Optimization of Sinter Plant Operating Conditions Using Advanced Multivariate Statistics: Intelligent Data Processing

NASA Astrophysics Data System (ADS)

Fernández-González, Daniel; Martín-Duarte, Ramón; Ruiz-Bustinza, Íñigo; Mochón, Javier; González-Gasca, Carmen; Verdeja, Luis Felipe

2016-08-01

Blast furnace operators expect to get sinter with homogenous and regular properties (chemical and mechanical), necessary to ensure regular blast furnace operation. Blends for sintering also include several iron by-products and other wastes that are obtained in different processes inside the steelworks. Due to their source, the availability of such materials is not always consistent, but their total production should be consumed in the sintering process, to both save money and recycle wastes. The main scope of this paper is to obtain the least expensive iron ore blend for the sintering process, which will provide suitable chemical and mechanical features for the homogeneous and regular operation of the blast furnace. The systematic use of statistical tools was employed to analyze historical data, including linear and partial correlations applied to the data and fuzzy clustering based on the Sugeno Fuzzy Inference System to establish relationships among the available variables.

Similarity preserving low-rank representation for enhanced data representation and effective subspace learning.

PubMed

Zhang, Zhao; Yan, Shuicheng; Zhao, Mingbo

2014-05-01

Latent Low-Rank Representation (LatLRR) delivers robust and promising results for subspace recovery and feature extraction through mining the so-called hidden effects, but the locality of both similar principal and salient features cannot be preserved in the optimizations. To solve this issue for achieving enhanced performance, a boosted version of LatLRR, referred to as Regularized Low-Rank Representation (rLRR), is proposed through explicitly including an appropriate Laplacian regularization that can maximally preserve the similarity among local features. Resembling LatLRR, rLRR decomposes given data matrix from two directions by seeking a pair of low-rank matrices. But the similarities of principal and salient features can be effectively preserved by rLRR. As a result, the correlated features are well grouped and the robustness of representations is also enhanced. Based on the outputted bi-directional low-rank codes by rLRR, an unsupervised subspace learning framework termed Low-rank Similarity Preserving Projections (LSPP) is also derived for feature learning. The supervised extension of LSPP is also discussed for discriminant subspace learning. The validity of rLRR is examined by robust representation and decomposition of real images. Results demonstrated the superiority of our rLRR and LSPP in comparison to other related state-of-the-art algorithms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Retaining both discrete and smooth features in 1D and 2D NMR relaxation and diffusion experiments

NASA Astrophysics Data System (ADS)

Reci, A.; Sederman, A. J.; Gladden, L. F.

2017-11-01

A new method of regularization of 1D and 2D NMR relaxation and diffusion experiments is proposed and a robust algorithm for its implementation is introduced. The new form of regularization, termed the Modified Total Generalized Variation (MTGV) regularization, offers a compromise between distinguishing discrete and smooth features in the reconstructed distributions. The method is compared to the conventional method of Tikhonov regularization and the recently proposed method of L1 regularization, when applied to simulated data of 1D spin-lattice relaxation, T1, 1D spin-spin relaxation, T2, and 2D T1-T2 NMR experiments. A range of simulated distributions composed of two lognormally distributed peaks were studied. The distributions differed with regard to the variance of the peaks, which were designed to investigate a range of distributions containing only discrete, only smooth or both features in the same distribution. Three different signal-to-noise ratios were studied: 2000, 200 and 20. A new metric is proposed to compare the distributions reconstructed from the different regularization methods with the true distributions. The metric is designed to penalise reconstructed distributions which show artefact peaks. Based on this metric, MTGV regularization performs better than Tikhonov and L1 regularization in all cases except when the distribution is known to only comprise of discrete peaks, in which case L1 regularization is slightly more accurate than MTGV regularization.

78 FR 54951 - Petition for Waiver of Compliance

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-06

.... The subject cars and their type, capacities, reporting marks, and other features are listed in an enclosure with the petition letter. Also included in the enclosure are the design, type, components, or... tourist attractions and historical purposes and will not be interchanged in regular freight operations...

The Brown University Child and Adolescent Behavior Letter, 1997.

ERIC Educational Resources Information Center

Lipsitt, Lewis P., Ed.

1997-01-01

These 12 monthly issues, one special report, and index from 1997 explore problems encountered by children and adolescents. Regular features include "Keep Your Eye On...," brief accounts of research into childhood and adolescent problems; "What's New in Research," summarizing research from recent publications and professional…

Guide to Special Information in Scientific and Engineering Journals.

ERIC Educational Resources Information Center

Harris, Mary Elizabeth

This annotated bibliography lists 203 special features or special issues of science and technology periodicals with emphasis on compilations of information that appear in periodicals on a regular basis. Subjects covered in the guide include aeronautics, air-conditioning and refrigeration engineering, astronomy, automobiles, biology, botany,…

Human action recognition with group lasso regularized-support vector machine

NASA Astrophysics Data System (ADS)

Luo, Huiwu; Lu, Huanzhang; Wu, Yabei; Zhao, Fei

2016-05-01

The bag-of-visual-words (BOVW) and Fisher kernel are two popular models in human action recognition, and support vector machine (SVM) is the most commonly used classifier for the two models. We show two kinds of group structures in the feature representation constructed by BOVW and Fisher kernel, respectively, since the structural information of feature representation can be seen as a prior for the classifier and can improve the performance of the classifier, which has been verified in several areas. However, the standard SVM employs L2-norm regularization in its learning procedure, which penalizes each variable individually and cannot express the structural information of feature representation. We replace the L2-norm regularization with group lasso regularization in standard SVM, and a group lasso regularized-support vector machine (GLRSVM) is proposed. Then, we embed the group structural information of feature representation into GLRSVM. Finally, we introduce an algorithm to solve the optimization problem of GLRSVM by alternating directions method of multipliers. The experiments evaluated on KTH, YouTube, and Hollywood2 datasets show that our method achieves promising results and improves the state-of-the-art methods on KTH and YouTube datasets.

The AMATYC Review. 1994-1995.

ERIC Educational Resources Information Center

Browne, Joseph, Ed.

1995-01-01

Designed as an avenue of communication for mathematics educators concerned with the views, ideas, and experiences of two-year college students and teachers, this journal contains articles on mathematics exposition and education, and regular features presenting book and software reviews and math problems. In addition to regular features such as…

The AMATYC Review, Volume 10, Number 1, Fall 1988.

ERIC Educational Resources Information Center

Cohen, Don, Ed.

1988-01-01

Designed as an avenue of communication for all mathematics educators concerned with the views, ideas, and experiences pertinent to two-year college teachers and students, this journal presents articles and regular features related to mathematical and pedagogical themes. This issue includes the following articles: (1) "Fractals for Freshmen? Or,…

Image Manipulation: Then and Now.

ERIC Educational Resources Information Center

Sutton, Ronald E.

The images of photography have been manipulated almost from the moment of their discovery. The blending together in the studio and darkroom of images not found in actual scenes from life has been a regular feature of modern photography in both art and advertising. Techniques of photograph manipulation include retouching; blocking out figures or…

Parent and Preschooler Newsletter: A Monthly Exploration of Early Childhood Topics, 2003.

ERIC Educational Resources Information Center

Wolkoff, Sandra, Ed.; Schwartzberg, Neala S., Ed.

2003-01-01

This document consists of 10 monthly newsletter issues, in English- and Spanish-language versions, exploring topics related to early childhood behavior and parenting. Regularly appearing features include book recommendations, "Library Resources,""Preschoolers in the Kitchen,""Kids Crafts,""Research News," and "The Health Corner." Major topics of…

Child Care Health Connections, 2002.

ERIC Educational Resources Information Center

Guralnick, Eva, Ed.; Zamani, Rahman, Ed.; Evinger, Sara, Ed.; Dailey, Lyn, Ed.; Sherman, Marsha, Ed.; Oku, Cheryl, Ed.; Kunitz, Judith, Ed.

2002-01-01

This document is comprised of the six 2002 issues of a bimonthly newsletter on children's health for California's child care professionals. The newsletter provides information on current and emerging health and safety issues relevant to child care providers and links the health, safety, and child care communities. Regular features include columns…

Innovations in Early Education: The International Reggio Exchange, 2000-2001.

ERIC Educational Resources Information Center

Kaminsky, Judith Allen, Ed.

2001-01-01

This document is comprised of four issues of a quarterly publication presenting information related to the Reggio Emilia approach to early childhood education. Regularly appearing features of the publication include a calendar of Reggio conferences; information on the Reggio Children organization, contacts, exhibit schedule, and study tours; and a…

Efficient and sparse feature selection for biomedical text classification via the elastic net: Application to ICU risk stratification from nursing notes.

PubMed

Marafino, Ben J; Boscardin, W John; Dudley, R Adams

2015-04-01

Sparsity is often a desirable property of statistical models, and various feature selection methods exist so as to yield sparser and interpretable models. However, their application to biomedical text classification, particularly to mortality risk stratification among intensive care unit (ICU) patients, has not been thoroughly studied. To develop and characterize sparse classifiers based on the free text of nursing notes in order to predict ICU mortality risk and to discover text features most strongly associated with mortality. We selected nursing notes from the first 24h of ICU admission for 25,826 adult ICU patients from the MIMIC-II database. We then developed a pair of stochastic gradient descent-based classifiers with elastic-net regularization. We also studied the performance-sparsity tradeoffs of both classifiers as their regularization parameters were varied. The best-performing classifier achieved a 10-fold cross-validated AUC of 0.897 under the log loss function and full L2 regularization, while full L1 regularization used just 0.00025% of candidate input features and resulted in an AUC of 0.889. Using the log loss (range of AUCs 0.889-0.897) yielded better performance compared to the hinge loss (0.850-0.876), but the latter yielded even sparser models. Most features selected by both classifiers appear clinically relevant and correspond to predictors already present in existing ICU mortality models. The sparser classifiers were also able to discover a number of informative - albeit nonclinical - features. The elastic-net-regularized classifiers perform reasonably well and are capable of reducing the number of features required by over a thousandfold, with only a modest impact on performance. Copyright © 2015 Elsevier Inc. All rights reserved.

HPAC Info-dex 4: Locating recently published HPAC articles

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

NONE

1995-06-01

This is an alphabetical index of articles recently published in the Heating, Piping and Air Conditioning magazine. The lists include feature editorial material and articles from HPAC`s You`ll Want To Know Department. For each entry the month and year of publication are given, followed by the page number. Material is indexed by type of system, construction, or function. All regular columns are included.

Joint Associations of Residential Density and Neighborhood Involvement with Physical Activity among a Multiethnic Sample of Urban Adults

ERIC Educational Resources Information Center

Johnson-Lawrence, Vicki; Schulz, Amy J.; Zenk, Shannon N.; Israel, Barbara A.; Wineman, Jean; Marans, Robert W.; Rowe, Zachary

2015-01-01

Regular physical activity is associated with improvements in overall health. Although resident involvement in neighborhood social activities is positively associated with physical activity, neighborhood design features, including residential density, have varied associations with physical activity. Using data from a multiethnic sample of 696…

The EDUTECH Report. The Education Technology Newsletter for Faculty and Administrators, 1992-1993.

ERIC Educational Resources Information Center

EDUTECH Report, 1993

1993-01-01

This newsletter examines education technology issues of concern to school faculty and administrators. Regular features in each issue include educational technology news, a book review, and a question and answer column. The cover articles during this volume year are: "Data Access Issues: Security Vs. Openness"; "Creation of an…

The EDUTECH Report. The Education Technology Newsletter for Faculty and Administrators, 1994-1995.

ERIC Educational Resources Information Center

EDUTECH Report, 1995

1995-01-01

This newsletter examines education technology issues of concern to school faculty and administrators. Regular features in each issue include educational technology news, a book review, and a question and answer column. The cover articles during this volume year are: "The Decision-Making Process: as Important as the Decision";…

The AMATYC Review, Volume 15, Numbers 1-2, Fall 1993-Spring 1994.

ERIC Educational Resources Information Center

Browne, Joseph, Ed.

1994-01-01

Designed as a avenue of communication for mathematics educators concerned with the views, ideas, and experiences of two-year college students and teachers, this journal contains articles on mathematics exposition and education, and regular features presenting book and software reviews and math problems. Volume 15 includes the following articles:…

Addressing Barriers to Learning. Volume 9, Number 2. Spring 2004

ERIC Educational Resources Information Center

Center for Mental Health in Schools at UCLA, 2004

2004-01-01

This issue of the quarterly newsletter of the Center for Mental Health in Schools includes the following features and regular segments: (1) Diversity and Professional Competence in Schools... a Mental Health Perspective; (2) Diversity Competence Relevant to Mental Health in Schools: Eliminating Disparities in School Practices; (3) Where it's…

The EDUTECH Report. The Education Technology Newsletter for Faculty and Administrators, 1993-1994.

ERIC Educational Resources Information Center

EDUTECH Report, 1994

1994-01-01

This newsletter examines education technology issues of concern to school faculty and administrators. Regular features in each issue include educational technology news, a book review, and a question and answer column. The cover articles during this volume year are: "The Build-or-Buy Decision: No One Right Answer"; "The National…

Additivity of Feature-Based and Symmetry-Based Grouping Effects in Multiple Object Tracking

PubMed Central

Wang, Chundi; Zhang, Xuemin; Li, Yongna; Lyu, Chuang

2016-01-01

Multiple object tracking (MOT) is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the “laws of perceptual organization” proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape) among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. “Additive effect” refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The “where” and “what” pathways might have played an important role in the additive grouping effect. PMID:27199875

Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations

NASA Astrophysics Data System (ADS)

Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian

2018-04-01

Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.

R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization

PubMed Central

Dazard, Jean-Eudes; Xu, Hua; Rao, J. Sunil

2015-01-01

We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets (p ≫ n paradigm), such as in ‘omics’-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real ‘omics’ test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR (‘Mean-Variance Regularization’), downloadable from the CRAN. PMID:26819572

Probing the cross-effect of strains in non-linear elasticity of nearly regular polymer networks by pure shear deformation.

PubMed

Katashima, Takuya; Urayama, Kenji; Chung, Ung-il; Sakai, Takamasa

2015-05-07

The pure shear deformation of the Tetra-polyethylene glycol gels reveals the presence of an explicit cross-effect of strains in the strain energy density function even for the polymer networks with nearly regular structure including no appreciable amount of structural defect such as trapped entanglement. This result is in contrast to the expectation of the classical Gaussian network model (Neo Hookean model), i.e., the vanishing of the cross effect in regular networks with no trapped entanglement. The results show that (1) the cross effect of strains is not dependent on the network-strand length; (2) the cross effect is not affected by the presence of non-network strands; (3) the cross effect is proportional to the network polymer concentration including both elastically effective and ineffective strands; (4) no cross effect is expected exclusively in zero limit of network concentration in real polymer networks. These features indicate that the real polymer networks with regular network structures have an explicit cross-effect of strains, which originates from some interaction between network strands (other than entanglement effect) such as nematic interaction, topological interaction, and excluded volume interaction.

Image Reconstruction from Under sampled Fourier Data Using the Polynomial Annihilation Transform

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

Archibald, Richard K.; Gelb, Anne; Platte, Rodrigo

Fourier samples are collected in a variety of applications including magnetic resonance imaging and synthetic aperture radar. The data are typically under-sampled and noisy. In recent years, l 1 regularization has received considerable attention in designing image reconstruction algorithms from under-sampled and noisy Fourier data. The underlying image is assumed to have some sparsity features, that is, some measurable features of the image have sparse representation. The reconstruction algorithm is typically designed to solve a convex optimization problem, which consists of a fidelity term penalized by one or more l 1 regularization terms. The Split Bregman Algorithm provides a fastmore » explicit solution for the case when TV is used for the l1l1 regularization terms. Due to its numerical efficiency, it has been widely adopted for a variety of applications. A well known drawback in using TV as an l 1 regularization term is that the reconstructed image will tend to default to a piecewise constant image. This issue has been addressed in several ways. Recently, the polynomial annihilation edge detection method was used to generate a higher order sparsifying transform, and was coined the “polynomial annihilation (PA) transform.” This paper adapts the Split Bregman Algorithm for the case when the PA transform is used as the l 1 regularization term. In so doing, we achieve a more accurate image reconstruction method from under-sampled and noisy Fourier data. Our new method compares favorably to the TV Split Bregman Algorithm, as well as to the popular TGV combined with shearlet approach.« less

An improved arteriovenous classification method for the early diagnostics of various diseases in retinal image.

PubMed

Xu, Xiayu; Ding, Wenxiang; Abràmoff, Michael D; Cao, Ruofan

2017-04-01

Retinal artery and vein classification is an important task for the automatic computer-aided diagnosis of various eye diseases and systemic diseases. This paper presents an improved supervised artery and vein classification method in retinal image. Intra-image regularization and inter-subject normalization is applied to reduce the differences in feature space. Novel features, including first-order and second-order texture features, are utilized to capture the discriminating characteristics of arteries and veins. The proposed method was tested on the DRIVE dataset and achieved an overall accuracy of 0.923. This retinal artery and vein classification algorithm serves as a potentially important tool for the early diagnosis of various diseases, including diabetic retinopathy and cardiovascular diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

Addressing Barriers to Learning. Volume 12, Number 4. Fall 2007

ERIC Educational Resources Information Center

Center for Mental Health in Schools at UCLA, 2007

2007-01-01

Leaders concerned with advancing mental health in school need to focus on much more than just increasing clinical services. This issue of the quarterly newsletter of the Center for Mental Health in Schools includes the following features and regular segments: (1) Mental Health in Schools: Much More than Services for the Few; (2) Many Schools, Many…

Child Care Health Connections, 1999: A Health and Safety Newsletter for California Child Care Professionals.

ERIC Educational Resources Information Center

Walery, Nancy, Ed.; Evinger, Sara, Ed.; Dailey, Lyn, Ed.; Sherman, Marsha, Ed.; Zamani, Rahman, Ed.

1999-01-01

This document is comprised of the six 1999 issues of a bimonthly newsletter providing information on young children's health and safety for California's child care professionals. Regular features include a column on infant/toddler concerns, a question-answer column regarding medical and health issues, a nutrition column, and resources for child…

Youth Sport Development through Soccer: An Evaluation of an After-School Program Using the TPSR Model

ERIC Educational Resources Information Center

Cryan, Mark; Martinek, Thomas

2017-01-01

The Soccer Coaching Club program used the Teaching Personal and Social Responsibility (TPSR) model in an after-school soccer program for sixth grade boys between 11 and 12 years old in a local middle school. Soccer, as the featured physical activity, provided the "hook" for regular attendance. Desired outcomes included improved…

Guide to Special Information in Scientific and Engineering Journals.

ERIC Educational Resources Information Center

Harris, Mary Elizabeth

This update of a 1983 annotated bibliography lists 298 special features or special issues of science and technology periodicals with emphasis on compilations of information that appear in periodicals on a regular basis. In addition to the 203 entries listed in the original edition, 95 new entries are included. Subjects covered in the guide include…

More than Words: Fast Acquisition and Generalization of Orthographic Regularities during Novel Word Learning in Adults

ERIC Educational Resources Information Center

Laine, Matti; Polonyi, Tünde; Abari, Kálmán

2014-01-01

In literates, reading is a fundamental channel for acquiring new vocabulary both in the mother tongue and in foreign languages. By using an artificial language learning task, we examined the acquisition of novel written words and their embedded regularities (an orthographic surface feature and a syllabic feature) in three groups of university…

An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

PubMed

Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

2014-01-01

The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

Manifold Regularized Multitask Feature Learning for Multimodality Disease Classification

PubMed Central

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2015-01-01

Multimodality based methods have shown great advantages in classification of Alzheimer’s disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis. PMID:25277605

MO-DE-207A-02: A Feature-Preserving Image Reconstruction Method for Improved Pancreaticlesion Classification in Diagnostic CT Imaging

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

Xu, J; Tsui, B; Noo, F

Purpose: To develop a feature-preserving model based image reconstruction (MBIR) method that improves performance in pancreatic lesion classification at equal or reduced radiation dose. Methods: A set of pancreatic lesion models was created with both benign and premalignant lesion types. These two classes of lesions are distinguished by their fine internal structures; their delineation is therefore crucial to the task of pancreatic lesion classification. To reduce image noise while preserving the features of the lesions, we developed a MBIR method with curvature-based regularization. The novel regularization encourages formation of smooth surfaces that model both the exterior shape and the internalmore » features of pancreatic lesions. Given that the curvature depends on the unknown image, image reconstruction or denoising becomes a non-convex optimization problem; to address this issue an iterative-reweighting scheme was used to calculate and update the curvature using the image from the previous iteration. Evaluation was carried out with insertion of the lesion models into the pancreas of a patient CT image. Results: Visual inspection was used to compare conventional TV regularization with our curvature-based regularization. Several penalty-strengths were considered for TV regularization, all of which resulted in erasing portions of the septation (thin partition) in a premalignant lesion. At matched noise variance (50% noise reduction in the patient stomach region), the connectivity of the septation was well preserved using the proposed curvature-based method. Conclusion: The curvature-based regularization is able to reduce image noise while simultaneously preserving the lesion features. This method could potentially improve task performance for pancreatic lesion classification at equal or reduced radiation dose. The result is of high significance for longitudinal surveillance studies of patients with pancreatic cysts, which may develop into pancreatic cancer. The Senior Author receives financial support from Siemens GmbH Healthcare.« less

Heterogeneous clinicopathological features of intraductal carcinoma of the prostate: a comparison between "precursor-like" and "regular type" lesions.

PubMed

Miyai, Kosuke; Divatia, Mukul K; Shen, Steven S; Miles, Brian J; Ayala, Alberto G; Ro, Jae Y

2014-01-01

Intraductal carcinoma of the prostate (IDC-P) has been described as a lesion associated with intraductal spread of invasive carcinoma and consequently aggressive disease. However, there are a few reported cases of pure IDC-P without an associated invasive component, strongly suggesting that this subset of IDC-P may represent a precursor lesion. We compared the clinicopathological features between the morphologically "regular type" IDC-P and "precursor-like" IDC-P. IDC-P was defined as follows; 1) solid/dense cribriform lesions or 2) loose cribriform/micropapillary lesions with prominent nuclear pleomorphism and/or non-focal comedonecrosis. We defined precursor-like IDC-P as follows; 1) IDC-P without adjoining invasive adenocarcinoma but carcinoma present distant from the IDC-P or 2) IDC-P having adjoining invasive microcarcinoma (less than 0.05 ml) and showing a morphologic transition from high-grade prostatic intraepithelial neoplasia (HGPIN) to the IDC-P. IDC-P lacking the features of precursor-like IDC-P was categorized as regular type IDC-P. Of 901 radical prostatectomies performed at our hospital, 141 and 14 showed regular type IDC-P and precursor-like IDC-P in whole-mounted specimens, respectively. Regular type IDC-P cases had significantly higher Gleason score, more frequent extraprostatic extension and seminal vesicle invasion, more advanced pathological T stage, and lower 5-year biochemical recurrence-free rate than precursor-like IDC-P cases. Multivariate analysis revealed nodal metastasis and the presence of regular type IDC-P as independent predictors for biochemical recurrence. Our data suggest that IDC-P may be heterogeneous with variable clinicopathological features. We also suggest that not all IDC-P cases represent intraductal spread of pre-existing invasive cancer, and a subset of IDC-P may be a precursor lesion.

Multiplicative Multitask Feature Learning

PubMed Central

Wang, Xin; Bi, Jinbo; Yu, Shipeng; Sun, Jiangwen; Song, Minghu

2016-01-01

We investigate a general framework of multiplicative multitask feature learning which decomposes individual task’s model parameters into a multiplication of two components. One of the components is used across all tasks and the other component is task-specific. Several previous methods can be proved to be special cases of our framework. We study the theoretical properties of this framework when different regularization conditions are applied to the two decomposed components. We prove that this framework is mathematically equivalent to the widely used multitask feature learning methods that are based on a joint regularization of all model parameters, but with a more general form of regularizers. Further, an analytical formula is derived for the across-task component as related to the task-specific component for all these regularizers, leading to a better understanding of the shrinkage effects of different regularizers. Study of this framework motivates new multitask learning algorithms. We propose two new learning formulations by varying the parameters in the proposed framework. An efficient blockwise coordinate descent algorithm is developed suitable for solving the entire family of formulations with rigorous convergence analysis. Simulation studies have identified the statistical properties of data that would be in favor of the new formulations. Extensive empirical studies on various classification and regression benchmark data sets have revealed the relative advantages of the two new formulations by comparing with the state of the art, which provides instructive insights into the feature learning problem with multiple tasks. PMID:28428735

FOCUSR: Feature Oriented Correspondence using Spectral Regularization–A Method for Precise Surface Matching

PubMed Central

Lombaert, Herve; Grady, Leo; Polimeni, Jonathan R.; Cheriet, Farida

2013-01-01

Existing methods for surface matching are limited by the trade-off between precision and computational efficiency. Here we present an improved algorithm for dense vertex-to-vertex correspondence that uses direct matching of features defined on a surface and improves it by using spectral correspondence as a regularization. This algorithm has the speed of both feature matching and spectral matching while exhibiting greatly improved precision (distance errors of 1.4%). The method, FOCUSR, incorporates implicitly such additional features to calculate the correspondence and relies on the smoothness of the lowest-frequency harmonics of a graph Laplacian to spatially regularize the features. In its simplest form, FOCUSR is an improved spectral correspondence method that nonrigidly deforms spectral embeddings. We provide here a full realization of spectral correspondence where virtually any feature can be used as additional information using weights on graph edges, but also on graph nodes and as extra embedded coordinates. As an example, the full power of FOCUSR is demonstrated in a real case scenario with the challenging task of brain surface matching across several individuals. Our results show that combining features and regularizing them in a spectral embedding greatly improves the matching precision (to a sub-millimeter level) while performing at much greater speed than existing methods. PMID:23868776

Prior Learning Assessment at Home and Abroad. Excerpts from Recent Articles in the CAEL Forum and News

ERIC Educational Resources Information Center

Council for Adult and Experiential Learning (NJ1), 2007

2007-01-01

This paper features several articles previously published in the CAEL (Council for Adult and Experiential Learning) Forum and News, an e-newsletter CAEL regularly shares with its members. This publication includes a summary of the data gathered in CAEL's 2006 institutional survey on PLA (Prior Learning Assessment), results of a research on…

Focus on Infants & Toddlers (Ages 0-3): A Quarterly Newsletter for the Education Community, 2000-2001.

ERIC Educational Resources Information Center

Barry, Virginia M., Ed.; Cantor, Patricia, Ed.

2001-01-01

These four quarterly newsletter issues address various topics of interest to child caregivers. Each issue includes articles on a specific theme, along with regular news or a column by an AECI Executive Board vice president. The Fall 2000 issue focuses on the special features and unique concerns of employer-sponsored child care, with one article…

Properties of nanostructures obtained by anodization of aluminum in phosphoric acid at moderate potentials

NASA Astrophysics Data System (ADS)

Zaraska, L.; Sulka, G. D.; Jaskuła, M.

2009-01-01

The influence of the process duration, anodizing potential and methanol addition on the structural features of porous anodic alumina formed in a 0.3 M H3PO4 solutions by twostep self-organized anodizing was investigated for potentials ranging from 100 to 170 V. The structural features of porous structures including pore diameter and interpore distance were evaluated from FE-SEM top-view images for samples anodized in the presence and absence of methanol. For the highest studied anodizing time and methanol volume fraction, an excellent agreement between experimental values of the interpore distance and theoretical predictions was observed. The pore arrangement regularity was analyzed for various electrolyte compositions and anodizing potentials. It was found that the regularity ratio of porous alumina increases linearly with increasing anodizing potential and time. The addition of methanol improves the quality of nanostructures and especially better uniformity of pore sizes is observed in the presence of the highest studied methanol content.

Can Birds Perceive Rhythmic Patterns? A Review and Experiments on a Songbird and a Parrot Species

PubMed Central

ten Cate, Carel; Spierings, Michelle; Hubert, Jeroen; Honing, Henkjan

2016-01-01

While humans can easily entrain their behavior with the beat in music, this ability is rare among animals. Yet, comparative studies in non-human species are needed if we want to understand how and why this ability evolved. Entrainment requires two abilities: (1) recognizing the regularity in the auditory stimulus and (2) the ability to adjust the own motor output to the perceived pattern. It has been suggested that beat perception and entrainment are linked to the ability for vocal learning. The presence of some bird species showing beat induction, and also the existence of vocal learning as well as vocal non-learning bird taxa, make them relevant models for comparative research on rhythm perception and its link to vocal learning. Also, some bird vocalizations show strong regularity in rhythmic structure, suggesting that birds might perceive rhythmic structures. In this paper we review the available experimental evidence for the perception of regularity and rhythms by birds, like the ability to distinguish regular from irregular stimuli over tempo transformations and report data from new experiments. While some species show a limited ability to detect regularity, most evidence suggests that birds attend primarily to absolute and not relative timing of patterns and to local features of stimuli. We conclude that, apart from some large parrot species, there is limited evidence for beat and regularity perception among birds and that the link to vocal learning is unclear. We next report the new experiments in which zebra finches and budgerigars (both vocal learners) were first trained to distinguish a regular from an irregular pattern of beats and then tested on various tempo transformations of these stimuli. The results showed that both species reduced the discrimination after tempo transformations. This suggests that, as was found in earlier studies, they attended mainly to local temporal features of the stimuli, and not to their overall regularity. However, some individuals of both species showed an additional sensitivity to the more global pattern if some local features were left unchanged. Altogether our study indicates both between and within species variation, in which birds attend to a mixture of local and to global rhythmic features. PMID:27242635

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Walker occupancy has an impact on changing airborne bacterial communities in an underground pedestrian space, as small-dust particles increased with raising both temperature and humidity.

PubMed

Okubo, Torahiko; Osaki, Takako; Nozaki, Eriko; Uemura, Akira; Sakai, Kouhei; Matushita, Mizue; Matsuo, Junji; Nakamura, Shinji; Kamiya, Shigeru; Yamaguchi, Hiroyuki

2017-01-01

Although human occupancy is a source of airborne bacteria, the role of walkers on bacterial communities in built environments is poorly understood. Therefore, we visualized the impact of walker occupancy combined with other factors (temperature, humidity, atmospheric pressure, dust particles) on airborne bacterial features in the Sapporo underground pedestrian space in Sapporo, Japan. Air samples (n = 18; 4,800L/each sample) were collected at 8:00 h to 20:00 h on 3 days (regular sampling) and at early morning / late night (5:50 h to 7:50 h / 22:15 h to 24:45 h) on a day (baseline sampling), and the number of CFUs (colony forming units) OTUs (operational taxonomic units) and other factors were determined. The results revealed that temperature, humidity, and atmospheric pressure changed with weather. The number of walkers increased greatly in the morning and evening on each regular sampling day, although total walker numbers did not differ significantly among regular sampling days. A slight increase in small dust particles (0.3-0.5μm) was observed on the days with higher temperature regardless of regular or baseline sampling. At the period on regular sampling, CFU levels varied irregularly among days, and the OTUs of 22-phylum types were observed, with the majority being from Firmicutes or Proteobacteria (γ-), including Staphylococcus sp. derived from human individuals. The data obtained from regular samplings reveled that although no direct interaction of walker occupancy and airborne CFU and OTU features was observed upon Pearson's correlation analysis, cluster analysis indicated an obvious lineage consisting of walker occupancy, CFU numbers, OTU types, small dust particles, and seasonal factors (including temperature and humidity). Meanwhile, at the period on baseline sampling both walker and CFU numbers were similarly minimal. Taken together, the results revealed a positive correlation of walker occupancy with airborne bacteria that increased with increases in temperature and humidity in the presence of airborne small particles. Moreover, the results indicated that small dust particles at high temperature and humidity may be a crucial factor responsible for stabilizing the bacteria released from walkers in built environments. The findings presented herein advance our knowledge and understanding of the relationship between humans and bacterial communities in built environments, and will help improve public health in urban communities.

Walker occupancy has an impact on changing airborne bacterial communities in an underground pedestrian space, as small-dust particles increased with raising both temperature and humidity

PubMed Central

Okubo, Torahiko; Osaki, Takako; Nozaki, Eriko; Uemura, Akira; Sakai, Kouhei; Matushita, Mizue; Matsuo, Junji; Nakamura, Shinji; Kamiya, Shigeru

2017-01-01

Although human occupancy is a source of airborne bacteria, the role of walkers on bacterial communities in built environments is poorly understood. Therefore, we visualized the impact of walker occupancy combined with other factors (temperature, humidity, atmospheric pressure, dust particles) on airborne bacterial features in the Sapporo underground pedestrian space in Sapporo, Japan. Air samples (n = 18; 4,800L/each sample) were collected at 8:00 h to 20:00 h on 3 days (regular sampling) and at early morning / late night (5:50 h to 7:50 h / 22:15 h to 24:45 h) on a day (baseline sampling), and the number of CFUs (colony forming units) OTUs (operational taxonomic units) and other factors were determined. The results revealed that temperature, humidity, and atmospheric pressure changed with weather. The number of walkers increased greatly in the morning and evening on each regular sampling day, although total walker numbers did not differ significantly among regular sampling days. A slight increase in small dust particles (0.3–0.5μm) was observed on the days with higher temperature regardless of regular or baseline sampling. At the period on regular sampling, CFU levels varied irregularly among days, and the OTUs of 22-phylum types were observed, with the majority being from Firmicutes or Proteobacteria (γ-), including Staphylococcus sp. derived from human individuals. The data obtained from regular samplings reveled that although no direct interaction of walker occupancy and airborne CFU and OTU features was observed upon Pearson's correlation analysis, cluster analysis indicated an obvious lineage consisting of walker occupancy, CFU numbers, OTU types, small dust particles, and seasonal factors (including temperature and humidity). Meanwhile, at the period on baseline sampling both walker and CFU numbers were similarly minimal. Taken together, the results revealed a positive correlation of walker occupancy with airborne bacteria that increased with increases in temperature and humidity in the presence of airborne small particles. Moreover, the results indicated that small dust particles at high temperature and humidity may be a crucial factor responsible for stabilizing the bacteria released from walkers in built environments. The findings presented herein advance our knowledge and understanding of the relationship between humans and bacterial communities in built environments, and will help improve public health in urban communities. PMID:28922412

[Analysis of on medication rules for Qi-deficiency and blood-stasis syndrome of chronic heart failure based on data mining technology].

PubMed

Wang, Qian; Yao, Geng-Zhen; Pan, Guang-Ming; Huang, Jing-Yi; An, Yi-Pei; Zou, Xu

2017-01-01

To analyze the medication features and the regularity of prescriptions of traditional Chinese medicine in treating patients with Qi-deficiency and blood-stasis syndrome of chronic heart failure based on modern literature. In this article, CNKI Chinese academic journal database, Wanfang Chinese academic journal database and VIP Chinese periodical database were all searched from January 2000 to December 2015 for the relevant literature on traditional Chinese medicine treatment for Qi-deficiency and blood-stasis syndrome of chronic heart failure. Then a normalized database was established for further data mining and analysis. Subsequently, the medication features and the regularity of prescriptions were mined by using traditional Chinese medicine inheritance support system(V2.5), association rules, improved mutual information algorithm, complex system entropy clustering and other mining methods. Finally, a total of 171 articles were included, involving 171 prescriptions, 140 kinds of herbs, with a total frequency of 1 772 for the herbs. As a result, 19 core prescriptions and 7 new prescriptions were mined. The most frequently used herbs included Huangqi(Astragali Radix), Danshen(Salviae Miltiorrhizae Radix et Rhizoma), Fuling(Poria), Renshen(Ginseng Radix et Rhizoma), Tinglizi(Semen Lepidii), Baizhu(Atractylodis Macrocephalae Rhizoma), and Guizhi(Cinnamomum Ramulus). The core prescriptions were composed of Huangqi(Astragali Radix), Danshen(Salviae Miltiorrhizae Radix et Rhizoma) and Fuling(Poria), etc. The high frequent herbs and core prescriptions not only highlight the medication features of Qi-invigorating and blood-circulating therapy, but also reflect the regularity of prescriptions of blood-circulating, Yang-warming, and urination-promoting therapy based on syndrome differentiation. Moreover, the mining of the new prescriptions provide new reference and inspiration for clinical treatment of various accompanying symptoms of chronic heart failure. In conclusion, this article provides new reference for traditional Chinese medicine in the treatment of chronic heart failure. Copyright© by the Chinese Pharmaceutical Association.

Label-aligned Multi-task Feature Learning for Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zu, Chen; Jie, Biao; Liu, Mingxia; Chen, Songcan

2015-01-01

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI. PMID:26572145

Using Tikhonov Regularization for Spatial Projections from CSR Regularized Spherical Harmonic GRACE Solutions

NASA Astrophysics Data System (ADS)

Save, H.; Bettadpur, S. V.

2013-12-01

It has been demonstrated before that using Tikhonov regularization produces spherical harmonic solutions from GRACE that have very little residual stripes while capturing all the signal observed by GRACE within the noise level. This paper demonstrates a two-step process and uses Tikhonov regularization to remove the residual stripes in the CSR regularized spherical harmonic coefficients when computing the spatial projections. We discuss methods to produce mass anomaly grids that have no stripe features while satisfying the necessary condition of capturing all observed signal within the GRACE noise level.

Coordination and interpretation of vocal and visible resources: 'trail-off' conjunctions.

PubMed

Walker, Gareth

2012-03-01

The empirical focus of this paper is a conversational turn-taking phenomenon in which conjunctions produced immediately after a point of possible syntactic and pragmatic completion are treated by co-participants as points of possible completion and transition relevance. The data for this study are audio-video recordings of 5 unscripted face-to-face interactions involving native speakers of US English, yielding 28 'trail-off' conjunctions. Detailed sequential analysis of talk is combined with analysis of visible features (including gaze, posture, gesture and involvement with material objects) and technical phonetic analysis. A range of phonetic and visible features are shown to regularly co-occur in the production of 'trail-off' conjunctions. These features distinguish them from other conjunctions followed by the cessation of talk.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

The perception of regularity in an isochronous stimulus in zebra finches (Taeniopygia guttata) and humans.

PubMed

van der Aa, Jeroen; Honing, Henkjan; ten Cate, Carel

2015-06-01

Perceiving temporal regularity in an auditory stimulus is considered one of the basic features of musicality. Here we examine whether zebra finches can detect regularity in an isochronous stimulus. Using a go/no go paradigm we show that zebra finches are able to distinguish between an isochronous and an irregular stimulus. However, when the tempo of the isochronous stimulus is changed, it is no longer treated as similar to the training stimulus. Training with three isochronous and three irregular stimuli did not result in improvement of the generalization. In contrast, humans, exposed to the same stimuli, readily generalized across tempo changes. Our results suggest that zebra finches distinguish the different stimuli by learning specific local temporal features of each individual stimulus rather than attending to the global structure of the stimuli, i.e., to the temporal regularity. Copyright © 2015 Elsevier B.V. All rights reserved.

X-ray computed tomography using curvelet sparse regularization.

PubMed

Wieczorek, Matthias; Frikel, Jürgen; Vogel, Jakob; Eggl, Elena; Kopp, Felix; Noël, Peter B; Pfeiffer, Franz; Demaret, Laurent; Lasser, Tobias

2015-04-01

Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method's strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.

Biased Dropout and Crossmap Dropout: Learning towards effective Dropout regularization in convolutional neural network.

PubMed

Poernomo, Alvin; Kang, Dae-Ki

2018-08-01

Training a deep neural network with a large number of parameters often leads to overfitting problem. Recently, Dropout has been introduced as a simple, yet effective regularization approach to combat overfitting in such models. Although Dropout has shown remarkable results on many deep neural network cases, its actual effect on CNN has not been thoroughly explored. Moreover, training a Dropout model will significantly increase the training time as it takes longer time to converge than a non-Dropout model with the same architecture. To deal with these issues, we address Biased Dropout and Crossmap Dropout, two novel approaches of Dropout extension based on the behavior of hidden units in CNN model. Biased Dropout divides the hidden units in a certain layer into two groups based on their magnitude and applies different Dropout rate to each group appropriately. Hidden units with higher activation value, which give more contributions to the network final performance, will be retained by a lower Dropout rate, while units with lower activation value will be exposed to a higher Dropout rate to compensate the previous part. The second approach is Crossmap Dropout, which is an extension of the regular Dropout in convolution layer. Each feature map in a convolution layer has a strong correlation between each other, particularly in every identical pixel location in each feature map. Crossmap Dropout tries to maintain this important correlation yet at the same time break the correlation between each adjacent pixel with respect to all feature maps by applying the same Dropout mask to all feature maps, so that all pixels or units in equivalent positions in each feature map will be either dropped or active during training. Our experiment with various benchmark datasets shows that our approaches provide better generalization than the regular Dropout. Moreover, our Biased Dropout takes faster time to converge during training phase, suggesting that assigning noise appropriately in hidden units can lead to an effective regularization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Overlay of multiframe SEM images including nonlinear field distortions

NASA Astrophysics Data System (ADS)

Babin, S.; Borisov, S.; Ivonin, I.; Nakazawa, S.; Yamazaki, Y.

2018-03-01

To reduce charging and shrinkage, CD-SEMs utilize low electron energies and multiframe imaging. This results in every next frame being altered due to stage and beam instability, as well as due to charging. Regular averaging of the frames blurs the edges; this directly effects the extracted values of critical dimensions. A technique was developed to overlay multiframe images without the loss of quality. This method takes into account drift, rotation, and magnification corrections, as well as nonlinear distortions due to wafer charging. A significant improvement in the signal to noise ratio and overall image quality without degradation of the feature's edge quality was achieved. The developed software is capable of working with regular and large size images up to 32K pixels in each direction.

Components of aesthetic experience: aesthetic fascination, aesthetic appraisal, and aesthetic emotion

PubMed Central

Marković, Slobodan

2012-01-01

In this paper aesthetic experience is defined as an experience qualitatively different from everyday experience and similar to other exceptional states of mind. Three crucial characteristics of aesthetic experience are discussed: fascination with an aesthetic object (high arousal and attention), appraisal of the symbolic reality of an object (high cognitive engagement), and a strong feeling of unity with the object of aesthetic fascination and aesthetic appraisal. In a proposed model, two parallel levels of aesthetic information processing are proposed. On the first level two sub-levels of narrative are processed, story (theme) and symbolism (deeper meanings). The second level includes two sub-levels, perceptual associations (implicit meanings of object's physical features) and detection of compositional regularities. Two sub-levels are defined as crucial for aesthetic experience, appraisal of symbolism and compositional regularities. These sub-levels require some specific cognitive and personality dispositions, such as expertise, creative thinking, and openness to experience. Finally, feedback of emotional processing is included in our model: appraisals of everyday emotions are specified as a matter of narrative content (eg, empathy with characters), whereas the aesthetic emotion is defined as an affective evaluation in the process of symbolism appraisal or the detection of compositional regularities. PMID:23145263

Application of L1/2 regularization logistic method in heart disease diagnosis.

PubMed

Zhang, Bowen; Chai, Hua; Yang, Ziyi; Liang, Yong; Chu, Gejin; Liu, Xiaoying

2014-01-01

Heart disease has become the number one killer of human health, and its diagnosis depends on many features, such as age, blood pressure, heart rate and other dozens of physiological indicators. Although there are so many risk factors, doctors usually diagnose the disease depending on their intuition and experience, which requires a lot of knowledge and experience for correct determination. To find the hidden medical information in the existing clinical data is a noticeable and powerful approach in the study of heart disease diagnosis. In this paper, sparse logistic regression method is introduced to detect the key risk factors using L(1/2) regularization on the real heart disease data. Experimental results show that the sparse logistic L(1/2) regularization method achieves fewer but informative key features than Lasso, SCAD, MCP and Elastic net regularization approaches. Simultaneously, the proposed method can cut down the computational complexity, save cost and time to undergo medical tests and checkups, reduce the number of attributes needed to be taken from patients.

Clinical abnormalities, early intervention program of Down syndrome children: Queen Sirikit National Institute of Child Health experience.

PubMed

Fuengfoo, Adidsuda; Sakulnoom, Kim

2014-06-01

Queen Sirikit National Institute of Child Health is a tertiary institute of children in Thailand, where early intervention programs have been provided since 1990 by multidisciplinary approach especially in Down syndrome children. This aim of the present study is to follow the impact of early intervention on the outcome of Down syndrome children. The school attendance number of Down syndrome children was compared between regular early intervention and non-regular early intervention. The present study group consists of 210 Down syndrome children who attended early intervention programs at Queen Sirikit National Institute of Child Health between June 2008 and January 2012. Data include clinical features, school attendance developmental quotient (DQ) at 3 years of age using Capute Scales Cognitive Adaptive Test/Scale (CAT/CLAMS). Developmental milestones have been recorded as to the time of appearance of gross motor, fine motor, language, personal-social development compared to those non-regular intervention patients. Of 210 Down syndrome children, 117 were boys and 93 were girls. About 87% received regular intervention, 68% attended speech training. Mean DQ at 3 years of age was 65. Of the 184 children who still did follow-up at developmental department, 124 children (59%) attended school: mainstream school children 78 (63%) and special school children 46 (37%). The mean age at entrance to school was 5.8 ± 1.4 years. The school attendance was correlated with maternal education and regular early intervention attendance. Regular early intervention starts have proven to have a positive effect on development. The school attendance number of Down syndrome children receiving regular early intervention was statistically and significantly higher than the number of Down syndrome children receiving non-regular early intervention was. School attendance correlated with maternal education and attended regularly early intervention. Regular early intervention together with maternal education are contributing factors influencing school attendance in Down syndrome children in the present study

Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

PubMed Central

Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

2012-01-01

Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

Multi-View Budgeted Learning under Label and Feature Constraints Using Label-Guided Graph-Based Regularization

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

Symons, Christopher T; Arel, Itamar

2011-01-01

Budgeted learning under constraints on both the amount of labeled information and the availability of features at test time pertains to a large number of real world problems. Ideas from multi-view learning, semi-supervised learning, and even active learning have applicability, but a common framework whose assumptions fit these problem spaces is non-trivial to construct. We leverage ideas from these fields based on graph regularizers to construct a robust framework for learning from labeled and unlabeled samples in multiple views that are non-independent and include features that are inaccessible at the time the model would need to be applied. We describemore » examples of applications that fit this scenario, and we provide experimental results to demonstrate the effectiveness of knowledge carryover from training-only views. As learning algorithms are applied to more complex applications, relevant information can be found in a wider variety of forms, and the relationships between these information sources are often quite complex. The assumptions that underlie most learning algorithms do not readily or realistically permit the incorporation of many of the data sources that are available, despite an implicit understanding that useful information exists in these sources. When multiple information sources are available, they are often partially redundant, highly interdependent, and contain noise as well as other information that is irrelevant to the problem under study. In this paper, we are focused on a framework whose assumptions match this reality, as well as the reality that labeled information is usually sparse. Most significantly, we are interested in a framework that can also leverage information in scenarios where many features that would be useful for learning a model are not available when the resulting model will be applied. As with constraints on labels, there are many practical limitations on the acquisition of potentially useful features. A key difference in the case of feature acquisition is that the same constraints often don't pertain to the training samples. This difference provides an opportunity to allow features that are impractical in an applied setting to nevertheless add value during the model-building process. Unfortunately, there are few machine learning frameworks built on assumptions that allow effective utilization of features that are only available at training time. In this paper we formulate a knowledge carryover framework for the budgeted learning scenario with constraints on features and labels. The approach is based on multi-view and semi-supervised learning methods that use graph-encoded regularization. Our main contributions are the following: (1) we propose and provide justification for a methodology for ensuring that changes in the graph regularizer using alternate views are performed in a manner that is target-concept specific, allowing value to be obtained from noisy views; and (2) we demonstrate how this general set-up can be used to effectively improve models by leveraging features unavailable at test time. The rest of the paper is structured as follows. In Section 2, we outline real-world problems to motivate the approach and describe relevant prior work. Section 3 describes the graph construction process and the learning methodologies that are employed. Section 4 provides preliminary discussion regarding theoretical motivation for the method. In Section 5, effectiveness of the approach is demonstrated in a series of experiments employing modified versions of two well-known semi-supervised learning algorithms. Section 6 concludes the paper.« less

Feature Clustering for Accelerating Parallel Coordinate Descent

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

Scherrer, Chad; Tewari, Ambuj; Halappanavar, Mahantesh

2012-12-06

We demonstrate an approach for accelerating calculation of the regularization path for L1 sparse logistic regression problems. We show the benefit of feature clustering as a preconditioning step for parallel block-greedy coordinate descent algorithms.

Breast Cancers Between Mammograms Have Aggressive Features

Cancer.gov

Breast cancers that are discovered in the period between regular screening mammograms—known as interval cancers—are more likely to have features associated with aggressive behavior and a poor prognosis than cancers found via screening mammograms.

Optimizing methods for linking cinematic features to fMRI data.

PubMed

Kauttonen, Janne; Hlushchuk, Yevhen; Tikka, Pia

2015-04-15

One of the challenges of naturalistic neurosciences using movie-viewing experiments is how to interpret observed brain activations in relation to the multiplicity of time-locked stimulus features. As previous studies have shown less inter-subject synchronization across viewers of random video footage than story-driven films, new methods need to be developed for analysis of less story-driven contents. To optimize the linkage between our fMRI data collected during viewing of a deliberately non-narrative silent film 'At Land' by Maya Deren (1944) and its annotated content, we combined the method of elastic-net regularization with the model-driven linear regression and the well-established data-driven independent component analysis (ICA) and inter-subject correlation (ISC) methods. In the linear regression analysis, both IC and region-of-interest (ROI) time-series were fitted with time-series of a total of 36 binary-valued and one real-valued tactile annotation of film features. The elastic-net regularization and cross-validation were applied in the ordinary least-squares linear regression in order to avoid over-fitting due to the multicollinearity of regressors, the results were compared against both the partial least-squares (PLS) regression and the un-regularized full-model regression. Non-parametric permutation testing scheme was applied to evaluate the statistical significance of regression. We found statistically significant correlation between the annotation model and 9 ICs out of 40 ICs. Regression analysis was also repeated for a large set of cubic ROIs covering the grey matter. Both IC- and ROI-based regression analyses revealed activations in parietal and occipital regions, with additional smaller clusters in the frontal lobe. Furthermore, we found elastic-net based regression more sensitive than PLS and un-regularized regression since it detected a larger number of significant ICs and ROIs. Along with the ISC ranking methods, our regression analysis proved a feasible method for ordering the ICs based on their functional relevance to the annotated cinematic features. The novelty of our method is - in comparison to the hypothesis-driven manual pre-selection and observation of some individual regressors biased by choice - in applying data-driven approach to all content features simultaneously. We found especially the combination of regularized regression and ICA useful when analyzing fMRI data obtained using non-narrative movie stimulus with a large set of complex and correlated features. Copyright © 2015. Published by Elsevier Inc.

Breast masses in mammography classification with local contour features.

PubMed

Li, Haixia; Meng, Xianjing; Wang, Tingwen; Tang, Yuchun; Yin, Yilong

2017-04-14

Mammography is one of the most popular tools for early detection of breast cancer. Contour of breast mass in mammography is very important information to distinguish benign and malignant mass. Contour of benign mass is smooth and round or oval, while malignant mass has irregular shape and spiculated contour. Several studies have shown that 1D signature translated from 2D contour can describe the contour features well. In this paper, we propose a new method to translate 2D contour of breast mass in mammography into 1D signature. The method can describe not only the contour features but also the regularity of breast mass. Then we segment the whole 1D signature into different subsections. We extract four local features including a new contour descriptor from the subsections. The new contour descriptor is root mean square (RMS) slope. It can describe the roughness of the contour. KNN, SVM and ANN classifier are used to classify benign breast mass and malignant mass. The proposed method is tested on a set with 323 contours including 143 benign masses and 180 malignant ones from digital database of screening mammography (DDSM). The best accuracy of classification is 99.66% using the feature of root mean square slope with SVM classifier. The performance of the proposed method is better than traditional method. In addition, RMS slope is an effective feature comparable to most of the existing features.

A Unified Approach for Solving Nonlinear Regular Perturbation Problems

ERIC Educational Resources Information Center

Khuri, S. A.

2008-01-01

This article describes a simple alternative unified method of solving nonlinear regular perturbation problems. The procedure is based upon the manipulation of Taylor's approximation for the expansion of the nonlinear term in the perturbed equation. An essential feature of this technique is the relative simplicity used and the associated unified…

Health Care Indicators

PubMed Central

Donham, Carolyn S.; Sensenig, Arthur L.

1994-01-01

This regular feature of the journal includes a discussion of each of the following four topics: community hospital statistics; employment, hours, and earnings in the private health sector; health care prices; and national economic indicators. These statistics are valuable in their own right for understanding the relationship between the health care sector and the overall economy. In addition, they allow us to anticipate the direction and magnitude of health care cost changes prior to the availability of more comprehensive data. PMID:10142373

Hospital, Employment, and Price Indicators for the Health Care Industry: Third Quarter 1996

PubMed Central

Sensenig, Arthur L.; Heffler, Stephen K.; Donham, Carolyn S.

1997-01-01

This regular feature of the journal includes a discussion of recent trends in health care spending, employment, and prices. The statistics presented in this article are valuable in their own right and for understanding the relationship between the health care sector and the overall economy. In addition, they allow us to anticipate the direction and magnitude of health care cost changes prior to the availability of more comprehensive data. PMID:10170351

Topic Repetition in Conversations on Different Days as a Sign of Dementia.

PubMed

Shinkawa, Kaoru; Yamada, Yasunori

2018-01-01

Detecting early signs of dementia in everyday situations becomes more and more important in a rapidly aging society. Language dysfunctions are recognized as the prominent signs of dementia. Previous computational studies characterized these language dysfunctions by using acoustic and linguistic features for detecting dementia. However, they mainly investigated language dysfunctions collected from patients during neuropsychological tests. Language dysfunctions observed during regular conversations in everyday situations received little attention. One of the dysfunctions associated with dementia which is frequently observed in regular conversations is the repetition of a topic on different days. In this study, we propose a feature to characterize topic repetition in conversations on different days. We used conversational data obtained from a daily monitoring service of eight elderly people, two of whom had dementia. Through the analysis of topic extraction with latent Dirichlet allocation, we found that the frequency of topic repetition was significantly higher in people with dementia than in the control group. The results suggest that our proposed feature for identifying topic repetition in regular conversations on different days might be used for detecting dementia.

Statistical universals reveal the structures and functions of human music.

PubMed

Savage, Patrick E; Brown, Steven; Sakai, Emi; Currie, Thomas E

2015-07-21

Music has been called "the universal language of mankind." Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation.

Statistical universals reveal the structures and functions of human music

PubMed Central

Savage, Patrick E.; Brown, Steven; Sakai, Emi; Currie, Thomas E.

2015-01-01

Music has been called “the universal language of mankind.” Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation. PMID:26124105

Search asymmetry: a diagnostic for preattentive processing of separable features.

PubMed

Treisman, A; Souther, J

1985-09-01

The search rate for a target among distractors may vary dramatically depending on which stimulus plays the role of target and which that of distractors. For example, the time required to find a circle distinguished by an intersecting line is independent of the number of regular circles in the display, whereas the time to find a regular circle among circles with lines increases linearly with the number of distractors. The pattern of performance suggests parallel processing when the target has a unique distinguishing feature and serial self-terminating search when the target is distinguished only by the absence of a feature that is present in all the distractors. The results are consistent with feature-integration theory (Treisman & Gelade, 1980), which predicts that a single feature should be detected by the mere presence of activity in the relevant feature map, whereas tasks that require subjects to locate multiple instances of a feature demand focused attention. Search asymmetries may therefore offer a new diagnostic to identify the primitive features of early vision. Several candidate features are examined in this article: Colors, line ends or terminators, and closure (in the sense of a partly or wholly enclosed area) appear to be functional features; connectedness, intactness (absence of an intersecting line), and acute angles do not.

A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD.

PubMed

Cao, Peng; Liu, Xiaoli; Zhang, Jian; Li, Wei; Zhao, Dazhe; Huang, Min; Zaiane, Osmar

2017-03-01

The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD). In this paper, we describes a new CT lung CAD method which aims to detect solid nodules. Specially, we proposed a multi-kernel classifier with a ℓ 2, 1 norm regularizer for heterogeneous feature fusion and selection from the feature subset level, and designed two efficient strategies to optimize the parameters of kernel weights in non-smooth ℓ 2, 1 regularized multiple kernel learning algorithm. The first optimization algorithm adapts a proximal gradient method for solving the ℓ 2, 1 norm of kernel weights, and use an accelerated method based on FISTA; the second one employs an iterative scheme based on an approximate gradient descent method. The results demonstrates that the FISTA-style accelerated proximal descent method is efficient for the ℓ 2, 1 norm formulation of multiple kernel learning with the theoretical guarantee of the convergence rate. Moreover, the experimental results demonstrate the effectiveness of the proposed methods in terms of Geometric mean (G-mean) and Area under the ROC curve (AUC), and significantly outperforms the competing methods. The proposed approach exhibits some remarkable advantages both in heterogeneous feature subsets fusion and classification phases. Compared with the fusion strategies of feature-level and decision level, the proposed ℓ 2, 1 norm multi-kernel learning algorithm is able to accurately fuse the complementary and heterogeneous feature sets, and automatically prune the irrelevant and redundant feature subsets to form a more discriminative feature set, leading a promising classification performance. Moreover, the proposed algorithm consistently outperforms the comparable classification approaches in the literature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Embedded Incremental Feature Selection for Reinforcement Learning

DTIC Science & Technology

2012-05-01

Prior to this work, feature selection for reinforce- ment learning has focused on linear value function ap- proximation ( Kolter and Ng, 2009; Parr et al...InProceed- ings of the the 23rd International Conference on Ma- chine Learning, pages 449–456. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature

Multi-task feature learning by using trace norm regularization

NASA Astrophysics Data System (ADS)

Jiangmei, Zhang; Binfeng, Yu; Haibo, Ji; Wang, Kunpeng

2017-11-01

Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.

Self-assembly of a binodal metal-organic framework exhibiting a demi-regular lattice.

PubMed

Yan, Linghao; Kuang, Guowen; Zhang, Qiushi; Shang, Xuesong; Liu, Pei Nian; Lin, Nian

2017-10-26

Designing metal-organic frameworks with new topologies is a long-standing quest because new topologies often accompany new properties and functions. Here we report that 1,3,5-tris[4-(pyridin-4-yl)phenyl]benzene molecules coordinate with Cu atoms to form a two-dimensional framework in which Cu adatoms form a nanometer-scale demi-regular lattice. The lattice is articulated by perfectly arranged twofold and threefold pyridyl-Cu coordination motifs in a ratio of 1 : 6 and features local dodecagonal symmetry. This structure is thermodynamically robust and emerges solely when the molecular density is at a critical value. In comparison, we present three framework structures that consist of semi-regular and regular lattices of Cu atoms self-assembled out of 1,3,5-tris[4-(pyridin-4-yl)phenyl]benzene and trispyridylbenzene molecules. Thus a family of regular, semi-regular and demi-regular lattices can be achieved by Cu-pyridyl coordination.

Systematic genomic identification of colorectal cancer genes delineating advanced from early clinical stage and metastasis

PubMed Central

2013-01-01

Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539

LCG/AA build infrastructure

NASA Astrophysics Data System (ADS)

Hodgkins, Alex Liam; Diez, Victor; Hegner, Benedikt

2012-12-01

The Software Process & Infrastructure (SPI) project provides a build infrastructure for regular integration testing and release of the LCG Applications Area software stack. In the past, regular builds have been provided using a system which has been constantly growing to include more features like server-client communication, long-term build history and a summary web interface using present-day web technologies. However, the ad-hoc style of software development resulted in a setup that is hard to monitor, inflexible and difficult to expand. The new version of the infrastructure is based on the Django Python framework, which allows for a structured and modular design, facilitating later additions. Transparency in the workflows and ease of monitoring has been one of the priorities in the design. Formerly missing functionality like on-demand builds or release triggering will support the transition to a more agile development process.

Application of Two-Parameter Stabilizing Functions in Solving a Convolution-Type Integral Equation by Regularization Method

NASA Astrophysics Data System (ADS)

Maslakov, M. L.

2018-04-01

This paper examines the solution of convolution-type integral equations of the first kind by applying the Tikhonov regularization method with two-parameter stabilizing functions. The class of stabilizing functions is expanded in order to improve the accuracy of the resulting solution. The features of the problem formulation for identification and adaptive signal correction are described. A method for choosing regularization parameters in problems of identification and adaptive signal correction is suggested.

High resolution skin colorimetry, strain mapping and mechanobiology.

PubMed

Devillers, C; Piérard-Franchimont, C; Schreder, A; Docquier, V; Piérard, G E

2010-08-01

Skin colours are notoriously different between individuals. They are governed by ethnicities and phototypes, and further influenced by a variety of factors including photoexposures and sustained mechanical stress. Indeed, mechanobiology is a feature affecting the epidermal melanization. High-resolution epiluminescence colorimetry helps in deciphering the effects of forces generated by Langer's lines or relaxed skin tension lines on the melanocyte activity. The same procedure shows a prominent laddering pattern of melanization in striae distensae contrasting with the regular honeycomb pattern in the surrounding skin.

Health Care Indicators: Hospital, Employment, and Price Indicators for the Health Care Industry: Fourth Quarter 1995 and Annual Data for 1987-95

PubMed Central

Heffler, Stephen K.; Donham, Carolyn S.; Won, Darleen K.; Sensenig, Arthur L.

1996-01-01

This regular feature of the journal includes a discussion of recent trends in health care spending, employment, and prices. The statistics presented in this article are valuable in their own right and for understanding the relationship between the health care sector and the overall economy. In addition, they allow us to anticipate the direction and magnitude of health care cost changes prior to the availability of more comprehensive data. PMID:10165709

Filter Bank Regularized Common Spatial Pattern Ensemble for Small Sample Motor Imagery Classification.

PubMed

Park, Sang-Hoon; Lee, David; Lee, Sang-Goog

2018-02-01

For the last few years, many feature extraction methods have been proposed based on biological signals. Among these, the brain signals have the advantage that they can be obtained, even by people with peripheral nervous system damage. Motor imagery electroencephalograms (EEG) are inexpensive to measure, offer a high temporal resolution, and are intuitive. Therefore, these have received a significant amount of attention in various fields, including signal processing, cognitive science, and medicine. The common spatial pattern (CSP) algorithm is a useful method for feature extraction from motor imagery EEG. However, performance degradation occurs in a small-sample setting (SSS), because the CSP depends on sample-based covariance. Since the active frequency range is different for each subject, it is also inconvenient to set the frequency range to be different every time. In this paper, we propose the feature extraction method based on a filter bank to solve these problems. The proposed method consists of five steps. First, motor imagery EEG is divided by a using filter bank. Second, the regularized CSP (R-CSP) is applied to the divided EEG. Third, we select the features according to mutual information based on the individual feature algorithm. Fourth, parameter sets are selected for the ensemble. Finally, we classify using ensemble based on features. The brain-computer interface competition III data set IVa is used to evaluate the performance of the proposed method. The proposed method improves the mean classification accuracy by 12.34%, 11.57%, 9%, 4.95%, and 4.47% compared with CSP, SR-CSP, R-CSP, filter bank CSP (FBCSP), and SR-FBCSP. Compared with the filter bank R-CSP ( , ), which is a parameter selection version of the proposed method, the classification accuracy is improved by 3.49%. In particular, the proposed method shows a large improvement in performance in the SSS.

On-line transmission electron microscopic image analysis of chromatin texture for differentiation of thyroid gland tumors.

PubMed

Kriete, A; Schäffer, R; Harms, H; Aus, H M

1987-06-01

Nuclei of the cells from the thyroid gland were analyzed in a transmission electron microscope by direct TV scanning and on-line image processing. The method uses the advantages of a visual-perception model to detect structures in noisy and low-contrast images. The features analyzed include area, a form factor and texture parameters from the second derivative stage. Three tumor-free thyroid tissues, three follicular adenomas, three follicular carcinomas and three papillary carcinomas were studied. The computer-aided cytophotometric method showed that the most significant differences were the statistics of the chromatin texture features of homogeneity and regularity. These findings document the possibility of an automated differentiation of tumors at the ultrastructural level.

A Variational Approach to the Denoising of Images Based on Different Variants of the TV-Regularization

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

Bildhauer, Michael, E-mail: bibi@math.uni-sb.de; Fuchs, Martin, E-mail: fuchs@math.uni-sb.de

2012-12-15

We discuss several variants of the TV-regularization model used in image recovery. The proposed alternatives are either of nearly linear growth or even of linear growth, but with some weak ellipticity properties. The main feature of the paper is the investigation of the analytic properties of the corresponding solutions.

Diminutivization supports gender acquisition in Russian children.

PubMed

Kempe, Vera; Brooks, Patricia J; Mironova, Natalija; Fedorova, Olga

2003-05-01

Gender agreement elicitation was used with Russian children to examine how diminutives common in Russian child-directed speech affect gender learning. Forty-six children (2;9-4;8) were shown pictures of familiar and of novel animals and asked to describe them after hearing their names, which all contained regular morphophonological cues to masculine or feminine gender. Half were presented as simplex (e.g. jozh 'porcupine') and half as diminutive forms (e.g. jozhik 'porcupine-DIM'). Children produced fewer agreement errors for diminutive than for simplex nouns, indicating that the regularizing features of diminutives enhance gender categorization. The study demonstrates how features of child-directed speech can facilitate language learning.

Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

Formative Work to Develop a Tailored HIV Testing Smartphone App for Diverse, At-Risk, HIV-Negative Men Who Have Sex With Men: A Focus Group Study.

PubMed

Mitchell, Jason W; Torres, Maria Beatriz; Joe, Jennifer; Danh, Thu; Gass, Bobbi; Horvath, Keith J

2016-11-16

Although gay, bisexual, and other men who have sex with men (MSM) are disproportionately affected by human immunodeficiency virus (HIV) infection, few test for HIV at regular intervals. Smartphone apps may be an ideal tool to increase regular testing among MSM. However, the success of apps to encourage regular testing among MSM will depend on how frequently the apps are downloaded, whether they continue to be used over months or years, and the degree to which such apps are tailored to the needs of this population. The primary objectives of this study were to answer the following questions. (1) What features and functions of smartphone apps do MSM believe are associated with downloading apps to their mobile phones? (2) What features and functions of smartphone apps are most likely to influence MSM's sustained use of apps over time? (3) What features and functions do MSM prefer in an HIV testing smartphone app? We conducted focus groups (n=7, with a total of 34 participants) with a racially and ethnically diverse group of sexually active HIV-negative MSM (mean age 32 years; 11/34 men, 33%, tested for HIV ≥10 months ago) in the United States in Miami, Florida and Minneapolis, Minnesota. Focus groups were digitally recorded, transcribed verbatim, and deidentified for analysis. We used a constant comparison method (ie, grounded theory coding) to examine and reexamine the themes that emerged from the focus groups. Men reported cost, security, and efficiency as their primary reasons influencing whether they download an app. Usefulness and perceived necessity, as well as peer and posted reviews, affected whether they downloaded and used the app over time. Factors that influenced whether they keep and continue to use an app over time included reliability, ease of use, and frequency of updates. Poor performance and functionality and lack of use were the primary reasons why men would delete an app from their phone. Participants also shared their preferences for an app to encourage regular HIV testing by providing feedback on test reminders, tailored testing interval recommendations, HIV test locator, and monitoring of personal sexual behaviors. Mobile apps for HIV prevention have proliferated, despite relatively little formative research to understand best practices for their development and implementation. The findings of this study suggest key design characteristics that should be used to guide development of an HIV testing app to promote regular HIV testing for MSM. The features and functions identified in this and prior research, as well as existing theories of behavior change, should be used to guide mobile app development in this critical area. ©Jason W Mitchell, Maria Beatriz Torres, Jennifer Joe, Thu Danh, Bobbi Gass, Keith J Horvath. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 16.11.2016.

History matching by spline approximation and regularization in single-phase areal reservoirs

NASA Technical Reports Server (NTRS)

Lee, T. Y.; Kravaris, C.; Seinfeld, J.

1986-01-01

An automatic history matching algorithm is developed based on bi-cubic spline approximations of permeability and porosity distributions and on the theory of regularization to estimate permeability or porosity in a single-phase, two-dimensional real reservoir from well pressure data. The regularization feature of the algorithm is used to convert the ill-posed history matching problem into a well-posed problem. The algorithm employs the conjugate gradient method as its core minimization method. A number of numerical experiments are carried out to evaluate the performance of the algorithm. Comparisons with conventional (non-regularized) automatic history matching algorithms indicate the superiority of the new algorithm with respect to the parameter estimates obtained. A quasioptimal regularization parameter is determined without requiring a priori information on the statistical properties of the observations.

An intelligent fault diagnosis method of rolling bearings based on regularized kernel Marginal Fisher analysis

NASA Astrophysics Data System (ADS)

Jiang, Li; Shi, Tielin; Xuan, Jianping

2012-05-01

Generally, the vibration signals of fault bearings are non-stationary and highly nonlinear under complicated operating conditions. Thus, it's a big challenge to extract optimal features for improving classification and simultaneously decreasing feature dimension. Kernel Marginal Fisher analysis (KMFA) is a novel supervised manifold learning algorithm for feature extraction and dimensionality reduction. In order to avoid the small sample size problem in KMFA, we propose regularized KMFA (RKMFA). A simple and efficient intelligent fault diagnosis method based on RKMFA is put forward and applied to fault recognition of rolling bearings. So as to directly excavate nonlinear features from the original high-dimensional vibration signals, RKMFA constructs two graphs describing the intra-class compactness and the inter-class separability, by combining traditional manifold learning algorithm with fisher criteria. Therefore, the optimal low-dimensional features are obtained for better classification and finally fed into the simplest K-nearest neighbor (KNN) classifier to recognize different fault categories of bearings. The experimental results demonstrate that the proposed approach improves the fault classification performance and outperforms the other conventional approaches.

Modern Pathologic Diagnosis of Renal Oncocytoma.

PubMed

Wobker, Sara E; Williamson, Sean R

2017-01-01

Oncocytoma is a well-defined benign renal tumor, with classic gross and histologic features, including a tan or mahogany-colored mass with central scar, microscopic nested architecture, bland cytology, and round, regular nuclei with prominent central nucleoli. As a result of variations in this classic appearance, difficulty in standardizing diagnostic criteria, and entities that mimic oncocytoma, such as eosinophilic variant chromophobe renal cell carcinoma and succinate dehydrogenase-deficient renal cell carcinoma, pathologic diagnosis remains a challenge. This review addresses the current state of pathologic diagnosis of oncocytoma, with emphasis on modern diagnostic markers, areas of controversy, and emerging techniques for less invasive diagnosis, including renal mass biopsy and advanced imaging.

Nonclassic Congenital Adrenal Hyperplasia

PubMed Central

Witchel, Selma Feldman; Azziz, Ricardo

2010-01-01

Nonclassic congenital adrenal hyperplasia (NCAH) due to P450c21 (21-hydroxylase deficiency) is a common autosomal recessive disorder. This disorder is due to mutations in the CYP21A2 gene which is located at chromosome 6p21. The clinical features predominantly reflect androgen excess rather than adrenal insufficiency leading to an ascertainment bias favoring diagnosis in females. Treatment goals include normal linear growth velocity and “on-time” puberty in affected children. For adolescent and adult women, treatment goals include regularization of menses, prevention of progression of hirsutism, and fertility. This paper will review key aspects regarding pathophysiology, diagnosis, and treatment of NCAH. PMID:20671993

Anxiety, Depression and Emotion Regulation Among Regular Online Poker Players.

PubMed

Barrault, Servane; Bonnaire, Céline; Herrmann, Florian

2017-12-01

Poker is a type of gambling that has specific features, including the need to regulate one's emotion to be successful. The aim of the present study is to assess emotion regulation, anxiety and depression in a sample of regular poker players, and to compare the results of problem and non-problem gamblers. 416 regular online poker players completed online questionnaires including sociodemographic data, measures of problem gambling (CPGI), anxiety and depression (HAD scale), and emotion regulation (ERQ). The CPGI was used to divide participants into four groups according to the intensity of their gambling practice (non-problem, low risk, moderate risk and problem gamblers). Anxiety and depression were significantly higher among severe-problem gamblers than among the other groups. Both significantly predicted problem gambling. On the other hand, there was no difference between groups in emotion regulation (cognitive reappraisal and expressive suppression), which was linked neither to problem gambling nor to anxiety and depression (except for cognitive reappraisal, which was significantly correlated to anxiety). Our results underline the links between anxiety, depression and problem gambling among poker players. If emotion regulation is involved in problem gambling among poker players, as strongly suggested by data from the literature, the emotion regulation strategies we assessed (cognitive reappraisal and expressive suppression) may not be those involved. Further studies are thus needed to investigate the involvement of other emotion regulation strategies.

Behavioral Interventions: Creating a Safe Environment in Our Schools.

ERIC Educational Resources Information Center

National Association of School Psychologists, Bethesda, MD.

This publication features articles on prevention of school violence and focuses upon promising practices that reflect practical approaches to positive behavioral interventions. Directed at both regular and special education students, these articles feature prosocial skills for improving student responsibility and discipline, effective parenting…

Coarse-graining time series data: Recurrence plot of recurrence plots and its application for music

NASA Astrophysics Data System (ADS)

Fukino, Miwa; Hirata, Yoshito; Aihara, Kazuyuki

2016-02-01

We propose a nonlinear time series method for characterizing two layers of regularity simultaneously. The key of the method is using the recurrence plots hierarchically, which allows us to preserve the underlying regularities behind the original time series. We demonstrate the proposed method with musical data. The proposed method enables us to visualize both the local and the global musical regularities or two different features at the same time. Furthermore, the determinism scores imply that the proposed method may be useful for analyzing emotional response to the music.

Coarse-graining time series data: Recurrence plot of recurrence plots and its application for music.

PubMed

Fukino, Miwa; Hirata, Yoshito; Aihara, Kazuyuki

2016-02-01

We propose a nonlinear time series method for characterizing two layers of regularity simultaneously. The key of the method is using the recurrence plots hierarchically, which allows us to preserve the underlying regularities behind the original time series. We demonstrate the proposed method with musical data. The proposed method enables us to visualize both the local and the global musical regularities or two different features at the same time. Furthermore, the determinism scores imply that the proposed method may be useful for analyzing emotional response to the music.

Nanostructure formation and regulation during low-energy ion beam sputtering of fused silica surfaces

NASA Astrophysics Data System (ADS)

Liao, Wenlin; Dai, Yi-Fan; Nie, Xutao; Nie, Xuqing; Xu, Mingjin

2017-12-01

Ion beam sputtering (IBS) possesses strong surface nanostructuring behaviors, where dual microscopic phenomenon can be aroused to induce the formation of ultrasmooth surfaces or regular nanostructures. Low-energy IBS of fused silica surfaces is investigated to discuss the formation mechanism and the regulation of the IBS-induced nanostructures. The research results indicate that these microscopic phenomena can be attributed to the interaction of the IBS-induced surface roughening and smoothing effects, and the interaction process strongly depends on the sputtering conditions. Alternatively, ultrasmooth surface or regular nanostructure can be selectively generated through the regulation of the nanostructuring process, and the features of the generated nanostructures, such as amplitude and period, also can be regulated. Consequently, two different technology aims of nanofabrication, including nanometer-scale and nanometer-precision fabrication, can be realized, respectively. These dual microscopic mechanisms distinguish IBS as a promising nanometer manufacturing technology for the optical surfaces.

A Modeling Approach for Burn Scar Assessment Using Natural Features and Elastic Property

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

Tsap, L V; Zhang, Y; Goldgof, D B

2004-04-02

A modeling approach is presented for quantitative burn scar assessment. Emphases are given to: (1) constructing a finite element model from natural image features with an adaptive mesh, and (2) quantifying the Young's modulus of scars using the finite element model and the regularization method. A set of natural point features is extracted from the images of burn patients. A Delaunay triangle mesh is then generated that adapts to the point features. A 3D finite element model is built on top of the mesh with the aid of range images providing the depth information. The Young's modulus of scars ismore » quantified with a simplified regularization functional, assuming that the knowledge of scar's geometry is available. The consistency between the Relative Elasticity Index and the physician's rating based on the Vancouver Scale (a relative scale used to rate burn scars) indicates that the proposed modeling approach has high potentials for image-based quantitative burn scar assessment.« less

Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

PubMed

Põder, Endel

2014-11-06

Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data. © 2014 ARVO.

Multi-label learning with fuzzy hypergraph regularization for protein subcellular location prediction.

PubMed

Chen, Jing; Tang, Yuan Yan; Chen, C L Philip; Fang, Bin; Lin, Yuewei; Shang, Zhaowei

2014-12-01

Protein subcellular location prediction aims to predict the location where a protein resides within a cell using computational methods. Considering the main limitations of the existing methods, we propose a hierarchical multi-label learning model FHML for both single-location proteins and multi-location proteins. The latent concepts are extracted through feature space decomposition and label space decomposition under the nonnegative data factorization framework. The extracted latent concepts are used as the codebook to indirectly connect the protein features to their annotations. We construct dual fuzzy hypergraphs to capture the intrinsic high-order relations embedded in not only feature space, but also label space. Finally, the subcellular location annotation information is propagated from the labeled proteins to the unlabeled proteins by performing dual fuzzy hypergraph Laplacian regularization. The experimental results on the six protein benchmark datasets demonstrate the superiority of our proposed method by comparing it with the state-of-the-art methods, and illustrate the benefit of exploiting both feature correlations and label correlations.

Design principles and developmental mechanisms underlying retinal mosaics.

PubMed

Reese, Benjamin E; Keeley, Patrick W

2015-08-01

Most structures within the central nervous system (CNS) are composed of different types of neuron that vary in both number and morphology, but relatively little is known about the interplay between these two features, i.e. about the population dynamics of a given cell type. How such arrays of neurons are distributed within a structure, and how they differentiate their dendrites relative to each other, are issues that have recently drawn attention in the invertebrate nervous system, where the genetic and molecular underpinnings of these organizing principles are being revealed in exquisite detail. The retina is one of the few locations where these principles have been extensively studied in the vertebrate CNS, indeed, where the design principles of 'mosaic regularity' and 'uniformity of coverage' were first explicitly defined, quantified, and related to each other. Recent studies have revealed a number of genes that influence the formation of these histotypical features in the retina, including homologues of those invertebrate genes, although close inspection reveals that they do not always mediate comparable developmental processes nor elucidate fundamental design principles. The present review considers just how pervasive these features of 'mosaic regularity' and 'uniform dendritic coverage' are within the mammalian retina, discussing the means by which such features can be assessed in the mature and developing nervous system and examining the limitations associated with those assessments. We then address the extent to which these two design principles co-exist within different populations of neurons, and how they are achieved during development. Finally, we consider the neural phenotypes obtained in mutant nervous systems, to address whether a prospective gene of interest underlies those very design principles. © 2014 The Authors. Biological Reviews © 2014 Cambridge Philosophical Society.

A simplifying feature of the heterotic one loop four graviton amplitude

NASA Astrophysics Data System (ADS)

Basu, Anirban

2018-01-01

We show that the weight four modular graph functions that contribute to the integrand of the t8t8D4R4 term at one loop in heterotic string theory do not require regularization, and hence the integrand is simple. This is unlike the graphs that contribute to the integrands of the other gravitational terms at this order in the low momentum expansion, and these integrands require regularization. This property persists for an infinite number of terms in the effective action, and their integrands do not require regularization. We find non-trivial relations between weight four graphs of distinct topologies that do not require regularization by performing trivial manipulations using auxiliary diagrams.

Can deformation of a polymer film with a rigid coating model geophysical processes?

NASA Astrophysics Data System (ADS)

Volynskii, A. L.; Bazhenov, S. L.

2007-12-01

The structural and mechanical behavior of polymer films with a thin rigid coating is analyzed. The behavior of such systems under applied stress is accompanied by the formation of a regular wavy surface relief and by regular fragmentation of the coating. The above phenomena are shown to be universal. Both phenomena (stress-induced development of a regular wavy surface relief and regular fragmentation of the coating) are provided by the specific features of mechanical stress transfer from a compliant soft support to a rigid thin coating. The above phenomena are associated with a specific structure of the system, which is referred to as “a rigid coating on a soft substratum” system (RCSS). Surface microrelief in RCSS systems is similar to the ocean floor relief in the vicinity of mid-oceanic ridges. Thus, the complex system composed of a young oceanic crust and upper Earth's mantle may be considered as typically “a solid coating on a soft substratum” system. Specific features of the ocean floor relief are analyzed in terms of the approach advanced for the description of the structural mechanical behavior of polymer films with a rigid coating. This analysis allowed to estimate the strength of an ocean floor.

Psoriasis or not? Review of 51 clinically confirmed cases reveals an expanded histopathologic spectrum of psoriasis.

PubMed

Chau, Thinh; Parsi, Kory K; Ogawa, Toru; Kiuru, Maija; Konia, Thomas; Li, Chin-Shang; Fung, Maxwell A

2017-12-01

Psoriasis is usually diagnosed clinically, so only non-classic or refractory cases tend to be biopsied. Diagnostic uncertainty persists when dermatopathologists encounter features regarded as non-classic for psoriasis. Define and document classic and non-classic histologic features in skin biopsies from patients with clinically confirmed psoriasis. Minimal clinical diagnostic criteria were informally validated and applied to a consecutive series of biopsies histologically consistent with psoriasis. Clinical confirmation required 2 of the following criteria: (1) classic morphology, (2) classic distribution, (3) nail pitting, and (4) family history, with #1 and/or #2 as 1 criterion in every case RESULTS: Fifty-one biopsies from 46 patients were examined. Classic features of psoriasis included hypogranulosis (96%), club-shaped rete ridges (96%), dermal papilla capillary ectasia (90%), Munro microabscess (78%), suprapapillary plate thinning (63%), spongiform pustules (53%), and regular acanthosis (14%). Non-classic features included irregular acanthosis (84%), junctional vacuolar alteration (76%), spongiosis (76%), dermal neutrophils (69%), necrotic keratinocytes (67%), hypergranulosis (65%), neutrophilic spongiosis (61%), dermal eosinophils (49%), compact orthokeratosis (37%), papillary dermal fibrosis (35%), lichenoid infiltrate (25%), plasma cells (16%), and eosinophilic spongiosis (8%). Psoriasis exhibits a broader histopathologic spectrum. The presence of some non-classic features does not necessarily exclude the possibility of psoriasis. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Wavelet-based edge correlation incorporated iterative reconstruction for undersampled MRI.

PubMed

Hu, Changwei; Qu, Xiaobo; Guo, Di; Bao, Lijun; Chen, Zhong

2011-09-01

Undersampling k-space is an effective way to decrease acquisition time for MRI. However, aliasing artifacts introduced by undersampling may blur the edges of magnetic resonance images, which often contain important information for clinical diagnosis. Moreover, k-space data is often contaminated by the noise signals of unknown intensity. To better preserve the edge features while suppressing the aliasing artifacts and noises, we present a new wavelet-based algorithm for undersampled MRI reconstruction. The algorithm solves the image reconstruction as a standard optimization problem including a ℓ(2) data fidelity term and ℓ(1) sparsity regularization term. Rather than manually setting the regularization parameter for the ℓ(1) term, which is directly related to the threshold, an automatic estimated threshold adaptive to noise intensity is introduced in our proposed algorithm. In addition, a prior matrix based on edge correlation in wavelet domain is incorporated into the regularization term. Compared with nonlinear conjugate gradient descent algorithm, iterative shrinkage/thresholding algorithm, fast iterative soft-thresholding algorithm and the iterative thresholding algorithm using exponentially decreasing threshold, the proposed algorithm yields reconstructions with better edge recovery and noise suppression. Copyright © 2011 Elsevier Inc. All rights reserved.

Regulatory sequence analysis tools.

PubMed

van Helden, Jacques

2003-07-01

The web resource Regulatory Sequence Analysis Tools (RSAT) (http://rsat.ulb.ac.be/rsat) offers a collection of software tools dedicated to the prediction of regulatory sites in non-coding DNA sequences. These tools include sequence retrieval, pattern discovery, pattern matching, genome-scale pattern matching, feature-map drawing, random sequence generation and other utilities. Alternative formats are supported for the representation of regulatory motifs (strings or position-specific scoring matrices) and several algorithms are proposed for pattern discovery. RSAT currently holds >100 fully sequenced genomes and these data are regularly updated from GenBank.

Middle-aged women's preferred theory-based features in mobile physical activity applications.

PubMed

Ehlers, Diane K; Huberty, Jennifer L

2014-09-01

The purpose of this study was to describe which theory-based behavioral and technological features middle-aged women prefer to be included in a mobile application designed to help them adopt and maintain regular physical activity (PA). Women aged 30 to 64 years (N = 120) completed an online survey measuring their demographics and mobile PA application preferences. The survey was developed upon behavioral principles of Social Cognitive Theory, recent mobile app research, and technology adoption principles of the Unified Theory of Acceptance and Use of Technology. Frequencies were calculated and content analyses conducted to identify which features women most preferred. Behavioral features that help women self-regulate their PA (PA tracking, goal-setting, progress monitoring) were most preferred. Technological features that enhance perceived effort expectancy and playfulness were most preferred. Many women reported the desire to interact and compete with others through the application. Theory-based PA self-regulation features and theory-based design features that improve perceived effort expectancy and playfulness may be most beneficial in a mobile PA application for middle-aged women. Opportunities to interact with other people and the employment of social, game-like activities may also be attractive. Interdisciplinary engagement of experts in PA behavior change, technology adoption, and software development is needed.

Engaging with Islamic Patterns

ERIC Educational Resources Information Center

Sugarman, Ian

2012-01-01

Islamic patterns were a regular feature in mathematics classrooms, and probably still feature in many wall displays. However, as part of the learning process, these ancient designs appear to have lost any significant contemporary appeal. Here, the power of software is engaged to bring the construction of Islamic type patterns up to date. Forget…

Consequentialism and harsh interrogations.

PubMed

Wynia, Matthew K

2005-01-01

With this issue, we begin a regular feature on bioethics and public health. We welcome Matthew K. Wynia, M.D., M.P.H., Director of the Institute for Ethics of the American Medical Association as our new Contributing Editor. If you have comments or suggestions regarding this feature, please email us at manuscript@ bioethics.net.

Characterizing Reinforcement Learning Methods through Parameterized Learning Problems

DTIC Science & Technology

2011-06-03

extraneous. The agent could potentially adapt these representational aspects by applying methods from feature selection ( Kolter and Ng, 2009; Petrik et al...611–616. AAAI Press. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature selection in least-squares temporal difference learning. In A. P

Wavelet domain image restoration with adaptive edge-preserving regularization.

PubMed

Belge, M; Kilmer, M E; Miller, E L

2000-01-01

In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.

The emergence of polychronization and feature binding in a spiking neural network model of the primate ventral visual system.

PubMed

Eguchi, Akihiro; Isbister, James B; Ahmad, Nasir; Stringer, Simon

2018-07-01

We present a hierarchical neural network model, in which subpopulations of neurons develop fixed and regularly repeating temporal chains of spikes (polychronization), which respond specifically to randomized Poisson spike trains representing the input training images. The performance is improved by including top-down and lateral synaptic connections, as well as introducing multiple synaptic contacts between each pair of pre- and postsynaptic neurons, with different synaptic contacts having different axonal delays. Spike-timing-dependent plasticity thus allows the model to select the most effective axonal transmission delay between neurons. Furthermore, neurons representing the binding relationship between low-level and high-level visual features emerge through visually guided learning. This begins to provide a way forward to solving the classic feature binding problem in visual neuroscience and leads to a new hypothesis concerning how information about visual features at every spatial scale may be projected upward through successive neuronal layers. We name this hypothetical upward projection of information the "holographic principle." (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Enhanced transformation of incidentally learned knowledge into explicit memory by dopaminergic modulation.

PubMed

Clos, Mareike; Sommer, Tobias; Schneider, Signe L; Rose, Michael

2018-01-01

During incidental learning statistical regularities are extracted from the environment without the intention to learn. Acquired implicit memory of these regularities can affect behavior in the absence of awareness. However, conscious insight in the underlying regularities can also develop during learning. Such emergence of explicit memory is an important learning mechanism that is assumed to involve prediction errors in the striatum and to be dopamine-dependent. Here we directly tested this hypothesis by manipulating dopamine levels during incidental learning in a modified serial reaction time task (SRTT) featuring a hidden regular sequence of motor responses in a placebo-controlled between-group study. Awareness for the sequential regularity was subsequently assessed using cued generation and additionally verified using free recall. The results demonstrated that dopaminergic modulation nearly doubled the amount of explicit sequence knowledge emerged during learning in comparison to the placebo group. This strong effect clearly argues for a causal role of dopamine-dependent processing for the development of awareness for sequential regularities during learning.

Two-layer contractive encodings for learning stable nonlinear features.

PubMed

Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven

2015-04-01

Unsupervised learning of feature hierarchies is often a good strategy to initialize deep architectures for supervised learning. Most existing deep learning methods build these feature hierarchies layer by layer in a greedy fashion using either auto-encoders or restricted Boltzmann machines. Both yield encoders which compute linear projections of input followed by a smooth thresholding function. In this work, we demonstrate that these encoders fail to find stable features when the required computation is in the exclusive-or class. To overcome this limitation, we propose a two-layer encoder which is less restricted in the type of features it can learn. The proposed encoder is regularized by an extension of previous work on contractive regularization. This proposed two-layer contractive encoder potentially poses a more difficult optimization problem, and we further propose to linearly transform hidden neurons of the encoder to make learning easier. We demonstrate the advantages of the two-layer encoders qualitatively on artificially constructed datasets as well as commonly used benchmark datasets. We also conduct experiments on a semi-supervised learning task and show the benefits of the proposed two-layer encoders trained with the linear transformation of perceptrons. Copyright © 2014 Elsevier Ltd. All rights reserved.

High-order graph matching based feature selection for Alzheimer's disease identification.

PubMed

Liu, Feng; Suk, Heung-Il; Wee, Chong-Yaw; Chen, Huafu; Shen, Dinggang

2013-01-01

One of the main limitations of l1-norm feature selection is that it focuses on estimating the target vector for each sample individually without considering relations with other samples. However, it's believed that the geometrical relation among target vectors in the training set may provide useful information, and it would be natural to expect that the predicted vectors have similar geometric relations as the target vectors. To overcome these limitations, we formulate this as a graph-matching feature selection problem between a predicted graph and a target graph. In the predicted graph a node is represented by predicted vector that may describe regional gray matter volume or cortical thickness features, and in the target graph a node is represented by target vector that include class label and clinical scores. In particular, we devise new regularization terms in sparse representation to impose high-order graph matching between the target vectors and the predicted ones. Finally, the selected regional gray matter volume and cortical thickness features are fused in kernel space for classification. Using the ADNI dataset, we evaluate the effectiveness of the proposed method and obtain the accuracies of 92.17% and 81.57% in AD and MCI classification, respectively.

Identification of chemogenomic features from drug–target interaction networks using interpretable classifiers

PubMed Central

Tabei, Yasuo; Pauwels, Edouard; Stoven, Véronique; Takemoto, Kazuhiro; Yamanishi, Yoshihiro

2012-01-01

Motivation: Drug effects are mainly caused by the interactions between drug molecules and their target proteins including primary targets and off-targets. Identification of the molecular mechanisms behind overall drug–target interactions is crucial in the drug design process. Results: We develop a classifier-based approach to identify chemogenomic features (the underlying associations between drug chemical substructures and protein domains) that are involved in drug–target interaction networks. We propose a novel algorithm for extracting informative chemogenomic features by using L1 regularized classifiers over the tensor product space of possible drug–target pairs. It is shown that the proposed method can extract a very limited number of chemogenomic features without loosing the performance of predicting drug–target interactions and the extracted features are biologically meaningful. The extracted substructure–domain association network enables us to suggest ligand chemical fragments specific for each protein domain and ligand core substructures important for a wide range of protein families. Availability: Softwares are available at the supplemental website. Contact: yamanishi@bioreg.kyushu-u.ac.jp Supplementary Information: Datasets and all results are available at http://cbio.ensmp.fr/~yyamanishi/l1binary/ . PMID:22962471

Clinical and genetic features of the patients with X-Linked agammaglobulinemia from Turkey: Single-centre experience.

PubMed

Esenboga, S; Cagdas, D; Ozgur, T T; Gur Cetinkaya, P; Turkdemir, L M; Sanal, O; VanDerBurg, M; Tezcan, I

2018-03-01

X-linked agammaglobulinemia is a primary immunodeficiency disorder resulting from BTK gene mutations. There are many studies in the literature suggesting contradictory ideas about phenotype-genotype correlation. The aim of this study was to identify the mutations and clinical findings of patients with XLA in Turkey, to determine long-term complications related to the disease and to analyse the phenotype-genotype correlation. Thirty-two patients with XLA diagnosed between 1985 and 2016 in Pediatric Immunology Department of Hacettepe University Ihsan Dogramaci Children's Hospital were investigated. A clinical survey including clinical features of the patients was completed, and thirty-two patients from 26 different families were included in the study. Getting early diagnosis and regular assessment with imaging techniques seem to be the most important issues for improving the health status of the patients with XLA. Early molecular analysis gives chance for definitive diagnosis and genetic counselling, but not for predicting the clinical severity and prognosis. © 2018 The Foundation for the Scandinavian Journal of Immunology.

Local/non-local regularized image segmentation using graph-cuts: application to dynamic and multispectral MRI.

PubMed

Hanson, Erik A; Lundervold, Arvid

2013-11-01

Multispectral, multichannel, or time series image segmentation is important for image analysis in a wide range of applications. Regularization of the segmentation is commonly performed using local image information causing the segmented image to be locally smooth or piecewise constant. A new spatial regularization method, incorporating non-local information, was developed and tested. Our spatial regularization method applies to feature space classification in multichannel images such as color images and MR image sequences. The spatial regularization involves local edge properties, region boundary minimization, as well as non-local similarities. The method is implemented in a discrete graph-cut setting allowing fast computations. The method was tested on multidimensional MRI recordings from human kidney and brain in addition to simulated MRI volumes. The proposed method successfully segment regions with both smooth and complex non-smooth shapes with a minimum of user interaction.

TRANSIENT LUNAR PHENOMENA: REGULARITY AND REALITY

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

Crotts, Arlin P. S.

2009-05-20

Transient lunar phenomena (TLPs) have been reported for centuries, but their nature is largely unsettled, and even their existence as a coherent phenomenon is controversial. Nonetheless, TLP data show regularities in the observations; a key question is whether this structure is imposed by processes tied to the lunar surface, or by terrestrial atmospheric or human observer effects. I interrogate an extensive catalog of TLPs to gauge how human factors determine the distribution of TLP reports. The sample is grouped according to variables which should produce differing results if determining factors involve humans, and not reflecting phenomena tied to the lunarmore » surface. Features dependent on human factors can then be excluded. Regardless of how the sample is split, the results are similar: {approx}50% of reports originate from near Aristarchus, {approx}16% from Plato, {approx}6% from recent, major impacts (Copernicus, Kepler, Tycho, and Aristarchus), plus several at Grimaldi. Mare Crisium produces a robust signal in some cases (however, Crisium is too large for a 'feature' as defined). TLP count consistency for these features indicates that {approx}80% of these may be real. Some commonly reported sites disappear from the robust averages, including Alphonsus, Ross D, and Gassendi. These reports begin almost exclusively after 1955, when TLPs became widely known and many more (and inexperienced) observers searched for TLPs. In a companion paper, we compare the spatial distribution of robust TLP sites to transient outgassing (seen by Apollo and Lunar Prospector instruments). To a high confidence, robust TLP sites and those of lunar outgassing correlate strongly, further arguing for the reality of TLPs.« less

Regularization of instabilities in gravity theories

NASA Astrophysics Data System (ADS)

Ramazanoǧlu, Fethi M.

2018-01-01

We investigate instabilities and their regularization in theories of gravitation. Instabilities can be beneficial since their growth often leads to prominent observable signatures, which makes them especially relevant to relatively low signal-to-noise ratio measurements such as gravitational wave detections. An indefinitely growing instability usually renders a theory unphysical; hence, a desirable instability should also come with underlying physical machinery that stops the growth at finite values, i.e., regularization mechanisms. The prototypical gravity theory that presents such an instability is the spontaneous scalarization phenomena of scalar-tensor theories, which feature a tachyonic instability. We identify the regularization mechanisms in this theory and show that they can be utilized to regularize other instabilities as well. Namely, we present theories in which spontaneous growth is triggered by a ghost rather than a tachyon and numerically calculate stationary solutions of scalarized neutron stars in these theories. We speculate on the possibility of regularizing known divergent instabilities in certain gravity theories using our findings and discuss alternative theories of gravitation in which regularized instabilities may be present. Even though we study many specific examples, our main point is the recognition of regularized instabilities as a common theme and unifying mechanism in a vast array of gravity theories.

Writing Feature Articles with Intermediate Students

ERIC Educational Resources Information Center

Morgan, Denise N.

2010-01-01

Students need regular opportunities to write expository text. However, focusing on report writing often leaves students without strong examples to study or analyze to guide and grow their own writing. Writing and studying feature articles, meant to inform and explain, can become an alternative to report writing, as they can easily be located in…

Speak Out for Children. Winter 1992/1993 through Summer/Fall 1994.

ERIC Educational Resources Information Center

Levy, David L., Ed.; Diamond, Elliott H., Ed.

1993-01-01

"Speak Out for Children" is the quarterly newsletter of the Children's Rights Council (CRC), which is concerned with the healthy development of children of divorced and separated parents. The newsletter consists of feature articles and regular sections and columns. Feature articles of Volume 8, Number 1 are: "The Controversial Truth: Two-Parent…

5 CFR 532.213 - Industries included in regular appropriated fund wage surveys.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 5 Administrative Personnel 1 2012-01-01 2012-01-01 false Industries included in regular... CIVIL SERVICE REGULATIONS PREVAILING RATE SYSTEMS Prevailing Rate Determinations § 532.213 Industries included in regular appropriated fund wage surveys. (a) The lead agency must include the industries in the...

5 CFR 532.213 - Industries included in regular appropriated fund wage surveys.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 5 Administrative Personnel 1 2013-01-01 2013-01-01 false Industries included in regular... CIVIL SERVICE REGULATIONS PREVAILING RATE SYSTEMS Prevailing Rate Determinations § 532.213 Industries included in regular appropriated fund wage surveys. (a) The lead agency must include the industries in the...

5 CFR 532.213 - Industries included in regular appropriated fund wage surveys.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 5 Administrative Personnel 1 2014-01-01 2014-01-01 false Industries included in regular... CIVIL SERVICE REGULATIONS PREVAILING RATE SYSTEMS Prevailing Rate Determinations § 532.213 Industries included in regular appropriated fund wage surveys. (a) The lead agency must include the industries in the...

Deviance detection based on regularity encoding along the auditory hierarchy: electrophysiological evidence in humans.

PubMed

Escera, Carles; Leung, Sumie; Grimm, Sabine

2014-07-01

Detection of changes in the acoustic environment is critical for survival, as it prevents missing potentially relevant events outside the focus of attention. In humans, deviance detection based on acoustic regularity encoding has been associated with a brain response derived from the human EEG, the mismatch negativity (MMN) auditory evoked potential, peaking at about 100-200 ms from deviance onset. By its long latency and cerebral generators, the cortical nature of both the processes of regularity encoding and deviance detection has been assumed. Yet, intracellular, extracellular, single-unit and local-field potential recordings in rats and cats have shown much earlier (circa 20-30 ms) and hierarchically lower (primary auditory cortex, medial geniculate body, inferior colliculus) deviance-related responses. Here, we review the recent evidence obtained with the complex auditory brainstem response (cABR), the middle latency response (MLR) and magnetoencephalography (MEG) demonstrating that human auditory deviance detection based on regularity encoding-rather than on refractoriness-occurs at latencies and in neural networks comparable to those revealed in animals. Specifically, encoding of simple acoustic-feature regularities and detection of corresponding deviance, such as an infrequent change in frequency or location, occur in the latency range of the MLR, in separate auditory cortical regions from those generating the MMN, and even at the level of human auditory brainstem. In contrast, violations of more complex regularities, such as those defined by the alternation of two different tones or by feature conjunctions (i.e., frequency and location) fail to elicit MLR correlates but elicit sizable MMNs. Altogether, these findings support the emerging view that deviance detection is a basic principle of the functional organization of the auditory system, and that regularity encoding and deviance detection is organized in ascending levels of complexity along the auditory pathway expanding from the brainstem up to higher-order areas of the cerebral cortex.

Sensor Placement Optimization using Chama

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

Klise, Katherine A.; Nicholson, Bethany L.; Laird, Carl Damon

Continuous or regularly scheduled monitoring has the potential to quickly identify changes in the environment. However, even with low - cost sensors, only a limited number of sensors can be deployed. The physical placement of these sensors, along with the sensor technology and operating conditions, can have a large impact on the performance of a monitoring strategy. Chama is an open source Python package which includes mixed - integer, stochastic programming formulations to determine sensor locations and technology that maximize monitoring effectiveness. The methods in Chama are general and can be applied to a wide range of applications. Chama ismore » currently being used to design sensor networks to monitor airborne pollutants and to monitor water quality in water distribution systems. The following documentation includes installation instructions and examples, description of software features, and software license. The software is intended to be used by regulatory agencies, industry, and the research community. It is assumed that the reader is familiar with the Python Programming Language. References are included for addit ional background on software components. Online documentation, hosted at http://chama.readthedocs.io/, will be updated as new features are added. The online version includes API documentation .« less

Psychosynthesis Workbook

ERIC Educational Resources Information Center

Synthesis, 1974

1974-01-01

A regular feature with practical ideas and techniques for enhancing one's personal development and integration. The theme for this issue is the subpersonalities or inner personages in each of us. (Author)

Recurrent miscarriage: principles of management.

PubMed

Li, T C

1998-02-01

Recurrent miscarriage is a heterogeneous condition which has many possible underlying causes. Ideally, couples with the problem should be managed in a dedicated miscarriage clinic, with thorough investigations according to a protocol, with structured history and investigation sheets. Counselling is an important feature and may be provided by a specially trained counsellor, or specialized nurse appropriately trained in counselling. Counselling should include an explanation of the possible underlying causes of the condition, and of the prognosis of each of the conditions. There is no definite cause of miscarriage in approximately half of the patients. No treatment is needed in this group, apart from reassurance and tender loving care. Treatment of unproven value, for example progesterone support in early pregnancy, should not be offered. Treatment offered empirically or as part of a research project should have a sound scientific and statistical basis, and should include careful counselling with informed consent of the patient. There are many controversial issues in the management of recurrent miscarriage; consequently, there is a need for locally agreed guidelines for management. Women who conceive again should be offered regular monitoring, including serial ultrasonography in the first trimester of pregnancy. An active audit programme to review regularly the various outcome measures set against defined targets should be established in the clinic.

General three-state model with biased population replacement: Analytical solution and application to language dynamics

NASA Astrophysics Data System (ADS)

Colaiori, Francesca; Castellano, Claudio; Cuskley, Christine F.; Loreto, Vittorio; Pugliese, Martina; Tria, Francesca

2015-01-01

Empirical evidence shows that the rate of irregular usage of English verbs exhibits discontinuity as a function of their frequency: the most frequent verbs tend to be totally irregular. We aim to qualitatively understand the origin of this feature by studying simple agent-based models of language dynamics, where each agent adopts an inflectional state for a verb and may change it upon interaction with other agents. At the same time, agents are replaced at some rate by new agents adopting the regular form. In models with only two inflectional states (regular and irregular), we observe that either all verbs regularize irrespective of their frequency, or a continuous transition occurs between a low-frequency state, where the lemma becomes fully regular, and a high-frequency one, where both forms coexist. Introducing a third (mixed) state, wherein agents may use either form, we find that a third, qualitatively different behavior may emerge, namely, a discontinuous transition in frequency. We introduce and solve analytically a very general class of three-state models that allows us to fully understand these behaviors in a unified framework. Realistic sets of interaction rules, including the well-known naming game (NG) model, result in a discontinuous transition, in agreement with recent empirical findings. We also point out that the distinction between speaker and hearer in the interaction has no effect on the collective behavior. The results for the general three-state model, although discussed in terms of language dynamics, are widely applicable.

Disease Prediction based on Functional Connectomes using a Scalable and Spatially-Informed Support Vector Machine

PubMed Central

Watanabe, Takanori; Kessler, Daniel; Scott, Clayton; Angstadt, Michael; Sripada, Chandra

2014-01-01

Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D “connectome space,” offering an additional layer of interpretability that could provide new insights about various disease processes. PMID:24704268

Management of prolonged post-operative ileus: evidence-based recommendations.

PubMed

Vather, Ryash; Bissett, Ian

2013-05-01

Prolonged post-operative ileus (PPOI) occurs in up to 25% of patients following major elective abdominal surgery. It is associated with a higher risk of developing post-operative complications, prolongs hospital stay and confers a significant financial load on health-care institutions. Literature outlining best-practice management strategies for PPOI is nebulous. The aim of this text was to review the literature and provide concise evidence-based recommendations for its management. A literature search through the Ovid MEDLINE, EMBASE, Google Scholar and Cochrane databases was performed from inception to July 2012 using a combination of keywords and MeSH terms. Review of the literature was followed by synthesis of concise recommendations for management accompanied by Strength of Recommendation Taxonomy (either A, B or C). Recommendations for management include regular evaluation and correction of electrolytes (B); review of analgesic prescription with weaning of narcotics and substitution with regular paracetamol, regular non-steroidal anti-inflammatory drugs if not contraindicated, and regular or as-required Tramadol (A); nasogastric decompression for those with nausea or vomiting as prominent features (C); isotonic dextrose-saline crystalloid maintenance fluids administered within a restrictive regimen (B); balanced isotonic crystalloid replacement fluids containing supplemental potassium, in equivalent volume to losses (C); regular ambulation (C); parenteral nutrition if unable to tolerate an adequate oral intake for more than 7 days post-operatively (A) and exclusion of precipitating pathology or alternate diagnoses if clinically suspected (C). Recommendations have a variable and frequently inconsistent evidence base. Further research is required to validate many of the outlined recommendations and to investigate novel interventions that may be used to shorten duration of PPOI. © 2013 The Authors. ANZ Journal of Surgery © 2013 Royal Australasian College of Surgeons.

Extremely Selective Attention: Eye-Tracking Studies of the Dynamic Allocation of Attention to Stimulus Features in Categorization

ERIC Educational Resources Information Center

Blair, Mark R.; Watson, Marcus R.; Walshe, R. Calen; Maj, Fillip

2009-01-01

Humans have an extremely flexible ability to categorize regularities in their environment, in part because of attentional systems that allow them to focus on important perceptual information. In formal theories of categorization, attention is typically modeled with weights that selectively bias the processing of stimulus features. These theories…

Classic of the Month. [Columns Compiled from Three Issues of "Notes Plus," September 1983 to January 1984.

ERIC Educational Resources Information Center

Notes Plus, 1984

1984-01-01

Three installments of "Classic of the Month," a regular feature of the National Council of Teachers of English publication, "Notes Plus," are presented in this compilation. Each installment of this feature is intended to provide teaching ideas related to a "classic" novel. The first article offers a variety of…

[Bioinformatics Analysis of Clustered Regularly Interspaced Short Palindromic Repeats in the Genomes of Shigella].

PubMed

Wang, Pengfei; Wang, Yingfang; Duan, Guangcai; Xue, Zerun; Wang, Linlin; Guo, Xiangjiao; Yang, Haiyan; Xi, Yuanlin

2015-04-01

This study was aimed to explore the features of clustered regularly interspaced short palindromic repeats (CRISPR) structures in Shigella by using bioinformatics. We used bioinformatics methods, including BLAST, alignment and RNA structure prediction, to analyze the CRISPR structures of Shigella genomes. The results showed that the CRISPRs existed in the four groups of Shigella, and the flanking sequences of upstream CRISPRs could be classified into the same group with those of the downstream. We also found some relatively conserved palindromic motifs in the leader sequences. Repeat sequences had the same group with corresponding flanking sequences, and could be classified into two different types by their RNA secondary structures, which contain "stem" and "ring". Some spacers were found to homologize with part sequences of plasmids or phages. The study indicated that there were correlations between repeat sequences and flanking sequences, and the repeats might act as a kind of recognition mechanism to mediate the interaction between foreign genetic elements and Cas proteins.

V3 spinal neurons establish a robust and balanced locomotor rhythm during walking.

PubMed

Zhang, Ying; Narayan, Sujatha; Geiman, Eric; Lanuza, Guillermo M; Velasquez, Tomoko; Shanks, Bayle; Akay, Turgay; Dyck, Jason; Pearson, Keir; Gosgnach, Simon; Fan, Chen-Ming; Goulding, Martyn

2008-10-09

A robust and well-organized rhythm is a key feature of many neuronal networks, including those that regulate essential behaviors such as circadian rhythmogenesis, breathing, and locomotion. Here we show that excitatory V3-derived neurons are necessary for a robust and organized locomotor rhythm during walking. When V3-mediated neurotransmission is selectively blocked by the expression of the tetanus toxin light chain subunit (TeNT), the regularity and robustness of the locomotor rhythm is severely perturbed. A similar degeneration in the locomotor rhythm occurs when the excitability of V3-derived neurons is reduced acutely by ligand-induced activation of the allatostatin receptor. The V3-derived neurons additionally function to balance the locomotor output between both halves of the spinal cord, thereby ensuring a symmetrical pattern of locomotor activity during walking. We propose that the V3 neurons establish a regular and balanced motor rhythm by distributing excitatory drive between both halves of the spinal cord.

netCDF Operators for Rapid Analysis of Measured and Modeled Swath-like Data

NASA Astrophysics Data System (ADS)

Zender, C. S.

2015-12-01

Swath-like data (hereafter SLD) are defined by non-rectangular and/or time-varying spatial grids in which one or more coordinates are multi-dimensional. It is often challenging and time-consuming to work with SLD, including all Level 2 satellite-retrieved data, non-rectangular subsets of Level 3 data, and model data on curvilinear grids. Researchers and data centers want user-friendly, fast, and powerful methods to specify, extract, serve, manipulate, and thus analyze, SLD. To meet these needs, large research-oriented agencies and modeling center such as NASA, DOE, and NOAA increasingly employ the netCDF Operators (NCO), an open-source scientific data analysis software package applicable to netCDF and HDF data. NCO includes extensive, fast, parallelized regridding features to facilitate analysis and intercomparison of SLD and model data. Remote sensing, weather and climate modeling and analysis communities face similar problems in handling SLD including how to easily: 1. Specify and mask irregular regions such as ocean basins and political boundaries in SLD (and rectangular) grids. 2. Bin, interpolate, average, or re-map SLD to regular grids. 3. Derive secondary data from given quality levels of SLD. These common tasks require a data extraction and analysis toolkit that is SLD-friendly and, like NCO, familiar in all these communities. With NCO users can 1. Quickly project SLD onto the most useful regular grids for intercomparison. 2. Access sophisticated statistical and regridding functions that are robust to missing data and allow easy specification of quality control metrics. These capabilities improve interoperability, software-reuse, and, because they apply to SLD, minimize transmission, storage, and handling of unwanted data. While SLD analysis still poses many challenges compared to regularly gridded, rectangular data, the custom analyses scripts SLD once required are now shorter, more powerful, and user-friendly.

Considering the Spatial Layout Information of Bag of Features (BoF) Framework for Image Classification.

PubMed

Mu, Guangyu; Liu, Ying; Wang, Limin

2015-01-01

The spatial pooling method such as spatial pyramid matching (SPM) is very crucial in the bag of features model used in image classification. SPM partitions the image into a set of regular grids and assumes that the spatial layout of all visual words obey the uniform distribution over these regular grids. However, in practice, we consider that different visual words should obey different spatial layout distributions. To improve SPM, we develop a novel spatial pooling method, namely spatial distribution pooling (SDP). The proposed SDP method uses an extension model of Gauss mixture model to estimate the spatial layout distributions of the visual vocabulary. For each visual word type, SDP can generate a set of flexible grids rather than the regular grids from the traditional SPM. Furthermore, we can compute the grid weights for visual word tokens according to their spatial coordinates. The experimental results demonstrate that SDP outperforms the traditional spatial pooling methods, and is competitive with the state-of-the-art classification accuracy on several challenging image datasets.

Stickney Crater on Phobos and some other outstanding planetary depressions as features of crustal wave interference origin

NASA Astrophysics Data System (ADS)

Kochemasov, G. G.

2011-10-01

Some not fully understood (enigmatic) large planetary depressions and geoid minima on planets and satellites are better understood as regular wave woven features, not random large impacts [1]. A main reason for this is their similar tectonic position in a regular sectoral network produced by interfering crossing standing waves warping any celestial body. These waves arise in the bodies due to their movements in keplerian elliptical orbits with changing accelerations. The fundamental wave1 produces universal tectonic dichotomy, its first overtone wave2 superposes on it sectoring - a regular network of risen and fallen blocks [2, 3]. Thus, deeply subsided sectoral blocks are formed on uplifted highland segments -hemispheres [1]. Examples of this pattern are shown in Fig. 1 to 8 on various globes and irregular bodies. The Moon - the SPA basin, Earth - Indian geoid min imum, Phobos - Stickney Crater, Miranda - an ovoid, Phoebe - a sector, Mars - Hellas Planitia, Lutetia - a deep sector indentation. Fig. 9 - a geometrical model of dichotomy and sectors format ion by wave interference.

Local Variation of Hashtag Spike Trains and Popularity in Twitter

PubMed Central

Sanlı, Ceyda; Lambiotte, Renaud

2015-01-01

We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamical properties, while properly detrending for the time-dependent features of a signal. The methodology is tested on both real and randomized hashtag spike trains, and identifies that popular hashtags present regular and so less bursty behavior, suggesting its potential use for predicting online popularity in social media. PMID:26161650

Complex Synchronization Phenomena in Ecological Systems

NASA Astrophysics Data System (ADS)

Stone, Lewi; Olinky, Ronen; Blasius, Bernd; Huppert, Amit; Cazelles, Bernard

2002-07-01

Ecological and biological systems provide us with many striking examples of synchronization phenomena. Here we discuss a number of intriguing cases and attempt to explain them taking advantage of a modelling framework. One main focus will concern synchronized ecological end epidemiological cycles which have Uniform Phase growth associated with their regular recurrence, and Chaotic Amplitudes - a feature we term UPCA. Examples come from different areas and include decadal cycles of small mammals, recurrent viral epidemics such as childhood infections (eg., measles), and seasonally driven phytoplankton blooms observed in lakes and the oceans. A more detailed theoretical analysis of seasonally synchronized chaotic population cycles is presented.

The addition of entropy-based regularity parameters improves sleep stage classification based on heart rate variability.

PubMed

Aktaruzzaman, M; Migliorini, M; Tenhunen, M; Himanen, S L; Bianchi, A M; Sassi, R

2015-05-01

The work considers automatic sleep stage classification, based on heart rate variability (HRV) analysis, with a focus on the distinction of wakefulness (WAKE) from sleep and rapid eye movement (REM) from non-REM (NREM) sleep. A set of 20 automatically annotated one-night polysomnographic recordings was considered, and artificial neural networks were selected for classification. For each inter-heartbeat (RR) series, beside features previously presented in literature, we introduced a set of four parameters related to signal regularity. RR series of three different lengths were considered (corresponding to 2, 6, and 10 successive epochs, 30 s each, in the same sleep stage). Two sets of only four features captured 99 % of the data variance in each classification problem, and both of them contained one of the new regularity features proposed. The accuracy of classification for REM versus NREM (68.4 %, 2 epochs; 83.8 %, 10 epochs) was higher than when distinguishing WAKE versus SLEEP (67.6 %, 2 epochs; 71.3 %, 10 epochs). Also, the reliability parameter (Cohens's Kappa) was higher (0.68 and 0.45, respectively). Sleep staging classification based on HRV was still less precise than other staging methods, employing a larger variety of signals collected during polysomnographic studies. However, cheap and unobtrusive HRV-only sleep classification proved sufficiently precise for a wide range of applications.

Diversity of human lip prints: a collaborative study of ethnically distinct world populations.

PubMed

Sharma, Namita Alok; Eldomiaty, Magda Ahmed; Gutiérrez-Redomero, Esperanza; George, Adekunle Olufemi; Garud, Rajendra Somnath; Sánchez-Andrés, Angeles; Almasry, Shaima Mohamed; Rivaldería, Noemí; Al-Gaidi, Sami Awda; Ilesanmi, Toyosi

2014-01-01

Cheiloscopy is a comparatively recent counterpart to the long established dactyloscopic studies. Ethnic variability of these lip groove patterns has not yet been explored. This study was a collaborative effort aimed at establishing cheiloscopic variations amongst modern human populations from four geographically and culturally far removed nations: India, Saudi Arabia, Spain and Nigeria. Lip prints from a total of 754 subjects were collected and each was divided into four equal quadrants. The patterns were classified into six regular types (A-F), while some patterns which could not be fitted into the regular ones were segregated into G groups (G-0, G-1, G-2). Furthermore, co-dominance of more than one pattern type in a single quadrant forced us to identify the combination (COM, G-COM) patterns. The remarkable feature noted after compilation of the data included pattern C (a bifurcate/branched prototype extending the entire height of the lip) being a frequent feature of the lips of all the populations studied, save for the Nigerian population in which it was completely absent and which showed a tendency for pattern A (a vertical linear groove) and a significantly higher susceptibility for combination (COM) patterns. Chi-square test and correspondence analysis applied to the frequency of patterns appearing in the defined topographical areas indicated a significant variation for the populations studied.

Salient Object Detection via Structured Matrix Decomposition.

PubMed

Peng, Houwen; Li, Bing; Ling, Haibin; Hu, Weiming; Xiong, Weihua; Maybank, Stephen J

2016-05-04

Low-rank recovery models have shown potential for salient object detection, where a matrix is decomposed into a low-rank matrix representing image background and a sparse matrix identifying salient objects. Two deficiencies, however, still exist. First, previous work typically assumes the elements in the sparse matrix are mutually independent, ignoring the spatial and pattern relations of image regions. Second, when the low-rank and sparse matrices are relatively coherent, e.g., when there are similarities between the salient objects and background or when the background is complicated, it is difficult for previous models to disentangle them. To address these problems, we propose a novel structured matrix decomposition model with two structural regularizations: (1) a tree-structured sparsity-inducing regularization that captures the image structure and enforces patches from the same object to have similar saliency values, and (2) a Laplacian regularization that enlarges the gaps between salient objects and the background in feature space. Furthermore, high-level priors are integrated to guide the matrix decomposition and boost the detection. We evaluate our model for salient object detection on five challenging datasets including single object, multiple objects and complex scene images, and show competitive results as compared with 24 state-of-the-art methods in terms of seven performance metrics.

3D model of fault and fissures structure of the Kovdor Baddeleyite-Apatite-Magnetite Deposit (NE of the Fennoscandian Shield)

NASA Astrophysics Data System (ADS)

Zhirov, Dmitry; Klimov, Sergey

2015-04-01

The Kovdor baddeleyite-apatite-magnetite deposit (KBAMD) is represented by a large vertical ore body and is located in the southwestern part of the Kovdor ultramafic-alkaline central-type intrusion. The intrusion represents a concentrically zoned complex of rocks with an oval shape in plan, and straight zoning, which complies with the injection and displacement of each of further magma phases from the center towards the periphery. The operation of the deposit in open pits started in 1962, and nowadays, it has produced over 500,000,000 tons of ore. This is one of the largest open pits in the Kola region, which is ca. 2 km long, 1.8 km wide, and over 400 m deep. Regular structural studies has been carried out since late 1970. A unique massif of spatial data has been accumulated so far to include over 25,000 measurements of fissures and faults from the surface, ca. 20,000 measurements of fissures in the oriented drill core (over 18 km) etc. Using this data base the 3D model of fault and fissures structure was designed. The analysis of one has resulted in the identification of a series of laws and features, which are necessary to be taken into account when designing a deep open pit and mining is carried out. These are mainly aspects concerning the origin, kinematics, mechanics and ratio of spatial extension of various fault systems, variation of their parameters at deep horizons, features of a modern stress field in the country rocks, etc. The 3D model has allowed to divide the whole fracture / fissure systems of the massif rocks into 2 large groups: prototectonic system of joints, including cracks of 'liquid magmatic (carbonatite stage) contraction genesis', and newly formed faults due to the superimposed tectonic stages. With regard to the deposit scale, these are characterized as intraformational and transformational, respectively. Each group shows a set (an assemblage) of fault systems with unique features and signs, as well as regular interconnections. The prototectonic assemblage of fissures includes the following main systems: 2-3 subsystems Rd of radial with angle of dip within 65-90° (median at 78°), two subsystems S of a circular subvertical (tangential, crossing Rd) with angle of dip within 60-90° (74°), and two diagonal-conic ones: a centriclinal C dipping towards the center of the intrusion at angles of 25-55° (43°), and a periclinal P dipping from the center of the intrusion at angles of 5-35° (18°). The system of subhorizontal joints L (angle of dip within 0-12°) at deep horizons is insignificantly manifested. All the prototectonic systems are regularly interrelated, and vary asymuthal features according to the law of axial symmetry (when moving around the vertical axis of symmetry passed through the geometric center of the carbonatite intrusion). The superimposed tectonics of post-ore stages forms a few large faults and systems of rupture discontinuities. A few (up to 3) variously oriented displacements are documented in the field on kinematic features (slide furrows, oriented cleavages). They were used for reconstruction of stresses and tectonic evolution. The superimposed tectonic faulting has heterogeneous (local) distribution in the rocks of the deposit, and slight predictability of main parameters. This study was supported by the Russian Scientific Fund (project nos. 14-17-00751).

Recovering fine details from under-resolved electron tomography data using higher order total variation ℓ 1 regularization

DOE PAGES

Sanders, Toby; Gelb, Anne; Platte, Rodrigo B.; ...

2017-01-03

Over the last decade or so, reconstruction methods using ℓ 1 regularization, often categorized as compressed sensing (CS) algorithms, have significantly improved the capabilities of high fidelity imaging in electron tomography. The most popular ℓ 1 regularization approach within electron tomography has been total variation (TV) regularization. In addition to reducing unwanted noise, TV regularization encourages a piecewise constant solution with sparse boundary regions. In this paper we propose an alternative ℓ 1 regularization approach for electron tomography based on higher order total variation (HOTV). Like TV, the HOTV approach promotes solutions with sparse boundary regions. In smooth regions however,more » the solution is not limited to piecewise constant behavior. We demonstrate that this allows for more accurate reconstruction of a broader class of images – even those for which TV was designed for – particularly when dealing with pragmatic tomographic sampling patterns and very fine image features. In conclusion, we develop results for an electron tomography data set as well as a phantom example, and we also make comparisons with discrete tomography approaches.« less

Moving force identification based on redundant concatenated dictionary and weighted l1-norm regularization

NASA Astrophysics Data System (ADS)

Pan, Chu-Dong; Yu, Ling; Liu, Huan-Lin; Chen, Ze-Peng; Luo, Wen-Feng

2018-01-01

Moving force identification (MFI) is an important inverse problem in the field of bridge structural health monitoring (SHM). Reasonable signal structures of moving forces are rarely considered in the existing MFI methods. Interaction forces are complex because they contain both slowly-varying harmonic and impact signals due to bridge vibration and bumps on a bridge deck, respectively. Therefore, the interaction forces are usually hard to be expressed completely and sparsely by using a single basis function set. Based on the redundant concatenated dictionary and weighted l1-norm regularization method, a hybrid method is proposed for MFI in this study. The redundant dictionary consists of both trigonometric functions and rectangular functions used for matching the harmonic and impact signal features of unknown moving forces. The weighted l1-norm regularization method is introduced for formulation of MFI equation, so that the signal features of moving forces can be accurately extracted. The fast iterative shrinkage-thresholding algorithm (FISTA) is used for solving the MFI problem. The optimal regularization parameter is appropriately chosen by the Bayesian information criterion (BIC) method. In order to assess the accuracy and the feasibility of the proposed method, a simply-supported beam bridge subjected to a moving force is taken as an example for numerical simulations. Finally, a series of experimental studies on MFI of a steel beam are performed in laboratory. Both numerical and experimental results show that the proposed method can accurately identify the moving forces with a strong robustness, and it has a better performance than the Tikhonov regularization method. Some related issues are discussed as well.

Turkey Meatloaf

MedlinePlus

... this page: https://medlineplus.gov/recipe/turkeymeatloaf.html Turkey Meatloaf To use the sharing features on this ... old dinner favorite. Ingredients 1 lb lean ground turkey 1/2 cup regular oats, dry 1 large ...

Semi-regular remeshing based trust region spherical geometry image for 3D deformed mesh used MLWNN

NASA Astrophysics Data System (ADS)

Dhibi, Naziha; Elkefi, Akram; Bellil, Wajdi; Ben Amar, Chokri

2017-03-01

Triangular surface are now widely used for modeling three-dimensional object, since these models are very high resolution and the geometry of the mesh is often very dense, it is then necessary to remesh this object to reduce their complexity, the mesh quality (connectivity regularity) must be ameliorated. In this paper, we review the main methods of semi-regular remeshing of the state of the art, given the semi-regular remeshing is mainly relevant for wavelet-based compression, then we present our method for re-meshing based trust region spherical geometry image to have good scheme of 3d mesh compression used to deform 3D meh based on Multi library Wavelet Neural Network structure (MLWNN). Experimental results show that the progressive re-meshing algorithm capable of obtaining more compact representations and semi-regular objects and yield an efficient compression capabilities with minimal set of features used to have good 3D deformation scheme.

Feature extraction for change analysis in SAR time series

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten; Hinz, Stefan

2015-10-01

In remote sensing, the change detection topic represents a broad field of research. If time series data is available, change detection can be used for monitoring applications. These applications require regular image acquisitions at identical time of day along a defined period. Focusing on remote sensing sensors, radar is especially well-capable for applications requiring regularity, since it is independent from most weather and atmospheric influences. Furthermore, regarding the image acquisitions, the time of day plays no role due to the independence from daylight. Since 2007, the German SAR (Synthetic Aperture Radar) satellite TerraSAR-X (TSX) permits the acquisition of high resolution radar images capable for the analysis of dense built-up areas. In a former study, we presented the change analysis of the Stuttgart (Germany) airport. The aim of this study is the categorization of detected changes in the time series. This categorization is motivated by the fact that it is a poor statement only to describe where and when a specific area has changed. At least as important is the statement about what has caused the change. The focus is set on the analysis of so-called high activity areas (HAA) representing areas changing at least four times along the investigated period. As first step for categorizing these HAAs, the matching HAA changes (blobs) have to be identified. Afterwards, operating in this object-based blob level, several features are extracted which comprise shape-based, radiometric, statistic, morphological values and one context feature basing on a segmentation of the HAAs. This segmentation builds on the morphological differential attribute profiles (DAPs). Seven context classes are established: Urban, infrastructure, rural stable, rural unstable, natural, water and unclassified. A specific HA blob is assigned to one of these classes analyzing the CovAmCoh time series signature of the surrounding segments. In combination, also surrounding GIS information is included to verify the CovAmCoh based context assignment. In this paper, the focus is set on the features extracted for a later change categorization procedure.

Sparse generalized linear model with L0 approximation for feature selection and prediction with big omics data.

PubMed

Liu, Zhenqiu; Sun, Fengzhu; McGovern, Dermot P

2017-01-01

Feature selection and prediction are the most important tasks for big data mining. The common strategies for feature selection in big data mining are L 1 , SCAD and MC+. However, none of the existing algorithms optimizes L 0 , which penalizes the number of nonzero features directly. In this paper, we develop a novel sparse generalized linear model (GLM) with L 0 approximation for feature selection and prediction with big omics data. The proposed approach approximate the L 0 optimization directly. Even though the original L 0 problem is non-convex, the problem is approximated by sequential convex optimizations with the proposed algorithm. The proposed method is easy to implement with only several lines of code. Novel adaptive ridge algorithms ( L 0 ADRIDGE) for L 0 penalized GLM with ultra high dimensional big data are developed. The proposed approach outperforms the other cutting edge regularization methods including SCAD and MC+ in simulations. When it is applied to integrated analysis of mRNA, microRNA, and methylation data from TCGA ovarian cancer, multilevel gene signatures associated with suboptimal debulking are identified simultaneously. The biological significance and potential clinical importance of those genes are further explored. The developed Software L 0 ADRIDGE in MATLAB is available at https://github.com/liuzqx/L0adridge.

The formation of ice sails

NASA Astrophysics Data System (ADS)

Fowler, A. C.; Mayer, C.

2017-11-01

Debris-covered glaciers are prone to the formation of a number of supraglacial geomorphological features, and generally speaking, their upper surfaces are far from level surfaces. Some of these features are due to radiation screening or enhancing properties of the debris cover, but theoretical explanations of the consequent surface forms are in their infancy. In this paper we consider a theoretical model for the formation of "ice sails", which are regularly spaced bare ice features which are found on debris-covered glaciers in the Karakoram.

Annotated checklist of Georgia birds

USGS Publications Warehouse

Beaton, G.; Sykes, P.W.; Parrish, J.W.

2003-01-01

This edition of the checklist includes 446 species, of which 407 are on the Regular Species List, 8 on the Provisional, and 31 on the Hypothetical. This new publication has been greatly expanded and much revised over the previous checklist (GOS Occasional Publ. No. 10, 1986, 48 pp., 6x9 inches) to a 7x10-inch format with an extensive Literature Cited section added, 22 species added to the Regular List, 2 to the Provisional List, and 9 to the Hypothetical List. Each species account is much more comprehensive over all previous editions of the checklist. Among some of the new features are citations for sources of most information used, high counts of individuals for each species on the Regular List, extreme dates of occurrence within physiographic regions, a list of abbreviations and acronyms, and for each species the highest form of verifiable documentation given with its repository institution with a catalog number. This checklist is helpful for anyone working with birds in the Southeastern United States or birding in that region. Sykes' contribution to this fifth edition of the Annotated Checklist of Georgia Birds includes: suggestion of the large format and spiral binding, use of Richard A. Parks' painting of the Barn Owl on the front cover, use of literature citations throughout, and inclusion of high counts for each species. Sykes helped plan all phases of the publication, wrote about 90% of the Introduction and 84 species accounts (Osprey through Red Phalarope), designed the four maps in the introduction section and format for the Literature Cited, and with Giff Beaton designed the layout of the title page.

"Change deafness" arising from inter-feature masking within a single auditory object.

PubMed

Barascud, Nicolas; Griffiths, Timothy D; McAlpine, David; Chait, Maria

2014-03-01

Our ability to detect prominent changes in complex acoustic scenes depends not only on the ear's sensitivity but also on the capacity of the brain to process competing incoming information. Here, employing a combination of psychophysics and magnetoencephalography (MEG), we investigate listeners' sensitivity in situations when two features belonging to the same auditory object change in close succession. The auditory object under investigation is a sequence of tone pips characterized by a regularly repeating frequency pattern. Signals consisted of an initial, regularly alternating sequence of three short (60 msec) pure tone pips (in the form ABCABC…) followed by a long pure tone with a frequency that is either expected based on the on-going regular pattern ("LONG expected"-i.e., "LONG-expected") or constitutes a pattern violation ("LONG-unexpected"). The change in LONG-expected is manifest as a change in duration (when the long pure tone exceeds the established duration of a tone pip), whereas the change in LONG-unexpected is manifest as a change in both the frequency pattern and a change in the duration. Our results reveal a form of "change deafness," in that although changes in both the frequency pattern and the expected duration appear to be processed effectively by the auditory system-cortical signatures of both changes are evident in the MEG data-listeners often fail to detect changes in the frequency pattern when that change is closely followed by a change in duration. By systematically manipulating the properties of the changing features and measuring behavioral and MEG responses, we demonstrate that feature changes within the same auditory object, which occur close together in time, appear to compete for perceptual resources.

Effects of metric hierarchy and rhyme predictability on word duration in The Cat in the Hat.

PubMed

Breen, Mara

2018-05-01

Word durations convey many types of linguistic information, including intrinsic lexical features like length and frequency and contextual features like syntactic and semantic structure. The current study was designed to investigate whether hierarchical metric structure and rhyme predictability account for durational variation over and above other features in productions of a rhyming, metrically-regular children's book: The Cat in the Hat (Dr. Seuss, 1957). One-syllable word durations and inter-onset intervals were modeled as functions of segment number, lexical frequency, word class, syntactic structure, repetition, and font emphasis. Consistent with prior work, factors predicting longer word durations and inter-onset intervals included more phonemes, lower frequency, first mention, alignment with a syntactic boundary, and capitalization. A model parameter corresponding to metric grid height improved model fit of word durations and inter-onset intervals. Specifically, speakers realized five levels of metric hierarchy with inter-onset intervals such that interval duration increased linearly with increased height in the metric hierarchy. Conversely, speakers realized only three levels of metric hierarchy with word duration, demonstrating that they shortened the highly predictable rhyme resolutions. These results further understanding of the factors that affect spoken word duration, and demonstrate the myriad cues that children receive about linguistic structure from nursery rhymes. Copyright © 2018 Elsevier B.V. All rights reserved.

Efficient robust conditional random fields.

PubMed

Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A

2015-10-01

Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.

The Use of E-Cigarettes.

PubMed

Eichler, Martin; Blettner, Maria; Singer, Susanne

2016-12-16

Electronic cigarettes (e-cigarettes) are a consumer product whose benefits and risks are currently debated. Advocates of the "tobacco harm reduction" strategy emphasize their potential as an aid to smoking cessation, while advocates of the precautionary principle emphasize their risks instead. There have been only a few studies to date on the prevalence of e-cigarette use in Germany. In May 2016, in collaboration with Forsa, an opinion research firm, we carried out a survey among 4002 randomly chosen persons aged 14 and older, asking them about their consumption of e-cigarettes with and without nicotine, reasons for using e-cigarettes, plans for future use, estimation of danger compared to that of tobacco products, smoking behavior, and sociodemographic features. 1.4% of the respondents used e-cigarettes regularly, and a further 2.2% had used them regularly in the past. 11.8% had at least tried them, including 32.7% of smokers and 2.3% of persons who had never smoked. 24.5% of ex-smokers who had quit smoking after 2010 had used e-cigarettes at least once. 20.7% of the respondents considered electronic cigarettes less dangerous than conventional cigarettes, 46.3% equally dangerous, and 16.1% more dangerous. An extrapolation of these data to the general population suggests that about one million persons in Germany use e-cigarettes regularly and another 1.55 million have done so in the past. The consumption of electronic cigarettes in Germany is not very widespread, but it is not negligible either. Nearly 1 in 8 Germans has tried e-cigarettes at least once. Regular consumers of e-cigarettes are almost exclusively smokers and ex-smokers.

Corticosteroid-treated chronic active hepatitis in remission: uncertain prognosis of chronic persistent hepatitis.

PubMed

Czaja, A J; Ludwig, J; Baggenstoss, A H; Wolf, A

1981-01-01

To assess the prognosis of patients with severe chronic hepatitis after histologic examination had shown an improvement to chronic persistent hepatitis, we followed 52 such patients regularly for 54 +/- 4 months after the cessation of corticosteroid therapy. In 24 patients, the condition deteriorated 7 +/- 1 months after therapy and required further treatment with prednisone. Histologic features of chronic active hepatitis, including bridging and multilobular necrosis, were documented in all 14 patients in whom biopsies were performed. In 20 of 24 patients, the disease responded to retreatment, but 13 again had relapses, and cirrhosis developed in two. Of 28 patients who remained asymptomatic for 48 +/- 6 months, 17 retained features of chronic persistent hepatitis, and nine had improvement to normal histologic features. Cirrhosis developed in two patients without clinical manifestations of active inflammation. Findings before and after treatment did not predict outcome. We conclude that severe chronic active hepatitis that has been treated with prednisone and converted to chronic persistent hepatitis will often and unpredictably deteriorate after treatment has been stopped. Cirrhosis develops rarely but may occur with or without clinically overt chronic active hepatitis.

For Men, Ignoring Diabetes Can Be Deadly

MedlinePlus

... page please turn Javascript on. Feature: Diabetes For Men, Ignoring Diabetes Can Be Deadly Past Issues / Fall ... that when it comes to their own health, men have fewer checkups with a regular healthcare provider ...

Random Variables: Simulations and Surprising Connections.

ERIC Educational Resources Information Center

Quinn, Robert J.; Tomlinson, Stephen

1999-01-01

Features activities for advanced second-year algebra students in grades 11 and 12. Introduces three random variables and considers an empirical and theoretical probability for each. Uses coins, regular dice, decahedral dice, and calculators. (ASK)

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction

PubMed Central

Lu, Hongyang; Wei, Jingbo; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values. PMID:27110235

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.

PubMed

Lu, Hongyang; Wei, Jingbo; Liu, Qiegen; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.

Intrinsic Patterns of Human Activity

NASA Astrophysics Data System (ADS)

Hu, Kun; Ivanov, Plamen Ch.; Chen, Zhi; Hilton, Michael; Stanley, H. Eugene; Shea, Steven

2003-03-01

Activity is one of the defining features of life. Control of human activity is complex, being influenced by many factors both extrinsic and intrinsic to the body. The most obvious extrinsic factors that affect activity are the daily schedule of planned events, such as work and recreation, as well as reactions to unforeseen or random events. These extrinsic factors may account for the apparently random fluctuations in human motion observed over short time scales. The most obvious intrinsic factors are the body clocks including the circadian pacemaker that influences our sleep/wake cycle and ultradian oscillators with shorter time scales [2, 3]. These intrinsic rhythms may account for the underlying regularity in average activity level over longer periods of up to 24 h. Here we ask if the known extrinsic and intrinsic factors fully account for all complex features observed in recordings of human activity. To this end, we measure activity over two weeks from forearm motion in subjects undergoing their regular daily routine. Utilizing concepts from statistical physics, we demonstrate that during wakefulness human activity possesses previously unrecognized complex dynamic patterns. These patterns of activity are characterized by robust fractal and nonlinear dynamics including a universal probability distribution and long-range power-law correlations that are stable over a wide range of time scales (from minutes to hours). Surprisingly, we find that these dynamic patterns are unaffected by changes in the average activity level that occur within individual subjects throughout the day and on different days of the week, and between subjects. Moreover, we find that these patterns persist when the same subjects undergo time-isolation laboratory experiments designed to account for the phase of the circadian pacemaker, and control the known extrinsic factors by restricting behaviors and manipulating scheduled events including the sleep/wake cycle. We attribute these newly discovered patterns to a robust intrinsic multi-scale dynamic regulation of human activity that is independent of known extrinsic factors, and independent from the circadian and ultradian rhythms.

Nonlocal sparse model with adaptive structural clustering for feature extraction of aero-engine bearings

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Li, Xiang; Yan, Ruqiang

2016-04-01

Fault information of aero-engine bearings presents two particular phenomena, i.e., waveform distortion and impulsive feature frequency band dispersion, which leads to a challenging problem for current techniques of bearing fault diagnosis. Moreover, although many progresses of sparse representation theory have been made in feature extraction of fault information, the theory also confronts inevitable performance degradation due to the fact that relatively weak fault information has not sufficiently prominent and sparse representations. Therefore, a novel nonlocal sparse model (coined NLSM) and its algorithm framework has been proposed in this paper, which goes beyond simple sparsity by introducing more intrinsic structures of feature information. This work adequately exploits the underlying prior information that feature information exhibits nonlocal self-similarity through clustering similar signal fragments and stacking them together into groups. Within this framework, the prior information is transformed into a regularization term and a sparse optimization problem, which could be solved through block coordinate descent method (BCD), is formulated. Additionally, the adaptive structural clustering sparse dictionary learning technique, which utilizes k-Nearest-Neighbor (kNN) clustering and principal component analysis (PCA) learning, is adopted to further enable sufficient sparsity of feature information. Moreover, the selection rule of regularization parameter and computational complexity are described in detail. The performance of the proposed framework is evaluated through numerical experiment and its superiority with respect to the state-of-the-art method in the field is demonstrated through the vibration signals of experimental rig of aircraft engine bearings.

Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification

PubMed Central

Satheesha, T. Y.; Prasad, M. N. Giri; Dhruve, Kashyap D.

2017-01-01

Melanoma mortality rates are the highest amongst skin cancer patients. Melanoma is life threating when it grows beyond the dermis of the skin. Hence, depth is an important factor to diagnose melanoma. This paper introduces a non-invasive computerized dermoscopy system that considers the estimated depth of skin lesions for diagnosis. A 3-D skin lesion reconstruction technique using the estimated depth obtained from regular dermoscopic images is presented. On basis of the 3-D reconstruction, depth and 3-D shape features are extracted. In addition to 3-D features, regular color, texture, and 2-D shape features are also extracted. Feature extraction is critical to achieve accurate results. Apart from melanoma, in-situ melanoma the proposed system is designed to diagnose basal cell carcinoma, blue nevus, dermatofibroma, haemangioma, seborrhoeic keratosis, and normal mole lesions. For experimental evaluations, the PH2, ISIC: Melanoma Project, and ATLAS dermoscopy data sets is considered. Different feature set combinations is considered and performance is evaluated. Significant performance improvement is reported the post inclusion of estimated depth and 3-D features. The good classification scores of sensitivity = 96%, specificity = 97% on PH2 data set and sensitivity = 98%, specificity = 99% on the ATLAS data set is achieved. Experiments conducted to estimate tumor depth from 3-D lesion reconstruction is presented. Experimental results achieved prove that the proposed computerized dermoscopy system is efficient and can be used to diagnose varied skin lesion dermoscopy images. PMID:28512610

Incorporating a Spatial Prior into Nonlinear D-Bar EIT Imaging for Complex Admittivities.

PubMed

Hamilton, Sarah J; Mueller, J L; Alsaker, M

2017-02-01

Electrical Impedance Tomography (EIT) aims to recover the internal conductivity and permittivity distributions of a body from electrical measurements taken on electrodes on the surface of the body. The reconstruction task is a severely ill-posed nonlinear inverse problem that is highly sensitive to measurement noise and modeling errors. Regularized D-bar methods have shown great promise in producing noise-robust algorithms by employing a low-pass filtering of nonlinear (nonphysical) Fourier transform data specific to the EIT problem. Including prior data with the approximate locations of major organ boundaries in the scattering transform provides a means of extending the radius of the low-pass filter to include higher frequency components in the reconstruction, in particular, features that are known with high confidence. This information is additionally included in the system of D-bar equations with an independent regularization parameter from that of the extended scattering transform. In this paper, this approach is used in the 2-D D-bar method for admittivity (conductivity as well as permittivity) EIT imaging. Noise-robust reconstructions are presented for simulated EIT data on chest-shaped phantoms with a simulated pneumothorax and pleural effusion. No assumption of the pathology is used in the construction of the prior, yet the method still produces significant enhancements of the underlying pathology (pneumothorax or pleural effusion) even in the presence of strong noise.

Automated method for measuring the extent of selective logging damage with airborne LiDAR data

NASA Astrophysics Data System (ADS)

Melendy, L.; Hagen, S. C.; Sullivan, F. B.; Pearson, T. R. H.; Walker, S. M.; Ellis, P.; Kustiyo; Sambodo, Ari Katmoko; Roswintiarti, O.; Hanson, M. A.; Klassen, A. W.; Palace, M. W.; Braswell, B. H.; Delgado, G. M.

2018-05-01

Selective logging has an impact on the global carbon cycle, as well as on the forest micro-climate, and longer-term changes in erosion, soil and nutrient cycling, and fire susceptibility. Our ability to quantify these impacts is dependent on methods and tools that accurately identify the extent and features of logging activity. LiDAR-based measurements of these features offers significant promise. Here, we present a set of algorithms for automated detection and mapping of critical features associated with logging - roads/decks, skid trails, and gaps - using commercial airborne LiDAR data as input. The automated algorithm was applied to commercial LiDAR data collected over two logging concessions in Kalimantan, Indonesia in 2014. The algorithm results were compared to measurements of the logging features collected in the field soon after logging was complete. The automated algorithm-mapped road/deck and skid trail features match closely with features measured in the field, with agreement levels ranging from 69% to 99% when adjusting for GPS location error. The algorithm performed most poorly with gaps, which, by their nature, are variable due to the unpredictable impact of tree fall versus the linear and regular features directly created by mechanical means. Overall, the automated algorithm performs well and offers significant promise as a generalizable tool useful to efficiently and accurately capture the effects of selective logging, including the potential to distinguish reduced impact logging from conventional logging.

Form drag in rivers due to small-scale natural topographic features: 2. Irregular sequences

USGS Publications Warehouse

Kean, J.W.; Smith, J.D.

2006-01-01

The size, shape, and spacing of small-scale topographic features found on the boundaries of natural streams, rivers, and floodplains can be quite variable. Consequently, a procedure for determining the form drag on irregular sequences of different-sized topographic features is essential for calculating near-boundary flows and sediment transport. A method for carrying out such calculations is developed in this paper. This method builds on the work of Kean and Smith (2006), which describes the flow field for the simpler case of a regular sequence of identical topographic features. Both approaches model topographic features as two-dimensional elements with Gaussian-shaped cross sections defined in terms of three parameters. Field measurements of bank topography are used to show that (1) the magnitude of these shape parameters can vary greatly between adjacent topographic features and (2) the variability of these shape parameters follows a lognormal distribution. Simulations using an irregular set of topographic roughness elements show that the drag on an individual element is primarily controlled by the size and shape of the feature immediately upstream and that the spatial average of the boundary shear stress over a large set of randomly ordered elements is relatively insensitive to the sequence of the elements. In addition, a method to transform the topography of irregular surfaces into an equivalently rough surface of regularly spaced, identical topographic elements also is given. The methods described in this paper can be used to improve predictions of flow resistance in rivers as well as quantify bank roughness.

5 CFR 532.221 - Industries included in regular nonappropriated fund surveys.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 5 Administrative Personnel 1 2014-01-01 2014-01-01 false Industries included in regular... CIVIL SERVICE REGULATIONS PREVAILING RATE SYSTEMS Prevailing Rate Determinations § 532.221 Industries... American Industry Classification System (NAICS) codes in all regular nonappropriated fund wage surveys...

3D first-arrival traveltime tomography with modified total variation regularization

NASA Astrophysics Data System (ADS)

Jiang, Wenbin; Zhang, Jie

2018-02-01

Three-dimensional (3D) seismic surveys have become a major tool in the exploration and exploitation of hydrocarbons. 3D seismic first-arrival traveltime tomography is a robust method for near-surface velocity estimation. A common approach for stabilizing the ill-posed inverse problem is to apply Tikhonov regularization to the inversion. However, the Tikhonov regularization method recovers smooth local structures while blurring the sharp features in the model solution. We present a 3D first-arrival traveltime tomography method with modified total variation (MTV) regularization to preserve sharp velocity contrasts and improve the accuracy of velocity inversion. To solve the minimization problem of the new traveltime tomography method, we decouple the original optimization problem into two following subproblems: a standard traveltime tomography problem with the traditional Tikhonov regularization and a L2 total variation problem. We apply the conjugate gradient method and split-Bregman iterative method to solve these two subproblems, respectively. Our synthetic examples show that the new method produces higher resolution models than the conventional traveltime tomography with Tikhonov regularization. We apply the technique to field data. The stacking section shows significant improvements with static corrections from the MTV traveltime tomography.

Nonsmooth, nonconvex regularizers applied to linear electromagnetic inverse problems

NASA Astrophysics Data System (ADS)

Hidalgo-Silva, H.; Gomez-Trevino, E.

2017-12-01

Tikhonov's regularization method is the standard technique applied to obtain models of the subsurface conductivity distribution from electric or electromagnetic measurements by solving UT (m) = | F (m) - d |2 + λ P(m). The second term correspond to the stabilizing functional, with P (m) = | ∇ m |2 the usual approach, and λ the regularization parameter. Due to the roughness penalizer inclusion, the model developed by Tikhonov's algorithm tends to smear discontinuities, a feature that may be undesirable. An important requirement for the regularizer is to allow the recovery of edges, and smooth the homogeneous parts. As is well known, Total Variation (TV) is now the standard approach to meet this requirement. Recently, Wang et.al. proved convergence for alternating direction method of multipliers in nonconvex, nonsmooth optimization. In this work we present a study of several algorithms for model recovering of Geosounding data based on Infimal Convolution, and also on hybrid, TV and second order TV and nonsmooth, nonconvex regularizers, observing their performance on synthetic and real data. The algorithms are based on Bregman iteration and Split Bregman method, and the geosounding method is the low-induction numbers magnetic dipoles. Non-smooth regularizers are considered using the Legendre-Fenchel transform.

The pollination biology of a pavement plain: pollinator visitation patterns.

PubMed

O'Brien, Mary H

1980-01-01

The pollination biology of the 20 plant species of a treeless, pavement plain in the San Bernardino Mountains of southern California was studied throughout one flowering season.Several patterns of pollinator activity recorded during the season underline the necessity for noting the activity of all insect pollinators whether specialized, non-specialized, regular, or occasional: 1) Occasional insect visitors were a feature of the visitation to nine of the twelve entomophilous plant species and were the sole pollinators for three of these twelve species. 2) The eight entomophilous plant species which had open, generalized flower morphologies received the heaviest pollinator visitation, while three of the four entomophilous species with specialized flower morphologies received little visitation. 3) Most regular flower visitors, whether bees, flies, or wasps, appeared to be similar with respect to number of plant species visited regularly, purity of pollen load, length of residence and localization of activity on the site. The question is raised as to whether such similarity of behavior as pollen vectors is a function of the low plant diversity or a feature commonly found when the pollen loads and behavior of different pollinator types are actually monitored.

A complex baleen whale call recorded in the Mariana Trench Marine National Monument.

PubMed

Nieukirk, Sharon L; Fregosi, Selene; Mellinger, David K; Klinck, Holger

2016-09-01

In fall 2014 and spring 2015, passive acoustic data were collected via autonomous gliders east of Guam in an area that included the Mariana Trench Marine National Monument. A short (2-4 s), complex sound was recorded that features a ∼38 Hz moan with both harmonics and amplitude modulation, followed by broad-frequency metallic-sounding sweeps up to 7.5 kHz. This sound was recorded regularly during both fall and spring surveys. Aurally, the sound is quite unusual and most resembles the minke whale "Star Wars" call. It is likely this sound is biological and produced by a baleen whale.

Hybrid near-optimal aeroassisted orbit transfer plane change trajectories

NASA Technical Reports Server (NTRS)

Calise, Anthony J.; Duckeman, Gregory A.

1994-01-01

In this paper, a hybrid methodology is used to determine optimal open loop controls for the atmospheric portion of the aeroassisted plane change problem. The method is hybrid in the sense that it combines the features of numerical collocation with the analytically tractable portions of the problem which result when the two-point boundary value problem is cast in the form of a regular perturbation problem. Various levels of approximation are introduced by eliminating particular collocation parameters and their effect upon problem complexity and required number of nodes is discussed. The results include plane changes of 10, 20, and 30 degrees for a given vehicle.

Expectations Do Not Alter Early Sensory Processing during Perceptual Decision-Making.

PubMed

Rungratsameetaweemana, Nuttida; Itthipuripat, Sirawaj; Salazar, Annalisa; Serences, John T

2018-06-13

Two factors play important roles in shaping perception: the allocation of selective attention to behaviorally relevant sensory features, and prior expectations about regularities in the environment. Signal detection theory proposes distinct roles of attention and expectation on decision-making such that attention modulates early sensory processing, whereas expectation influences the selection and execution of motor responses. Challenging this classic framework, recent studies suggest that expectations about sensory regularities enhance the encoding and accumulation of sensory evidence during decision-making. However, it is possible, that these findings reflect well documented attentional modulations in visual cortex. Here, we tested this framework in a group of male and female human participants by examining how expectations about stimulus features (orientation and color) and expectations about motor responses impacted electroencephalography (EEG) markers of early sensory processing and the accumulation of sensory evidence during decision-making (the early visual negative potential and the centro-parietal positive potential, respectively). We first demonstrate that these markers are sensitive to changes in the amount of sensory evidence in the display. Then we show, counter to recent findings, that neither marker is modulated by either feature or motor expectations, despite a robust effect of expectations on behavior. Instead, violating expectations about likely sensory features and motor responses impacts posterior alpha and frontal theta oscillations, signals thought to index overall processing time and cognitive conflict. These findings are inconsistent with recent theoretical accounts and suggest instead that expectations primarily influence decisions by modulating post-perceptual stages of information processing. SIGNIFICANCE STATEMENT Expectations about likely features or motor responses play an important role in shaping behavior. Classic theoretical frameworks posit that expectations modulate decision-making by biasing late stages of decision-making including the selection and execution of motor responses. In contrast, recent accounts suggest that expectations also modulate decisions by improving the quality of early sensory processing. However, these effects could instead reflect the influence of selective attention. Here we examine the effect of expectations about sensory features and motor responses on a set of electroencephalography (EEG) markers that index early sensory processing and later post-perceptual processing. Counter to recent empirical results, expectations have little effect on early sensory processing but instead modulate EEG markers of time-on-task and cognitive conflict. Copyright © 2018 the authors 0270-6474/18/385632-17$15.00/0.

Learning multiple rules simultaneously: Affixes are more salient than reduplications.

PubMed

Gervain, Judit; Endress, Ansgar D

2017-04-01

Language learners encounter numerous opportunities to learn regularities, but need to decide which of these regularities to learn, because some are not productive in their native language. Here, we present an account of rule learning based on perceptual and memory primitives (Endress, Dehaene-Lambertz, & Mehler, Cognition, 105(3), 577-614, 2007; Endress, Nespor, & Mehler, Trends in Cognitive Sciences, 13(8), 348-353, 2009), suggesting that learners preferentially learn regularities that are more salient to them, and that the pattern of salience reflects the frequency of language features across languages. We contrast this view with previous artificial grammar learning research, which suggests that infants "choose" the regularities they learn based on rational, Bayesian criteria (Frank & Tenenbaum, Cognition, 120(3), 360-371, 2013; Gerken, Cognition, 98(3)B67-B74, 2006, Cognition, 115(2), 362-366, 2010). In our experiments, adult participants listened to syllable strings starting with a syllable reduplication and always ending with the same "affix" syllable, or to syllable strings starting with this "affix" syllable and ending with the "reduplication". Both affixation and reduplication are frequently used for morphological marking across languages. We find three crucial results. First, participants learned both regularities simultaneously. Second, affixation regularities seemed easier to learn than reduplication regularities. Third, regularities in sequence offsets were easier to learn than regularities at sequence onsets. We show that these results are inconsistent with previous Bayesian rule learning models, but mesh well with the perceptual or memory primitives view. Further, we show that the pattern of salience revealed in our experiments reflects the distribution of regularities across languages. Ease of acquisition might thus be one determinant of the frequency of regularities across languages.

A regularized approach for geodesic-based semisupervised multimanifold learning.

PubMed

Fan, Mingyu; Zhang, Xiaoqin; Lin, Zhouchen; Zhang, Zhongfei; Bao, Hujun

2014-05-01

Geodesic distance, as an essential measurement for data dissimilarity, has been successfully used in manifold learning. However, most geodesic distance-based manifold learning algorithms have two limitations when applied to classification: 1) class information is rarely used in computing the geodesic distances between data points on manifolds and 2) little attention has been paid to building an explicit dimension reduction mapping for extracting the discriminative information hidden in the geodesic distances. In this paper, we regard geodesic distance as a kind of kernel, which maps data from linearly inseparable space to linear separable distance space. In doing this, a new semisupervised manifold learning algorithm, namely regularized geodesic feature learning algorithm, is proposed. The method consists of three techniques: a semisupervised graph construction method, replacement of original data points with feature vectors which are built by geodesic distances, and a new semisupervised dimension reduction method for feature vectors. Experiments on the MNIST, USPS handwritten digit data sets, MIT CBCL face versus nonface data set, and an intelligent traffic data set show the effectiveness of the proposed algorithm.

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

PubMed

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

2013-02-01

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

The Structure of Esperanto.

ERIC Educational Resources Information Center

Moore, John

1980-01-01

Gives a brief description of the features of Esperanto: phonetic spelling, a regular grammar with no exceptions to rules, an international vocabulary with a rule for adding new words, and a word-building system making full use of affixes. (Author/MES)

“Kerrr” black hole: The lord of the string

NASA Astrophysics Data System (ADS)

Smailagic, Anais; Spallucci, Euro

2010-04-01

Kerrr in the title is not a typo. The third “r” stands for regular, in the sense of pathology-free rotating black hole. We exhibit a long search-for, exact, Kerr-like, solution of the Einstein equations with novel features: (i) no curvature ring singularity; (ii) no “anti-gravity” universe with causality violating time-like closed world-lines; (iii) no “super-luminal” matter disk. The ring singularity is replaced by a classical, circular, rotating string with Planck tension representing the inner engine driving the rotation of all the surrounding matter. The resulting geometry is regular and smoothly interpolates among inner Minkowski space, borderline de Sitter and outer Kerr universe. The key ingredient to cure all unphysical features of the ordinary Kerr black hole is the choice of a “non-commutative geometry inspired” matter source as the input for the Einstein equations, in analogy with spherically symmetric black holes described in earlier works.

Retrieving cloudy atmosphere parameters from RPG-HATPRO radiometer data

NASA Astrophysics Data System (ADS)

Kostsov, V. S.

2015-03-01

An algorithm for simultaneously determining both tropospheric temperature and humidity profiles and cloud liquid water content from ground-based measurements of microwave radiation is presented. A special feature of this algorithm is that it combines different types of measurements and different a priori information on the sought parameters. The features of its use in processing RPG-HATPRO radiometer data obtained in the course of atmospheric remote sensing experiments carried out by specialists from the Faculty of Physics of St. Petersburg State University are discussed. The results of a comparison of both temperature and humidity profiles obtained using a ground-based microwave remote sensing method with those obtained from radiosonde data are analyzed. It is shown that this combined algorithm is comparable (in accuracy) to the classical method of statistical regularization in determining temperature profiles; however, this algorithm demonstrates better accuracy (when compared to the method of statistical regularization) in determining humidity profiles.

Regularization destriping of remote sensing imagery

NASA Astrophysics Data System (ADS)

Basnayake, Ranil; Bollt, Erik; Tufillaro, Nicholas; Sun, Jie; Gierach, Michelle

2017-07-01

We illustrate the utility of variational destriping for ocean color images from both multispectral and hyperspectral sensors. In particular, we examine data from a filter spectrometer, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar Partnership (NPP) orbiter, and an airborne grating spectrometer, the Jet Population Laboratory's (JPL) hyperspectral Portable Remote Imaging Spectrometer (PRISM) sensor. We solve the destriping problem using a variational regularization method by giving weights spatially to preserve the other features of the image during the destriping process. The target functional penalizes the neighborhood of stripes (strictly, directionally uniform features) while promoting data fidelity, and the functional is minimized by solving the Euler-Lagrange equations with an explicit finite-difference scheme. We show the accuracy of our method from a benchmark data set which represents the sea surface temperature off the coast of Oregon, USA. Technical details, such as how to impose continuity across data gaps using inpainting, are also described.

Distributed acoustic cues for caller identity in macaque vocalization.

PubMed

Fukushima, Makoto; Doyle, Alex M; Mullarkey, Matthew P; Mishkin, Mortimer; Averbeck, Bruno B

2015-12-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured 'coo' call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral-temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call's fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized.

Distributed acoustic cues for caller identity in macaque vocalization

PubMed Central

Doyle, Alex M.; Mullarkey, Matthew P.; Mishkin, Mortimer; Averbeck, Bruno B.

2015-01-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured ‘coo’ call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral–temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call’s fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized. PMID:27019727

Evasion of No-Hair Theorems and Novel Black-Hole Solutions in Gauss-Bonnet Theories

NASA Astrophysics Data System (ADS)

Antoniou, G.; Bakopoulos, A.; Kanti, P.

2018-03-01

We consider a general Einstein-scalar-Gauss-Bonnet theory with a coupling function f (ϕ ) . We demonstrate that black-hole solutions appear as a generic feature of this theory since a regular horizon and an asymptotically flat solution may be easily constructed under mild assumptions for f (ϕ ). We show that the existing no-hair theorems are easily evaded, and a large number of regular black-hole solutions with scalar hair are then presented for a plethora of coupling functions f (ϕ ).

Evasion of No-Hair Theorems and Novel Black-Hole Solutions in Gauss-Bonnet Theories.

PubMed

Antoniou, G; Bakopoulos, A; Kanti, P

2018-03-30

We consider a general Einstein-scalar-Gauss-Bonnet theory with a coupling function f(ϕ). We demonstrate that black-hole solutions appear as a generic feature of this theory since a regular horizon and an asymptotically flat solution may be easily constructed under mild assumptions for f(ϕ). We show that the existing no-hair theorems are easily evaded, and a large number of regular black-hole solutions with scalar hair are then presented for a plethora of coupling functions f(ϕ).

Joint Simultaneous Reconstruction of Regularized Building Superstructures from Low-Density LIDAR Data Using Icp

NASA Astrophysics Data System (ADS)

Wichmann, Andreas; Kada, Martin

2016-06-01

There are many applications for 3D city models, e.g., in visualizations, analysis, and simulations; each one requiring a certain level of detail to be effective. The overall trend goes towards including various kinds of anthropogenic and natural objects therein with ever increasing geometric and semantic details. A few years back, the featured 3D building models had only coarse roof geometry. But nowadays, they are expected to include detailed roof superstructures like dormers and chimneys. Several methods have been proposed for the automatic reconstruction of 3D building models from airborne based point clouds. However, they are usually unable to reliably recognize and reconstruct small roof superstructures as these objects are often represented by only few point measurements, especially in low-density point clouds. In this paper, we propose a recognition and reconstruction approach that overcomes this problem by identifying and simultaneously reconstructing regularized superstructures of similar shape. For this purpose, candidate areas for superstructures are detected by taking into account virtual sub-surface points that are assumed to lie on the main roof faces below the measured points. The areas with similar superstructures are detected, extracted, grouped together, and registered to one another with the Iterative Closest Point (ICP) algorithm. As an outcome, the joint point density of each detected group is increased, which helps to recognize the shape of the superstructure more reliably and in more detail. Finally, all instances of each group of superstructures are modeled at once and transformed back to their original position. Because superstructures are reconstructed in groups, symmetries, alignments, and regularities can be enforced in a straight-forward way. The validity of the approach is presented on a number of example buildings from the Vaihingen test data set.

Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging

PubMed Central

Reishofer, Gernot; Koschutnig, Karl; Langkammer, Christian; Porter, David; Jehna, Margit; Enzinger, Christian; Keeling, Stephen; Ebner, Franz

2013-01-01

Readout-segmented echo planar imaging with 2D navigator-based reacquisition is an uprising technique enabling the sampling of high-resolution diffusion images with reduced susceptibility artifacts. However, low signal from the small voxels and long scan times hamper the clinical applicability. Therefore, we introduce a regularization algorithm based on total variation that is applied directly on the entire diffusion tensor. The spatially varying regularization parameter is determined automatically dependent on spatial variations in signal-to-noise ratio thus, avoiding over- or under-regularization. Information about the noise distribution in the diffusion tensor is extracted from the diffusion weighted images by means of complex independent component analysis. Moreover, the combination of those features enables processing of the diffusion data absolutely user independent. Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking such as Mean Fiber Length, Track Count, Volume and Voxel Count. Specifically, for in vivo data findings suggest that tractography results from the regularized diffusion tensor based on one measurement (16 min) generates results comparable to the un-regularized data with three averages (48 min). This significant reduction in scan time renders high resolution (1×1×2.5 mm3) diffusion tensor imaging of the entire brain applicable in a clinical context. PMID:24019951

Continuous Dropout.

PubMed

Shen, Xu; Tian, Xinmei; Liu, Tongliang; Xu, Fang; Tao, Dacheng

2017-10-03

Dropout has been proven to be an effective algorithm for training robust deep networks because of its ability to prevent overfitting by avoiding the co-adaptation of feature detectors. Current explanations of dropout include bagging, naive Bayes, regularization, and sex in evolution. According to the activation patterns of neurons in the human brain, when faced with different situations, the firing rates of neurons are random and continuous, not binary as current dropout does. Inspired by this phenomenon, we extend the traditional binary dropout to continuous dropout. On the one hand, continuous dropout is considerably closer to the activation characteristics of neurons in the human brain than traditional binary dropout. On the other hand, we demonstrate that continuous dropout has the property of avoiding the co-adaptation of feature detectors, which suggests that we can extract more independent feature detectors for model averaging in the test stage. We introduce the proposed continuous dropout to a feedforward neural network and comprehensively compare it with binary dropout, adaptive dropout, and DropConnect on Modified National Institute of Standards and Technology, Canadian Institute for Advanced Research-10, Street View House Numbers, NORB, and ImageNet large scale visual recognition competition-12. Thorough experiments demonstrate that our method performs better in preventing the co-adaptation of feature detectors and improves test performance.

Form drag in rivers due to small-scale natural topographic features: 1. Regular sequences

USGS Publications Warehouse

Kean, J.W.; Smith, J.D.

2006-01-01

Small-scale topographic features are commonly found on the boundaries of natural rivers, streams, and floodplains. A simple method for determining the form drag on these features is presented, and the results of this model are compared to laboratory measurements. The roughness elements are modeled as Gaussian-shaped features defined in terms of three parameters: a protrusion height, H; a streamwise length scale, ??; and a spacing between crests, ??. This shape is shown to be a good approximation to a wide variety of natural topographic bank features. The form drag on an individual roughness element embedded in a series of identical elements is determined using the drag coefficient of the individual element and a reference velocity that includes the effects of roughness elements further upstream. In addition to calculating the drag on each element, the model determines the spatially averaged total stress, skin friction stress, and roughness height of the boundary. The effects of bank roughness on patterns of velocity and boundary shear stress are determined by combining the form drag model with a channel flow model. The combined model shows that drag on small-scale topographic features substantially alters the near-bank flow field. These methods can be used to improve predictions of flow resistance in rivers and to form the basis for fully predictive (no empirically adjusted parameters) channel flow models. They also provide a foundation for calculating the near-bank boundary shear stress fields necessary for determining rates of sediment transport and lateral erosion.

Noninvasive Dissection of Mouse Sleep Using a Piezoelectric Motion Sensor

PubMed Central

Yaghouby, Farid; Donohue, Kevin D.; O’Hara, Bruce F.; Sunderam, Sridhar

2015-01-01

Background Changes in autonomic control cause regular breathing during NREM sleep to fluctuate during REM. Piezoelectric cage-floor sensors have been used to successfully discriminate sleep and wake states in mice based on signal features related to respiration and other movements. This study presents a classifier for noninvasively classifying REM and NREM using a piezoelectric sensor. New Method Vigilance state was scored manually in 4-second epochs for 24-hour EEG/EMG recordings in twenty mice. An unsupervised classifier clustered piezoelectric signal features quantifying movement and respiration into three states: one active; and two inactive with regular and irregular breathing respectively. These states were hypothesized to correspond to Wake, NREM, and REM respectively. States predicted by the classifier were compared against manual EEG/EMG scores to test this hypothesis. Results Using only piezoelectric signal features, an unsupervised classifier distinguished Wake with high (89% sensitivity, 96% specificity) and REM with moderate (73% sensitivity, 75% specificity) accuracy, but NREM with poor sensitivity (51%) and high specificity (96%). The classifier sometimes confused light NREM sleep—characterized by irregular breathing and moderate delta EEG power—with REM. A supervised classifier improved sensitivities to 90, 81, and 67% and all specificities to over 90% for Wake, NREM, and REM respectively. Comparison with Existing Methods Unlike most actigraphic techniques, which only differentiate sleep from wake, the proposed piezoelectric method further dissects sleep based on breathing regularity into states strongly correlated with REM and NREM. Conclusions This approach could facilitate large-sample screening for genes influencing different sleep traits, besides drug studies or other manipulations. PMID:26582569

Conservative regularization of compressible dissipationless two-fluid plasmas

NASA Astrophysics Data System (ADS)

Krishnaswami, Govind S.; Sachdev, Sonakshi; Thyagaraja, A.

2018-02-01

This paper extends our earlier approach [cf. A. Thyaharaja, Phys. Plasmas 17, 032503 (2010) and Krishnaswami et al., Phys. Plasmas 23, 022308 (2016)] to obtaining à priori bounds on enstrophy in neutral fluids and ideal magnetohydrodynamics. This results in a far-reaching local, three-dimensional, non-linear, dispersive generalization of a KdV-type regularization to compressible/incompressible dissipationless 2-fluid plasmas and models derived therefrom (quasi-neutral, Hall, and ideal MHD). It involves the introduction of vortical and magnetic "twirl" terms λl 2 ( w l + ( q l / m l ) B ) × ( ∇ × w l ) in the ion/electron velocity equations ( l = i , e ) where w l are vorticities. The cut-off lengths λl and number densities nl must satisfy λl 2 n l = C l , where Cl are constants. A novel feature is that the "flow" current ∑ l q l n l v l in Ampère's law is augmented by a solenoidal "twirl" current ∑ l ∇ × ∇ × λl 2 j flow , l . The resulting equations imply conserved linear and angular momenta and a positive definite swirl energy density E * which includes an enstrophic contribution ∑ l ( 1 / 2 ) λl 2 ρ l wl 2 . It is shown that the equations admit a Hamiltonian-Poisson bracket formulation. Furthermore, singularities in ∇ × B are conservatively regularized by adding ( λB 2 / 2 μ 0 ) ( ∇ × B ) 2 to E * . Finally, it is proved that among regularizations that admit a Hamiltonian formulation and preserve the continuity equations along with the symmetries of the ideal model, the twirl term is unique and minimal in non-linearity and space derivatives of velocities.

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational ℓ1-Norm Regularization in the Derivative Domain

NASA Astrophysics Data System (ADS)

Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

2014-05-01

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall), and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients (called ℓ1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a data base of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

NASA Technical Reports Server (NTRS)

Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

2013-01-01

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Neural mechanisms of rhythm perception: current findings and future perspectives.

PubMed

Grahn, Jessica A

2012-10-01

Perception of temporal patterns is fundamental to normal hearing, speech, motor control, and music. Certain types of pattern understanding are unique to humans, such as musical rhythm. Although human responses to musical rhythm are universal, there is much we do not understand about how rhythm is processed in the brain. Here, I consider findings from research into basic timing mechanisms and models through to the neuroscience of rhythm and meter. A network of neural areas, including motor regions, is regularly implicated in basic timing as well as processing of musical rhythm. However, fractionating the specific roles of individual areas in this network has remained a challenge. Distinctions in activity patterns appear between "automatic" and "cognitively controlled" timing processes, but the perception of musical rhythm requires features of both automatic and controlled processes. In addition, many experimental manipulations rely on participants directing their attention toward or away from certain stimulus features, and measuring corresponding differences in neural activity. Many temporal features, however, are implicitly processed whether attended to or not, making it difficult to create controlled baseline conditions for experimental comparisons. The variety of stimuli, paradigms, and definitions can further complicate comparisons across domains or methodologies. Despite these challenges, the high level of interest and multitude of methodological approaches from different cognitive domains (including music, language, and motor learning) have yielded new insights and hold promise for future progress. Copyright © 2012 Cognitive Science Society, Inc.

Health Care Indicators for the United States

PubMed Central

Donham, Carolyn S.; Maple, Brenda T.; Levit, Katharine R.

1992-01-01

Contained in this regular feature of the journal is a section on each of the following four topics community hospital statistics; employment, hours, and earnings in the private health sector; health care prices; and national economic indicators. PMID:10122005

Complex supramolecular interfacial tessellation through convergent multi-step reaction of a dissymmetric simple organic precursor

NASA Astrophysics Data System (ADS)

Zhang, Yi-Qi; Paszkiewicz, Mateusz; Du, Ping; Zhang, Liding; Lin, Tao; Chen, Zhi; Klyatskaya, Svetlana; Ruben, Mario; Seitsonen, Ari P.; Barth, Johannes V.; Klappenberger, Florian

2018-03-01

Interfacial supramolecular self-assembly represents a powerful tool for constructing regular and quasicrystalline materials. In particular, complex two-dimensional molecular tessellations, such as semi-regular Archimedean tilings with regular polygons, promise unique properties related to their nontrivial structures. However, their formation is challenging, because current methods are largely limited to the direct assembly of precursors, that is, where structure formation relies on molecular interactions without using chemical transformations. Here, we have chosen ethynyl-iodophenanthrene (which features dissymmetry in both geometry and reactivity) as a single starting precursor to generate the rare semi-regular (3.4.6.4) Archimedean tiling with long-range order on an atomically flat substrate through a multi-step reaction. Intriguingly, the individual chemical transformations converge to form a symmetric alkynyl-Ag-alkynyl complex as the new tecton in high yields. Using a combination of microscopy and X-ray spectroscopy tools, as well as computational modelling, we show that in situ generated catalytic Ag complexes mediate the tecton conversion.

Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization

PubMed Central

Zhu, Qingxin; Niu, Xinzheng

2016-01-01

By combining with sparse kernel methods, least-squares temporal difference (LSTD) algorithms can construct the feature dictionary automatically and obtain a better generalization ability. However, the previous kernel-based LSTD algorithms do not consider regularization and their sparsification processes are batch or offline, which hinder their widespread applications in online learning problems. In this paper, we combine the following five techniques and propose two novel kernel recursive LSTD algorithms: (i) online sparsification, which can cope with unknown state regions and be used for online learning, (ii) L 2 and L 1 regularization, which can avoid overfitting and eliminate the influence of noise, (iii) recursive least squares, which can eliminate matrix-inversion operations and reduce computational complexity, (iv) a sliding-window approach, which can avoid caching all history samples and reduce the computational cost, and (v) the fixed-point subiteration and online pruning, which can make L 1 regularization easy to implement. Finally, simulation results on two 50-state chain problems demonstrate the effectiveness of our algorithms. PMID:27436996

Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization.

PubMed

Zhang, Chunyuan; Zhu, Qingxin; Niu, Xinzheng

2016-01-01

By combining with sparse kernel methods, least-squares temporal difference (LSTD) algorithms can construct the feature dictionary automatically and obtain a better generalization ability. However, the previous kernel-based LSTD algorithms do not consider regularization and their sparsification processes are batch or offline, which hinder their widespread applications in online learning problems. In this paper, we combine the following five techniques and propose two novel kernel recursive LSTD algorithms: (i) online sparsification, which can cope with unknown state regions and be used for online learning, (ii) L 2 and L 1 regularization, which can avoid overfitting and eliminate the influence of noise, (iii) recursive least squares, which can eliminate matrix-inversion operations and reduce computational complexity, (iv) a sliding-window approach, which can avoid caching all history samples and reduce the computational cost, and (v) the fixed-point subiteration and online pruning, which can make L 1 regularization easy to implement. Finally, simulation results on two 50-state chain problems demonstrate the effectiveness of our algorithms.

Fusion of shallow and deep features for classification of high-resolution remote sensing images

NASA Astrophysics Data System (ADS)

Gao, Lang; Tian, Tian; Sun, Xiao; Li, Hang

2018-02-01

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.

Weighted low-rank sparse model via nuclear norm minimization for bearing fault detection

NASA Astrophysics Data System (ADS)

Du, Zhaohui; Chen, Xuefeng; Zhang, Han; Yang, Boyuan; Zhai, Zhi; Yan, Ruqiang

2017-07-01

It is a fundamental task in the machine fault diagnosis community to detect impulsive signatures generated by the localized faults of bearings. The main goal of this paper is to exploit the low-rank physical structure of periodic impulsive features and further establish a weighted low-rank sparse model for bearing fault detection. The proposed model mainly consists of three basic components: an adaptive partition window, a nuclear norm regularization and a weighted sequence. Firstly, due to the periodic repetition mechanism of impulsive feature, an adaptive partition window could be designed to transform the impulsive feature into a data matrix. The highlight of partition window is to accumulate all local feature information and align them. Then, all columns of the data matrix share similar waveforms and a core physical phenomenon arises, i.e., these singular values of the data matrix demonstrates a sparse distribution pattern. Therefore, a nuclear norm regularization is enforced to capture that sparse prior. However, the nuclear norm regularization treats all singular values equally and thus ignores one basic fact that larger singular values have more information volume of impulsive features and should be preserved as much as possible. Therefore, a weighted sequence with adaptively tuning weights inversely proportional to singular amplitude is adopted to guarantee the distribution consistence of large singular values. On the other hand, the proposed model is difficult to solve due to its non-convexity and thus a new algorithm is developed to search one satisfying stationary solution through alternatively implementing one proximal operator operation and least-square fitting. Moreover, the sensitivity analysis and selection principles of algorithmic parameters are comprehensively investigated through a set of numerical experiments, which shows that the proposed method is robust and only has a few adjustable parameters. Lastly, the proposed model is applied to the wind turbine (WT) bearing fault detection and its effectiveness is sufficiently verified. Compared with the current popular bearing fault diagnosis techniques, wavelet analysis and spectral kurtosis, our model achieves a higher diagnostic accuracy.

Visual communications and image processing '92; Proceedings of the Meeting, Boston, MA, Nov. 18-20, 1992

NASA Astrophysics Data System (ADS)

Maragos, Petros

The topics discussed at the conference include hierarchical image coding, motion analysis, feature extraction and image restoration, video coding, and morphological and related nonlinear filtering. Attention is also given to vector quantization, morphological image processing, fractals and wavelets, architectures for image and video processing, image segmentation, biomedical image processing, and model-based analysis. Papers are presented on affine models for motion and shape recovery, filters for directly detecting surface orientation in an image, tracking of unresolved targets in infrared imagery using a projection-based method, adaptive-neighborhood image processing, and regularized multichannel restoration of color images using cross-validation. (For individual items see A93-20945 to A93-20951)

Results of complex annual parasitological monitoring in the coastal area of Kola Bay

NASA Astrophysics Data System (ADS)

Kuklin, V. V.; Kuklina, M. M.; Kisova, N. E.; Maslich, M. A.

2009-12-01

The results of annual parasitological monitoring in the coastal area near the Abram-mys (Kola Bay, Barents Sea) are presented. The studies were performed in 2006-2007 and included complex examination of the intermediate hosts (mollusks and crustaceans) and definitive hosts (marine fish and birds) of the helminths. The biodiversity of the parasite fauna, seasonal dynamics, and functioning patterns of the parasite systems were investigated. The basic regularities in parasite circulation were assessed in relation to their life cycle strategies and the ecological features of the intermediate and definitive hosts. The factors affecting the success of parasite circulation in the coastal ecosystems were revealed through analysis of parasite biodiversity and abundance dynamics.

Lex-SVM: exploring the potential of exon expression profiling for disease classification.

PubMed

Yuan, Xiongying; Zhao, Yi; Liu, Changning; Bu, Dongbo

2011-04-01

Exon expression profiling technologies, including exon arrays and RNA-Seq, measure the abundance of every exon in a gene. Compared with gene expression profiling technologies like 3' array, exon expression profiling technologies could detect alterations in both transcription and alternative splicing, therefore they are expected to be more sensitive in diagnosis. However, exon expression profiling also brings higher dimension, more redundancy, and significant correlation among features. Ignoring the correlation structure among exons of a gene, a popular classification method like L1-SVM selects exons individually from each gene and thus is vulnerable to noise. To overcome this limitation, we present in this paper a new variant of SVM named Lex-SVM to incorporate correlation structure among exons and known splicing patterns to promote classification performance. Specifically, we construct a new norm, ex-norm, including our prior knowledge on exon correlation structure to regularize the coefficients of a linear SVM. Lex-SVM can be solved efficiently using standard linear programming techniques. The advantage of Lex-SVM is that it can select features group-wisely, force features in a subgroup to take equal weihts and exclude the features that contradict the majority in the subgroup. Experimental results suggest that on exon expression profile, Lex-SVM is more accurate than existing methods. Lex-SVM also generates a more compact model and selects genes more consistently in cross-validation. Unlike L1-SVM selecting only one exon in a gene, Lex-SVM assigns equal weights to as many exons in a gene as possible, lending itself easier for further interpretation.

Polycystic ovarian syndrome.

PubMed

Khan, Khurshid A; Stas, Sameer; Kurukulasuriya, L Romayne

2006-01-01

Polycystic ovarian syndrome (PCOS) is the most common reproductive endocrinopathy of women during their childbearing years. A significant degree of controversy exists regarding the etiology of this syndrome, but there is a growing consensus that the key features include insulin resistance, androgen excess, and abnormal gonadotropin dynamics. Familial and genetic factors cause predisposition to PCOS. Insulin resistance and adiposity put women with PCOS at a higher risk for diabetes, hypertension, dyslipidemia, and cardiovascular disease. Even though the adverse health consequences associated with PCOS are substantial, most women are not aware of these risks. Early recognition and treatment of metabolic sequelae should be the main focus of clinicians. Lifestyle modifications, mainly a balanced diet, weight loss, and regular exercise, are of utmost importance. On the pharmacologic front, various therapies including metformin, thiazolidinediones, and others appear to be very promising in the management of cardiometabolic aspects of PCOS.

Asteroid Lightcurves from Etscorn Observatory

NASA Astrophysics Data System (ADS)

Klinglesmith, Daniel A., III; Hendrickx, Sebastian

2018-01-01

During 2017 August and September, we observed five spin-shape asteroids: 418 Alemannia, 1095 Tulipa, 2648 Owa, 3122 Florence, and 5040 Rabinowitz. The selections were by listed by Warner et al. (2017) in their regular MPB paper featuring photometric opportunities for the upcoming quarter.

Elastic energy storage in the shoulder and the evolution of high-speed throwing in Homo

PubMed Central

Roach, Neil T.; Venkadesan, Madhusudhan; Rainbow, Michael J.; Lieberman, Daniel E.

2013-01-01

Although some primates, including chimpanzees, throw objects occasionally1,2, only humans regularly throw projectiles with high speed and great accuracy. Darwin noted that humans’ unique throwing abilities, made possible when bipedalism emancipated the arms, enabled foragers to effectively hunt using projectiles3. However, there has been little consideration of the evolution of throwing in the years since Darwin made his observations, in part because of a lack of evidence on when, how, and why hominins evolved the ability to generate high-speed throws4-8. Here, we show using experimental studies of throwers that human throwing capabilities largely result from several derived anatomical features that enable elastic energy storage and release at the shoulder. These features first appear together approximately two million years ago in the species Homo erectus. Given archaeological evidence that suggests hunting activity intensified around this time9, we conclude that selection for throwing in order to hunt likely played an important role in the evolution of the human genus. PMID:23803849

Improving sub-grid scale accuracy of boundary features in regional finite-difference models

USGS Publications Warehouse

Panday, Sorab; Langevin, Christian D.

2012-01-01

As an alternative to grid refinement, the concept of a ghost node, which was developed for nested grid applications, has been extended towards improving sub-grid scale accuracy of flow to conduits, wells, rivers or other boundary features that interact with a finite-difference groundwater flow model. The formulation is presented for correcting the regular finite-difference groundwater flow equations for confined and unconfined cases, with or without Newton Raphson linearization of the nonlinearities, to include the Ghost Node Correction (GNC) for location displacement. The correction may be applied on the right-hand side vector for a symmetric finite-difference Picard implementation, or on the left-hand side matrix for an implicit but asymmetric implementation. The finite-difference matrix connectivity structure may be maintained for an implicit implementation by only selecting contributing nodes that are a part of the finite-difference connectivity. Proof of concept example problems are provided to demonstrate the improved accuracy that may be achieved through sub-grid scale corrections using the GNC schemes.

Pathview Web: user friendly pathway visualization and data integration

PubMed Central

Pant, Gaurav; Bhavnasi, Yeshvant K.; Blanchard, Steven G.; Brouwer, Cory

2017-01-01

Abstract Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. PMID:28482075

Large-Scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses

PubMed Central

Xu, Jiansong; Potenza, Marc N.; Calhoun, Vince D.; Zhang, Rubin; Yip, Sarah W.; Wall, John T.; Pearlson, Godfrey D.; Worhunsky, Patrick D.; Garrison, Kathleen A.; Moran, Joseph M.

2016-01-01

Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-linear-model-based analyses (GLM). Their findings are often inconsistent across different studies, perhaps because of several fundamental brain properties including functional heterogeneity, balanced excitation and inhibition (E/I), and sparseness of neuronal activities. These properties stipulate heterogeneous neuronal activities in the same voxels and likely limit the sensitivity and specificity of GLM. This paper selectively reviews findings of histological and electrophysiological studies and fMRI spatial independent component analysis (sICA) and reports new findings by applying sICA to two existing datasets. The extant and new findings consistently demonstrate several novel features of brain functional organization not revealed by GLM. They include overlap of large-scale functional networks (FNs) and their concurrent opposite modulations, and no significant modulations in activity of most FNs across the whole brain during any task conditions. These novel features of brain functional organization are highly consistent with the brain’s properties of functional heterogeneity, balanced E/I, and sparseness of neuronal activity, and may help reconcile inconsistent GLM findings. PMID:27592153

Collective stochastic coherence in recurrent neuronal networks

NASA Astrophysics Data System (ADS)

Sancristóbal, Belén; Rebollo, Beatriz; Boada, Pol; Sanchez-Vives, Maria V.; Garcia-Ojalvo, Jordi

2016-09-01

Recurrent networks of dynamic elements frequently exhibit emergent collective oscillations, which can show substantial regularity even when the individual elements are considerably noisy. How noise-induced dynamics at the local level coexists with regular oscillations at the global level is still unclear. Here we show that a combination of stochastic recurrence-based initiation with deterministic refractoriness in an excitable network can reconcile these two features, leading to maximum collective coherence for an intermediate noise level. We report this behaviour in the slow oscillation regime exhibited by a cerebral cortex network under dynamical conditions resembling slow-wave sleep and anaesthesia. Computational analysis of a biologically realistic network model reveals that an intermediate level of background noise leads to quasi-regular dynamics. We verify this prediction experimentally in cortical slices subject to varying amounts of extracellular potassium, which modulates neuronal excitability and thus synaptic noise. The model also predicts that this effectively regular state should exhibit noise-induced memory of the spatial propagation profile of the collective oscillations, which is also verified experimentally. Taken together, these results allow us to construe the high regularity observed experimentally in the brain as an instance of collective stochastic coherence.

Extensive regularization of the coupled cluster methods based on the generating functional formalism: application to gas-phase benchmarks and to the S(N)2 reaction of CHCl3 and OH- in water

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

Kowalski, Karol; Valiev, Marat

2009-12-21

The recently introduced energy expansion based on the use of generating functional (GF) [K. Kowalski, P.D. Fan, J. Chem. Phys. 130, 084112 (2009)] provides a way of constructing size-consistent non-iterative coupled-cluster (CC) corrections in terms of moments of the CC equations. To take advantage of this expansion in a strongly interacting regime, the regularization of the cluster amplitudes is required in order to counteract the effect of excessive growth of the norm of the CC wavefunction. Although proven to be effcient, the previously discussed form of the regularization does not lead to rigorously size-consistent corrections. In this paper we addressmore » the issue of size-consistent regularization of the GF expansion by redefning the equations for the cluster amplitudes. The performance and basic features of proposed methodology is illustrated on several gas-phase benchmark systems. Moreover, the regularized GF approaches are combined with QM/MM module and applied to describe the SN2 reaction of CHCl3 and OH- in aqueous solution.« less

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

PubMed

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Use of a Machine-learning Method for Predicting Highly Cited Articles Within General Radiology Journals.

PubMed

Rosenkrantz, Andrew B; Doshi, Ankur M; Ginocchio, Luke A; Aphinyanaphongs, Yindalon

2016-12-01

This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article features. We downloaded from PubMed the title, abstract, and medical subject heading terms for 10,065 articles published in 25 general radiology journals in 2012 and 2013. Three machine-learning models were applied to predict the top 10% of included articles in terms of the number of citations to the article in 2014 (reflecting the 2-year time window in conventional impact factor calculations). The model having the highest area under the curve was selected to derive a list of article features (words) predicting high citation volume, which was iteratively reduced to identify the smallest possible core feature list maintaining predictive power. Overall themes were qualitatively assigned to the core features. The regularized logistic regression (Bayesian binary regression) model had highest performance, achieving an area under the curve of 0.814 in predicting articles in the top 10% of citation volume. We reduced the initial 14,083 features to 210 features that maintain predictivity. These features corresponded with topics relating to various imaging techniques (eg, diffusion-weighted magnetic resonance imaging, hyperpolarized magnetic resonance imaging, dual-energy computed tomography, computed tomography reconstruction algorithms, tomosynthesis, elastography, and computer-aided diagnosis), particular pathologies (prostate cancer; thyroid nodules; hepatic adenoma, hepatocellular carcinoma, non-alcoholic fatty liver disease), and other topics (radiation dose, electroporation, education, general oncology, gadolinium, statistics). Machine learning can be successfully applied to create specific feature-based models for predicting articles likely to achieve high influence within the radiological literature. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Semantic classification of business images

NASA Astrophysics Data System (ADS)

Erol, Berna; Hull, Jonathan J.

2006-01-01

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.

E&V Guidebook, Version 1.1

DTIC Science & Technology

1989-08-15

checklist 14.1] Chapter 3, Language-related issues, extracts from the Ada language reference manua! [,_D 1982] those features exp!icitly a!owcd to vay...welcome. Please send comments electronically (preferred) to szymansk~aja;po.sei.cmu.edu, or by regular mail to Mr. Raymond Szymanski , AFWAL/AAAF, Wright...of Tool Features for the Ada Programming Support Environment (APSE) 4-3 4.3 E&V Report: DoD APSE Analysis 4-4 4.4 Classification Schema/E&V Taxonomy

Slope Streaks or RSL?

NASA Image and Video Library

2016-12-14

The image shows a region we see many slope streaks, typically dark features on slopes in the equatorial regions on Mars. They may extend for tens of meters in length and gradually fade away with time as new ones form. The most common hypothesis is that they are generated by dust avalanches that regularly occur on steep slopes exposing fresh dark materials from underneath the brighter dust. There are many types of slope streaks but one of the most recent and significant findings using HiRISE was the discovery of a new type called "recurring slope lineae," or RSL for short. Recent studies suggest that RSL may form through the flow of briny (extremely salty) liquid water that can be stable on the surface of Mars even under current climatic conditions for a limited time in summer when it is relatively warm. How can we distinguish between conventional slope streaks like the ones we see here and RSL? There are many criteria. For instance, RSL are usually smaller in size than regular slope streaks. However, one of the most important conditions is seasonal behavior, since RSL appear to be active only in summer while regular slope streaks can be active anytime of the year. This site is monitored regularly by HiRISE scientists because of the high density of slope streaks and their different sizes and orientations. If we look at a time-lapse sequence, we will see that a new slope streak has indeed formed in the period since April 2016 (and we can note how dark it is in comparison to the others indicating its freshness). However, this period corresponds mainly to the autumn season in this part of Mars, whereas we do not see any major changes in the summer season. This suggests that the feature that developed is a regular slope streak just like all the others in the area. http://photojournal.jpl.nasa.gov/catalog/PIA21272

Feature Selection for Ridge Regression with Provable Guarantees.

PubMed

Paul, Saurabh; Drineas, Petros

2016-04-01

We introduce single-set spectral sparsification as a deterministic sampling-based feature selection technique for regularized least-squares classification, which is the classification analog to ridge regression. The method is unsupervised and gives worst-case guarantees of the generalization power of the classification function after feature selection with respect to the classification function obtained using all features. We also introduce leverage-score sampling as an unsupervised randomized feature selection method for ridge regression. We provide risk bounds for both single-set spectral sparsification and leverage-score sampling on ridge regression in the fixed design setting and show that the risk in the sampled space is comparable to the risk in the full-feature space. We perform experiments on synthetic and real-world data sets; a subset of TechTC-300 data sets, to support our theory. Experimental results indicate that the proposed methods perform better than the existing feature selection methods.

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

Robinson, Judith; Johnson, Timothy C.; Slater, Lee D.

There is an increasing need to characterize discrete fractures away from boreholes to better define fracture distributions and monitor solute transport. We performed a 3D evaluation of static and time-lapse cross-borehole electrical resistivity tomography (ERT) data sets from a limestone quarry in which flow and transport are controlled by a bedding-plane feature. Ten boreholes were discretized using an unstructured tetrahedral mesh, and 2D panel measurements were inverted for a 3D distribution of conductivity. We evaluated the benefits of 3D versus 2.5D inversion of ERT data in fractured rock while including the use of borehole regularization disconnects (BRDs) and borehole conductivitymore » constraints. High-conductivity halos (inversion artifacts) surrounding boreholes were removed in static images when BRDs and borehole conductivity constraints were implemented. Furthermore, applying these constraints focused transient changes in conductivity resulting from solute transport on the bedding plane, providing a more physically reasonable model for conductivity changes associated with solute transport at this fractured rock site. Assuming bedding-plane continuity between fractures identified in borehole televiewer data, we discretized a planar region between six boreholes and applied a fracture regularization disconnect (FRD). Although the FRD appropriately focused conductivity changes on the bedding plane, the conductivity distribution within the discretized fracture was nonunique and dependent on the starting homogeneous model conductivity. Synthetic studies performed to better explain field observations showed that inaccurate electrode locations in boreholes resulted in low-conductivity halos surrounding borehole locations. These synthetic studies also showed that the recovery of the true conductivity within an FRD depended on the conductivity contrast between the host rock and fractures. Our findings revealed that the potential exists to improve imaging of fractured rock through 3D inversion and accurate modeling of boreholes. However, deregularization of localized features can result in significant electrical conductivity artifacts, especially when representing features with a high degree of spatial uncertainty.« less

Sensitivity to structure in action sequences: An infant event-related potential study.

PubMed

Monroy, Claire D; Gerson, Sarah A; Domínguez-Martínez, Estefanía; Kaduk, Katharina; Hunnius, Sabine; Reid, Vincent

2017-05-06

Infants are sensitive to structure and patterns within continuous streams of sensory input. This sensitivity relies on statistical learning, the ability to detect predictable regularities in spatial and temporal sequences. Recent evidence has shown that infants can detect statistical regularities in action sequences they observe, but little is known about the neural process that give rise to this ability. In the current experiment, we combined electroencephalography (EEG) with eye-tracking to identify electrophysiological markers that indicate whether 8-11-month-old infants detect violations to learned regularities in action sequences, and to relate these markers to behavioral measures of anticipation during learning. In a learning phase, infants observed an actor performing a sequence featuring two deterministic pairs embedded within an otherwise random sequence. Thus, the first action of each pair was predictive of what would occur next. One of the pairs caused an action-effect, whereas the second did not. In a subsequent test phase, infants observed another sequence that included deviant pairs, violating the previously observed action pairs. Event-related potential (ERP) responses were analyzed and compared between the deviant and the original action pairs. Findings reveal that infants demonstrated a greater Negative central (Nc) ERP response to the deviant actions for the pair that caused the action-effect, which was consistent with their visual anticipations during the learning phase. Findings are discussed in terms of the neural and behavioral processes underlying perception and learning of structured action sequences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Breast Cancer Basics and You: Detection and Diagnosis | NIH MedlinePlus the Magazine

MedlinePlus

... of this page please turn Javascript on. Feature: Breast Cancer Breast Cancer Basics and You: Detection and Diagnosis Past Issues / ... regular clinical breast exams and mammograms to find breast cancer early, when treatment is more likely to work ...

Child Support Report, 2000.

ERIC Educational Resources Information Center

Sharman, Phil, Ed.

2000-01-01

This document comprises the 12 issues for 2000 of the "Child Support Report," which explores problems related to child support enforcement, reports on federal and state government child support enforcement initiatives, and summarizes research related to child support. Featured regularly are editorials and information on events of…

Q & A with Ed Tech Leaders: Interview with Robert Talbert

ERIC Educational Resources Information Center

Shaughnessy, Michael F.; Yan, Juchao

2015-01-01

In this regular feature of "Educational Technology," Michael F. Shaughnessy and Juchao Yan present their interview with Robert Talbert, Associate Professor, Mathematics Department, Grand Valley State University, Allendale, Michigan. Their interview centered around thirteen questions that professor Talbert provided enlightening responds…

Research on image retrieval using deep convolutional neural network combining L1 regularization and PRelu activation function

NASA Astrophysics Data System (ADS)

QingJie, Wei; WenBin, Wang

2017-06-01

In this paper, the image retrieval using deep convolutional neural network combined with regularization and PRelu activation function is studied, and improves image retrieval accuracy. Deep convolutional neural network can not only simulate the process of human brain to receive and transmit information, but also contains a convolution operation, which is very suitable for processing images. Using deep convolutional neural network is better than direct extraction of image visual features for image retrieval. However, the structure of deep convolutional neural network is complex, and it is easy to over-fitting and reduces the accuracy of image retrieval. In this paper, we combine L1 regularization and PRelu activation function to construct a deep convolutional neural network to prevent over-fitting of the network and improve the accuracy of image retrieval

Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study.

PubMed

Saeb, Sohrab; Zhang, Mi; Karr, Christopher J; Schueller, Stephen M; Corden, Marya E; Kording, Konrad P; Mohr, David C

2015-07-15

Depression is a common, burdensome, often recurring mental health disorder that frequently goes undetected and untreated. Mobile phones are ubiquitous and have an increasingly large complement of sensors that can potentially be useful in monitoring behavioral patterns that might be indicative of depressive symptoms. The objective of this study was to explore the detection of daily-life behavioral markers using mobile phone global positioning systems (GPS) and usage sensors, and their use in identifying depressive symptom severity. A total of 40 adult participants were recruited from the general community to carry a mobile phone with a sensor data acquisition app (Purple Robot) for 2 weeks. Of these participants, 28 had sufficient sensor data received to conduct analysis. At the beginning of the 2-week period, participants completed a self-reported depression survey (PHQ-9). Behavioral features were developed and extracted from GPS location and phone usage data. A number of features from GPS data were related to depressive symptom severity, including circadian movement (regularity in 24-hour rhythm; r=-.63, P=.005), normalized entropy (mobility between favorite locations; r=-.58, P=.012), and location variance (GPS mobility independent of location; r=-.58, P=.012). Phone usage features, usage duration, and usage frequency were also correlated (r=.54, P=.011, and r=.52, P=.015, respectively). Using the normalized entropy feature and a classifier that distinguished participants with depressive symptoms (PHQ-9 score ≥5) from those without (PHQ-9 score <5), we achieved an accuracy of 86.5%. Furthermore, a regression model that used the same feature to estimate the participants' PHQ-9 scores obtained an average error of 23.5%. Features extracted from mobile phone sensor data, including GPS and phone usage, provided behavioral markers that were strongly related to depressive symptom severity. While these findings must be replicated in a larger study among participants with confirmed clinical symptoms, they suggest that phone sensors offer numerous clinical opportunities, including continuous monitoring of at-risk populations with little patient burden and interventions that can provide just-in-time outreach.

Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study

PubMed Central

Saeb, Sohrab; Zhang, Mi; Karr, Christopher J; Schueller, Stephen M; Corden, Marya E; Kording, Konrad P

2015-01-01

Background Depression is a common, burdensome, often recurring mental health disorder that frequently goes undetected and untreated. Mobile phones are ubiquitous and have an increasingly large complement of sensors that can potentially be useful in monitoring behavioral patterns that might be indicative of depressive symptoms. Objective The objective of this study was to explore the detection of daily-life behavioral markers using mobile phone global positioning systems (GPS) and usage sensors, and their use in identifying depressive symptom severity. Methods A total of 40 adult participants were recruited from the general community to carry a mobile phone with a sensor data acquisition app (Purple Robot) for 2 weeks. Of these participants, 28 had sufficient sensor data received to conduct analysis. At the beginning of the 2-week period, participants completed a self-reported depression survey (PHQ-9). Behavioral features were developed and extracted from GPS location and phone usage data. Results A number of features from GPS data were related to depressive symptom severity, including circadian movement (regularity in 24-hour rhythm; r=-.63, P=.005), normalized entropy (mobility between favorite locations; r=-.58, P=.012), and location variance (GPS mobility independent of location; r=-.58, P=.012). Phone usage features, usage duration, and usage frequency were also correlated (r=.54, P=.011, and r=.52, P=.015, respectively). Using the normalized entropy feature and a classifier that distinguished participants with depressive symptoms (PHQ-9 score ≥5) from those without (PHQ-9 score <5), we achieved an accuracy of 86.5%. Furthermore, a regression model that used the same feature to estimate the participants’ PHQ-9 scores obtained an average error of 23.5%. Conclusions Features extracted from mobile phone sensor data, including GPS and phone usage, provided behavioral markers that were strongly related to depressive symptom severity. While these findings must be replicated in a larger study among participants with confirmed clinical symptoms, they suggest that phone sensors offer numerous clinical opportunities, including continuous monitoring of at-risk populations with little patient burden and interventions that can provide just-in-time outreach. PMID:26180009

Polycystic ovary syndrome: a complex condition with psychological, reproductive and metabolic manifestations that impacts on health across the lifespan.

PubMed

Teede, H; Deeks, A; Moran, L

2010-06-30

Polycystic ovary syndrome (PCOS) is of clinical and public health importance as it is very common, affecting up to one in five women of reproductive age. It has significant and diverse clinical implications including reproductive (infertility, hyperandrogenism, hirsutism), metabolic (insulin resistance, impaired glucose tolerance, type 2 diabetes mellitus, adverse cardiovascular risk profiles) and psychological features (increased anxiety, depression and worsened quality of life). Polycystic ovary syndrome is a heterogeneous condition and, as such, clinical and research agendas are broad and involve many disciplines. The phenotype varies widely depending on life stage, genotype, ethnicity and environmental factors including lifestyle and bodyweight. Importantly, PCOS has unique interactions with the ever increasing obesity prevalence worldwide as obesity-induced insulin resistance significantly exacerbates all the features of PCOS. Furthermore, it has clinical implications across the lifespan and is relevant to related family members with an increased risk for metabolic conditions reported in first-degree relatives. Therapy should focus on both the short and long-term reproductive, metabolic and psychological features. Given the aetiological role of insulin resistance and the impact of obesity on both hyperinsulinaemia and hyperandrogenism, multidisciplinary lifestyle improvement aimed at normalising insulin resistance, improving androgen status and aiding weight management is recognised as a crucial initial treatment strategy. Modest weight loss of 5% to 10% of initial body weight has been demonstrated to improve many of the features of PCOS. Management should focus on support, education, addressing psychological factors and strongly emphasising healthy lifestyle with targeted medical therapy as required. Monitoring and management of long-term metabolic complications is also an important part of routine clinical care. Comprehensive evidence-based guidelines are needed to aid early diagnosis, appropriate investigation, regular screening and treatment of this common condition. Whilst reproductive features of PCOS are well recognised and are covered here, this review focuses primarily on the less appreciated cardiometabolic and psychological features of PCOS.

Polycystic ovary syndrome: a complex condition with psychological, reproductive and metabolic manifestations that impacts on health across the lifespan

PubMed Central

2010-01-01

Polycystic ovary syndrome (PCOS) is of clinical and public health importance as it is very common, affecting up to one in five women of reproductive age. It has significant and diverse clinical implications including reproductive (infertility, hyperandrogenism, hirsutism), metabolic (insulin resistance, impaired glucose tolerance, type 2 diabetes mellitus, adverse cardiovascular risk profiles) and psychological features (increased anxiety, depression and worsened quality of life). Polycystic ovary syndrome is a heterogeneous condition and, as such, clinical and research agendas are broad and involve many disciplines. The phenotype varies widely depending on life stage, genotype, ethnicity and environmental factors including lifestyle and bodyweight. Importantly, PCOS has unique interactions with the ever increasing obesity prevalence worldwide as obesity-induced insulin resistance significantly exacerbates all the features of PCOS. Furthermore, it has clinical implications across the lifespan and is relevant to related family members with an increased risk for metabolic conditions reported in first-degree relatives. Therapy should focus on both the short and long-term reproductive, metabolic and psychological features. Given the aetiological role of insulin resistance and the impact of obesity on both hyperinsulinaemia and hyperandrogenism, multidisciplinary lifestyle improvement aimed at normalising insulin resistance, improving androgen status and aiding weight management is recognised as a crucial initial treatment strategy. Modest weight loss of 5% to 10% of initial body weight has been demonstrated to improve many of the features of PCOS. Management should focus on support, education, addressing psychological factors and strongly emphasising healthy lifestyle with targeted medical therapy as required. Monitoring and management of long-term metabolic complications is also an important part of routine clinical care. Comprehensive evidence-based guidelines are needed to aid early diagnosis, appropriate investigation, regular screening and treatment of this common condition. Whilst reproductive features of PCOS are well recognised and are covered here, this review focuses primarily on the less appreciated cardiometabolic and psychological features of PCOS. PMID:20591140

LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction

PubMed Central

Huang, Li

2017-01-01

Predicting novel microRNA (miRNA)-disease associations is clinically significant due to miRNAs’ potential roles of diagnostic biomarkers and therapeutic targets for various human diseases. Previous studies have demonstrated the viability of utilizing different types of biological data to computationally infer new disease-related miRNAs. Yet researchers face the challenge of how to effectively integrate diverse datasets and make reliable predictions. In this study, we presented a computational model named Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction (LRSSLMDA), which projected miRNAs/diseases’ statistical feature profile and graph theoretical feature profile to a common subspace. It used Laplacian regularization to preserve the local structures of the training data and a L1-norm constraint to select important miRNA/disease features for prediction. The strength of dimensionality reduction enabled the model to be easily extended to much higher dimensional datasets than those exploited in this study. Experimental results showed that LRSSLMDA outperformed ten previous models: the AUC of 0.9178 in global leave-one-out cross validation (LOOCV) and the AUC of 0.8418 in local LOOCV indicated the model’s superior prediction accuracy; and the average AUC of 0.9181+/-0.0004 in 5-fold cross validation justified its accuracy and stability. In addition, three types of case studies further demonstrated its predictive power. Potential miRNAs related to Colon Neoplasms, Lymphoma, Kidney Neoplasms, Esophageal Neoplasms and Breast Neoplasms were predicted by LRSSLMDA. Respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predictions were validated by experimental evidences. Therefore, we conclude that LRSSLMDA would be a valuable computational tool for miRNA-disease association prediction. PMID:29253885

Predicting age groups of Twitter users based on language and metadata features

PubMed Central

Morgan-Lopez, Antonio A.; Chew, Robert F.; Ruddle, Paul

2017-01-01

Health organizations are increasingly using social media, such as Twitter, to disseminate health messages to target audiences. Determining the extent to which the target audience (e.g., age groups) was reached is critical to evaluating the impact of social media education campaigns. The main objective of this study was to examine the separate and joint predictive validity of linguistic and metadata features in predicting the age of Twitter users. We created a labeled dataset of Twitter users across different age groups (youth, young adults, adults) by collecting publicly available birthday announcement tweets using the Twitter Search application programming interface. We manually reviewed results and, for each age-labeled handle, collected the 200 most recent publicly available tweets and user handles’ metadata. The labeled data were split into training and test datasets. We created separate models to examine the predictive validity of language features only, metadata features only, language and metadata features, and words/phrases from another age-validated dataset. We estimated accuracy, precision, recall, and F1 metrics for each model. An L1-regularized logistic regression model was conducted for each age group, and predicted probabilities between the training and test sets were compared for each age group. Cohen’s d effect sizes were calculated to examine the relative importance of significant features. Models containing both Tweet language features and metadata features performed the best (74% precision, 74% recall, 74% F1) while the model containing only Twitter metadata features were least accurate (58% precision, 60% recall, and 57% F1 score). Top predictive features included use of terms such as “school” for youth and “college” for young adults. Overall, it was more challenging to predict older adults accurately. These results suggest that examining linguistic and Twitter metadata features to predict youth and young adult Twitter users may be helpful for informing public health surveillance and evaluation research. PMID:28850620

Predicting age groups of Twitter users based on language and metadata features.

PubMed

Morgan-Lopez, Antonio A; Kim, Annice E; Chew, Robert F; Ruddle, Paul

2017-01-01

Health organizations are increasingly using social media, such as Twitter, to disseminate health messages to target audiences. Determining the extent to which the target audience (e.g., age groups) was reached is critical to evaluating the impact of social media education campaigns. The main objective of this study was to examine the separate and joint predictive validity of linguistic and metadata features in predicting the age of Twitter users. We created a labeled dataset of Twitter users across different age groups (youth, young adults, adults) by collecting publicly available birthday announcement tweets using the Twitter Search application programming interface. We manually reviewed results and, for each age-labeled handle, collected the 200 most recent publicly available tweets and user handles' metadata. The labeled data were split into training and test datasets. We created separate models to examine the predictive validity of language features only, metadata features only, language and metadata features, and words/phrases from another age-validated dataset. We estimated accuracy, precision, recall, and F1 metrics for each model. An L1-regularized logistic regression model was conducted for each age group, and predicted probabilities between the training and test sets were compared for each age group. Cohen's d effect sizes were calculated to examine the relative importance of significant features. Models containing both Tweet language features and metadata features performed the best (74% precision, 74% recall, 74% F1) while the model containing only Twitter metadata features were least accurate (58% precision, 60% recall, and 57% F1 score). Top predictive features included use of terms such as "school" for youth and "college" for young adults. Overall, it was more challenging to predict older adults accurately. These results suggest that examining linguistic and Twitter metadata features to predict youth and young adult Twitter users may be helpful for informing public health surveillance and evaluation research.

An ecological mechanism to create regular patterns of surface dissolution in a low-relief carbonate landscape

NASA Astrophysics Data System (ADS)

Cohen, M. J.; Martin, J. B.; Mclaughlin, D. L.; Osborne, T.; Murray, A.; Watts, A. C.; Watts, D.; Heffernan, J. B.

2012-12-01

Development of karst landscapes is controlled by focused delivery of water undersaturated with respect to the soluble rock minerals. As that water comes to equilibrium with the rock, secondary porosity is incrementally reinforced creating a positive feedback that acts to augment the drainage network and subsequent water delivery. In most self-organizing systems, spatial positive feedbacks create features (in landscapes: patches; in karst aquifers: conduits) whose size-frequency relationship follows a power function, indicating a higher probability of large features than would occur with a random or Gaussian genesis process. Power functions describe several aspects of secondary porosity in the Upper Floridan Aquifer in north Florida. In contrast, a different pattern arises in the karst landscape in southwest Florida (Big Cypress National Preserve; BICY), where low-relief and a shallow aquiclude govern regional hydrology. There, the landscape pattern is highly regular (Fig. 1), with circular cypress-dominated wetlands occupying depressions that are hydrologically isolated and distributed evenly in a matrix of pine uplands. Regular landscape patterning results from spatially coupled feedbacks, one positive operating locally that expands patches coupled to another negative that operates at distance, eventually inhibiting patch expansion. The positive feedback in BICY is thought to derive from the presence of surface depressions, which sustain prolonged inundation in this low-relief setting, and facilitate wetland development that greatly augments dissolution potential of infiltrating water in response to ecosystem metabolic processes. In short, wetlands "drill" into the carbonate leading to both vertical and lateral basin expansion. Wetland expansion occurs at the expense of surrounding upland area, which is the local catchment that subsidizes water availability. A distal inhibitory feedback on basin expansion thus occurs as the water necessary to sustain prolonged inundation becomes limiting. The implied strong reciprocal coupling between surface production of organic matter and patterns of induced subsurface carbonate dissolution are a novel example of co-evolving biogeomorphic processes in the earth system. Fig. 1 - Regular patterned landscape in Big Cypress National Preserve showing cypress dominated wetlands (round features) embedded in a mosaic of pine and grass uplands. Exposed carbonate rings are evident at the margins of many of the wetland basins.

Apply lightweight deep learning on internet of things for low-cost and easy-to-access skin cancer detection

NASA Astrophysics Data System (ADS)

Sahu, Pranjal; Yu, Dantong; Qin, Hong

2018-03-01

Melanoma is the most dangerous form of skin cancer that often resembles moles. Dermatologists often recommend regular skin examination to identify and eliminate Melanoma in its early stages. To facilitate this process, we propose a hand-held computer (smart-phone, Raspberry Pi) based assistant that classifies with the dermatologist-level accuracy skin lesion images into malignant and benign and works in a standalone mobile device without requiring network connectivity. In this paper, we propose and implement a hybrid approach based on advanced deep learning model and domain-specific knowledge and features that dermatologists use for the inspection purpose to improve the accuracy of classification between benign and malignant skin lesions. Here, domain-specific features include the texture of the lesion boundary, the symmetry of the mole, and the boundary characteristics of the region of interest. We also obtain standard deep features from a pre-trained network optimized for mobile devices called Google's MobileNet. The experiments conducted on ISIC 2017 skin cancer classification challenge demonstrate the effectiveness and complementary nature of these hybrid features over the standard deep features. We performed experiments with the training, testing and validation data splits provided in the competition. Our method achieved area of 0.805 under the receiver operating characteristic curve. Our ultimate goal is to extend the trained model in a commercial hand-held mobile and sensor device such as Raspberry Pi and democratize the access to preventive health care.

A Comparative Analysis of the Universal Elements of Music and the Fetal Environment

PubMed Central

Teie, David

2016-01-01

Although the idea that pulse in music may be related to human pulse is ancient and has recently been promoted by researchers (Parncutt, 2006; Snowdon and Teie, 2010), there has been no ordered delineation of the characteristics of music that are based on the sounds of the womb. I describe features of music that are based on sounds that are present in the womb: tempo of pulse (pulse is understood as the regular, underlying beat that defines the meter), amplitude contour of pulse, meter, musical notes, melodic frequency range, continuity, syllabic contour, melodic rhythm, melodic accents, phrase length, and phrase contour. There are a number of features of prenatal development that allow for the formation of long-term memories of the sounds of the womb in the areas of the brain that are responsible for emotions. Taken together, these features and the similarities between the sounds of the womb and the elemental building blocks of music allow for a postulation that the fetal acoustic environment may provide the bases for the fundamental musical elements that are found in the music of all cultures. This hypothesis is supported by a one-to-one matching of the universal features of music with the sounds of the womb: (1) all of the regularly heard sounds that are present in the fetal environment are represented in the music of every culture, and (2) all of the features of music that are present in the music of all cultures can be traced to the fetal environment. PMID:27555828

Child Support Report, 2002.

ERIC Educational Resources Information Center

Sharman, Phil, Ed.

2002-01-01

This document comprises the 12 issues for 2002 of the Child Support Report, which explores problems related to child support enforcement, reports on federal and state government child support enforcement initiatives, and summarizes research related to child support. Featured regularly are editorials and information on events of interest and…

Mare Orientale: Widely Accepted Large Impact or a Regular Tectonic Depression?

NASA Astrophysics Data System (ADS)

Kochemasov, G. G.

2018-04-01

Mare Orientale is one of the critical features on Moon surface explaining its tectonics. The impact origin of it is widely accepted, but an attentive examination shows that this large Mare is a part of endogenous tectonic structure, not a random impact.

In-plane crashworthiness of bio-inspired hierarchical honeycombs

DOE PAGES

Yin, Hanfeng; Huang, Xiaofei; Scarpa, Fabrizio; ...

2018-03-13

Biological tissues like bone, wood, and sponge possess hierarchical cellular topologies, which are lightweight and feature an excellent energy absorption capability. Here we present a system of bio-inspired hierarchical honeycomb structures based on hexagonal, Kagome, and triangular tessellations. The hierarchical designs and a reference regular honeycomb configuration are subjected to simulated in-plane impact using the nonlinear finite element code LS-DYNA. The numerical simulation results show that the triangular hierarchical honeycomb provides the best performance compared to the other two hierarchical honeycombs, and features more than twice the energy absorbed by the regular honeycomb under similar loading conditions. We also proposemore » a parametric study correlating the microstructure parameters (hierarchical length ratio r and the number of sub cells N) to the energy absorption capacity of these hierarchical honeycombs. The triangular hierarchical honeycomb with N = 2 and r = 1/8 shows the highest energy absorption capacity among all the investigated cases, and this configuration could be employed as a benchmark for the design of future safety protective systems.« less

Schwinger-variational-principle theory of collisions in the presence of multiple potentials

NASA Astrophysics Data System (ADS)

Robicheaux, F.; Giannakeas, P.; Greene, Chris H.

2015-08-01

A theoretical method for treating collisions in the presence of multiple potentials is developed by employing the Schwinger variational principle. The current treatment agrees with the local (regularized) frame transformation theory and extends its capabilities. Specifically, the Schwinger variational approach gives results without the divergences that need to be regularized in other methods. Furthermore, it provides a framework to identify the origin of these singularities and possibly improve the local frame transformation. We have used the method to obtain the scattering parameters for different confining potentials symmetric in x ,y . The method is also used to treat photodetachment processes in the presence of various confining potentials, thereby highlighting effects of the infinitely many closed channels. Two general features predicted are the vanishing of the total photoabsorption probability at every channel threshold and the occurrence of resonances below the channel thresholds for negative scattering lengths. In addition, the case of negative-ion photodetachment in the presence of uniform magnetic fields is also considered where unique features emerge at large scattering lengths.

In-plane crashworthiness of bio-inspired hierarchical honeycombs

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

Yin, Hanfeng; Huang, Xiaofei; Scarpa, Fabrizio

Biological tissues like bone, wood, and sponge possess hierarchical cellular topologies, which are lightweight and feature an excellent energy absorption capability. Here we present a system of bio-inspired hierarchical honeycomb structures based on hexagonal, Kagome, and triangular tessellations. The hierarchical designs and a reference regular honeycomb configuration are subjected to simulated in-plane impact using the nonlinear finite element code LS-DYNA. The numerical simulation results show that the triangular hierarchical honeycomb provides the best performance compared to the other two hierarchical honeycombs, and features more than twice the energy absorbed by the regular honeycomb under similar loading conditions. We also proposemore » a parametric study correlating the microstructure parameters (hierarchical length ratio r and the number of sub cells N) to the energy absorption capacity of these hierarchical honeycombs. The triangular hierarchical honeycomb with N = 2 and r = 1/8 shows the highest energy absorption capacity among all the investigated cases, and this configuration could be employed as a benchmark for the design of future safety protective systems.« less

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: The Fractal Dimensions of Complex Networks

NASA Astrophysics Data System (ADS)

Guo, Long; Cai, XU

2009-08-01

It is shown that many real complex networks share distinctive features, such as the small-world effect and the heterogeneous property of connectivity of vertices, which are different from random networks and regular lattices. Although these features capture the important characteristics of complex networks, their applicability depends on the style of networks. To unravel the universal characteristics many complex networks have in common, we study the fractal dimensions of complex networks using the method introduced by Shanker. We find that the average 'density' (ρ(r)) of complex networks follows a better power-law function as a function of distance r with the exponent df, which is defined as the fractal dimension, in some real complex networks. Furthermore, we study the relation between df and the shortcuts Nadd in small-world networks and the size N in regular lattices. Our present work provides a new perspective to understand the dependence of the fractal dimension df on the complex network structure.

Classification of high-resolution multispectral satellite remote sensing images using extended morphological attribute profiles and independent component analysis

NASA Astrophysics Data System (ADS)

Wu, Yu; Zheng, Lijuan; Xie, Donghai; Zhong, Ruofei

2017-07-01

In this study, the extended morphological attribute profiles (EAPs) and independent component analysis (ICA) were combined for feature extraction of high-resolution multispectral satellite remote sensing images and the regularized least squares (RLS) approach with the radial basis function (RBF) kernel was further applied for the classification. Based on the major two independent components, the geometrical features were extracted using the EAPs method. In this study, three morphological attributes were calculated and extracted for each independent component, including area, standard deviation, and moment of inertia. The extracted geometrical features classified results using RLS approach and the commonly used LIB-SVM library of support vector machines method. The Worldview-3 and Chinese GF-2 multispectral images were tested, and the results showed that the features extracted by EAPs and ICA can effectively improve the accuracy of the high-resolution multispectral image classification, 2% larger than EAPs and principal component analysis (PCA) method, and 6% larger than APs and original high-resolution multispectral data. Moreover, it is also suggested that both the GURLS and LIB-SVM libraries are well suited for the multispectral remote sensing image classification. The GURLS library is easy to be used with automatic parameter selection but its computation time may be larger than the LIB-SVM library. This study would be helpful for the classification application of high-resolution multispectral satellite remote sensing images.

Deep convolutional neural networks for classifying GPR B-scans

NASA Astrophysics Data System (ADS)

Besaw, Lance E.; Stimac, Philip J.

2015-05-01

Symmetric and asymmetric buried explosive hazards (BEHs) present real, persistent, deadly threats on the modern battlefield. Current approaches to mitigate these threats rely on highly trained operatives to reliably detect BEHs with reasonable false alarm rates using handheld Ground Penetrating Radar (GPR) and metal detectors. As computers become smaller, faster and more efficient, there exists greater potential for automated threat detection based on state-of-the-art machine learning approaches, reducing the burden on the field operatives. Recent advancements in machine learning, specifically deep learning artificial neural networks, have led to significantly improved performance in pattern recognition tasks, such as object classification in digital images. Deep convolutional neural networks (CNNs) are used in this work to extract meaningful signatures from 2-dimensional (2-D) GPR B-scans and classify threats. The CNNs skip the traditional "feature engineering" step often associated with machine learning, and instead learn the feature representations directly from the 2-D data. A multi-antennae, handheld GPR with centimeter-accurate positioning data was used to collect shallow subsurface data over prepared lanes containing a wide range of BEHs. Several heuristics were used to prevent over-training, including cross validation, network weight regularization, and "dropout." Our results show that CNNs can extract meaningful features and accurately classify complex signatures contained in GPR B-scans, complementing existing GPR feature extraction and classification techniques.

A new feature detection mechanism and its application in secured ECG transmission with noise masking.

PubMed

Sufi, Fahim; Khalil, Ibrahim

2009-04-01

With cardiovascular disease as the number one killer of modern era, Electrocardiogram (ECG) is collected, stored and transmitted in greater frequency than ever before. However, in reality, ECG is rarely transmitted and stored in a secured manner. Recent research shows that eavesdropper can reveal the identity and cardiovascular condition from an intercepted ECG. Therefore, ECG data must be anonymized before transmission over the network and also stored as such in medical repositories. To achieve this, first of all, this paper presents a new ECG feature detection mechanism, which was compared against existing cross correlation (CC) based template matching algorithms. Two types of CC methods were used for comparison. Compared to the CC based approaches, which had 40% and 53% misclassification rates, the proposed detection algorithm did not perform any single misclassification. Secondly, a new ECG obfuscation method was designed and implemented on 15 subjects using added noises corresponding to each of the ECG features. This obfuscated ECG can be freely distributed over the internet without the necessity of encryption, since the original features needed to identify personal information of the patient remain concealed. Only authorized personnel possessing a secret key will be able to reconstruct the original ECG from the obfuscated ECG. Distribution of the would appear as regular ECG without encryption. Therefore, traditional decryption techniques including powerful brute force attack are useless against this obfuscation.

Independent processing of changes in auditory single features and feature conjunctions in humans as indexed by the mismatch negativity.

PubMed

Takegata, R; Paavilainen, P; Näätänen, R; Winkler, I

1999-05-07

The mismatch negativity (MMN), an event-related potential component of the EEG, is elicited by violations of auditory regularities In the present study, the stimulus blocks contained two types of standard tones, differing from each other in frequency and intensity. MMNs were recorded to three different types of deviant stimuli: (a) feature deviants, differing from standards in their perceived locus of origin; (b) conjunction deviants, having the frequency of one of the standards and the intensity of the other; (c) double deviants, differing from standards in both (a) and (b). The MMN to double deviants was similar to the sum of the MMNs to feature and conjunction deviants. This result indicates that changes in simple stimulus features and conjunction of features are processed independently by the automatic sound change detection system indexed by MMN.

Crowding with conjunctions of simple features.

PubMed

Põder, Endel; Wagemans, Johan

2007-11-20

Several recent studies have related crowding with the feature integration stage in visual processing. In order to understand the mechanisms involved in this stage, it is important to use stimuli that have several features to integrate, and these features should be clearly defined and measurable. In this study, Gabor patches were used as target and distractor stimuli. The stimuli differed in three dimensions: spatial frequency, orientation, and color. A group of 3, 5, or 7 objects was presented briefly at 4 deg eccentricity of the visual field. The observers' task was to identify the object located in the center of the group. A strong effect of the number of distractors was observed, consistent with various spatial pooling models. The analysis of incorrect responses revealed that these were a mix of feature errors and mislocalizations of the target object. Feature errors were not purely random, but biased by the features of distractors. We propose a simple feature integration model that predicts most of the observed regularities.

Fast incorporation of optical flow into active polygons.

PubMed

Unal, Gozde; Krim, Hamid; Yezzi, Anthony

2005-06-01

In this paper, we first reconsider, in a different light, the addition of a prediction step to active contour-based visual tracking using an optical flow and clarify the local computation of the latter along the boundaries of continuous active contours with appropriate regularizers. We subsequently detail our contribution of computing an optical flow-based prediction step directly from the parameters of an active polygon, and of exploiting it in object tracking. This is in contrast to an explicitly separate computation of the optical flow and its ad hoc application. It also provides an inherent regularization effect resulting from integrating measurements along polygon edges. As a result, we completely avoid the need of adding ad hoc regularizing terms to the optical flow computations, and the inevitably arbitrary associated weighting parameters. This direct integration of optical flow into the active polygon framework distinguishes this technique from most previous contour-based approaches, where regularization terms are theoretically, as well as practically, essential. The greater robustness and speed due to a reduced number of parameters of this technique are additional and appealing features.

Gene Expression Data to Mouse Atlas Registration Using a Nonlinear Elasticity Smoother and Landmark Points Constraints

PubMed Central

Lin, Tungyou; Guyader, Carole Le; Dinov, Ivo; Thompson, Paul; Toga, Arthur; Vese, Luminita

2013-01-01

This paper proposes a numerical algorithm for image registration using energy minimization and nonlinear elasticity regularization. Application to the registration of gene expression data to a neuroanatomical mouse atlas in two dimensions is shown. We apply a nonlinear elasticity regularization to allow larger and smoother deformations, and further enforce optimality constraints on the landmark points distance for better feature matching. To overcome the difficulty of minimizing the nonlinear elasticity functional due to the nonlinearity in the derivatives of the displacement vector field, we introduce a matrix variable to approximate the Jacobian matrix and solve for the simplified Euler-Lagrange equations. By comparison with image registration using linear regularization, experimental results show that the proposed nonlinear elasticity model also needs fewer numerical corrections such as regridding steps for binary image registration, it renders better ground truth, and produces larger mutual information; most importantly, the landmark points distance and L2 dissimilarity measure between the gene expression data and corresponding mouse atlas are smaller compared with the registration model with biharmonic regularization. PMID:24273381

Multifractal surrogate-data generation algorithm that preserves pointwise Hölder regularity structure, with initial applications to turbulence

NASA Astrophysics Data System (ADS)

Keylock, C. J.

2017-03-01

An algorithm is described that can generate random variants of a time series while preserving the probability distribution of original values and the pointwise Hölder regularity. Thus, it preserves the multifractal properties of the data. Our algorithm is similar in principle to well-known algorithms based on the preservation of the Fourier amplitude spectrum and original values of a time series. However, it is underpinned by a dual-tree complex wavelet transform rather than a Fourier transform. Our method, which we term the iterated amplitude adjusted wavelet transform can be used to generate bootstrapped versions of multifractal data, and because it preserves the pointwise Hölder regularity but not the local Hölder regularity, it can be used to test hypotheses concerning the presence of oscillating singularities in a time series, an important feature of turbulence and econophysics data. Because the locations of the data values are randomized with respect to the multifractal structure, hypotheses about their mutual coupling can be tested, which is important for the velocity-intermittency structure of turbulence and self-regulating processes.

An adaptive surface filter for airborne laser scanning point clouds by means of regularization and bending energy

NASA Astrophysics Data System (ADS)

Hu, Han; Ding, Yulin; Zhu, Qing; Wu, Bo; Lin, Hui; Du, Zhiqiang; Zhang, Yeting; Zhang, Yunsheng

2014-06-01

The filtering of point clouds is a ubiquitous task in the processing of airborne laser scanning (ALS) data; however, such filtering processes are difficult because of the complex configuration of the terrain features. The classical filtering algorithms rely on the cautious tuning of parameters to handle various landforms. To address the challenge posed by the bundling of different terrain features into a single dataset and to surmount the sensitivity of the parameters, in this study, we propose an adaptive surface filter (ASF) for the classification of ALS point clouds. Based on the principle that the threshold should vary in accordance to the terrain smoothness, the ASF embeds bending energy, which quantitatively depicts the local terrain structure to self-adapt the filter threshold automatically. The ASF employs a step factor to control the data pyramid scheme in which the processing window sizes are reduced progressively, and the ASF gradually interpolates thin plate spline surfaces toward the ground with regularization to handle noise. Using the progressive densification strategy, regularization and self-adaption, both performance improvement and resilience to parameter tuning are achieved. When tested against the benchmark datasets provided by ISPRS, the ASF performs the best in comparison with all other filtering methods, yielding an average total error of 2.85% when optimized and 3.67% when using the same parameter set.

CSTEM User Manual

NASA Technical Reports Server (NTRS)

Hartle, M.; McKnight, R. L.

2000-01-01

This manual is a combination of a user manual, theory manual, and programmer manual. The reader is assumed to have some previous exposure to the finite element method. This manual is written with the idea that the CSTEM (Coupled Structural Thermal Electromagnetic-Computer Code) user needs to have a basic understanding of what the code is actually doing in order to properly use the code. For that reason, the underlying theory and methods used in the code are described to a basic level of detail. The manual gives an overview of the CSTEM code: how the code came into existence, a basic description of what the code does, and the order in which it happens (a flowchart). Appendices provide a listing and very brief description of every file used by the CSTEM code, including the type of file it is, what routine regularly accesses the file, and what routine opens the file, as well as special features included in CSTEM.

Meeting the challenges of clinical information provision.

PubMed

Spring, Hannah

2017-12-01

This virtual issue of the Health Information and Libraries Journal (HILJ) has been compiled to mark the 5th International Clinical Librarian Conference 2011. In considering the challenges of clinical information provision, the content selected for the virtual issue offers an international flavour of clinical information provision and covers a variety of different facets of clinical librarianship. The issue broadly covers the areas of information needs and preferences, clinical librarian roles and services, and education and training, and reflects the way in which a normal issue of the HILJ would be presented. This includes a review article, a collection of original articles, and the three regular features which comprise International Perspectives and Initiatives, Learning and Teaching in Action, and Using Evidence in Practice. All papers included in this virtual issue are available free online. © 2011 The authors. Health Information and Libraries Journal © 2011 Health Libraries Group.

CATV and the Broadcasters.

ERIC Educational Resources Information Center

Flanagan, Bill

Competition between cable television systems (CATV) and regular broadcast stations concerns pay-TV and distant signal importation. The pay-TV that CATV provides competes with the networks by "siphoning" away sports and feature films, while the distant signals that CATV imports to a local market "fragment" the local audience and…

Technical Adequacy of the SWPBIS Tiered Fidelity Inventory

ERIC Educational Resources Information Center

McIntosh, Kent; Massar, Michelle M.; Algozzine, Robert F.; George, Heather Peshak; Horner, Robert H.; Lewis, Timothy J.; Swain-Bradway, Jessica

2017-01-01

Full and durable implementation of school-based interventions is supported by regular evaluation of fidelity of implementation. Multiple assessments have been developed to evaluate the extent to which schools are applying the core features of school-wide positive behavioral interventions and supports (SWPBIS). The "SWPBIS Tiered Fidelity…

The Portable Pediatrician.

ERIC Educational Resources Information Center

Markel, Howard; And Others

This ready reference health guide features 240 major topics that occur regularly in clinical work with children and adolescents. It sorts out the information vital to successful management of common health problems and concerns by presentation of tables, charts, lists, criteria for diagnosis, and other useful tips. References on which the entries…

Chemistry in a Large, Multidisciplinary Laboratory.

ERIC Educational Resources Information Center

Lingren, Wesley E.; Hughson, Robert C.

1982-01-01

Describes a science facility built at Seattle Pacific University for approximately 70 percent of the capital cost of a conventional science building. The building serves seven disciplines on a regular basis. The operation of the multidisciplinary laboratory, special features, laboratory security, and student experience/reactions are highlighted.…

Threat captures attention but does not affect learning of contextual regularities.

PubMed

Yamaguchi, Motonori; Harwood, Sarah L

2017-04-01

Some of the stimulus features that guide visual attention are abstract properties of objects such as potential threat to one's survival, whereas others are complex configurations such as visual contexts that are learned through past experiences. The present study investigated the two functions that guide visual attention, threat detection and learning of contextual regularities, in visual search. Search arrays contained images of threat and non-threat objects, and their locations were fixed on some trials but random on other trials. Although they were irrelevant to the visual search task, threat objects facilitated attention capture and impaired attention disengagement. Search time improved for fixed configurations more than for random configurations, reflecting learning of visual contexts. Nevertheless, threat detection had little influence on learning of the contextual regularities. The results suggest that factors guiding visual attention are different from factors that influence learning to guide visual attention.

Power-law regularities in human language

NASA Astrophysics Data System (ADS)

Mehri, Ali; Lashkari, Sahar Mohammadpour

2016-11-01

Complex structure of human language enables us to exchange very complicated information. This communication system obeys some common nonlinear statistical regularities. We investigate four important long-range features of human language. We perform our calculations for adopted works of seven famous litterateurs. Zipf's law and Heaps' law, which imply well-known power-law behaviors, are established in human language, showing a qualitative inverse relation with each other. Furthermore, the informational content associated with the words ordering, is measured by using an entropic metric. We also calculate fractal dimension of words in the text by using box counting method. The fractal dimension of each word, that is a positive value less than or equal to one, exhibits its spatial distribution in the text. Generally, we can claim that the Human language follows the mentioned power-law regularities. Power-law relations imply the existence of long-range correlations between the word types, to convey an especial idea.

Design methodology of Dutch banknotes

NASA Astrophysics Data System (ADS)

de Heij, Hans A. M.

2000-04-01

Since the introduction of a design methodology for Dutch banknotes, the quality of Dutch paper currency has improved in more than one way. The methodology is question provides for (i) a design policy, which helps fix clear objectives; (ii) design management, to ensure a smooth cooperation between the graphic designer, printer, papermaker an central bank, (iii) a program of requirements, a banknote development guideline for all parties involved. This systematic approach enables an objective selection of design proposals, including security features. Furthermore, the project manager obtains regular feedback from the public by conducting market surveys. Each new design of a Netherlands Guilder banknote issued by the Nederlandsche Bank of the past 50 years has been an improvement on its predecessor in terms of value recognition, security and durability.

Monitoring of blazars on the SPbSU 16" telescope

NASA Astrophysics Data System (ADS)

Troitskiy, I. S.; Morozova, D. A.; Blinov, D. A.; Larionov, V. M.; Ershtadt, S. G.

2012-05-01

The fast variability in the total and polarized fluxes is prominent feature of blazars. The analysis demands dense series of observations. Meade 16" LX200 telescope is one of the basic instruments for these purposes in St.Petersburg State University. The photometry in B, V, R, I bands and polarimetry of the majority of program sources are spent. Thanks to organizational, methodical and technical solutions it was possible to achieve high efficiency of usage of the telescope for blazar monitoring. Unique observаtions series have been received. Results were included into articles published in such magazines, as the Astronomy Letters, Astronomy Reports, A&A, ApJ, Nature. International programs of active galactic nuclei monitoring are regularly spent.

Index of NACA Technical Publications, 1949 - May, 1951

NASA Technical Reports Server (NTRS)

1952-01-01

The Preface to the Index of NACA Technical Publications, 1915-1949, mentioned that regular supplements would be issued in the future. This is the first such Supplement and covers those documents issued through May of 1951. Similar arrangement is used in both Indexes. First, there is a classified listing of the subject categories; second, a chronological listing of NACA publications under each subject category; third, an alphabetical index to the subject categories; and finally, an author index. The latter feature was not included in the basic 1915-1949 Index but has been issued separately and is available upon request. Immediately following this Preface is an Explanatory Chart of NACA Publications Series Designations which may be of use in identifying references to NACA documents encountered in the literature.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil

2012-01-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput “omics” data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel “similarity statistic”-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called ‘MVR’ (‘Mean-Variance Regularization’), downloadable from the CRAN website. PMID:22711950

Direct Recordings of Pitch Responses from Human Auditory Cortex

PubMed Central

Griffiths, Timothy D.; Kumar, Sukhbinder; Sedley, William; Nourski, Kirill V.; Kawasaki, Hiroto; Oya, Hiroyuki; Patterson, Roy D.; Brugge, John F.; Howard, Matthew A.

2010-01-01

Summary Pitch is a fundamental percept with a complex relationship to the associated sound structure [1]. Pitch perception requires brain representation of both the structure of the stimulus and the pitch that is perceived. We describe direct recordings of local field potentials from human auditory cortex made while subjects perceived the transition between noise and a noise with a regular repetitive structure in the time domain at the millisecond level called regular-interval noise (RIN) [2]. RIN is perceived to have a pitch when the rate is above the lower limit of pitch [3], at approximately 30 Hz. Sustained time-locked responses are observed to be related to the temporal regularity of the stimulus, commonly emphasized as a relevant stimulus feature in models of pitch perception (e.g., [1]). Sustained oscillatory responses are also demonstrated in the high gamma range (80–120 Hz). The regularity responses occur irrespective of whether the response is associated with pitch perception. In contrast, the oscillatory responses only occur for pitch. Both responses occur in primary auditory cortex and adjacent nonprimary areas. The research suggests that two types of pitch-related activity occur in humans in early auditory cortex: time-locked neural correlates of stimulus regularity and an oscillatory response related to the pitch percept. PMID:20605456

76 FR 61374 - Massachusetts; Emergency and Related Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-04

...), including direct Federal assistance, under the Public Assistance program. This assistance excludes regular time costs for subgrantees' regular employees. Consistent with the requirement that Federal assistance... protective measures (Category B), including direct Federal assistance, under the Public Assistance program...

Acceleration display system for aircraft zero-gravity research

NASA Technical Reports Server (NTRS)

Millis, Marc G.

1987-01-01

The features, design, calibration, and testing of Lewis Research Center's acceleration display system for aircraft zero-gravity research are described. Specific circuit schematics and system specifications are included as well as representative data traces from flown trajectories. Other observations learned from developing and using this system are mentioned where appropriate. The system, now a permanent part of the Lewis Learjet zero-gravity program, provides legible, concise, and necessary guidance information enabling pilots to routinely fly accurate zero-gravity trajectories. Regular use of this system resulted in improvements of the Learjet zero-gravity flight techniques, including a technique to minimize later accelerations. Lewis Gates Learjet trajectory data show that accelerations can be reliably sustained within 0.01 g for 5 consecutive seconds, within 0.02 g for 7 consecutive seconds, and within 0.04 g for up to 20 second. Lewis followed the past practices of acceleration measurement, yet focussed on the acceleration displays. Refinements based on flight experience included evolving the ranges, resolutions, and frequency responses to fit the pilot and the Learjet responses.

The production and perception of emotionally expressive walking sounds: similarities between musical performance and everyday motor activity.

PubMed

Giordano, Bruno L; Egermann, Hauke; Bresin, Roberto

2014-01-01

Several studies have investigated the encoding and perception of emotional expressivity in music performance. A relevant question concerns how the ability to communicate emotions in music performance is acquired. In accordance with recent theories on the embodiment of emotion, we suggest here that both the expression and recognition of emotion in music might at least in part rely on knowledge about the sounds of expressive body movements. We test this hypothesis by drawing parallels between musical expression of emotions and expression of emotions in sounds associated with a non-musical motor activity: walking. In a combined production-perception design, two experiments were conducted, and expressive acoustical features were compared across modalities. An initial performance experiment tested for similar feature use in walking sounds and music performance, and revealed that strong similarities exist. Features related to sound intensity, tempo and tempo regularity were identified as been used similarly in both domains. Participants in a subsequent perception experiment were able to recognize both non-emotional and emotional properties of the sound-generating walkers. An analysis of the acoustical correlates of behavioral data revealed that variations in sound intensity, tempo, and tempo regularity were likely used to recognize expressed emotions. Taken together, these results lend support the motor origin hypothesis for the musical expression of emotions.

The correlation study of parallel feature extractor and noise reduction approaches

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

Dewi, Deshinta Arrova; Sundararajan, Elankovan; Prabuwono, Anton Satria

2015-05-15

This paper presents literature reviews that show variety of techniques to develop parallel feature extractor and finding its correlation with noise reduction approaches for low light intensity images. Low light intensity images are normally displayed as darker images and low contrast. Without proper handling techniques, those images regularly become evidences of misperception of objects and textures, the incapability to section them. The visual illusions regularly clues to disorientation, user fatigue, poor detection and classification performance of humans and computer algorithms. Noise reduction approaches (NR) therefore is an essential step for other image processing steps such as edge detection, image segmentation,more » image compression, etc. Parallel Feature Extractor (PFE) meant to capture visual contents of images involves partitioning images into segments, detecting image overlaps if any, and controlling distributed and redistributed segments to extract the features. Working on low light intensity images make the PFE face challenges and closely depend on the quality of its pre-processing steps. Some papers have suggested many well established NR as well as PFE strategies however only few resources have suggested or mentioned the correlation between them. This paper reviews best approaches of the NR and the PFE with detailed explanation on the suggested correlation. This finding may suggest relevant strategies of the PFE development. With the help of knowledge based reasoning, computational approaches and algorithms, we present the correlation study between the NR and the PFE that can be useful for the development and enhancement of other existing PFE.« less

Algorithm-Dependent Generalization Bounds for Multi-Task Learning.

PubMed

Liu, Tongliang; Tao, Dacheng; Song, Mingli; Maybank, Stephen J

2017-02-01

Often, tasks are collected for multi-task learning (MTL) because they share similar feature structures. Based on this observation, in this paper, we present novel algorithm-dependent generalization bounds for MTL by exploiting the notion of algorithmic stability. We focus on the performance of one particular task and the average performance over multiple tasks by analyzing the generalization ability of a common parameter that is shared in MTL. When focusing on one particular task, with the help of a mild assumption on the feature structures, we interpret the function of the other tasks as a regularizer that produces a specific inductive bias. The algorithm for learning the common parameter, as well as the predictor, is thereby uniformly stable with respect to the domain of the particular task and has a generalization bound with a fast convergence rate of order O(1/n), where n is the sample size of the particular task. When focusing on the average performance over multiple tasks, we prove that a similar inductive bias exists under certain conditions on the feature structures. Thus, the corresponding algorithm for learning the common parameter is also uniformly stable with respect to the domains of the multiple tasks, and its generalization bound is of the order O(1/T), where T is the number of tasks. These theoretical analyses naturally show that the similarity of feature structures in MTL will lead to specific regularizations for predicting, which enables the learning algorithms to generalize fast and correctly from a few examples.

Carleton College Geology Department: Seventy Years of Planning for Change

NASA Astrophysics Data System (ADS)

Savina, M. E.; Davidson, C.

2003-12-01

On the back of a fire door leading to the Carleton geology lounge and classroom, students have painted a geologic time scale representing the history of the geology department from its establishment in 1933 to its present configuration. Along the way, Laurence McKinley Gould, George Gibson, Duncan Stewart VII, Leonard Wilson, Eiler Henrickson, Ed Buchwald, Shelby Boardman, Mary Savina, David Bice, Clem Shearer, Bereket Haileab, Clint Cowan, Cam Davidson, Jenn Macalady and a host of other faculty have contributed to an excellent undergraduate program. Features that have maintained the strength of the program over the years include: Outstanding support staff (Betty Bray and Tim Vick); Weekly department meetings that include discussion of department goals and pedagogy, including attention to giving students the tools to complete the major and capstone project; Regular department retreats that allow more comprehensive discussion; Encouraging different teaching styles among the faculty; A curriculum that emphasizes active learning from day one in introductory geology through the senior capstone experience; Involving students in the department, from planning field trips to hiring to TAs; Increasing student role models by having sophomore, junior and senior majors in most courses; Emphasizing the liberal arts character of geology, rather than pre-professional; Bringing alumni back to campus on a regular basis; Publishing an annual alumni newsletter and maintaining a department web site; Creating a social and intellectual space within the department for students and faculty; Making a particular effort to be welcoming and affirming to people of all colors, ethnicities, affectional orientations and gender identities;

76 FR 60850 - Rhode Island; Emergency and Related Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-30

...), including direct Federal assistance, under the Public Assistance program. This assistance excludes regular time costs for subgrantees' regular employees. Consistent with the requirement that Federal assistance...), including direct federal assistance, under the Public Assistance program. The following Catalog of Federal...

"I'm Proud to Be Me": Health, Community and Schooling

ERIC Educational Resources Information Center

Burrrows, Lisette

2011-01-01

Health reportage in New Zealand's popular and professional media regularly features large, avowedly inactive, indigenous and/or "poor" people failing to nurture their children properly on account of their size. While well-meaning government and school-based initiatives explicitly target these so-called "high-need" communities,…

A Level Playing Field

ERIC Educational Resources Information Center

Harac, Lani

2004-01-01

In this article, the author features the Universal Design for Learning, a computer-assisted methodology that has enabled special-needs kids in the Boston area to stay in regular classrooms. Developed by a nonprofit group called the Center for Applied Special Technology, the UDL approach--in which students use whatever print or technological tools…

The AMATYC Review, Volume 18, Numbers 1-2, Fall 1996-Spring 1997.

ERIC Educational Resources Information Center

Browne, Joseph, Ed.

1997-01-01

Designed as an avenue of communication for mathematics educators concerned with the views, ideas, and experiences of two-year college students and teachers, this journal contains articles on mathematics exposition and education and regular features presenting book and software reviews, classroom activities, instructor experiences, and math…

The Professional Educator: How I Support LGBTQ+ Students at My School

ERIC Educational Resources Information Center

Hsu, Taica

2017-01-01

Professional educators--in the classroom, library, counseling center, or anywhere in between--share one overarching goal: ensuring all students receive the rich, well-rounded education they need to be productive, engaged citizens. In this regular feature, "American Educator" explores the work of professional educators--their…

Evaluation of a Tobacco and Alcohol Abuse Prevention Curriculum for Adolescents.

ERIC Educational Resources Information Center

Hansen, William B.; And Others

Programs which have been somewhat effective in reducing the rates of onset of regular tobacco use have featured such components as peer pressure resistance training, correction of normative expectations, inoculation against mass media messages, information about parental influences, information about consequences of use, public commitments, or…

Videodiscs in Special Education.

ERIC Educational Resources Information Center

Education Turnkey Systems, Inc., Falls Church, VA.

One of four reports designed to assess the current state of new technologies, the document reviews the current and future 5-year status of videodisc technology in special and regular education. Described first are the history, technological features, and prices of videodisc systems (which consist of a player, programing material stored on a disc,…

Processing of Irregular Polysemes in Sentence Reading

ERIC Educational Resources Information Center

Brocher, Andreas; Foraker, Stephani; Koenig, Jean-Pierre

2016-01-01

The degree to which meanings are related in memory affects ambiguous word processing. We examined irregular polysemes, which have related senses based on similar or shared features rather than a relational rule, like regular polysemy. We tested to what degree the related meanings of irregular polysemes ("wire") are represented with…

The Professional Educator: Pittsburgh's Winning Partnership

ERIC Educational Resources Information Center

Hamill, Sean D.

2011-01-01

Professional educators--whether in the classroom, library, counseling center, or anywhere in between--share one overarching goal: seeing all students succeed in school and life. In this regular feature, the work of professional educators is explored--not just their accomplishments, but also their challenges--so that the lessons they have learned…

The Professional Educator: Connecting with Students and Families through Home Visits

ERIC Educational Resources Information Center

Faber, Nick

2015-01-01

Professional educators--in the classroom, library, counseling center, or anywhere in between--share one overarching goal: ensuring all students receive the rich, well-rounded education they need to be productive, engaged citizens. This regular feature, explores the work of professional educators--their accomplishments and their challenges--so that…

The Professional Educator: Celebrating the Voices of Immigrant Students

ERIC Educational Resources Information Center

Zehr, Mary Ann

2018-01-01

Professional educators--in the classroom, library, counseling center, or anywhere in between--share one overarching goal: ensuring all students receive the rich, well-rounded education they need to be productive, engaged citizens. In this regular feature, the work of professional educators is explored--their accomplishments and their…

Pre-Service Teachers' Perceptions of a Short-Term International Experience Programme

ERIC Educational Resources Information Center

Barkhuizen, Gary; Feryok, Anne

2006-01-01

Short-term international experiences (STIE) are becoming a regular, sometimes required, feature of pre-service language teacher education programmes. Often inappropriately termed "immersion programmes", they aim to give teachers the opportunity to improve their language proficiency in the language they will teach, to develop their…

Between the Lines. A Basic Skills Newspaper Pack.

ERIC Educational Resources Information Center

Adult Literacy and Basic Skills Unit, London (England).

This document incorporates source materials from local and regional newspapers from different parts of the United Kingdom into learning activities to develop literacy skills. The activities are organized into seven sections as follows: local newspapers (types of local newspapers, regular and special features, columns and blocks, and reading the…

The Pancake Professor and the Decline of Scholarly Writing

ERIC Educational Resources Information Center

Sweet, Charlie; Blythe, Hal; Carpenter, Russell

2015-01-01

With this issue of the "Journal of Faculty Development," we begin a new feature called "Brief Communications." Manuscripts that do not fit one of the regular "JFD" categories may be published as Brief Communications. These pieces must still meet the "Journal's" publication standards in all other respects.…

The Role of Teachers' Guided Reflection in Effecting Positive Program Change.

ERIC Educational Resources Information Center

Vogt, Lynn Allington; Au, Kathryn H. P.

1995-01-01

Examines the evolution of teacher support and development in the Kamehameha Elementary Education Program (KEEP) and Rough Rock Community School collaboration. Ongoing teacher development featured regular classroom observation and feedback with mentors and peers and self-reflection through videotaping and journal writing. (two references) (MDM)

The AMATYC Review, Volume 17. Numbers 1-2, Fall 1995-Spring 1996.

ERIC Educational Resources Information Center

Browne, Joseph, Ed.

1996-01-01

Designed as an avenue of communication for mathematics educators concerned with the views, ideas, and experiences of two-year college students and teachers, this journal contains articles on mathematics exposition and education and regular features presenting book and software reviews, classroom activities, instructor experiences, and math…

Playing to Win: The Evolution of Athletics and Reform in American Higher Education

ERIC Educational Resources Information Center

Lee, Candice Storey

2012-01-01

Intercollegiate athletics, namely "big-time" athletics, is an enduring feature of American higher education. Its visibility is unmatched by other institutional activities, and its influence reaches far beyond the campus. College athletics' longevity insulates it from the likelihood of elimination, but it regularly earns criticism…

The Role of Semantic Features in Verb Processing

ERIC Educational Resources Information Center

Bonnotte, Isabelle

2008-01-01

The present study examined the general hypothesis that, as for nouns, stable representations of semantic knowledge relative to situations expressed by verbs are available and accessible in long term memory in normal people. Regular associations between verbs and past tenses in French adults allowed to abstract two superordinate semantic features…

Regional Trends Sustainable Development. ASPBAE Courier No. 51.

ERIC Educational Resources Information Center

ASPBAE Courier, 1991

1991-01-01

This issue contains six articles about the practice of adult and nonformal education in the Asian South Pacific region, as well as committee reports, policy statements, and regular features. The articles on adult and nonformal education, and other entries are as follows: "Emerging Trends, Concerns and Issues in Educational Development in…

MSLICE Sequencing

NASA Technical Reports Server (NTRS)

Crockett, Thomas M.; Joswig, Joseph C.; Shams, Khawaja S.; Norris, Jeffrey S.; Morris, John R.

2011-01-01

MSLICE Sequencing is a graphical tool for writing sequences and integrating them into RML files, as well as for producing SCMF files for uplink. When operated in a testbed environment, it also supports uplinking these SCMF files to the testbed via Chill. This software features a free-form textural sequence editor featuring syntax coloring, automatic content assistance (including command and argument completion proposals), complete with types, value ranges, unites, and descriptions from the command dictionary that appear as they are typed. The sequence editor also has a "field mode" that allows tabbing between arguments and displays type/range/units/description for each argument as it is edited. Color-coded error and warning annotations on problematic tokens are included, as well as indications of problems that are not visible in the current scroll range. "Quick Fix" suggestions are made for resolving problems, and all the features afforded by modern source editors are also included such as copy/cut/paste, undo/redo, and a sophisticated find-and-replace system optionally using regular expressions. The software offers a full XML editor for RML files, which features syntax coloring, content assistance and problem annotations as above. There is a form-based, "detail view" that allows structured editing of command arguments and sequence parameters when preferred. The "project view" shows the user s "workspace" as a tree of "resources" (projects, folders, and files) that can subsequently be opened in editors by double-clicking. Files can be added, deleted, dragged-dropped/copied-pasted between folders or projects, and these operations are undoable and redoable. A "problems view" contains a tabular list of all problems in the current workspace. Double-clicking on any row in the table opens an editor for the appropriate sequence, scrolling to the specific line with the problem, and highlighting the problematic characters. From there, one can invoke "quick fix" as described above to resolve the issue. Once resolved, saving the file causes the problem to be removed from the problem view.

Expanding the Universe of "Astronomy on Tap" Public Outreach Events

NASA Astrophysics Data System (ADS)

Rice, Emily L.; Levine, Brian; Livermore, Rachael C.; Silverman, Jeffrey M.; LaMassa, Stephanie M.; Tyndall, Amy; Muna, Demitri; Garofali, Kristen; Morris, Brett; Byler, Nell; Fyhrie, Adalyn; Rehnberg, Morgan; Hart, Quyen N.; Connelly, Jennifer L.; Silvia, Devin W.; Morrison, Sarah J.; Agarwal, Bhaskar; Tremblay, Grant; Schwamb, Megan E.

2016-01-01

Astronomy on Tap (AoT, astronomyontap.org) is free public outreach event featuring engaging science presentations in bars, often combined with music, games, and prizes, to encourage a fun, interactive atmosphere. AoT events feature several short astronomy-related presentations primarily by local professional scientists, but also by visiting scientists, students, educators, amatuer astronomers, writers, and artists. Events are held in social venues (bars, coffee shops, art galleries, etc.) in order to bring science directly to the public in a relaxed, informal atmosphere. With this we hope to engage a more diverse audience than typical lectures at academic and cultural institutions and to develop enthusiasm for science among voting, tax-paying adults. The flexible format and content of an AoT event is easy to adapt and expand based on the priorities, resources, and interests of local organizers. The social nature of AoT events provides important professional development and networking opportunities in science communication. Since the first New York City event in April 2013, Astronomy on Tap has expanded to more than ten cities globally, including monthly events in NYC, Austin, Seattle, and Tucson; semi-regular events in Columbus, New Haven, Santiago, Toronto, and Denver; occasional (so far) events in Rochester (NY), Baltimore, Lansing, and Washington, DC; and one-off events in Chicago and Taipei. Several venues regularly attract audiences of over 200 people. We have received media coverage online, in print, and occasionally even on radio and television. In this poster we describe the overarching goals and characteristics of AoT events, distinct adaptations of various locations, resources we have developed, and the methods we use to coordinate among the worldwide local organizers.

Body Acceleration as Indicator for Walking Economy in an Ageing Population.

PubMed

Valenti, Giulio; Bonomi, Alberto G; Westerterp, Klaas R

2015-01-01

In adults, walking economy declines with increasing age and negatively influences walking speed. This study aims at detecting determinants of walking economy from body acceleration during walking in an ageing population. 35 healthy elderly (18 males, age 51 to 83 y, BMI 25.5±2.4 kg/m2) walked on a treadmill. Energy expenditure was measured with indirect calorimetry while body acceleration was sampled at 60Hz with a tri-axial accelerometer (GT3X+, ActiGraph), positioned on the lower back. Walking economy was measured as lowest energy needed to displace one kilogram of body mass for one meter while walking (WCostmin, J/m/kg). Gait features were extracted from the acceleration signal and included in a model to predict WCostmin. On average WCostmin was 2.43±0.42 J/m/kg and correlated significantly with gait rate (r2 = 0.21, p<0.01) and regularity along the frontal (anteroposterior) and lateral (mediolateral) axes (r2 = 0.16, p<0.05 and r2 = 0.12, p<0.05 respectively). Together, the three variables explained 46% of the inter-subject variance (p<0.001) with a standard error of estimate of 0.30 J/m/kg. WCostmin and regularity along the frontal and lateral axes were related to age (WCostmin: r2 = 0.44, p<0.001; regularity: r2 = 0.16, p<0.05 and r2 = 0.12, p<0.05 respectively frontal and lateral). The age associated decline in walking economy is induced by the adoption of an increased gait rate and by irregular body acceleration in the horizontal plane.

Performance analysis of model based iterative reconstruction with dictionary learning in transportation security CT

NASA Astrophysics Data System (ADS)

Haneda, Eri; Luo, Jiajia; Can, Ali; Ramani, Sathish; Fu, Lin; De Man, Bruno

2016-05-01

In this study, we implement and compare model based iterative reconstruction (MBIR) with dictionary learning (DL) over MBIR with pairwise pixel-difference regularization, in the context of transportation security. DL is a technique of sparse signal representation using an over complete dictionary which has provided promising results in image processing applications including denoising,1 as well as medical CT reconstruction.2 It has been previously reported that DL produces promising results in terms of noise reduction and preservation of structural details, especially for low dose and few-view CT acquisitions.2 A distinguishing feature of transportation security CT is that scanned baggage may contain items with a wide range of material densities. While medical CT typically scans soft tissues, blood with and without contrast agents, and bones, luggage typically contains more high density materials (i.e. metals and glass), which can produce severe distortions such as metal streaking artifacts. Important factors of security CT are the emphasis on image quality such as resolution, contrast, noise level, and CT number accuracy for target detection. While MBIR has shown exemplary performance in the trade-off of noise reduction and resolution preservation, we demonstrate that DL may further improve this trade-off. In this study, we used the KSVD-based DL3 combined with the MBIR cost-minimization framework and compared results to Filtered Back Projection (FBP) and MBIR with pairwise pixel-difference regularization. We performed a parameter analysis to show the image quality impact of each parameter. We also investigated few-view CT acquisitions where DL can show an additional advantage relative to pairwise pixel difference regularization.

76 FR 60852 - District of Columbia; Emergency and Related Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-30

...), including direct Federal assistance, under the Public Assistance program. This assistance excludes regular time costs for subgrantees' regular employees. Consistent with the requirement that Federal assistance... measures (Category B), including direct federal assistance, under the Public Assistance program for the...

76 FR 61726 - North Carolina; Emergency and Related Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-05

...), including direct Federal assistance, under the Public Assistance program. This assistance excludes regular time costs for subgrantees' regular employees. Consistent with the requirement that Federal assistance...), including direct federal assistance, under the Public Assistance program at 75 percent federal funding. The...

A-Train Education Activities: Partnerships to Engage Citizens with Atmospheric Science

NASA Astrophysics Data System (ADS)

Ellis, T. D.; Taylor, J.; Chambers, L. H.; Graham, S.; Butcher, G. J.

2016-12-01

Since the launch of Aqua in 2002, the A-Train satellites have been at the forefront of observing Earth's atmosphere using the wide variety of instruments on the spacecraft in the formation. Similarly, the A-Train missions have also taken a variety of perspectives on engaging the general public with NASA science. These approaches have included a range of formal education partnerships featuring the GLOBE program (including a cloud observation network through CloudSat, several initiatives to understand and measure aerosols, and development of a new elementary story book), unique citizen-science activities such as Students' Cloud Observations On Line (S'COOL), connections with the PBS Kids SciGirls program, and much more. An education component was also featured at the first A-Train symposium in New Orleans, engaging local educators to learn about the many education resources available from the A-Train missions. Increasingly, the mission education teams have been working together to drive home thematic science content, such as the roles of clouds in our climate system and regular measurements of Earth's radiant energy balance. This paper describes the evolution of A-Train education efforts over the past decade, highlights key achievements, and presents information on new initiatives to continue to engage the public with A-Train science.

A novel method for determining sex in late term gestational mice based on the external genitalia

PubMed Central

Murdaugh, Laura B.; Mendoza-Romero, Haley N.; Fish, Eric W.

2018-01-01

In many experiments using fetal mice, it is necessary to determine the sex of the individual fetus. However, other than genotyping for sex-specific genes, there is no convenient, reliable method of sexing mice between gestational day (GD) 16.5 and GD 18.0. We designed a rapid, relatively simple visual method to determine the sex of mouse fetuses in the GD 16.5—GD 18.0 range that can be performed as part of a routine morphological assessment. By examining the genitalia for the presence or absence of key features, raters with minimal experience with the method were able to correctly identify the sex of embryos with 99% accuracy, while raters with no experience were 95% accurate. The critical genital features include: the presence or absence of urethral seam or proximal urethral meatus; the shape of the genitalia, and the presence or absence of an area related to the urethral plate. By comparing these morphological features of the external genitalia, we show a simple, accurate, and fast way to determine the sex of late stage mouse fetuses. Integrating this method into regular morphological assessments will facilitate the determination of sex differences in fetuses between GD 16.5 and GD 18.0. PMID:29617407

MRI reconstruction with joint global regularization and transform learning.

PubMed

Tanc, A Korhan; Eksioglu, Ender M

2016-10-01

Sparsity based regularization has been a popular approach to remedy the measurement scarcity in image reconstruction. Recently, sparsifying transforms learned from image patches have been utilized as an effective regularizer for the Magnetic Resonance Imaging (MRI) reconstruction. Here, we infuse additional global regularization terms to the patch-based transform learning. We develop an algorithm to solve the resulting novel cost function, which includes both patchwise and global regularization terms. Extensive simulation results indicate that the introduced mixed approach has improved MRI reconstruction performance, when compared to the algorithms which use either of the patchwise transform learning or global regularization terms alone. Copyright © 2016 Elsevier Ltd. All rights reserved.

A TV Camera System Which Extracts Feature Points For Non-Contact Eye Movement Detection

NASA Astrophysics Data System (ADS)

Tomono, Akira; Iida, Muneo; Kobayashi, Yukio

1990-04-01

This paper proposes a highly efficient camera system which extracts, irrespective of background, feature points such as the pupil, corneal reflection image and dot-marks pasted on a human face in order to detect human eye movement by image processing. Two eye movement detection methods are sugested: One utilizing face orientation as well as pupil position, The other utilizing pupil and corneal reflection images. A method of extracting these feature points using LEDs as illumination devices and a new TV camera system designed to record eye movement are proposed. Two kinds of infra-red LEDs are used. These LEDs are set up a short distance apart and emit polarized light of different wavelengths. One light source beams from near the optical axis of the lens and the other is some distance from the optical axis. The LEDs are operated in synchronization with the camera. The camera includes 3 CCD image pick-up sensors and a prism system with 2 boundary layers. Incident rays are separated into 2 wavelengths by the first boundary layer of the prism. One set of rays forms an image on CCD-3. The other set is split by the half-mirror layer of the prism and forms an image including the regularly reflected component by placing a polarizing filter in front of CCD-1 or another image not including the component by not placing a polarizing filter in front of CCD-2. Thus, three images with different reflection characteristics are obtained by three CCDs. Through the experiment, it is shown that two kinds of subtraction operations between the three images output from CCDs accentuate three kinds of feature points: the pupil and corneal reflection images and the dot-marks. Since the S/N ratio of the subtracted image is extremely high, the thresholding process is simple and allows reducting the intensity of the infra-red illumination. A high speed image processing apparatus using this camera system is decribed. Realtime processing of the subtraction, thresholding and gravity position calculation of the feature points is possible.

Developing Sustainable and Impactful Mobile Phone HIV Testing Interventions for Spanish-Speaking Men Who Have Sex With Men in the United States: Lessons Learned From Informative Interviews

PubMed Central

Torres, Maria Beatriz; Asmar, Lucy; Danh, Thu; Horvath, Keith J

2018-01-01

Background Although many men who have sex with men (MSM) test for HIV at least once in their lifetime, opportunities to improve regular HIV testing, particularly among Hispanic or Latino MSM, is needed. Many mHealth interventions in development, including the ones on HIV testing, have primarily focused on English-speaking white, black, and MSM of other races. To date, no studies have assessed app use, attitudes, and motivations for downloading and sustaining use of mobile apps and preferences with respect to HIV prevention among Spanish-speaking, Hispanic MSM in the United States. Objective The primary aims of this study were to determine what features and functions of smartphone apps do Hispanic, Spanish-speaking MSM believe are associated with downloading apps to their smartphones, (2) what features and functions of smartphone apps are most likely to influence men’s sustained use of apps over time, and (3) what features and functions do men prefer in a smartphone app aimed to promote regular testing for HIV. Methods Interviews (N=15) were conducted with a racially diverse group of sexually active, HIV-negative, Spanish-speaking, Hispanic MSM in Miami, Florida. Interviews were digitally recorded, transcribed verbatim, translated back to English, and de-identified for analysis. A constant-comparison method (ie, grounded theory coding) was employed to examine themes that emerged from the interviews. Results Personal interest was the primary reason associated with whether men downloaded an app. Keeping personal information secure, cost, influence by peers and posted reviews, ease of use, and functionality affected whether they downloaded and used the app over time. Men also reported that entertainment value and frequency of updates influenced whether they kept and continued to use an app over time. There were 4 reasons why participants chose to delete an app—dislike, lack of use, cost, and lack of memory or space. Participants also shared their preferences for an app to encourage regular HIV testing by providing feedback on test reminders, tailored testing interval recommendations, HIV test locator, and monitoring of personal sexual behaviors. Conclusions The features and functions of mobile apps that Spanish-speaking MSM in this study believed were associated with downloading and/or sustained engagement of an app generally reflected the priorities mentioned in an earlier study with English-speaking MSM. Unlike the earlier study, Spanish-speaking MSM prioritized personal interest in a mobile app and de-emphasized the efficiency of an app to make their lives easier in their decision to download an app to their mobile device. Tailoring mobile apps to the language and needs of Spanish-speaking MSM is critical to help increase their willingness to download a mobile app. Despite the growing number of HIV-prevention apps in development, few are tailored to Spanish-speaking MSM, representing an important gap that should be addressed in future research. PMID:29691205

Automated Geometry assisted PEC for electron beam direct write nanolithography

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

Ocola, Leonidas E.; Gosztola, David J.; Rosenmann, Daniel

Nanoscale geometry assisted proximity effect correction (NanoPEC) is demonstrated to improve PEC for nanoscale structures over standard PEC, in terms of feature sharpness for sub-100 nm structures. The method was implemented onto an existing commercially available PEC software. Plasmonic arrays of crosses were fabricated using regular PEC and NanoPEC, and optical absorbance was measured. Results confirm that the improved sharpness of the structures leads to increased sharpness in the optical absorbance spectrum features. We also demonstrated that this method of PEC is applicable to arbitrary shaped structures beyond crosses.

Understanding human dynamics in microblog posting activities

NASA Astrophysics Data System (ADS)

Jiang, Zhihong; Zhang, Yubao; Wang, Hui; Li, Pei

2013-02-01

Human activity patterns are an important issue in behavior dynamics research. Empirical evidence indicates that human activity patterns can be characterized by a heavy-tailed inter-event time distribution. However, most researchers give an understanding by only modeling the power-law feature of the inter-event time distribution, and those overlooked non-power-law features are likely to be nontrivial. In this work, we propose a behavior dynamics model, called the finite memory model, in which humans adaptively change their activity rates based on a finite memory of recent activities, which is driven by inherent individual interest. Theoretical analysis shows a finite memory model can properly explain various heavy-tailed inter-event time distributions, including a regular power law and some non-power-law deviations. To validate the model, we carry out an empirical study based on microblogging activity from thousands of microbloggers in the Celebrity Hall of the Sina microblog. The results show further that the model is reasonably effective. We conclude that finite memory is an effective dynamics element to describe the heavy-tailed human activity pattern.

Pathview Web: user friendly pathway visualization and data integration.

PubMed

Luo, Weijun; Pant, Gaurav; Bhavnasi, Yeshvant K; Blanchard, Steven G; Brouwer, Cory

2017-07-03

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Simple proteomics data analysis in the object-oriented PowerShell.

PubMed

Mohammed, Yassene; Palmblad, Magnus

2013-01-01

Scripting languages such as Perl and Python are appreciated for solving simple, everyday tasks in bioinformatics. A more recent, object-oriented command shell and scripting language, Windows PowerShell, has many attractive features: an object-oriented interactive command line, fluent navigation and manipulation of XML files, ability to consume Web services from the command line, consistent syntax and grammar, rich regular expressions, and advanced output formatting. The key difference between classical command shells and scripting languages, such as bash, and object-oriented ones, such as PowerShell, is that in the latter the result of a command is a structured object with inherited properties and methods rather than a simple stream of characters. Conveniently, PowerShell is included in all new releases of Microsoft Windows and therefore already installed on most computers in classrooms and teaching labs. In this chapter we demonstrate how PowerShell in particular allows easy interaction with mass spectrometry data in XML formats, connection to Web services for tools such as BLAST, and presentation of results as formatted text or graphics. These features make PowerShell much more than "yet another scripting language."

Early-onset restrictive eating disturbances in primary school boys and girls.

PubMed

Kurz, Susanne; van Dyck, Zoé; Dremmel, Daniela; Munsch, Simone; Hilbert, Anja

2015-07-01

This study sought to determine the distribution of early-onset restrictive eating disturbances characteristic of the new DSM-5 diagnosis, avoidant/restrictive food intake disorder (ARFID) in middle childhood, as well as to evaluate the screening instrument, Eating Disturbances in Youth-Questionnaire (EDY-Q). A total of 1,444 8- to 13-year-old children were screened in regular schools (3rd to 6th grade) in Switzerland using the self-report measure EDY-Q, consisting of 12 items based on the DSM-5 criteria for ARFID. 46 children (3.2%) reported features of ARFID in the self-rating. Group differences were found for body mass index, with underweight children reporting features of ARFID more often than normal and overweight children. The EDY-Q revealed good psychometric properties, including adequate discriminant and convergent validity. Early-onset restrictive eating disturbances are commonly reported in middle childhood. Because of possible negative short- and long-term impact, early detection is essential. Further studies with structured interviews and parent reports are needed to confirm this study's findings.

Notes on an Outreach Forum for High School Chemistry Teachers - An Unexpected Success

NASA Astrophysics Data System (ADS)

Mayfield, Darwin L.

1997-05-01

Public realization in the United States of deficiencies in understanding basic facts and processes in science and mathematics is mounting. Teachers in these areas at all levels are key players in the challenges to come. This paper describes the activities of one small group of high school chemistry teachers as they have explored these challenges. The group of approximately sixteen has met regularly on the campus of California State University, Long Beach during the past seven years. The meetings (two or three each semester) are informal three-hour sessions over the dinner hour (box dinners are provided). A feature of each meeting is discussion of articles selected from the Journal of Chemical Education including retesting with variation of "Tested Demonstrations". Subscriptions to the Journal are provided to members. No fees are charged nor course credit given. The article outlines many of the program features, describes recruitment and changes in membership over time, examines possibilities for replication and emphasizes the great desire of secondary level chemistry teachers for exchange of ideas with peers. It explores the question "what did we do right?" in launching this successful forum.

5 CFR 532.213 - Industries included in regular appropriated fund wage surveys.

Code of Federal Regulations, 2010 CFR

2010-01-01

... food service and laundry establishments and industries having peculiar employment conditions that... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Industries included in regular... CIVIL SERVICE REGULATIONS PREVAILING RATE SYSTEMS Prevailing Rate Determinations § 532.213 Industries...

75 FR 25873 - West Virginia; Major Disaster and Related Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-10

... provide emergency protective measures, including snow assistance, under the Public Assistance program for... assistance, as warranted. This assistance excludes regular time costs for the sub-grantees' regular employees..., (Category B), including snow assistance, under the Public Assistance program for any continuous 48-hour...

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

PubMed

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Insightful monitoring of natural flood risk management features using a low-cost and participatory approach

NASA Astrophysics Data System (ADS)

Starkey, Eleanor; Barnes, Mhari; Quinn, Paul; Large, Andy

2016-04-01

Pressures associated with flooding and climate change have significantly increased over recent years. Natural Flood Risk Management (NFRM) is now seen as being a more appropriate and favourable approach in some locations. At the same time, catchment managers are also encouraged to adopt a more integrated, evidence-based and bottom-up approach. This includes engaging with local communities. Although NFRM features are being more readily installed, there is still limited evidence associated with their ability to reduce flood risk and offer multiple benefits. In particular, local communities and land owners are still uncertain about what the features entail and how they will perform, which is a huge barrier affecting widespread uptake. Traditional hydrometric monitoring techniques are well established but they still struggle to successfully monitor and capture NFRM performance spatially and temporally in a visual and more meaningful way for those directly affected on the ground. Two UK-based case studies are presented here where unique NFRM features have been carefully designed and installed in rural headwater catchments. This includes a 1km2 sub-catchment of the Haltwhistle Burn (northern England) and a 2km2 sub-catchment of Eddleston Water (southern Scotland). Both of these pilot sites are subject to prolonged flooding in winter and flash flooding in summer. This exacerbates sediment, debris and water quality issues downstream. Examples of NFRM features include ponds, woody debris and a log feature inspired by the children's game 'Kerplunk'. They have been tested and monitored over the 2015-2016 winter storms using low-cost techniques by both researchers and members of the community ('citizen scientists'). Results show that monitoring techniques such as regular consumer specification time-lapse cameras, photographs, videos and 'kite-cams' are suitable for long-term and low-cost monitoring of a variety of NFRM features. These techniques have been compared against traditional hydrometric monitoring equipment. It is clear that traditional techniques are expensive, require specialist skills and outputs are complicated to the untrained eye. These alternative methods tested are visually more meaningful, can be interpreted by all stakeholders and techniques can be easily utilised by citizen scientists, land owners or flood groups. Such techniques therefore offer a before, during and after NFRM monitoring solution which can be more realistically and readily implemented, supports engagement and subsequent uptake and maintenance of NFRM features on a local level. Although monitoring techniques presented are relatively simple, they are regarded as being essential given that many schemes are not monitored at all.

Consensus Statement of the American Academy of Sleep Medicine on the Recommended Amount of Sleep for Healthy Children: Methodology and Discussion.

PubMed

Paruthi, Shalini; Brooks, Lee J; D'Ambrosio, Carolyn; Hall, Wendy A; Kotagal, Suresh; Lloyd, Robin M; Malow, Beth A; Maski, Kiran; Nichols, Cynthia; Quan, Stuart F; Rosen, Carol L; Troester, Matthew M; Wise, Merrill S

2016-11-15

Members of the American Academy of Sleep Medicine developed consensus recommendations for the amount of sleep needed to promote optimal health in children and adolescents using a modified RAND Appropriateness Method. After review of 864 published articles, the following sleep durations are recommended: Infants 4 months to 12 months should sleep 12 to 16 hours per 24 hours (including naps) on a regular basis to promote optimal health. Children 1 to 2 years of age should sleep 11 to 14 hours per 24 hours (including naps) on a regular basis to promote optimal health. Children 3 to 5 years of age should sleep 10 to 13 hours per 24 hours (including naps) on a regular basis to promote optimal health. Children 6 to 12 years of age should sleep 9 to 12 hours per 24 hours on a regular basis to promote optimal health. Teenagers 13 to 18 years of age should sleep 8 to 10 hours per 24 hours on a regular basis to promote optimal health. Sleeping the number of recommended hours on a regular basis is associated with better health outcomes including: improved attention, behavior, learning, memory, emotional regulation, quality of life, and mental and physical health. Regularly sleeping fewer than the number of recommended hours is associated with attention, behavior, and learning problems. Insufficient sleep also increases the risk of accidents, injuries, hypertension, obesity, diabetes, and depression. Insufficient sleep in teenagers is associated with increased risk of self-harm, suicidal thoughts, and suicide attempts. A commentary on this article apears in this issue on page 1439. © 2016 American Academy of Sleep Medicine

Quantification of organ motion based on an adaptive image-based scale invariant feature method

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

Paganelli, Chiara; Peroni, Marta; Baroni, Guido

2013-11-15

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application ofmore » contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT, providing a motion description comparable to expert manual identification, as confirmed by DIR.Conclusions: The application of the method to a 4D lung CT patient dataset demonstrated adaptive-SIFT potential as an automatic tool to detect landmarks for DIR regularization and internal motion quantification. Future works should include the optimization of the computational cost and the application of the method to other anatomical sites and image modalities.« less

The AMATYC Review, Fall 1992-Spring 1993.

ERIC Educational Resources Information Center

Cohen, Don, Ed.; Browne, Joseph, Ed.

1993-01-01

Designed as an avenue of communication for mathematics educators concerned with the views, ideas, and experiences of two-year college students and teachers, this journal contains articles on mathematics exposition and education, as well as regular features presenting book and software reviews and math problems. The first of two issues of volume 14…

Contributions of Music Video Exposure to Black Adolescents' Gender and Sexual Schemas

ERIC Educational Resources Information Center

Ward, L. Monique; Hansbrough, Edwina; Walker, Eboni

2005-01-01

Although music videos feature prominently in the media diets of many adolescents, little is known of their impact on viewers' conceptions of femininity and masculinity. Accordingly, this study examines the impact of both regular and experimental music video exposure on adolescent viewers' conceptions about gender. Across two testing sessions, 152…

Q & A with Ed Tech Leaders: Interview with Ryan Watkins

ERIC Educational Resources Information Center

Shaughnessy, Michael F.; Fulgham, Susan M.

2016-01-01

In this regular feature of "Educational Technology," Michael F. Shaughnessy and Susan M. Fulgham present their interview with Ryan Watkins, Associate Professor of Educational Technology at the George Washington University and the author of 10 books and more than 95 articles. In this interview, Watkins discusses the following topics:…

School Science Inspired by Improving Weather Forecasts

ERIC Educational Resources Information Center

Reid, Heather; Renfrew, Ian A.; Vaughan, Geraint

2014-01-01

High winds and heavy rain are regular features of the British weather, and forecasting these events accurately is a major priority for the Met Office and other forecast providers. This is the challenge facing DIAMET, a project involving university groups from Manchester, Leeds, Reading, and East Anglia, together with the Met Office. DIAMET is part…

Substantive Nonadditivity in Rural Sociological Research: A Note on Induced Collinearity and Measurement and Testing of Effects.

ERIC Educational Resources Information Center

Miller, Michael K.; Farmer, Frank L.

Theories employed to explain regularities in social behavior often contain explicit or implicit reference to the presence of nonlinear and/or nonadditive (i.e., multiplicative) relationships among germane variables. While such nonadditive features are theoretically important, the inclusion of quadratic or multiplicative terms in structural…

Reverse and Add to 100: Explorations in Place Value

ERIC Educational Resources Information Center

Edwards, Michael Todd; Quinlan, James; Strayer, Jeremy F.

2016-01-01

During the past few years, several of the authors have incorporated student problem posing as a regular instructional feature in their classrooms. When they offer their students the opportunity to construct their own problems, particularly during the course of an entire school year, they create many novel tasks. Student-created tasks not only…

Ecological Consultancy

ERIC Educational Resources Information Center

Wilson, Scott McG.; Tattersfield, Peter

2004-01-01

This is the first of a new regular feature on careers, designed to provide those who teach biology with some inspiration when advising their students. In this issue, two consultant ecologists explain how their career paths developed. It is a misconception that there are few jobs in ecology. Over the past 20 or 30 years ecological consultancy has…

Emergent Feature Structures: Harmony Systems in Exemplar Models of Phonology

ERIC Educational Resources Information Center

Cole, Jennifer

2009-01-01

In exemplar models of phonology, phonotactic constraints are modeled as emergent from patterns of high activation between units that co-occur with statistical regularity, or as patterns of low activation or inhibition between units that co-occur less frequently or not at all. Exemplar models posit no a "priori" formal or representational…

Cultivating Advanced Technical Writing Skills through a Graduate-Level Course on Writing Research Proposals

ERIC Educational Resources Information Center

McCarthy, Brian D.; Dempsey, Jillian L.

2017-01-01

A graduate-level course focused on original research proposals is introduced to address the uneven preparation in technical writing of new chemistry graduate students. This course focuses on writing original research proposals. The general course structure features extensive group discussions, small-group activities, and regular in-class…

The AMATYC Review, Fall 1987, Spring 1988.

ERIC Educational Resources Information Center

Cohen, Don, Ed.

1988-01-01

Designed as an avenue of communication for mathematics educators concerned with the views, ideas, and experiences of two-year college students and teachers, this journal contains articles on mathematics exposition and education, and regular features that present book and software reviews and math problems. The first of two issues of volume 9…

Q & A with Ed Tech Leaders: Interview with Curt Bonk & Elaine Khoo

ERIC Educational Resources Information Center

Shaughnessy, Michael F.; Viner, Mark

2015-01-01

In this regular feature of "Educational Technology," Michael F. Shaughnessy and Mark Viner present their interview with Curt Bonk, Professor of Instructional Systems Technology at Indiana University and President of CourseShare; and Elaine Khoo, Research Fellow at the Wilf Malcolm Institute of Education, University of Waikato, Hamilton,…

Too Many Monkeys Jumping in Their Heads: Animal Lessons within Young Children's Media

ERIC Educational Resources Information Center

Timmerman, Nora; Ostertag, Julia

2011-01-01

Young children's media regularly features animals as its central characters. Potentially reflecting children's well-documented affinity for/with animals, this media--books, toys, songs, clothing, electronic media, and so on--carries with it many explicit and implicit messages about animals and human-animal relationships. This article focuses on…

Two-dimensional shape classification using generalized Fourier representation and neural networks

NASA Astrophysics Data System (ADS)

Chodorowski, Artur; Gustavsson, Tomas; Mattsson, Ulf

2000-04-01

A shape-based classification method is developed based upon the Generalized Fourier Representation (GFR). GFR can be regarded as an extension of traditional polar Fourier descriptors, suitable for description of closed objects, both convex and concave, with or without holes. Explicit relations of GFR coefficients to regular moments, moment invariants and affine moment invariants are given in the paper. The dual linear relation between GFR coefficients and regular moments was used to compare shape features derive from GFR descriptors and Hu's moment invariants. the GFR was then applied to a clinical problem within oral medicine and used to represent the contours of the lesions in the oral cavity. The lesions studied were leukoplakia and different forms of lichenoid reactions. Shape features were extracted from GFR coefficients in order to classify potentially cancerous oral lesions. Alternative classifiers were investigated based on a multilayer perceptron with different architectures and extensions. The overall classification accuracy for recognition of potentially cancerous oral lesions when using neural network classifier was 85%, while the classification between leukoplakia and reticular lichenoid reactions gave 96% (5-fold cross-validated) recognition rate.

Similarity-based Regularized Latent Feature Model for Link Prediction in Bipartite Networks.

PubMed

Wang, Wenjun; Chen, Xue; Jiao, Pengfei; Jin, Di

2017-12-05

Link prediction is an attractive research topic in the field of data mining and has significant applications in improving performance of recommendation system and exploring evolving mechanisms of the complex networks. A variety of complex systems in real world should be abstractly represented as bipartite networks, in which there are two types of nodes and no links connect nodes of the same type. In this paper, we propose a framework for link prediction in bipartite networks by combining the similarity based structure and the latent feature model from a new perspective. The framework is called Similarity Regularized Nonnegative Matrix Factorization (SRNMF), which explicitly takes the local characteristics into consideration and encodes the geometrical information of the networks by constructing a similarity based matrix. We also develop an iterative scheme to solve the objective function based on gradient descent. Extensive experiments on a variety of real world bipartite networks show that the proposed framework of link prediction has a more competitive, preferable and stable performance in comparison with the state-of-art methods.

A Class of Manifold Regularized Multiplicative Update Algorithms for Image Clustering.

PubMed

Yang, Shangming; Yi, Zhang; He, Xiaofei; Li, Xuelong

2015-12-01

Multiplicative update algorithms are important tools for information retrieval, image processing, and pattern recognition. However, when the graph regularization is added to the cost function, different classes of sample data may be mapped to the same subspace, which leads to the increase of data clustering error rate. In this paper, an improved nonnegative matrix factorization (NMF) cost function is introduced. Based on the cost function, a class of novel graph regularized NMF algorithms is developed, which results in a class of extended multiplicative update algorithms with manifold structure regularization. Analysis shows that in the learning, the proposed algorithms can efficiently minimize the rank of the data representation matrix. Theoretical results presented in this paper are confirmed by simulations. For different initializations and data sets, variation curves of cost functions and decomposition data are presented to show the convergence features of the proposed update rules. Basis images, reconstructed images, and clustering results are utilized to present the efficiency of the new algorithms. Last, the clustering accuracies of different algorithms are also investigated, which shows that the proposed algorithms can achieve state-of-the-art performance in applications of image clustering.

Cluster-size entropy in the Axelrod model of social influence: Small-world networks and mass media

NASA Astrophysics Data System (ADS)

Gandica, Y.; Charmell, A.; Villegas-Febres, J.; Bonalde, I.

2011-10-01

We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy Sc, which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the Sc(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait qc and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

Substructural Regularization With Data-Sensitive Granularity for Sequence Transfer Learning.

PubMed

Sun, Shichang; Liu, Hongbo; Meng, Jiana; Chen, C L Philip; Yang, Yu

2018-06-01

Sequence transfer learning is of interest in both academia and industry with the emergence of numerous new text domains from Twitter and other social media tools. In this paper, we put forward the data-sensitive granularity for transfer learning, and then, a novel substructural regularization transfer learning model (STLM) is proposed to preserve target domain features at substructural granularity in the light of the condition of labeled data set size. Our model is underpinned by hidden Markov model and regularization theory, where the substructural representation can be integrated as a penalty after measuring the dissimilarity of substructures between target domain and STLM with relative entropy. STLM can achieve the competing goals of preserving the target domain substructure and utilizing the observations from both the target and source domains simultaneously. The estimation of STLM is very efficient since an analytical solution can be derived as a necessary and sufficient condition. The relative usability of substructures to act as regularization parameters and the time complexity of STLM are also analyzed and discussed. Comprehensive experiments of part-of-speech tagging with both Brown and Twitter corpora fully justify that our model can make improvements on all the combinations of source and target domains.

Impulsivity and related neuropsychological features in regular and addictive first person shooter gaming.

PubMed

Metcalf, Olivia; Pammer, Kristen

2014-03-01

Putative cyber addictions are of significant interest. There remains little experimental research into excessive use of first person shooter (FPS) games, despite their global popularity. Moreover, the role between excessive gaming and impulsivity remains unclear, with previous research showing conflicting findings. The current study investigated performances on a number of neuropsychological tasks (go/no-go, continuous performance task, Iowa gambling task) and a trait measure of impulsivity for a group of regular FPS gamers (n=25), addicted FPS gamers (n=22), and controls (n=22). Gamers were classified using the Addiction-Engagement Questionnaire. Addicted FPS gamers had significantly higher levels of trait impulsivity on the Barratt Impulsiveness Scale compared to controls. Addicted FPS gamers also had significantly higher levels of disinhibition in a go/no-go task and inattention in a continuous performance task compared to controls, whereas the regular FPS gamers had better decision making on the Iowa gambling task compared to controls. The results indicate impulsivity is associated with FPS gaming addiction, comparable to pathological gambling. The relationship between impulsivity and excessive gaming may be unique to the FPS genre. Furthermore, regular FPS gaming may improve decision making ability.

Cluster-size entropy in the Axelrod model of social influence: small-world networks and mass media.

PubMed

Gandica, Y; Charmell, A; Villegas-Febres, J; Bonalde, I

2011-10-01

We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy S(c), which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the S(c)(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait q(c) and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

Identification of moving vehicle forces on bridge structures via moving average Tikhonov regularization

NASA Astrophysics Data System (ADS)

Pan, Chu-Dong; Yu, Ling; Liu, Huan-Lin

2017-08-01

Traffic-induced moving force identification (MFI) is a typical inverse problem in the field of bridge structural health monitoring. Lots of regularization-based methods have been proposed for MFI. However, the MFI accuracy obtained from the existing methods is low when the moving forces enter into and exit a bridge deck due to low sensitivity of structural responses to the forces at these zones. To overcome this shortcoming, a novel moving average Tikhonov regularization method is proposed for MFI by combining with the moving average concepts. Firstly, the bridge-vehicle interaction moving force is assumed as a discrete finite signal with stable average value (DFS-SAV). Secondly, the reasonable signal feature of DFS-SAV is quantified and introduced for improving the penalty function (∣∣x∣∣2 2) defined in the classical Tikhonov regularization. Then, a feasible two-step strategy is proposed for selecting regularization parameter and balance coefficient defined in the improved penalty function. Finally, both numerical simulations on a simply-supported beam and laboratory experiments on a hollow tube beam are performed for assessing the accuracy and the feasibility of the proposed method. The illustrated results show that the moving forces can be accurately identified with a strong robustness. Some related issues, such as selection of moving window length, effect of different penalty functions, and effect of different car speeds, are discussed as well.

Regular scattering patterns from near-cloaking devices and their implications for invisibility cloaking

NASA Astrophysics Data System (ADS)

Kocyigit, Ilker; Liu, Hongyu; Sun, Hongpeng

2013-04-01

In this paper, we consider invisibility cloaking via the transformation optics approach through a ‘blow-up’ construction. An ideal cloak makes use of singular cloaking material. ‘Blow-up-a-small-region’ construction and ‘truncation-of-singularity’ construction are introduced to avoid the singular structure, however, giving only near-cloaks. The study in the literature is to develop various mechanisms in order to achieve high-accuracy approximate near-cloaking devices, and also from a practical viewpoint to nearly cloak an arbitrary content. We study the problem from a different viewpoint. It is shown that for those regularized cloaking devices, the corresponding scattering wave fields due to an incident plane wave have regular patterns. The regular patterns are both a curse and a blessing. On the one hand, the regular wave pattern betrays the location of a cloaking device which is an intrinsic defect due to the ‘blow-up’ construction, and this is particularly the case for the construction by employing a high-loss layer lining. Indeed, our numerical experiments show robust reconstructions of the location, even by implementing the phaseless cross-section data. The construction by employing a high-density layer lining shows a certain promising feature. On the other hand, it is shown that one can introduce an internal point source to produce the canceling scattering pattern to achieve a near-cloak of an arbitrary order of accuracy.

Using statistical text classification to identify health information technology incidents

PubMed Central

Chai, Kevin E K; Anthony, Stephen; Coiera, Enrico; Magrabi, Farah

2013-01-01

Objective To examine the feasibility of using statistical text classification to automatically identify health information technology (HIT) incidents in the USA Food and Drug Administration (FDA) Manufacturer and User Facility Device Experience (MAUDE) database. Design We used a subset of 570 272 incidents including 1534 HIT incidents reported to MAUDE between 1 January 2008 and 1 July 2010. Text classifiers using regularized logistic regression were evaluated with both ‘balanced’ (50% HIT) and ‘stratified’ (0.297% HIT) datasets for training, validation, and testing. Dataset preparation, feature extraction, feature selection, cross-validation, classification, performance evaluation, and error analysis were performed iteratively to further improve the classifiers. Feature-selection techniques such as removing short words and stop words, stemming, lemmatization, and principal component analysis were examined. Measurements κ statistic, F1 score, precision and recall. Results Classification performance was similar on both the stratified (0.954 F1 score) and balanced (0.995 F1 score) datasets. Stemming was the most effective technique, reducing the feature set size to 79% while maintaining comparable performance. Training with balanced datasets improved recall (0.989) but reduced precision (0.165). Conclusions Statistical text classification appears to be a feasible method for identifying HIT reports within large databases of incidents. Automated identification should enable more HIT problems to be detected, analyzed, and addressed in a timely manner. Semi-supervised learning may be necessary when applying machine learning to big data analysis of patient safety incidents and requires further investigation. PMID:23666777

exVis: a visual analysis tool for wind tunnel data

NASA Astrophysics Data System (ADS)

Deardorff, D. G.; Keeley, Leslie E.; Uselton, Samuel P.

1998-05-01

exVis is a software tool created to support interactive display and analysis of data collected during wind tunnel experiments. It is a result of a continuing project to explore the uses of information technology in improving the effectiveness of aeronautical design professionals. The data analysis goals are accomplished by allowing aerodynamicists to display and query data collected by new data acquisition systems and to create traditional wind tunnel plots from this data by interactively interrogating these images. exVis was built as a collection of distinct modules to allow for rapid prototyping, to foster evolution of capabilities, and to facilitate object reuse within other applications being developed. It was implemented using C++ and Open Inventor, commercially available object-oriented tools. The initial version was composed of three main classes. Two of these modules are autonomous viewer objects intended to display the test images (ImageViewer) and the plots (GraphViewer). The third main class is the Application User Interface (AUI) which manages the passing of data and events between the viewers, as well as providing a user interface to certain features. User feedback was obtained on a regular basis, which allowed for quick revision cycles and appropriately enhanced feature sets. During the development process additional classes were added, including a color map editor and a data set manager. The ImageViewer module was substantially rewritten to add features and to use the data set manager. The use of an object-oriented design was successful in allowing rapid prototyping and easy feature addition.

Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial.

PubMed

Peikert, Tobias; Duan, Fenghai; Rajagopalan, Srinivasan; Karwoski, Ronald A; Clay, Ryan; Robb, Richard A; Qin, Ziling; Sicks, JoRean; Bartholmai, Brian J; Maldonado, Fabien

2018-01-01

Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with P<0.01. The optimism-corrected AUC for these 8 features is 0.939. Our novel radiomic LDCT-based approach for indeterminate screen-detected nodule characterization appears extremely promising however independent external validation is needed.

Quantitative Susceptibility Mapping using Structural Feature based Collaborative Reconstruction (SFCR) in the Human Brain

PubMed Central

Cai, Congbo; Chen, Zhong; van Zijl, Peter C.M.

2017-01-01

The reconstruction of MR quantitative susceptibility mapping (QSM) from local phase measurements is an ill posed inverse problem and different regularization strategies incorporating a priori information extracted from magnitude and phase images have been proposed. However, the anatomy observed in magnitude and phase images does not always coincide spatially with that in susceptibility maps, which could give erroneous estimation in the reconstructed susceptibility map. In this paper, we develop a structural feature based collaborative reconstruction (SFCR) method for QSM including both magnitude and susceptibility based information. The SFCR algorithm is composed of two consecutive steps corresponding to complementary reconstruction models, each with a structural feature based l1 norm constraint and a voxel fidelity based l2 norm constraint, which allows both the structure edges and tiny features to be recovered, whereas the noise and artifacts could be reduced. In the M-step, the initial susceptibility map is reconstructed by employing a k-space based compressed sensing model incorporating magnitude prior. In the S-step, the susceptibility map is fitted in spatial domain using weighted constraints derived from the initial susceptibility map from the M-step. Simulations and in vivo human experiments at 7T MRI show that the SFCR method provides high quality susceptibility maps with improved RMSE and MSSIM. Finally, the susceptibility values of deep gray matter are analyzed in multiple head positions, with the supine position most approximate to the gold standard COSMOS result. PMID:27019480

Between disorder and order: A case study of power law

NASA Astrophysics Data System (ADS)

Cao, Yong; Zhao, Youjie; Yue, Xiaoguang; Xiong, Fei; Sun, Yongke; He, Xin; Wang, Lichao

2016-08-01

Power law is an important feature of phenomena in long memory behaviors. Zipf ever found power law in the distribution of the word frequencies. In physics, the terms order and disorder are Thermodynamic or statistical physics concepts originally and a lot of research work has focused on self-organization of the disorder ingredients of simple physical systems. It is interesting what make disorder-order transition. We devise an experiment-based method about random symbolic sequences to research regular pattern between disorder and order. The experiment results reveal power law is indeed an important regularity in transition from disorder to order. About these results the preliminary study and analysis has been done to explain the reasons.

Machine Learning Topological Invariants with Neural Networks

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Shen, Huitao; Zhai, Hui

2018-02-01

In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.

Elastic amplitudes studied with the LHC measurements at 7 and 8 TeV

NASA Astrophysics Data System (ADS)

Kohara, A. K.; Ferreira, E.; Kodama, T.; Rangel, M.

2017-12-01

Recent measurements of the differential cross sections in the forward region of pp elastic scattering at 7 and 8 TeV show the precise form of the t dependence. We present a detailed analysis of these measurements including the structures of the real and imaginary parts of the scattering amplitude. A good description is achieved, confirming in all experiments the existence of a zero in the real part in the forward region close to the origin, in agreement with the prediction of a theorem by Martin, with an important role in the observed form of dσ /dt. A universal value for the position of this zero and regularity in other features of the amplitudes are found, leading to quantitative predictions for the forward elastic scattering at 13 TeV.

Wood anatomy of tribe Detarieae and comparison with tribe Caesalpinieae (Leguminosae, Caesalpinioideae) in Venezuela.

PubMed

Melandri, José Luis; de Pernía, Narcisana Espinoza

2009-01-01

We studied the wood anatomy of 29 species belonging to 10 genera of the tribe Detarieae, subfamily Caesalpinioideae and compare them with tribe Caesalpinieae. Detarieae is the largest of four tribes of Caesalpinioideae, with 84 genera, only eleven occur in Venezuela with species of timber importance. The specimens were collected in Venezuela and include wood samples from the collection of the Laboratorio de Anatomía de Maderas de la Facultad de Ciencias Forestales y Ambientales de la Universidad de Los Andes, Venezuela, and of the Forest Products Laboratory of the USDA Forest Service in Madison, Wisconsin, USA. The terminology and methodology used followed the IAWA List of Microscopic Features for Hardwood Identification of the IAWA Committee, 1989. Measurements from each specimen were averaged (vessel diameters, vessel element lengths, intervessels pit size, fibre lengths and ray height). The species of Detarieae can be separated using a combination of diagnostic features. Wood characters that provide the most important diagnosis and may be used in systematics of Detarieae include: intercellular axial canals, rays heterocellular, rays exclusively or predominantly uniseriate, prismatic crystals common in ray cells, irregular storied structure and fibre wall thickness. For comparative anatomy between Detarieae and Caesalpinieae: intercellular axial canals, heterocellular rays, rays exclusively or predominantly uniseriate, prismatic crystals common in ray cells (in Detarieae) and regular storied structure, fibres septate, fibre wall thick or very thick, rays homocellular, multiseriate rays and silica bodies (in Caesalpinieae). Axial parenchyma is typically a good diagnostic feature for Leguminosae, but not for Detarieae and Caesalpinieae comparisons.

Slice regular functions of several Clifford variables

NASA Astrophysics Data System (ADS)

Ghiloni, R.; Perotti, A.

2012-11-01

We introduce a class of slice regular functions of several Clifford variables. Our approach to the definition of slice functions is based on the concept of stem functions of several variables and on the introduction on real Clifford algebras of a family of commuting complex structures. The class of slice regular functions include, in particular, the family of (ordered) polynomials in several Clifford variables. We prove some basic properties of slice and slice regular functions and give examples to illustrate this function theory. In particular, we give integral representation formulas for slice regular functions and a Hartogs type extension result.

Combined rule extraction and feature elimination in supervised classification.

PubMed

Liu, Sheng; Patel, Ronak Y; Daga, Pankaj R; Liu, Haining; Fu, Gang; Doerksen, Robert J; Chen, Yixin; Wilkins, Dawn E

2012-09-01

There are a vast number of biology related research problems involving a combination of multiple sources of data to achieve a better understanding of the underlying problems. It is important to select and interpret the most important information from these sources. Thus it will be beneficial to have a good algorithm to simultaneously extract rules and select features for better interpretation of the predictive model. We propose an efficient algorithm, Combined Rule Extraction and Feature Elimination (CRF), based on 1-norm regularized random forests. CRF simultaneously extracts a small number of rules generated by random forests and selects important features. We applied CRF to several drug activity prediction and microarray data sets. CRF is capable of producing performance comparable with state-of-the-art prediction algorithms using a small number of decision rules. Some of the decision rules are biologically significant.

End-stage renal disease in Taiwan: a case-control study.

PubMed

Tsai, Su-Ying; Tseng, Hung-Fu; Tan, Hsiu-Fen; Chien, Yu-Shu; Chang, Chia-Chu

2009-01-01

Taiwan has the highest incidence of end-stage renal disease (ESRD) in the world. The epidemiologic features of ESRD, however, have not been investigated. In this case-control study, we evaluated the risk of ESRD associated with a number of putative risk factors. We studied 200 patients among whom ESRD had been newly diagnosed between 1 January 2005 and 31 December 2005; 200 controls were selected from among relatives of patients treated in the general surgery unit. Using a structured questionnaire, we collected information related to socioeconomic factors, history of disease, regular blood or urine screening, lifestyle, environmental exposure, consumption of vitamin supplements, and regular drug use at 5 years before disease onset. Our primary multivariate risk models indicated that low socioeconomic status was a strong predictor of ESRD (education: odds ratio [OR], 2.78; 95% confidence interval [CI], 1.49-5.19; income: OR, 2.86, 95% CI, 1.48-5.52), even after adjusting for other risk factors. Other significant predictors for ESRD were a history of hypertension (OR, 3.63-3.90), history of diabetes (OR, 3.85-5.50), and regular intake of folk remedies or over-the-counter Chinese herbs (OR, 10.84-12.51). Regular intake of a multivitamin supplement 5 years before diagnosis was associated with a decreased risk of ESRD (OR, 0.12-0.14). Our findings indicate that low socioeconomic status, history of hypertension, diabetes, and regular use of folk remedies or over-the-counter Chinese herbs were significant risk factors for ESRD, while regular intake of a multivitamin supplement was associated with a decreased risk of ESRD.

The Production and Perception of Emotionally Expressive Walking Sounds: Similarities between Musical Performance and Everyday Motor Activity

PubMed Central

Giordano, Bruno L.; Egermann, Hauke; Bresin, Roberto

2014-01-01

Several studies have investigated the encoding and perception of emotional expressivity in music performance. A relevant question concerns how the ability to communicate emotions in music performance is acquired. In accordance with recent theories on the embodiment of emotion, we suggest here that both the expression and recognition of emotion in music might at least in part rely on knowledge about the sounds of expressive body movements. We test this hypothesis by drawing parallels between musical expression of emotions and expression of emotions in sounds associated with a non-musical motor activity: walking. In a combined production-perception design, two experiments were conducted, and expressive acoustical features were compared across modalities. An initial performance experiment tested for similar feature use in walking sounds and music performance, and revealed that strong similarities exist. Features related to sound intensity, tempo and tempo regularity were identified as been used similarly in both domains. Participants in a subsequent perception experiment were able to recognize both non-emotional and emotional properties of the sound-generating walkers. An analysis of the acoustical correlates of behavioral data revealed that variations in sound intensity, tempo, and tempo regularity were likely used to recognize expressed emotions. Taken together, these results lend support the motor origin hypothesis for the musical expression of emotions. PMID:25551392

Aesthetic and Emotional Effects of Meter and Rhyme in Poetry

PubMed Central

Obermeier, Christian; Menninghaus, Winfried; von Koppenfels, Martin; Raettig, Tim; Schmidt-Kassow, Maren; Otterbein, Sascha; Kotz, Sonja A.

2013-01-01

Metrical patterning and rhyme are frequently employed in poetry but also in infant-directed speech, play, rites, and festive events. Drawing on four line-stanzas from nineteenth and twentieth German poetry that feature end rhyme and regular meter, the present study tested the hypothesis that meter and rhyme have an impact on aesthetic liking, emotional involvement, and affective valence attributions. Hypotheses that postulate such effects have been advocated ever since ancient rhetoric and poetics, yet they have barely been empirically tested. More recently, in the field of cognitive poetics, these traditional assumptions have been readopted into a general cognitive framework. In the present experiment, we tested the influence of meter and rhyme as well as their interaction with lexicality in the aesthetic and emotional perception of poetry. Participants listened to stanzas that were systematically modified with regard to meter and rhyme and rated them. Both rhyme and regular meter led to enhanced aesthetic appreciation, higher intensity in processing, and more positively perceived and felt emotions, with the latter finding being mediated by lexicality. Together these findings clearly show that both features significantly contribute to the aesthetic and emotional perception of poetry and thus confirm assumptions about their impact put forward by cognitive poetics. The present results are explained within the theoretical framework of cognitive fluency, which links structural features of poetry with aesthetic and emotional appraisal. PMID:23386837

Monitoring of the Crab Nebula with Chandra and Other Observatories Including HST

NASA Technical Reports Server (NTRS)

Weisskopf, Martin C.

2014-01-01

Subsequent to the detections AGILE and Fermi/LAT of the gamma-ray flares from the Crab Nebula in the fall of 2010, this team has been monitoring the X-Ray emission from the Crab on a regular basis. X-Ray observations have taken place typically once per month when viewing constraints allow and more recently four times per year. There have been notable exceptions, e.g. in April of 2011 and March 2013 when we initiated a set of Chandra Target of opportunity observations in conjunction with bright gamma-ray flares. For much of the time regular HST observations were made in conjunction with the Chandra observations. The aim of this program to further characterize, in depth, the X-Ray and optical variations that take place in the nebula, and by so doing determine the regions which contribute to the harder X-ray variations and, if possible, determine the precise location within the Nebula of the origin of the gamma-ray flares. As part of this project members of the team have developed Singular Value Decomposition techniques to sequences of images in order to more accurately characterize features. The current status of the project will be presented highlighting studies of the inner knot and possible correlations with the flares.

Successful treatment of groin pain syndrome in a pole-vault athlete with core stability exercise.

PubMed

Dello Iacono, Antonio; Maffulli, Nicola; Laver, Lior; Padulo, Johnny

2017-12-01

The purpose of this case report was to present a case of groin pain in a pole vault athlete describing the biomechanical features of the injury`s mechanism, acute medical management, and its successful rehabilitation. A 22-year-old professional pole-vaulter sustained an injury during a regular training session. The athlete reported significant left lower abdominal and left proximal adductor discomfort in all activities, including basic trunk motion when moving in bed, sit to stand, and walking, and was unable to return to the regular training. Clinical evaluation and imaging studies addressed the injury to a case of adductor-related groin pain associated with pubic symphysis degeneration. Treatment consisted of an exercise-based therapeutic protocol based on trunk and core muscle strengthening and stability program, with progressive motor and functional demands. Significant improvements in the overall clinical findings and functional outcomes were reported after 52 days of intervention when the athletes returned to his full athletic activity. These results suggest that an appropriate rehabilitation program, focused on trunk and core musculature stability exercise addressing to sport-related specific demands, should be considered as an optimal conservative method in the multidisciplinary approach for treatment of groin pain and prior to any surgical intervention.

Reconfigurable optical implementation of quantum complex networks

NASA Astrophysics Data System (ADS)

Nokkala, J.; Arzani, F.; Galve, F.; Zambrini, R.; Maniscalco, S.; Piilo, J.; Treps, N.; Parigi, V.

2018-05-01

Network theory has played a dominant role in understanding the structure of complex systems and their dynamics. Recently, quantum complex networks, i.e. collections of quantum systems arranged in a non-regular topology, have been theoretically explored leading to significant progress in a multitude of diverse contexts including, e.g., quantum transport, open quantum systems, quantum communication, extreme violation of local realism, and quantum gravity theories. Despite important progress in several quantum platforms, the implementation of complex networks with arbitrary topology in quantum experiments is still a demanding task, especially if we require both a significant size of the network and the capability of generating arbitrary topology—from regular to any kind of non-trivial structure—in a single setup. Here we propose an all optical and reconfigurable implementation of quantum complex networks. The experimental proposal is based on optical frequency combs, parametric processes, pulse shaping and multimode measurements allowing the arbitrary control of the number of the nodes (optical modes) and topology of the links (interactions between the modes) within the network. Moreover, we also show how to simulate quantum dynamics within the network combined with the ability to address its individual nodes. To demonstrate the versatility of these features, we discuss the implementation of two recently proposed probing techniques for quantum complex networks and structured environments.

Image superresolution by midfrequency sparse representation and total variation regularization

NASA Astrophysics Data System (ADS)

Xu, Jian; Chang, Zhiguo; Fan, Jiulun; Zhao, Xiaoqiang; Wu, Xiaomin; Wang, Yanzi

2015-01-01

Machine learning has provided many good tools for superresolution, whereas existing methods still need to be improved in many aspects. On one hand, the memory and time cost should be reduced. On the other hand, the step edges of the results obtained by the existing methods are not clear enough. We do the following work. First, we propose a method to extract the midfrequency features for dictionary learning. This method brings the benefit of a reduction of the memory and time complexity without sacrificing the performance. Second, we propose a detailed wiping-off total variation (DWO-TV) regularization model to reconstruct the sharp step edges. This model adds a novel constraint on the downsampling version of the high-resolution image to wipe off the details and artifacts and sharpen the step edges. Finally, step edges produced by the DWO-TV regularization and the details provided by learning are fused. Experimental results show that the proposed method offers a desirable compromise between low time and memory cost and the reconstruction quality.

Examining the Relationship Between Soda Consumption and Eating Disorder Pathology

PubMed Central

Bragg, M.A.; White, M. A.

2013-01-01

Objective This study aimed to compare diet soda drinkers, regular soda drinkers, and individuals who do not regularly consume soda on clinically significant eating disorder psychopathology, including binge eating, overeating, and purging. Method Participants (n=2077) were adult community volunteers who completed an online survey that included the Eating Disorder Examination Questionnaire and questions regarding binge eating behaviors, purging, current weight status, and the type and frequency of soda beverages consumed. Results Diet soda drinkers (34%, n=706) reported significantly higher levels of eating, shape, and weight concerns than regular soda drinkers (22%, n=465), who in turn reported higher levels on these variables than non-soda drinkers (44%, n=906). Diet soda drinkers were more likely to report binge eating and purging than regular soda drinkers, who were more likely to report these behaviors than non-soda drinkers. Consumption of any soda was positively associated with higher BMI, though individuals who consumed regular soda reported significantly higher BMI than diet soda drinkers, who in turn reported higher weight than those who do not consume soda regularly. Conclusions Individuals who consume soda regularly reported higher BMI and more eating psychopathology than those who do not consume soda. These findings extend previous research demonstrating positive associations between soda consumption and weight. PMID:24167775

The impact of the inclusion of students with handicaps and disabilities in the regular education science classroom

NASA Astrophysics Data System (ADS)

Donald, Cathey Nolan

This study was conducted to determine the impact of the inclusion of students with handicaps and disabilities in the regular education science classroom. Surveys were mailed to the members of the Alabama Science Teachers Association to obtain information from teachers in inclusive classrooms. Survey responses from teachers provide insight into these classrooms. This study reports the results of the teachers surveyed. Results indicate multiple changes occur in the educational opportunities presented to regular education students when students with handicaps and disabilities are included in the regular science classroom. Responding teachers (60%) report omitting activities that formerly provided experiences for students, such as laboratory activities using dangerous materials, field activities, and some group activities. Also omitted, in many instances (64.1%), are skill building opportunities of word problems and higher order thinking skills. Regular education students participate in classes where discipline problems related to included students are reported as the teachers most time consuming task. In these classrooms, directions are repeated frequently, reteaching of material already taught occurs, and the pace of instruction has been slowed. These changes to the regular classroom occur across school levels. Many teachers (44.9%) report they do not see benefits associated with the inclusion of students with special needs in the regular classroom.

Condition Number Regularized Covariance Estimation*

PubMed Central

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2012-01-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197

Condition Number Regularized Covariance Estimation.

PubMed

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2013-06-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n " setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.

Nonlinear Dynamics, Poor Data, and What to Make of Them?

NASA Astrophysics Data System (ADS)

Ghil, M.; Zaliapin, I. V.

2005-12-01

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict variability in the geosciences. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this talk we will describe the connections between time series analysis and nonlinear dynamics, discuss signal-to-noise enhancement, and present some of the novel methods for spectral analysis. These fall into two broad categories: (i) methods that try to ferret out regularities of the time series; and (ii) methods aimed at describing the characteristics of irregular processes. The former include singular-spectrum analysis (SSA), the multi-taper method (MTM), and the maximum-entropy method (MEM). The various steps, as well as the advantages and disadvantages of these methods, will be illustrated by their application to several important climatic time series, such as the Southern Oscillation Index (SOI), paleoclimatic time series, and instrumental temperature time series. The SOI index captures major features of interannual climate variability and is used extensively in its prediction. The other time series cover interdecadal and millennial time scales. The second category includes the calculation of fractional dimension, leading Lyapunov exponents, and Hurst exponents. More recently, multi-trend analysis (MTA), binary-decomposition analysis (BDA), and related methods have attempted to describe the structure of time series that include both regular and irregular components. Within the time available, I will try to give a feeling for how these methods work, and how well.

Factors associated with a continuous regular analgesic use - a population-based study of more than 45,000 Danish women and men 18-45 years of age.

PubMed

Hargreave, Marie; Andersen, Tina Veje; Nielsen, Ann; Munk, Christian; Liaw, Kai-Li; Kjaer, Susanne K

2010-01-01

Widespread use of and serious adverse effects associated with use of analgesics accentuates the need to consider factors related to analgesic use. The objective of this study was to describe continuous regular analgesics use and examine factors associated with a continuous regular analgesic use. The study was based on data from two surveys and included a random sample of women and men aged 18-45 years from the general Danish population. Information on analgesics use, self-rated health, demographic and lifestyle factors was collected using a self-administered questionnaire. A total of 28,000 women and 33 000 men were invited to participate and 22,199 women (response-rate 81.4%) and 23,080 men (response-rate 71.0%), respectively, were included in the study. Data were analyzed using multivariate logistic regression. We found that 27% of the women and 18% of the men reported a regular monthly use of at least seven analgesic tablets during the last year (continuous regular analgesics use). Besides poor self-rated health we found in both sexes that increasing age, poor self-rated fitness, and smoking were related to a continuous regular analgesics use. Nulliparity, low level of education, overweight/obesity, binge drinking, and abstinence were associated with a continuous regular analgesics use for women, while underweight and marital/cohabiting status were associated with a continuous regular analgesics use only for men. Regular monthly analgesic use during the last year was generally prevalent. Besides self-rated health, several socio-demographic and lifestyle factors were associated with a continuous regular analgesic use, although with some gender differences.

Development of Spelling Skills in a Shallow Orthography: The Case of Italian Language

ERIC Educational Resources Information Center

Notarnicola, Alessandra; Angelelli, Paola; Judica, Anna; Zoccolotti, Pierluigi

2012-01-01

This study analyzed the spelling skills of Italian children as a function of school experience. We examined the writing performances of 465 first- to eighth-grade normal readers on a spelling test that included regular words, context-sensitive regular words, words with ambiguous transcription, and regular pseudowords. Based on the dual-route model…

A system for tracking and recognizing pedestrian faces using a network of loosely coupled cameras

NASA Astrophysics Data System (ADS)

Gagnon, L.; Laliberté, F.; Foucher, S.; Branzan Albu, A.; Laurendeau, D.

2006-05-01

A face recognition module has been developed for an intelligent multi-camera video surveillance system. The module can recognize a pedestrian face in terms of six basic emotions and the neutral state. Face and facial features detection (eyes, nasal root, nose and mouth) are first performed using cascades of boosted classifiers. These features are used to normalize the pose and dimension of the face image. Gabor filters are then sampled on a regular grid covering the face image to build a facial feature vector that feeds a nearest neighbor classifier with a cosine distance similarity measure for facial expression interpretation and face model construction. A graphical user interface allows the user to adjust the module parameters.

Thermodynamics of a class of regular black holes with a generalized uncertainty principle

NASA Astrophysics Data System (ADS)

Maluf, R. V.; Neves, Juliano C. S.

2018-05-01

In this article, we present a study on thermodynamics of a class of regular black holes. Such a class includes Bardeen and Hayward regular black holes. We obtained thermodynamic quantities like the Hawking temperature, entropy, and heat capacity for the entire class. As part of an effort to indicate some physical observable to distinguish regular black holes from singular black holes, we suggest that regular black holes are colder than singular black holes. Besides, contrary to the Schwarzschild black hole, that class of regular black holes may be thermodynamically stable. From a generalized uncertainty principle, we also obtained the quantum-corrected thermodynamics for the studied class. Such quantum corrections provide a logarithmic term for the quantum-corrected entropy.

34 CFR 690.8 - Enrollment status for students taking regular and correspondence courses.

Code of Federal Regulations, 2010 CFR

2010-07-01

... No. of credit hours regular work No. of credit hours correspondence Total course load in credit hours... institution, the correspondence work may be included in determining the student's enrollment status to the... section, the correspondence work that may be included in determining a student's enrollment status is that...

Temporality of Features in Near-Death Experience Narratives

PubMed Central

Martial, Charlotte; Cassol, Héléna; Antonopoulos, Georgios; Charlier, Thomas; Heros, Julien; Donneau, Anne-Françoise; Charland-Verville, Vanessa; Laureys, Steven

2017-01-01

Background: After an occurrence of a Near-Death Experience (NDE), Near-Death Experiencers (NDErs) usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area. Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives) as well as the most frequently reported temporality sequences of features. Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32). A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features. Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs. Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon. PMID:28659779

Temporality of Features in Near-Death Experience Narratives.

PubMed

Martial, Charlotte; Cassol, Héléna; Antonopoulos, Georgios; Charlier, Thomas; Heros, Julien; Donneau, Anne-Françoise; Charland-Verville, Vanessa; Laureys, Steven

2017-01-01

Background: After an occurrence of a Near-Death Experience (NDE), Near-Death Experiencers (NDErs) usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area. Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives) as well as the most frequently reported temporality sequences of features. Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32). A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features. Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs. Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon.

ADAPTIVE FINITE ELEMENT MODELING TECHNIQUES FOR THE POISSON-BOLTZMANN EQUATION

PubMed Central

HOLST, MICHAEL; MCCAMMON, JAMES ANDREW; YU, ZEYUN; ZHOU, YOUNGCHENG; ZHU, YUNRONG

2011-01-01

We consider the design of an effective and reliable adaptive finite element method (AFEM) for the nonlinear Poisson-Boltzmann equation (PBE). We first examine the two-term regularization technique for the continuous problem recently proposed by Chen, Holst, and Xu based on the removal of the singular electrostatic potential inside biomolecules; this technique made possible the development of the first complete solution and approximation theory for the Poisson-Boltzmann equation, the first provably convergent discretization, and also allowed for the development of a provably convergent AFEM. However, in practical implementation, this two-term regularization exhibits numerical instability. Therefore, we examine a variation of this regularization technique which can be shown to be less susceptible to such instability. We establish a priori estimates and other basic results for the continuous regularized problem, as well as for Galerkin finite element approximations. We show that the new approach produces regularized continuous and discrete problems with the same mathematical advantages of the original regularization. We then design an AFEM scheme for the new regularized problem, and show that the resulting AFEM scheme is accurate and reliable, by proving a contraction result for the error. This result, which is one of the first results of this type for nonlinear elliptic problems, is based on using continuous and discrete a priori L∞ estimates to establish quasi-orthogonality. To provide a high-quality geometric model as input to the AFEM algorithm, we also describe a class of feature-preserving adaptive mesh generation algorithms designed specifically for constructing meshes of biomolecular structures, based on the intrinsic local structure tensor of the molecular surface. All of the algorithms described in the article are implemented in the Finite Element Toolkit (FETK), developed and maintained at UCSD. The stability advantages of the new regularization scheme are demonstrated with FETK through comparisons with the original regularization approach for a model problem. The convergence and accuracy of the overall AFEM algorithm is also illustrated by numerical approximation of electrostatic solvation energy for an insulin protein. PMID:21949541

Educational Aspirations of Survivors of the 1984 Anti-Sikh Violence in Delhi

ERIC Educational Resources Information Center

Agarwal, Yamini

2017-01-01

Violent conflicts are becoming a regular feature across the world. Studies have pointed to the impact they have on the education of young survivors. But education appears in these studies as an instrument of integration. They overlook the processes both within and outside schools that affect the educational lives of young survivors. This article…

"That Tricky Subject": The Integration of Contextual Studies in Pre-Degree Art and Design Education

ERIC Educational Resources Information Center

Rintoul, Jenny; James, David

2017-01-01

Contextual studies (CS), "theory", "visual culture" or "art history" (amongst other labels) refer to a regular and often compulsory feature in art and design education. However, this takes many forms and can sit in a variety of relationships with the practical elements of such courses. This article is based on mixed…

The Evolution of Technology: A Decade of Surfing the Net

ERIC Educational Resources Information Center

Berger, Sandra

2005-01-01

The world was a different place when "Understanding Our Gifted" introduced "Surfing the Net" in 1994 as a regular feature. Since then, technology and the Internet have become part of people's culture, permeating almost every aspect of their lives. The Internet has greatly changed the way they conduct business and communicate with friends, it helps…

Singular optimal control and the identically non-regular problem in the calculus of variations

NASA Technical Reports Server (NTRS)

Menon, P. K. A.; Kelley, H. J.; Cliff, E. M.

1985-01-01

A small but interesting class of optimal control problems featuring a scalar control appearing linearly is equivalent to the class of identically nonregular problems in the Calculus of Variations. It is shown that a condition due to Mancill (1950) is equivalent to the generalized Legendre-Clebsch condition for this narrow class of problems.

The Development of Education in Venezuela. Bulletin, 1963, No. 7. OE-14086

ERIC Educational Resources Information Center

Sanchez, George I.

1963-01-01

The present study is one of the regular series of Office of Education bulletins presenting salient features and analysis of the educational systems of other countries. Such studies in the field of comparative education are designed to serve educators, educational institutions and organizations concerned with the planning and conduct of programs in…

Physical Problems Associated with Computer Use and Implemented Ergonomic Measures.

ERIC Educational Resources Information Center

Alexander, Melody A.

1994-01-01

Survey responses from 404 (of 523) office support personnel showed that most used computers 3-6 hours per day and had experienced vision or musculoskeletal problems, but most did not see a doctor, take regular breaks, do stretching exercises, or discuss problems with their supervisors. Many were not aware of ergonomic features that could help, and…

Investigating a Nigerian XXL-Cohort Wiki-Learning Experience: Observation, Feedback and Reflection

ERIC Educational Resources Information Center

Aborisade, Peter

2009-01-01

A regular feature of the Nigerian tertiary education context is large numbers of students crammed into small classrooms or lecture theatres. This context had long begged for the creation of innovative learning spaces and adoption of engaging pedagogies. Recourse to technology support and experimenting with the WIKI as a learning tool at the…

Introducing Adaptivity Features to a Regular Learning Management System to Support Creation of Advanced eLessons

ERIC Educational Resources Information Center

Komlenov, Zivana; Budimac, Zoran; Ivanovic, Mirjana

2010-01-01

In order to improve the learning process for students with different pre-knowledge, personal characteristics and preferred learning styles, a certain degree of adaptability must be introduced to online courses. In learning environments that support such kind of functionalities students can explicitly choose different paths through course contents…

On Periodicity of Trigonometric Functions and Connections with Elementary Number Theoretic Ideas

ERIC Educational Resources Information Center

Stupel, Moshe

2012-01-01

The notion of periodicity stands for regular recurrence of phenomena in a particular order in nature or in the actions of man, machine, etc. Many examples can be given from daily life featuring periodicity. Mathematically the meaning of periodicity is that some value recurs with a constant frequency. Students learn about the periodicity of the…

Resource Room Model for Inclusive Education in China: Practitioners' Conceptualisation and Contextualisation

ERIC Educational Resources Information Center

Poon-McBrayer, Kim Fong

2016-01-01

China launched the "learning in a regular classroom" (LRC) model for inclusive education in the 1980s. In late 1990s, a few major cities of China began to adopt the resource room model as a key feature of the LRC to improve instructional qualities. This exploratory study examined resource teachers' (RTs) attitude towards inclusive…

Thinking Locally: Attending to Social Context in Studies of Marketing and Public Education

ERIC Educational Resources Information Center

Cucchiara, Maia

2016-01-01

A generation ago, billboards, flyers, or radio spots advertising a public school would have been unusual and surprising. Now they are an increasingly regular feature of the educational landscape. As schools compete for students and resources in the new educational marketplace, they increasingly look to market themselves to prospective parents (and…

International Trends in Health Science Librarianship Part 20: The Balkan States (Serbia and Slovenia).

PubMed

Ivkovic, Ana; Rožić, Anamarija; Turk, Nana

2016-12-01

This is the 20th in a series of articles exploring international trends in health science librarianship in the 21st century. The focus of the present issue is the Balkan region (Serbia and Slovenia). The next regular feature will look at Russia and the Ukraine. JM. © 2016 Health Libraries Group.

Ways to Promote the Positive Development of Children and Youth. Research-to-Results Brief. Publication #2008-11

ERIC Educational Resources Information Center

Zarrett, Nicole; Lerner, Richard M.

2008-01-01

This brief discusses the elements and features that define positive youth development and highlights some ways to support the positive development of children and youth. Specifically, this brief addresses the critical role that particular out-of-school time settings (regular family dinners and organized activity programs) can play in supporting…

Market Dynamics and Optimal Timber Salvage After a Natural Catastrophe

Treesearch

Jeffrey P. Prestemon; Thomas P. Holmes

2004-01-01

Forest-based natural catastrophes are regular features of timber production in the United States, especially from hurricanes, fires, and insect and disease outbreaks. These catastrophes affect timber prices and result in economic transfers. We develop a model of timber market dynamics after such a catastrophe that shows how timber salvage affects the welfare of...

Establishing a learning foundation in a dynamically changing world: Insights from artificial language work

NASA Astrophysics Data System (ADS)

Gonzales, Kalim

It is argued that infants build a foundation for learning about the world through their incidental acquisition of the spatial and temporal regularities surrounding them. A challenge is that learning occurs across multiple contexts whose statistics can greatly differ. Two artificial language studies with 12-month-olds demonstrate that infants come prepared to parse statistics across contexts using the temporal and perceptual features that distinguish one context from another. These results suggest that infants can organize their statistical input with a wider range of features that typically considered. Possible attention, decision making, and memory mechanisms are discussed.

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

Theiler, James; Grosklos, Guen

We examine the properties and performance of kernelized anomaly detectors, with an emphasis on the Mahalanobis-distance-based kernel RX (KRX) algorithm. Although the detector generally performs well for high-bandwidth Gaussian kernels, it exhibits problematic (in some cases, catastrophic) performance for distances that are large compared to the bandwidth. By comparing KRX to two other anomaly detectors, we can trace the problem to a projection in feature space, which arises when a pseudoinverse is used on the covariance matrix in that feature space. Here, we show that a regularized variant of KRX overcomes this difficulty and achieves superior performance over a widemore » range of bandwidths.« less

[Formation of individual somatotype parameters and features of constitutional organization in 7-12-year-old boys (longitudinal)].

PubMed

Kornienko, I A; Panasiuk, T V; Tambovtseva, R V

1997-01-01

Individual somatotype parameters and peculiarities of constitution in 7-12 years boys were evaluated in the present investigation. The age range studied was shown to be divided on 3 stages. Regular growth processes with the prevalence of "infantal" proportions occur at the age of 7-9. Signs of definite constitutional type are expressed yet insufficiently. The age of 10-11 is transitional which shows in delay of muscle growth. At the age of 11-12 prepubescent sets in, during which features of constitution types and appropriate somatotype parameters are distinctly manifested.

Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression.

PubMed

Malki, Karim; Tosto, Maria Grazia; Mouriño-Talín, Héctor; Rodríguez-Lorenzo, Sabela; Pain, Oliver; Jumhaboy, Irfan; Liu, Tina; Parpas, Panos; Newman, Stuart; Malykh, Artem; Carboni, Lucia; Uher, Rudolf; McGuffin, Peter; Schalkwyk, Leonard C; Bryson, Kevin; Herbster, Mark

2017-04-01

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Social coordination in animal vocal interactions. Is there any evidence of turn-taking? The starling as an animal model

PubMed Central

Henry, Laurence; Craig, Adrian J. F. K.; Lemasson, Alban; Hausberger, Martine

2015-01-01

Turn-taking in conversation appears to be a common feature in various human cultures and this universality raises questions about its biological basis and evolutionary trajectory. Functional convergence is a widespread phenomenon in evolution, revealing sometimes striking functional similarities between very distant species even though the mechanisms involved may be different. Studies on mammals (including non-human primates) and bird species with different levels of social coordination reveal that temporal and structural regularities in vocal interactions may depend on the species' social structure. Here we test the hypothesis that turn-taking and associated rules of conversations may be an adaptive response to the requirements of social life, by testing the applicability of turn-taking rules to an animal model, the European starling. Birdsong has for many decades been considered as one of the best models of human language and starling songs have been well described in terms of vocal production and perception. Starlings do have vocal interactions where alternating patterns predominate. Observational and experimental data on vocal interactions reveal that (1) there are indeed clear temporal and structural regularities, (2) the temporal and structural patterning is influenced by the immediate social context, the general social situation, the individual history, and the internal state of the emitter. Comparison of phylogenetically close species of Sturnids reveals that the alternating pattern of vocal interactions varies greatly according to the species' social structure, suggesting that interactional regularities may have evolved together with social systems. These findings lead to solid bases of discussion on the evolution of communication rules in relation to social evolution. They will be discussed also in terms of processes, at the light of recent neurobiological findings. PMID:26441787

Residual mercury content and leaching of mercury and silver from used amalgam capsules.

PubMed

Stone, M E; Pederson, E D; Cohen, M E; Ragain, J C; Karaway, R S; Auxer, R A; Saluta, A R

2002-06-01

The objective of this investigation was to carry out residual mercury (Hg) determinations and toxicity characteristic leaching procedure (TCLP) analysis of used amalgam capsules. For residual Hg analysis, 25 capsules (20 capsules for one brand) from each of 10 different brands of amalgam were analyzed. Total residual Hg levels per capsule were determined using United States Environmental Protection Agency (USEPA) Method 7471. For TCLP analysis, 25 amalgam capsules for each of 10 brands were extracted using a modification of USEPA Method 1311. Hg analysis of the TCLP extracts was done with USEPA Method 7470A. Analysis of silver (Ag) concentrations in the TCLP extract was done with USEPA Method 6010B. Analysis of the residual Hg data resulted in the segregation of brands into three groups: Dispersalloy capsules, Group A, retained the most Hg (1.225 mg/capsule). These capsules were the only ones to include a pestle. Group B capsules, Valliant PhD, Optaloy II, Megalloy and Valliant Snap Set, retained the next highest amount of Hg (0.534-0.770 mg/capsule), and were characterized by a groove in the inside of the capsule. Group C, Tytin regular set double-spill, Tytin FC, Contour, Sybraloy regular set, and Tytin regular set single-spill retained the least amount of Hg (0.125-0.266 mg/capsule). TCLP analysis of the triturated capsules showed Sybraloy and Contour leached Hg at greater than the 0.2 mg/l Resource Conservation and Recovery Act (RCRA) limit. This study demonstrated that residual mercury may be related to capsule design features and that TCLP extracts from these capsules could, in some brands, exceed RCRA Hg limits, making their disposal problematic. At current RCRA limits, the leaching of Ag is not a problem.

An ERP study of regular and irregular English past tense inflection.

PubMed

Newman, Aaron J; Ullman, Michael T; Pancheva, Roumyana; Waligura, Diane L; Neville, Helen J

2007-01-01

Compositionality is a critical and universal characteristic of human language. It is found at numerous levels, including the combination of morphemes into words and of words into phrases and sentences. These compositional patterns can generally be characterized by rules. For example, the past tense of most English verbs ("regulars") is formed by adding an -ed suffix. However, many complex linguistic forms have rather idiosyncratic mappings. For example, "irregular" English verbs have past tense forms that cannot be derived from their stems in a consistent manner. Whether regular and irregular forms depend on fundamentally distinct neurocognitive processes (rule-governed combination vs. lexical memorization), or whether a single processing system is sufficient to explain the phenomena, has engendered considerable investigation and debate. We recorded event-related potentials while participants read English sentences that were either correct or had violations of regular past tense inflection, irregular past tense inflection, syntactic phrase structure, or lexical semantics. Violations of regular past tense and phrase structure, but not of irregular past tense or lexical semantics, elicited left-lateralized anterior negativities (LANs). These seem to reflect neurocognitive substrates that underlie compositional processes across linguistic domains, including morphology and syntax. Regular, irregular, and phrase structure violations all elicited later positivities that were maximal over midline parietal sites (P600s), and seem to index aspects of controlled syntactic processing of both phrase structure and morphosyntax. The results suggest distinct neurocognitive substrates for processing regular and irregular past tense forms: regulars depending on compositional processing, and irregulars stored in lexical memory.

Feature Grouping and Selection Over an Undirected Graph.

PubMed

Yang, Sen; Yuan, Lei; Lai, Ying-Cheng; Shen, Xiaotong; Wonka, Peter; Ye, Jieping

2012-01-01

High-dimensional regression/classification continues to be an important and challenging problem, especially when features are highly correlated. Feature selection, combined with additional structure information on the features has been considered to be promising in promoting regression/classification performance. Graph-guided fused lasso (GFlasso) has recently been proposed to facilitate feature selection and graph structure exploitation, when features exhibit certain graph structures. However, the formulation in GFlasso relies on pairwise sample correlations to perform feature grouping, which could introduce additional estimation bias. In this paper, we propose three new feature grouping and selection methods to resolve this issue. The first method employs a convex function to penalize the pairwise l ∞ norm of connected regression/classification coefficients, achieving simultaneous feature grouping and selection. The second method improves the first one by utilizing a non-convex function to reduce the estimation bias. The third one is the extension of the second method using a truncated l 1 regularization to further reduce the estimation bias. The proposed methods combine feature grouping and feature selection to enhance estimation accuracy. We employ the alternating direction method of multipliers (ADMM) and difference of convex functions (DC) programming to solve the proposed formulations. Our experimental results on synthetic data and two real datasets demonstrate the effectiveness of the proposed methods.

Line fitting based feature extraction for object recognition

NASA Astrophysics Data System (ADS)

Li, Bing

2014-06-01

Image feature extraction plays a significant role in image based pattern applications. In this paper, we propose a new approach to generate hierarchical features. This new approach applies line fitting to adaptively divide regions based upon the amount of information and creates line fitting features for each subsequent region. It overcomes the feature wasting drawback of the wavelet based approach and demonstrates high performance in real applications. For gray scale images, we propose a diffusion equation approach to map information-rich pixels (pixels near edges and ridge pixels) into high values, and pixels in homogeneous regions into small values near zero that form energy map images. After the energy map images are generated, we propose a line fitting approach to divide regions recursively and create features for each region simultaneously. This new feature extraction approach is similar to wavelet based hierarchical feature extraction in which high layer features represent global characteristics and low layer features represent local characteristics. However, the new approach uses line fitting to adaptively focus on information-rich regions so that we avoid the feature waste problems of the wavelet approach in homogeneous regions. Finally, the experiments for handwriting word recognition show that the new method provides higher performance than the regular handwriting word recognition approach.

Reducing Mission Logistics with Multipurpose Cargo Transfer Bags

NASA Technical Reports Server (NTRS)

Baccus, Shelley; Broyan, James Lee, Jr.; Borrego, Melissa

2016-01-01

The Logistics Reduction (LR) project within Advanced Exploration Systems (AES) is tasked with reducing logistical mass and repurposing logistical items. Multipurpose Cargo Transfer Bags (MCTB) have been designed such that they can serve the same purpose as a Cargo Transfer Bag (CTB), the common logistics carrying bag for the International Space Station (ISS). After use as a cargo carrier, a regular CTB becomes trash, whereas the MCTB can be unfolded into a flat panel for reuse. Concepts and potential benefits for various MCTB applications will be discussed including partitions, crew quarters, solar radiation storm shelters, acoustic blankets, and forward osmosis water processing. Acoustic MCTBs are currently in use on ISS to reduce the noise generated by the T2 treadmill, which reaches the hazard limit at high speeds. The development of the AMCTB included identification of keep-out zones, acoustic properties, deployment considerations, and structural testing. Features developed for these considerations are applicable to MCTBs for all crew outfitting applications.

Multipurpose Cargo Transfer Bags fro Reducing Exploration Mission Logistics

NASA Technical Reports Server (NTRS)

Baccus, Shelley; Broyan, James Lee, Jr.; Borrego, Melissa

2016-01-01

The Logistics Reduction (LR) project within the Advanced Exploration Systems (AES) division is tasked with reducing logistical mass and repurposing logistical items. Multipurpose Cargo Transfer Bags (MCTB) have been designed such that they can serve the same purpose as a Cargo Transfer Bag (CTB), the common logistics carrying bag for the International Space Station (ISS). After use as a cargo carrier, a regular CTB becomes trash, whereas the MCTB can be unfolded into a flat panel for reuse. Concepts and potential benefits for various MCTB applications will be discussed including partitions, crew quarters, solar radiation storm shelters, acoustic blankets, and forward osmosis water processing. Acoustic MCTBs are currently in use on ISS to reduce the noise generated by the T2 treadmill, which reaches the hazard limit at high speeds. The development of the AMCTB included identification of keep out zones, acoustic properties, deployment considerations, and structural testing. Features developed for these considerations are applicable to MCTBs for all crew outfitting applications.

Seamless personal health information system in cloud computing.

PubMed

Chung, Wan-Young; Fong, Ee May

2014-01-01

Noncontact ECG measurement has gained popularity these days due to its noninvasive and conveniences to be applied on daily life. This approach does not require any direct contact between patient's skin and sensor for physiological signal measurement. The noncontact ECG measurement is integrated with mobile healthcare system for health status monitoring. Mobile phone acts as the personal health information system displaying health status and body mass index (BMI) tracking. Besides that, it plays an important role being the medical guidance providing medical knowledge database including symptom checker and health fitness guidance. At the same time, the system also features some unique medical functions that cater to the living demand of the patients or users, including regular medication reminders, alert alarm, medical guidance, appointment scheduling. Lastly, we demonstrate mobile healthcare system with web application for extended uses, thus health data are clouded into web server system and web database storage. This allows remote health status monitoring easily and so forth it promotes a cost effective personal healthcare system.

IEEE International Symposium on Biomedical Imaging.

PubMed

2017-01-01

The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2018 meeting will include tutorials, and a scientific program composed of plenary talks, invited special sessions, challenges, as well as oral and poster presentations of peer-reviewed papers. High-quality papers are requested containing original contributions to the topics of interest including image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological, and statistical modeling. Accepted 4-page regular papers will be published in the symposium proceedings published by IEEE and included in IEEE Xplore. To encourage attendance by a broader audience of imaging scientists and offer additional presentation opportunities, ISBI 2018 will continue to have a second track featuring posters selected from 1-page abstract submissions without subsequent archival publication.

Disappearance of the Propontis Regional Dark Albedo Feature on Mars

NASA Astrophysics Data System (ADS)

Lee, Steven W.; Thomas, P. C.; Cantor, B. A.

2013-10-01

The appearance of Propontis, one of many distinct classical dark albedo features on Mars, has been documented by ground-based observers for well over a century; Propontis was once thought to be the location of a “typical Martian canal”. The roughly circular feature (centered at 38°N, 179°W) covers about 500km in north-south extent. Modern spacecraft observations have shown the northern plains in which Propontis is located to include many subdued craters, knobs, and troughs. Observations by the Mars Color Imager (MARCI) onboard the Mars Reconnaissance Orbiter (MRO) have documented dramatic changes in the Propontis feature during August 2009. Daily MARCI mosaics (spatial resolution of 1 km/pixel) revealed extensive dust storm activity in this region over a ten day period (August 16-25, Ls ~ 322°-327°). At this time, the north polar seasonal ice cap was at maximum extent (reaching southward to about 55°N), and dust storm activity was frequently observed southward of the seasonal cap. These storms apparently led to sufficient deposition of bright dust to effectively “erase” the dark Propontis feature - yielding one of the most significant changes in regional albedo since Mars Global Surveyor began routine global mapping in 1997. Only minor changes have been detected over the course of repeated MARCI observations of this region since late-2009 - Propontis has not yet “recovered” to its previous extent and appearance. MRO is expected to provide ongoing MARCI mapping, enhanced with regular Context Imager (CTX, spatial resolution of 6 m/pixel) monitoring. An overview of the accumulated observations to date will be presented, along with interpretation of the magnitude of sediment transport required to account for the observed changes in Propontis.

TOOLKIT, Version 2. 0

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

Schroeder, E.; Bagot, B.; McNeill, R.L.

1990-05-09

The purpose of this User's Guide is to show by example many of the features of Toolkit II. Some examples will be copies of screens as they appear while running the Toolkit. Other examples will show what the user should enter in various situations; in these instances, what the computer asserts will be in boldface and what the user responds will be in regular type. The User's Guide is divided into four sections. The first section, FOCUS Databases'', will give a broad overview of the Focus administrative databases that are available on the VAX; easy-to-use reports are available for mostmore » of them in the Toolkit. The second section, Getting Started'', will cover the steps necessary to log onto the Computer Center VAX cluster and how to start Focus and the Toolkit. The third section, Using the Toolkit'', will discuss some of the features in the Toolkit -- the available reports and how to access them, as well as some utilities. The fourth section, Helpful Hints'', will cover some useful facts about the VAX and Focus as well as some of the more common problems that can occur. The Toolkit is not set in concrete but is continually being revised and improved. If you have any opinions as to changes that you would like to see made to the Toolkit or new features that you would like included, please let us know. Since we do try to respond to the needs of the user and make periodic improvement to the Toolkit, this User's Guide may not correspond exactly to what is available in the computer. In general, changes are made to provide new options or features; rarely is an existing feature deleted.« less

Consensus Statement of the American Academy of Sleep Medicine on the Recommended Amount of Sleep for Healthy Children: Methodology and Discussion

PubMed Central

Paruthi, Shalini; Brooks, Lee J.; D'Ambrosio, Carolyn; Hall, Wendy A.; Kotagal, Suresh; Lloyd, Robin M.; Malow, Beth A.; Maski, Kiran; Nichols, Cynthia; Quan, Stuart F.; Rosen, Carol L.; Troester, Matthew M.; Wise, Merrill S.

2016-01-01

Members of the American Academy of Sleep Medicine developed consensus recommendations for the amount of sleep needed to promote optimal health in children and adolescents using a modified RAND Appropriateness Method. After review of 864 published articles, the following sleep durations are recommended: Infants 4 months to 12 months should sleep 12 to 16 hours per 24 hours (including naps) on a regular basis to promote optimal health. Children 1 to 2 years of age should sleep 11 to 14 hours per 24 hours (including naps) on a regular basis to promote optimal health. Children 3 to 5 years of age should sleep 10 to 13 hours per 24 hours (including naps) on a regular basis to promote optimal health. Children 6 to 12 years of age should sleep 9 to 12 hours per 24 hours on a regular basis to promote optimal health. Teenagers 13 to 18 years of age should sleep 8 to 10 hours per 24 hours on a regular basis to promote optimal health. Sleeping the number of recommended hours on a regular basis is associated with better health outcomes including: improved attention, behavior, learning, memory, emotional regulation, quality of life, and mental and physical health. Regularly sleeping fewer than the number of recommended hours is associated with attention, behavior, and learning problems. Insufficient sleep also increases the risk of accidents, injuries, hypertension, obesity, diabetes, and depression. Insufficient sleep in teenagers is associated with increased risk of self-harm, suicidal thoughts, and suicide attempts. Commentary: A commentary on this article apears in this issue on page 1439. Citation: Paruthi S, Brooks LJ, D'Ambrosio C, Hall WA, Kotagal S, Lloyd RM, Malow BA, Maski K, Nichols C, Quan SF, Rosen CL, Troester MM, Wise MS. Consensus statement of the American Academy of Sleep Medicine on the recommended amount of sleep for healthy children: methodology and discussion. J Clin Sleep Med 2016;12(11):1549–1561. PMID:27707447

Informing the development of an Internet-based chronic pain self-management program.

PubMed

Gogovor, Amédé; Visca, Regina; Auger, Claudine; Bouvrette-Leblanc, Lucie; Symeonidis, Iphigenia; Poissant, Lise; Ware, Mark A; Shir, Yoram; Viens, Natacha; Ahmed, Sara

2017-01-01

Self-management can optimize health outcomes for individuals with chronic pain (CP), an increasing fiscal and social burden in Canada. However, self-management is rarely integrated into the regular care (team activities and medical treatment) patients receive. Health information technology offers an opportunity to provide regular monitoring and exchange of information between patient and care team. To identify information needs and gaps in chronic pain management as well as technology features to inform the development of an Internet-based self-management program. Two methods were used. First was a structured literature review: electronic databases were searched up to 2015 with combinations of MeSH terms and text-words such as chronic pain, self-management, self-efficacy, technology, Internet-based, patient portal, and e-health. A narrative synthesis of the characteristics and content of Internet-based pain management programs emerging from the literature review and how they relate to gaps in chronic pain management were completed. Second, four audiotaped focus group sessions were conducted with individuals with chronic pain and caregivers (n=9) and health professionals (n=7) recruited from three multidisciplinary tertiary and rehabilitation centres. A thematic analysis of the focus group transcripts was conducted. Thirty-nine primary articles related to 20 patient-oriented Internet-based programs were selected. Gaps in CP management included lack of knowledge, limited access to health care, suboptimal care, and lack of self-management support. Overall, 14 themes related to information needs and gaps in care were identified by both health professionals and patients, three were exclusive to patients and five to health professionals. Common themes from the focus groups included patient education on chronic pain care, attitude-belief-culture, financial and legal issues, end-of-program crash, and motivational content. Internet-based programs contain automated, communication and decision support features that can address information and care gaps reported by patients and clinicians. However, focus groups identified functionalities not reported in the literature, non-medical and condition- and context-specific information, integration of personal health records, and the role of the different health professionals in chronic pain management were not identified. These gaps need to be considered in the future development of Internet-based programs. While the association between the mechanisms of Internet-based programs' features and outcomes is not clearly established, the results of this study indicate that interactivity, personalization and tailored messages, combined with therapist contact will maximize the effectiveness of an Internet-based chronic pain program in enhancing self-management. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Irregular Wave Energy Extraction Analysis for a Slider Crank WEC Power Take-Off System

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

Sang, Yuanrui; Karayaka, H. Bora; Yan, Yanjun

2015-09-02

Slider crank Wave Energy Converter (WEC) is a novel energy conversion device. It converts wave energy into electricity at a relatively high efficiency, and it features a simple structure. Past analysis on this WEC has been done under regular sinusoidal wave conditions, and a suboptimal energy could be achieved. This paper presents the analysis of the system under irregular wave conditions; a time-domain hydrodynamics model is adopted and the control methodology is modified to better serve the irregular wave conditions. Results from the simulations show that the performance of the system under irregular wave conditions is different from that undermore » regular sinusoidal wave conditions, but still a reasonable amount of energy can be extracted.« less

Coherence resonance in bursting neural networks

NASA Astrophysics Data System (ADS)

Kim, June Hoan; Lee, Ho Jun; Min, Cheol Hong; Lee, Kyoung J.

2015-10-01

Synchronized neural bursts are one of the most noticeable dynamic features of neural networks, being essential for various phenomena in neuroscience, yet their complex dynamics are not well understood. With extrinsic electrical and optical manipulations on cultured neural networks, we demonstrate that the regularity (or randomness) of burst sequences is in many cases determined by a (few) low-dimensional attractor(s) working under strong neural noise. Moreover, there is an optimal level of noise strength at which the regularity of the interburst interval sequence becomes maximal—a phenomenon of coherence resonance. The experimental observations are successfully reproduced through computer simulations on a well-established neural network model, suggesting that the same phenomena may occur in many in vivo as well as in vitro neural networks.

Ionospheric-thermospheric UV tomography: 1. Image space reconstruction algorithms

NASA Astrophysics Data System (ADS)

Dymond, K. F.; Budzien, S. A.; Hei, M. A.

2017-03-01

We present and discuss two algorithms of the class known as Image Space Reconstruction Algorithms (ISRAs) that we are applying to the solution of large-scale ionospheric tomography problems. ISRAs have several desirable features that make them useful for ionospheric tomography. In addition to producing nonnegative solutions, ISRAs are amenable to sparse-matrix formulations and are fast, stable, and robust. We present the results of our studies of two types of ISRA: the Least Squares Positive Definite and the Richardson-Lucy algorithms. We compare their performance to the Multiplicative Algebraic Reconstruction and Conjugate Gradient Least Squares algorithms. We then discuss the use of regularization in these algorithms and present our new approach based on regularization to a partial differential equation.

A magneto-rheological fluid-based torque sensor for smart torque wrench application

NASA Astrophysics Data System (ADS)

Ahmadkhanlou, Farzad; Washington, Gregory N.

2013-04-01

In this paper, the authors have developed a new application where MR fluid is being used as a sensor. An MR-fluid based torque wrench has been developed with a rotary MR fluid-based damper. The desired set torque ranges from 1 to 6 N.m. Having continuously controllable yield strength, the MR fluid-based torque wrench presents a great advantage over the regular available torque wrenches in the market. This design is capable of providing continuous set toque from the lower limit to the upper limit while regular torque wrenches provide discrete set torques only at some limited points. This feature will be especially important in high fidelity systems where tightening torque is very critical and the tolerances are low.

Maximizing the Science Output of GOES-R SUVI during Operations

NASA Astrophysics Data System (ADS)

Shaw, M.; Vasudevan, G.; Mathur, D. P.; Mansir, D.; Shing, L.; Edwards, C. G.; Seaton, D. B.; Darnel, J.; Nwachuku, C.

2017-12-01

Regular manual calibrations are an often-unavoidable demand on ground operations personnel during long-term missions. This paper describes a set of features built into the instrument control software and the techniques employed by the Solar Ultraviolet Imager (SUVI) team to automate a large fraction of regular on-board calibration activities, allowing SUVI to be operated with little manual commanding from the ground and little interruption to nominal sequencing. SUVI is a Generalized Cassegrain telescope with a large field of view that images the Sun in six extreme ultraviolet (EUV) narrow bandpasses centered at 9.4, 13.1, 17.1, 19.5, 28.4 and 30.4 nm. It is part of the payload of the Geostationary Operational Environmental Satellite (GOES-R) mission.

The Beliefs and Practices of Canadian Teachers about Including Students with Special Needs in their Regular Elementary Classrooms

ERIC Educational Resources Information Center

Jordan, Anne; Stanovich, Paula

2004-01-01

While considerable research has been directed at examining the effectiveness of placement for exceptional students, few studies have examined the instructional characteristics which contribute to the success or failure of these students included in regular classrooms (Swanson & Hoskyn, 1999; Swanson, Hoskyn & Lee, 1999). Over the last decade we…

Regularity and/or Consistency in the Production of the Past Participle?

ERIC Educational Resources Information Center

Colombo, Lucia; Laudanna, Alessandro; De Martino, Maria; Brivio, Cristina

2004-01-01

In the present study we have investigated the acquisition of the past participle of Italian verbs of the second (including mostly irregular verbs) and third (including mostly regular verbs) conjugations in school age children, and with simulations with an artificial neural network. We aimed to verify the extent to which children are sensitive to…

Multi-fractal texture features for brain tumor and edema segmentation

NASA Astrophysics Data System (ADS)

Reza, S.; Iftekharuddin, K. M.

2014-03-01

In this work, we propose a fully automatic brain tumor and edema segmentation technique in brain magnetic resonance (MR) images. Different brain tissues are characterized using the novel texture features such as piece-wise triangular prism surface area (PTPSA), multi-fractional Brownian motion (mBm) and Gabor-like textons, along with regular intensity and intensity difference features. Classical Random Forest (RF) classifier is used to formulate the segmentation task as classification of these features in multi-modal MRIs. The segmentation performance is compared with other state-of-art works using a publicly available dataset known as Brain Tumor Segmentation (BRATS) 2012 [1]. Quantitative evaluation is done using the online evaluation tool from Kitware/MIDAS website [2]. The results show that our segmentation performance is more consistent and, on the average, outperforms other state-of-the art works in both training and challenge cases in the BRATS competition.

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring.

PubMed

Kallenberg, Michiel; Petersen, Kersten; Nielsen, Mads; Ng, Andrew Y; Pengfei Diao; Igel, Christian; Vachon, Celine M; Holland, Katharina; Winkel, Rikke Rass; Karssemeijer, Nico; Lillholm, Martin

2016-05-01

Mammographic risk scoring has commonly been automated by extracting a set of handcrafted features from mammograms, and relating the responses directly or indirectly to breast cancer risk. We present a method that learns a feature hierarchy from unlabeled data. When the learned features are used as the input to a simple classifier, two different tasks can be addressed: i) breast density segmentation, and ii) scoring of mammographic texture. The proposed model learns features at multiple scales. To control the models capacity a novel sparsity regularizer is introduced that incorporates both lifetime and population sparsity. We evaluated our method on three different clinical datasets. Our state-of-the-art results show that the learned breast density scores have a very strong positive relationship with manual ones, and that the learned texture scores are predictive of breast cancer. The model is easy to apply and generalizes to many other segmentation and scoring problems.

"Ersatz" and "hybrid" NMR spectral estimates using the filter diagonalization method.

PubMed

Ridge, Clark D; Shaka, A J

2009-03-12

The filter diagonalization method (FDM) is an efficient and elegant way to make a spectral estimate purely in terms of Lorentzian peaks. As NMR spectral peaks of liquids conform quite well to this model, the FDM spectral estimate can be accurate with far fewer time domain points than conventional discrete Fourier transform (DFT) processing. However, noise is not efficiently characterized by a finite number of Lorentzian peaks, or by any other analytical form, for that matter. As a result, noise can affect the FDM spectrum in different ways than it does the DFT spectrum, and the effect depends on the dimensionality of the spectrum. Regularization to suppress (or control) the influence of noise to give an "ersatz", or EFDM, spectrum is shown to sometimes miss weak features, prompting a more conservative implementation of filter diagonalization. The spectra obtained, called "hybrid" or HFDM spectra, are acquired by using regularized FDM to obtain an "infinite time" spectral estimate and then adding to it the difference between the DFT of the data and the finite time FDM estimate, over the same time interval. HFDM has a number of advantages compared to the EFDM spectra, where all features must be Lorentzian. They also show better resolution than DFT spectra. The HFDM spectrum is a reliable and robust way to try to extract more information from noisy, truncated data records and is less sensitive to the choice of regularization parameter. In multidimensional NMR of liquids, HFDM is a conservative way to handle the problems of noise, truncation, and spectral peaks that depart significantly from the model of a multidimensional Lorentzian peak.

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

Technology and tuberculosis control: the OUT-TB Web experience.

PubMed

Guthrie, Jennifer L; Alexander, David C; Marchand-Austin, Alex; Lam, Karen; Whelan, Michael; Lee, Brenda; Furness, Colin; Rea, Elizabeth; Stuart, Rebecca; Lechner, Julia; Varia, Monali; McLean, Jennifer; Jamieson, Frances B

2017-04-01

Develop a tool to disseminate integrated laboratory, clinical, and demographic case data necessary for improved contact tracing and outbreak detection of tuberculosis (TB). In 2007, the Public Health Ontario Laboratories implemented a universal genotyping program to monitor the spread of TB strains within Ontario. Ontario Universal Typing of TB (OUT-TB) Web utilizes geographic information system (GIS) technology with a relational database platform, allowing TB control staff to visualize genotyping matches and microbiological data within the context of relevant epidemiological and demographic data. OUT-TB Web is currently available to the 8 health units responsible for >85% of Ontario's TB cases and is a valuable tool for TB case investigation. Users identified key features to implement for application enhancements, including an e-mail alert function, customizable heat maps for visualizing TB and drug-resistant cases, socioeconomic map layers, a dashboard providing TB surveillance metrics, and a feature for animating the geographic spread of strains over time. OUT-TB Web has proven to be an award-winning application and a useful tool. Developed and enhanced using regular user feedback, future versions will include additional data sources, enhanced map and line-list filter capabilities, and development of a mobile app. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

PubMed

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

Learning to rank using user clicks and visual features for image retrieval.

PubMed

Yu, Jun; Tao, Dacheng; Wang, Meng; Rui, Yong

2015-04-01

The inconsistency between textual features and visual contents can cause poor image search results. To solve this problem, click features, which are more reliable than textual information in justifying the relevance between a query and clicked images, are adopted in image ranking model. However, the existing ranking model cannot integrate visual features, which are efficient in refining the click-based search results. In this paper, we propose a novel ranking model based on the learning to rank framework. Visual features and click features are simultaneously utilized to obtain the ranking model. Specifically, the proposed approach is based on large margin structured output learning and the visual consistency is integrated with the click features through a hypergraph regularizer term. In accordance with the fast alternating linearization method, we design a novel algorithm to optimize the objective function. This algorithm alternately minimizes two different approximations of the original objective function by keeping one function unchanged and linearizing the other. We conduct experiments on a large-scale dataset collected from the Microsoft Bing image search engine, and the results demonstrate that the proposed learning to rank models based on visual features and user clicks outperforms state-of-the-art algorithms.

Condom Use and Intimacy among Tajik Male Migrants and their Regular Female Partners in Moscow

PubMed Central

Polutnik, Chloe; Jonbekov, Jonbek; Shoakova, Farzona; Bahromov, Mahbat; Weine, Stevan

2014-01-01

This study examined condom use and intimacy among Tajik male migrants and their regular female partners in Moscow, Russia. This study included a survey of 400 Tajik male labour migrants; and longitudinal ethnographic interviews with 30 of the surveyed male migrants and 30 of their regular female partners. 351 (88%) of the surveyed male migrants reported having a regular female partner in Moscow. Findings demonstrated that the migrants’ and regular partners’ intentions to use condoms diminished with increased intimacy, yet each party perceived intimacy differently. Migrants’ intimacy with regular partners was determined by their familiarity and perceived sexual cleanliness of their partner. Migrants believed that Muslim women were cleaner than Orthodox Christian women and reported using condoms more frequently with Orthodox Christian regular partners. Regular partners reported determining intimacy based on the perceived commitment of the male migrant. When perceived commitment faced a crisis, intimacy declined, and regular partners renegotiated condom use. The association between intimacy and condom use suggests that HIV prevention programmes should aim to help male migrants and female regular partners to dissociate their approaches to condom use from their perceptions of intimacy. PMID:25033817

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia

PubMed Central

Kim, Junghoe; Calhoun, Vince D.; Shim, Eunsoo; Lee, Jong-Hwan

2015-01-01

Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was quantified by using kurtosis/modularity measures and features from the higher hidden layer showed holistic/global FC patterns differentiating SZ from HC. Our proposed schemes and reported findings attained by using the DNN classifier and whole-brain FC data suggest that such approaches show improved ability to learn hidden patterns in brain imaging data, which may be useful for developing diagnostic tools for SZ and other neuropsychiatric disorders and identifying associated aberrant FC patterns. PMID:25987366

Geostatistical regularization operators for geophysical inverse problems on irregular meshes

NASA Astrophysics Data System (ADS)

Jordi, C.; Doetsch, J.; Günther, T.; Schmelzbach, C.; Robertsson, J. OA

2018-05-01

Irregular meshes allow to include complicated subsurface structures into geophysical modelling and inverse problems. The non-uniqueness of these inverse problems requires appropriate regularization that can incorporate a priori information. However, defining regularization operators for irregular discretizations is not trivial. Different schemes for calculating smoothness operators on irregular meshes have been proposed. In contrast to classical regularization constraints that are only defined using the nearest neighbours of a cell, geostatistical operators include a larger neighbourhood around a particular cell. A correlation model defines the extent of the neighbourhood and allows to incorporate information about geological structures. We propose an approach to calculate geostatistical operators for inverse problems on irregular meshes by eigendecomposition of a covariance matrix that contains the a priori geological information. Using our approach, the calculation of the operator matrix becomes tractable for 3-D inverse problems on irregular meshes. We tested the performance of the geostatistical regularization operators and compared them against the results of anisotropic smoothing in inversions of 2-D surface synthetic electrical resistivity tomography (ERT) data as well as in the inversion of a realistic 3-D cross-well synthetic ERT scenario. The inversions of 2-D ERT and seismic traveltime field data with geostatistical regularization provide results that are in good accordance with the expected geology and thus facilitate their interpretation. In particular, for layered structures the geostatistical regularization provides geologically more plausible results compared to the anisotropic smoothness constraints.

Regular-Fat Dairy and Human Health: A Synopsis of Symposia Presented in Europe and North America (2014–2015)

PubMed Central

Astrup, Arne; Rice Bradley, Beth H.; Brenna, J. Thomas; Delplanque, Bernadette; Ferry, Monique; Torres-Gonzalez, Moises

2016-01-01

In recent history, some dietary recommendations have treated dairy fat as an unnecessary source of calories and saturated fat in the human diet. These assumptions, however, have recently been brought into question by current research on regular fat dairy products and human health. In an effort to disseminate, explore and discuss the state of the science on the relationship between regular fat dairy products and health, symposia were programmed by dairy industry organizations in Europe and North America at The Eurofed Lipids Congress (2014) in France, The Dairy Nutrition Annual Symposium (2014) in Canada, The American Society for Nutrition Annual Meeting held in conjunction with Experimental Biology (2015) in the United States, and The Federation of European Nutrition Societies (2015) in Germany. This synopsis of these symposia describes the complexity of dairy fat and the effects regular-fat dairy foods have on human health. The emerging scientific evidence indicates that the consumption of regular fat dairy foods is not associated with an increased risk of cardiovascular disease and inversely associated with weight gain and the risk of obesity. Dairy foods, including regular-fat milk, cheese and yogurt, can be important components of an overall healthy dietary pattern. Systematic examination of the effects of dietary patterns that include regular-fat milk, cheese and yogurt on human health is warranted. PMID:27483308

Regular-Fat Dairy and Human Health: A Synopsis of Symposia Presented in Europe and North America (2014-2015).

PubMed

Astrup, Arne; Rice Bradley, Beth H; Brenna, J Thomas; Delplanque, Bernadette; Ferry, Monique; Torres-Gonzalez, Moises

2016-07-29

In recent history, some dietary recommendations have treated dairy fat as an unnecessary source of calories and saturated fat in the human diet. These assumptions, however, have recently been brought into question by current research on regular fat dairy products and human health. In an effort to disseminate, explore and discuss the state of the science on the relationship between regular fat dairy products and health, symposia were programmed by dairy industry organizations in Europe and North America at The Eurofed Lipids Congress (2014) in France, The Dairy Nutrition Annual Symposium (2014) in Canada, The American Society for Nutrition Annual Meeting held in conjunction with Experimental Biology (2015) in the United States, and The Federation of European Nutrition Societies (2015) in Germany. This synopsis of these symposia describes the complexity of dairy fat and the effects regular-fat dairy foods have on human health. The emerging scientific evidence indicates that the consumption of regular fat dairy foods is not associated with an increased risk of cardiovascular disease and inversely associated with weight gain and the risk of obesity. Dairy foods, including regular-fat milk, cheese and yogurt, can be important components of an overall healthy dietary pattern. Systematic examination of the effects of dietary patterns that include regular-fat milk, cheese and yogurt on human health is warranted.

End-stage Renal Disease in Taiwan: A Case–Control Study

PubMed Central

Tsai, Su-Ying; Tseng, Hung-Fu; Tan, Hsiu-Fen; Chien, Yu-Shu; Chang, Chia-Chu

2009-01-01

Background Taiwan has the highest incidence of end-stage renal disease (ESRD) in the world. The epidemiologic features of ESRD, however, have not been investigated. In this case–control study, we evaluated the risk of ESRD associated with a number of putative risk factors. Methods We studied 200 patients among whom ESRD had been newly diagnosed between 1 January 2005 and 31 December 2005; 200 controls were selected from among relatives of patients treated in the general surgery unit. Using a structured questionnaire, we collected information related to socioeconomic factors, history of disease, regular blood or urine screening, lifestyle, environmental exposure, consumption of vitamin supplements, and regular drug use at 5 years before disease onset. Results Our primary multivariate risk models indicated that low socioeconomic status was a strong predictor of ESRD (education: odds ratio [OR], 2.78; 95% confidence interval [CI], 1.49–5.19; income: OR, 2.86, 95% CI, 1.48–5.52), even after adjusting for other risk factors. Other significant predictors for ESRD were a history of hypertension (OR, 3.63–3.90), history of diabetes (OR, 3.85–5.50), and regular intake of folk remedies or over-the-counter Chinese herbs (OR, 10.84–12.51). Regular intake of a multivitamin supplement 5 years before diagnosis was associated with a decreased risk of ESRD (OR, 0.12–0.14). Conclusions Our findings indicate that low socioeconomic status, history of hypertension, diabetes, and regular use of folk remedies or over-the-counter Chinese herbs were significant risk factors for ESRD, while regular intake of a multivitamin supplement was associated with a decreased risk of ESRD. PMID:19542686

Psychoacoustic Testing of Modulated Blade Spacing for Main Rotors

NASA Technical Reports Server (NTRS)

Edwards, Bryan; Booth, Earl R., Jr. (Technical Monitor)

2002-01-01

Psychoacoustic testing of simulated helicopter main rotor noise is described, and the subjective results are presented. The objective of these tests was to evaluate the potential acoustic benefits of main rotors with modulated (uneven) blade spacing. Sound simulations were prepared for six main rotor configurations. A baseline 4-blade main rotor with regular blade spacing was based on the Bell Model 427 helicopter. A 5-blade main rotor with regular spacing was designed to approximate the performance of the 427, but at reduced tipspeed. Four modulated rotors - one with "optimum" spacing and three alternate configurations - were derived from the 5 bladed regular spacing rotor. The sounds were played to 2 subjects at a time, with care being taken in the speaker selection and placement to ensure that the sounds were identical for each subject. A total of 40 subjects participated. For each rotor configuration, the listeners were asked to evaluate the sounds in terms of noisiness. The test results indicate little to no "annoyance" benefit for the modulated blade spacing. In general, the subjects preferred the sound of the 5-blade regular spaced rotor over any of the modulated ones. A conclusion is that modulated blade spacing is not a promising design feature to reduce the annoyance for helicopter main rotors.

Developing Sustainable and Impactful Mobile Phone HIV Testing Interventions for Spanish-Speaking Men Who Have Sex With Men in the United States: Lessons Learned From Informative Interviews.

PubMed

Mitchell, Jason; Torres, Maria Beatriz; Asmar, Lucy; Danh, Thu; Horvath, Keith J

2018-04-24

Although many men who have sex with men (MSM) test for HIV at least once in their lifetime, opportunities to improve regular HIV testing, particularly among Hispanic or Latino MSM, is needed. Many mHealth interventions in development, including the ones on HIV testing, have primarily focused on English-speaking white, black, and MSM of other races. To date, no studies have assessed app use, attitudes, and motivations for downloading and sustaining use of mobile apps and preferences with respect to HIV prevention among Spanish-speaking, Hispanic MSM in the United States. The primary aims of this study were to determine what features and functions of smartphone apps do Hispanic, Spanish-speaking MSM believe are associated with downloading apps to their smartphones, (2) what features and functions of smartphone apps are most likely to influence men's sustained use of apps over time, and (3) what features and functions do men prefer in a smartphone app aimed to promote regular testing for HIV. Interviews (N=15) were conducted with a racially diverse group of sexually active, HIV-negative, Spanish-speaking, Hispanic MSM in Miami, Florida. Interviews were digitally recorded, transcribed verbatim, translated back to English, and de-identified for analysis. A constant-comparison method (ie, grounded theory coding) was employed to examine themes that emerged from the interviews. Personal interest was the primary reason associated with whether men downloaded an app. Keeping personal information secure, cost, influence by peers and posted reviews, ease of use, and functionality affected whether they downloaded and used the app over time. Men also reported that entertainment value and frequency of updates influenced whether they kept and continued to use an app over time. There were 4 reasons why participants chose to delete an app-dislike, lack of use, cost, and lack of memory or space. Participants also shared their preferences for an app to encourage regular HIV testing by providing feedback on test reminders, tailored testing interval recommendations, HIV test locator, and monitoring of personal sexual behaviors. The features and functions of mobile apps that Spanish-speaking MSM in this study believed were associated with downloading and/or sustained engagement of an app generally reflected the priorities mentioned in an earlier study with English-speaking MSM. Unlike the earlier study, Spanish-speaking MSM prioritized personal interest in a mobile app and de-emphasized the efficiency of an app to make their lives easier in their decision to download an app to their mobile device. Tailoring mobile apps to the language and needs of Spanish-speaking MSM is critical to help increase their willingness to download a mobile app. Despite the growing number of HIV-prevention apps in development, few are tailored to Spanish-speaking MSM, representing an important gap that should be addressed in future research. ©Jason Mitchell, Maria Beatriz Torres, Lucy Asmar, Thu Danh, Keith J Horvath. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 24.04.2018.

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

Lafata, K; Ren, L; Wu, Q

Purpose: To develop a data-mining methodology based on quantum clustering and machine learning to predict expected dosimetric endpoints for lung SBRT applications based on patient-specific anatomic features. Methods: Ninety-three patients who received lung SBRT at our clinic from 2011–2013 were retrospectively identified. Planning information was acquired for each patient, from which various features were extracted using in-house semi-automatic software. Anatomic features included tumor-to-OAR distances, tumor location, total-lung-volume, GTV and ITV. Dosimetric endpoints were adopted from RTOG-0195 recommendations, and consisted of various OAR-specific partial-volume doses and maximum point-doses. First, PCA analysis and unsupervised quantum-clustering was used to explore the feature-space tomore » identify potentially strong classifiers. Secondly, a multi-class logistic regression algorithm was developed and trained to predict dose-volume endpoints based on patient-specific anatomic features. Classes were defined by discretizing the dose-volume data, and the feature-space was zero-mean normalized. Fitting parameters were determined by minimizing a regularized cost function, and optimization was performed via gradient descent. As a pilot study, the model was tested on two esophageal dosimetric planning endpoints (maximum point-dose, dose-to-5cc), and its generalizability was evaluated with leave-one-out cross-validation. Results: Quantum-Clustering demonstrated a strong separation of feature-space at 15Gy across the first-and-second Principle Components of the data when the dosimetric endpoints were retrospectively identified. Maximum point dose prediction to the esophagus demonstrated a cross-validation accuracy of 87%, and the maximum dose to 5cc demonstrated a respective value of 79%. The largest optimized weighting factor was placed on GTV-to-esophagus distance (a factor of 10 greater than the second largest weighting factor), indicating an intuitively strong correlation between this feature and both endpoints. Conclusion: This pilot study shows that it is feasible to predict dose-volume endpoints based on patient-specific anatomic features. The developed methodology can potentially help to identify patients at risk for higher OAR doses, thus improving the efficiency of treatment planning. R01-184173.« less

How do people with body dysmorphic disorder view themselves? A thematic analysis.

PubMed

Silver, Joanna; Reavey, Paula; Anne Fineberg, Naomi

2010-09-01

Abstract Objectives. To examine the accounts of people with body dysmorphic disorder (BDD) and qualitatively explore self perceptions. Methods. Eleven people with BDD were interviewed using a semi-structured schedule. Participants brought photographs of themselves and drew a self-portrait. Transcribed interviews were analysed using a thematic analysis. Results. The most common theme was increased threat perception resulting in disordered interpersonal relationships. Other themes included the wish for regularity and symmetry in appearance, an idealised childhood self, the duty to look good, and a focus on specific "defective" features rather than general ugliness. Conclusions. Using thematic analysis and visual methods, we identified core themes that appear to characterise the way individuals with BDD perceive themselves and their interpersonal relationships. Thematic analysis offers promise as a tool to explore the overlap between BDD and other putatively related mental health problems.

ANMCO/GICR-IACPR/SICI-GISE Consensus Document: the clinical management of chronic ischaemic cardiomyopathy

PubMed Central

Gulizia, Michele Massimo; Colivicchi, Furio; Di Lenarda, Andrea; Musumeci, Giuseppe; Faggiano, Pompilio Massimo; Abrignani, Maurizio Giuseppe; Rossini, Roberta; Fattirolli, Francesco; Valente, Serafina; Mureddu, Gian Francesco; Temporelli, Pier Luigi; Olivari, Zoran; Amico, Antonio Francesco; Casolo, Giancarlo; Fresco, Claudio; Menozzi, Alberto; Nardi, Federico

2017-01-01

Stable coronary artery disease (CAD) is a clinical entity of great epidemiological importance. It is becoming increasingly common due to the longer life expectancy, being strictly related to age and to advances in diagnostic techniques and pharmacological and non-pharmacological interventions. Stable CAD encompasses a variety of clinical and anatomic presentations, making the identification of its clinical and anatomical features challenging. Therapeutic interventions should be defined on an individual basis according to the patient’s risk profile. To this aim, management flow charts have been reviewed based on sustainability and appropriateness derived from recent evidence. Special emphasis has been placed on non-pharmacological interventions, stressing the importance of lifestyle changes, including smoking cessation, regular physical activity, and diet. Adherence to therapy as an emerging risk factor is also discussed. PMID:28533729

The LHC magnet system and its status of development

NASA Technical Reports Server (NTRS)

Bona, Maurizio; Perin, Romeo; Vlogaert, Jos

1995-01-01

CERN is preparing for the construction of a new high energy accelerator/collider, the Large Hadron Collider (LHC). This new facility will mainly consist of two superconducting magnetic beam channels, 27 km long, to be installed in the existing LEP tunnel. The magnetic system comprises about 1200 twin-aperture dipoles, 13.145 m long, with an operational field of 8.65 T, about 600 quadrupoles, 3 m long, and a very large number of other superconducting magnetic components. A general description of the system is given together with the main features of the design of the regular lattice magnets. The paper also describes the present state of the magnet R & D program. Results from short model work, as well as from full scale prototypes will be presented, including the recently tested 10 m long full-scale prototype dipole manufactured in industry.

Symbolic Dynamics and Grammatical Complexity

NASA Astrophysics Data System (ADS)

Hao, Bai-Lin; Zheng, Wei-Mou

The following sections are included: * Formal Languages and Their Complexity * Formal Language * Chomsky Hierarchy of Grammatical Complexity * The L-System * Regular Language and Finite Automaton * Finite Automaton * Regular Language * Stefan Matrix as Transfer Function for Automaton * Beyond Regular Languages * Feigenbaum and Generalized Feigenbaum Limiting Sets * Even and Odd Fibonacci Sequences * Odd Maximal Primitive Prefixes and Kneading Map * Even Maximal Primitive Prefixes and Distinct Excluded Blocks * Summary of Results

Data approximation using a blending type spline construction

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

Dalmo, Rune; Bratlie, Jostein

2014-11-18

Generalized expo-rational B-splines (GERBS) is a blending type spline construction where local functions at each knot are blended together by C{sup k}-smooth basis functions. One way of approximating discrete regular data using GERBS is by partitioning the data set into subsets and fit a local function to each subset. Partitioning and fitting strategies can be devised such that important or interesting data points are interpolated in order to preserve certain features. We present a method for fitting discrete data using a tensor product GERBS construction. The method is based on detection of feature points using differential geometry. Derivatives, which aremore » necessary for feature point detection and used to construct local surface patches, are approximated from the discrete data using finite differences.« less

Context-dependent logo matching and recognition.

PubMed

Sahbi, Hichem; Ballan, Lamberto; Serra, Giuseppe; Del Bimbo, Alberto

2013-03-01

We contribute, through this paper, to the design of a novel variational framework able to match and recognize multiple instances of multiple reference logos in image archives. Reference logos and test images are seen as constellations of local features (interest points, regions, etc.) and matched by minimizing an energy function mixing: 1) a fidelity term that measures the quality of feature matching, 2) a neighborhood criterion that captures feature co-occurrence/geometry, and 3) a regularization term that controls the smoothness of the matching solution. We also introduce a detection/recognition procedure and study its theoretical consistency. Finally, we show the validity of our method through extensive experiments on the challenging MICC-Logos dataset. Our method overtakes, by 20%, baseline as well as state-of-the-art matching/recognition procedures.

[Clinical and endoscopic features of a selected population with serrated colorectal adenomas in a private clinic in Lima - Peru].

PubMed

Castillo, Ofelia; Barreda, Carlos; Recavarren, Sixto; Barriga, José A; Salazar M, Fernando; Yriberry, Simón; Barriga, Eduardo; Salazar C, Fernando

2013-01-01

To describe the clinical and endoscopic caracteristics of a population that has only serrated polyps of colon (mainly sessile serrated adenomas) in a private clinic in Lima, Perú, from 2009-2011. Retrospective study conducted at the endoscopy center of Clinic Ricardo Palma, Lima, Peru. Olympus colonoscope was used with high definition, including NBI (narrow band imaging) and electronic magnification. Patients had pathologic diagnosis of “polyps and / or colorectal serrated adenomas” and excluded those with synchronous tubular or villous adenomas. Images were evaluated by two endoscopists and then by a third gastroenterologist. We found 201 serrated polyps in 108 patients. Women were 60.2% and overweight predominated. Eighty (74.1%) had only one serrated adenoma and 23 (21.3%) with at least one synchronous hyperplastic polyp. The average size of sessile serrated adenomas was 5.12 mm (± 3.87 DS) and the flat type was 91 (58.7%). There were significant differences in the diameter of sessile serrated adenomas between the distal and proximal colon (4.47 mm ± 2.23 vs. 6.90 mm ± 6.25; p<0.000). The common features of sessile serrated adenomas were: White (31/36, 86.1%), smooth (28/36, 77.8%) and regular margins (26/36, 72.2%). There was a relationship between vascular pattern according NBI and serrated polyp histology (p=0.024). The endoscopic features of sessile serrated adenomas can evade detection to white light. NBI is a useful tool to define some features of these lesions.

An Artificial Neural Network for Movement Pattern Analysis to Estimate Blood Alcohol Content Level.

PubMed

Gharani, Pedram; Suffoletto, Brian; Chung, Tammy; Karimi, Hassan A

2017-12-13

Impairments in gait occur after alcohol consumption, and, if detected in real-time, could guide the delivery of "just-in-time" injury prevention interventions. We aimed to identify the salient features of gait that could be used for estimating blood alcohol content (BAC) level in a typical drinking environment. We recruited 10 young adults with a history of heavy drinking to test our research app. During four consecutive Fridays and Saturdays, every hour from 8 p.m. to 12 a.m., they were prompted to use the app to report alcohol consumption and complete a 5-step straight-line walking task, during which 3-axis acceleration and angular velocity data was sampled at a frequency of 100 Hz. BAC for each subject was calculated. From sensor signals, 24 features were calculated using a sliding window technique, including energy, mean, and standard deviation. Using an artificial neural network (ANN), we performed regression analysis to define a model determining association between gait features and BACs. Part (70%) of the data was then used as a training dataset, and the results tested and validated using the rest of the samples. We evaluated different training algorithms for the neural network and the result showed that a Bayesian regularization neural network (BRNN) was the most efficient and accurate. Analyses support the use of the tandem gait task paired with our approach to reliably estimate BAC based on gait features. Results from this work could be useful in designing effective prevention interventions to reduce risky behaviors during periods of alcohol consumption.

Does a Foreign Accent Sell? The Effect of Foreign Accents in Radio Commercials for Congruent and Non-Congruent Products

ERIC Educational Resources Information Center

Hendriks, Berna; van Meurs, Frank; van der Meij, Els

2015-01-01

Commercials regularly feature foreign accents. This paper aims to investigate whether the use of foreign accents in radio commercials is more effective for congruent than incongruent products, and whether foreign-accented commercials are evaluated differently than non-accented commercials. In an experiment, a group of 228 Dutch participants rated…

Enhancing Children's Spatial and Numerical Skills through a Dynamic Spatial Approach to Early Geometry Instruction: Effects of a 32-Week Intervention

ERIC Educational Resources Information Center

Hawes, Zachary; Moss, Joan; Caswell, Beverly; Naqvi, Sarah; MacKinnon, Sharla

2017-01-01

This study describes the implementation and effects of a 32-week teacher-led spatial reasoning intervention in K-2 classrooms. The intervention targeted spatial visualization skills as an integrated feature of regular mathematics instruction. Compared to an active control group, children in the spatial intervention demonstrated gains in spatial…

Some Similarities and Differences Between Compositions Written by Remedial and Non-Remedial College Freshmen.

ERIC Educational Resources Information Center

House, Elizabeth B.; House, William J.

The essays composed by 84 remedial and 77 nonremedial college freshmen were analyzed for some features proposed by Mina Shaughnessy as being characteristic of basic writers. The students were enrolled in either a beginning remedial class (098), a class at the next level of remediation (099), or a regular English class (101). The essays were…

The Coverage of the Holocaust in High School History Textbooks

ERIC Educational Resources Information Center

Lindquist, David

2009-01-01

The Holocaust is now a regular part of high school history curricula throughout the United States and, as a result, coverage of the Holocaust has become a standard feature of high school textbooks. As with any major event, it is important for textbooks to provide a rigorously accurate and valid historical account. In dealing with the Holocaust,…

Judging the Quality of Teaching in Lessons: Some Thoughts Prompted by Ofsted's Subsidiary Guidance on Teaching Style

ERIC Educational Resources Information Center

Richards, Colin

2014-01-01

Lesson observations involving judgements of teaching quality are a regular feature of classroom life. Such observations and judgements are made by senior and middle managers in schools and also, very significantly, by Ofsted inspectors as a major component of their judgement on the quality of teaching in a school. Using the example of Ofsted…

International Trends in Health Science Librarianship Part 19: The Balkan States (Bulgaria and Croatia).

PubMed

Kirilova, Savina; Skoric, Lea

2016-09-01

This is the 19th in a series of articles exploring international trends in health science librarianship in the 21st century. The focus of the present issue is the Balkan Region (Bulgaria and Croatia). The next regular feature column will investigate two other Balkan states - Serbia and Slovenia. JM. © 2016 Health Libraries Group.

Idea Place: Early Grades. [Columns Compiled from Seven Issues of Learning Magazine, September to November 1982 and January to April-May 1983.

ERIC Educational Resources Information Center

Learning, 1983

1983-01-01

The "Idea Place," a regular feature carried by the magazine "Learning," provides an assortment of practical teaching techniques selected from commercially available materials and from ideas submitted by readers. Games, puzzles, and other activities are given for the areas of language arts, reading, mathematics, science, social…

Gaussian black holes in Rastall gravity

NASA Astrophysics Data System (ADS)

Spallucci, Euro; Smailagic, Anais

In this short note we present the solution of Rastall gravity equations sourced by a Gaussian matter distribution. We find that the black hole metric shares all the common features of other regular, General Relativity BH solutions discussed in the literature: there is no curvature singularity and the Hawking radiation leaves a remnant at zero temperature in the form of a massive ordinary particle.

A Comparison between Two Automatic Assessment Approaches for Programming: An Empirical Study on MOOCs

ERIC Educational Resources Information Center

Bey, Anis; Jermann, Patrick; Dillenbourg, Pierre

2018-01-01

Computer-graders have been in regular use in the context of MOOCs (Massive Open Online Courses). The automatic grading of programs presents an opportunity to assess and provide tailored feedback to large classes, while featuring at the same time a number of benefits like: immediate feedback, unlimited submissions, as well as low cost of feedback.…

Microcomputer-Assisted Needs Assessment System for Teacher Training in Special Education. Final Project Report, 8/1/83 through 5/31/86.

ERIC Educational Resources Information Center

Malouf, David; And Others

The report describes the features, underlying knowledge base, and goals of the "Smart Needs Assessment Program" (SNAP), an interactive, microcomputer-based system designed to provide inservice training in special education for regular education teachers. The Teacher Effectiveness Expert System portion uses teacher data concerning attitudes, goals,…

Trends and Issues in Technology Education Research in Taiwan: A Co-Word Analysis of 1994-2013 Graduate Theses

ERIC Educational Resources Information Center

Lee, Lung-Sheng; Fang, Yu-Shen

2015-01-01

In Taiwan, the Technology Education for 1-12 graders is comprised of two courses--Living Technology (LT) and Information Technology (IT). With its ever-changing feature, Technology Education needs on-going research to support its decisions and actions. The education-related academic programs in universities regularly concern about the development…

[Skin vessel lesions in aluminum potroom workers].

PubMed

Siurin, S A; Nikanov, A N; Shilov, V V

2012-01-01

The features of development of the skin vessels lesions in 550 aluminum production workers have been investigated. The high prevalence of these disorders have been revealed in anode-operators and cell-operators, 49, 3 and 26.0% of workers, respectively. The regularity and staging of the development of this abnormity have been established, etiology, pathogenesis and clinical significance of those remain unknown.

Plant Parts Snack--A Way to Family Involvement, Science Learning, and Nutrition

ERIC Educational Resources Information Center

Matt, Megan Mason

2008-01-01

As a teacher who loves to bring botany into her preschool classroom of 4- and 5-year-olds, the author makes edible plants a regular, popular feature of her students' environment. The author is fascinated when her students become increasingly adventurous in their tastes for vegetables the more they handle and understand plants. The author decided…

Hollowing Out: Job Loss, Job Growth and Skills for the Future. Executive Summary

ERIC Educational Resources Information Center

Halbert, Hannah; Krueger, Tim

2011-01-01

Even as unemployment in Ohio has remained high, headlines regularly feature employers lamenting the lack of qualified job applicants. Some have even suggested that a dearth of skilled workers is driving Ohio's unemployment crisis. In this report, Policy Matters Ohio uses Bureau of Labor Statistics job projections and wage data to look at whether a…

Optimized SIFTFlow for registration of whole-mount histology to reference optical images

PubMed Central

Shojaii, Rushin; Martel, Anne L.

2016-01-01

Abstract. The registration of two-dimensional histology images to reference images from other modalities is an important preprocessing step in the reconstruction of three-dimensional histology volumes. This is a challenging problem because of the differences in the appearances of histology images and other modalities, and the presence of large nonrigid deformations which occur during slide preparation. This paper shows the feasibility of using densely sampled scale-invariant feature transform (SIFT) features and a SIFTFlow deformable registration algorithm for coregistering whole-mount histology images with blockface optical images. We present a method for jointly optimizing the regularization parameters used by the SIFTFlow objective function and use it to determine the most appropriate values for the registration of breast lumpectomy specimens. We demonstrate that tuning the regularization parameters results in significant improvements in accuracy and we also show that SIFTFlow outperforms a previously described edge-based registration method. The accuracy of the histology images to blockface images registration using the optimized SIFTFlow method was assessed using an independent test set of images from five different lumpectomy specimens and the mean registration error was 0.32±0.22  mm. PMID:27774494

Qualitative analysis of feedback on functional imagery training: A novel motivational intervention for type 2 diabetes.

PubMed

Parham, Sophie C; Kavanagh, David J; Shimada, Mika; May, Jon; Andrade, Jackie

2018-03-01

Effective motivational support is needed in chronic disease management. This study was undertaken to improve a novel type 2 diabetes motivational intervention, (functional imagery training, FIT) based on participant feedback and results from a self-management randomised controlled trial. Qualitative inductive thematic analysis of semi-structured interviews. Open-ended questions on participant experiences of the FIT intervention content, process, most/least helpful features, suggestions for improvement and general feedback. Eight themes emerged. Participants thought FIT promoted autonomy and self-awareness. They found the intervention interesting and helpful in keeping their health on track through accountability provided by regular phone calls. However, boredom with repetitive use of imagery, feeling inadequately equipped to manage unhealthy cravings, and difficulty with the time commitment was reported by some. Supplementary written material was recommended. Several well-received features of FIT overlapped with those from traditional motivational interviewing. FIT sessions should ensure content is regularly adapted to new health-enhancing goals. After self-management behaviour becomes habitual, imagery practice could be restricted to challenging contexts. Provision of a written rationale and use of mindfulness for cravings is recommended. With these improvements, the impact of FIT on diabetic control may be substantially enhanced.

Transfer learning for visual categorization: a survey.

PubMed

Shao, Ling; Zhu, Fan; Li, Xuelong

2015-05-01

Regular machine learning and data mining techniques study the training data for future inferences under a major assumption that the future data are within the same feature space or have the same distribution as the training data. However, due to the limited availability of human labeled training data, training data that stay in the same feature space or have the same distribution as the future data cannot be guaranteed to be sufficient enough to avoid the over-fitting problem. In real-world applications, apart from data in the target domain, related data in a different domain can also be included to expand the availability of our prior knowledge about the target future data. Transfer learning addresses such cross-domain learning problems by extracting useful information from data in a related domain and transferring them for being used in target tasks. In recent years, with transfer learning being applied to visual categorization, some typical problems, e.g., view divergence in action recognition tasks and concept drifting in image classification tasks, can be efficiently solved. In this paper, we survey state-of-the-art transfer learning algorithms in visual categorization applications, such as object recognition, image classification, and human action recognition.

RSAT: regulatory sequence analysis tools.

PubMed

Thomas-Chollier, Morgane; Sand, Olivier; Turatsinze, Jean-Valéry; Janky, Rekin's; Defrance, Matthieu; Vervisch, Eric; Brohée, Sylvain; van Helden, Jacques

2008-07-01

The regulatory sequence analysis tools (RSAT, http://rsat.ulb.ac.be/rsat/) is a software suite that integrates a wide collection of modular tools for the detection of cis-regulatory elements in genome sequences. The suite includes programs for sequence retrieval, pattern discovery, phylogenetic footprint detection, pattern matching, genome scanning and feature map drawing. Random controls can be performed with random gene selections or by generating random sequences according to a variety of background models (Bernoulli, Markov). Beyond the original word-based pattern-discovery tools (oligo-analysis and dyad-analysis), we recently added a battery of tools for matrix-based detection of cis-acting elements, with some original features (adaptive background models, Markov-chain estimation of P-values) that do not exist in other matrix-based scanning tools. The web server offers an intuitive interface, where each program can be accessed either separately or connected to the other tools. In addition, the tools are now available as web services, enabling their integration in programmatic workflows. Genomes are regularly updated from various genome repositories (NCBI and EnsEMBL) and 682 organisms are currently supported. Since 1998, the tools have been used by several hundreds of researchers from all over the world. Several predictions made with RSAT were validated experimentally and published.

Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing.

PubMed

Rahim, Sarni Suhaila; Palade, Vasile; Shuttleworth, James; Jayne, Chrisina

2016-12-01

Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes.

A PDA study management tool (SMT) utilizing wireless broadband and full DICOM viewing capability

NASA Astrophysics Data System (ADS)

Documet, Jorge; Liu, Brent; Zhou, Zheng; Huang, H. K.; Documet, Luis

2007-03-01

During the last 4 years IPI (Image Processing and Informatics) Laboratory has been developing a web-based Study Management Tool (SMT) application that allows Radiologists, Film librarians and PACS-related (Picture Archiving and Communication System) users to dynamically and remotely perform Query/Retrieve operations in a PACS network. The users utilizing a regular PDA (Personal Digital Assistant) can remotely query a PACS archive to distribute any study to an existing DICOM (Digital Imaging and Communications in Medicine) node. This application which has proven to be convenient to manage the Study Workflow [1, 2] has been extended to include a DICOM viewing capability in the PDA. With this new feature, users can take a quick view of DICOM images providing them mobility and convenience at the same time. In addition, we are extending this application to Metropolitan-Area Wireless Broadband Networks. This feature requires Smart Phones that are capable of working as a PDA and have access to Broadband Wireless Services. With the extended application to wireless broadband technology and the preview of DICOM images, the Study Management Tool becomes an even more powerful tool for clinical workflow management.

Signs of Facial Aging in Men in a Diverse, Multinational Study: Timing and Preventive Behaviors.

PubMed

Rossi, Anthony M; Eviatar, Joseph; Green, Jeremy B; Anolik, Robert; Eidelman, Michael; Keaney, Terrence C; Narurkar, Vic; Jones, Derek; Kolodziejczyk, Julia; Drinkwater, Adrienne; Gallagher, Conor J

2017-11-01

Men are a growing patient population in aesthetic medicine and are increasingly seeking minimally invasive cosmetic procedures. To examine differences in the timing of facial aging and in the prevalence of preventive facial aging behaviors in men by race/ethnicity. Men aged 18 to 75 years in the United States, Canada, United Kingdom, and Australia rated their features using photonumeric rating scales for 10 facial aging characteristics. Impact of race/ethnicity (Caucasian, black, Asian, Hispanic) on severity of each feature was assessed. Subjects also reported the frequency of dermatologic facial product use. The study included 819 men. Glabellar lines, crow's feet lines, and nasolabial folds showed the greatest change with age. Caucasian men reported more severe signs of aging and earlier onset, by 10 to 20 years, compared with Asian, Hispanic, and, particularly, black men. In all racial/ethnic groups, most men did not regularly engage in basic, antiaging preventive behaviors, such as use of sunscreen. Findings from this study conducted in a globally diverse sample may guide clinical discussions with men about the prevention and treatment of signs of facial aging, to help men of all races/ethnicities achieve their desired aesthetic outcomes.

Tongue prints in biometric authentication: A pilot study

PubMed Central

Jeddy, Nadeem; Radhika, T; Nithya, S

2017-01-01

Background and Objectives: Biometric authentication is an important process for the identification and verification of individuals for security purposes. There are many biometric systems that are currently in use and also being researched. Tongue print is a new biometric authentication tool that is unique and cannot be easily forged because no two tongue prints are similar. The present study aims to evaluate the common morphological features of the tongue and its variations in males and females. The usefulness of alginate impression and dental cast in obtaining the lingual impression was also evaluated. Materials and Methods: The study sample included twenty participants. The participants were subjected to visual examination following which digital photographs of the dorsal surface of the tongue were taken. Alginate impressions of the tongue were made, and casts were prepared using dental stone. The photographs and the casts were analyzed by two observers separately for the surface morphology including shape, presence or absence of fissures and its pattern of distribution. Three reference points were considered to determine the shape of the tongue. Results: The most common morphological feature on the dorsum of the tongue was the presence of central fissures. Multiple vertical fissures were observed in males whereas single vertical fissure was a common finding in females. The fissures were predominantly shallow in males and deep in females. The tongue was predominantly U shaped in males and females. V-shaped tongue was observed in 25% of females. Conclusion: Tongue prints are useful in biometric authentication. The methodology used in the study is simple, easy and can be adopted by dentists on a regular basis. However, large-scale studies are required to validate the results and also identify other features of the tongue that can be used in forensics and biometric authentication process. PMID:28479712

Tongue prints in biometric authentication: A pilot study.

PubMed

Jeddy, Nadeem; Radhika, T; Nithya, S

2017-01-01

Biometric authentication is an important process for the identification and verification of individuals for security purposes. There are many biometric systems that are currently in use and also being researched. Tongue print is a new biometric authentication tool that is unique and cannot be easily forged because no two tongue prints are similar. The present study aims to evaluate the common morphological features of the tongue and its variations in males and females. The usefulness of alginate impression and dental cast in obtaining the lingual impression was also evaluated. The study sample included twenty participants. The participants were subjected to visual examination following which digital photographs of the dorsal surface of the tongue were taken. Alginate impressions of the tongue were made, and casts were prepared using dental stone. The photographs and the casts were analyzed by two observers separately for the surface morphology including shape, presence or absence of fissures and its pattern of distribution. Three reference points were considered to determine the shape of the tongue. The most common morphological feature on the dorsum of the tongue was the presence of central fissures. Multiple vertical fissures were observed in males whereas single vertical fissure was a common finding in females. The fissures were predominantly shallow in males and deep in females. The tongue was predominantly U shaped in males and females. V-shaped tongue was observed in 25% of females. Tongue prints are useful in biometric authentication. The methodology used in the study is simple, easy and can be adopted by dentists on a regular basis. However, large-scale studies are required to validate the results and also identify other features of the tongue that can be used in forensics and biometric authentication process.

Polycystic ovarian morphology and the diagnosis of polycystic ovary syndrome: redefining threshold levels for follicle count and serum anti-Müllerian hormone using cluster analysis.

PubMed

Lie Fong, S; Laven, J S E; Duhamel, A; Dewailly, D

2017-08-01

Can cluster analysis be used to differentiate between normo-ovulatory women with normal ovaries and normo-ovulatory women with polycystic ovarian morphology (PCOM) in a non-subjective manner? Cluster analysis can be used to accurately and non-subjectively differentiate between normo-ovulatory women with normal ovaries and normo-ovulatory women with PCOM. Currently, PCOM is diagnosed using a fixed threshold level, i.e. 12 or more follicles per ovary, and is one of the diagnostic criteria of polycystic ovary syndrome (PCOS). However, PCOM is also encountered in normo-ovulatory women, suggesting that it could just represent a normal variant. On the other hand, recent studies have shown subtle endocrine abnormalities in women with isolated PCOM that resemble those found in women with PCOS. Because of the strong correlation between anti-Müllerian hormone (AMH) and follicle number, a high serum AMH level has been proposed as a surrogate marker for PCOM and could, therefore, be integrated in the diagnostic classifications for PCOS. This was a retrospective observational cohort study. Original cohorts had been recruited for previous studies between 1998 and 2010. Two hundred ninety-seven regularly cycling women and 700 women with PCOS were eligible for inclusion. Cluster analysis was performed in 297 regularly cycling women. After exclusion of 'PCOM' clusters, each 'non-PCOM' cluster (young, n = 118 and old, n = 100) was included in the construction of a receiver operating characteristics curve to test the diagnostic performance of follicle number per ovary (FNPO) and serum AMH in discriminating similarly aged full-blown PCOS patients (n = 411 and 237, respectively) from normal regularly cycling non-PCOM women. The optimal number of clusters was four; age was the most important classifying variable, followed by the FNPO and serum AMH. Two distinct clusters of normo-ovulatory women with PCOM were isolated and differed solely by age, i.e. 'young' and 'old'. Both 'PCOM' clusters had their similarly aged counterpart of 'non-PCOM' clusters. Likewise, two clusters comprised women younger than 30 years, with (n = 28, 'PCOM regularly cycling women') or without (n = 118, 'normal regularly cycling women') features of PCOM (increased FNPO and/or serum AMH). The two other clusters in older women could be labelled 'normal regularly cycling women' or 'PCOM regularly cycling women' (n = 100 and 51, respectively). The prevalence of PCOM was significantly greater in old than in young regularly cycling women controls. In the young population, after exclusion of the 'PCOM regularly cycling women', the diagnostic performance of AMH, expressed by area under the curve (AUC) (AUC = 0.903; CI (0.876-0.930)) to differentiate PCOS women from normal regularly cycling women was similar to that using the FNPO (AUC = 0.915, CI (0.891-0.940)) (P = 0.25), confirming results from earlier studies. In the old population, the diagnostic performance of AMH was greater than that of FNPO (AUCs = 0.948 (0.927-0.970) vs 0.874 (0.836-0.912), respectively, P = 0.00035). Cut-off levels of AMH and antral follicle count distinguishing regularly cycling non-PCOM women from PCOS women were higher in young women than in older women. Data of normal women were obtained from earlier studies, aiming to measure normal endocrine values. Apparently, the strong effect of age in cluster analysis revealed a dichotomy in the age distribution among the cohort of regularly cycling women included. This was involuntary since in none of the original studies, eligibility was limited by age and there was considerable overlap in age ranges of the cohorts. Transvaginal ultrasound was performed using a 6.5-8 mHz probe and our data confirm that this threshold level for FNPO is still valid if using such probe frequencies, although the use of devices with a maximum frequency lower than 8 mHz has become obsolete. Obviously, newer ultrasound scanner using higher transducer frequency will facilitate the detection of more follicles. Our data support the use of AMH as a surrogate for ultrasound to define PCOM, which is one of the three items of the Rotterdam classification. They also show that age should be taken into account to define the optimal threshold. The fact that the prevalence of PCOM was increased in the older regularly cycling women, may be due to 'attenuated' PCOS, a phenomenon that has been described in ageing women with PCOS. These women might have had anovulatory cycles in the past and have become ovulatory with increasing age, and were, therefore, eligible for this study. However, since most women included at older age have had spontaneous pregnancies in the past, PCOM at older age may be associated with a subclinical form of PCOS, which may also be present in young regularly cycling women. No funding was received for this study. J.S.E.L. has received grants and support from Ferring, MSD, Organon, Merck-Serono, Schering Plough and Serono during recruitment and analysis of data for this study. S.L.F., A.D. and D.D. do not have any conflict of interest. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

3D shape decomposition and comparison for gallbladder modeling

NASA Astrophysics Data System (ADS)

Huang, Weimin; Zhou, Jiayin; Liu, Jiang; Zhang, Jing; Yang, Tao; Su, Yi; Law, Gim Han; Chui, Chee Kong; Chang, Stephen

2011-03-01

This paper presents an approach to gallbladder shape comparison by using 3D shape modeling and decomposition. The gallbladder models can be used for shape anomaly analysis and model comparison and selection in image guided robotic surgical training, especially for laparoscopic cholecystectomy simulation. The 3D shape of a gallbladder is first represented as a surface model, reconstructed from the contours segmented in CT data by a scheme of propagation based voxel learning and classification. To better extract the shape feature, the surface mesh is further down-sampled by a decimation filter and smoothed by a Taubin algorithm, followed by applying an advancing front algorithm to further enhance the regularity of the mesh. Multi-scale curvatures are then computed on the regularized mesh for the robust saliency landmark localization on the surface. The shape decomposition is proposed based on the saliency landmarks and the concavity, measured by the distance from the surface point to the convex hull. With a given tolerance the 3D shape can be decomposed and represented as 3D ellipsoids, which reveal the shape topology and anomaly of a gallbladder. The features based on the decomposed shape model are proposed for gallbladder shape comparison, which can be used for new model selection. We have collected 19 sets of abdominal CT scan data with gallbladders, some shown in normal shape and some in abnormal shapes. The experiments have shown that the decomposed shapes reveal important topology features.

Optimal Symmetric Multimodal Templates and Concatenated Random Forests for Supervised Brain Tumor Segmentation (Simplified) with ANTsR.

PubMed

Tustison, Nicholas J; Shrinidhi, K L; Wintermark, Max; Durst, Christopher R; Kandel, Benjamin M; Gee, James C; Grossman, Murray C; Avants, Brian B

2015-04-01

Segmenting and quantifying gliomas from MRI is an important task for diagnosis, planning intervention, and for tracking tumor changes over time. However, this task is complicated by the lack of prior knowledge concerning tumor location, spatial extent, shape, possible displacement of normal tissue, and intensity signature. To accommodate such complications, we introduce a framework for supervised segmentation based on multiple modality intensity, geometry, and asymmetry feature sets. These features drive a supervised whole-brain and tumor segmentation approach based on random forest-derived probabilities. The asymmetry-related features (based on optimal symmetric multimodal templates) demonstrate excellent discriminative properties within this framework. We also gain performance by generating probability maps from random forest models and using these maps for a refining Markov random field regularized probabilistic segmentation. This strategy allows us to interface the supervised learning capabilities of the random forest model with regularized probabilistic segmentation using the recently developed ANTsR package--a comprehensive statistical and visualization interface between the popular Advanced Normalization Tools (ANTs) and the R statistical project. The reported algorithmic framework was the top-performing entry in the MICCAI 2013 Multimodal Brain Tumor Segmentation challenge. The challenge data were widely varying consisting of both high-grade and low-grade glioma tumor four-modality MRI from five different institutions. Average Dice overlap measures for the final algorithmic assessment were 0.87, 0.78, and 0.74 for "complete", "core", and "enhanced" tumor components, respectively.

Optimal behaviour can violate the principle of regularity.

PubMed

Trimmer, Pete C

2013-07-22

Understanding decisions is a fundamental aim of behavioural ecology, psychology and economics. The regularity axiom of utility theory holds that a preference between options should be maintained when other options are made available. Empirical studies have shown that animals violate regularity but this has not been understood from a theoretical perspective, such decisions have therefore been labelled as irrational. Here, I use models of state-dependent behaviour to demonstrate that choices can violate regularity even when behavioural strategies are optimal. I also show that the range of conditions over which regularity should be violated can be larger when options do not always persist into the future. Consequently, utility theory--based on axioms, including transitivity, regularity and the independence of irrelevant alternatives--is undermined, because even alternatives that are never chosen by an animal (in its current state) can be relevant to a decision.

Editorial.

PubMed

Al-Deeb, Saleh M; Khan, Sonia

2009-01-01

Neurosciences continues to be the leading journal for Neurosciences in Saudi Arabia and the Middle East. In January 2007, Neurosciences was indexed by Thomson ISI in Science Citation Index Expanded online at ISI Web of KnowledgeSM and Neurosciences Citation Index. Since then a significantly increased volume of scientific articles continues to be submitted to the journal by enthusiastic authors, a fact that enriches the scientific contents of the journal. In 2008, we had a total number of website hits of 495,625 with a monthly average of 41,000. We received a total of 155 manuscripts, with a monthly average of 13 and an average rejection rate of 29%. From these, we published a total of 100 articles, totaling 523 pages for the entire volume. Forty-nine percent of these were original articles. Fifty-eight percent of published articles were from the Eastern Mediterranean Region (EMR), with 30% from KSA, 5% from the Gulf, and 23% from other Arab and EMR countries. The remaining 42% of published articles we received from Canada, India, Japan, Malaysia, and Turkey. The average time from received to acceptance of original articles was 4 months and 4.9 months for acceptance to publication. Reasons for rejection included unrelated topics, poor contents, or duplicate publication. In addition to our 4 regular issues in 2008, we published a supplement of abstracts presented at the 16th Saudi Neuroscience Symposium. We would like to thank the Editorial and Advisory Board Members for their significant contribution to maintain the standards of Neuroscience and looking forward to their important continued role in achieving our goals for 2009. In 2009, we aim to increase the number of issues to meet the increased load of manuscripts. Our objective is to enrich the scientific Neuroscience material presented by the journal with important topic reviews and regular neuroscience quizzes to achieve PubMed indexing. We will continue to promote our new web-based manuscript submission interface; strive to reduce the time from received to acceptance and acceptance to publication to no more than 3 to 4 months each; attend regional conferences, and participate in academic activities to encourage submission of high quality articles; encourage editorial board members to solicit potential authors from conferences; and commission our best reviewers to write good articles and encourage editorial board members to contribute material for a regular editorial feature on topical issues. We would also like to introduce a number of new features, such as highlights from international neuroscience meetings, regular basic neuroscience review articles, and 5 MCQs on basic/clinical neuroscience in each issue. These features will greatly enhance the journal and make it more attractive to trainees and board residents. However, their success will rely heavily on the contributions that we receive. The strict check for duplicate publication and plagiarism will continue, and if detected appropriate action will be taken in accordance with international guidelines. A small number of articles were rejected last year due to extensive plagiarism and duplicate publication. We hope all our readers benefitted from the introduction of the Arabic abstracts, and enjoyed the new look and the feel of the journal. We extend our sincerest thanks to our authors, readers, reviewers, and board members, and wish all a successful year.

Forming Effective Partnerships to Facilitate Inclusion of Students with Vision Impairments: Perceptions of a Regular Classroom Teacher and an Itinerant Teacher

ERIC Educational Resources Information Center

Sharma, Umesh; Moore, Dennis; Furlonger, Brett; King, Brian Smyth; Kaye, Linda; Constantinou, Olga

2010-01-01

This qualitative study reports on the perceptions of a regular classroom teacher and an itinerant teacher about the challenges they faced in including a student with vision impairment in regular school in New South Wales, Australia. Some of the common strategies employed by both these teachers to address these challenges are discussed. (Contains 1…

IMMUNISATION TRAINING NEEDS IN MALAWI.

PubMed

Tsega, A Y; Hausi, H T; Steinglass, R; Chirwa, G Z

2014-09-01

The Malawi Ministry of Health (MOH) and its immunisation partners conducted a training needs assessment in May 2013 to assess the current status of immunisation training programmemes in health training institutions, to identify unmet training needs, and to recommend possible solutions for training of health workers on a regular basis. A cross-sectional, descriptive study. Health training institutions in Malawi, a developing country that does not regularly update its curricula to include new vaccines and management tools, nor train healthcare workers on a regular basis. Researchers interviewed Malawi's central immunisation manager, three zonal immunisation officers, six district officers, 12 health facility immunisation coordinators, and eight principals of training institutions. All health training institutions in Malawi include immunisation in their preservice training curricula. However, the curriculum is not regularly updated; thus, the graduates are not well equipped to provide quality services. In addition, the duration of the training curriculum is inadequate, and in-service training sessions for managers and service providers are conducted only on an ad hoc basis. All levels of Malawi's health system have not met sufficient training needs for providing immunisations, and the health training institutions teach their students with outdated materials. It is recommended that the training institutions update their training curricula regularly and the service providers are trained on a regular basis.

Computer vision applications for coronagraphic optical alignment and image processing.

PubMed

Savransky, Dmitry; Thomas, Sandrine J; Poyneer, Lisa A; Macintosh, Bruce A

2013-05-10

Modern coronagraphic systems require very precise alignment between optical components and can benefit greatly from automated image processing. We discuss three techniques commonly employed in the fields of computer vision and image analysis as applied to the Gemini Planet Imager, a new facility instrument for the Gemini South Observatory. We describe how feature extraction and clustering methods can be used to aid in automated system alignment tasks, and also present a search algorithm for finding regular features in science images used for calibration and data processing. Along with discussions of each technique, we present our specific implementation and show results of each one in operation.

A Locally Adaptive Regularization Based on Anisotropic Diffusion for Deformable Image Registration of Sliding Organs

PubMed Central

Pace, Danielle F.; Aylward, Stephen R.; Niethammer, Marc

2014-01-01

We propose a deformable image registration algorithm that uses anisotropic smoothing for regularization to find correspondences between images of sliding organs. In particular, we apply the method for respiratory motion estimation in longitudinal thoracic and abdominal computed tomography scans. The algorithm uses locally adaptive diffusion tensors to determine the direction and magnitude with which to smooth the components of the displacement field that are normal and tangential to an expected sliding boundary. Validation was performed using synthetic, phantom, and 14 clinical datasets, including the publicly available DIR-Lab dataset. We show that motion discontinuities caused by sliding can be effectively recovered, unlike conventional regularizations that enforce globally smooth motion. In the clinical datasets, target registration error showed improved accuracy for lung landmarks compared to the diffusive regularization. We also present a generalization of our algorithm to other sliding geometries, including sliding tubes (e.g., needles sliding through tissue, or contrast agent flowing through a vessel). Potential clinical applications of this method include longitudinal change detection and radiotherapy for lung or abdominal tumours, especially those near the chest or abdominal wall. PMID:23899632

A locally adaptive regularization based on anisotropic diffusion for deformable image registration of sliding organs.

PubMed

Pace, Danielle F; Aylward, Stephen R; Niethammer, Marc

2013-11-01

We propose a deformable image registration algorithm that uses anisotropic smoothing for regularization to find correspondences between images of sliding organs. In particular, we apply the method for respiratory motion estimation in longitudinal thoracic and abdominal computed tomography scans. The algorithm uses locally adaptive diffusion tensors to determine the direction and magnitude with which to smooth the components of the displacement field that are normal and tangential to an expected sliding boundary. Validation was performed using synthetic, phantom, and 14 clinical datasets, including the publicly available DIR-Lab dataset. We show that motion discontinuities caused by sliding can be effectively recovered, unlike conventional regularizations that enforce globally smooth motion. In the clinical datasets, target registration error showed improved accuracy for lung landmarks compared to the diffusive regularization. We also present a generalization of our algorithm to other sliding geometries, including sliding tubes (e.g., needles sliding through tissue, or contrast agent flowing through a vessel). Potential clinical applications of this method include longitudinal change detection and radiotherapy for lung or abdominal tumours, especially those near the chest or abdominal wall.

Surface Changes in Chryse Planitia

NASA Technical Reports Server (NTRS)

1979-01-01

At the conclusion of the Viking Continuation Mission (May to November, 1978), all four cameras on the Viking Landers - two on each spacecraft - continued to function normally. During the two and one-half years since the landers touched down on Mars, images totaled 2,255 for Viking Lander 1 and 2,016 for Viking Lander 2. The surface around the landers was completely photographed by the end of 1976; subsequent images acquired during 1977-1978 have concentrated on searching for changes in the scene - changes which can be used to infer both the types of erosive processes which modify the landscape around the landers and the rates at which these processes may occur. The major surface changes have included the water-ice snow seen by Lander 2 during the winter at Utopia Planitia, and a thin dust layer deposited at both sites during the dust storms of 1977. The most recently identified change occurred at Chryse Planitia between VL-1 sols 767 (Sept. 16, 1978) and 771 (Sept. 20, 1978) as seen in the lower photo. Picture at top, selected to show similar lighting conditions, was taken during sol 25 (August 15, 1976). The change (A) appears as a small circle-like formation on the side of a drift in the lee, or downwind, side of Whale Rock. This is believed to have been a small-scale landslide of an unstable dust layer which had accumulated behind the rock. Interpretation of this feature would be difficult without an earlier change (B) near Big Joe, a slump which occurred between sols 74 and 183. The new slump is approximately 25- 35 meters from the lander, and just under a meter across. The slumping probably was initiated by the daily heating and cooling of the surface by solar radiation. More importantly, it is now believed that, based on the repeated occurrence of such slumping features, a dust layer which overlies the surface may in fact be redistributed fairly regularly during periods of high wind activity. There are no obvious indications of fossil slump features, therefore similar features must be destroyed on a regular basis. After the end of February, when Viking operations essentially terminate, Lander 1 will continue preselected observations over a period of possibly up to 10 years, following the instructions stored in its computer memory. Earth commands will be required only to initiate data transmission to Earth. During this time, it is now anticipated that one of the yearly planetwide global dust storms may reach an intensity necessary to shift the dust cover around the lander significantly.

A Cross-Sectional Investigation of the Importance of Park Features for Promoting Regular Physical Activity in Parks.

PubMed

Costigan, Sarah A; Veitch, Jenny; Crawford, David; Carver, Alison; Timperio, Anna

2017-11-02

Parks in the US and Australia are generally underutilised, and park visitors typically engage in low levels of physical activity (PA). Better understanding park features that may encourage visitors to be active is important. This study examined the perceived importance of park features for encouraging park-based PA and examined differences by sex, age, parental-status and participation in PA. Cross-sectional surveys were completed by local residents ( n = 2775) living near two parks (2013/2015). Demographic variables, park visitation and leisure-time PA were self-reported, respondents rated the importance of 20 park features for encouraging park-based PA in the next fortnight. Chi-square tests of independence examined differences in importance of park features for PA among sub-groups of local residents (sex, age, parental-status, PA). Park features ranked most important for park-based PA were: well maintained (96.2%), feel safe (95.4%), relaxing atmosphere (91.2%), easy to get to (91.7%), and shady trees (90.3%). All subgroups ranked 'well maintained' as most important. Natural and built environment features of parks are important for promoting adults' park-based PA, and should be considered in park (re)design.

Discriminant analysis for fast multiclass data classification through regularized kernel function approximation.

PubMed

Ghorai, Santanu; Mukherjee, Anirban; Dutta, Pranab K

2010-06-01

In this brief we have proposed the multiclass data classification by computationally inexpensive discriminant analysis through vector-valued regularized kernel function approximation (VVRKFA). VVRKFA being an extension of fast regularized kernel function approximation (FRKFA), provides the vector-valued response at single step. The VVRKFA finds a linear operator and a bias vector by using a reduced kernel that maps a pattern from feature space into the low dimensional label space. The classification of patterns is carried out in this low dimensional label subspace. A test pattern is classified depending on its proximity to class centroids. The effectiveness of the proposed method is experimentally verified and compared with multiclass support vector machine (SVM) on several benchmark data sets as well as on gene microarray data for multi-category cancer classification. The results indicate the significant improvement in both training and testing time compared to that of multiclass SVM with comparable testing accuracy principally in large data sets. Experiments in this brief also serve as comparison of performance of VVRKFA with stratified random sampling and sub-sampling.

The Regularity of Optimal Irrigation Patterns

NASA Astrophysics Data System (ADS)

Morel, Jean-Michel; Santambrogio, Filippo

2010-02-01

A branched structure is observable in draining and irrigation systems, in electric power supply systems, and in natural objects like blood vessels, the river basins or the trees. Recent approaches of these networks derive their branched structure from an energy functional whose essential feature is to favor wide routes. Given a flow s in a river, a road, a tube or a wire, the transportation cost per unit length is supposed in these models to be proportional to s α with 0 < α < 1. The aim of this paper is to prove the regularity of paths (rivers, branches,...) when the irrigated measure is the Lebesgue density on a smooth open set and the irrigating measure is a single source. In that case we prove that all branches of optimal irrigation trees satisfy an elliptic equation and that their curvature is a bounded measure. In consequence all branching points in the network have a tangent cone made of a finite number of segments, and all other points have a tangent. An explicit counterexample disproves these regularity properties for non-Lebesgue irrigated measures.

Normetex Pump Alternatives Study

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

Clark, Elliot A.

2013-04-25

A mainstay pump for tritium systems, the Normetex scroll pump, is currently unavailable because the Normetex company went out of business. This pump was an all-metal scroll pump that served tritium processing facilities very well. Current tritium system operators are evaluating replacement pumps for the Normetex pump and for general used in tritium service. An all-metal equivalent alternative to the Normetex pump has not yet been identified. 1. The ideal replacement tritium pump would be hermetically sealed and contain no polymer components or oils. Polymers and oils degrade over time when they contact ionizing radiation. 2. Halogenated polymers (containing fluorine,more » chlorine, or both) and oils are commonly found in pumps. These materials have many properties that surpass those of hydrocarbon-based polymers and oils, including thermal stability (higher operating temperature) and better chemical resistance. Unfortunately, they are less resistant to degradation from ionizing radiation than hydrocarbon-based materials (in general). 3. Polymers and oils can form gaseous, condensable (HF, TF), liquid, and solid species when exposed to ionizing radiation. For example, halogenated polymers form HF and HCl, which are extremely corrosive upon reaction with water. If a pump containing polymers or oils must be used in a tritium system, the system must be designed to be able to process the unwanted by-products. Design features to mitigate degradation products include filters and chemical or physical traps (eg. cold traps, oil traps). 4. Polymer components can work in tritium systems, but must be replaced regularly. Polymer components performance should be monitored or be regularly tested, and regular replacement of components should be viewed as an expected normal event. A radioactive waste stream must be established to dispose of used polymer components and oil with an approved disposal plan developed based on the facility location and its regulators. Polymers have varying resistances to ionizing radiation - aromatic polymers such as polyimide Vespel (TM) and the elastomer EPDM (ethylene propylene diene monomer) have been found to be more resistant to degradation in tritium than other polymers. This report presents information to help select replacement pumps for Normetex pumps in tritium systems. Several pumps being considered as Normetex replacement pumps are discussed.« less

Patient reports of the quality of care in community health centers: the importance of having a regular provider.

PubMed

Beal, Anne; Hernandez, Susan

2010-05-01

To examine the importance of having a regular provider in community health centers (CHCs) for high quality care. Analyses of a national survey-the Commonwealth Fund 2006 Health care Quality Survey-among patients with a private doctor's (PMD) office (n=1,743) or CHC (n=275) as their regular source of care. Outcomes include prevention measures, and measures of patient experience. Patients at CHCs are less likely than patients who use a PMD to report having a regular doctor (53% vs. 95%, p

Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy

NASA Astrophysics Data System (ADS)

Valdes, Gilmer; Solberg, Timothy D.; Heskel, Marina; Ungar, Lyle; Simone, Charles B., II

2016-08-01

To develop a patient-specific ‘big data’ clinical decision tool to predict pneumonitis in stage I non-small cell lung cancer (NSCLC) patients after stereotactic body radiation therapy (SBRT). 61 features were recorded for 201 consecutive patients with stage I NSCLC treated with SBRT, in whom 8 (4.0%) developed radiation pneumonitis. Pneumonitis thresholds were found for each feature individually using decision stumps. The performance of three different algorithms (Decision Trees, Random Forests, RUSBoost) was evaluated. Learning curves were developed and the training error analyzed and compared to the testing error in order to evaluate the factors needed to obtain a cross-validated error smaller than 0.1. These included the addition of new features, increasing the complexity of the algorithm and enlarging the sample size and number of events. In the univariate analysis, the most important feature selected was the diffusion capacity of the lung for carbon monoxide (DLCO adj%). On multivariate analysis, the three most important features selected were the dose to 15 cc of the heart, dose to 4 cc of the trachea or bronchus, and race. Higher accuracy could be achieved if the RUSBoost algorithm was used with regularization. To predict radiation pneumonitis within an error smaller than 10%, we estimate that a sample size of 800 patients is required. Clinically relevant thresholds that put patients at risk of developing radiation pneumonitis were determined in a cohort of 201 stage I NSCLC patients treated with SBRT. The consistency of these thresholds can provide radiation oncologists with an estimate of their reliability and may inform treatment planning and patient counseling. The accuracy of the classification is limited by the number of patients in the study and not by the features gathered or the complexity of the algorithm.

Intramolecular triple helix as a model for regular polyribonucleotide (CAA)(n).

PubMed

Efimov, Alexander V; Spirin, Alexander S

2009-10-09

The regular (CAA)(n) polyribonucleotide, as well as the omega leader sequence containing (CAA)-rich core, have recently been shown to form cooperatively melted and compact structures. In this report, we propose a structural model for the (CAA)(n) sequence in which the polyribonucleotide chain is folded upon itself, so that it forms an intramolecular triple helix. The triple helix is stabilized by hydrogen bonding between bases thus forming coplanar triads, and by stacking interactions between the base triads. A distinctive feature of the proposed triple helix is that it does not contain the canonical double-helix elements. The difference from the known triple helices is that Watson-Crick hydrogen bond pairings do not take place in the interactions between the bases within the base triads.

Helicity moduli of three-dimensional dilute XY models

NASA Astrophysics Data System (ADS)

Garg, Anupam; Pandit, Rahul; Solla, Sara A.; Ebner, C.

1984-07-01

The helicity moduli of various dilute, classical XY models on three-dimensional lattices are studied with a view to understanding some aspects of the superfluidity of 4He in Vycor glass. A spinwave calculation is used to obtain the low-temperature helicity modulus of a regularly-diluted XY model. A similar calculation is performed for the randomly bond-diluted and site-diluted XY models in the limit of low dilution. A Monte Carlo simulation is used to obtain the helicity modulus of the randomly bond-diluted XY model over a wide range of temperature and dilution. It is found that the randomly diluted models do agree and the regularly diluted model does not agree with certain experimentally found features of the variation in superfluid fraction with coverage of 4He in Vycor glass.

Energy Extraction from a Slider-Crank Wave Energy under Irregular Wave Conditions: Preprint

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

Sang, Yuanrui; Karayaka, H. Bora; Yan, Yanjun

2015-08-24

A slider-crank wave energy converter (WEC) is a novel energy conversion device. It converts wave energy into electricity at a relatively high efficiency, and it features a simple structure. Past analysis on this particular WEC has been done under regular sinusoidal wave conditions, and suboptimal energy could be achieved. This paper presents the analysis of the system under irregular wave conditions; a time-domain hydrodynamics model is adopted and a rule-based control methodology is introduced to better serve the irregular wave conditions. Results from the simulations show that the performance of the system under irregular wave conditions is different from thatmore » under regular sinusoidal wave conditions, but a reasonable amount of energy can still be extracted.« less

Energy Extraction from a Slider-Crank Wave Energy Converter under Irregular Wave Conditions

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

Sang, Yuanrui; Karayaka, H. Bora; Yan, Yanjun

2015-10-19

A slider-crank wave energy converter (WEC) is a novel energy conversion device. It converts wave energy into electricity at a relatively high efficiency, and it features a simple structure. Past analysis on this particular WEC has been done under regular sinusoidal wave conditions, and suboptimal energy could be achieved. This paper presents the analysis of the system under irregular wave conditions; a time-domain hydrodynamics model is adopted and a rule-based control methodology is introduced to better serve the irregular wave conditions. Results from the simulations show that the performance of the system under irregular wave conditions is different from thatmore » under regular sinusoidal wave conditions, but a reasonable amount of energy can still be extracted.« less

The dynamics of innovation through the expansion in the adjacent possible

NASA Astrophysics Data System (ADS)

Tria, F.

2016-03-01

The experience of something new is part of our daily life. At different scales, innovation is also a crucial feature of many biological, technological and social systems. Recently, large databases witnessing human activities allowed the observation that novelties -such as the individual process of listening a song for the first time- and innovation processes -such as the fixation of new genes in a population of bacteria- share striking statistical regularities. We here indicate the expansion into the adjacent possible as a very general and powerful mechanism able to explain such regularities. Further, we will identify statistical signatures of the presence of the expansion into the adjacent possible in the analyzed datasets, and we will show that our modeling scheme is able to predict remarkably well these observations.

On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.

PubMed

Mizutani, Eiji; Demmel, James W

2003-01-01

This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).

Regularized iterative integration combined with non-linear diffusion filtering for phase-contrast x-ray computed tomography.

PubMed

Burger, Karin; Koehler, Thomas; Chabior, Michael; Allner, Sebastian; Marschner, Mathias; Fehringer, Andreas; Willner, Marian; Pfeiffer, Franz; Noël, Peter

2014-12-29

Phase-contrast x-ray computed tomography has a high potential to become clinically implemented because of its complementarity to conventional absorption-contrast.In this study, we investigate noise-reducing but resolution-preserving analytical reconstruction methods to improve differential phase-contrast imaging. We apply the non-linear Perona-Malik filter on phase-contrast data prior or post filtered backprojected reconstruction. Secondly, the Hilbert kernel is replaced by regularized iterative integration followed by ramp filtered backprojection as used for absorption-contrast imaging. Combining the Perona-Malik filter with this integration algorithm allows to successfully reveal relevant sample features, quantitatively confirmed by significantly increased structural similarity indices and contrast-to-noise ratios. With this concept, phase-contrast imaging can be performed at considerably lower dose.

Basic Strategies for Mainstream Integration.

ERIC Educational Resources Information Center

Lawrence, Patrick A.

1988-01-01

Guidelines for effectively integrating learning-disabled or behavior problem students into regular classrooms are discussed. They include meetings between regular and special education teachers, class rules, discipline, clear directions, individualized instruction, direct instruction for skill acquisition, peer tutoring, structured activities,…

Time-varying spectral analysis revealing differential effects of sevoflurane anaesthesia: non-rhythmic-to-rhythmic ratio.

PubMed

Lin, Y-T; Wu, H-T; Tsao, J; Yien, H-W; Hseu, S-S

2014-02-01

Heart rate variability (HRV) may reflect various physiological dynamics. In particular, variation of R-R peak interval (RRI) of electrocardiography appears regularly oscillatory in deeper levels of anaesthesia and less regular in lighter levels of anaesthesia. We proposed a new index, non-rhythmic-to-rhythmic ratio (NRR), to quantify this feature and investigated its potential to estimate depth of anaesthesia. Thirty-one female patients were enrolled in this prospective study. The oscillatory pattern transition of RRI was visualised by the time-varying power spectrum and quantified by NRR. The prediction of anaesthetic events, including skin incision, first reaction of motor movement during emergence period, loss of consciousness (LOC) and return of consciousness (ROC) by NRR were evaluated by serial prediction probability (PK ) analysis; the ability to predict the decrease of effect-site sevoflurane concentration was also evaluated. The results were compared with Bispectral Index (BIS). NRR well-predicted first reaction (PK  > 0.90) 30 s ahead, earlier than BIS and significantly better than HRV indices. NRR well-correlated with sevoflurane concentration, although its correlation was inferior to BIS, while HRV indices had no such correlation. BIS indicated LOC and ROC best. Our findings suggest that NRR provides complementary information to BIS regarding the differential effects of anaesthetics on the brain, especially the subcortical motor activity. © 2014 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Arrays of strongly coupled atoms in a one-dimensional waveguide

NASA Astrophysics Data System (ADS)

Ruostekoski, Janne; Javanainen, Juha

2017-09-01

We study the cooperative optical coupling between regularly spaced atoms in a one-dimensional waveguide using decompositions to subradiant and super-radiant collective excitation eigenmodes, direct numerical solutions, and analytical transfer-matrix methods. We illustrate how the spectrum of transmitted light through the waveguide, including the emergence of narrow Fano resonances, can be understood by the resonance features of the eigenmodes. We describe a method based on super-radiant and subradiant modes to engineer the optical response of the waveguide and to store light. The stopping of light is obtained by transferring an atomic excitation to a subradiant collective mode with the zero radiative resonance linewidth by controlling the level shift of an atom in the waveguide. Moreover, we obtain an exact analytic solution for the transmitted light through the waveguide for the case of a regular lattice of atoms and provide a simple description of how the light transmission may present large resonance shifts when the lattice spacing is close, but not exactly equal, to half of the wavelength of the light. Experimental imperfections such as fluctuations of the positions of the atoms and loss of light from the waveguide are easily quantified in the numerical simulations, which produce the natural result that the optical response of the atomic array tends toward the response of a gas with random atomic positions.

Time and its uses in accounts of conditional discharge in forensic psychiatry.

PubMed

Coffey, Michael

2013-11-01

Time is a recurring feature of storied accounts of health and social care. This article addresses the use of time in accounts of conditionally discharged patients and workers in forensic psychiatry. This study contributes new knowledge about time and its uses by a seldom heard group. An analysis of time-relevant discourse taken from 59 in-depth interviews with patients and their workers is provided to show regularities and discontinuities in schedules of post-discharge supervision in community living. Regularities included timed phases for achieving discretionary permission for greater liberty from services. Discontinuities indicate mismatches between hospital and community time and patient and professional time. Benchmarking by patients is an important resource and allows comparisons and measurements of stages in the discharge process. The discharged patients showed awareness of deviance and implicated time as an important resource in claiming ordinary identities. The participants produced progressive stories to show their incremental movement towards recovery and, ultimately, establish their non-deviant identities. The workers use time as just one part of a complex display of professional judgement of continued risk status. Fixed periods of elapsed time are necessary but not sufficient criteria for workers to reduce surveillance. Time remains a useful resource for patients to chart their way towards more routine identities. © 2013 The Author. Sociology of Health & Illness © 2013 Foundation for the Sociology of Health & Illness/John Wiley & Sons Ltd.

Recent advances in management of alkaptonuria (invited review; best practice article).

PubMed

Ranganath, Lakshminarayan R; Jarvis, Jonathan C; Gallagher, James A

2013-05-01

Alkaptonuria (AKU) is an autosomal recessive condition arising as a result of a genetic deficiency of the enzyme homogentisate 1,2 dioxygenase and characterised by accumulation of homogentisic acid (HGA). Oxidative conversion of HGA leads to production of a melanin-like polymer in a process termed ochronosis. The binding of ochronotic pigment to the connective tissues of the body leads to multisystem disorder dominated by premature severe spondylo-arthropathy. Other systemic features include stones (renal, prostatic, salivary, gall bladder), renal damage/failure, osteopenia/fractures, ruptures of tendons/muscle/ligaments, respiratory compromise, hearing loss and aortic valve disease. Detection of these features requires systematic investigation. Treatment in AKU patients is palliative and unsatisfactory. Ascorbic acid, low protein diet and physiotherapy have been tried but do not alter the underlying metabolic defect. Regular surveillance to detect and treat complications early is important. Palliative pain management is a crucial issue in AKU. Timely spinal surgery and arthroplasty are the major treatment approaches at present. A potential disease modifying drug, nitisinone, inhibits 4-hydroxy-phenyl-pyruvate-dioxygenase and decreases formation of HGA and could prevent or slow the progression of disease in AKU. If nitisinone therapy is able to complement the biochemical 'cure' with improved outcomes, it will completely alter the way we approach the management of this disease. Greater efforts to improve recognition and registration of the disease will be worthwhile. Improved laboratory diagnostics to monitor the tyrosine metabolic pathway that includes plasma metabolites including tyrosine to monitor efficacy, toxicity and safety postnitisinone will also be required.

Long-Term Exercise Training for an Individual With Mixed Corticobasal Degeneration and Progressive Supranuclear Palsy Features: 10-Year Case Report Follow-up

PubMed Central

Boeve, Bradley F.; Petersen, Cheryl M.; Dvorak, Leah; Kantarci, Kejal

2014-01-01

Background and Purpose This case report describes the effects of long-term (10-year) participation in a community exercise program for a client with mixed features of corticobasal degeneration (CBD) and progressive supranuclear palsy (PSP). The effects of exercise participation on both functional status and brain volume are described. Case Description A 60-year-old male dentist initially reported changes in gait and limb coordination. He received a diagnosis of atypical CBD at age 66 years; PSP was added at age 72 years. At age 70 years, the client began a therapist-led community group exercise program for people with Parkinson disease (PD). The program included trunk and lower extremity stretching and strengthening, upright balance and strengthening, and both forward and backward treadmill walking. The client participated twice weekly for 1 hour for 10 years and was reassessed in years 9 to 10. Outcomes Falls (self-reported weekly over the 10-year period of the study by the client and his wife) decreased from 1.9 falls per month in year 1 to 0.3 falls per month in year 10. Balance, walking endurance, and general mobility declined slightly. Gait speed (both comfortable and fast) declined; the client was unable to vary gait speed. Quantitative brain measurements indicated a slow rate of whole brain volume loss and ventricular expansion compared with clients with autopsy-proven CBD or PSP. Discussion This client has participated consistently in a regular group exercise program for 10 years. He has reduced fall frequency, maintained balance and endurance, and retained community ambulation using a walker. Combined with the slow rate of brain volume loss, this evidence supports the efficacy of a regular exercise program to prolong longevity and maintain function in people with CBD or PSP. PMID:24114439

A space-frequency multiplicative regularization for force reconstruction problems

NASA Astrophysics Data System (ADS)

Aucejo, M.; De Smet, O.

2018-05-01

Dynamic forces reconstruction from vibration data is an ill-posed inverse problem. A standard approach to stabilize the reconstruction consists in using some prior information on the quantities to identify. This is generally done by including in the formulation of the inverse problem a regularization term as an additive or a multiplicative constraint. In the present article, a space-frequency multiplicative regularization is developed to identify mechanical forces acting on a structure. The proposed regularization strategy takes advantage of one's prior knowledge of the nature and the location of excitation sources, as well as that of their spectral contents. Furthermore, it has the merit to be free from the preliminary definition of any regularization parameter. The validity of the proposed regularization procedure is assessed numerically and experimentally. It is more particularly pointed out that properly exploiting the space-frequency characteristics of the excitation field to identify can improve the quality of the force reconstruction.

Optimal behaviour can violate the principle of regularity

PubMed Central

Trimmer, Pete C.

2013-01-01

Understanding decisions is a fundamental aim of behavioural ecology, psychology and economics. The regularity axiom of utility theory holds that a preference between options should be maintained when other options are made available. Empirical studies have shown that animals violate regularity but this has not been understood from a theoretical perspective, such decisions have therefore been labelled as irrational. Here, I use models of state-dependent behaviour to demonstrate that choices can violate regularity even when behavioural strategies are optimal. I also show that the range of conditions over which regularity should be violated can be larger when options do not always persist into the future. Consequently, utility theory—based on axioms, including transitivity, regularity and the independence of irrelevant alternatives—is undermined, because even alternatives that are never chosen by an animal (in its current state) can be relevant to a decision. PMID:23740781

l0 regularization based on a prior image incorporated non-local means for limited-angle X-ray CT reconstruction.

PubMed

Zhang, Lingli; Zeng, Li; Guo, Yumeng

2018-01-01

Restricted by the scanning environment in some CT imaging modalities, the acquired projection data are usually incomplete, which may lead to a limited-angle reconstruction problem. Thus, image quality usually suffers from the slope artifacts. The objective of this study is to first investigate the distorted domains of the reconstructed images which encounter the slope artifacts and then present a new iterative reconstruction method to address the limited-angle X-ray CT reconstruction problem. The presented framework of new method exploits the structural similarity between the prior image and the reconstructed image aiming to compensate the distorted edges. Specifically, the new method utilizes l0 regularization and wavelet tight framelets to suppress the slope artifacts and pursue the sparsity. New method includes following 4 steps to (1) address the data fidelity using SART; (2) compensate for the slope artifacts due to the missed projection data using the prior image and modified nonlocal means (PNLM); (3) utilize l0 regularization to suppress the slope artifacts and pursue the sparsity of wavelet coefficients of the transformed image by using iterative hard thresholding (l0W); and (4) apply an inverse wavelet transform to reconstruct image. In summary, this method is referred to as "l0W-PNLM". Numerical implementations showed that the presented l0W-PNLM was superior to suppress the slope artifacts while preserving the edges of some features as compared to the commercial and other popular investigative algorithms. When the image to be reconstructed is inconsistent with the prior image, the new method can avoid or minimize the distorted edges in the reconstructed images. Quantitative assessments also showed that applying the new method obtained the highest image quality comparing to the existing algorithms. This study demonstrated that the presented l0W-PNLM yielded higher image quality due to a number of unique characteristics, which include that (1) it utilizes the structural similarity between the reconstructed image and prior image to modify the distorted edges by slope artifacts; (2) it adopts wavelet tight frames to obtain the first and high derivative in several directions and levels; and (3) it takes advantage of l0 regularization to promote the sparsity of wavelet coefficients, which is effective for the inhibition of the slope artifacts. Therefore, the new method can address the limited-angle CT reconstruction problem effectively and have practical significance.

Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data

NASA Astrophysics Data System (ADS)

Khaninezhad, Mohammad-Reza; Golmohammadi, Azarang; Jafarpour, Behnam

2018-04-01

Subsurface flow model calibration involves many more unknowns than measurements, leading to ill-posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher-order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., k-SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient-based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.

Intertextual Content Analysis: An Approach for Analysing Text-Related Discussions with Regard to Movability in Reading and How Text Content Is Handled

ERIC Educational Resources Information Center

Hallesson, Yvonne; Visén, Pia

2018-01-01

Reading and discussing texts as a means for learning subject content are regular features within educational contexts. This paper presents an approach for intertextual content analysis (ICA) of such text-related discussions revealing what the participants make of the text. Thus, in contrast to many other approaches for analysing conversation that…

Everyone Needs Regular Dental Care, but What if You Can't Get to the Dentist?

ERIC Educational Resources Information Center

Blumin, Scott

2011-01-01

This article features the three-dentist House Call Dentist (HCD) team, a division of the nationally known Blende Dental Group based in San Francisco, headed by Dr. David Blende. Dr. Blende is best known for providing dental care utilizing sleep and sedation modalities, and as a leader in the field of dentistry for patients with special needs. The…