro E P

    2010-12-31

    We provide a decidable hierarchical classification of first-order recurrent neural networks made up of McCulloch and Pitts cells. This classification is achieved by proving an equivalence result between such neural networks and deterministic Büuchi automata, and then translating the Wadge classification theory from the abstract machine to the neural network context. The obtained hierarchy of neural networks is proved to have width 2 and height omega + 1, and a decidability procedure of this hierarchy is provided. Notably, this classification is shown to be intimately related to the attractive properties of the considered networks.

  9. [Globally harmonized system of classification and labelling of chemicals (GHS) and its implementation in Japan].

    Science.gov (United States)

    Miyagawa, Muneyuki

    2010-01-01

    The Globally Harmonized System of Classification and Labelling of Chemicals (GHS) is a set of recommendations by the United Nations, first issued in 2003 as a communication tool for the sound management of chemicals, comprising harmonized classification criteria for physical, health and environmental hazards, a unified format for material safety data sheets (MSDS), and labeling elements including pictograms and hazard statements preassigned to each classification category. The GHS has been introduced into Japan and implemented in the regulatory framework for chemical safety. The Japanese Industrial Standards (JIS) adopted the GHS, and the GHS-based JIS rules have become the Japanese standards for labels and MSDS. The use of the JIS format for labels and MSDS is recommended by several competent authorities in Japan although mostly on a voluntary basis. In the workplace, however, GHS-based JIS labels and MSDS have become legal requirements by the Industrial Safety and Health Law since 2006; namely, issuing MSDS in such a format is mandatory for the 640 specified chemicals and also labeling for the 99 targeted chemicals*. Although the GHS provides definitions and classification criteria for 10 classes of health hazards (acute toxicity, skin and eye corrosion/irritation, sensitization, germ cell mutagenicity, carcinogenicity, reproductive toxicity, specific target organ toxicity single/repeated exposures, and aspiration hazard), it does not provide actual classification of chemicals, so that competent authorities and industries need to classify a number of chemicals and/or mixtures. Weight-of-evidence judgment and/or expert judgment would be necessary in many cases. In this paper, the outline of the GHS classification is described and problems of the GHS and its implementation are discussed.

  10. Mixing linear SVMs for nonlinear classification.

    Science.gov (United States)

    Fu, Zhouyu; Robles-Kelly, Antonio; Zhou, Jun

    2010-12-01

    In this paper, we address the problem of combining linear support vector machines (SVMs) for classification of large-scale nonlinear datasets. The motivation is to exploit both the efficiency of linear SVMs (LSVMs) in learning and prediction and the power of nonlinear SVMs in classification. To this end, we develop a LSVM mixture model that exploits a divide-and-conquer strategy by partitioning the feature space into subregions of linearly separable datapoints and learning a LSVM for each of these regions. We do this implicitly by deriving a generative model over the joint data and label distributions. Consequently, we can impose priors on the mixing coefficients and do implicit model selection in a top-down manner during the parameter estimation process. This guarantees the sparsity of the learned model. Experimental results show that the proposed method can achieve the efficiency of LSVMs in the prediction phase while still providing a classification performance comparable to nonlinear SVMs.

  11. Iris Data Classification Using Quantum Neural Networks

    International Nuclear Information System (INIS)

    Sahni, Vishal; Patvardhan, C.

    2006-01-01

    Quantum computing is a novel paradigm that promises to be the future of computing. The performance of quantum algorithms has proved to be stunning. ANN within the context of classical computation has been used for approximation and classification tasks with some success. This paper presents an idea of quantum neural networks along with the training algorithm and its convergence property. It synergizes the unique properties of quantum bits or qubits with the various techniques in vogue in neural networks. An example application of Fisher's Iris data set, a benchmark classification problem has also been presented. The results obtained amply demonstrate the classification capabilities of the quantum neuron and give an idea of their promising capabilities

  12. Classification of sudden and arrhythmic death

    DEFF Research Database (Denmark)

    Torp-Pedersen, C; Køber, L; Elming, H

    1997-01-01

    Since all death is (eventually) sudden and associated with cardiac arrhythmias, the concept of sudden death is only meaningful if it is unexpected, while arrhythmic death is only meaningful if life could have continued had the arrhythmia been prevented or treated. Current classifications of death...... as being arrhythmic or sudden are all biased by the difficulty of having to decide on the degree of unexpectedness or the likelihood that life could continue without the arrhythmia. The uncertainties are enlarged by the fact that critical data (such as knowledge of arrhythmias at the time of death...... or autopsy) are available in only a few percent of cases. A main problem in using classifications is the lack of validation data. This situation has, with the MADIT trial, changed in the case of the Thaler and Hinkle classification of arrhythmic death. The MADIT trial demonstrated that arrhythmic death...

  13. Towards Automatic Classification of Wikipedia Content

    Science.gov (United States)

    Szymański, Julian

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

  14. Dense Iterative Contextual Pixel Classification using Kriging

    DEFF Research Database (Denmark)

    Ganz, Melanie; Loog, Marco; Brandt, Sami

    2009-01-01

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

  15. Diagnosis and classification of autoimmune hemolytic anemia.

    Science.gov (United States)

    Bass, Garrett F; Tuscano, Emily T; Tuscano, Joseph M

    2014-01-01

    Uncompensated autoantibody-mediated red blood cell (RBC) consumption is the hallmark of autoimmune hemolytic anemia (AIHA). Classification of AIHA is pathophysiologically based and divides AIHA into warm, mixed or cold-reactive subtypes. This thermal-based classification is based on the optimal autoantibody-RBC reactivity temperatures. AIHA is further subcategorized into idiopathic and secondary with the later being associated with a number of underlying infectious, neoplastic and autoimmune disorders. In most cases AIHA is confirmed by a positive direct antiglobulin test (DAT). The standard therapeutic approaches to treatment of AIHA include corticosteroids, splenectomy, immunosuppressive agents and monoclonal antibodies. Published by Elsevier B.V.

  16. Clinical classification of syncope.

    Science.gov (United States)

    Sutton, Richard

    2013-01-01

    Syncope is a presenting symptom, and in itself is not a diagnosis. An etiology or a mechanism must be sought in all cases. Currently, most clinicians classify syncope on clinical grounds by attempting to ascertain its etiology. They then use this classification to guide further management. Using this approach, reflex syncope is the most common form of syncope, occurring in approximately 60% of syncope presentations. Orthostatic hypotension presents in around 15% with arrhythmic syncope in 10% and structural heart disease as the cause of syncope in 5%; in 10% of patients no diagnosis is made. An alternative classification system uses the mechanism of syncope derived from an implanted ECG loop recorder (ILR). While this approach may be of value for optimizing therapy, it cannot be considered as the primary classification since ILRs are not typically implanted early in the evaluation process of most patients. ILRs are usually placed after "risk stratification" in those deemed not to be at high risk but remain in the uncertain etiology category. Furthermore, there exists, in current ILR technology, lack of ambulatory blood pressure monitoring capability. Thus, vasodilation leading to hypotension, the main trigger of cerebral hypoperfusion other than bradycardia, cannot be detected and is currently unavailable for use in a mechanistic-based classification. Thus, the etiological classification remains the basis for both risk stratification and subsequent clinical management. Copyright © 2013 Elsevier Inc. All rights reserved.

  17. Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

    OpenAIRE

    Moran, Emilio Federico.

    2010-01-01

    High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervi...

  18. HYPERSPECTRAL DATA CLASSIFICATION USING FACTOR GRAPHS

    Directory of Open Access Journals (Sweden)

    A. Makarau

    2012-07-01

    each class and comparison of the probabilities leads to classification. Since the factor graphs operate on input data represented on an alphabet (the represented data transferred into multinomial distribution the number of training samples can be relatively low. Classification assessment on Salinas hyperspectral data benchmark allowed to obtain a competitive accuracy of classification. Employment of training data consisting of 20 randomly selected points for a class allowed to obtain the overall classification accuracy equal to 85.32% and Kappa equal to 0.8358. Representation of input data on a finite domain discards the curse of dimensionality problem allowing to use large hyperspectral data with a moderately high number of bands.

  19. Classification of diabetic foot ulcers.

    Science.gov (United States)

    Game, Frances

    2016-01-01

    It is known that the relative importance of factors involved in the development of diabetic foot problems can vary in both their presence and severity between patients and lesions. This may be one of the reasons why outcomes seem to vary centre to centre and why some treatments may seem more effective in some people than others. There is a need therefore to classify and describe lesions of the foot in patients with diabetes in a manner that is agreed across all communities but is simple to use in clinical practice. No single system is currently in widespread use, although a number have been published. Not all are well validated outside the system from which they were derived, and it has not always been made clear the clinical purposes to which such classifications should be put to use, whether that be for research, clinical description in routine clinical care or audit. Here the currently published classification systems, their validation in clinical practice, whether they were designed for research, audit or clinical care, and the strengths and weaknesses of each are explored. Copyright © 2016 John Wiley & Sons, Ltd.

  20. A new incomplete pattern classification method based on evidential reasoning.

    Science.gov (United States)

    Liu, Zhun-Ga; Pan, Quan; Mercier, Gregoire; Dezert, Jean

    2015-04-01

    The classification of incomplete patterns is a very challenging task because the object (incomplete pattern) with different possible estimations of missing values may yield distinct classification results. The uncertainty (ambiguity) of classification is mainly caused by the lack of information of the missing data. A new prototype-based credal classification (PCC) method is proposed to deal with incomplete patterns thanks to the belief function framework used classically in evidential reasoning approach. The class prototypes obtained by training samples are respectively used to estimate the missing values. Typically, in a c -class problem, one has to deal with c prototypes, which yield c estimations of the missing values. The different edited patterns based on each possible estimation are then classified by a standard classifier and we can get at most c distinct classification results for an incomplete pattern. Because all these distinct classification results are potentially admissible, we propose to combine them all together to obtain the final classification of the incomplete pattern. A new credal combination method is introduced for solving the classification problem, and it is able to characterize the inherent uncertainty due to the possible conflicting results delivered by different estimations of the missing values. The incomplete patterns that are very difficult to classify in a specific class will be reasonably and automatically committed to some proper meta-classes by PCC method in order to reduce errors. The effectiveness of PCC method has been tested through four experiments with artificial and real data sets.

  1. Simple agarose micro-confinement array and machine-learning-based classification for analyzing the patterned differentiation of mesenchymal stem cells.

    Directory of Open Access Journals (Sweden)

    Nobuyuki Tanaka

    Full Text Available The geometrical confinement of small cell colonies gives differential cues to cells sitting at the periphery versus the core. To utilize this effect, for example to create spatially graded differentiation patterns of human mesenchymal stem cells (hMSCs in vitro or to investigate underpinning mechanisms, the confinement needs to be robust for extended time periods. To create highly repeatable micro-fabricated structures for cellular patterning and high-throughput data mining, we employed here a simple casting method to fabricate more than 800 adhesive patches confined by agarose micro-walls. In addition, a machine learning based image processing software was developed (open code to detect the differentiation patterns of the population of hMSCs automatically. Utilizing the agarose walls, the circular patterns of hMSCs were successfully maintained throughout 15 days of cell culture. After staining lipid droplets and alkaline phosphatase as the markers of adipogenic and osteogenic differentiation, respectively, the mega-pixels of RGB color images of hMSCs were processed by the software on a laptop PC within several minutes. The image analysis successfully showed that hMSCs sitting on the more central versus peripheral sections of the adhesive circles showed adipogenic versus osteogenic differentiation as reported previously, indicating the compatibility of patterned agarose walls to conventional microcontact printing. In addition, we found a considerable fraction of undifferentiated cells which are preferentially located at the peripheral part of the adhesive circles, even in differentiation-inducing culture media. In this study, we thus successfully demonstrated a simple framework for analyzing the patterned differentiation of hMSCs in confined microenvironments, which has a range of applications in biology, including stem cell biology.

  2. A cell-centred finite volume method for the Poisson problem on non-graded quadtrees with second order accurate gradients

    Science.gov (United States)

    Batty, Christopher

    2017-02-01

    This paper introduces a two-dimensional cell-centred finite volume discretization of the Poisson problem on adaptive Cartesian quadtree grids which exhibits second order accuracy in both the solution and its gradients, and requires no grading condition between adjacent cells. At T-junction configurations, which occur wherever resolution differs between neighboring cells, use of the standard centred difference gradient stencil requires that ghost values be constructed by interpolation. To properly recover second order accuracy in the resulting numerical gradients, prior work addressing block-structured grids and graded trees has shown that quadratic, rather than linear, interpolation is required; the gradients otherwise exhibit only first order convergence, which limits potential applications such as fluid flow. However, previous schemes fail or lose accuracy in the presence of the more complex T-junction geometries arising in the case of general non-graded quadtrees, which place no restrictions on the resolution of neighboring cells. We therefore propose novel quadratic interpolant constructions for this case that enable second order convergence by relying on stencils oriented diagonally and applied recursively as needed. The method handles complex tree topologies and large resolution jumps between neighboring cells, even along the domain boundary, and both Dirichlet and Neumann boundary conditions are supported. Numerical experiments confirm the overall second order accuracy of the method in the L∞ norm.

  3. Bosniak classification system

    DEFF Research Database (Denmark)

    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...

  4. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    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...

  5. Benchmarking B-Cell Epitope Prediction for the Design of Peptide-Based Vaccines: Problems and Prospects

    Directory of Open Access Journals (Sweden)

    Salvador Eugenio C. Caoili

    2010-01-01

    Full Text Available To better support the design of peptide-based vaccines, refinement of methods to predict B-cell epitopes necessitates meaningful benchmarking against empirical data on the cross-reactivity of polyclonal antipeptide antibodies with proteins, such that the positive data reflect functionally relevant cross-reactivity (which is consistent with antibody-mediated change in protein function and the negative data reflect genuine absence of cross-reactivity (rather than apparent absence of cross-reactivity due to artifactual masking of B-cell epitopes in immunoassays. These data are heterogeneous in view of multiple factors that complicate B-cell epitope prediction, notably physicochemical factors that define key structural differences between immunizing peptides and their cognate proteins (e.g., unmatched electrical charges along the peptide-protein sequence alignments. If the data are partitioned with respect to these factors, iterative parallel benchmarking against the resulting subsets of data provides a basis for systematically identifying and addressing the limitations of methods for B-cell epitope prediction as applied to vaccine design.

  6. Pulmonary function in children and adolescents with sickle cell disease: have we paid proper attention to this problem?

    Directory of Open Access Journals (Sweden)

    Ana Karine Vieira

    Full Text Available ABSTRACT Objective: To evaluate pulmonary function and functional capacity in children and adolescents with sickle cell disease. Methods: This was a cross-sectional study involving 70 children and adolescents (8-15 years of age with sickle cell disease who underwent pulmonary function tests (spirometry and functional capacity testing (six-minute walk test. The results of the pulmonary function tests were compared with variables related to the severity of sickle cell disease and history of asthma and of acute chest syndrome. Results: Of the 64 patients who underwent spirometry, 15 (23.4% showed abnormal results: restrictive lung disease, in 8 (12.5%; and obstructive lung disease, in 7 (10.9%. Of the 69 patients who underwent the six-minute walk test, 18 (26.1% showed abnormal results regarding the six-minute walk distance as a percentage of the predicted value for age, and there was a ≥ 3% decrease in SpO2 in 36 patients (52.2%. Abnormal pulmonary function was not significantly associated with any of the other variables studied, except for hypoxemia and restrictive lung disease. Conclusions: In this sample of children and adolescents with sickle cell disease, there was a significant prevalence of abnormal pulmonary function. The high prevalence of respiratory disorders suggests the need for a closer look at the lung function of this population, in childhood and thereafter.

  7. Psychopathology and classification in psychiatry.

    Science.gov (United States)

    Goldberg, David

    2015-01-01

    The strengths and weaknesses of the 5th edition of the Diagnostic and Statistical Manual of the American Psychiatric Association are considered, and the likely form of the revised version of the International Classification of Disease, due to be released in the future is briefly considered. It is argued that there are a number of problems in the checklist approach to diagnosis: there are no points of rarity between common disorders, and that many disorders are rough groupings containing highly heterogeneous syndromes. The tendency to reify these disorders and to view them as independent entities, and to stretch the concept of co-morbidity to cover individuals who satisfy more than one of the diagnostic checklists is seen as being misleading as it gives a false air of precision. Two broadly similar solutions are proposed for an alternative approach to common mental disorders.

  8. Comparative metabolomics approach coupled with cell- and gene-based assays for species classification and anti-inflammatory bioactivity validation of Echinacea plants.

    Science.gov (United States)

    Hou, Chia-Chung; Chen, Chun-Houh; Yang, Ning-Sun; Chen, Yi-Ping; Lo, Chiu-Ping; Wang, Sheng-Yang; Tien, Yin-Jing; Tsai, Pi-Wen; Shyur, Lie-Fen

    2010-11-01

    Echinacea preparations were the top-selling herbal supplements or medicines in the past decade; however, there is still frequent misidentification or substitution of the Echinacea plant species in the commercial Echinacea products with not well chemically defined compositions in a specific preparation. In this report, a comparative metabolomics study, integrating supercritical fluid extraction, gas chromatography/mass spectrometry and data mining, demonstrates that the three most used medicinal Echinacea species, Echinacea purpurea, E. pallida, and E. angustifolia, can be easily classified by the distribution and relative content of metabolites. A mitogen-induced murine skin inflammation study suggested that alkamides were the active anti-inflammatory components present in Echinacea plants. Mixed alkamides and the major component, dodeca-2E,4E,8Z,10Z(E)-tetraenoic acid isobutylamides, were then isolated from E. purpurea root extracts for further bioactivity elucidation. In macrophages, the alkamides significantly inhibited cyclooxygenase 2 (COX-2) activity and the lipopolysaccharide-induced expression of COX-2, inducible nitric oxide synthase and specific cytokines or chemokines [i.e., TNF-α, interleukin (IL)-1α, IL-6, MCP-1, MIP-1β] but elevated heme oxygenase-1 protein expression. Cichoric acid, however, exhibited little or no effect. The results of high-performance liquid chromatography/electron spray ionization/mass spectrometry metabolite profiling of alkamides and phenolic compounds in E. purpurea roots showed that specific phytocompound (i.e., alkamides, cichoric acid and rutin) contents were subject to change under certain post-harvest or abiotic treatment. This study provides new insight in using the emerging metabolomics approach coupled with bioactivity assays for medicinal/nutritional plant species classification, quality control and the identification of novel botanical agents for inflammatory disorders. Copyright © 2010 Elsevier Inc. All rights

  9. Speech Problems

    Science.gov (United States)

    ... Staying Safe Videos for Educators Search English Español Speech Problems KidsHealth / For Teens / Speech Problems What's in ... a person's ability to speak clearly. Some Common Speech and Language Disorders Stuttering is a problem that ...

  10. Classification of iconic images

    OpenAIRE

    Zrianina, Mariia; Kopf, Stephan

    2016-01-01

    Iconic images represent an abstract topic and use a presentation that is intuitively understood within a certain cultural context. For example, the abstract topic “global warming” may be represented by a polar bear standing alone on an ice floe. Such images are widely used in media and their automatic classification can help to identify high-level semantic concepts. This paper presents a system for the classification of iconic images. It uses a variation of the Bag of Visual Words approach wi...

  11. Classification and structural analysis of live and dead salmonella cells using fourier transform infrared (FT-IR) spectroscopy and principle component analysis (PCA)

    Science.gov (United States)

    Fourier Transform Infrared Spectroscopy (FT-IR) was used to detect Salmonella typhimurium and Salmonella enteritidis foodborne bacteria and distinguish between live and dead cells of both serotypes. Bacteria were loaded individually on the ZnSe Attenuated Total Reflection (ATR) crystal surface and s...

  12. Information gathering for CLP classification

    Directory of Open Access Journals (Sweden)

    Ida Marcello

    2011-01-01

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

  13. Hemiequilibrium problems

    Directory of Open Access Journals (Sweden)

    Muhammad Aslam Noor

    2004-01-01

    Full Text Available We consider a new class of equilibrium problems, known as hemiequilibrium problems. Using the auxiliary principle technique, we suggest and analyze a class of iterative algorithms for solving hemiequilibrium problems, the convergence of which requires either pseudomonotonicity or partially relaxed strong monotonicity. As a special case, we obtain a new method for hemivariational inequalities. Since hemiequilibrium problems include hemivariational inequalities and equilibrium problems as special cases, the results proved in this paper still hold for these problems.

  14. Geographical classification of wine and olive oil by means of classification and influence matrix analysis (CAIMAN).

    Science.gov (United States)

    Ballabio, Davide; Mauri, Andrea; Todeschini, Roberto; Buratti, Susanna

    2006-06-16

    Classification and influence matrix analysis (CAIMAN) is a new classification method, recently proposed and based on the influence matrix (also called leverage matrix). Depending on the purposes of the classification analysis, CAIMAN can be used in three outlines: (1) D-CAIMAN is a discriminant classification method, (2) M-CAIMAN is a class modelling method allowing a sample to be classified, not classified at all, or assigned to more than one class (confused) and (3) A-CAIMAN deals with the asymmetric case, where only a reference class needs to be modelled. In this work, the geographic classification of samples of wine and olive oil has been carried out by means of CAIMAN and its results compared with discriminant analysis, by focusing great attention on the model predictive capabilities. The geographic characterization has been carried out on three different datasets: extra virgin olive oils produced in a small area, with a "protected denomination of origin" label, wines with different denominations of origin, but produced in enclosed geographical areas, and olive oils belonging to different production areas. Final results seem to indicate that the application of CAIMAN to the geographical origin identification offers several advantages: first, it shows--on an average basis--good performances; second, it is able to deal in a simple way classification problems related to tipicity, authenticity, and uniqueness characterization, which are of increasing interest in food quality issues.

  15. 76 FR 20840 - Medical Devices; General and Plastic Surgery Devices; Classification of the Low Level Laser...

    Science.gov (United States)

    2011-04-14

    ... lipids from these cells for noninvasive aesthetic use. (b) Classification. Class II (special controls.... FDA-2011-N-0188] Medical Devices; General and Plastic Surgery Devices; Classification of the Low Level.... DATES: This rule is effective May 16, 2011. The classification was effective on August 24, 2010. FOR...

  16. Revised interface-current relations for the unit-cell transport problem in cylindrical and spherical geometries

    International Nuclear Information System (INIS)

    Bogado Leite, S.Q.

    1997-01-01

    Escape and transmission probabilities, defined in terms of both the region the neutron originates from and the region it penetrates, are used to develop new interface-current relations for unit-cells with an arbitrary number of annular regions in cylindrical and spherical geometries. Comparisons with currents, obtained in terms of standard transmission and escape probabilities, as well as with accurate results reported in the literature, are presented for selected situations, showing significant discrepancies between the two models. (author)

  17. Incredibly Versatile Microbial Fuel Cells Innovative Ideas at HES-SO Valais-Wallis for Solving Topical Problems.

    Science.gov (United States)

    Heinzelmann, Elsbeth

    2016-01-01

    At HES-SO Valais-Wallis, Prof. Fabian Fischer is specialized in microbial fuel cells for novel applications that meet the challenge of producing renewable energies. He and his team possess a unique expertise in bioelectric energy vector generation, phosphate extraction (CHIMIA 2015, 69, 296) and the testing of antimicrobial surfaces. Let's take a look behind the scenes of the Institute of Life Technologies in Sion.

  18. Pap-smear Benchmark Data For Pattern Classification

    DEFF Research Database (Denmark)

    Jantzen, Jan; Norup, Jonas; Dounias, Georgios

    2005-01-01

    This case study provides data and a baseline for comparing classification methods. The data consists of 917 images of Pap-smear cells, classified carefully by cyto-technicians and doctors. Each cell is described by 20 numerical features, and the cells fall into 7 classes. A basic data analysis in...

  19. Rule-guided human classification of Volunteered Geographic Information

    Science.gov (United States)

    Ali, Ahmed Loai; Falomir, Zoe; Schmid, Falko; Freksa, Christian

    2017-05-01

    During the last decade, web technologies and location sensing devices have evolved generating a form of crowdsourcing known as Volunteered Geographic Information (VGI). VGI acted as a platform of spatial data collection, in particular, when a group of public participants are involved in collaborative mapping activities: they work together to collect, share, and use information about geographic features. VGI exploits participants' local knowledge to produce rich data sources. However, the resulting data inherits problematic data classification. In VGI projects, the challenges of data classification are due to the following: (i) data is likely prone to subjective classification, (ii) remote contributions and flexible contribution mechanisms in most projects, and (iii) the uncertainty of spatial data and non-strict definitions of geographic features. These factors lead to various forms of problematic classification: inconsistent, incomplete, and imprecise data classification. This research addresses classification appropriateness. Whether the classification of an entity is appropriate or inappropriate is related to quantitative and/or qualitative observations. Small differences between observations may be not recognizable particularly for non-expert participants. Hence, in this paper, the problem is tackled by developing a rule-guided classification approach. This approach exploits data mining techniques of Association Classification (AC) to extract descriptive (qualitative) rules of specific geographic features. The rules are extracted based on the investigation of qualitative topological relations between target features and their context. Afterwards, the extracted rules are used to develop a recommendation system able to guide participants to the most appropriate classification. The approach proposes two scenarios to guide participants towards enhancing the quality of data classification. An empirical study is conducted to investigate the classification of grass

  20. Trends and concepts in fern classification

    Science.gov (United States)

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

    2014-01-01

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

  1. Genetic programming and serial processing for time series classification.

    Science.gov (United States)

    Alfaro-Cid, Eva; Sharman, Ken; Esparcia-Alcázar, Anna I

    2014-01-01

    This work describes an approach devised by the authors for time series classification. In our approach genetic programming is used in combination with a serial processing of data, where the last output is the result of the classification. The use of genetic programming for classification, although still a field where more research in needed, is not new. However, the application of genetic programming to classification tasks is normally done by considering the input data as a feature vector. That is, to the best of our knowledge, there are not examples in the genetic programming literature of approaches where the time series data are processed serially and the last output is considered as the classification result. The serial processing approach presented here fills a gap in the existing literature. This approach was tested in three different problems. Two of them are real world problems whose data were gathered for online or conference competitions. As there are published results of these two problems this gives us the chance to compare the performance of our approach against top performing methods. The serial processing of data in combination with genetic programming obtained competitive results in both competitions, showing its potential for solving time series classification problems. The main advantage of our serial processing approach is that it can easily handle very large datasets.

  2. The demonstration of pulmonary neuroendocrine cell hyperplasia with tumorlets in a patient with chronic cough and a history of multiple medical problems.

    Science.gov (United States)

    Carmichael, Mark G; Zacher, Lisa L

    2005-05-01

    A 58-year-old woman presented with chronic cough felt to be multifactorial secondary to asthma, gastroesophageal reflux disease, and chronic sinusitis. Additional medical history included obstructive sleep apnea, type 2 diabetes, and hypertension. She had a 40- year history of tobacco use, but quit 10 years ago. Her examination was significant for obesity and cobble stoning of the oropharynx. Pulmonary function testing and arterial blood gases were unrevealing. Chest films were normal. High-resolution computed tomography revealed multiple focal lucencies in a mosaic pattern consistent with air trapping and small airways disease. Bronchoscopy revealed normal airways and a noninflammatory bronchoalveolar lavage. Transbronchial biopsies revealed inflammatory infiltrates of the peribronchiolar interstitium. Lung biopsy revealed pulmonary neuroendocrine cell hyperplasia with tumorlets that stained positive for neuroendocrine tissue. We present the case of a woman with chronic cough, multiple medical problems, and pulmonary neuroendocrine cell hyperplasia with tumorlets.

  3. Event Classification using Concepts

    NARCIS (Netherlands)

    Boer, M.H.T. de; Schutte, K.; Kraaij, W.

    2013-01-01

    The semantic gap is one of the challenges in the GOOSE project. In this paper a Semantic Event Classification (SEC) system is proposed as an initial step in tackling the semantic gap challenge in the GOOSE project. This system uses semantic text analysis, multiple feature detectors using the BoW

  4. Shark Teeth Classification

    Science.gov (United States)

    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…

  5. Classification system: Netherlands

    NARCIS (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

  6. Text document classification

    Czech Academy of Sciences Publication Activity Database

    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

  7. Classifications in popular music

    NARCIS (Netherlands)

    van Venrooij, A.; Schmutz, V.; Wright, J.D.

    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

  8. Mimicking human texture classification

    NARCIS (Netherlands)

    Rogowitz, B.E.; van Rikxoort, Eva M.; van den Broek, Egon; Pappas, T.N.; Schouten, Theo E.; Daly, S.J.

    2005-01-01

    In an attempt to mimic human (colorful) texture classification by a clustering algorithm three lines of research have been encountered, in which as test set 180 texture images (both their color and gray-scale equivalent) were drawn from the OuTex and VisTex databases. First, a k-means algorithm was

  9. Classification of myocardial infarction

    DEFF Research Database (Denmark)

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

    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...

  10. Faculty Assignment Classification System.

    Science.gov (United States)

    Whatcom Community Coll., Ferndale, WA.

    This document outlines the point-based faculty assignment classification system in effect at Whatcom Community College (Washington). The purpose of the point system is to provide an equitable and flexible means of compensating faculty members based on a system of assigning quantitative values to tasks. Teaching, which includes classroom…

  11. Steel column base classification

    OpenAIRE

    Jaspart, J.P.; Wald, F.; Weynand, K.; Gresnigt, A.M.

    2008-01-01

    The influence of the rotational characteristics of the column bases on the structural frame response is discussed and specific design criteria for stiffness classification into semi-rigid and rigid joints are derived. The particular case of an industrial portal frame is then considered. Peer reviewed

  12. Principles for ecological classification

    Science.gov (United States)

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

    1999-01-01

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

  13. Ecosystem classification, Chapter 2

    Science.gov (United States)

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

    2011-01-01

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

  14. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    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...

  15. Bosniak classification system

    DEFF Research Database (Denmark)

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

    2015-01-01

    BACKGROUND: The Bosniak classification is a diagnostic tool for the differentiation of cystic changes in the kidney. The process of categorizing renal cysts may be challenging, involving a series of decisions that may affect the final diagnosis and clinical outcome such as surgical management. PU...

  16. An automated cirrus classification

    Science.gov (United States)

    Gryspeerdt, Edward; Quaas, Johannes; Sourdeval, Odran; Goren, Tom

    2017-04-01

    Cirrus clouds play an important role in determining the radiation budget of the earth, but our understanding of the lifecycle and controls on cirrus clouds remains incomplete. Cirrus clouds can have very different properties and development depending on their environment, particularly during their formation. However, the relevant factors often cannot be distinguished using commonly retrieved satellite data products (such as cloud optical depth). In particular, the initial cloud phase has been identified as an important factor in cloud development, but although back-trajectory based methods can provide information on the initial cloud phase, they are computationally expensive and depend on the cloud parametrisations used in re-analysis products. In this work, a classification system (Identification and Classification of Cirrus, IC-CIR) is introduced. Using re-analysis and satellite data, cirrus clouds are separated in four main types: frontal, convective, orographic and in-situ. The properties of these classes show that this classification is able to provide useful information on the properties and initial phase of cirrus clouds, information that could not be provided by instantaneous satellite retrieved cloud properties alone. This classification is designed to be easily implemented in global climate models, helping to improve future comparisons between observations and models and reducing the uncertainty in cirrus clouds properties, leading to improved cloud parametrisations.

  17. Selection of Objective Function For Imbalanced Classification: An Industrial Case Study

    DEFF Research Database (Denmark)

    Khan, Abdul Rauf; Schiøler, Henrik; Kulahci, Murat

    2017-01-01

    In this article we discuss the issue of selecting suitable objective function for Genetic Algorithm to solve an imbalanced classification problem. More precisely, first we discuss the need of specialized objective function to solve a real classification problem from our industrial partner...

  18. Prevalence of problematic cell phone use in an adult population in Spain as assessed by the Mobile Phone Problem Use Scale (MPPUS.

    Directory of Open Access Journals (Sweden)

    José de-Sola

    Full Text Available Problematic cell phone use has alarmingly increased in industrialized countries in the past 10 years. For many perpetrators, it can turn into a behavioural addiction, although this is not a recognized medical condition. Although there are many tools for evaluating this use, one of the most widely used tools is the Mobile Phone Problematic Use Scale (MPPUS, which we test on a representative sample of the population in Spain to obtain an estimate of the prevalence of problematic cell phone use in our midst. The age range consists of 16-65 years, with 1,126 surveys conducted. In this population, we verify that the reliability and internal consistency of the MPPUS (α = 0.939 are maintained. Additionally, the construct validity, considering the derived factors (Abuse and Dependence, Craving and Loss of Control, and Dependence on the Social Environment are aligned with other research and with diverse external criteria of addiction. We establish four categories of users (Casual, Regular, At Risk, and Problematic and obtain a prevalence of 15.4% among At Risk Users and 5.1% among Problematic Users. This finding implies a total of 20.5% of Users with Problems. A binary logistic regression analysis shows that age, gender, level of education, and daily cell phone use predict problematic cell phone use. The results, based on multiple criteria, show that such problematic use shares features of recognized addictions, affecting large segments of the population and not only adolescents.

  19. Prevalence of problematic cell phone use in an adult population in Spain as assessed by the Mobile Phone Problem Use Scale (MPPUS).

    Science.gov (United States)

    de-Sola, José; Talledo, Hernán; Rodríguez de Fonseca, Fernando; Rubio, Gabriel

    2017-01-01

    Problematic cell phone use has alarmingly increased in industrialized countries in the past 10 years. For many perpetrators, it can turn into a behavioural addiction, although this is not a recognized medical condition. Although there are many tools for evaluating this use, one of the most widely used tools is the Mobile Phone Problematic Use Scale (MPPUS), which we test on a representative sample of the population in Spain to obtain an estimate of the prevalence of problematic cell phone use in our midst. The age range consists of 16-65 years, with 1,126 surveys conducted. In this population, we verify that the reliability and internal consistency of the MPPUS (α = 0.939) are maintained. Additionally, the construct validity, considering the derived factors (Abuse and Dependence, Craving and Loss of Control, and Dependence on the Social Environment) are aligned with other research and with diverse external criteria of addiction. We establish four categories of users (Casual, Regular, At Risk, and Problematic) and obtain a prevalence of 15.4% among At Risk Users and 5.1% among Problematic Users. This finding implies a total of 20.5% of Users with Problems. A binary logistic regression analysis shows that age, gender, level of education, and daily cell phone use predict problematic cell phone use. The results, based on multiple criteria, show that such problematic use shares features of recognized addictions, affecting large segments of the population and not only adolescents.

  20. Prevalence of problematic cell phone use in an adult population in Spain as assessed by the Mobile Phone Problem Use Scale (MPPUS)

    Science.gov (United States)

    de-Sola, José; Talledo, Hernán; Rubio, Gabriel

    2017-01-01

    Problematic cell phone use has alarmingly increased in industrialized countries in the past 10 years. For many perpetrators, it can turn into a behavioural addiction, although this is not a recognized medical condition. Although there are many tools for evaluating this use, one of the most widely used tools is the Mobile Phone Problematic Use Scale (MPPUS), which we test on a representative sample of the population in Spain to obtain an estimate of the prevalence of problematic cell phone use in our midst. The age range consists of 16–65 years, with 1,126 surveys conducted. In this population, we verify that the reliability and internal consistency of the MPPUS (α = 0.939) are maintained. Additionally, the construct validity, considering the derived factors (Abuse and Dependence, Craving and Loss of Control, and Dependence on the Social Environment) are aligned with other research and with diverse external criteria of addiction. We establish four categories of users (Casual, Regular, At Risk, and Problematic) and obtain a prevalence of 15.4% among At Risk Users and 5.1% among Problematic Users. This finding implies a total of 20.5% of Users with Problems. A binary logistic regression analysis shows that age, gender, level of education, and daily cell phone use predict problematic cell phone use. The results, based on multiple criteria, show that such problematic use shares features of recognized addictions, affecting large segments of the population and not only adolescents. PMID:28771626